DUJS | 20F Print Journal

DUJS

Dartmouth Undergraduate Journal of Science FA L L 20 20

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VOL. XXII

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N O. 4

CHAOS PIECING TOGETHER SCIENCE IN AN UNCERTAIN WORLD

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Technology and the Developing World

Growing Organs in Vitro: A History of Discovery and a Future of Possibilities

Cancer and Its Treatments

pg. 24

pg. 86

pg. 172 DARTMOUTH UNDERGRADUATE JOURNAL OF SCIENCE

Letter From the Editor in Chief Isaac Newton was a famous proponent of the concept of standing atop the shoulders of giants, saying “If I have seen further, it is by standing on the shoulders of giants.” We, at the Dartmouth Undergraduate of Science, firmly abide by that same principle. As science journalists, we seek to report on contemporary issues and recent experiments that have redefined the scientific landscape and have made marked contribution to their field. Without the scientists who had dedicated their lives to the individual cells, pathways, and tissues as well as those who have spent their academic lives pursuing the space phenomena, psychological patterns, and chemical structures, we would not be able to learn more about our scientific fields of interest and such that we can push the proverbial envelope ourselves.

We at the Dartmouth Undergraduate Journal of Science make an active effort to celebrate the diversity of the scientific field, along with its accomplishments. This term was no different; despite coming at the close of the strangest year of the century (so far), our students were able to continue the development of their curiosity and supplement their (online) classes with extracurricular talks, conferences, and papers which then made up the writing that they submitted for DUJS. As a result, this term we had a diverse array of articles written covering everything from malaria vaccines to the psychology of music to the health impacts of e-cigarette use. Our writers also expored the marriage of social science and hard science, describing the importance of understanding structural racism within the context of the pandemic, the influence of socioeconomic status on the concept of pain and pain treatment, and the transfer and development of technology within the developing world. The idea that scientific experiments done in a lab have real-world implications for our social, economic, geographic, and political world is a theme that we have explored throughout the past year – and is certainly something that we will continue to explore in the coming terms as we hopefully see the resolution and aftermath of the pandemic that we currently face.

This fall was special in another way too, as we welcomed onto campus (and online) many members of the class of 2024. The DUJS Executive Board, comprised of members of the class of 2021, were thrilled to see such young interest in scientific journalism and are now eager to train the next generation of editors that will take over at the end of the winter term. In addition to attending meetings, joining in on group print articles, and writing solo articles, we had many ‘24s present articles during meetings, discuss with members of the executive board topics for group articles that they would like to lead or co-lead in the future, and present ideas of their own about how to grow the scientific journalism community. Of note in particular are Aksheta Kanuganti, Amittai Wekesa, Ashna Kumar, Grace Nguyen, Megan Liu, Miranda Yu, Rujuta Purohit, and Vaani Gupta, all members of the Class of 2024 who decided to write an individual print article on their first term with DUJS! While many members of the older generation of DUJS often fall back on their collegiate STEM classes as a preliminary foundation for their articles, these new students had the daunting task of building their own foundation of collegiate-level understanding largely from scratch. Doing so, especially in a remote environment without the capability to conference in person with editors, is no small feat and is worthy of celebration.

As we usher in the new year with the start of the winter term, DUJS is looking to continue to grow its numbers and introduce new projects that will help members deconstruct and synthesize scientific publications in an efficient and effective manner. We are inclined to continue presenting students with the idea that even as an undergraduate, they possess the tools to appreciate the very cutting edge of science. Thank you to all of our phenomenal writers for the term, our fearless President for carrying the group through a difficult time, our dedicated editors for helping make the papers the best that they can be, and our audience for their continued support.

The Dartmouth Undergraduate Journal of Science aims to increase scientific awareness within the Dartmouth community and beyond by providing an interdisciplinary forum for sharing undergraduate research and enriching scientific knowledge.

EXECUTIVE BOARD President: Sam Neff '21 Editor-in-Chief: Nishi Jain '21 Chief Copy Editors: Anna Brinks '21, Liam Locke '21, Megan Zhou '21 EDITORIAL BOARD Managing Editors: Anahita Kodali '23, Dev Kapadia '23, Dina Rabadi '22, Kristal Wong '22, Maddie Brown '22 Assistant Editors: Aditi Gupta '23, Alex Gavitt '23, Daniel Cho '22, Eric Youth '23, Sophia Koval '21 STAFF WRITERS Aarun Devgan '23

Julia Picker '24

Abigail Fischer '23

Julia Robitaille '23

Advaita Chaudhari '24

Juliette Courtine '24

Aidan Ferrin '24

Katie Walther '24

Akshay Kelshiker '24

Kristal Wong '22

Aksheta Kanuganti '24

Lauren Lee '24

Amanda Jiang '21

Liam Locke '21

Amittai Wekesa '24

Love Tsai '23

Anahita Kodali '23

Maeen Arslan '23

Andrew Goyette '23

Manya Kodali - Hampton HS

Andrew Sasser '23

Mary-Margaret Cummings '24

Anna Brinks '21

Megan Liu '24

Anna Koln '22

Megan Zhou '21

Annaliese OuYang '23

Michael Del Sesto '23

Anupam Sharma '22

Miranda Yu '24

Anushka Bhatia '24

Noa Phillips '23

Arshdeep Danoa '24

Nishi Jain '21

Ashlyn Morris '21

Owen Seiner '24

Ashna Kumar '24

Regan Harnois '23

Audrey Herrald '23

Rujuta Purohit '24

Ayushya Ajmani '24

Sam Hedley '23

Bamlak Messay '23

Sam Neff '21

Benjamin Chen '24

Sophia Arana '22

Bryn Williams '23

Sophia Koval '21

Callie Moody '24

Soyeon (Sophie) Cho '24

Cameron Sabet '24

Sreekar Kasturi '24

Carolina Guerrero '23

Stephanie Finley '23

Dhasiya Anderson '23

Stephanie Lebby '20

Dev Kapadia '23

Vaani Gupta '24

Dina Rabadi '22

Vaishnavi Katragadda '24

Evan Craft '20

Valentina Fernandez '24

George Shan '23

Varun Lingadal '23

Georgia Dawahare '23

Vishi Agrawal - University of

Grace Nguyen '24

Pittsburgh

Hubert Galan-Vargas '23

Whitney Thomas '24

Isaiah Menning '24

Wilson Murane '22

Jennifer Chen '23

Sincerely, Nishi Jain DUJS Hinman Box 6225 Dartmouth College Hanover, NH 03755 (603) 646-8714 http://dujs.dartmouth.edu dujs.dartmouth.science@gmail.com Copyright © 2020 The Trustees of Dartmouth College

SPECIAL THANKS Dean of Faculty Associate Dean of Sciences Thayer School of Engineering Office of the Provost Office of the President Undergraduate Admissions R.C. Brayshaw & Company

Table of Contents Individual Articles Understanding Practices for Cancer Prevention Aarun Devgan '23, Pg. 6

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The Journey to a Potential Vaccine Against Plasmodium vivax (P. vivax) Malaria Aksheta Kanuganti '24, Pg. 10

Technology and the Developing World Amittai Wekesa '24, Pg. 16

Current State of Fluorescence Microscopy for Biological Research Applications Anahita Kodali '23, Pg. 24

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Double-Edged Sword: The Potential of MMP Inhibitors in Treating Disease Andrew Sasser '23, Pg. 32

Impact of COVID-19 on Immunosuppressed Solid Organ Transplant Recipients Anupam Sharma '22, Pg. 40

Behavioral and Neural Evidence for Number Sense in Nonhuman Mammals Ashlyn Morris '21, Pg. 46

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Anaplastic Lymphoma Kinase-Positive Non-Small Cell Lung Cancer and its Targeted Therapies Ashna Kumar '24, Pg. 54

On the Structure of Field Theories III Evan Craft '20 , Pg. 62

The Impact of Mozart’s Music on Epileptic Patients Georgia Dawahare '23, Pg. 68

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Changing Times Reflect the Need for Diversity in Clinical Trials Grace Nguyen '24, Pg. 74

Structural Racism: A Crisis Amidst the Pandemic Hubert Galan-Vargas '23, Pg. 82

Growing Organs in Vitro: A History of Discovery and a Future of Possibilities Jennifer Chen '23, Pg. 86

Socioeconomic Influence on Chronic Pain: Psychological and Neurological

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Maeen Arslan '23, Pg. 94

The Health Impacts of Electronic Cigarette Use Manya Kodali, Hampton High School, Pg. 100

DARTMOUTH UNDERGRADUATE JOURNAL OF SCIENCE

Table of Contents Individual Articles Neuroscience and Artificial Intelligence Megan Liu '24, Pg.106

A Scientific Review of the Impacts of Music on the Human Body Miranda Yu '24, Pg.112

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The Universe’s Return to a Singularity: The Big Rip Rujuta Purohit '24, Pg.118

Markov Chain Monte Carlo Utility in Systems Biology Stephanie Finley '23, Pg. 128 The Effect of Vegetation on Mosquito Abundance and Spread of Mosquito-Borne Illnesses Vaani Gupta '24, Pg. 138

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Effect of Gut Microbiome Composition on Mental Health and Neurodegenerative Diseases Varun Lingadal '23, Pg. 148

Team Articles Research on COVID-19 and COVID-19 Impacts on Research

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Pg. 156

Cancer and its Treatments Pg. 172

Onward to Mars: The Past, Present, and Future of Human Space Travel Pg. 188

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Thinking Small: Applications of Nanotechnology Pg. 214

Alzheimer’s Disease: Molecular Mechanisms, Clinical Manifestations, and Treatments Pg. 228

FALL 2020

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Understanding Practices for Cancer Prevention

BY AARUN DEVGAN ’23 Cover image: Illustration depicting a man casually smoking a cigar, apparently unbothered by the carcinogenic characteristics of tobacco.

Source: Wikimedia Commons “The top two causes – tobacco and diet – account for almost two thirds of all cancer deaths and are among the most correctable” (Trichopoulos et al., 1996).

Introduction Over the past 25 years, The US has achieved significant reductions in the cancer death rate. It has fallen 27% from its peak in 1991 of 215 deaths per 100,000 people, resulting in an average annual decrease of 1.5%. This decrease is largely due to a steady reduction in the number of people who smoke and advancements in early detection methods and treatments (American Cancer Society, 2020). Older demographics tend to have the highest risks for developing cancer; 80% of all diagnoses in the United States are in patients who are at least 55 years of age or older (American Cancer Society, 2020). In addition to age, certain lifestyle choices such as smoking, obesity, and drinking alcohol can make one much more likely to get cancer.

However, the risk of developing cancer can be minimized by making conscious decisions to live a healthy life. In fact, according to research

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done by the American Cancer Society, 42% of newly diagnosed cancer cases were potentially avoidable. Also, more than 5 million skin cancer cases that are diagnosed annually could be prevented by protecting skin from excessive sun exposure and not using indoor tanning devices (American Cancer Society, 2020).

Don’t Use Tobacco Tobacco is the most lethal carcinogen in the US. Smoking causes 30 percent of cancer deaths as it directly increases the likelihood of developing cancer of the lungs, upper respiratory tract, esophagus, bladder, pancreas, stomach, liver, and kidney. In addition to smoking, other forms of tobacco, such as chewing tobacco, are linked to oral cancer. The potential for tobacco to do permanent damage to one’s body increases with frequency and duration of use. Taking up the habit of using tobacco products at a young age significantly amplifies one’s risks because people who start smoking as teenagers are DARTMOUTH UNDERGRADUATE JOURNAL OF SCIENCE

Figure 1: This figure depicts the two common methods of the intermittent fasting diet. The image on the left depicts the method that involves only eating during a specified time interval every day. For example, only eating between 12pm and 6pm.

The image on the right depicts the other method of intermittent fasting: picking 2 or 3 days each week to eat nothing and eating normally on all the other days.

Source: Wikimedia Commons

more susceptible to addiction and they will use tobacco products for a longer period of time on average (Trichopoulos et al., 1996).

While it is the best option is to never smoke in the first place, there are still significant health benefits to quitting smoking. Researchers have found that there is a direct correlation between the time since a person quit smoking and the benefits they reap from doing so.

Specifically, within five to ten years of quitting, the chances of getting cancer of the mouth, throat, and voice box drop by half. After ten years of quitting, chances of getting cancer of the bladder, esophagus, or kidney drops significantly. Between ten and fifteen years of quitting, the risk of lung cancer drops by half. Finally, 20 years after one quits smoking, the chances of getting cancer of the mouth, throat, larynx (voice box), and pancreas drops to levels close to that of someone who has never smoked (Center for Disease Control and Prevention, 2020).

Eat a Healthy Diet Although it is easier said than done, eating a healthy diet is essential to living a long life and reducing one’s risk of cancer. A healthy diet entails basing one’s diet around plant sources such as fruits, vegetables, beans, and whole grains. In addition, one should avoid processed meats as the cancer agency of the World Health Organization concluded that eating large amounts of processed meat can slightly increase the risk of certain types of cancer FALL 2020

(Mayo Foundation for Medical Education and Research, 2018). Additionally, it is important to maintain a healthy body weight – this is dependent not only on the types of foods eaten but also the quantity of those foods consumed. One should only eat the number of calories needed to maintain healthy body weight. It is much easier to limit one’s calories when eating fruits and vegetables which are nutrient-rich and low in calories. On the other hand, fast food is dangerous because it is very calorie-dense but lacks nutrients and leaves one wanting more. This is the reason why it is important to consciously choose foods that have a low-calorie-density. For instance, vegetable may only have 30 calories per 100 grams while chocolate has 550 calories per 100 grams. A research study highlights the dangers of calorie dense foods: “Participants ate 56% more calories when provided a high-energydensity meal, compared with a low-energydensity one” (Mawer, 2019).

“Researchers have found that there is a direct correlation between the time since a person quit smoking and the benefits they reap from doing so."

Obesity in the United States has increased from 30.5% to 42.4% of the population over the last 20 years (Center for Disease Control and Prevention, 2020). In addition to cancer, obesity is directly correlated with many other life-threatening conditions such as heart disease, stroke, and type 2 diabetes.

The obesity epidemic in the United States requires a practical strategy to combat it, such as intermittent fasting. Intermittent fasting is currently one of the most recognized diets and a variation of it includes eating only 20% of one’s energy requirement on fast days and eating normally on other days (Ganesan et 7

Figure 2: While sunrays can be truly beautiful, the UV rays emitted from the hits the DNA in the skin cells and can break at connection points. This changes the message of the DNA to reproduce over and over, leading to a tumor.

Image Source: Pixabay

"a meta-analysis review shows that physical activity is directly related to lower chances of getting colon cancer.

In fact, physically active people had half the risk as those who live a sedentary lifestyle"

al., 2018). In general, dieters will usually have one to three fast days a week. There are many different forms of intermittent fasting that can be tailored to each individual’s needs. Another common form of dieting is restricting ones eating to a certain time interval, such as only eating from noon to 6 p.m. each day. The success and effectiveness of intermittent fasting are supported in a meta-analysis study conducted

by Ganesan et al. (2018), which concluded that intermittent fasting has been proven to be effective for losing weight in the short term.

A separate study conducted by Mattson et al.

(2017) focuses on the long-term possibilities of intermittent fasting. The study shows that the dropout rate of the diet was between 0 and 40% and that 65 to 75% of fasting days were adhered to. These retention percentages are widely

Figure 3: Regular doctor visits and checkups are an essential part to cancer prevention. Early detection of cancer directly leads to a higher success rate of cancer survival.

Image Source: Pixabay

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considered to be a sustainable diet according to dietitians. The idea that intermittent fasting results in increased hunger and therefore overindulgence on non-fasting days has also been refuted. In fact, Mattson’s study claims that intermittent fasting does not lead to overeating on non-fasting days.

Part of a healthy diet also includes only drinking alcohol in moderation, if one chooses to do so at all. “An estimated 6% of cancer cases can be attributed to alcohol consumption” (American Cancer Society). Cancers of the mouth, pharynx, larynx, esophagus, liver, colorectum, female breast, and stomach are all more prevalent in those who consume alcohol. The risk increases with the volume of alcohol consumed and even a few drinks per week may increase the risk of these cancers.

Exercise Regularly Adult obesity is a major contributor to cancer of the endometrium (the lining of the uterus), breast, colon, kidney, and gallbladder (Trichopoulos et al., 1996). While exercise does help people burn calories and therefore lose fat, exercise also helps to prevent certain types of cancer in and of itself. For instance, a metaanalysis review shows that physical activity is directly related to lower chances of getting colon cancer. In fact, physically active people had half the risk as those who live a sedentary lifestyle (Batty & Thune, 2000). In addition to the weight loss benefits, exercise favorably effects insulin, prostaglandin, and bile acid levels with influence the growth of cells in the colon (Batty & Thune, 2000). Exercise is also known to help speed up bowel movements which results in less contact between fecal carcinogens and the lining of the colon (Batty & Thune, 2000).

DARTMOUTH UNDERGRADUATE JOURNAL OF SCIENCE

According to the American Cancer Society (2020), an estimated 3% of cancer cases can be attributed to physical inactivity. In addition to colon cancer, physical activity decreases the risk of breast, endometrial, kidney, bladder, esophageal, and stomach cancer. (American Cancer Society, 2020).

Protect Yourself from the Sun Skin cancer is both one of the most common and one of the most preventable types of cancer. The sun’s high-frequency ultraviolet B rays can damage DNA. These B rays alone lead to 90% of all skin cancers including the more deadly melanomas (Trichopoulos et al., 1996). While it is true that people with fairer skin are more prone to skin cancer, there are some strategies that all people should follow to prevent skin cancer. If possible, one should avoid mid-day sun (between 10 am and 4 pm), stay in the shade, cover exposed skin, use sunscreen generously, and avoid tanning beds and sunlamps (Mayo Foundation for Medical Education and Research, 2018).

Get Vaccinated, Avoid Risky Behavior, and Get Regular Medical Care Certain viral infections result in an increased likelihood of developing a number of cancers.

For instance, Hepatitis B infection can increase one’s risk of developing liver cancer (Mayo Foundation for Medical Education and Research, 2018). Similarly, Human papillomavirus (HPV) is a sexually transmitted virus that can lead to cervical and genital cancers as well as squamous cell cancer of the head and neck (Mayo Foundation for Medical Education and Research, 2018). To stay clear of these viruses and resulting cancers, it is always a good idea to practice safe sex and avoid other risky behaviors such as sharing needles.

Detecting cancer early is one of the single most effective ways of treating that cancer. Therefore, self-exams should be conducted regularly, and doctors should tell their patients how often they should be professionally screened, depending on their age, health history, and family history.

Some common self-exams include belly fat check, heart rate check, blood pressure check, testicular cancer check, oral heath check, skin cancer check, and breast cancer check (“8 SelfExams,” n.d.).

FALL 2020

Conclusion Although society has made progress in reducing the cancer death rate, a significant portion of cancer deaths can still be attributed to poor lifestyle decisions. Notably, tobacco use and obesity as a result of poor diet and sedentary lifestyle are the two major causes of cancer deaths today. Furthermore, one should take the necessary steps to protect oneself from harmful sun rays and to receive regular medical care. The methods outlined in this paper, if promoted by health care professionals and adopted by the public, will significantly increase the longevity of the population.

References 8 Self-Exams. Bellin Health Systems. https://www.bellin.org/ services_programs/mens-health/screenings.

Batty, D., & Thune, I. (2000, December 9). Does physical activity prevent cancer? The BMJ. https://www.bmj.com/ content/321/7274/1424.short?casa_token=IZGMlDHinfUAAA AA%3AasU7ktCo9C8I1T3-EtKW-FMWsF9VgkV8o1d7RQrqcgnxBU6lmvg-lbY1yvTLvE7QXJPfz_EiVFw. Cancer Facts & Figures 2020. American Cancer Society. (2020). https://www.cancer.org/research/cancer-facts-statistics/allcancer-facts-figures/cancer-facts-figures-2020.html.

Centers for Disease Control and Prevention. (2020, July 29).

Cancer Screening Tests. Centers for Disease Control and Prevention. https://www.cdc.gov/cancer/dcpc/prevention/ screening.htm.

Centers for Disease Control and Prevention. (2020, June 29). Adult Obesity Facts. Centers for Disease Control and Prevention. https://www.cdc.gov/obesity/data/adult.html.

Centers for Disease Control and Prevention. (2020, March 23). Smoking and Cancer. Centers for Disease Control and Prevention. https://www.cdc.gov/tobacco/campaign/tips/ diseases/cancer.html.

Ganesan, K., Habboush, Y., & Sultan, S. (2018). Intermittent Fasting: The Choice for a Healthier Lifestyle. Cureus. https:// doi.org/10.7759/cureus.2947 Mattson, M. P., Longo, V. D., & Harvie, M. (2017). Impact of intermittent fasting on health and disease processes. Ageing Research Reviews, 39, 46-58. doi:10.1016/j.arr.2016.10.005 Mawer, R. (2019, June 26). Calorie Density - How to Lose Weight Eating More Food. Healthline. https://www.healthline. com/nutrition/calorie-density.

Mayo Foundation for Medical Education and Research.

(2018, November 28). 7 healthy habits that can reduce your risk of cancer. Mayo Clinic. https://www.mayoclinic.org/ healthy-lifestyle/adult-health/in-depth/cancer-prevention/ art-20044816.

Trichopoulos, D., Li, F., & Hunter, D. (1996). What Causes Cancer? Scientific American, 275(3), 80-87. Retrieved October 22, 2020, from http://www.jstor.org/stable/24993351

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The Journey to a Potential Vaccine Against Plasmodium vivax (P. vivax) Malaria

BY AKSHETA KANUGANTI ’24 Cover image: This is a female Anopheles mosquito, a vector of Plasmodium vivax malaria.

Source: Wikimedia Commons

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Plasmodium vivax (P. vivax) Malaria Prevalence The parasite P. vivax is predominant in some of the world’s most densely populated areas, such as Asia, and Central and South America, exposing approximately 2.2 billion people to the risk of malaria infection. It causes over 14 million cases each year (Plasmodium., 2015). In the past, P. vivax malaria has been underprioritized as public health officials focused on Plasmodium falciparum (P. falciparum) malaria due to its higher mortality rate (Ntumngia et al., 2012). However, just in the past decade, researchers shifted their attention towards P. vivax as a result of a consistent rise in P. vivax cases and its deadly effects. P. vivax is known to incapacitate individuals and to cause seizures, severe anemia, and respiratory distress. An acute P. vivax infection can result in maternal morbidity and stillbirth (Kochar et al., 2009). The emerging, drug-resistant forms

of the parasite can reactivate dormant forms of itself, so even those who have been infected before are still at risk. This virulent form of P. vivax can no longer be cured with medication, emphasizing the necessity of a coherent vaccine program against this disease.

COVID’s Impact on P. vivax Since the beginning of the P. vivax vaccine development program in the United States and Thailand, enormous progress has been made in reducing the burden of P. vivax in Africa, Asia, and Central and South America. Effective tools, such as insecticide-treated nets and spraying structures with long-lasting insecticides, coupled with stronger healthcare systems have significantly reduced the prevalence of P. vivax.

Yet without a long-lasting vaccine, P. vivax transmission remains high and therefore is likely to resurge rapidly if the aforementioned prevention mechanisms are hindered. The DARTMOUTH UNDERGRADUATE JOURNAL OF SCIENCE

Figure 1: P. vivax Malaria Life Cycle- Sporozoites are released from the mosquito, infect human liver cells, and turn into merozoites. The merozoites rupture the liver cells and move into the blood stream to rupture red blood cells. While most merozoites continue to rupture red blood cells, others become gametes, and are taken up by a female mosquito during a blood meal. In the mosquito, the gametes are fertilized and rupture the mosquito’s midgut cells to become sporozoites, ready to infect another human host.

Source: Wikimedia Commons

presence of COVID-19 in Africa threatens P. vivax control in various ways. Firstly, the weak healthcare system in Africa runs the risk of being overwhelmed with COVID-19 cases, resulting in limited capacity for severe malaria cases. Secondly, delivery of effective tools against malaria, such as mosquito nets and mosquito repellants, is heavily dependent on field and logistics personnel, healthy system administrators, front-line healthcare workers, and campaigns in Africa that advertise the use of the tools. Campaigns, such as Zero Malaria, rely on travelling to villages to relay lessons to the villagers about how to prevent the spread of malaria in their village while providing them with the necessary tools to do so. The restrictions on travel and widespread absenteeism of workers due to COVID-19 restrains the amount of malaria preventative equipment that can be sent to Africa. Finally, severe cases of P. vivax require families to seek foreign treatment; however, the fear of coronavirus infection deters many from taking this step, and lives are lost as a result. The absence of the mass campaigns and restricted delivery of the preventative tools to African countries is projected to cause 46.4 million cases and 1167 deaths by the end of 2020 (Weiss et al., 2020). Now, more than ever, a P. vivax vaccine is essential.

P. vivax Proliferation and Life Cycle As a parasite, P. vivax has two separate life cycles: one in the human and one in the female Anopheles mosquito. During a blood meal, FALL 2020

an infected mosquito releases sporozoites, a cellular form of P. vivax with the capacity to infect a new host’s liver cells. In the liver stage, the parasite may remain dormant for a couple weeks or even years, during which time there are no clinical symptoms present.

Sporozoites use the nutrients in the liver cells to become larger (larger sporozoites are called merozoites). Eventually, the infected liver cells burst and release the merozoites into the blood stream. The merozoites infect the host’s red blood cells and then rapidly reproduce asexually. Ultimately, the reproduction of the merozoites will destroy the cell, releasing more merozoites that move on to rupture more red blood cells. While some merozoites continue infecting the blood, others become female and male gametes, ready to infect and undergo sexual reproduction in the next mosquito that sucks them up in a blood meal. In the mosquito, the gametes become ookinets, fertilized female gametes. Then, the ookinets penetrate the midgut wall of the mosquito where they rupture and release sporozoites which travel to the salivary glands of the mosquito (Refer to Figure 1). With each blood meal the mosquito takes, the P. vivax malaria life cycle is perpetuated. Unfortunately, the mosquito does not suffer from the parasite like the human host (Prevention, 2020).

"The absence of the mass campaigns and restricted delivery of the preventative tools to African countries is projected to cause 46.4 million cases and 1167 deaths by the end of 2020."

Current Treatments for P. vivax Currently, the best preventative and treatment measure against P. vivax is chloroquine (Aralen, 11

Figure 2: DBPII binding to the Duffy antigen on host red blood cells through a domain known as region II which plays a major role in establishing P. vivax invasion and infection of red blood cells.

Source: Image Created by Author

2020). Chloroquine works by taking advantage of the fact that merozoites need a slightly acidic environment in the red blood cells to rupture them. As a base, chloroquine neutralizes the acidity of red blood cells, which saves the hemoglobin, but makes an uninhabitable environment for merozoites, and therefore ends the invasion of merozoites into more red blood cells (Slater, 1993). While this treatment was a highly effective anti-malaria medicine at one time, P. falciparum has become resistant to it and P. vivax is losing its sensitivity to chloroquine as well. Although P. vivax remains vulnerable to chloroquine in the Indian subcontinent, strains in New Guinea, Oceania, and parts of Indonesia, South-East Asia, and South America have developed high-level resistance to chloroquine (NCBI, 2015). Not only does chloroquine have low efficacy against certain strains of P. vivax, but it also presents many side effects. People taking chloroquine often experience skin rashes, muscle weakness, vomiting, and ringing in the ears. Furthermore, chloroquine can also cause visual impairment in the form of retinal damage (Primaquine, 2020). The ineffectiveness of this malaria treatment and the side effects of chloroquine further highlight the need for P. vivax vaccine development

Vaccine Strategies against P. vivax "vaccines can safely stimulate the immune response by introducing a noninfectious form of the virus, with its associated viral antigens, to the body."

One component of the mammalian immune response is the B lymphocyte, a type of white blood cell, which synthesize a specific antibody that can bind to a specific antigen on the surface of an invading organism. In the absence of a foreign invader, the concentration of B lymphocytes in the blood is very low (Allot & Mindorff , 2020). However, vaccines can safely stimulate the immune response by introducing a noninfectious form of the virus, with its associated viral antigens, to the body. The advantage of this approach is that, once the immune system has encountered an antigen, it creates memory cells that remember the antigen and the antibodies used against it. These memory cells remain in the blood stream for a long time and allow the body to quickly respond to the pathogen in the future.

If encountered again, the symptoms associated with the disease will be minimal.

There are three different vaccine strategies against parasitic diseases: pre-erythrocytic, transmission blocking, and blood stage. The pre-erythrocytic strategy for P. vivax requires the development of an antigen that prevents the sporozoites from rupturing liver cells. However, liver cells reproduce fairly quickly, so even if the

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sporozoites are continuously rupturing them, they are able to come back fairly quickly. If there is no sickness involved with the liver stage of the disease, it would be less helpful to create a vaccine using the pre-erythrocytic strategy.

Transmission blocking prevents the infection of mosquitos by targeting gametocytes. Although transmission blocking can impede the spread of the disease eventually, it does not prevent the spread of P. vivax from mosquitos that are already infected. When the infection reaches the red blood cells, the clinical symptoms manifest and the disease becomes deadly.

Therefore, protecting the invasion of red blood cells from merozoites is the best target for vaccine development (Beeson et al., 2019).

To protect the red blood cells from a P. vivax invasion, the Duffy Binding Protein II (DBPII) was identified and tested in previous studies.

The DBPII antigen is a surface protein on P. vivax which binds to a Duffy Antigen Receptor for Chemokines (DARC) present on human red blood cells (Red) (Refer to Figure 2). Previous studies indicate that Africans who did not have the DARC receptor on their red blood cells were not susceptible to P. vivax infection (Ntumngia et al., 2014). The DARC receptors cannot be removed, but we can prevent the parasite from binding to the receptor. This can be done by introducing the DBPII antigen to the immune system, which will lead the body to create memory cells that produce antibodies to protect the DARC receptors from a potential future infection by the P. vivax parasite. If binding of the DBPII antigen to the DARC receptor is intercepted by a naturally produced antibody, the P. vivax infection can be neutralized (Ntumngia et al., 2014). Hence, it became crucial to develop the DBPII antigen as a potential vaccine candidate. However, the question for how to test the DBPII antigen remains unanswered.

Although P. vivax has been around for as long

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Figure 3: Visual for the COS 7 Cell Assay: If erythrocytes bind to the DBPII antigen, it shows that the DBPII can mimic the P.vivax.

Source: Image Created by Author

as P. falciparum, P. vivax’s vaccine program has been hampered not only due to the relatively low mortality rate of P. vivax infection, but also because scientists have been unable to culture P. vivax in vitro. P. vivax only infects erythrocytes (immature red blood cells), which mature within 24 hours and are therefore unable to support the growth of a P. vivax culture (Ntumngia et al., 2018). For this reason, samples have to be taken freshly from infected patients or primates, but this is costly and results in a short-lived culture (Grimberg et al., 2007). Given the limitations of both in vitro culture and blood samples collected from patients, researchers have started looking at biological assays that would mimic P. vivax. For the imitation, a staple fibroblast cell line from an African green monkey, called COS 7 cells, has been used (COS-7, 2020). Scientists can induce the COS-7 cells to express DBPII as a surface protein, similar to how it appears on P. vivax.

In a perfect case scenario, erythrocytes would bind to the surface proteins on the COS 7 cells (Refer to Figure 3). The binding would show that the DBPII antigen can emulate P. vivax, implicating that DBPII should be able to compel the immune system to produce antibodies against the disease (Ntumngia et al., 2012).

With this cellular model of P. Vivax infection in hand, scientists have been enabled to develop a DBPII antigen vaccine for P. Vivax infection

Duffy Binding Protein II (DBPII) Antigen Production While the theory behind the development of the P. vivax vaccine appears straightforward, the execution has proved to be challenging. The first challenge for researchers was producing large amounts of DBPII antigen so it could be tested in a COS 7 cell assay and eventually be introduced to the mammalian immune system as a vaccine. In laboratories, the DNA of the DBPII antigen is commercially bought

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and transfected into E. coli cells (Rosano et al., 2014). The E. coli cell acts as a breeding ground, producing large amounts of DBPII antigen, which can then be purified from the organelles of the E. coli (“Protein Purification”, 2020). After purification, the antigen must be expressed in a COS 7 cell assay to test its efficacy, and subsequently developed into an effective vaccine. However, DBPII is an insoluble protein, which requires an additional step in the protein purification process and makes the process much more difficult. Insoluble proteins clump together in an E. coli cell, and the clumps must be broken apart during the protein purification process. The buffers utilized during this process lead to a great deal of misfolded, broken, and lost protein, which cannot be utilized for the vaccine (Palmer, 2004). However, while working to optimize the production of DBPII, scientists found that the denatured protein can actually be refolded after purification from the E. coli cells. With this method to fix destroyed proteins at hand, the main goal became tweaking the generic protein production process to induce the largest amount of DBPII possible every time researchers attempted to produce it.

To optimize the production of DBPII, alterations to the final step in the protein purification process were made. The final step in the purification process is affinity (binding) purification in a Nickel-Sepharose column (Protein, 2020). The Nickel-Sepharose column is a commercially-bought syringe coated with nickel. When the impure DBPII antigen is poured into the column, the nickel binds to the DBPII antigen and lets any excess parts of the E. coli cells run through the column. Finally, an elution buffer is poured in to elute out pure DBPII. An elution buffer simply breaks the binding of the DBPII antigen and Nickel, allowing for the pure DBPII antigen to flow out of the column and be collected. The incubation times after the elution buffer is poured in are important because, if the buffer is kept with the antigen

"Given the limitations of both in vitro culture and blood samples collected from patients, researchers have started looking at biological assays that would mimic P. vivax."

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for too long, the antigen can “dry up” and be of no use. However, if the elution buffer is not kept long enough, it does not have enough time to break the affinity of the nickel and antigen. If the binding between the nickel and antigen is not broken, most of the antigen will stay inside the column, and all of the elution buffer would just be collected from the column, and the antigen would be thrown out with the column. Once the perfect incubation time is found for the elution buffer to break the binding of DBPII and nickel, the maximum amount of DBPII antigen can be collected.

Current Research in the P. vivax Vaccine Development Program "A potential vaccine candidate – the DBPII antigen vaccine – has been identified and its production has been optimized.

Now, researchers are testing the reliability of the antigen in COS 7 cell assays and will challenge mice to produce antibodies against DBPII."

After an adequate amount of pure DBPII antigen is produced, it is expressed in COS 7 cells and exposed to erythrocytes for binding. If the DBPII antigen folds and is expressed properly for binding, researchers should see rosettes, which implies that the DBPII antigen is ready for trials in mice (Ntumngia, 2018). Once the mice have been injected with the antigen, the production of antibodies in B-cells commences.

The spleenocytes of the mice, containing B-cells, are collected and tested for the presence of antibodies using a sandwich Enzyme-Linked Immunosorbent Assay (ELISA). A sandwich ELISA serves to demonstrate the binding of an antigen to an antibody (Jones, n.d.).

First, the ELISA plate is coated with the antibody found in the mice sera. To detect the antibody, Macrophage Stimulating Protein 1 (MSP1) is added, followed by a substrate that changes colors if there is any binding between MSP1 and the antibody of interest (Jones). Although the ELISA may change colors as predicted, there is still no guarantee that the MSP1 bound to an antibody of interest. There is always a chance that MSP1 binds to a different antibody present in the mouse sera. Even though this test is not totally foolproof, it is important to run an ELISA because if there is no color change, then it definitively confirms the lack of an antibody.

If there is no antibody, then researchers do not have to waste resources and money with further steps. However, if the ELISA shows the presence of an antibody, there must be another test done to demonstrate the presence of the antibody to DBPII specifically. B-cells have to be sorted for DBPII-specific B-cells and sequenced. The B-cells are sorted because mice are exposed to many different infections and therefore, produce many different antibodies (Sklar et al.,

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2007). To sequence the antibody, scientists run polymerase chain reactions (PCR), which makes many copies of the antibody DNA so it can be easily sequenced (“Polymerase Chain Reaction,” 2020). If the sequence is complementary to the known DNA sequence of DBPII, then the correct antibody is present.

Conclusion In the past, P. vivax received very little attention; but just in the last decade, the constant dedication of researchers has pushed the vaccine development program to unexpected heights. With P. vivax becoming less sensitive to current malaria treatments and COVID-19 threatening a spike in P. vivax cases, the urgency of a P. vivax vaccine has increased. A potential vaccine candidate – the DBPII antigen vaccine – has been identified and its production has been optimized. Now, researchers are testing the reliability of the antigen in COS 7 cell assays and will challenge mice to produce antibodies against DBPII. These developments show that there is reason to be optimistic that a successful DBPII antigen-based vaccine against P. vivax may be developed in the near future.

Acknowledgments I would like to thank Dr. John Adam’s parasitology lab at the University of South Florida for allowing me to assist with optimizing the production of DBPII. References Allot, A. & Mindorff, D. (2014). Oxford IB Diploma Program: Biology-HL. Retrieved October 21, 2020, from http://www. marvin.ch/Biology-HL.html Anopheles sinensis. (n.d.). Military Health System. Retrieved November 3, 2020, from http://health.mil/News/Gallery/ Photos/2018/11/28/Anopheles-sinensis Aralen (chloroquine): Possible Treatment for COVID-19. (n.d.).

Retrieved October 21, 2020, from https://www.medicinenet. com/chloroquine-oral/article.htm Batchelor, J. D., Malpede, B. M., Omattage, N. S., DeKoster, G. T., Henzler-Wildman, K. A., & Tolia, N. H. (2014). Red Blood Cell Invasion by Plasmodium vivax: Structural Basis for DBP Engagement of DARC. PLOS Pathogens, 10(1), e1003869. https://doi.org/10.1371/journal.ppat.1003869 Beeson, J. G., Kurtovic, L., Dobaño, C., Opi, D. H., Chan, J.-A., Feng, G., Good, M. F., Reiling, L., & Boyle, M. J. (2019).

Challenges and strategies for developing efficacious and long-lasting malaria vaccines. Science Translational Medicine, 11(474). https://doi.org/10.1126/scitranslmed.aau1458

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COS-7 ATCC ® CRL-1651TM Cercopithecus aethiops kidney. (n.d.). Retrieved November 21, 2020, from https://www.atcc. org/Products/All/CRL-1651 Grimberg, B. T., Udomsangpetch, R., Xainli, J., McHenry, A., Panichakul, T., Sattabongkot, J., Cui, L., Bockarie, M., Chitnis, C., Adams, J., Zimmerman, P. A., & King, C. L. (2007). Plasmodium vivax Invasion of Human Erythrocytes Inhibited by Antibodies Directed against the Duffy Binding Protein. PLoS Medicine, 4(12). https://doi.org/10.1371/journal.pmed.0040337 He, F. (2011). BCA (Bicinchoninic Acid) Protein Assay. BioProtocol, e44–e44.

Information, N. C. for B., Pike, U. S. N. L. of M. 8600 R., MD, B., & Usa, 20894. (2015). TREATMENT OF UNCOMPLICATED MALARIA CAUSED BY P. VIVAX, P. OVALE, P. MALARIAE OR P. KNOWLESI. In Guidelines for the Treatment of Malaria. 3rd edition. World Health Organization. https://www.ncbi.nlm. nih.gov/books/NBK294428/ Jones, L. (n.d.). Enzyme-Linked ImmunoSorbant Assay (ELISA).

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Kochar, D. K., Das, A., Kochar, S. K., Saxena, V., Sirohi, P., Garg, S., Kochar, A., Khatri, M. P., & Gupta, V. (2009). Severe Plasmodium vivax malaria: A report on serial cases from Bikaner in northwestern India. The American Journal of Tropical Medicine and Hygiene, 80(2), 194–198.

Ntumngia, F. B., Barnes, S. J., McHenry, A. M., George, M. T., Schloegel, J., & Adams, J. H. (2014). Immunogenicity of a Synthetic Vaccine Based on Plasmodium vivax Duffy Binding Protein Region II. Clinical and Vaccine Immunology : CVI, 21(9), 1215–1223. https://doi.org/10.1128/CVI.00205-14 Ntumngia, F. B., King, C. L., & Adams, J. H. (2012). Finding the sweet spots of inhibition: Understanding the targets of a functional antibody against Plasmodium vivax Duffy binding protein. International Journal Elesvier.

Protein Purification from E. coli and Mammalian Cells. (n.d.).

Retrieved November 3, 2020, from https://www.promega. com/resources/technologies/halotag-technology/proteinpurification-from-e-coli-and-mammalian-cells/ Rosano, G. L., & Ceccarelli, E. A. (2014). Recombinant protein expression in Escherichia coli: Advances and challenges.

Frontiers in Microbiology, 5, 172. https://doi.org/10.3389/ fmicb.2014.00172 Sklar, L. A., Carter, M. B., & Edwards, B. S. (2007). Flow Cytometry for Drug Discovery, Receptor Pharmacology and High Throughput Screening. Current Opinion in Pharmacology, 7(5), 527–534. https://doi.org/10.1016/j. coph.2007.06.006 Slater, A. F. (1993). Chloroquine: Mechanism of drug action and resistance in Plasmodium falciparum.

Pharmacology & Therapeutics, 57(2–3), 203–235. https://doi. org/10.1016/0163-7258(93)90056-j Tripathy, S., Dassarma, B., Roy, S., Chabalala, H., & Matsabisa, M. G. (2020). A review on possible modes of action of chloroquine/hydroxychloroquine: Repurposing against SAR-CoV-2 (COVID-19) pandemic. International Journal of Antimicrobial Agents, 56(2), 106028. https://doi. org/10.1016/j.ijantimicag.2020.106028 Weiss, D. J., Bertozzi-Villa, A., Rumisha, S. F., Amratia, P., Arambepola, R., Battle, K. E., Cameron, E., Chestnutt, E., Gibson, H. S., Harris, J., Keddie, S., Millar, J. J., Rozier, J., Symons, T. L., Vargas-Ruiz, C., Hay, S. I., Smith, D. L., Alonso, P. L., Noor, A. M., … Gething, P. W. (2020). Indirect effects of the COVID-19 pandemic on malaria intervention coverage, morbidity, and mortality in Africa: A geospatial modelling analysis. The Lancet Infectious Diseases, 0(0). https://doi.org/10.1016/ S1473-3099(20)30700-3

Ntumngia, F. B., Thomson-Luque, R., Galusic, S., Frato, G., Frischmann, S., Peabody, D. S., Chackerian, B., Ferreira, M. U., King, C. L., & Adams, J. H. (2018). Identification and Immunological Characterization of the Ligand Domain of Plasmodium vivax Reticulocyte Binding Protein 1a. The Journal of Infectious Diseases, 218(7), 1110–1118. https://doi. org/10.1093/infdis/jiy273 Palmer, I., & Wingfield, P. T. (2004). Preparation and Extraction of Insoluble (Inclusion-Body) Proteins from Escherichia coli. Current Protocols in Protein Science / Editorial Board, John E. Coligan ... [et Al.], CHAPTER, Unit-6.3. https://doi. org/10.1002/0471140864.ps0603s38 Plasmodium vivax and drug resistance. (2015, June 3).

Worldwide Antimalarial Resistance Network. https://www. wwarn.org/about-us/malaria-drug-resistance/plasmodiumvivax-and-drug-resistance Polymerase Chain Reaction (PCR) Fact Sheet. (n.d.). Genome.

Gov. Retrieved November 3, 2020, from https://www. genome.gov/about-genomics/fact-sheets/PolymeraseChain-Reaction-Fact-Sheet Prevention, C.-C. for D. C. and. (2020, July 16). CDC - Malaria— About Malaria—Biology. https://www.cdc.gov/malaria/ about/biology/index.html Primaquine | drug | Britannica. (n.d.). Retrieved November 3, 2020, from https://www.britannica.com/science/primaquine

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Technology and the Developing World

BY AMITTAI WEKESA ’24 Cover image: People using mobile phones. Mobile computing and communication is one of the modern technologies driving innovation in developing and leastdeveloped countries.

Source: Wikimedia Commons

Abstract It is notable that some countries – specifically the developing and the least-developed countries – lag behind others in developing and using technology. While this might put them at a disadvantage, it also uniquely positions them to implement technology from the ground up to tackle their big issues such as poverty and other developmental problems.

This research paper attempts to analyze themes surrounding the technological gap between developed countries and developing/ least-developed countries and predict future opportunities for developing/least-developed countries to use technology and boost growth and development.

Introduction Developed countries are generally categorized as those that have a per capita income level higher than $12,000 (on average, developed 16

nations have a per capita income of $38,000) while developing nations fall in the per capita income range of $1,000 to $12,000, and least-developed nations fall below the $1,000 mark (Advocates for International Development, 2019). Currently, developing and least-developed nations are significantly behind developed nations in terms of adopting technology, which puts them at a serious disadvantage. To understand this gap and how it can be bridged, it is useful to understand the history of technological inventions.

History of Technological Developments How and why exactly does technology develop?

A persistent driver in the past has been energy.

According to the first law of thermodynamics, energy can neither be created nor destroyed – it is only possible to transform energy between different forms. But the law does have one DARTMOUTH UNDERGRADUATE JOURNAL OF SCIENCE

Figure 1: A world map showing the distribution of countries classified as developed, developing, and leastdeveloped. Developed countries fall under the “advanced economies” and “in transition” labels (dark blue and light blue), developing countries fall under the “less developed,” (orange) and least-developed economies fall under the “least developed” (red) labels respectively.

Source: Wikimedia Commons

special caveat. Einstein’s special theory of relativity relates a body’s mass to its energy using the equation E = mc^2. In short, the equation means that mass can be converted to energy and vice versa. (Fernflores, 2019).

This equation has real-world applications – specifically in energy production. For example, nuclear fusion uses a manageable amount of energy to combine two atomic nuclei and, in the process, converts a slight amount of their mass into energy. However, nuclear physics was a non-existent field until the late 1800s and early 1900s when Henri Becquerel, Marie Curie, and Pierre Curie made significant discoveries about radioactivity (Marie Sklodowska Curie, 2020).

Prior to the discoveries of radioactivity and nuclear fusion, elementary methods were employed to produce energy. One of the earliest ever energy sources was fire, which archaeologists estimate first came into use about two million years ago. However, it wasn’t until around 8000 BCE that proper human settlements evolved, and agriculture became common practice (Technology Timeline, 2020). Once concentrated settlements started developing, people began seeking more resourceful means of utilizing their land and resources. For a long time, productive work – agricultural activity or the work of craftsmen, was done entirely with manual, hand-held tools The use of metals such as copper, bronze, and iron over the traditional use of less strong wood emerged from 3000 to 600 BCE to make manual labor somewhat easier.

More proper use of energy to power devices was the steam engine, which is actually thought to have been pioneered by the Greeks in 62 CE.

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However, it was not until the 19th century that steam engines had widespread, productive use in factories, steamships, and railroad transportation. This lag in productive use is true of many pioneering inventions. Before the turn of the common era, basic concepts of windmills, gunpowder, microscopes, and even telescopes had already been developed. In 1703, Gottfried Leibniz pioneered the binary number system that is used in virtually all computers today.

In 1769, Wolfgang von Kempelen developed the first speech synthesizer. And in 1801, Joseph-Marie Jacquard’s automated clothweaving loom which used punched cards to store patterns inspired a similar method of data storage in first-generation computers (Technology Timeline, 2020). These new inventions required a mechanism for power storage. Sure enough, around 11 years later the first battery was invented.

"Prior to the discoveries of radioactivity and nuclear fusion, elementary methods were employed to produce energy."

Over time, it seems that technological developments have been employed with greater haste. For example, it only took about ten years after Michael Faraday developed the first-ever, primitive electric generator for a practical electric motor to be implemented using the same concept employed in modern motors (Technology Timeline, 2020). This motor enabled the use of electric batteries to drive physical engines, which was a significant step that allowed further development of mobile machines such as trains.

The next major era in the evolution of science and technology, taking place in the 19th century, involved the transportation sector. As new technology that enabled faster, longerdistance travel was introduced, civilizations could operate more efficiently – shipping and

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sending messages over long distances. The 19th century was the setting for a communications revolution too. In the 1830s, Charles Wheatstone, William Cooke, and Samuel Morse developed the first functional electronic telegraph – a forerunner of the modern telephone – which Wheatstone and Cooke used to send a message from England across the Atlantic to Morse in the United States. Another method of communication, the fax machine, emerged in Source: Wikimedia Commons the 1840s. Fax machines necessitated a standard keyboard format, so the QWERTY layout – which is still used in modern computers – was pioneered in 1868 (Technology Timeline, 2020).

Figure 2: Marie Curie, one of the revolutionaries who paved the way for modern technologies.

Curie was the first female Nobel laureate and the first person to win a Nobel prize in both physics and chemistry in recognition of her contributions to nuclear physics. On the 4th of July, 1934, Curie died of aplastic anemia, a blood disease caused by exposure to nuclear radiation.

"This is a significant reason why developing and leastdeveloped countries are lacking in terms of infrastructure development, and therefore general economic prosperity: they are behind in developing and using technology."

The next wave of developments came courtesy of the rivalry between Thomas Edison and Nikola Tesla in the late 1800s. Edison pioneered phonographs in 1868, but his most significant contributions were in the field of electricity.

In the 1880s, Edison opened the world’s first power station based on direct current (DC) power, which Nikola Tesla briskly followed with his invention: alternating current (AC). What followed was a bitter competition that resulted in Edison electrocuting an elephant using alternating current, Tesla’s invention, on January 4th of 1903 to show that alternating current is dangerous and should not be adopted by society.

Other modern technologies, such as X rays for biological imaging and basic, fundamental space rocketry theories, had also been born at the end of the 19th century (Technology Timeline, 2020).

The 20th century brought an even greater array of inventions. In 1912, chemist Gilbert Lewis formulated the chemistry used in rechargeable lithium batteries. It took just ten years to go from the first monochrome television in the 1920s to the first color television in the 1930s.

In contrast, it took an entire 45 years to go from the first use of radio waves for the idea of using a space-based “mirror” to bounce radio waves

Figure 3: The steam engine, one of the early devices designed to harness energy.

Source: Wikimedia Commons

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from one side of the planet to the other was conceptualized. The development of space technology and other modern technologies enabled even more discoveries and innovation.

And the development of transistors allowed engineers to build vast, sophisticated circuitry onto small boards, which was a significant step toward modern microprocessors and integrated circuits. Memex, the first digital storage device which was developed by a US engineer called Vannevar Bush, was also a forerunner of modern computer storage devices. (Technology Timeline, 2020).

The Technology Gap Revisited A nation’s economic and developmental sustainability is very much contingent on its ability to create or otherwise acquire and adapt to new technologies. This is a significant reason why developing and least-developed countries are lacking in terms of infrastructure development, and therefore general economic prosperity: they are behind in developing and using technology (‘Utoikamanu, n.d.). It must be noted that these countries do not lack the capacity and determination to catch up with their more developed peers; rather, they have faced and continue to face challenges such as political instability, poverty, and other developmental challenges. For example, The Democratic Republic of Congo (DRC) has rich mineral deposits, but its growth is crippled by political instability and a decrepit government (Cackler et al., 2008).

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compared to 1100 in developed nations (‘Utoikamanu, n.d.). Therefore, a crucial step to closing the technological gap is enhancing access to education and ensuring more children go to school.

Most least-developed and developing countries were not even proper nations until the mid1900s when their colonization and occupation

by European powers ended. In contrast, the United States is 244 years old, and most of the Western European nations are far older even than that Developing and least-developed countries have only started taking steps towards industrialization relatively recently. Although they capitalized on earlier developments, it still takes years for the development culture and an appropriately-skilled workforce to develop. This results in most developing and least-developed countries needing technology they do not develop. Most devices such as cars, consumer electronics, technology-based services, and even industrial equipment are imported from developed nations. This phenomenon is known as technology transfer.

Technology Transfer and Factors Contributing to the Technology Gap Numerous international forums such as the Annual Forum of Developing Country Investment Negotiators, organizations such as The United Nations, and agreements such as The United Nations’ sustainable development agenda have acknowledged the importance of transferring technology to developing countries. If done correctly, this transfer can empower states to build their capacity for growth and sustainability. However, even with the import of technology, developing and leastdeveloped countries often lack a sufficiently skilled workforce. For instance, the net school enrollment rate for school-aged children was less than 9% in the least-developed countries in 2013 compared to a worldwide 33% average. In 2015, 40% of all out-of-school children resided in least-developed countries (‘Utoikamanu, n.d.). Most African countries fall in the developing/least-developed category. In 2013, Africa had an average of 7 scientific and technical journal articles per million people,

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Infrastructure constraints also pose a significant challenge to developing and using technology in developing and least-developed countries.

For example, some of these countries lack reliable connectivity to the world through internet infrastructure, and most of them lack universal connectivity. Today’s world is highly dependent on online access and collaboration, so the lack of connectivity hinders these countries’ interaction with other countries and ultimately limits their development. Similarly, developing other forms of infrastructure such as transport and energy, are vital too for a nation’s economic growth.

Figure 4: Young African soldiers in Burundi. Burundi and multiple other least-developed countries have been plagued by civil wars and instability, which is a hindrance to their development.

Burundi’s Civil War took place from 1993-2005.

Source: Wikimedia Commons

"Most African countries fall in the developing/leastdeveloped category.

In 2013, Africa had an average of 7 scientific Native Development and Use of and technical journal Technology in Developing Countries articles per million Technology has and will continue to be people, compared to instrumental in the industrial and economic 1100 in developed progress of developing countries. Recent polls nations." show that an astonishing 83% of adults in developing economies have mobile phones (Klapper, 2019). Entrepreneurs and developers in developing and least-developed countries have capitalized on this extensive use of mobile phones to create innovative technology and services that use mobile phones as portals to multiple industries. However, one of the biggest challenges for such development is the lack of capital. In recognition of the immense potential that such initiatives have in creating a positive impact and returning a profit, several programs have emerged to source funding. One such program is Kiva, an online platform that allows people worldwide to sign up and pool money to microfinance high-impact technology and

Figure 5: An M-Pesa sign at a restaurant that allows payment through the financial service. M-Pesa allows isolated populations to access financial services that would otherwise be more difficult to access.

Source: Wikimedia Commons

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Figure 6: M-Pesa menu. The service allows people to send and receive payments straight through their phones without the need to access the internet.

Source: Wikimedia Commons

"In Malawi [...], an SMS-based service called Airtel 321 provides maternal advice, child-care, and nutritional information to pregnant mothers in their native language, which makes it easier, faster, and cheaper for mothers to access necessary information."

social impact entrepreneurs in developing and least-developed countries (Roodman, 2009).

Some of the most successful ideas in developing and least-developed countries utilize mobile phones as gateways to industries and products that are not physically available in specific areas.

These services can range from banking, health, information services, and even e-commerce.

For example, phones have been used to access banking services, health information, weather information, online markets for goods, and many other virtual spaces. The success of past technological applications in developing and least-developed countries also motivates new technological innovations to solve new problems (Cackler et al., 2008).

Perhaps the most successful mobile service in developing and least-developed countries is mobile money. Mobile money is an SMS-based money transfer and monetary storage tool that was first developed in Kenya but has been adopted in many developing and developed countries worldwide. The Kenyan pioneer program called M-Pesa was rolled out in 2007 to widespread success. M-Pesa appealed to people in rural areas, a demographic of people previously underserved in financial and banking services. In 2014, 58% of the adult population in Kenya had an M-Pesa account, a number that is likely higher today (Thorstein et al., 2018).

With M-Pesa, clients do not have to travel long distances to get banking services such as sending money or receiving money – they merely have to visit an M-Pesa agent in the local town where they can deposit money into an account linked to their phone number, or they can withdraw money from their account. The process of sending money is even more straightforward: just key in the recipient’s phone number, select an amount to send and confirm your account pin code. Due to this simplicity, many people, especially rural farmers and entrepreneurs who needed to frequently send and receive money, preferred it over traditional banking services (Conocimiento, 2019).

With time, M-Pesa has accomplished integration with traditional banking options, thus extending the service’s reach and giving users the chance to send money to or take money from their bank accounts without physically visiting a bank.

This integration has dramatically improved the efficiency and ease of banking, one of the reasons M-Pesa in Kenya and similar services in other countries have been widely adopted. In fact, in the financial year ending June 2020, an

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estimated 43% of Kenya’s annual GDP flowed through M-Pesa. A study by the Massachusetts Institute of Technology estimated that M-Pesa had helped lift 194,000 Kenyan households out of extreme poverty, 2% of the estimated total number of families in the country (Conocimiento, 2019).

The health sectors in developing and least-developed countries have also seen tremendous growth due to technological developments. Most developing countries have a hard time developing advanced medical equipment and building hospitals for their entire populations (Casarez, 2016). The use of key technologies has immensely helped bridge the gap in access to healthcare. In Malawi, for example, an SMS-based service called Airtel 321 provides maternal advice, child-care, and nutritional information to pregnant mothers in their native language, which makes it easier, faster, and cheaper for mothers to access necessary information (‘Utoikamanu, n.d.).

Similar services in Tanzania and Rwanda have also experienced much success. Zipline, the Rwandan service, even has a partnership with the national government to deliver medical supplies using drones, which dramatically reduces the time required for deliveries and bypasses poor roads and other transport challenges (‘Utoikamanu, n.d.).

Agriculture is one of the critical industries in developing and especially least-developed countries where most of the population participates in subsistence farming. In recent years, climate change and a deteriorating natural resource base have contributed to a decline in productivity, especially in Africa and South Asia. A key to improving agricultural productivity and raising income and sustainability is the adoption of innovative technologies and efficient practices by farmers (Chand & The World Bank, 2019). This will enable farmers to adapt to climate change, adopt new

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between businesses and people in the two cities (Railway Technology, 2020).

Aviation improvements have also improved export trade. For example, Kenya is one of the biggest exporters of horticultural products to the European Union despite being thousands of miles away. Horticultural products are timesensitive, but trade is possible because of modern fast transport speeds.

Figure 7: A motorcycle taxi operating in a rural township in Kenya. Due to unequal distribution of resources and infrastructure, rural areas in developing countries tend to be left behind as urban areas develop.

Source: Wikimedia Commons

Future Trends and Caveats crops and production systems, raise yields, and improve product quality.

Notably, technology is already offering multiple benefits to agriculture in developing and least-developed countries as international administrations such as The United Nations and The World Bank push for more widespread technology adoption. For example, the introduction of genetically-modified crops that are resistant or adapted to changing climate patterns has not only enabled developing and least-developed countries to cope with climate change, but has also increased production in these countries (Cackler et al., 2008).

Transgenic crops such as herbicide-tolerant soybeans could potentially benefit developing economies. Some countries have also made traditional applications of technology to improve agriculture. For instance, the Pink Phone project in Cambodia helps farmers exchange expertise, access resources, and even buy and sell land through their mobile phones, facilitating easier production and sale of farm products (‘Utoikamanu, n.d.).

Technology has also greatly improved the transport sectors in developing and least-developed countries. Technological advancements have led to more straightforward, cheaper, and more accessible means of transportation (Lee & The World Bank, 2015).

A good case in point is the implementation of a light railway system in Addis Ababa, the Ethiopian capital, in 2015. This railway system has dramatically improved mobility and therefore eased business in the city. A similar approach in Kenya linking the Kenyan capital of Nairobi to Mombasa, a coastal town that acts as Kenya’s main port of import and export, has immensely reduced the time taken to transport imported goods from Mombasa to Nairobi where a majority of the clientele lives. This improvement has enhanced import and export trade in the city and encouraged more trade

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Despite all the advantages offered by technology in the developing world, it is imperative to remain aware of trends and risks around developing and adopting technology in these countries. It is a challenge to ensure the fair distribution of technology in rural and urban areas. Urban areas often end up advancing faster while rural areas remain isolated and behind. This phenomenon tends to create a social divide between rural and urban communities. Adopting new technologies also requires a skilled workforce, meaning citizens in these countries often need to learn new skills and foreign languages to operate imported machinery.

"Kenya is one of the biggest exporters of horticultural products to the European Union despite being thousands of miles away. Horticultural products are timesensitive, but trade is possible because of modern fast transport A majority of the companies and businesses in speeds." developing and least-developed countries rely on manual labor. But as companies do adopt automation technologies, the people employed to provide manual work can be quickly rendered jobless. This fact creates a hostile attitude toward technology and makes society opposed to the adoption of specific technologies. On the other hand, companies still using manual models face industry pressure to keep up with their competitors who have adopted faster and more efficient technology processes.

When such companies do not adopt new technology, they fall behind, and monopolies tend to arise, potentially hindering further

Figure 8: AI is dreaded by many as an existential threat to human existence, akin to an imaginary game of chess between human intelligence and artificial intelligence. However, artificial intelligence could be the path to a prosperous and more inclusive future.

Source: Wikimedia Commons

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"Perhaps a strong indicator of the potential interest that Fintech has in developing countries, Chipper Cash was able to raise 30 million USD during a funding initiative held in October 2020, which even attracted the backing of Amazon founder Jeff Bezos."

innovation. For example, Kenya’s M-Pesa service has a 99% market share despite multiple other competitors. Even as companies use technology to empower communities, it is equally essential that a balance of the competitive landscape is maintained.

Additionally, AI-based pharmacogenomics companies use artificial intelligence to analyze patient responses to specific treatments based on the patients' genetic markers, which enables more intelligent prescriptions (Travaly & Muvunyi, 2020).

Over the past decade, the startup scene in developing countries has greatly improved.

Jackson (2019) points out that this has led to new innovative ideas that utilize technology to offer cutting-edge solutions for common problems.

One area that has seen significant innovation is the finance and banking industries. With the rapid growth of fintech (the use of computer programs and the internet to support banking and other financial services), many startups have emerged. Because they have access to the full power of the internet, such startups can offer way more advantages than those offered by USSD-based and SMS-based services such as MPesa. For example, Chipper Cash, an African cross-border startup, runs a Peer-to-Peer (P2P) service that allows users to send and receive money over the internet for free. Chipper Cash operates in seven countries in Africa: Nigeria, Kenya, Uganda, Ghana, Rwanda, Tanzania, and South Africa. Chipper Cash also offers access to forex trading and even bitcoin trading. Perhaps a strong indicator of the potential interest that Fintech has in developing countries, Chipper Cash was able to raise 30 million USD during a funding initiative held in October 2020, which even attracted the backing of Amazon founder Jeff Bezos (Bright, 2020).

Conclusion

Another trend in the developing world is the rise of artificial intelligence (AI). The AI market in the Middle East and Africa was nonexistent in the early 2000s. In contrast, the industry in these regions grew to an estimated value of $66 million in 2017 (MEST Africa & Lipman, 2019). This has attracted key global players in technology and AI into these regions. For example, Google opened an AI lab in Ghana in 2019. The same year, Microsoft set up its first-ever $100 million Africa Development Hubs in Kenya and Nigeria, matched with a hyper-scale data center in South Africa. Several other companies such as DataProphet and Clevva are spearheading the AI revolution in Africa. DataProphet offers AI data analytics while Clevva uses AI to offer technical and financial consultancy services. In agriculture, an AI startup called My Intelligent Machines uses machine learning algorithms to achieve genomic precision, making it possible to build intelligent breeding programs that minimize the ecological footprints of livestock (Travaly & Muvunyi, 2020).

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It is true that most developing and leastdeveloped countries lag behind in the development and use of technology.

Technology has the potential to immensely boost the growth of developing and leastdeveloped countries if utilized properly. This has been evident in recent years as a more widespread use of technology has immensely boosted growth in these countries. The use of technology also enables these countries to invent new solutions to decades-old problems.

Key global players such as Microsoft, Google, and Amazon are starting to recognize that technology is a significant driver for growth in developing nations and are starting to set up a more dominant presence in developing and least-developed countries. Additionally, the startup sector is an important agent pushing the adoption of technology. It is therefore important for developing countries to invest in their startup sectors and cultivate an innovative culture in their citizens by promoting access to education and making it easier for technology entrepreneurs to access funding.

References Advocates for International Development. (2019, February 18). Understanding the Developed/Developing Country Taxonomy | A4ID. http://www.a4id.org/policy/understandingthe-developeddeveloping-country-taxonomy/ Alatas, S.H.., et al. “Science and Technology Development in the Third World: Competing Policy Perspectives.” Knowledge, Technology & Policy, Springer Netherlands, 1 Jan. 1976, link.springer.com/article/10.1007/s12130-999-1012-6.

Bright, J. (2020, November 18). African fintech startup Chipper Cash raises $30M backed by Jeff Bezos. Techcrunch. https://techcrunch.com/2020/11/18/african-fintech-startupchipper-cash-raises-30m-backed-by-jeff-bezos/ Cackler, J., Gu, E., & Rodgers, M. (2008, March 17). Technology in Developing Economies » Economics » Appropriate Technology. CS 201: Computers, Ethics, and Social Responsibility. https://cs.stanford.edu/people/eroberts/ cs181/projects/2007-08/developing-economies/economicsappropriate.html Casarez, C. (2016, December 15). How the Developing World is Adopting Healthcare Technology - CareCloud. Continuum. https://www.carecloud.com/continuum/how-thedeveloping-world-is-adopting-healthcare-technology/ Chand, I. & The World Bank. (2019, September 16).

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Agricultural Innovation & Technology Hold Key to Poverty Reduction in Developing Countries, says World Bank Report.

World Bank. https://www.worldbank.org/en/news/pressrelease/2019/09/16/agricultural-innovation-technologyhold-key-to-poverty-reduction-in-developing-countries-saysworld-bank-report Conocimiento, V. A. (2019, September 27). Mobile technologies for third world development. OpenMind. https://www.bbvaopenmind.com/en/technology/ innovation/mobile-technologies-for-third-worlddevelopment/ Fallah, M.. “Information Economy and Developing Countries Can They Overcome the Technology Barrier ?”, 2005.

Fernflores, F. (2019, August 15). The Equivalence of Mass and Energy (Stanford Encyclopedia of Philosophy). Stanford Encyclopedia of Philosophy. https://plato.stanford.edu/ entries/equivME/#MiscAbouEoMc2

ScienceDirect. https://www.sciencedirect.com/science/ article/pii/S0304387818300075 Travaly, Y., & Muvunyi, K. (2020, February 7). The future is intelligent: Harnessing the potential of artificial intelligence in Africa. Brookings. https://www.brookings.edu/blog/africain-focus/2020/01/13/the-future-is-intelligent-harnessing-thepotential-of-artificial-intelligence-in-africa/ ‘Utoikamanu, F. (n.d.). Closing the Technology Gap in Least Developed Countries. United Nations. Retrieved November 1, 2020, from https://www.un.org/en/chronicle/article/closingtechnology-gap-least-developed-countries

Jackson, T. (2019, November 20). Africa’s tech startup scene is growing, but who is benefiting? Disrupt Africa. https:// disrupt-africa.com/2019/11/africas-tech-startup-scene-isgrowing-but-who-is-benefiting/ Klapper, L. (2019, April 10). Mobile phones are key to economic development. Are women missing out? Brookings. https://www.brookings.edu/blog/ future-development/2019/04/10/mobile-phones-arekey-to-economic-development-are-women-missingout/#:%7E:text=Fresh%20Gallup%20World%20Poll%20 data,they%20need%20to%20escape%20poverty Lee, C. W. & The World Bank. (2015, May 14). How ICTs Can Help Transport Systems Evolve. World Bank. https://www. worldbank.org/en/news/feature/2015/05/14/informationand-communication-technologies-facilitate-the-evolutionof-transport-systems Mafe, E. & World Economic Forum. (2017, November 10).

More than half of the world’s population is still offline. Here’s what we’re doing about it. World Economic Forum. https:// www.weforum.org/our-impact/creating-hundreds-ofmillions-of-new-internet-users Marie Sklodowska Curie. (2020, June 26). Science History Institute. https://www.sciencehistory. org/historical-profile/marie-sklodowskacurie#:%7E:text=Marie%20Sklodowska%20Curie%20 (1867%E2%80%931934,discovery%20of%20the%20 radioactive%20elements MEST Africa, & Lipman, A. (2019, November 28). 5 Predictions for the African 2020 Tech Scene - The GPS. Medium. https:// medium.com/the-gps/5-predictions-for-the-african-2020tech-scene-afc6a8a964d3 Technology timeline. (2020, October 14). Explain That Stuff. https://www.explainthatstuff.com/timeline.html Railway Technology. (2020, June 10). Mombasa-Nairobi Standard Gauge Railway Project, Kenya. https://www.railwaytechnology.com/projects/mombasa-nairobi-standardgauge-railway-project/ Roodman, D. (2009, October 2). Kiva Is Not Quite What It Seems. Center For Global Development. https://www.cgdev. org/blog/kiva-not-quite-what-it-seems Thorstein, B., Pamuk, H., Ramrattan, R., & Uras, B. R. (2018, July 1). Payment instruments, finance and development.

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Current State of Fluorescence Microscopy for Biological Research Applications

BY ANAHITA KODALI ’23 Cover Image: Fluorescence imaging can allow researchers to study deep tissues; pictured here is a subsection of the kidney with different fluorescent tags and dyes.

Source: Wikimedia Commons

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Introduction Every year, researchers make hundreds of new discoveries that add significantly to the existing body of scientific literature. Often, advancements made by researchers go hand in hand with advancements made to preexisting technologies. One of the most significant tools in the scientist’s toolbox today is imaging techniques, which can give scientists insight into parts of the body that would otherwise be undetectable by the naked eye. Imaging is particularly critical for cellular and molecular biologists, who need microscopy techniques in order to visualize cells, cellular components, and macromolecules. One popular type of microscopy is fluorescence microscopy, which, due to recent advances, has emerged as an essential technique for researchers in the field.

The goal of fluorescence microscopy is to study the anatomy of the living cell. Fluorescence microscopy techniques allow researchers to visualize the physiology of cells at a subcellular

and systems level, giving insight into cellular organization, function, and kinetics (Combs, 2010).

The roots of fluorescence microscopy date back to 1845 with Sir Frederick William Herschel’s recording of fluorescence in solutions of quinine, a compound that is often used in medical tonics and was formerly used as an anti-malarial agent (Renz, 2013; Archan et al., 2011). Herschel, a British-German astronomer, noted that despite quinine solutions being clear, when illuminated by the sun, the solutions would appear blue. Throughout the second half of the nineteenth century, other researchers described fluorescence in great detail and worked to understand how fluorescence lighting gave researchers more clarity when studying specimens (Renz, 2013).

Finally, in 1904, August Köhler, a German professor, built the first fluorescence DARTMOUTH UNDERGRADUATE JOURNAL OF SCIENCE

The Mechanics of Fluorescence and Fluorescence Microscopy

microscope. He was quickly followed by Carl Reichert and Oskar Heimstädt in 1911 and Carl Zeiss and Heinrich Lehmann in 1913 (Dunst & Tomancak, 2019). Throughout the rest of the century and up to the modern day, researchers have worked to improve fluorescence microscopy techniques. The microscopes themselves are faster and allow for extremely good resolution, making them useful for a variety of scientific disciplines; additionally, multi-photon imaging (described later in this article) has become a widely popular technique to study deep tissue. Tagging, which is the process of labeling different molecules (often proteins or antibodies) for detection in fluorescence microscopy, has also improved appreciably due to an increase in the number of fluorophores – the chemical labels used for tagging – and the introduction of fluorescent proteins to imaging techniques (Combs, 2010).

With several types of fluorescence imaging available, it can be difficult for less experienced researchers to choose the correct microscope and technique for their particular project. This paper aims to review the physical explanations for fluorescence and give an overview of the mechanics involved in fluorescence microscopy.

It also discusses several types of fluorescence microscopy with applications in cellular and molecular biology research; however, fluorescence microscopy also has integral uses in several other applications, including biochemistry, biophysics, environmental studies, and pharmacy (see Figure 2).

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Fluorescence refers to the type of luminescence wherein a molecule absorbs and then emits light (Edinburgh Super-Resolution Imaging Consortium, 2016). This paper will primarily focus on production of fluorescence in fluorophores, as these are the compounds most commonly used in fluorescence microscopy.

However, as mentioned above, fluorescence can also occur in other molecules, including proteins. Fluorescence is based on the excitation of electrons. Electron excitation occurs when a discrete amount of energy is added to an atom; the amount of energy, referred to as “excitation energy,” causes the atomic system to promote an electron from its ground (lowest energy) state up to an excited (higher energy) state (The Editors of Encyclopaedia Britannica, 2019).

Fluorescence occurs in a three-step process: photoexcitation of an electron, relaxation of the excited electron, and light emission (Parang et al., 2012).

In the first step, a photon of some energy hv is defined where h is Planck’s constant (equal to 6.626e-34 Js) and v is the photon’s frequency.

The photons are provided by an external source of light, which could be the sun, a lamp, or a laser. Once absorbed by the fluorophore, if the photon has enough energy to excite electrons (photon hvEX), it puts the electrons in an excited electronic singlet state (a state in which the spins of the excited electrons are still paired with the ground electron state) (ThermoFisher Scientific, n.d.; Wong, 2020). This state can be defined as S1’ (ThermoFisher Scientific, n.d.). In total, the excited state lasts anywhere between one and ten nanoseconds.

In the second step, electrons relax; as the electrons relax, the fluorophore undergoes conformational changes and interacts with its molecular environment, resulting in energy dissipation. The fluorophore goes from S1’ to S1, a relaxed singlet excited state; this intermediary step is the state that produces fluorescence emission. Note, however, that not every molecule excited in the first step enters S1. In order to understand how many fluorophores emitted light, scientists created a fluorescence quantum yield, which is defined as the ratio of the number fluorescence photons emitted to the number of photons originally absorbed (ThermoFisher Scientific, n.d.).

Figure 1: Pictured is Sir Frederick William Herschel, the man credited with first discovering and scientifically detailing fluorescence.

Source: Wikimedia Commons

"Fluorescence is based on the excitation of electrons. Electron excitation occurs when a discrete amount of energy is added to an atom; the amount of energy, referred to as “excitation energy,” causes the atomic system to promote an electron from its ground (lowest energy) state up to an excited (higher energy) state."

In the third step, a photon, defined as hvEM, is emitted and the fluorophore enters its ground state (S0). Because energy is dissipated in 25

Figure 2: Ecology is another field where fluorescence microscopy has led to several advances.

Pictured here is fluorescence imaging of a fungal colony.

Studies using fluorescence microscopy can help researchers better understand the cellular interactions of organisms like fungi with the environment.

step two, photon hvEM is of lower energy and therefore longer wavelength than photon hvEX; this difference, called the Stokes shift, can be defined with the equation hvEX - hvEM. One fluorophore can generate thousands of photons (ThermoFisher Scientific, n.d.).

Fluorophores can theoretically go through this process infinitely. However, in certain cases, Source: Wikimedia Commons fluorophores can be destroyed while in state S1’. This is because in S1’, fluorophores can react with oxygen and produce reactive oxygen species, including hydrogen peroxide, hydroxyl radicals, and superoxide radicals. These can all damage cells; they generally morph the redox states of mitochondria and can also oxidize DNA, proteins, and unsaturated fatty acids.

DNA oxidation can result in mutations, while protein and unsaturated fatty acid oxidation renders them both useless. The combination of the change in redox state to the overall cell and degradation of DNA, proteins, and unsaturated fatty acids is referred to as photobleaching and can destroy the fluorophore (Icha et al., 2017).

"In most cases, fluorophores are used to label the sample of interest (one common example is attaching fluorophores to antibodies). Then, the microscope uses a high energy light source, like a Xenon or Mercury arc-discharge lamp, to illuminate the fluorophores through a lens."

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Fluorescence microscopy relies on the principles of fluorescence to detect light and create highresolution images. Generally, the microscopes used in fluorescence microscopy are similar in some ways to conventional microscopes.

Conventional microscopes traditionally use light to illuminate and magnify a sample. The light used in fluorescence microscopes is much more intense than the light used in conventional microscopes; this light, rather than illuminating the sample itself, excites a fluorescent species within the sample, which in turn produces light and creates the magnified image of the sample (Rice, n.d.).

In most cases, fluorophores are used to label the sample of interest (one common example is attaching fluorophores to antibodies). Then, the microscope uses a high energy light source, like a Xenon or Mercury arc-discharge lamp, to illuminate the fluorophores through a lens; this lens is equipped with several filters that allow only specific wavelengths of light through (these wavelengths are the wavelengths of light that can cause fluorophores to produce light). The fluorophores in the sample absorb the light and emit photons with lower energy and wavelength. The light emitted from the fluorophores is subsequently filtered through a series of filters so that researchers can view only the light that is coming from fluorescence (Rice, n.d.).

There are three basic variables to keep in mind when conducting experiments involving fluorescence microscopy. The first is optimization of competing properties of image resolution (Combs, 2010). Image resolution is typically defined as the smallest distance between two points on some sample that, when viewed, can still be distinguished from each other. As resolution goes up, the distance between the two points gets smaller, and a more detailed and clearer image is produced (“Resolution,” n.d.). In fluorescence microscopy, the competing properties lie in the different dimensions, as fluorescence microscopy creates 3D images. Researchers want the optimum resolution between the lateral (XY) plane and the axial (Z) dimension; while they could get a very clear image from just focusing on one plane, they would be losing depth. Thus, striking a balance of where to focus the light is of utmost importance (Combs, 2010).

The second is the runtime of the experiment.

Generally, researchers want to optimize the speed of the acquisition of their image from the microscope without compromising the image resolution. Thus, investment into good equipment is critical. A barrier to speed is both size of sample and laboratory funding (Combs, 2010).

The third is the amount of fluorescence collected from fluorophores in the sample.

As aforementioned, fluorophores could theoretically fluoresce forever. Despite this, there are immediate issues with loss of light and energy as not every fluorophore fluoresces every time light is directed at the sample.

More critically, however, are the issues of photobleaching and phototoxicity (Combs, 2010). Though the two are similar, they are not the same (please refer above for an explanation of photobleaching). Phototoxicity

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can refer generally to the damage that a living organism or cell undergoes due to exposure to light. It is a complex process that involves several different photophysical mechanisms that create highly reactive products, as well as produce high amounts of heat and damage DNA (often through photobleaching). Factors in the amount of phototoxicity present include excitation wavelength, intensity of excitation light and light produced by fluorescence, exposure time, and concentration and location of fluorophores. As fluorescence always results in development of free radical products, it is not possible to fully eliminate phototoxicity or photobleaching, but cells do have mechanisms to overcome these issues –the task of the researcher is to make sure that the sample’s cells are not overwhelmed (Laissue et al., 2017).

Fluorescent Tagging Techniques There are several different targets that researchers may want to track and image (and therefore several different targets for tagging with fluorophores). The most common target is proteins. When working with proteins, the first step that researchers must take is deciding which of three types of fluorescent protein to use. The first is intrinsically fluorescent proteins, which do not require the addition of an external fluorophore; rather, they become fluorescent after folding (the process in which a protein acquires its functional, 3D shape). These are arguably the easiest to use, as researchers just have to make sure that they will fold in the environment they are placed in. However, because they are not being externally manipulated, they lack the flexibility that researchers often need when studying dynamic cellular environments.

The second type is extrinsically fluorescent proteins that bind directly to biomolecules (like fluorophores). Often, these are as easy to use as intrinsically fluorescent proteins if the fluorophore is present in the cellular environment being targeted. Typically, this is the case, but sometimes researchers need to supplement the fluorophore externally. The third and final type is extrinsically fluorescent proteins that need to bind to ligands in order to connect to fluorophores. These require the use of synthetic molecules, and while they are more difficult to use, they allow for a high amount of flexibility in fluorescence as the fluorescent tags are usually separate from the molecules that bind to the proteins themselves and are therefore easily interchangeable for other types of fluorophores (Thorn, 2017).

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If the researcher decides on an extrinsically fluorescent protein, they will generally rely on one of three tagging techniques. The first technique involves the use of self-labeling enzymes. These are fusion tags that can catalyze the auto-attachment of organic fluorophores preexisting in the cellular environment that the proteins are in. Once the proteins come in contact with these enzymes, they are able to connect to fluorophores. While this method is advantageous in that researchers do not have to exogenously introduce fluorophores to the sample, it depends on the expression of the fusion tag, which results in variability of the amount of fluorescence produced.

The second technique is use of enzymes that catalyze attachment of fluorophores to some target sequence on the protein. This technique involves use of short peptide sequences that are rare in the native cellular environment.

Enzymes, when exposed to the sequences, catalyze the binding of the protein to some fluorophore. This technique can involve introduction of external fluorophores and also has some variability. In the third technique, researchers can use dyes that fluoresce instead of using enzymes to catalyze reactions between proteins and fluorophores. Dyes target protein motifs and can fluoresce once they come into contact with particular protein sequences (Crivat & Taraska, 2012).

Different Types and Applications of Fluorescence Microscopy A baseline fluorescence technique applicable for several situations is the dark-field system.

Dark-field microscopy refers to any kind of microscopy that excludes unscattered beams of excitation light from the final image produced, thus creating a darker field around the specimen being viewed and allowing for better visualization of the sample (Weigel et al., 2014). In fluorescence microscopy, creating a dark-field system gives several advantages to the researcher. The biggest impact is that the use of a dark-field system provides a black background to the image produced, allowing for the formation of an image with high contrast; this allows the researcher to see the details of the image more clearly. Additionally, the focal length of the system is relatively short, resulting in a concentration of energy in a smaller area, which minimizes energy loss (Young, 1961).

"The biggest impact is that the use of a dark-field system provides a black background to the image produced, allowing for the formation of an image with high contrast; this allows the researcher to see the details of the image more clearly."

There are several different options and advantages to other techniques. A major decision a researcher must make is use of

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Figure 3: This image represents the ideal room setup for fluorescence microscopy experiments. The room should be kept as dark as possible, with the only external light coming from any critical monitors and the excitation light. By cutting out as much light pollution as possible, the final image will come out with the highest possible resolution.

Image Citation: Wikimedia

"Optical sectioning microscopy only collects information from one specific image plane that is in focus. This allows for a much higher resolution image but also comes with barriers of longer acquisition times and higher photobleaching and phototoxicity."

widefield versus optical sectioning versus superresolution microscopy. In widefield microscopy, the sample is illuminated on the microscope’s whole field of view, which is advantageous because a low-intensity application of excitation light is enough to illuminate the entire sample.

This method minimizes photobleaching and phototoxicity while having relatively fast acquisition of the image. However, as a result of the speed and low-intensity excitation photons, the images created tend to be lower-resolution, as information is collected not just from the areas of interest but areas outside of the bounds that researchers want to examine as well. This technique is optimal for researchers attempting to study living specimens for long periods of time (Dunst & Tomancak, 2019).

Optical sectioning microscopy only collects information from one specific image plane that is in focus. This allows for a much higher resolution image but also comes with barriers of longer acquisition times and higher photobleaching and phototoxicity (Dunst & Tomancak, 2019).

There are several different kinds of optical sectioning microscopy. Multiphoton imaging is typically used to collect deep-tissue information.

Often, researchers use two-photon microscopy.

In this technique, two-photons of relatively long wavelength are absorbed by the fluorophore at the same point in time, which minimizes the amount of stray light involved in the analysis and therefore reduces photobleaching and phototoxicity. Because of this, the imaging can

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be run for a long time. The main downside of multiphoton imagery is that researchers penetrate deeper into the tissue and image resolution goes down (Larson, 2011). Lightsheet microscopy is another common optical sectioning technique. This technique is often used to study cellular kinetics and dynamics, which are both critical for understanding tissue formation (Albert-Smet et al., 2019). Lightsheet microscopy generates a light-sheet to illuminate the sample, which selectively illuminates one plane across the microscope’s entire plane of view. Because only one plane is focused on at a time, this technique is extremely fast and issues with photobleaching and phototoxicity are highly reduced (Dunst & Tomancak, 2019). Issues come with building the microscopes themselves. Because they are so specific to the samples created, light-sheet microscopes often need to be custom built and require many extra parts. Thus, this technique is much more expensive than other fluorescence microscopy techniques (Albert-Smet et al., 2019).

The basic goal of super-resolution imaging is to get the absolute highest possible resolution possible. As such, it is fundamentally bound by the resolution limit; this limit is defined by two critical principles (Dunst & Tomancak, 2019).

The first is the Abbe criterion. Ernst Abbe, a German physicist, proposed that images are composed of overlapping diffraction-limited spots; these are areas that limit the resolution

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of images. The way to minimize the spots of diffraction is to decrease excitation wavelength and use samples with higher refractive indexes.

Even under ideal conditions, however, lateral resolution is limited to at most 250 nanometers (“The Diffraction Barrier in Optical Microscopy,” n.d.). Thus, the Abbe criterion is a limitation on lateral resolution due to diffraction of lines in imaging planes (Dunst & Tomancak, 2019). The second critical principle is the Rayleigh criterion, which puts a limit on angular resolution. The principle states that for any circular lens, two images are only resolvable if the diffraction pattern center of the first image is directly over the first minimum diffraction spot of the second image (“Limits of Resolution: The Rayleigh Criterion,” n.d.). Thus, the Rayleigh criterion defines the limit of resolution in terms of point object diffraction. In reference to fluorescence microscopy, these principles come into play when considering collection of fluoresced light from fluorophores. These principles put significant limits on the angles at which light can be collected and the distances from both the sample and the excitation source that the light can be emitted (Dunst & Tomancak, 2019).

Despite these limits, researchers have been working steadily to break the resolution limit through super-resolution imaging techniques.

Super Resolution Structured Illumination Microscopy (SR-SIM) imaging, for example, works by using a pattern of illumination rather than using a concentrated excitation source, which disperses the amount of diffraction spots and lowers the impact of the Abbe and Rayleigh criterions (Wu & Shroff, 2018). A major limitation of SR-SIM imaging is that it requires layering of individual images, which increases time of acquisition and therefore increases exposure to the excitation light, resulting in higher chance of fatal photobleaching and toxicity (Dunst & Tomancak, 2019).

Conclusions There are several options available for researchers who are trying to employ fluorescence microscopy techniques for their work. As the tagging and imaging techniques become more specific, the results can have higher resolution and more specificity to what the researcher is studying. However, one must take caution when choosing what technique to use, as different methods have different pitfalls and may not be suitable for all projects. As fluorescence microscopy continues to advance, there will undoubtedly be new microscopes, add-ons, and techniques that further refine imaging in cellular and molecular biology fields,

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which leaves the possibilities for future research nearly endless. These advances will come with a greater amount of difficulty in employing fluorescence microscopy techniques and a much steeper initial learning curve. As such, it is important to write up to date reviews on the state of microscopy to help guide researchers in their work.

References Achan, J., Talisuna, A. O., Erhart, A., Yeka, A., Tibenderana, J. K., Baliraine, F. N., Rosenthal, P. J., & D’Alessandro, U. (2011).

Quinine, an old anti-malarial drug in a modern world: Role in the treatment of malaria. Malaria Journal, 10(1), 144. https:// doi.org/10.1186/1475-2875-10-144 Albert-Smet, I., Marcos-Vidal, A., Vaquero, J. J., Desco, M., Muñoz-Barrutia, A., & Ripoll, J. (2019). Applications of Light-Sheet Microscopy in Microdevices. Frontiers in Neuroanatomy, 13, 1. https://doi.org/10.3389/ fnana.2019.00001 Combs, C. A. (2010). Fluorescence Microscopy: A Concise Guide to Current Imaging Methods. Current Protocols in Neuroscience, 50(1). https://doi.org/10.1002/0471142301. ns0201s50 Crivat, G., & Taraska, J. W. (2012). Imaging proteins inside cells with fluorescent tags. Trends in Biotechnology, 30(1), 8–16. https://doi.org/10.1016/j.tibtech.2011.08.002 Dunst, S., & Tomancak, P. (2019). Imaging Flies by Fluorescence Microscopy: Principles, Technologies, and Applications. Genetics, 211(1), 15–34. https://doi. org/10.1534/genetics.118.300227 Edinburgh Super-Resolution Imaging Consortium. (2016, May 31). PRINCIPLES OF FLUORESCENCE. ESRIC. https:// www.esric.org/education/education-centre/principles-offluorescence.

Icha, J., Weber, M., Waters, J. C., & Norden, C. (2017).

Phototoxicity in live fluorescence microscopy, and how to avoid it. BioEssays, 39(8), 1700003. https://doi.org/10.1002/ bies.201700003 Laissue, P. P., Alghamdi, R. A., Tomancak, P., Reynaud, E. G., & Shroff, H. (2017). Assessing phototoxicity in live fluorescence imaging. Nature Methods, 14(7), 657–661. https://doi. org/10.1038/nmeth.4344 Larson, A. M. (2011). Multiphoton microscopy. Nature Photonics, 5(1), 1–1. https://doi.org/10.1038/nphoton. an.2010.2 Limits of Resolution: The Rayleigh Criterion. (n.d.). Lumen.

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Parang, Z., Keshavarz, A., Farahi, S., Elahi, S. M., Ghoranneviss, M., & Parhoodeh, S. (2012). Fluorescence emission spectra of silver and silver/cobalt nanoparticles. Scientia Iranica, 19(3), 943–947. https://doi.org/10.1016/j.scient.2012.02.026 Renz, M. (2013). Fluorescence microscopy-A historical and technical perspective: Fluorescence Microscopy. Cytometry

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Part A, 83(9), 767–779. https://doi.org/10.1002/cyto.a.22295 Resolution. (n.d.) Nikon MicroscopyU - The Source for Microscope Education. Nikon. Retrieved from https://www.microscopyu.com/microscopy-basics/ resolution#:~:text=The%20resolution%20of%20an%20 optical,camera%20system%20as%20separate%20entities.

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Molecular Biology of the Cell, 28(7), 848–857. https://doi. org/10.1091/mbc.e16-07-0504 Weigel, A., Sebesta, A., & Kukura, P. (2014). Dark Field Microspectroscopy with Single Molecule Fluorescence Sensitivity. ACS Photonics, 1(9), 848–856. https://doi. org/10.1021/ph500138u Wu, Y., & Shroff, H. (2018). Faster, sharper, and deeper: Structured illumination microscopy for biological imaging.

Nature Methods, 15(12), 1011–1019. https://doi.org/10.1038/ s41592-018-0211-z Wong, D. (2020, March 18). 15.1: Electronically Excited Molecules can Relax by a Number of Processes. Chemistry LibreTexts. Retrieved from https://chem.libretexts.org/Courses/ Pacific_Union_College/Quantum_Chemistry/15%3A_Lasers_ Laser_Spectroscopy_and_Photochemistry/15.01%3A_ Electronically_Excited_Molecules_can_Relax_by_a_Number_ of_Processes Young, M. R. (1961). Principles and Technique of Fluorescence Microscopy. Quarterly Journal of Microscopical Science, s3102(60), 419.

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Double-Edged Sword: The Potential of MMP Inhibitors in Treating Disease

BY ANDREW SASSER ’23 Cover Image: Matrix Metallopeptidase 13 (MMP 13) is a Metalloprotein expressed by the body that is capable of cleaving parts of the extracellular matrix. MMPs like MMP-13 play important biological roles in the regulation of reproduction and tissue repair, but their overexpression has been linked to the development of tumors and osteoarthritis Source: Wikimedia Commons

Introduction In the human body, there are estimated to be at least 20,000 different types of proteins encoded by the genome (Ponomarenko et al., 2016). These proteins play significant roles in the functions of life – ranging from enzymatic activity, cell signaling pathways, and even the causes of various diseases. In fact, proteases are the enzymes crucial for the production of free amino acids needed to synthesize the entire proteome, and they play a crucial role in the functions of all life. One particular class of these proteases, the matrix metalloproteases (MMPs), have significant roles in the regulation and function of the human body.

MMPs are primarily responsible for the degradation of the extracellular matrix, which is composed of various fibers, proteoglycans, glycoproteins and polysaccharides responsible for regulating cell growth and development (Laronha and Caldeira, 2020). First discovered

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in 1962 through the degradation of collagen in tadpoles, MMPs have been found to have roles in a variety of areas including angiogenesis, embryo implementation, and cell death (Rodriguez et al., 2010). MMPs are also secreted in a number of pathological processes, including arthritis, vascular disease and several types of cancer. In the human body, the production of MMPs is strictly regulated by tissue inhibitors of MMPs (TIMPs); a lack of regulation is generally associated with symptoms of inflammation (Verma and Hansch, 2007). As a result, MMP inhibitors have been studied as potential treatments for several diseases associated with overexpression of certain MMPs. Although many of these inhibitors showed promising results initially, the broad spectrum MMP inhibitors first investigated in the 1980s led to off-target inhibition of beneficial MMPs, resulting in many patients experiencing musculoskeletal and gastrointestinal disorders (Fields, 2019). However, as investigated in DARTMOUTH UNDERGRADUATE JOURNAL OF SCIENCE

this paper, more selective MMP inhibitors have since been developed; these new MMP inhibitors may serve as a potential treatment for cancer and inflammatory diseases while avoiding the unintended side effects of earlier inhibitors classes.

Structure and Chemical Mechanism of MMPs The structure of MMPs play an important role in their ability to degrade parts of the extracellular matrix. Classified as members of the matrixin subfamily, these enzymes have four main components: a pro-domain associated with the inactive enzyme, a catalytic domain with a zinc ion, a linker peptide, and a hemopexin-like terminal domain (Nagase et al., 2006). When MMPs are first synthesized, a cysteine residue in the pro-domain is responsible for blocking enzymatic activity by coordinating to the catalytic zinc ion to form a tetrahedral sphere – preventing binding by a substrate (Laronha and Calderia, 2020). These groups are typically activated by cleaving from other MMPs; however, they can also be activated by mercury reagents or strong oxidants such as HOCl. These strong oxidants are often associated with inflammatory conditions, possibly explaining MMP activity in patients with these conditions (Nagase et al., 2006). The active site, composed of approximately 160 amino acids, contains a zinc ion that often has up to three calcium ions associated with it. It is believed that these calcium ions are responsible for helping to maintain the 3D folding structure of the polypeptide (Nagase et al., 2006). This region is subsequently connected to the hemopexin domain via a proline-rich linker that lessens enzyme rigidity. This domain is likely responsible for cleaving collagen, with the catalytic domain being sufficient for the cleavage of non-collagen substrates (Laronha and Caldeira, 2020).

Proposed mechanistic pathways for the activation and action of MMPs indicate that the zinc ion plays a crucial role in the enzymes’ function. Initial investigations by Kester and Matthews suggested that the interaction of a peptide substrate with a water molecule and the zinc ion is crucial for the process of catalysis. After investigating the binding of ß-phenylpropionyl-L-phenylalanine to the MMP thermolysin, the group proposed that a water molecule is responsible for nucleophilic attack at the carbonyl carbon, with a histidine residue donating a proton to the adjacent nitrogen to break the bond. The zinc ion was

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proposed to be coordinated to the carbonyl carbon of the peptide bond and responsible for depolarizing the peptide bond, making it easier to break (Kester and Matthews, 1977).

Later investigations by M.F. Browner suggested a similar nucleophilic role for water in the enzymatic mechanism for human matrilysin, with a glutamate residue acting as the proton donor needed to cleave the peptide bond (Browner et al., 1995). However, more recent work from Manzetti et al. suggests that water may not be directly involved in hydrolysis. In studies of the MMP-3 and ADAM-9 matrix MMP enzymes, the group discovered significant hydrophobic pockets in the enzyme that would inhibit nucleophilic attack from water.

Instead, the group proposed that the zinc ion polarizes a glutamic acid residue to attack the peptide carbonyl to form a tetrahedral intermediate, with subsequent elimination of the amino group. They also proposed that a water molecule would subsequently attack the carbonyl group in the glutamic acid residue to free the enzyme for further catalysis (Manzetti et al., 2003).

Function and Disease Background of Different Classes of MMPs While MMPs generally have similar structural features, slight variations and additions to different MMPs enable their respective functions. Among MMPs, there are five main classes: collagenases, gelatinases, stromelysins, matrilysins, and membrane-bound MMPs (Laronha and Caldeira, 2020). Their normal biological function, as well as their role in selected disease states, will be explored below.

The collagenases, among the first MMP classes to be discovered, are responsible for the cleavage of fibrillar collagen – one of the most abundant protein classes of the extracellular matrix. The rigid triple helix conformation of the polypeptide enables their ability to withstand action from other proteinases (Amălinei et al., 2007). Secreted by a wide variety of cells such as fibroblasts and endothelial cells, the cleavage products of collagenases produce gelatin (Laronha and Caldeira, 2020). It has been suggested they may a play role in the in vivo healing of injuries through the stimulation of keratinocytes (Riley and Herman, 2005).

However, elevated collagenase activity has been implicated in the development of abdominal aortic aneurysms and aortic occlusive disease. Often associated with atherosclerosis (buildup of cholesterol in the arteries), the elevated presence of collagenases leads to the destruction of collagen in the aorta, thinning the blood vessels and increasing the

"While MMPs generally have similar structural features, slight variations and additions to different MMPs enable their respective functions.

Among MMPs, there are five main classes: collagenases, gelatinases, stromelysins, matrilysins, and membrane-bound MMPs."

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possibility of rupture (Donahue et al., 2006).

Gelatinases play a significant role in the digestion of gelatin, type IV collagen, and laminin. The addition of three fibronectin type II domains enables the enzyme to effectively bind gelatin for further processing into smaller peptides and free amino acids (Laronha and Caldeira, 2020).

Gelatinases are often associated with normal physiological states such as embryonic growth and development and angiogenesis but may also play a role in the pathogenesis of some bacteria. For example, Thurlow et al. found that in rabbit models infected with E. faecalis, elevated gelatinase levels were responsible for increasing bacterial loads and increasing viral dissemination through the cleavage of fibrin (Thurlow et al., 2010).

"While an imbalance in various classes of MMPs has been implicated in a number of inflammatory conditions, most research into the biological activity of MMPs has been directed into its role in the development and spread of a wide variety of cancers."

Unlike the prior two categories of MMPs, the stromelysins are generally incapable of cleaving most types of interstitial collagen (Nagase et al., 2006). While arranged with a similar domain arrangement to that of the collagenases, stromelysins instead participate in cleaving other parts of the extracellular matrix such as elastin, fibronectin, and aggrecan (Cui et al., 2017). Stromelysins play a regulatory role in the expression of connective tissue growth factor and may also be involved in normal cell apoptosis (Cui et al., 2017). However, stromelysin upregulation is associated with inflammatory conditions such as post-traumatic osteoarthiritis.

Ding et al. discovered that an up-regulation of MMP-3, a stromelysin, occurred after blunt force was applied to dead cow cartilage. This upregulation was responsible for damaging cartilage and producing catalytic fibronectin fragments, creating a positive feedback loop of further cartilage destruction (Ding et al., 2014).

Unique among the MMPs, matrilysins lack the hemopexin and hinge region associated with most other MMPs, thus rendering them incapable of effectively binding to most types of collagen (Laronha and Caldeira, 2020). Their primary purpose is cleavage of plasminogen to produce angiostatin fragments which are capable of inhibiting angiogenesis. They are also capable of processing some cell surface molecules to either induce or inhibit apoptosis and tissue remodeling (Cui et al., 2017). This class of MMPs has been implicated in the development of chronic tonsilitis. Acioglu et al. discovered that patients with more severe tonsilitis had a significantly higher level of the matrilysin MMP-7. The group suggested that the degraded protein fragments generated by

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elevated levels of matrilysin may be responsible for the inflammation associated with tonsilitis (Acioglu et al., 2010).

Finally, the membrane-type MMPs are the only class of MMPs that are activated intracellularly and bound to the cell surface. In order to remain bound to cell surfaces, these enzymes have membrane anchoring domains, with a domain similar to that of the peptide furin present in the pro-enzyme (Nagase et al., 2006).

They are largely responsible for the activation of other MMPs (such as MMP-2 and MMP-9) and play important roles in pericellular matrix remodeling in late fetal development (Amălinei et al., 2007; Laronha and Caldeira, 2020). Some of these MMPs have also been associated with neural functioning; for example, MMP24 is necessary for the development of neuroplasticity and pain recognition (Cui et al., 2017). However, members of this MMP class also play a role in facilitating undesirable cell migration and proliferation through the degradation of the extracellular matrix; for instance, MMP-16 upregulation led to cell migration that limited the effects of cardiac cell regeneration (Liu et al., 2012).

MMPs and Cancer - A Deeper Investigation While an imbalance in various classes of MMPs has been implicated in a number of inflammatory conditions, most research into the biological activity of MMPs has been directed into its role in the development and spread of a wide variety of cancers. This is due to their role in enhancing angiogenesis and metastasis through the degradation of the extracellular matrix (ECM) (Reunaen and Kähäri, 2013). Studies have suggested that a lack of MMP expression can inhibit cancer spread. For example, Itoh et al. found that when B16-BL6 melanoma cells were injected into the lungs of mice who were deficient in MMP-2, total tumor volume decreased by 39% compared to the control after three weeks.

The same group discovered a 24% relative reduction for Lewis lung carcinomas (Itoh et al., 1998). Conversely, the overexpression of MMPs has been suggested as a possible factor for increased cancer malignancy. For example, Shima et al. discovered that the overexpression of MMP2 and MMP3 was associated with lymph node metastasis and vascular invasion for esophageal carcinoma (Shima et al., 1992).

Similarly, Johansson et al. discovered that MMP13 was overexpressed in the most invasive

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Figure 1: An overview of the structural purposes of various MMPs. Unlike many other types of enzymes, MMPs are capable of cleaving several different substrates in the extracellular matrix. Most MMPs are secreted by cells.

Source: Wikimedia Commons

and aggressive squamous cell carcinomas (Johannson et al., 1997). However, while MMPs have been implicated in the spread of cancer through angiogenesis enhancement, other studies have found that MMPs can limit tumor vascularization. O’Reilly et al. found that MMP 2 was capable of cleaving plasminogen to form angiostatin, a protein fragment that down-regulates the development of new blood vessels in cancer cell lines (O’Reilly et al., 1999). Overall, MMPs play a complicated role in the spread and inhibition of cancer; this dual-faceted role suggests that simply limiting MMPs generally is not enough to stop cancer.

Early Attempts at MMP Inhibitors: Successes and Problems As a result of early studies examining the influence of MMPs on the spread of cancer and other diseases, many pharmaceutical companies have worked on synthesizing MMP inhibitors. Early efforts at synthetic drug design focused on the introduction of a functional group capable of chelating the zinc ion to deactivate the enzyme (Fields, 2019). Among the most promising of these substrates were the succinate-derived hydroxamic acids, in particular those with larger macrocyclic rings which could increase compound potency (Steinman et al., 1998). These hydroxamic acidbased products were derived from the natural structure of collagen but replaced the terminal amide group with a hydroxamate group FALL 2020

(Whittaker et al., 1999). Other initial research efforts investigated carboxylic acids, thiols, phosphorus-based compounds, and various natural products. However, these groups were generally believed to be less effective at successfully chelating the zinc cation of MMPs. For instance, Babine and Bender suggested that carboxylic acid-derived inhibitors are generally 100-2000-fold less potent than their hydroxamate counterparts; they suggested this was due to the need of carboxyl groups to bind a proton after coordinating to zinc. Thus, they estimated that carboxyl groups require about 3-5 kcal/mol of additional energy to successfully bind as compared to hydroxamate (Babine and Bender, 1997). Similarly, the group reported that thiol-based compounds were 20-50-fold less potent due to binding in a monodentate matter that is less stable than the bidentate binding of hydroxamates (Babine and Bender, 1997). Because of these factors, the hydroxamic acid derivatives were the first to reach clinical trials, with drugs such as Marimastat (intended to treat metastatic breast cancer through the inhibition of several different MMPs) and Batimastat (intended to treat inflammation through broad inhibition of several MMPs) being among the first to be tested (Gialeli et al., 2011).

"As a result of early studies examining the influence of MMPs on the spread of cancer and other diseases, many pharmaceutical companies have worked on synthesizing MMP inhibitors."

While pharmacological modeling and lab testing demonstrated that these first classes of MMP inhibitors were generally successful in chelating the zinc ions, initial

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Figure 2: Structure of the first generation MMP Inhibitor Marimastat, in comparison to the natural structure of the alpha-chain of collagen. The use of Marimastat in early clinical trials led to the development of painful musculoskeletal side effects, resulting in the discontinuation of the drug Source: Wikimedia Commons

"Pre-clinical tests with animal models had shown great promise – Batimastat was found to reduce tumor growth by 50% for ovarian carcinoma in mice and completely prevent metastasis of human pancreatic cancer xenografts in mice.

However, clinical tests revealed a lack of efficacy for many of these drugs."

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clinical trials revealed several problems with these first-generation inhibitors. Pre-clinical tests with animal models had shown great promise – Batimastat was found to reduce tumor growth by 50% for ovarian carcinoma in mice and completely prevent metastasis of human pancreatic cancer xenografts in mice (Rasmussen and McCann, 1997). However, clinical tests revealed a lack of efficacy for many of these drugs. For instance, the poor solubility of Batimastat led to its low bioavailability; it was subsequently replaced by the more soluble Marimastat (Zucker et al., 2000). Similarly, clinical trials of the MMP inhibitor BAY 12-9566 for advanced small cell lung cancer revealed shorter survival rates than the placebo, while Ro 32-3555 was found to be ineffective in the treatment of rheumatoid arthritis (Zucker et al., 2000). More worrisome yet was the revelation of dose-limiting side effects associated with MMP inhibitors. Treatment of Marimastat in patients with advanced lung cancer was found to induce a severe polyarthritis for up to eight weeks after discontinuation of the drug (Wojtowicz-Praga et al., 1998). Similarly, patients treated with PG116800 for knee osteoarthritis suffered from reductions in shoulder range-of-motion and neck pain, with 78% of patients experiencing adverse events at the 200 mg dose level (Krzeski et al., 2007).

Attempts to investigate the clinical failure of this first generation of MMP inhibitors suggested that off-target interactions and metabolic instability were possible culprits.

It has been proposed that the complicated proteolytic web of enzymes may be responsible for inducing some of the reported side effects, as hydroxamic acid inhibitors were found to inhibit several different MMPs and some of the related adamlysins (Peterson, 2006). Additional research into hydroxamic acid groups has revealed that there may be poor selectivity for zinc over other transition metals, thus allowing these inhibitors to chelate other transition metals from other enzymes (e.g. iron) (Fingleton, 2008). Metabolic instability of hydroxamic acidbased inhibitors may have also contributed to the lack of drug efficacy. Hydroxamic acids can be easily hydrolyzed to carboxylic acids or reduced to amides by esterases, consequently reducing their effectiveness in chelating to zinc.

It has been suggested that differences in blood plasma between mice and humans also explain why these inhibitors were more effective in animal models as opposed to clinical trials (Fields, 2019).

More Recent Improvements While the initial failure of MMP inhibitors discouraged further research into the subject, more recent improvements have improved their efficacy and selectivity. Both synthetic inhibitors and natural antibodies are currently

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Figure 3: Structure of the specific MMP-13 Inhibitor Pyrmidine Dicarboxamide. Rather than chelating to the zinc ion, this inhibitor targets a side chain specific to MMP-13 Source: Wikimedia Commons

under investigation and have shown some signs of promise. Some of these new developments will be explored below.

Researchers have developed new functional groups that more effectively bind zinc than the initial class of inhibitors. One particular class of compounds that has shown great promise is phosphorus-based inhibitors. Biasone et al. found that the r-enantiomeric variants of α-Biphenylsulfonylamino 2-methylpropyl phosphonates are capable of selectively inhibiting MMP-8 with an IC50 (half maximal inhibition concentration) between 0.8 and 2 nanomolar for most of these derivatives (Biasone et al., 2007). Similar studies have been applied for carbamoyl phosphonates, which chelate in a manner similar to hydroxamic acids but target MMP-2 and MMP-9 with high specificity and no toxic side effects. In fact, this class of compounds reduced tumor growth by 60% and metastasis by 90% in mice at 50 mg/ kg, well below the toxicity threshold of 500 mg/ kg (Hoffman et al., 2008). Groups such as amides and heterocycles have also demonstrated incredible selectivity and potency for certain MMPs. For example, pyrimidinetrione-based inhibitors were capable of achieving 100-fold potency for MMP-13 over MMP-14, and the introduction of oxazole terminal groups gave IC50 values ranging from 1.7 to 3.4 nM (Reiter et al., 2006).

Additionally, while much effort has gone into improving zinc binding MMP-inhibitors, some studies have demonstrated potential efficacy of groups that lack a zinc binding group. These classes of molecules demonstrate higher selectivity for certain MMPs as they target MMP-specific features besides zinc.

High-throughput screening, a technique of evaluating millions of potential compounds in assays through robotics, has helped to determine which compounds may work best at specific inhibition (Macarron et al., 2011).

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Two carboxylic acid compounds have been discovered that achieve IC50 values of 32 nM and 0.67 nM for MMP-13, with no inhibition of other MMPs or adamlysins at concentrations up to 100 micromolar (Johnson et al., 2007).

Similarly, through high-throughput screening and computer aided drug design, Li et al. were able to design pyrido[3,4-d]pyrimidin-4ones that were capable of inhibiting MMP-13 in rabbits to relieve osteoarthritis. The group successfully targeted the S1’ pocket of MMP-13, a part of the MMPs that determines the binding affinities for many substrates and inhibitors but varies significantly between enzymes in amino acid length (Li et al., 2008; Vanderbroucke et al., 2014). With this specificity, the group found that even high doses (10 mg/kg per day) did not cause fibroplasias in mice when compared to a non-specific inhibitor (Li et al., 2008).

Finally, more recent attempts to generate specificity have focused on the identification and testing of antibody-based inhibitors.

Unlike synthetic inhibitors, inhibitors based on monoclonal antibodies are capable of limiting certain functions of MMPs while allowing others to continue – especially for the membrane bound type MMPs. For instance, Ingvarsen et al. reported that a monoclonal antibody generated from a recombinant murine MT1-MMP protein was capable of completely inhibiting its ability to activate proMMP-2. However, it had only minimal impacts on the collagenolytic functions of the enzyme (Ingvarsen et al., 2013). Similarly, Sela-passwell et al. generated antibodies that mimic the function of the TIMPs, an endogenous class of MMP regulators. Through mice immunization with a tris-imidazole zinc complex that served as a “mimic” of MMPs, the group generated antibodies that selectively targeted the catalytic domain of MMP-9 and helped to attenuate the severity of inflammatory bowel disease in mice (Sela-Passwell et al., 2011).

"Researchers have developed new functional groups that more effectively bind zinc than the initial class of inhibitors. One particular class of compounds that has shown great promise is phosphorus-based inhibitors."

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Conclusion

61–68. https://doi.org/10.1016/j.semcdb.2007.06.006

The development of MMP inhibitors represents an important potential step in treating a wide variety of inflammatory diseases and cancers.

Though their role in the proteolytic web is complex, MMPs have been demonstrated to have significant roles in the propagation and severity of a wide variety of diseases.

Furthermore, although the initial class of MMP inhibitors failed due to their lack of specificity, new developments in synthetic and natural inhibitors represent a promising new front for effectively treating inflammatory diseases and cancers.

Gialeli, C., Theocharis, A. D., & Karamanos, N. K. (2011). Roles of matrix metalloproteinases in cancer progression and their pharmacological targeting. The FEBS Journal, 278(1), 16–27. https://doi.org/10.1111/j.1742-4658.2010.07919.x

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Journal of Computer-Aided Molecular Design, 17(9), 551–565. https://doi.org/10.1023/B:JCAM.0000005765.13637.38 Nagase, H., Visse, R., & Murphy, G. (2006). Structure and function of matrix metalloproteinases and TIMPs. Cardiovascular Research, 69(3), 562–573. https://doi. org/10.1016/j.cardiores.2005.12.002 O’Reilly, M. S., Wiederschain, D., Stetler-Stevenson, W. G., Folkman, J., & Moses, M. A. (1999). Regulation of angiostatin production by matrix metalloproteinase-2 in a model of concomitant resistance. The Journal of Biological Chemistry, 274(41), 29568–29571. https://doi.org/10.1074/ jbc.274.41.29568 Peterson, J. T. (2006). The importance of estimating the therapeutic index in the development of matrix metalloproteinase inhibitors. Cardiovascular Research, 69(3), 677–687. https://doi.org/10.1016/j.cardiores.2005.11.032 Ponomarenko, E. A., Poverennaya, E. V., Ilgisonis, E. V., Pyatnitskiy, M. A., Kopylov, A. T., Zgoda, V. G., Lisitsa, A. V., & Archakov, A. I. (2016). The Size of the Human Proteome: The Width and Depth. International Journal of Analytical Chemistry, 2016. https://doi.org/10.1155/2016/7436849 Rasmussen, H. S., & McCann, P. P. (1997). Matrix Metalloproteinase Inhibition as a Novel Anticancer Strategy: A Review with Special Focus on Batimastat and Marimastat.

Pharmacology & Therapeutics, 75(1), 69–75. https://doi. org/10.1016/S0163-7258(97)00023-5 Reiter, L. A., Freeman-Cook, K. D., Jones, C. S., Martinelli, G. J., Antipas, A. S., Berliner, M. A., Datta, K., Downs, J. T., Eskra, J. D., Forman, M. D., Greer, E. M., Guzman, R., Hardink, J. R., Janat, F., Keene, N. F., Laird, E. R., Liras, J. L., Lopresti-Morrow, L. L., Mitchell, P. G., … Yocum, S. A. (2006). Potent, selective pyrimidinetrione-based inhibitors of MMP-13. Bioorganic & Medicinal Chemistry Letters, 16(22), 5822–5826. https://doi. org/10.1016/j.bmcl.2006.08.066 Reunanen, N., & Kähäri, V. (2013). Matrix Metalloproteinases in Cancer Cell Invasion. Landes Bioscience. https://www.ncbi. nlm.nih.gov/books/NBK6598/

and biological roles identified by murine models and proteomics. Biochimica et Biophysica Acta (BBA) - Molecular Cell Research, 1803(1), 39–54. https://doi.org/10.1016/j. bbamcr.2009.09.015 Sela-Passwell, N., Kikkeri, R., Dym, O., Rozenberg, H., Margalit, R., Arad-Yellin, R., Eisenstein, M., Brenner, O., Shoham, T., Danon, T., Shanzer, A., & Sagi, I. (2012). Antibodies targeting the catalytic zinc complex of activated matrix metalloproteinases show therapeutic potential. Nature Medicine, 18(1), 143–147. https://doi.org/10.1038/nm.2582 Shima, I., Sasaguri, Y., Kusukawa, J., Yamana, H., Fujita, H., Kakegawa, T., & Morimatsu, M. (1992). Production of matrix metalloproteinase-2 and metalloproteinase-3 related to malignant behavior of esophageal carcinoma. A clinicopathologic study. Cancer, 70(12), 2747–2753. https:// doi.org/10.1002/1097-0142(19921215)70:12<2747::aidcncr2820701204>3.0.co;2-5 Steinman, D. H., Curtin, M. L., Garland, R. B., Davidsen, S. K., Heyman, H. R., Holms, J. H., Albert, D. H., Magoc, T. J., Nagy, I. B., Marcotte, P. A., Li, J., Morgan, D. W., Hutchins, C., & Summers, J. B. (1998). The design, synthesis, and structure-activity relationships of a series of macrocyclic MMP inhibitors.

Bioorganic & Medicinal Chemistry Letters, 8(16), 2087–2092. https://doi.org/10.1016/S0960-894X(98)00396-5 Thurlow, L. R., Thomas, V. C., Narayanan, S., Olson, S., Fleming, S. D., & Hancock, L. E. (2010). Gelatinase Contributes to the Pathogenesis of Endocarditis Caused by Enterococcus faecalis. Infection and Immunity, 78(11), 4936–4943. https:// doi.org/10.1128/IAI.01118-09 Vandenbroucke, R. E., & Libert, C. (2014). Is there new hope for therapeutic matrix metalloproteinase inhibition? Nature Reviews Drug Discovery, 13(12), 904–927. https://doi. org/10.1038/nrd4390 Verma, R. P., & Hansch, C. (2007). Matrix metalloproteinases (MMPs): Chemical–biological functions and (Q)SARs. Bioorganic & Medicinal Chemistry, 15(6), 2223–2268. https:// doi.org/10.1016/j.bmc.2007.01.011 Whittaker, M., Floyd, C. D., Brown, P., & Gearing, A. J. H. (1999). Design and Therapeutic Application of Matrix Metalloproteinase Inhibitors. Chemical Reviews, 99(9), 2735–2776. https://doi.org/10.1021/cr9804543 Wojtowicz-Praga, S., Torri, J., Johnson, M., Steen, V., Marshall, J., Ness, E., Dickson, R., Sale, M., Rasmussen, H. S., Chiodo, T. A., & Hawkins, M. J. (1998). Phase I trial of Marimastat, a novel matrix metalloproteinase inhibitor, administered orally to patients with advanced lung cancer. Journal of Clinical Oncology, 16(6), 2150–2156. https://doi.org/10.1200/ JCO.1998.16.6.2150 Zucker, S., Cao, J., & Chen, W.-T. (2000). Critical appraisal of the use of matrix metalloproteinase inhibitors in cancer treatment. Oncogene, 19(56), 6642–6650. https://doi. org/10.1038/sj.onc.1204097

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Impact of COVID-19 on Immunosuppressed Solid Organ Transplant Recipients

BY ANUPAM SHARMA ’22 Cover Image: A doctor in Italy taking a brief moment of rest during the height of the coronavirus pandemic in 2020.

Source: Giuliano, A. (Wikimedia Commons)

Introduction The global COVID-19 pandemic has brought more than 34 million cases and resulted in more than a million deaths as of September 2020 (Jankowicz 2020). Over a span of six months, the scientific community has scrambled to understand exactly how the SARS-CoV-2 affects the human body and how it elicits an immune response. Solid Organ Transplant (SOT) recipients are particularly vulnerable to contracting COVID-19 due to their immunocompromised state and proper treatment presents a complex challenge for scientists and doctors alike.

Overview of the Immune System Our immune system is a complex collection of proteins, cells, and organs that defend against germs and other foreign substances, which are collectively referred to as “pathogens” or “antigens.” The immune system is broadly 40

divided into two parts, the innate immune system and the adaptive immune system. The innate immune system is widely regarded as the first line of defense, a “non-specific” mechanism named because it responds the same regardless the foreign substance (Nicholson 2016).

Contrary to the innate immune system, the adaptive immune system consists of cells and proteins each tailored to combat a specific germ or classification of germs. Because of this specificity, the adaptive immune system is slower than the innate system and acts as the secondary line of defense. The most wellknown and primary elements of the adaptive immune system are T cells and antibodies.

Produced in the bone marrow, T cells are responsible for recruiting other immune elements to and identify and kill infected cells.

The recruitment cells are known as “helper T cells” and the cytotoxic cells are known as “killer T cells.” A small portion of T cells are known DARTMOUTH UNDERGRADUATE JOURNAL OF SCIENCE

Figure 1: A flowchart depicting the parts of the Immune System.

Note: I created this flowchart Source: Created by Author

as “Memory T Cells” because they retain their ability to recognize particular pathogens and elicit a rapid adaptive immune response to the same pathogen in the future (Tanel et al. 2020).

White blood cells, also known as “leukocytes,'' are the cells generally associated with being immune system cells. These include both the T cells of the adaptive immune system and a group of non-specific innate immune system cells known as “granulocytes.” Antibodies are proteins that attach to particular pathogens using a type of lock and key mechanism. By binding to particular pathogens, antibodies can either render them inactive and act as markers for macrophages which would then “eat” the pathogens or trigger their destruction by bringing in other immune system elements (MBL International 2020). In the relation between COVID-19 and SOT, the functioning of the adaptive immune system is crucial to fighting off pathogens like COVID-19 but poses a major challenge to ensure the survival of SOT recipients (Chaplin 2010).

Overview of Organ Transplantation Immunology In 2019, over 39,700 people in the United States suffering from organ failure - either as a consequence of a genetic condition, chronic illness, or acute infection - received organ transplants (UNOS 2019). While successful organ transplant procedures offer recipients and their families a new lease on life, it comes with a number of fundamental lifestyle changes. First and foremost is drug-induced immunosuppression. All cells specific to an FALL 2020

individual contain a group of surface receptors known as Human Leukocyte Antigens (HLAs) which are recognized as innate by the immune system. Since neither a virus nor a donated organ originated within the body, they would not possess the appropriate HLAs and would therefore be treated as foreign objects (Delves 2020). As such, a new organ in a body will elicit a response from both the innate and adaptive parts of the immune system against the transplant, referred to as “rejection.” Rejection can happen at either or both of two scenarios: immediately after the transplant operation occurs, known as “acute graft rejection,” and one to three years after the transplant, known as “chronic graft rejection.” As such, medications are prescribed to SOT recipients to suppress the immune system and the likelihood of rejection.

Today, a combination of Tacrolimus (TAC) and Mycophenolate mofetil (MMF) has been found to be the most effective treatment to maintain long-term immunosuppression. Tacrolimus binds to an FK Binding Protein, and, together, the TAC-FK Binding Protein complex inhibits the transcription of T cell genes. As a result, fewer helper T cells are produced to identify antigens, and cytotoxic T cells are essentially entirely inhibited, reducing the frequency of rejection. Mycophenolate Mofetil, on the other hand, inhibits the synthesis of purines, particularly guanosine, in lymphocytes.

Guanosine is one of the four chemical building blocks of DNA and by inhibiting its synthesis, MMF “suppresses both cell-mediated immune responses and antibody formation” (Dalal et al., 2020). Additionally, Mycophenolate Mofetil interferes with the attachment of leukocytes

"In 2019, over 39,700 people in the United States suffering from organ failure - either as a consequence of a genetic condition, chronic illness, or acute infection - received organ transplants."

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Figure 2: A 3D Model of the coronavirus.

Source: Wikimedia commons

"Research has shown that the virus has a protein on its surface called the Spike (S) protein that can latch onto cells with the appropriate receptor on the cell membrane (Li et al, 2020). In this case, the novel coronavirus uses its Spike protein to recognize and attach onto cells with angiotensinconverting enzyme 2 (ACE2) receptors."

to cells that form the lining of blood vessels (endothelial cells) and inhibits the recruitment of lymphocytes to sites of inflammation (Dalal et al, 2020). So, while Tacrolimus reduces T cell generation, Mycophenolate Mofetil inhibits guanosine synthesis and prevents the recruitment of leukocytes to endothelial cells. As such, combination TacrolimusMycophenolate Mofetil therapies are very powerful immunosuppressants, significantly reducing the risk of both acute and chronic solid organ graft rejections by inhibiting different elements of the immune system. The downside, however, is that because SOT patients are taking drugs to suppress their immune system, they are at a disproportionately high risk for contracting infections more frequently. When infected, these recipients have a higher likelihood to contract other severe diseases. Unsurprisingly, physicians and scientists are concerned with SOT recipientsâ&#x20AC;&#x2122; contractability and ability to recover from COVID-19.

COVID-19 and Immune System With the world roughly six months into the coronavirus pandemic, scientists are still scrambling to fully understand the manner in which the Sars-CoV-2 virus infects the human body and how the body elicits an immune response. Research has shown that the virus has a protein on its surface called the Spike (S) protein that can latch onto cells with the appropriate receptor on the cell membrane (Li et al, 2020). In this case, the novel coronavirus uses its Spike protein to recognize and attach onto cells with angiotensin-converting enzyme 2 (ACE2) receptors. When inhaled, the virus latches onto ACE2 receptors in epithelial cells that line

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the respiratory passageways leading to the lungs (Cevik et al, 2020).

A major focus for COVID-19 research is understanding how and why different people have varied immune responses to COVID-19.

Understanding the differences in immune responses among people who have only a mild progression of symptoms versus those who have severe cases of COVID-19 is crucial for the development of treatment options to stop disease progression in patients.

Published in Nature, Lucas et al. of the Yale School of Medicine followed 113 hospitalized patients who had either a moderate or severe disease over a period of 51 days. The authors analyzed immune system proteins and other molecules in the blood, in addition to T and B lymphocytes. All 113 COVID-19 patients in the study had lymphopenia, a condition in which patients have decreased levels T cells. Lucas et al. found that levels of inflammation-promoting molecules, called cytokines, increased in all COVID-19 patients relative to healthy, nonCOVID-19-infected controls. This immediate increase of inflammation-promoting molecules is referred to as a â&#x20AC;&#x153;cytokine storm.â&#x20AC;? Furthermore, these scientists found that patients with more severe cases had elevated cytokine levels for a longer period than patients with moderate cases of COVID-19.

Most interestingly, patients with COVID-19 have elevated levels of cytokines associated with immune responses to parasites and allergens (Lucas et al, 2020).

As a result of the study, Lucas et al. concluded that a dysregulated immune response is characteristic of patients with more severe courses of COVID-19.

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York City stressed the importance of efficient and accurate testing as it is likely that many SOT patients are COVID-19 positive without showing the usual initial symptoms (Pereira et al, 2020). In any case, doctors must be ever vigilant when any SOT recipient comes into the ER. It is when such patients subsequently test positive for COVID-19 that the real battle begins.

Figure 3: A photo of a doctor weilding a vaccine.

Source: Wikimedia Commons

Treatment of COVID Positive Immunosuppressed Patients

Clinical Presentation of Immunosuppressed COVID Patients Due to the dysfunctional immune response found in COVID-19 patients, doctors are understandably concerned about patients with suppressed immune system capabilities contracting COVID-19. Presently, there are no universally recognized treatment guidelines pertaining to the management of SOT recipients who contract the virus. A primary concern that doctors have is identifying the initial symptoms that immunosuppressed patients have when they contract COVID-19.

Non-immunosuppressed patients who contract COVID-19 usually first show signs of respiratory symptoms (shortness of breath, cough, etc.), fever, and cough. This is not always the case with immunosuppressed patients. A case study coming out of the Hospital Clinic Barcelona in Spain conducted by Guillen et al. details the experience of a 50-year-old kidney transplant recipient who was admitted to the Emergency Room (ER) with fever and vomiting, but no other symptoms (Guillen et al, 2020). He received a presumptive diagnosis of gastroenteritis and was discharged from the hospital. Four days later, however, the man returned with a “persistent fever, but at this time, with a productive cough and, upon further testing, mild kidney impairment” (Pereira et al, 2020).

The patient was then administered a realtime reverse-transcriptase Polymerase Chain Reaction (rRT-PCR) test for COVID-19, which came back positive. Other SOT patients who contracted COVID-19 also had atypical initial presentations, including symptoms of fatigue, vomiting and diarrhea. Although limited research has been conducted in this area, early studies suggest that immunosuppressed SOT patients who contract COVID-19 can present with atypical symptoms. One study from New

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The novel coronavirus can wreak havoc on the immune system of healthy people, and immunosuppressed SOT recipients are already at a disadvantage before even contracting the virus. When they do test positive for COVID-19, healthcare workers have the challenge of administering and controlling medications such that the patients’ immune responses are quick and effective enough to fight off the virus without also attacking the transplanted organ.

To reiterate, there are no treatment guidelines for SOT recipients, so physicians must rely almost entirely on clinical intuition. It should be noted, however, that some SOT patients, though very few, can contract COVID-19 and be asymptomatic. One case study out of Turkey details a clinical encounter with a middle-aged kidney transplant recipient who had tested positive for COVID-19, but did not report any symptoms characteristic of the disease. In this particular case, Turkish physicians opted to reduce immunosuppressive medications in the same way if the patient had been symptomatic (Velioglu and Tuglular, 2020). In contrast, a European working group of renal transplant experts, epidemiologists, and other physicians, known as the DESCARTES Group, recommends continuing prescribed immunosuppressants (Maggiore et al, 2020). This difference in treatment approach simply demonstrates how much there remains to understand about COVID-19 and how to treat immunosuppressed patients, let alone asymptomatic ones.

"SOT recipients are already at a disadvantage before even contracting the virus. When they do test positive for COVID-19, healthcare workers have the challenge of administering and controlling medications such that the patients’ immune responses are quick and effective enough to fight off the virus without also attacking the transplanted organ."

For the majority of cases, a delicate balance is struck between encouraging an immune response to fight off the virus and limiting immune response as to not elicit rejection. One case study came from a group of physicians working in different hospitals in New York City at the height of the coronavirus outbreak in late March 2020. In treatment plans for ninety patients, physicians usually began by administering hydroxychloroquine, an arthritis medication that has not been explicitly approved for the treatment of COVID-19 by the

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FDA but which does seem to possess certain “anti-virus and anti-inflammation effects” (Li et al, 2020). Patients who were experiencing a cytokine storm were also given antibiotics such as azithromycin. Importantly, physicians made the decision to moderately reduce levels of immunosuppressive medications, particularly Mycophenolate Mofetil, which normally suppresses the synthesis of cytotoxic T cells (Pereira et al, 2020). By stopping or reducing a drug that normally inhibits T cell synthesis, physicians are managing medications to upregulate the patient’s immune system to fight the virus. Given that immunosuppressive therapy is the main technique for preventing chronic organ transplant rejection, however, the healthcare team is taking a considerable risk in decreasing immunosuppressant administration.

In terms of patient outcomes, sixteen of sixtyeight hospitalized patients (18%) died while thirty-seven (41%) were successfully discharged from the New York City study. For context, the “hospitalized cohort had higher rates of severe disease…and mortality [when compared to non-transplant patients with COVID-19]” (Pereira et al, 2020).

"One of the reasons why so many are in development is because certain vaccines may not be appropriate for immunosuppressed and other niche populations, so alternative ones must be developed."

Whereas the doctors in New York City decided to slightly limit immunosuppressants, a group of physicians in London, reduced doses of the T-cellinhibiting Tacrolimus and ceased administration of Mycophenolate Mofetil (Banerjee et al, 2020). One patient out of the (admittedly small) seven patient sample died in the study out of London (Banerjee et al, 2020). These different approaches to immunosuppression management demonstrate the uncertain nature of immunosuppression management during the pandemic. The clinical outcomes of these two studies are indicative of the fact that immunosuppressed SOT patients are far more susceptible to suffering from a severe disease and dying, making the development of proper treatment techniques all the more critical.

Conclusion and Implications for Vaccine Development Immunosuppressed SOT recipients are at great risk during the coronavirus pandemic. With few studies conducted and virtually no universal treatment guidelines, those who test positive for COVID-19 pose a complex challenge to physicians working to strike a delicate balance between mobilizing the immune system to combat the virus without rejecting the transplanted organ.

One of the most important steps to making this population safer is the rapid development and administration of a vaccine. Vaccines are

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generally used to train the immune system to fight off a particular virus or pathogen.

According to the World Health Organization, there are currently 42 COVID-19 vaccine candidates currently under development as of October 6, 2020 (World Health Organization).

One of the reasons why so many are in development is because certain vaccines may not be appropriate for immunosuppressed and other niche populations, so alternative ones must be developed. In a time when hospitals live in perpetual uncertainty, a vaccine for COVID-19 holds promise of a healthier future.

References Banerjee, D., Popoola, J., Shah, S., Ster, I., Quan, V., & Phanish, M. (n.d.). COVID-19 infection in kidney transplant recipients.

97(6), 1076–1082. https://doi.org/10.1016/j.kint.2020.03.018 Cevik, M., Bamford, C. G. G., & Ho, A. (2020). COVID-19 pandemic—A focused review for clinicians. Clinical Microbiology and Infection, 26(7), 842–847. https://doi. org/10.1016/j.cmi.2020.04.023 Chaplin, D. (2010). Overview of the Immune Response.

Journal of Allergy and Clinical Immunology, 125(2), S3–S23. https://doi.org/10.1016/j.jaci.2009.12.980 Dalal, P., Shah, G., Chhabra, D., & Gallon, L. (2010). Role of tacrolimus combination therapy with mycophenolate mofetil in the prevention of organ rejection in kidney transplant patients. International Journal of Nephrology and Renovascular Disease, 3, 107–115. https://doi.org/10.2147/ ijnrd.s7044 Delves, P. (Apr 2020). Overview of The Immune System. Merck Manual Consumer Version. https://www.merckmanuals.com/ home/immune-disorders/biology-of-the-immune-system/ overview-of-the-immune-system#:~:text=Human%20 leukocyte%20antigens%20(HLA)%20are,called%20the%20 major%20histocompatibility%20complex.

Guillen, E., Pineiro, G., Revuelta, I., Rodriguez, D., Bodro, M., Moreno, A., Campistol, J., & Diekmann, F. (2020). Case report of COVID‐19 in a kidney transplant recipient: Does immunosuppression alter the clinical presentation? American Journal of Transplantation, 20(7), 1875–1878. https://doi. org/10.1111/ajt.15874 Jankowicz, M. (2020, September 18). All-time coronavirus cases have surpassed 30 million, doubling in the past 2 months. Business Insider. businessinsider.com/ global-coronavirus-cases-pass-30-million-doubling-2months-2020-9 Li, H., Liu, S.-M., Yu, X.-H., Tang, S.-L., & Tang, C.-K. (n.d.).

Coronavirus disease 2019 (COVID-19): Current status and future perspectives.

Li, X., Wang, Y., Agostinis, P., Rabson, A., Melino, G., Carafoli, E., Shi, Y., & Sun, E. (2020). Is hydroxychloroquine beneficial for COVID-19 patients? Cell Death & Disease, 11.

Lucas, C., Wong, P., & Klein, J. (2020). Longitudinal analyses reveal immunological misfiring in severe COVID-19. Nature, 584, 463–469. https://doi.org/doi.org/10.1038/s41586-0202588-y

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Maggiore, U., Abramowicz, D., Crespo, M., Mariat, C., Mjoen, G., Peruzzi, L., Sever, M., Oniscu, G., & Hilbrands, L. (2020). How should I manage immunosuppression in a kidney transplant patient with COVID-19? An ERA-EDTA DESCARTES expert opinion. Nephrology Dialysis Transplantation, 35(6), 899–904. https://doi.org/10.1093/ndt/gfaa130 MBL International Corporation. (2016). The role of Antibodies. https://www.mblintl.com/products/role-antibodiesmbli/#:~:text=1)%20Antibodies%20are%20secreted%20 into,holes%20in%20the%20cell%20wall).

Nicholson, L. (2020). The immune system. Essays in Biochemistry, 60(3), 275–301. https://doi.org/10.1042/ EBC20160017 Pereira, M., Mohan, S., Cohen, D., Husain, S., Dube, G., Ratner, L., Arcasoy, S., Aversa, M., Benvenuto, L., Dadhania, D., Kapur, S., Dove, L., Brown Jr., R., Rosenblatt, R., Samstein, B., Uriel, N., Farr, M., Satlin, M., Small, C., … Verna, E. (2020). COVID‐19 in solid organ transplant recipients: Initial report from the US epicenter. American Journal of Transplantation, 20(7), 1800–1808. https://doi.org/10.1111/ajt.15941 Tanel, A., Fonseca, S., Yassine-Diab, B., Bordi, R., Zeidan, J., Shi, Y., Benne, C., & Sekaly, R.-P. (2014). Cellular and molecular mechanisms of memory T-cell survival.

Expert Review of Vaccines, 8(3), 299–312. https://doi. org/10.1586/14760584.8.3.299 UNOS. (n.d.). Organ donation again sets record in 2019 [UNOS.org]. Retrieved October 16, 2020, from https://unos.org/news/organ-donation-sets-record-in2019/#:~:text=Organ%20transplants%20from%20living%20 donors,both%20deceased%20and%20living%20donors.

Velioglu, A., & Tuglular, S. (2020). Care of asymptomatic SARS‐CoV‐2 positive kidney transplant recipients. Transplant International, 33(10), 1331–1332. https://doi.org/10.1111/ tri.13691 World Health Organization. (2020, October 6). What we know about COVID-19 vaccine development. https://www.who. int/docs/default-source/coronaviruse/risk-comms-updates/ update37-vaccine-development.pdf?sfvrsn=2581e994_6

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Behavioral and Neural Evidence for Number Sense in Nonhuman Mammals

BY ASHLYN MORRIS ’21 Cover Image: Increasing evidence suggests that chimpanzees are capable of counting, learning Arabic symbols corresponding to numerosities, and even performing basic math.

Source: Wikimedia Commons

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Introduction In the early 20th century, a horse in Berlin drew world-wide attention due to reports that it possessed an ability to count and perform arithmetic operations (Samhita & Gross, 2013).

Nicknamed “Clever Hans” for these impressive displays of mathematical ability, the horse appeared to demonstrate an ability to identify the date and to spell as well. Although many believed that these apparent capabilities were merely the result of extensive training between Hans and its owner, Wilhelm von Osten, the horse later proved to be able to solve similar types of puzzles presented by complete strangers. It was not until Oskar Pfungst performed a detailed investigation that people realized that the horse was actually carefully watching the reactions of observers and using their facial expressions and body language to know what the correct answers to questions were. Pfungst’s theory was confirmed when people realized that Hans was not able to

correctly answer a question for which the asker also did not know the right answer.

Although Hans’s ability to read the body language and facial expressions of humans was an impressive skill in its own right, the disproving of the horse’s mathematical abilities cast a shadow of doubt on any experiments purporting to show that animals are capable of numerical abilities, or other forms of complex thought, for the decades to come. However, more recent evidence from rigorous experiments supports the idea that many nonhuman animals, or at the very least mammals, actually do have number sense, or an ability to quickly understand, approximate, and manipulate numerical quantities (Dehaene, 2001). This article will first review the evidence that nonhuman mammals possess an abstract number concept. The next section will explore the results of behavioral studies indicating that there are two different systems with which DARTMOUTH UNDERGRADUATE JOURNAL OF SCIENCE

numbers are represented within animal minds.

Then, the focus will be on the neural basis of numerical abilities in mammals, including the discovery of number-sensitive neurons in the parietal lobe of the brain. Finally, this article will conclude with a brief discussion on the similarities and differences between human and nonhuman mammal numerical abilities.

Mammals have an abstract number concept In the scientific community, in order to prove that a nonhuman animal has an abstract concept of number, two criteria must be met (Brannon, 2005). First, the animal must be shown capable of discriminating between stimuli based on the number of objects depicted alone; to do so, researchers must ensure that the animal is actually attending to number and not to any of the other features of a stimulus that typically covary with number.

Some examples of continuous features that typically covary with the numerosity of stimuli are size, density, surface area, perimeter, and volume. Second, to prove the existence of a number concept in the animal, it must show an ability to transfer learned numerical rules to new types of stimuli. This is to ensure that it has a true concept in mind and is not simply relying on associative learning to solve a given task.

Researchers have already shown that mammals are able to discriminate between stimuli based on numerosity alone (Jordan & Brannon, 2006).

To do so, Jordan and Brannonâ&#x20AC;&#x2122;s team trained three rhesus macaques on a standard delayed match-to-sample paradigm. Monkeys were shown a sample stimulus on a screen that contained either two or eight dots within a yellow rectangle. After the monkeys touched the screen, two choice stimuli were shown.

If the monkey selected the choice stimuli containing the same number of dots as the sample stimulus, then the animal would receive a juice reward. At first, the sample stimulus was always identical to the choice stimulus. In subsequent sets of trials, additional controls were placed on the sample and choice stimuli to assess whether or not the monkeys were truly attending to the number of dots present.

To rule out the possibility that the animals were attending to the color or arrangement of the dots to solve the matching task, it was then manipulated to determine if the animals were capable of matching stimuli with the same number of dots that were of different colors and that were placed in a different configuration on the screen. To ensure the monkeys were not attending to the surface area of the dots FALL 2020

to make their matches, the animals were also tasked with matching stimuli containing the same number of dots that were of different sizes. Finally, to rule out the possibility that the monkeys were making matches based on the density of the dots on the screen, the monkeys were tasked with matching stimuli containing the same number of dots in yellow rectangles of different sizes.

All three monkeys tested were shown capable of using numbers and not relying on continuous variables that typically covary with numbers to solve the matching puzzles.

As the experimenters introduced controls for each continuous variable one-by-one, the accuracy of the monkeys on the puzzles still remained high. Notably, after being trained in the original condition in which the sample stimulus and choice stimulus were identical and no controls were implemented, all monkeys were able to immediately perform significantly above chance levels as each new control was implemented. Jordan and Brannon argue that this is evidence that the monkeys were attending to the numerosity present in the stimuli from the very first trials and were not resorting to using numerosity as a last resort once they realized that their old strategies werenâ&#x20AC;&#x2122;t working. These results stand in stark contrast to the opposing argument that animals may be capable of discriminating based on number but only do so as a last resort (Davis & Memmott, 1982).

"In the scientific community, in order to prove that a nonhuman animal has an abstract concept of number, two criteria must be met [...]"

Other researchers provided further evidence that monkeys possess an abstract number concept (Brannon & Terrace, 1998). In their experiment, two rhesus macaques were trained to tap exemplars of the numerosities one to four in ascending order. In other words, they would tap the stimulus with one shape, then the stimulus containing two shapes, next the stimulus containing three shapes, and finally the stimulus containing four shapes.

The monkeys proved capable of learning to tap the stimuli in ascending order by numerosity.

Notably, the experimenters varied the size, color, arrangement, shape, and surface area of the objects that made up each of the stimuli such that the only way to successfully solve the task consistently would be to attend to the number of objects present in each stimulus.

The monkeys were first trained on seven sets of stimuli to which each monkey was repeatedly exposed and for which correct answers were reinforced. Following this training period, to ensure that the monkeys were not solving the puzzles by route memorization and had instead learned an ordinal rule, the monkeys were 47

Figure 1: An example of a display representing the numerosity four. Brannon and Terrace showed that monkeys were capable of tapping displays representing the numerosities one to four in ascending order.

then given 150 test sets of stimuli to which they were only exposed and tested on once. Results showing that monkeys were able to complete the task on novel sample sets provided strong evidence that they were holding a number rule in mind and using it to solve problems.

Source: Wikimedia Commons

"Overall, a rich body of experimental evidence supports the idea that nonhuman mammals possess an abstract number concept."

After completing reinforced trials testing their ability to order the numbers one through four, the same monkeys were tested on their ability to order the numbers one through nine without any additional training. In this new paradigm, they were shown two screens, each displaying a representation of a number between one and nine, and were tasked with tapping the screens in ascending numerical order. The monkeys were tasked with solving three types of trials: familiar-familiar pairs, which could contain representations of the numbers one through four to which the monkeys had prior training, familiar-novel pairs, which contained one number to which the monkeys had prior training and one novel number, and novelnovel pairs, which contained representations of two numbers with which the monkeys had no prior training. The monkeys were reinforced on familiar-familiar pairs, but received no reinforcement on familiar-novel or novel-novel trials. Both monkeys displayed high rates of accuracy, 92% and 94%, on familiar-familiar trials. Incredibly, after being trained on only the order of the numerosities one through four, the monkeys displayed high rates of accuracy on the unreinforced familiar-novel and novel-novel trials. Both monkeys displayed an accuracy rate of 93% on familiar-novel trials, and the monkeys still showed relatively high accuracy rates, 73% and 75%, on novel-novel trials. The results of both of Brannon and Terraceâ&#x20AC;&#x2122;s 1998 experiments provide strong evidence in favour of Brannonâ&#x20AC;&#x2122;s second criteria for animals possessing an abstract number concept: an ability to transfer number rules to novel types of stimuli (Brannon, 2005).

Further evidence supports the ability of mammals to transfer a number rule to novel stimuli types (Church & Meck, 1984). In their key experiment, rats were trained to press a righthand lever when presented with two sounds and a left-hand lever when presented with four sounds. The tones were then replaced with flashes of light, and half of the rats were given the same contingency as their training, while the other half were tasked with now pressing a right-hand lever for four light flashes and the left-hand lever for two light flashes. Notably, the rats in this reversal condition took much longer

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to learn these new pairings when compared with the other group, suggesting that the rats were holding a number rule in mind and had to relearn it. This experiment produced some of the first results supporting cross-modal number representation within nonhuman mammals.

Additional experiments by Church and Meck have indicated that rats can sum stimuli across modalities to decide which lever they should push (Brannon, 2005). For example, after being trained to press a right lever for either two tones or light flashes and a left lever for four tones or light flashes, a given test rat would then be presented with a trial consisting of a combination of tones and light flashes. For example, on one trial, a rat could be presented with the combination of two flashes of light and two tones. The tones and light flashes were presented simultaneously to rule out the possibility that the rats were using the time it took to deliver a stimulus to make their decision of which lever to push. Interestingly, the rats would then press the left lever for four stimuli, suggesting that they were summating the stimuli across modalities to select which lever they would push.

Overall, a rich body of experimental evidence supports the idea that nonhuman mammals possess an abstract number concept. Carefully designed experiments have shown that mammals attend to the numerosity of stimuli in lieu of continuous variables that typically covary with number. Further, mammals can transfer number rules to novel stimuli and across modalities. Given these findings, the next key step in understanding number sense in nonhuman mammals involves understanding the ways in which they hold a representation of number within their mind.

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Figure 2: To avoid confounds associated with over-training in their experiments, Hauser and his colleagues sought out rhesus macaques in their natural environment and only tested each animal once.

Source: Wikimedia Commons

Two systems for numerical representation Although it is a commonly held belief that humans represent numbers as discrete elements, a large body of experimental evidence suggests that humans and nonhuman animals alike most often represent numbers as rough mental magnitudes and not discrete elements. This system for representing numbers is termed the analog-magnitude system (Feigenson et al., 2002). Some of the first evidence supporting the idea that nonhuman mammals represent numbers via rough magnitudes comes from Francis Mechner’s thesis research (Mechner, 1958).

Mechner trained rats to press a lever, Lever A, a specific numbers of times, n, for a water reward; over the course of the study, each rat was trained to press the lever four, eight, twelve, and sixteen times. Once the rat pressed Lever A as many times as it wished, it terminated the trial by pressing Lever B and would receive a reward if it pressed Lever A the correct number of times. Sometimes, the rat would not press Lever A exactly n times before pressing Lever B. Instead, the number of responses was normally distributed around n, with the rats much more likely to press Lever A n+1 times than n+5 times before pressing Lever B. Notably, the standard deviation of these normally distributed results increased as n increased, and these results were replicable (Platt & Johnson, 1971). These findings support the idea that rats represent numbers approximately and with scalar variability, or variance that increases linearly with mean value. Findings that mammals represent number with scalar variability are highly reproducible in many different nonhuman mammals and in both developing and adult humans (Platt & Johnson, 1971;

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Jordan & Brannon, 2006; Moyer & Landauer, 1967). Brannon argues that the aggregate of the findings in these experiments suggests that numbers are commonly represented by animals as rough, continuous magnitudes and not discrete entities, much in the same way brightness or weight are represented in human minds (Brannon, 2005).

Although it is widely accepted that many species can represent numbers via the analogmagnitude system, there is increasing evidence that a second system exists that humans and, at the very least, primates can use to more precisely represent small sets of objects. Hauser and his colleagues’ research provided evidence for this second system with rhesus macaques (Hauser et al., 200). Worried about the potential confounds of over-training in experiments that were making claims about the ‘natural numerical abilities’ of animals, Hauser’s team tested their experimental paradigm on over 200 free-ranging monkeys, with efforts to keep the number of trials on any given monkey as close to one as possible. During each trial, experimenters would allow monkeys to watch as they placed a specific number of apple slices into two boxes, before allowing a macaque to approach and eat the reward from one of the boxes. The subjects preferentially approached the box containing the larger quantity of apple slices when the number of slices put in either box was either one, two, or three slices. With the exception of a statistically significant result for discriminating between three and five slices, the monkeys picked between the boxes at chance levels when the number of slices placed into one or both of the boxes exceeded three.

"a large body of experimental evidence suggests that humans and nonhuman animals alike most often represent numbers as rough mental magnitudes and not discrete elements."

If monkeys were using the rough mental 49

Figure 3: An overview of the major external regions of the brain. The intraparietal sulcus is a groove located on the lateral surface of the parietal lobe, while the prefrontal cortex is found at the very anterior portion of the frontal lobe.

Source: Wikimedia Commons

"The existence of a “numerosity detector” at the level of a single neuron was first proposed

by Dehaene and Changeux."

magnitude system to solve this task, Hauser and his colleagues argued that the monkeys would have equal success rates on one versus two apple slices as they would on four versus eight apple slices (Hauser et al., 2000). In fact, other studies have shown that rhesus macaques have the capacity to represent rough magnitudes of much larger than three items (Brannon & Terrace, 1998). Thus, the experimenters argue that, under the conditions of their study, a separate system for representing numbers was being deployed.

Under this second system, termed the objectfile model, an animal is representing “each tobe-enumerated item by a single object file, and there are a limited number of object files” (Brannon, 2005). Thus, deploying this system involves representing each number as a discrete, and not a rough, value; however, the number of object files is limited and so this system can only be used to distinguish exactly between very small numbers.

The underlying conditions necessary for one numerical representation system to be activated over the other are still unclear (Hauser et al., 2000). Further, studies implicating the objectfile model are relatively rare, and so it cannot be said with certainty which mammals may possess this second system for representing numbers.

More recently, though, the focus in experiments attempting to understand how nonhuman mammals represent numbers has shifted from validating abstract theories of how mammals might represent number to more concrete studies attempting to understand the neural basis of number representation.

The neural basis of number sense in mammals The neural basis of numerical processing has been tackled by a number of studies in humans; typically, results of fMRI imaging studies implicate the inferior or superior lobule of the parietal cortex when humans are solving numerical tasks (Brannon, 2005). In comparison, relatively little is known about the neural basis of number sense in nonhuman animals, including mammals. Recently, electrophysiology studies have made progress towards resolving the question and have found evidence for numbersensitive neurons within both the parietal lobe and prefrontal cortex of monkey brains.

The existence of a “numerosity detector” at the level of a single neuron was first proposed by Dehaene and Changeux (Dehaene & Changeux, 1993). According to these scientists, there were likely neurons which were coarsely tuned to

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fire for an approximate quantity. For example, a neuron tuned to the number three would fire preferentially when three objects were displayed or when three tones were produced.

In keeping with the analog-magnitude system for representing numbers, these neurons might at times fire for two flashes of light or for four objects, but would be more likely to fire for two stimuli than one stimulus and would fire at the highest rate for three stimuli.

At the time they proposed their theoretical model, there was already one study providing evidence in support of Dehaene and Changeux’s theory. While recording from the association cortex of a cat, an area that may be homologous to the posterior parietal cortex in monkeys and humans, Thompson’s research team found neurons that “appear to code the property of number” (Thompson et al., 1970). Electrophysiological recordings were taken from this region while a repetitive stimulus was presented to the cat. Five neurons were identified that fired preferentially after a specific number of stimuli had been presented.

The responses of these cells were shown to be independent of stimulus modality, exhibiting the same response for their preferred number when exposed to either visual or auditory stimuli. The intensity of the stimuli and variations in the interstimulus interval were also shown to have little effect on the firing properties of these neurons. Following the results of this experiment, though, a number of decades passed before further evidence of neurons that fired preferentially for a specific number was found.

In 2002, Sawamura and colleagues provided new evidence for the existence of number

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selectivity within select neurons. In their study, monkeys were extensively trained to repetitively perform movement A five times, then movement B five times, then movement A five times again, and so on (Sawamura et al., 2002). During performance of this task, the experimenters recorded neuronal activity from the superior parietal lobule in the left hemisphere of the monkeysâ&#x20AC;&#x2122; brains. Within this region, they found a large number of cells that were active during or before the onset of the nth movement in a set in the monkeys. In other words, some neurons fired preferentially on the second movement in a set, while other neurons fired preferentially on the fifth movement.

Two types of cells that seemed to have some numerical tuning properties were identified.

The first type of neurons were broadly-tuned number-selective cells that fired preferentially for a given value but that would at times also fire for similar values. Interestingly, 46% of the neurons were identified as narrowly-tuned number-selective cells and only ever fired for one specific value. Although a noteworthy study with exciting results, researchers have critiqued it for two key reasons (Piazza & Stanislas, 2015). The first is that, given the task that Sawamuraâ&#x20AC;&#x2122;s team employed, the neurons identified were tuned to the numerical position in a sequence, or ordinal number, and not the true numerical quantity itself, or cardinal number. Second, many of the neurons identified showed significant tuning properties to both number and to a specific action (such as to movement A or movement B). Stronger evidence for number-selective neurons would come from evidence of cells that were tuned to cardinal number and that fired consistently no matter what action or sensory modality was being employed.

Nieder and Miller addressed both of these key concerns in their study involving a delayedmatch-to-sample paradigm (Nieder & Miller, 2003). When recording from the dorsolateral prefrontal cortex while monkeys matched stimuli representing the same number, Nieder and Miller identified neurons that were selective for specific cardinal numbers. Further, the tuning curves of these neurons were shown to be largely unaffected by variations in spatial layout, object size, or density of the stimuli to which they were exposed.

Although this experiment suggested that a large proportion of number-selective neurons are found in the prefrontal cortex when compared to the parietal cortex, further research has

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indicated that these results were obtained due to incomplete samplings of the prefrontal and parietal cortices. More rigorous and complete sampling methods have shown that there are also a large number of number-selective neurons in the parietal cortex, specifically within the intraparietal sulcus, of monkeys (Piazza & Dehaene, 2015). Further, numberselective neurons in the intraparietal sulcus fire at an average latency of 80 milliseconds following their preferred numerical stimulus, while number-selective neurons in the prefrontal cortex fire at an average latency of 120 milliseconds following their preferred number stimulus. When considered together, these findings are consistent with the hypothesis that numerosity is first represented within the intraparietal sulcus following a given stimulus and that the information is then transmitted to the prefrontal cortex where it is integrated with other relevant information for performance on a given task (Brannon, 2005; Piazza & Dehaene, 2015). Additional research is necessary to elucidate specific pathways of numerical information within the brain and to determine whether any additional brain areas are important.

Conclusion: The aggregate of behavioral and neuroscience data suggests that nonhuman mammals do have the capacity for number sense. That being said, there is no question that human numerical abilities, on average, greatly exceed that of nonhuman animals (Brannon, 2005). However, considering that humans undergo years of training in mathematical concepts (including classes on algebra, geometry, and calculus), the demonstrated abilities of nonhuman mammals are still impressive in their own right.

Nonhuman mammals have demonstrated a robust abstract number concept, showing both a capability to represent number independently of any potentially confounding variables and a capability to transfer number rules to novel types of stimuli. Further, humans and a wide array of mammals both make use of the same analog-magnitude system to roughly represent numerical values; humans and, at the very least, primates are capable of representing numbers via the more exact but limited objectfile model as well. Finally, neural recordings have identified number-sensitive cells in the same or homologous brain regions of humans and nonhuman mammal brains.

However, key differences remain between the numerical abilities of humans and other

"The aggregate of behavioral and neuroscience data suggests that nonhuman mammals do have the capacity for number sense.

That being said, there is no question that human numerical abilities, on average, greatly exceed that of nonhuman animals."

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mammals. It is important to point out that the use of symbolic representations of number, whether through Arabic numerals or number words, is a unique human achievement (Nieder & Dehaene, 2009). Further, the use of these numerical symbolic representations has been extremely influential in many of the advances in science and technology that have occurred throughout the history of human civilization.

A handful of animals have been taught the relationships between abstract symbols and numerosities, indicating that animals are not incapable of learning them (Matsuzawa, 1985). For example, a chimpanzee named Ai was able to master symbols corresponding to the numerosities one through six and to use these symbols flexibly to describe many types of stimuli. However, in contrast to humans who become increasingly efficient at learning new symbols corresponding to numerosities over time, Ai did not become more efficient and instead required arduous training to learn each successive symbol. Brannon concluded that these results suggest that “animals do not make the same kind of conceptual leaps and intelligent numerical inferences as do young children” (Brannon, 2005).

Scientists have made great strides towards understanding the behavioral and neurological underpinnings of number sense in nonhuman mammals during the past century.

Although Clever Hans may not have been as mathematically-gifted as scientists had hoped, more rigorous experiments have indicated that number sense is not a unique human ability.

Instead, precursors of human numerical abilities are increasingly being identified throughout the animal kingdom.

Feigenson, L., Carey, S., & Spelke, E. (2002). Infants’ Discrimination of Number vs. Continuous Extent. Cognitive Psychology, 44, 33-66.

Hauser, M. D., Carey, S., & Hauser, L. B. (2000). Spontaneous Number Representation in Semi-Free-Ranging Rhesus Monkeys. Proceedings of the Royal Society B, 267(1445), 829-833.

Jordan, K. E., & Brannon, E. M. (2006). A Common Representation System Governed by Weber’s Law: Nonverbal Numerical Similarity Judgments in 6-Year-Olds and Rhesus Macaques. Journal of Experimental Child Psychology, 95(3), 215-229.

Jordan, K. E., & Brannon, E. M. (2006). Weber’s Law Influences Numerical Representations in Rhesus Macaques (Macaca Mulatta). Animal Cognition, 9, 159-172.

Kilian, A., Yaman, S., von Fersen, L., & Güntürkün. (2003). A Bottlenose Dolphin Discriminates Visual Stimuli Differing in Numerosity. Animal Learning & Behavior, 31(2), 133-142.

Mechner, F. (1958). Probability Relations within Response Sequences under Ratio Reinforcement. Journal of the Experimental Analysis of Behavior, 109-121.

Meck, W. H., & Church, R. M. (1983). A Mode Control Model of Counting and Timing Processes. Journal of Experimental Psychology: Animal Behavior Processes, 9(3), 320-334.

Moyer, R. S., & Landauer, T. K. (1967). Time Required for Judgments of Numerical Inequality. Nature, 215, 1519-1520.

Nieder, A. (2018). Evolution of Cognitive and Neural Solutions Enabling Numerosity Judgements: Lessons from Primates and Corvids. Philosophy Transactions of the Royal Society B, 373(1740), 1-12.

Nieder, A., & Dehaene, S. (2009). Representation of Number in the Brain. Annual Review of Neuroscience, 32, 185-208.

Nieder, A., & Miller, E. K. (2003). Coding of Cognitive Magnitude: Compressed Scaling of Numerical Information in the Primate Prefrontal Cortex. Neuron, 37(1), 149-157.

Ai. Chimpanzee Ai. https://langint.pri.kyoto-u.ac.jp/ai/en/ friends/ai.html.

Piazza, M., & Dehaene, S. (2015). From Number Neurons to Mental Arithmetic: The Cognitive Neuroscience of Number Sense. In M. S. Gazzaniga (Ed.), Cognitive Neuroscience: The Biology of the Mind (4th Ed.). W. W. Norton & Company.

Boysen, S. T., & Berntson, G. G. (1989). Numerical Competence in a Chimpanzee. Journal of Comparative Psychology, 103(1), 23-31.

Platt, J. R., & Johnson, D. M. (1971). Localization of Position within a Homogeneous Behavior Chain: Effects of Error Contingencies. Learning and Motivation, 2(4), 386-414.

Brannon, E. M. (2005). What Animals Know about Numbers. In J. I. D. Campbell (Ed.), Handbook of Mathematical Cognition (1st ed., pp. 85-107). Psychology Press.

Samhita, L., & Gross, H. J. (2013). The ‘Clever Hans Phenomenon’ Revisited. Communicative & Integrative Biology, 6(6), e-27122-1-e27122-3.

Brannon, E. M., & Terrace, H. S. (1998). Ordering of the Numerosities 1 to 9 by Monkeys. Science, 282, 746-749.

Sawamura, H., Shima, K., & Tanji, J. (2002). Numerical Representation for Action in the Parietal Cortex of the Monkey. Nature, 415, 918-922.

Davis, H., & Memmott, J. (1982). Counting Behavior in Animals: A Critical Evaluation. Psychological Bulletin, 92(3), 547-571.

Dehaene, S. (2001). Précis of The Number Sense. Mind & Language, 16(1), 16-36.

Sulkowski, G. M., & Hauser, M. D. (2001). Can Monkeys Spontaneously Subtract? Cognition, 79(3), 239-262.

References

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Dehaene, S., & Changeux, J. (1993). Development of Elementary Numerical Abilities: A Neuronal Model. Journal of Cognitive Neuroscience, 5(4), 390-407.

Thompson, R. F., Mayers, K. S., Robertson, R. T., & Patterson, C.

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J. (1970). Number Coding in Association Cortices of the Cat. Science, 168(3928), 271-273.

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53

Anaplastic Lymphoma Kinase-Positive Non-Small Cell Lung Cancer and its Targeted Therapies

BY ASHNA KUMAR ’24 Cover Image: Illustration of tumors growing in the lungs Source: iStock

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Abstract With over one hundred different types, cancer is a prevalent, lethal disease that claims the lives of hundreds of thousands annually. Lung cancer is the most fatal subset of cancer. It presents itself in two main subtypes: small cell lung cancer (SCLC) and non-small cell lung cancer (NSCLC), the latter of which has a significantly higher incidence rate. Many variations of NSCLC exist, as each patient is susceptible to developing driver mutations, or mutations that provide a selective growth advantage, that can be identified on a molecular level. One of the most prominent oncogene mutations (mutations in genes that promote the proliferation and survival of cells) is that of the anaplastic lymphoma kinase (ALK). Researchers have been developing treatments that specifically target the ALK protein in order to provide a treatment more specialized than chemotherapy for patients with ALK-positive NSCLC. Within the past decade, pharmaceutical companies have

developed a few FDA-approved ALK inhibitor drugs for treating ALK-positive NSCLC, while other, next generation ALK inhibitors are undergoing clinical trials, yielding promising results (American Cancer Society, n.d.).

Introduction Lung cancer typically originates in the cells that line the wall of the bronchi, bronchioles, or alveoli, but can start anywhere in the lungs.

Lung cancer is thought to be the result of precancerous alterations, in which cells in the lungs may undergo more rapid proliferation without forming a tumor and then acquire certain mutations that result in the onset of lung cancer (American Lung Association, n.d.).

In order for a tumor to develop, normal cells must acquire certain specific characteristics and capabilities, commonly referred to as the “hallmarks” of cancer (Hanahan & Weinberg, 2011).

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Hallmarks of Cancer The first hallmark of cancer is the ability of cells to sustain proliferative signaling without depending on external mitogenic growth signals to grow. They instead becoming autonomous by producing their own. Normal cells rely on specific growth factors to divide, but cancerous cells can instead synthesize their own growth factors, amplify the number of growth factor receptors present on the cell surface, or circumvent the need for growth factors and receptors altogether through mutations in cellular signaling pathways.

The second hallmark involves the evasion of growth suppressors. Just as there are signals that promote cell growth and proliferation, there are signals that work against cell proliferation in order to maintain homeostasis and make sure unnecessary division does not occur. The body has complex, strong regulatory systems that work against cell proliferation, derived from tumor suppressor genes like retinoblastoma and p53, which produce antigrowth signals.

Antigrowth signals can work either by forcing cells out of the proliferative cycle and into the inactive G0 phase of cell division, or forcing them into a post-mitotic state. Tumor cells, however, are capable of ignoring or interfering with these growth-inhibitory signals, and therefore can rapidly and abnormally proliferate. Some cancer cells have fewer antigrowth signal receptors on their surface or have mutated receptors that do not respond to signals, while others possess mutated tumor suppression pathways. Tumor cells also seem to avoid instruction to enter any post-mitotic, differentiated states that would prevent rapid division. (Hanahan & Weinberg, 2011).

In addition to inhibiting growth suppressors, cancer cells may acquire resistance towards apoptosis (programmed cell death), allowing for unhealthy proliferation. This is the third hallmark of cancer. Apoptosis can occur in the case of DNA damage, signaling imbalances caused by the activation of oncogenes, a lack of an oxygen supply, or insufficient growth factors. All of these characteristics can be found in tumor cells. Apoptosis is a crucial mechanism to get rid of the accumulation of aberrations such as these, but as cancerous cells have the capability to evade programmed death, tumor growth continues (Hanahan & Weinberg, 2011).

The fourth hallmark of cancer is related to the replicative immortality of cancer cells.

While healthy cells grow, divide, and multiply numerous times, they also have a limited span FALL 2020

of existence. Each cell is usually only capable of replicating a certain number of times before its replicative process is significantly slowed down and the cell enters a state of senescence, or inactivity. This process depends on telomeres, which are regions of DNA made up of short tandem repeats located at the ends of each chromosome that serve to protect the coding DNA from damage during the replication process. Each time a cell divides, the chromosomesâ&#x20AC;&#x2122; telomeres shorten in length.

Eventually, the telomeres are completely truncated, leaving the chromosomal DNA exposed to potential harm. When this occurs, the p53 tumor suppressor protein induces apoptosis. Cancer cells manage to avoid this fate by enlisting telomerase, an enzyme responsible for attaching more tandem repeats to the end of each telomere region. Cancer cells have an overexpression of this protein which works to counteract the progressive erosion of the telomere regions, immortalizing the cell and allowing for unrestricted cell division (Hanahan & Weinberg, 2011).

The body contains blood vessels that allow for the circulation of blood to all organs and tissues. Not only does the blood carry oxygen and essential nutrients to cells, it also disposes of waste molecules like carbon dioxide created from various chemical processes. Angiogenesis is the process in which new blood vessels form from already existing ones, a process that is essential for the development of embryonic tissue and for tissue repair, such as in wound healing. After the main stages of human development, a fixed structure of blood vessels is established, meaning major angiogenesis is no longer necessary. Because tumors are new, unexpected growths, they initially do not have associated blood vessels just to provide oxygen, nutrients, and a waste disposal pathway. This results in hypoxia, or insufficient levels of oxygen, once the tumor has grown past a certain size. Thus, as the fifth hallmark of cancer, tumor cells developed the ability to induce angiogenesis as needed in order for new blood vessels to provide them with oxygen, nutrients, and prevent the buildup of harmful waste, all of which is crucial for their survival.

"In addition to inhibiting growth suppressors, cancer cells may acquire resistance towards apoptosis (programmed cell death), allowing for unhealthy proliferation."

The final hallmark of cancer is metastasis, or the development of secondary tumors at a different site from the primary tumor. There are certain alterations that cause a program called the invasion-metastasis cascade to be initiated. This cascade is a series of events that occur within the body that ultimately lead to metastasis. During this process, there is an 55

Figure 1: This distribution of lung cancer types demonstrates that around 85% of all lung cancers are non-small cell lung cancers, including adenocarcinomas, squamous cell carcinomas, and large cell carcinomas.

Source: Image Created by Author

intravasation, meaning invasion of cancer cells into the circulatory and lymphatic system, which spreads the cancer cells throughout the body.

This results in the formation of new colonies of cancer cells, which retain metastatic capabilities and so can spread again and again (Hanahan & Weinberg, 2011).

Characterizing Lung Cancer

"Lung cancer can spread to the lymph nodes surrounding the bronchi and in between the lungs by utilizing the lymphatic vessels as an entranceway. "

The lymphatic system is one of the main channels through which lung cancer can spread.

Lung cancer can spread to the lymph nodes surrounding the bronchi and in between the lungs by utilizing the lymphatic vessels as an entranceway. The degree to which the lung cancer has spread to surrounding lymph nodes between the lungs determines the probability of the cancer spreading to external organs and the severity of the cancer and its treatment (American Cancer Society, n.d.).

Non-small cell lung cancer accounts for eighty to eighty five percent of all cases of lung cancer.

This disease is characterized by relatively large tumor cells compared to small cell lung cancer as well as a slower rate of metastasis. NSCLC has several subtypes including adenocarcinomas, squamous cell carcinomas, and large cell carcinomas. Adenocarcinomas consist of forty percent of all lung cancers and are typically the cancer found in former or current smokers.

Squamous cell carcinomas, which are also linked to smoking, consist of twenty-five to thirty percent of all lung cancers. Large cell carcinomas are less common, accounting for ten to fifteen percent of all lung cancers, and are generally the most rapidly spreading, and therefore the most difficult to treat (American Cancer Society, n.d.).

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ALK Fusion Oncogene It is well known that smoking is a leading cause of lung cancer; however, acquired gene rearrangements in lung cells are also prominent causes. The anaplastic lymphoma kinase (ALK) gene is the oncogene responsible for ALK+ NSCLC. Approximately five percent of all lung cancers possess the ALK gene rearrangement, and are referred to as ALK+ NSCLC. This mutation is most notable in non-smokers suffering from adenocarcinomas (American Cancer Society, n.d.). The ALK gene rearrangement is the result of a translocation, which is a chromosomal rearrangement where a segment from one chromosome swaps locations with a segment of another chromosome or another section of the same chromosome to form a fusion gene. However, there are several different variations of the ALK fusion gene. One of the most common fusion genes involves ALK and the gene encoding echinoderm microtubuleassociated protein-like 4 (EML4). The results of all ALK gene rearrangements is a mutated ALK receptor tyrosine kinase that excessively promotes cell proliferation, engendering rapid tumor growth (Genentech Oncology).

Non-specialized Therapies Current standardized therapies for ALK+ NSCLC include chemotherapy, radiation therapy, radiofrequency ablation, and surgery.

Treatment can also consist of a combination of any of these therapies. While the above methods of treatment are effective to some extent, they still do not produce the most optimal results. Surgery may only be effective

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Figure 2: Molecular model of the drug Crizotinib bound to its target protein ALK Source: Wikimedia Commons

in early cases of NSCLC and can have serious side effects like excessive bleeding, wound infections, and pneumonia. A combination of radiation therapy and chemotherapy is the primary treatment utilized for lung cancer, but it comes with the risk of countless side effects, common ones being gastrointestinal and clotting problems (American Cancer Society).

ALK Inhibitors In recent years, researchers have taken to developing drugs called ALK inhibitors that specifically target the ALK fusion oncogene as a means of more specialized, effective targeted therapy in order to improve survival rates. Current FDA-approved ALK inhibitors include Ceritinib (Xalkori), Crizotinib (Zykadia), Alectinib (Alecensa), Brigatinib (Alunbrig), and Lorlatinib (Lobrena) (American Cancer Society, n.d.). ALK inhibitors generally work by prohibiting the ALK fusion protein from triggering cell proliferation and signaling pathways. In a mutated ALK protein, selfdimerization (joining of two subunits) and phosphorylation (addition of a phosphate group) occur, making it not dependent on external growth signals. In order to counteract this self-sufficiency, ALK inhibitors prevent the ALK proteinâ&#x20AC;&#x2122;s ability to auto-phosphorylate and subsequently activate downstream receptors that promote uncontrolled cell growth. This means that multiple downstream pathways leading to cell proliferation and survival are not activated in tumor cells, and tumor growth is stalled (Genentech Oncology, n.d.).

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Crizotinib The first ALK inhibitor developed was Crizotinib. In phase III clinical trials, researchers compared the effectiveness of Crizotinib with chemotherapy on a study population of three hundred and forty-three patients. None of these patients had received prior treatment for their cancer. In the study, patients either received a dose of Crizotinib twice daily or intravenous chemotherapy every three weeks for a maximum of six, three week cycles. If a patientâ&#x20AC;&#x2122;s tumor progressed after receiving chemotherapy, they were allowed to switch to the Crizotinib treatment plan. The study found that Crizotinib was by far the superior treatment; progression-free survival with Crizotinib was 10.9 months, 3.9 months longer than for those receiving chemotherapy. The Crizotinib therapy also yielded an objective response rate (the percentage of subjects with partial or complete response to drug) 29% higher than the chemotherapy, and the one-year survival rate was 5% greater with Crizotinib. However, while this drug performed significantly better than chemotherapy during the trial, certain side effects like hepatic failure were serious concerns and the drug was unable to overcome certain resistance mutations and the activation of alternate oncogenic pathways in tumor cells (Solomon et al., 2014).

"In recent years, researchers have taken to developing drugs called ALK inhibitors that specifically target the ALK fusion oncogene as a means of more specialized, effective targeted therapy in order to improve survival rates."

Ceritinib Following Crizotinib, scientists ran trials for an ALK inhibitor Ceritinib, as a more potent therapy was needed; chemotherapy and Crizotinib, the only treatments then available for patients with ALK+ NSCLC, were insufficient. In Phase I and II

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Figure 3: Chemical struture of the drug Alectinib Source: Wikimedia Commons

"In the Phase III trials, Alectinib was compared to Crizotinib and maintained its status as the most effective and potent drug produced so far."

trials, Ceritinib showed strong anti-tumor activity and succeeded in several ways in which Crizotinib had previously failed in some patients. Patientsâ&#x20AC;&#x2122; tumors acquired resistance to Crizotinib within approximately twelve months of treatment, and Crizotinib was incapable of effectively inducing tumor regression in the brain, which is the most common site of ALK+ NSCLC metastases. Of two hundred and thirty-one patients, one hundred and fifteen, or half of the total trial population, were subjected to Ceritinib, while the remainder were left to be treated with chemotherapy.

Under Ceritinib, progression-free survival rates were approximately four months longer and patients reported some partial and complete tumor regression in the central nervous system (Soria et al., 2017).

Alectinib Alectinib began its clinical trial journey shortly after Crizotinib. Alectinib was originally intended for use in patients who had failed prior ALK inhibitor treatment. Within recent months, it has been promoted to a front-line therapy, able to be used in patients with ALK+ NSCLC without any previous treatment. Patients with ALK+ NSCLC from thirteen hospitals in Japan were enrolled in the Phase I trial. All of these patients had not been treated with an ALK inhibitor drug yet and had experienced disease progression following chemotherapy. Each of the patients received Alectinib twice daily in increasing doses. Fortunately, no severe adverse side effects were noted even when patients were taking the highest dosage, allowing three hundred milligrams to become the recommended dose for the Phase II trial. In that trial, the forty-six participants received this dosage two times per

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day. An astonishing forty-three of the patients, or 93.5%, achieved an objective response, two of which were complete responses, while the remainder were partial responses. Alectinib also proved to be efficient; eighty seven percent of patients achieved their response within six weeks of beginning treatment. Additionally, all patients experienced a reduction in tumor size of more than thirty percent.

One notable downside of Alectinib usage was the side effects of this drug, as ninety three percent of patients experienced grade 3 side effects, which includes nausea, constipation, and rashes. However, these side effects were much less serious than the ones caused by previous ALK inhibitors. In the three-year follow up of the Phase II trial, the overall survival rate was a surprising seventy eight percent and the progression-free survival rate was sixty two percent. Evidently, Alectinib possessed an unparalleled efficacy. In the Phase III trials, Alectinib was compared to Crizotinib and maintained its status as the most effective and potent drug produced so far. Among three hundred and three patients randomly chosen to receive either Alectinib or Crizotinib daily, Alectinib had a greater twelve-month progression-free survival rate by 19.7% and an impressive 15.3 month higher median progression-free survival time. Twenty-seven fewer patients experienced disease progression or death, even though the difference in overall survival rates were not that significant. The study concluded that Alectinib had a higher efficacy and lower toxicity than Crizotinib.

Alectinib also was better at controlling the resistance mutations that tend to develop in tumors. Furthermore, Alectinib was able to

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cross the blood-brain barrier, a feat few drugs are able to accomplish, and successfully shrink metastases in the central nervous system (Seto et al., 2013). In the beginning of 2017, the drug was promoted to a first-line treatment for ALK+ NSCLC. Brigatinib Nevertheless, it was noticed that, in patients who endured treatment with Ceritinib and Alectinib that although some secondary ALK mutations that developed were overcome by the drugs, certain other secondary resistance mutations like G1202R persisted. In an attempt to resolve this weakness, researchers began to develop a new drug called Brigatinib that could overpower a wider range of resistance mutations. It was only approved by the FDA for treatment of ALK+ NSCLC in Crizotinib-resistant patients in early 2017. Even in the earliest models, though, Brigatinib exhibited exceptional efficiency. The inhibitor was capable of acting against all ALK resistance mutations as well as suppressing the mechanisms of resistance to past ALK inhibitors. In the Phase I and II trials, Brigatinib was observed to have a median progressionfree survival of 14.5 months in Crizotinibresistant patients, although the efficacy of the drug in CNS metastases was not considerably improved with Brigatinib.

In addition, the majority of Brigatinib’s side effects were only Grade 1 or 2, making it less toxic than any other ALK inhibitor. In the Phase II ALTA clinical study that granted Brigatinib accelerated approval by the FDA, this drug showed a median progression-free survival that ranged from 9.2 to 12.9 months and objective response rates of forty-eight to fiftythree percent, reflecting a promising future for the drug as a first-line treatment (McCall et al., 2017). In May 2020, the FDA approved Brigatinib for adults with metastatic ALK+ NSCLC based on the efficacy of a randomized 1:1 trial where 275 patients were assigned to receive specific dosages of either Brigatinib or Crizotinib. The median progression-free survival for patients that received Brigatinib was 13 months greater than those that received Crizotinib, further demonstrating Brigatinib’s robustness. Brigatinib’s overall response rate for this trial was also 12% higher than that of Crizotinib’s (U.S. Food & Drug Administration, n.d.).

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Recent Therapies: Lorlatinib and Ensartinib In November 2018, the FDA granted accelerated approval to Lorlatinib, a third-generation brainpenetrant ALK inhibitor, to treat metastatic ALK+ NSCLC. It was approved specifically for patients whose cancer progressed under the treatment of Crizotinib and one or more other ALK inhibitor, or patients whose cancer progressed while using Alectinib or Ceritinib as their first ALK inhibitor. A group of 215 patients who previously received one or more ALK inhibitors partook in a non-randomized trial that yielded an overall response rate of 48%, 92% of which were complete responses.

The overall median response duration was 12.5 months, while the median response duration among patients with CNS lesions was 19.5 months (U.S. Food & Drug Administration, n.d.).

In another trial, 90% of treatment-naive (not previously treated) patients, 69.5% of patients who were previously treated with Crizotinib, and 38.7% of patients who were previously treated with two or more ALK inhibitors saw an objective response. The respective intracranial objective response rates concerning CNS metastases were 66.7%, 87%, and 53.1%. Only 7% of patients experienced serious side effects due to treatment, and 3% chose to discontinue treatment, but no treatment-related deaths were recorded. Lorlatinib treatment led to a significant change in disease progression in both groups that had received various treatments previously and in patients with no prior treatment experience, suggesting it would make for a robust first-line therapy in the future. However, Lorlatinib currently remains a second or third-line treatment (Solomon et al., 2018).

"Fairly more recent drugs like Ensartinib are in the process of undergoing clinical trials today, and have shown remarkable efficacy thus far."

Fairly more recent drugs like Ensartinib are in the process of undergoing clinical trials today, and have shown remarkable efficacy thus far. Results from a Phase I/II study show that among ALK+ NSCLC patients who were given a dose of 200mg or greater, the response rate was 60% and the median progression-free survival was 9.2 months. In patients who had not received prior treatment, the response rate was 80% with a median PFS of 26.2 months.

In patients who were previously treated with Crizotinib, the response rate was lower at 69%, with a median PFS of 9 months. The intracranial response rate was 64%. Overall, Ensartinib was tolerated fairly well in ALK+ treatment groups (Horn et al., 2018). An ongoing global Phase 3 study is proving Ensartinib’s superiority to Crizotinib, as the former’s median PFS has been

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around twice the latter’s. This, in conjunction with its safety profile, suggests Ensartinib has potential as a first-line treatment (Nanda, 2020).

Conclusion Current therapies such as Crizotinib, Ceritinib, Alectinib, Brigatinib, and Lorlatinib specifically target the ALK fusion oncoprotein and are intended to suppress the promotion of cell proliferation and survival pathways, with the ultimate goal being to engender substantial lung cancer tumor regression. The effectiveness of each new ALK tyrosine kinase inhibitor demonstrates a substantial effect across several treatment groups, including patients with CNS metastases. With the development of each novel drug, researchers come one step closer to fulfilling their overarching mission to ensure a functional, successful treatment for all patients diagnosed with ALK+ NSCLC.

2020, from https://www.health.com/condition/lung-cancer/ small-cell-lung-cancer-non-small-cell-lung-cancer Nanda, S. (2020, August 12). Ensartinib 'a new first-line option' for ALK-positive NSCLC. Medicine Matters. Retrieved October 18, 2020, from https://oncology.medicinematters.com/ non-small-cell-lung-cancer/ensartinib/exalt3-ensartinib-alkpositive-nsclc/18273496 Solomon, B. J., Besse, B., Bauer, T. M., Felip, E., Soo, R. A., Camidge, D. R., Chiari, R., Bearz, A., Lin, C. C., Gadgeel, S. M., Riely, G. J., Tan, E. H., Seto, T., James, L. P., Clancy, J. S., Abbattista, A., Martini, J. F., Chen, J., Peltz, G., Thurm, H., …

Shaw, A. T. (2018). Lorlatinib in patients with ALK-positive non-small-cell lung cancer: results from a global phase 2 study. The Lancet. Oncology, 19(12), 1654–1667. https://doi. org/10.1016/S1470-2045(18)30649-1 Solomon, B. J., Mok, T., Kim, D. W., Wu, Y. L., Nakagawa, K., Mekhail, T., Felip, E., Cappuzzo, F., Paolini, J., Usari, T., Iyer, S., Reisman, A., Wilner, K. D., Tursi, J., Blackhall, F., & PROFILE 1014 Investigators (2014). First-line crizotinib versus chemotherapy in ALK-positive lung cancer. The New England journal of medicine, 371(23), 2167–2177. https://doi.org/10.1056/ NEJMoa1408440

References Alectinib: an Anaplastic Lymphoma Kinase (ALK) Inhibitor.

(2016). Value-based Cancer Care. Retrieved October 17, 2020, from http://www.valuebasedcancer.com/special-issues/ mechanism-of-action-magnifier-2016-desk-reference/1322alectinib-an-anaplastic-lymphoma-kinase-alk-inhibitor ALK: A Driver of Cancer Pathogenesis. (n.d.). Genentech Oncology. Retrieved October 17, 2020, from https://www. genentechoncology.com/pathways/cancer-tumor-targets/alk. html FDA approves brigatinib for ALK-positive metastatic NSCLC. (n.d.). U.S. Food & Drug Administration. Retrieved October 18, 2020, from https://www.fda.gov/ drugs/drug-approvals-anddatabases/fda-approves-brigatinib-alk-positive-metastaticnsclc FDA approves lorlatinib for second- or third-line treatment of ALK-positive metastatic NSCLC. (n.d.). U.S. Food & Drug Administration. Retrieved October 18, 2020, from https://www. fda.gov/drugs/fda-approves-lorlatinib-second-or-third-linetreatment-alk-positive-metastatic-nsclc Hanahan, D., & Weinberg, R. (2011). Hallmarks of Cancer: The Next Generation. Cell, 144(5), 646-674. doi:10.1016/j. cell.2011.02.013 Horn, L., Infante, J. R., Reckamp, K. L., Blumenschein, G. R., Leal, T. A., Waqar, S. N., Gitlitz, B. J., Sanborn, R. E., Whisenant, J. G., Du, L., Neal, J. W., Gockerman, J. P., Dukart, G., Harrow, K., Liang, C., Gibbons, J. J., Holzhausen, A., Lovly, C. M., & Wakelee, H. A. (2018). Ensartinib (X-396) in ALK-Positive Non-Small Cell Lung Cancer: Results from a First-in-Human Phase I/II, Multicenter Study. Clinical cancer research : an official journal of the American Association for Cancer Research, 24(12), 2771–2779. https://doi.org/10.1158/1078-0432.CCR-17-2398 Lung Cancer. (n.d.). American Cancer Society. Retrieved October 17, 2020, from https://www.cancer.org/cancer/lungcancer.html Migala, J. (2020, July 1). The Difference Between Small Cell and Non-Small Cell Lung Cancer. Health. Retrieved November 3,

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On the Structure of Field Theories III

BY EVAN CRAFT â&#x20AC;&#x2122;20 Cover: ATLAS Experiment Image Source: CERN

This article is the third in a series of articles about Field Theories by Evan Craft. For the first two of the series, read the DUJS 20X Print Journal

Abstract In this paper, Noetherâ&#x20AC;&#x2122;s theorem relating symmetries of the action and conserved quantities is extended to an isomorphism.

We then give a number of complementary theorems before applying these ideas to theories which are in correspondence. We conclude with an extension to the quantum theory.

Preliminary Remarks Noether found that for every continuous transformation G which leaves the action invariant there is a corresponding conserved quantity [1]. By invariance, we mean

where S is the action functional

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and is the action of G on S. Such transformations are called symmetries of the action. Let J be the current operator which maps a symmetry G of S to its corresponding current . We would then have

In the following sections, we extend this theorem to a number of different isomorphisms.

Internal Symmetries We can decompose any transformation G into a field and Lorenz part so that

The field component, of course, act on the field while the Lorenz component acts on the coordinates. We may can now apply G to the action

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Using this, we may promote the set of all currents into a group by forcing

For some choice of product. If we choose composition, we have Where we have taken So that

The composition of two field transformations is itself a field transformation. We can assert a similar result for Lorenz transformations.

Therefore, each components is itself a part of a larger group. We can promote the set of all symmetries to a group by defining

Hence the set of all symmetries is isomorphic to the set of all currents as they are representations of the same vector field. In particular, they are both vector fields over the symmetry group.

A Complimentary Theorem Again consider

where we are taking the composition of each transformation. Our goal now is to find a group isomorphic to this one. Begin with Noether’s theorem. It is well known that the conserved current associate with a symmetry G is given by

"Many times, a theory is independent of representative. That is, given two actions, they imply the same physical results."

We can choose a different decomposition. We can represent this current as

where the basis vectors are given by We can simplify this current by simplifying G. To first order,

Again, we may turn the currents into a group by forcing so that

We can now decompose the current as

where we have introduced a shorthand notation to differentiate the results from the coming section. The basis vectors are given by

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for some choice of product. If we choose addition, we have

Where the factor of 1/2 will be justified shortly.

Here, Qμν is the stress tensor for the second Lagrangian. We would now like to construct a group isomorphic to the above. To do this, consider to Lagrangians L and F . We will say that and are equivalent if they give the same equations of motion so that 63

(29) will have the isomorphism structure we will describe.

We can then define the product of two equivalent Lagrangians to be

so that the product again gives the same equations of motions: elevating our set of equivalent Lagrangians to a group. Choose a symmetry of the first action

Action Invariants We will now show that the requirement (29) implies that the symmetry groups of S and I are isomorphic. Consider a symmetry

Since the theories are in correspondence, we can construct the map The second Lagrangian would yield This is a homomorphism as But from (21) we would then have

"In theories following Noether’s result, we have that for every symmetry of the system, we can construct a corresponding conserved current."

since the variations are equal. Therefore, for a set of equivalent Lagrangians, the symmetry group is fixed so that the current map becomes a homomorphism

It is an isomorphism as the composition of bijective functions is bijective. This is indeed a symmetry as of I since

where the same symmetry is chosen for both currents. This can easily be extended to the action functionals so that

as the set of all Lagrangians can be mapped isomorphically to an action functional by taking

External Symmetries

Cover image: Artist’s impression of Planet Nine. The yellow ring around the Sun is Neptune’s orbit.

Source: Wikimedia Commons/ nagualdesign and Tomruen, CC-BY-SA 4.0

Many times, a theory is independent of representative. That is, given two actions, they imply the same physical results. In the previous examples, this would require and so that

for some choice of ϕ and ψ . We say that these theories are in correspondence. We focus on the case where the correspondence can be extended to a bijection between action functionals

We will call q the correspondence function. In the proofs that follow, S and I need not be action functionals. Indeed, any such theories related by

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In theories following Noether’s result, we have that for every symmetry of the system, we can construct a corresponding conserved current.

Again, let J be the current operator which maps a symmetry of S to its corresponding conserved current

Where we have used the shorthand notation from the previous sections. We would have a corresponding current operator for I and one of its symmetries H

In the case that J and K are bijections, we could form the map

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So that Since K maps symmetries to conserved currents then is also conserved. Furthermore, if J and K can be extended to isomorphisms (as is possible for theories in Section 2) then would the composition of isomorphisms and therefore an isomorphism itself. Finally, this would imply that the symmetry group of S is isomorphic to the current group of I.

So that there is an extra factor in the definition of the path integral. We may also consider

And in certain cases, we may have

Isomorphic Variables There are a number of ways to construct such a correspondence function. We can define the coordinate operator such that

We can again say that the symmetry groups are isomorphic as we have a correspondence between the path integrals. And hence the conserved current groups of the path integral also correspond. These ideas can be extended to higher order theories

Furthermore, if we insist on a relation between the variables

We can construct a correspondence function

"We can again say that the symmetry groups are isomorphic as we have a correspondence between the path integrals"

Quantum Mechanics All of the above results can be seen in quantum theory. Consider a unitary operator T in Hilbert space.

so that Infinitesimally so long as the coordination functions and variable relations are invertible. Many times, the coordinate relation may be a homomorphism.

We call such variables homomorphic and the definition of isomorphic variables then follows.

If T preserves the Hamiltonian,

Path Integrals we would then have We may also use this symmetry of the action to produce a symmetry of the path integral. Given [2] or rather

This is the infinite limit of

where we have defined the charge operator

We know that

Internal Symmetries We can consider this time two infinitesimal symmetries of the action

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We then have

Calculating this out, we have

to first order. Hence we may associate the product with the infinitesimal translation

up to first order so that

and hence

Hence

And hence we have a homomorphism between the charge symmetry groups.

External Symmetries Suppose that two separate Hamiltonians H and K give the same equations of motion. Furthermore, assume that there exists some correspondence between the two theories such that

By the previous sections, we will have a four part isomorphism between the current groups and symmetry groups.

References [1] E. Noether. (1918). Kgl. Ges. d. Wiss. Nachrichten, Math.-phys.

Klasse [2] R. P. Feynman. (1948). Rev. of Mod. Phys., 20, 367.

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The Impact of Mozart’s Music on Epileptic Patients

BY GEORGIA DAWAHARE ’23 Cover Image: Portrait of Wolfgang Amadeus Mozart (1756-1791). Mozart is one of the greatest musical composers of all time, and his music continues to influence the world today.

In 1993, Rauscher et al. found surprising research results that suggested that Mozart’s music (K448) improves spatial reasoning skills and has aptly been named the Mozart Effect Source: Wikimedia Commons, Created by: Edward Lehmann

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Introduction Wolfgang Amadeus Mozart is widely considered one of the greatest musical composers of all time. Starting his career as a four-fold infant prodigy (harpsichordist, violinist, organist, composer), Mozart composed more than 600 pieces during his short lifetime of 35 years (TIME, 1938; Britannica, n.d.). While Mozart was indeed a genius whose music inspired many, he could never have predicted the effect his work would one day have on babies and epileptic patients. In 1993, Rauscher, Shaw, and Ky made the claim that after listening to the first movement “allegro con spirito” of the Mozart Sonata for Two Pianos in D major (K448), subjects with epilepsy showed significantly better spatial reasoning skills. In the years following, commercial shelves were flooded with products incorporating Mozart’s music, targeting eager parents-to-be and promising improved childhood intelligence.

In 1998, the governor of Georgia, Zell Miller,

escalated matters by mandating that mothers of newborns in the state be given classical music CDs to foster their offspring’s intelligence (Swaminathan, n.d., Pietschnig et al., 2010).

Several studies have attempted to replicate Rauscher et al.’s study since then, but they have produced mixed results. However, while there is little evidence for a specific, performanceenhancing Mozart effect, two researchers have recently conducted a systematic review of works related to the effect of Mozart’s music on epilepsy. Based on the review, the researchers found music therapy to be a legitimate noninvasive approach that could serve as a complementary form of treatment for epilepsy and epileptiform discharges (Sesso & Sicca, 2020).

The Mozart Effect In the original study that gave birth to the Mozart effect, three scientists at the Center DARTMOUTH UNDERGRADUATE JOURNAL OF SCIENCE

for the Neurobiology of Learning and Memory at the University of California performed an experiment in which 36 college students were each given three sets of standard IQ spatial reasoning tasks (Rauscher et al., 1993). Each task was preceded by 10 minutes of either (1) listening to Mozart’s sonata for two pianos in D major (K448), (2) listening to a relaxation tape, or (3) silence. The researchers observed improved performance for the three tasks immediately following the Mozart tape compared to the second two treatments. The students’ spatial reasoning skills were tested using the StanfordBinet intelligence scale. To assess the impact of the scores, Rauscher et al. translated the mean standard age scores (SAS) to spatial IQ scores, concluding with a score of 119 for the first group, 111 for the second, and 110 for the third (1993). These results indicate that the IQs of subjects participating in the music condition were 8 - 9 points above their IQ in the other two conditions. The researchers acknowledged that since they only used one musical sample by one composer, a variety of composers and pieces should be an area of future study to corroborate their findings (Rauscher et al., 1993).

After the publication of this controversial study, the Mozart effect has been subject to intense skepticism. A meta-analysis published by Pietschnig et al. in 2010 looked at 39 different studies on the Mozart effect to determine whether or not a Mozart effect exists. The study found little support for a Mozart effect in published and unpublished work. While the results of the published works indicate a positive, significant effect of exposure to K448 when compared to no stimulus at all on spatial task performance, observed effects were small in size. Additionally, exposure to other musical stimuli compared to exposure to no stimulus at all yielded an overall effect of about the same size as K448’s effect (Pietschnig et al., 2010). More importantly, however, the study found strong evidence for publication bias for the magnitude of the effect of studies that compared samples exposed to the Mozart sonata and samples exposed to no stimulus at all. Overall effects seem to be inflated in published and popular studies when compared to unpublished studies and those with less attention that use the same conditions. This discrepancy suggests that studies showing strong effects in expected directions tend to be published more often, quicker, and more prominently (Pietschnig et al., 2010).

In the process of attempting to prove the positive effect of Mozart’s music on spatial-

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temporal reasoning, scientists stumbled upon a totally unrelated but groundbreaking finding in studies with epileptic patients. In 1998, 23 of 29 patients with focal discharges (bursts of generalized spike and wave complexes on electroencephalograms, or EEGs) who listened to the Mozart piano sonata K448 experienced a significant decrease in epileptiform activity (Hughes et al., 2016).

The Science of Epilepsy Epilepsy is one of the most common neurological diseases of the brain and is characterized by an enduring predisposition to generate seizures. Those suffering from the condition face the neurobiological, cognitive, psychological, and social consequences of seizure recurrences. The prevalence and incidence of epilepsy are slightly higher in men compared to women and tend to peak in the elderly, reflecting the higher frequency of stroke, neurodegenerative diseases, and tumors in this age-group (Beghi, 2020).

Epileptic seizures are recurrent paroxysmal events characterized by stereotyped behavioral alterations resulting from underlying neural mechanisms of the disease (Beghi, 2020). While all people with epilepsy experience seizures, not all individuals with seizures have epilepsy.

According to the International League against Epilepsy (ILAE), epilepsy is defined by any of the following conditions: (1) at least two seizures without apparent cause occurring more than 24 hours apart, (2) one unprovoked seizure and a probability of further seizures similar to the general recurrence risk (at least 60%) after two unprovoked seizures, occurring over the next ten years, and (3) diagnosis of epilepsy syndrome (Fisher et al., 2014). Seizure onset can be focal (seizures arising in one hemisphere of the brain), generalized (seizures originating in both hemispheres simultaneously), or unknown (Fisher et al., 2017). Core to the pathology of epilepsy is the atypical increase or decrease in neural activity that provokes abnormal brain function. Regional fluctuations in neuronal activity tend to vary between generalized, absence, and focal seizures (Cavanna & Ali, 2011).

"In the process of attempting to prove the positive effect of Mozart’s music on spatial-temporal reasoning, scientists stumbled upon a totally unrelated but groundbreaking finding in studies with epileptic patients."

Generalized tonic-clonic seizures (GTCS) or “grand mal” seizures are characterized by abnormal bi-hemispheric neuronal discharge generating complete unresponsiveness and convulsions. The sudden tonic phase of these seizures comprises of sustained axial muscle (muscles of the trunk or head) contraction, 69

Figure 1: The thalamus relays sensory and motor signals in the brain and is a regulator of consciousness and alertness (Torrico & Munakomi, 2020).

During grand mal seizures, SPECT studies of cerebral blood flow have detected increased blood flow in the thalamus (red) and specific regions of the cortex (blue) Source: Wikimedia Commons, Creator: Colder B

"Absence seizures are typified by sudden onset of blank staring and unresponsiveness, usually lasting 5-10 seconds. Eyelid fluttering and quick, involuntary muscle jerks called myoclonic jerks are common."

upward eye deviation, and pupillary dilation, represented by by 10-20 seconds of high frequency electroencephalographic (EEG) activity which is indicative of abnormal brain activity. The “clonic” portion refers to rhythmic limb contractions accompanied by repetitive spikes in EEG activity (Cavanna & Ali, 2011).

Blood flow and metabolic mappings of GTCS indicate that specific brain regions intensely reject the idea of participating with the whole brain. Signal photon emission computerized tomography (SPECT) studies of cerebral blood flow found increased blood flow in the thalamus, brainstem, and portions of the cortex during GTCS, indicating significant stress in these areas (Figure 1). The thalamus and cortex play a large role in sensation and sensation interpretation while the brain stem functions to relay information from the brain to the body and vice versa. Conversely, decreases in cerebral blood flow were seen during the seizure period in the cingulate gyrus which helps regulate emotions and pain (Cavanna & Ali, 2011). The focal disruption in GTCS of these loci, together with effects on related sub-cortical structures, yield the intense and persevering impaired consciousness typical of GTCS. Despite these disruptions, there is relative sparing of the intervening regions of the primary sensory and motor cortices (Cavanna & Ali, 2011).

Absence seizures are typified by sudden onset of blank staring and unresponsiveness, usually lasting 5-10 seconds. Eyelid fluttering and quick, involuntary muscle jerks called myoclonic jerks are common. Yet, the motor manifestations of absence seizures are subtle, allowing absence seizures to pose as the most “transparent” or unnoticeable form of seizure, or ictal, impaired

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consciousness (Cavanna & Ali, 2011). Absences are generated through abnormal EEG oscillations in the cortico-thalamic network (Figure 2). Although absences are regarded as highly similar to generalized seizures, preliminary investigation through functional magnetic resonance imaging (fMRI) with simultaneous EEG recordings (EEG-fMRI) has verified that generalized spike-wave seizures (seizures which produce a specific type of EEG signature that is indicative of absence epilepsy episodes) selectively involve particular networks whilst sparing others. Specifically, improved spatial and temporal resolution has led to the identification of bilateral thalamic activation, and cortical signal decrease in various association areas (areas that form connections between sensory and motor areas) (Cavanna & Ali, 2011).

Complex partial seizures usually last between 15 seconds and 3 minutes. Characteristically, consciousness is initially spared, but seizure progression brings variable loss of contact with the environment; the most profound impairment typically occurs late in the seizure, persisting for several minutes post-ictally. The temporal lobe, most commonly associated with auditory processing and memory encoding, is the original seizure focus in ~80% of patients with complex partial seizures (Cavanna & Ali, 2011). As the seizure evolves, epileptic patients experience clinical manifestations ranging from affective, mnemonic, and composite perceptual phenomena. Certain components of the medial temporal lobe such as the amygdala have been related to the affective component of experiential phenomena. However, the vast array of experiential phenomena indicates the

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Figure 2: Absence seizures are a type of epileptic seizure generated through abnormal EEG oscillations in the corticothalamic network. This image depicts the EEG signature of an absence epilepsy episode which are the generalized 3 Hz spikewave discharges Source: Wikimedia Commons, Creator: EB Bromfield

recruitment of wider neural networks beyond the temporal lobe (Cavanna & Ali, 2011).

Scientists hypothesize that abnormal activity, which disseminates into diffuse inhibition of the frontoparietal cortex, in the midline cortical structures (upper brainstem-diencephalon activating systems like the thalamus and hypothalamus) causes loss of consciousness during temporal lobe seizures (Cavanna & Ali, 2011).

Neurostimulation through Sonatas In an attempt to understand the relation between the Mozart effect and epileptic treatment, studies have found that exposure to K448 effectively decreases interictal spikes in children with different epileptic seizure types. One study in 2010 enrolled 58 Taiwanese children with epilepsy and used a continuous EEG to record and compare the frequencies of discharge before, during, and after exposure to K448 (Lin et al., 2010). Interictal discharges were reduced in most (81%) patients as they listened to K448. Patients with generalized or central discharge showed the most improvement.

In most patients (76.1%), the decrease in epileptiform discharges continued after the music ended (Lin et al., 2010). Despite positive results, Lin et al. neglected to use control music, casting a marginal amount of doubt on their results and attempt to remove a possible placebo effect.

Fortunately, other studies have investigated the effect of Mozart music as well as control

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music on epilepsy. In 2018, 45 children (with a range of 2-18 years and a mean of 7 years 10 months) were recruited based on previous EEGs performed while the children were awake in which the report stated that frequent epileptic discharges were present (focal or generalized; Grylls et al.). Patients had to try and maintain a constant state of awareness while they were exposed to five musical treatments with no breaks in between, each lasting five minutes: 1) before Mozart music (baseline), 2) during Mozart music (K448), 3) after Mozart music/ before control music, 4) during control music, and 5) after control music. Experimenters used age-appropriate control music depending on what parents listed as music the children would like to listen to in order to make enjoyment of control music as constant a factor as possible. Of the 45 patients included in the study, 23 female and 22 male, 24 had epilepsy with structural/ unknown etiology and 21 had genetic etiology (Grylls et al., 2018). The researchers found a significant decrease in epileptic activity in children during the Mozart listening period compared to the baseline. More interestingly, the study found no significant decrease in epileptiform EEG activity during or after listening to the control music compared to the baseline. This ultimately supports the idea that this effect is unique to Mozart, or at least to similarly structured music (Grylls et al., 2018).

"The studies discussed provide significant evidence supporting the existence of a Mozart effect related to epilepsy, but studies of the Mozart effect often produce conflicting results."

The studies discussed provide significant evidence supporting the existence of a Mozart effect related to epilepsy, but studies of the Mozart effect often produce conflicting results.

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"Epilepsy is a surprisingly common neurological disease, affecting just under 1 person for every hundred worldwide."

Two Italian researchers, Dr. Gianluca Sesso and Dr. Federico Sicca from the University of Pisa have recently conducted a systematic review of works related to the effect of Mozart’s music on epilepsy. Working according to accepted standard methods for analyzing clinical treatment, the scientists studied 147 published research articles and ultimately selected 12 pieces of research that represented the best available science on the effect of Mozart’s music on epilepsy (Neuroscience News, 2020). Nine meta-analyses showed significant reductions in seizures and IED (interictal epileptiform discharge) frequencies after long-term music treatment and in IED frequency during and after a single music stimulus (Sesso & Sicca, 2020).

They found that listening to Mozart, especially on a daily basis, led to a significant reduction in epileptic seizures and also to a reduced frequency of abnormal brain activities (interictal epileptiform discharges) in epileptic patients.

These effects occurred after a single listening session and were maintained after a prolonged period of treatment. The meta-analysis indicates that a period of listening to Mozart can cause an average reduction in epileptic seizures ranging from between 31% and 66%, but this varies from person to person and according to the music stimulus used (Neuroscience News, 2020).

must be understood (Neuroscience News, 2020). In the near future, more consistent and reproducible results will have to determine the effects of music on the mind.

Conclusion

Hughes, D. J. R., Daaboul, Y., Fino, J. J., & Shaw, G. L. (2016). The “Mozart Effect” on Epileptiform Activity: Clinical Electroencephalography. https://doi. org/10.1177/155005949802900301

Epilepsy is a surprisingly common neurological disease, affecting just under 1 person for every hundred worldwide. It is characterized by chronic seizures and affects all populations regardless of sex and race (Beghi, 2020; Neuroscience News, 2020). A recent meta-analysis revealed that Mozart music could be an effective, non-invasive, and prolonged method of neurostimulation, reducing the frequency of epileptic seizures, even in hard-to-treat patients (Neuroscience News, 2020). Dr. Sesso, one of the authors of the meta-analysis, explained that “All cultures have music, so it obviously fulfills some psychological need. The mechanisms of the Mozart effect are poorly understood. Obviously, other music may have similar effects, but it may be that Mozart’s sonatas have distinctive rhythmic structures which are particularly suited to working on epilepsy” (Neuroscience News, 2020). Indeed, other studies have used Mozart’s K448 to demonstrate the power of music to produce positive effects in epileptic patients, particularly children. In order to harness the Mozart effect as a brain stimulation technique in the treatment of epilepsy in clinical settings, however, the exact mechanism of the Mozart effect on the brain

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References Beghi, E. (2020). The Epidemiology of Epilepsy.

Neuroepidemiology, 54(2), 185–191. https://doi. org/10.1159/000503831 Cavanna, A. E., & Ali, F. (2011). Epilepsy: The Quintessential Pathology of Consciousness. Behavioural Neurology, 24(1), 3–10. https://doi.org/10.1155/2011/374507 Fisher, R. S., Acevedo, C., Arzimanoglou, A., Bogacz, A., Cross, J. H., Elger, C. E., Engel, J., Forsgren, L., French, J. A., Glynn, M., Hesdorffer, D. C., Lee, B. I., Mathern, G. W., Moshé, S. L., Perucca, E., Scheffer, I. E., Tomson, T., Watanabe, M., & Wiebe, S. (2014).

ILAE official report: A practical clinical definition of epilepsy.

Epilepsia, 55(4), 475–482. https://doi.org/10.1111/epi.12550 Fisher, R. S., Cross, J. H., French, J. A., Higurashi, N., Hirsch, E., Jansen, F. E., Lagae, L., Moshé, S. L., Peltola, J., Roulet Perez, E., Scheffer, I. E., & Zuberi, S. M. (2017). Operational classification of seizure types by the International League Against Epilepsy: Position Paper of the ILAE Commission for Classification and Terminology. Epilepsia, 58(4), 522–530. https://doi. org/10.1111/epi.13670 Grylls, E., Kinsky, M., Baggott, A., Wabnitz, C., & McLellan, A. (2018). Study of the Mozart effect in children with epileptic electroencephalograms. Seizure, 59, 77–81. https://doi. org/10.1016/j.seizure.2018.05.006

Is the “Mozart Effect” Real? New Analysis Indicates That Music Can Help Epilepsy. (2020, September 12). Neuroscience News. https://neurosciencenews.com/mozart-effectepilepsy-17012/ Lin, L.-C., Lee, W.-T., Wu, H.-C., Tsai, C.-L., Wei, R.-C., Jong, Y.-J., & Yang, R.-C. (2010). Mozart K.448 and epileptiform discharges: Effect of ratio of lower to higher harmonics.

Epilepsy Research, 89(2), 238–245. https://doi.org/10.1016/j. eplepsyres.2010.01.007 Mozart Biography. (1938). TIME Magazine, 32(13), 32–32.

Pietschnig, J., Voracek, M., & Formann, A. K. (2010). Mozart effect–Shmozart effect: A meta-analysis. Intelligence, 38(3), 314–323. https://doi.org/10.1016/j.intell.2010.03.001 Rauscher, F. H., Shaw, G. L., & Ky, C. N. (1993). Music and spatial task performance. Nature, 365(6447), 611–611. https://doi. org/10.1038/365611a0 Sesso, G., & Sicca, F. (2020). Safe and sound: Meta-analyzing the Mozart effect on epilepsy. Clinical Neurophysiology, 131(7), 1610–1620. https://doi.org/10.1016/j clinph.2020.03.039 Swaminathan, N. (n.d.). Fact or Fiction?: Babies Exposed to Classical Music End Up Smarter. Scientific American. Retrieved October 13, 2020, from https://www.scientificamerican.com/

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article/fact-or-fiction-babies-ex/ Torrico, T. J., & Munakomi, S. (2020). Neuroanatomy, Thalamus.

In StatPearls. StatPearls Publishing. http://www.ncbi.nlm.nih. gov/books/NBK542184/ Wolfgang Amadeus Mozart | Biography, Facts, & Works. (n.d.).

Encyclopedia Britannica. Retrieved October 13, 2020, from https://www.britannica.com/biography/Wolfgang-AmadeusMozart

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Changing Times Reflect the Need for Diversity in Clinical Trials

BY GRACE NGUYEN '24 Cover image: A volunteer participates in a phase 3 trial for the Sinovac COVID-19 vaccine at Padjadjaran University in Indonesia. During the global COVID-19, a wide variation in symptoms has been observed in response to infection. This variation emphasizes the need for diversity in clinical trials, as the only way to properly address COVID-19 is to understand the differences among people.

Source: Wikimedia Commons

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Introduction The core of America’s identity revolves around its diversity, as its “salad bowl” of cultures have helped cultivate its growth and—arguably— allowed it to become the international power it is today. Yet in light of the chaos that has characterized the United States in 2020 (i.e. the Covid-19 global pandemic, police brutality, disunity aided by divergent political beliefs, the 2020 presidential election, etc.), it seems that America is more divided than ever. Perhaps this division is inevitable when there are so many different beliefs interacting with one another, but this division seems to be driven by underlying inequality and differential representation of minority groups in the institutions that comprise 21st century American society. One notable disparity is in the field of medicine. America’s diversity is not adequately represented in medicine, as underrepresented ethnic minorities and other minority groups only compose a small

percentage of participants in clinical trials. In order to obtain accurate results that will be effective for all Americans, the diversity of America must first be represented in the clinical trials.

The Participation Gap Despite America’s diversity, the United States still sees a lack of representation in many forms.

For example, most of the media and positions of authority are occupied by non-Hispanic whites, as ethnic minorities only made up 19.8% of all film leads in 2019 despite constituting 40% of the population (Hunt et al, 2019).

The US also ranked 76th out of 193 countries for women representation in government (Inter-Parliamentary Union, 2019). Similarly, biomedical research is no exception to this lack of diversity. As a field that aims to discover solutions that will benefit all of humanity, the discipline itself fails to recognize all of humanity from the beginning. In the United States alone, DARTMOUTH UNDERGRADUATE JOURNAL OF SCIENCE

most clinical trials consist of participants who are young, thin, non-Hispanic white males (in studies that are labeled as mixed gendered).

When the research behind many treatments created to prevent illnesses involves samples that often have no relation to the illness itself, how can patients be assured that such a treatment is safe for them to take?

The Oxford English Dictionary defines minority as “any identifiable subgroup within a society, [especially] one perceived as suffering from discrimination or from relative lack of status or power” (Oxford Advanced English Dictionary, 2020). Non-Hispanic white males are the majority group in the United States, as they have been since the birth of the nation; thus, they outnumber minority groups and control most industries. Women and people of color have often been subjected to secondary roles and careers throughout history. It is no surprise, then, that minority groups are not as equally represented in clinical trials as majority groups. However, this participation gap is not new. In recent decades, participation in clinical trials by men has overshadowed women’s involvement. Men, often non-Hispanic whites, were considered the “norm” study group, and it was believed that women were unqualified to be productive participants due to fluctuating hormone levels. In 1975 to 1977, pregnant women in particular were deemed a “vulnerable population” and were especially barred from enrolling in the early stages of research. The primary concern for pregnant women was possible detrimental effects on reproductive health, and this concern later extended to women of child-bearing potential (Liu & Mager, 2016). Furthermore, protocols for the diagnosis and treatment of heart disease—the number one cause of American deaths—were based upon findings from middle-aged white male patients. Consequently, women were often diagnosed much later with an advanced disease that was more difficult to treat (Vlassoff, 2007).

It can then be seen that a history of maltreatment has resulted in mistrust between minority groups and the scientific community; this plays a considerable role in the seemingly increasing participation gap. Minority groups retain a “relative lack of status or power,” and consequently are often subjected to exclusion and exploitation by the majority group.

Such exclusion and manipulation, evident during the 1932 Tuskegee syphilis study (African-American males with syphilis were passively monitored and denied treatment) and the 1950s Willowbrook hepatitis study FALL 2020

(intellectually challenged children were test subjects for a preliminary hepatitis vaccine), has persisted throughout America’s scientific history, as many of the scientific achievements praised by the public have been accomplished through the mistreatment of minority groups (Alsan & Wanamaker, 2018; Rosenbaum, n.d.). This history of victimization inevitably generated a sense of mistrust between the white-dominated scientific community and minority groups, which is one of many reasons for the absence of diversity in clinical research.

The Need for Diversity in Clinical Trials It is clear that minority groups have long been underrepresented in clinical trials, and it is extremely likely that in doing so, medical treatments have not been fully developed.

The participation gap between majority and minority groups in clinical trials creates an inaccurate representation of the population to which many of these treatments are targeted.

A 2018 Scientific American editorial noted just that: “Nearly 40 percent of Americans belong to a racial or ethnic minority, but the patients who participate in clinical trials for new drugs skew heavily white—in some cases, 80 to 90 percent.

Yet nonwhite patients will ultimately take the drugs that come out of clinical studies […]”

(THE EDITORS, 2018). By disregarding minority groups’ involvement in clinical trials, scientists fail to account for all the environmental factors that could contribute to the minority groups’ reception of the treatment. This reduced involvement of minority groups in clinical trials then limits scientists’ understanding of treatment efficacy for these groups, ultimately putting these individuals at higher risk of disease morbidity and mortality. The United States is currently predominantly white, but research predicts that in nearly 35 years, nonHispanic whites may no longer be the majority group. This is not to say that this is the only reason why clinical trials need to be more diversified, but it does further emphasize its future value.

"Nearly 40 percent of Americans belong to a racial or ethnic minority, but the patients who participate in clinical trials for new drugs skew heavily white— in some cases, 80 to 90 percent."

Race and Disease Prevalence The lack of different racial groups in clinical trials is perhaps the most prominent gap in clinical trial representation of minorities. Race has often been a politically charged topic that has become associated with a sociocultural component, but it has also been implicated in many health disparities. It is known that some diseases result from some genes that are more present in certain racial and/or ethnic groups than others; examples include sickle-cell anemia prevalence in the African, African-American, 75

Figure 1: Thalidomide was widely used throughout the late 1950s and early 1960s for the treatment of nausea in pregnant women and caused severe birth defects. Upon seeing the tragedy that Thalidomide enacted in Europe, the United States Congress passed the KefauverHarris Amendment in 1962 that strengthened FDA authority.

The FDA then issued “General Considerations for the Clinical Evaluation of Drugs” in 1977 that discouraged the participation of women of “child-bearing potential” in clinical trials. The loose definition of “child-bearing potential” ultimately led to a significant lack of female involvement in clinical trials for decades following the FDA mandate (Kim & Scialli, 2011; Liu & Mager, 2016).

Source: Wikimedia Commons

"Disproportionate rates of cardiovascular disease (CVD) persist in the African American community, with the mortality rate of African Americans being 20% higher than that of non-Hispanic whites."

and Mediterranean populations and Tay-Sachs disease, which is common among the Ashkenazi Jewish and French Canadian populations (Akli et al., 1993; Solovieff et al., 2011). However, the question of whether differential appearance of a disease among racial populations is primarily attributable to biological or environmental factors is still highly contested. Epigenetics, the study of how environmental factors influence genetic expression, has started exploring how environment and biology interact and how this interaction contributes to health and disease (Eichler, 2019). While epigenetics is still a developing field and the study of how human genetic variation influences how a disease presents itself still needs further research, it is clear that there are differences in mortality rates for a given disease within different racial groups.

Disproportionate rates of cardiovascular disease (CVD) persist in the African American community, with the mortality rate of African Americans being 20% higher than that of nonHispanic whites (Mensah, 2018). It is not entirely clear why this disparity in CVD exists. Some believe that this is due partly (if not wholly) to differences in genetic disposition, claiming that human genetic variation could be more homogenous within racial clusters, resulting in higher a prevalence of genetic risk factors in a particular racial group. Others argue that such a disparity results from social factors such as healthcare access, economic disadvantages, and institutional and personal discrimination, among other social differences (Kuzawa & Sweet, 2009).

CVD has been found to be linked with deviations

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in DNA methylation, a chemical modification to DNA that reduces gene transcription. A study done by Zhong and colleagues examined the correlation between short-term fine particle (PM2.5) exposure and cardiac outcomes in 573 elderly men around Boston over a span of 11 years and found that those who had higher TLR2 methylation were more susceptible to critical cardiac autonomic impacts caused by PM2.5 exposure (Zhong et al., 2015). From these types of studies, it can be concluded that the environment exudes at least some influence on gene expression, indicating an important connection between genetics, environment, and disease. The tremendous diversity in genetics and environment between populations necessitates that clinical trials account for geographic and socioeconomic diversity in order to gather a holistic understanding of a treatment’s effectiveness.

As previously emphasized, social influencers of health very likely contribute to minority health disparities, especially economic disadvantages and institutional discrimination.

Racial minority groups like African Americans and Hispanics have more high-risk factors and a higher mortality rate for CVD; Hispanics also higher rates of hypertension, diabetes, and heart failure than the general non-Hispanic white population (Graham, 2015; Mitchell et al., 1990). Native Americans have a mortality rate for tuberculosis that is 750% higher than that of other Americans (Brockie et al., 2013).

Adverse childhood experiences—historical

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loss, discrimination, childhood abuse and neglect, violence—have been considered to be predispositions to diabetes and alcoholism (524% higher in Native American populations), which are both risk factors for tuberculosis; a study conducted by Jeon et. al in 2008 found that those with diabetes were three times more likely to contract active tuberculosis than non-diabetics (Brockie et al., 2013; Jeon & Murray, 2008). While there may not be a causal relationship between diabetes and tuberculosis, it can be gathered that both environment and genetics influence the appearance of this disease; the combination of genetic risk and environmental “activation” is important to consider and indicates the importance of encompassing both genetic and environmental diversity in clinical trials.

Gender and Disease Prevalence Gender differences also exist in disease prevalence and prevention, as most of what clinicians know about the diagnosis, treatment, and prevention of disease has been derived from studies done on male cells, male mice, and men (Clayton, 2016). Gender refers to “the array of socially constructed roles and relationships, personality traits, attitudes, behaviors, values, relative power and influence that society ascribes to the two sexes on a differential basis (Health Canada, 2000; Vlassoff, 2007). In this way, gender encompasses social differences, while sex refers to exclusively to biological differences.

Gender differences in social determinants of health and illness have been observed through food consumption patterns and nutrition, where studies have found that in some countries—particularly in South Asia— male children receive greater amounts of food than female children (Borooah, 2004). Another study found that such gender bias of food allocation in childhood often leads to gendered healthcare allocation in the future (Larme, 1997). Sociocultural emphasis on the “ideal” female body has also contributed to gendered social determinants in nutrition, as it presents a risk factor for eating disorders (Deheeger et al., 2002). Furthermore, gender differences in biological determinants of health includes genetic vulnerability to disease, reproductive and hormonal factors, and deviations in physiology during the life-cycle (Vlassoff, 2007).

Ischemic heart disease especially sees biological sex differences in its pathogenesis.

Women are more likely to be affected by

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coronary microvascular dysfunction leading to chronic myocardial ischemia without obstructive coronary artery disease and are more likely to present with nausea, shortness of breath, and pain between the shoulder blades than men (Merz et al., 2017; Reis et al., 2001). Even the recognition of ischemic heart disease presentation in women is influenced by a gender bias; both men and women with ischemic heart disease who score high on feminine roles and personality traits on a questionnaire are at an increased risk of recurring ischemic heart disease, regardless of their sex (Greenwood et al., 2018). Given the complexity of gender differences in health and illness and historically common usage of men in clinical trials, it becomes clear that gender differences need to change to truly represent gender diversity.

Lack of Diversity in Clinical Trials Results in Reduced Treatment Success for Minorities The lack of diversity in clinical trials has always existed, but not much was known about it outside the scientific community itself. In 2018, journalists writing for ProPublica published an eye-opening article about Ninlaro, a favorable new drug for multiple myeloma (Chen & Wong, 2018). The pill form of Ninlaro’s drug allowed patients to avoid painful injections and IV treatments generally used to treat this blood cancer, and it proved effective in preventing metastases during a six month study. Only after the Federal Drug Administration (FDA) approved the drug in 2015 was it recognized that the trials had a major limitation: a lack of racial diversity. While 20% of Americans affected by multiple myeloma are African American, only 13 of the 722 participants in the trials were black (Bhatnagar et al., 2017). Socioeconomic status has been identified as a risk factor for many cancers through its potential correlation with lifestyle risk factors and/or accessibility to healthcare services, so a lack of socioeconomic diversity in cancer drug trials may misrepresent treatment efficacy (Marinac et al., 2020). Not only did this uncover the drastic gap between the racial diversity of the participants in the trials, but it illustrated the implications of the lack of diversity in clinical trials to the public.

"Gender differences in social determinants of health and illness have been observed through food consumption patterns and nutrition, where studies have found that in some countries— particularly in South Asia—male children receive greater amounts of food than female children."

Multiple myeloma is not the only cancer that has seen treatments derived from test samples consisting of little to no minorities.

Black participation has only achieved 10% involvement in trials of two of the thirty-one

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Figure 2: An FDA analysis of 31 cancer drugs approved since 2015 found that 24 of the drug trials featured fewer than 5 percent of black participants, when African Americans make up 13.4% of the American population. Of the 31 drugs, 13 drugs targeted cancers were that most prevalent in white Americans, 12 drugs targeted cancers that were most prevalent in black Americans, and 6 targeted cancers targeted cancers that were “similar risk” in both black and white Americans; “similar risk” cancers refer to those where African Americans are at least 80% as likely as white Americans to be diagnosed with a cancer. Of the 31 drugs, white Americans were the largest group represented in the clinical trials of drugs (Chen & Wong, 2018).

Source: Wikimedia Commons

"Clark and colleagues approached the five critical barriers to minority involvement by categorizing the approaches into major themes: reinforcing personal health, ensuring safety, confirming clear information, appreciating involvement, and emphasizing emotional support."

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cancer drugs available: Darzalex, which actually is for multiple myeloma and whose clinical trials had exactly 10% black participants, and Yondelis, which targets two different types of soft tissue cancers (Chen & Wong, 2018). Furthermore, breast cancer mortality rates among black and non-Hispanic white women reveal potential contributing factors to the mortality disparity; black women are less likely to be diagnosed with breast cancer than white women, but they are also more likely to die from it (Doamekpor & Zuckerman, 2014). It took over a decade for researchers to realize that black women are more likely to be diagnosed with triple negative breast cancer, a more aggressive form of breast cancer with fewer treatment options, than white women, who more often suffer from estrogen-receptor positive breast cancer that is successfully treated with Tamoxifen and other newly approved aromatase inhibitor hormone therapies (Amirikia et al., 2011; Early Breast Cancer Trialists’ Collaborative Group (EBCTCG), 2005). From this, it can be deduced that most forms of treatment for breast cancer have been tested for and catered to the forms of breast cancer that are more prevalent in white women, barring black women from effective treatment.

This also highlights the need for black women to be the focus of breast cancer treatment studies, as they have been overlooked for decades.

Approaches to Advancing Inclusion in Clinical Trials Clinical trials often feature homogeneity in some form in order for findings to be established for a certain population (e.g., a sample of asthma in children aged 4-14 or a sample of liver disease in Asian women), but generalized findings do not effectively contribute to clinical knowledge. Many of the barriers that prevent minority groups from participating in clinical trials are preventable and/or can be minimized, such as mistrust, discomfort with the clinical trial process, lack of information regarding the clinical trial process, time and resource accessibility associated with clinical trial participation, and lack of clinical trial awareness (Clark et al., 2019). While increasing diversity in clinical trials is a challenging process that requires time and effort, numerous studies have outlined potential solutions. Clark and colleagues approached the five critical barriers to minority involvement by categorizing the approaches into major themes: reinforcing personal health, ensuring safety, confirming clear information, appreciating involvement, and emphasizing emotional support (2019). The study found that patients often feared being a “guinea pig” and lacked trust in the research community, and patients were also frequently influenced by their friends’ and families’ opinions on participating in clinical trials. To address these concerns, it is important for physicians to not only educate patients about what the clinical trial process entails, but also

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to directly refer patients to certain clinical trials.

Many patients remain with the same physician for years, and consequently, physician-patient relationships are established through a trust that is not shared with researchers to the same extent.

Another factor to consider when examining the lack of diversity in clinical trials is the changing face of medicine. As new biotechnology is developed and the field of telemedicine has expanded to allow patients access to physicians from home (e.g., while quarantining during the Covid-19 pandemic), the members of the scientific community have also diversified as there are more means to connect to patients in rural and remote populations; this requires more healthcare professionals of similar backgrounds (Toh et al., 2020). A key step to increase diversity in clinical trials is recruiting more female and minority physicians into the trials, as patients are more comfortable around and seek physicians of their own race (Coakley et al., 2012). Furthermore, as previously mentioned, mistrust may be a critical barrier to increased diversity in clinical trials that must to be overcome. Historical involvement of minorities in clinical trials has not always been ethical, and this medical exploitation has had a great influence in tarnishing the relationship between minority patients and researchers.

Approaches to combat this have been outlined in various studies; Coakley et al. has identified organizations—the National Clinical Trials Network, National Minority AIDS Council, Project Increase Minority Participation and Awareness of Clinical Trials (National Medical Association’s IMPACT project), and the National Hispanic Research Network—dedicated to training minority and female physicians in clinical trial protocols, and research from the University of Maryland has signified that having a team member with a similar cultural background or an extensive knowledge of the cultural norms within a targeted minority group would contribute to establishing greater trust between the research team and the minority group (Garza et al., 2017).

Barriers to diversity in clinical trials also extend beyond the participants as researchers themselves have to take responsibility for the recruitment of potential minority participants as well. Researchers have to be aware of the demographics where a disease is most prevalent in and the importance of conveying information regarding trial facts, their risks and benefits, and culturally sensitive terms to

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participants in a study. Physicians are often the ones who introduce the option of clinical trials in the first place, therefore playing a pivotal role in recruiting minority participants. Their more personal relationship with the patients enables them to understand their patients on a personal level and clearly communicate the details of a clinical trial in the most effective manner (Howerton et al., 2007). While physician bias has been found to prevent the referral of potentially eligible patients for certain clinical trials, it becomes evident that physicians are the link between patients and the scientific research community that may allow increased minority involvement in clinical trials (Grunfeld et al., 2002).

Looking Ahead Much of what is known today about diseases and their treatments have been gathered from studies of majority groups, giving results that are often inaccurate or misrepresentative for minority groups. Minority health has not seen the same progress that majority health has.

With the push for civil rights and inclusion in more industries within the United States, the push toward equal representation has found its way into research as well, where the participation gap of minorities in clinical trials has begun to be prioritized after being overlooked for nearly the entirety of biomedical research. Even so, the deficit created by decades of minority exclusion in clinical trials will be difficult to correct. Acknowledging the distinctions between minority and majority risk factors in health and bridging the gap between the scientific community and the actual patients will not only benefit the health of minority groups, but it will also contribute to and advance of science and benefit all of humanity. The journey to full representation in clinical trials will not be an easy one, but the current push towards more inclusive studies is promising. Now, all that is left is to continue pushing for minority involvement and equality in clinical trials in the future.

"Historical involvement of minorities in clinical trials has not always been ethical, and this medical exploitation has had a great influence in tarnishing the relationship between minority patients and researchers."

References Akli, S., Boue, J., Sandhoff, K., Kleijer, W., Vamos, E., Young, E., Gatti, R., Di Natale, P., Motte, J., Vanier, M. T., Maire, I., Miranda, C., Salvaire, R., Kahn, A., & Poenaru, L. (1993). Collaborative Study of the Molecular Epidemiology of Tay-Sachs Disease in Europe. European Journal of Human Genetics, 1(3), 229–238. https://doi.org/10.1159/000472416 Alsan, M., & Wanamaker, M. (2018). TUSKEGEE AND THE HEALTH OF BLACK MEN. The Quarterly Journal of Economics, 133(1), 407–455. https://doi.org/10.1093/qje/qjx029

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Amirikia, K. C., Mills, P., Bush, J., & Newman, L. A. (2011). Higher population-based incidence rates of triple-negative breast cancer among young African-American women. Cancer, 117(12), 2747–2753. https://doi.org/10.1002/cncr.25862 Bhatnagar, V., Gormley, N., Kazandjian, D., Goldberg, K., McKee, A. E., Blumenthal, G., Farrell, A. T., & Pazdur, R. (2017).

FDA Analysis of Racial Demographics in Multiple Myeloma Trials. Blood, 130(Supplement 1), 4352–4352. https://doi. org/10.1182/blood.V130.Suppl_1.4352.4352 Borooah, V. K. (2004). Gender bias among children in India in their diet and immunisation against disease. Social Science & Medicine, 58(9), 1719–1731. https://doi.org/10.1016/S02779536(03)00342-3 Brockie, T. N., Heinzelmann, M., & Gill, J. (2013, December 9). A Framework to Examine the Role of Epigenetics in Health Disparities among Native Americans [Review Article]. Nursing Research and Practice; Hindawi. https://doi. org/10.1155/2013/410395 Chen, C., & Wong, R. (2018, September 19). Black Patients Miss Out On Promising Cancer Drugs. ProPublica. https://www. propublica.org/article/black-patients-miss-out-on-promisingcancer-drugs?token=F1W4XoVHukeDvXTmrb8HqM4rOmJyOjp Clark, L. T., Watkins, L., Piña, I. L., Elmer, M., Akinboboye, O., Gorham, M., Jamerson, B., McCullough, C., Pierre, C., Polis, A. B., Puckrein, G., & Regnante, J. M. (2019). Increasing Diversity in Clinical Trials: Overcoming Critical Barriers. Current Problems in Cardiology, 44(5), 148–172. https://doi.org/10.1016/j. cpcardiol.2018.11.002 Clayton, J. A. (2016). Studying both sexes: A guiding principle for biomedicine. The FASEB Journal, 30(2), 519–524. https://doi. org/10.1096/fj.15-279554 Coakley, M., Fadiran, E. O., Parrish, L. J., Griffith, R. A., Weiss, E., & Carter, C. (2012). Dialogues on Diversifying Clinical Trials: Successful Strategies for Engaging Women and Minorities in Clinical Trials. Journal of Women’s Health, 21(7), 713–716. https://doi.org/10.1089/jwh.2012.3733 Deheeger, M., Bellisle, F., & Rolland‐Cachera, M. F. (2002). The French longitudinal study of growth and nutrition: Data in adolescent males and females. Journal of Human Nutrition and Dietetics, 15(6), 429–438. https://doi.org/10.1046/j.1365277X.2002.00396.x Doamekpor, L. A., & Zuckerman, D. M. (2014). Lack of diversity in cancer drug clinical trials may exacerbate racial disparities in mortality rates. Cancer Epidemiology, 38(5), 645–646. https:// doi.org/10.1016/j.canep.2014.06.007 Early Breast Cancer Trialists’ Collaborative Group (EBCTCG).

(2005). Effects of chemotherapy and hormonal therapy for early breast cancer on recurrence and 15-year survival: An overview of the randomised trials. The Lancet, 365(9472), 1687–1717. https://doi.org/10.1016/S0140-6736(05)66544-0 Eichler, E. E. (2019). Genetic Variation, Comparative Genomics, and the Diagnosis of Disease. New England Journal of Medicine. https://www.nejm.org/doi/10.1056/NEJMra1809315 Garza, M. A., Quinn, S. C., Li, Y., Assini-Meytin, L., Casper, E. T., Fryer, C. S., Butler, J., Brown, N. A., Kim, K. H., & Thomas, S. B. (2017). The influence of race and ethnicity on becoming a human subject: Factors associated with participation in research. Contemporary Clinical Trials Communications, 7,

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57–63. https://doi.org/10.1016/j.conctc.2017.05.009 Graham, G. (2015). Disparities in Cardiovascular Disease Risk in the United States. Current Cardiology Reviews, 11(3), 238– 245. https://doi.org/10.2174/1573403X11666141122220003 Greenwood, B. N., Carnahan, S., & Huang, L. (2018). Patient– physician gender concordance and increased mortality among female heart attack patients. Proceedings of the National Academy of Sciences of the United States of America, 115(34), 8569–8574. https://doi.org/10.1073/ pnas.1800097115 Grunfeld, E., Zitzelsberger, L., Coristine, M., & Aspelund, F. (2002). Barriers and facilitators to enrollment in cancer clinical trials: Qualitative study of the perspectives of clinical research associates. Cancer, 95(7), 1577–1583. https://doi.org/10.1002/ cncr.10862 Howerton, M. W., Gibbons, M. C., Baffi, C. R., Gary, T. L., Lai, G. Y., Bolen, S., Tilburt, J., Tanpitukpongse, T. P., Wilson, R. F., Powe, N. R., Bass, E. B., & Ford, J. G. (2007). Provider roles in the recruitment of underrepresented populations to cancer clinical trials. Cancer, 109(3), 465–476. https://doi. org/10.1002/cncr.22436 Inter-Parliamentary Union. (2019, February 1). Women in Parliaments: World Classification. Inter-Parliamentary Union. http://archive.ipu.org/wmn-e/classif.htm Jeon, C. Y., & Murray, M. B. (2008). Diabetes Mellitus Increases the Risk of Active Tuberculosis: A Systematic Review of 13 Observational Studies. PLOS Medicine, 5(7), e152. https://doi. org/10.1371/journal.pmed.0050152 Kim, J. H., & Scialli, A. R. (2011). Thalidomide: The Tragedy of Birth Defects and the Effective Treatment of Disease.

Toxicological Sciences, 122(1), 1–6. https://doi.org/10.1093/ toxsci/kfr088 Kuzawa, C. W., & Sweet, E. (2009). Epigenetics and the embodiment of race: Developmental origins of US racial disparities in cardiovascular health. American Journal of Human Biology, 21(1), 2–15. https://doi.org/10.1002/ ajhb.20822 Larme, A. C. (1997). Health care allocation and selective neglect in rural Peru. Social Science & Medicine, 44(11), 1711–1723. https://doi.org/10.1016/S0277-9536(96)00373-5 Liu, K. A., & Mager, N. A. D. (2016). Women’s involvement in clinical trials: Historical perspective and future implications.

Pharmacy Practice, 14(1). https://doi.org/10.18549/ PharmPract.2016.01.708 Marinac, C. R., Ghobrial, I. M., Birmann, B. M., Soiffer, J., & Rebbeck, T. R. (2020). Dissecting racial disparities in multiple myeloma. Blood Cancer Journal, 10(2), 1–8. https://doi. org/10.1038/s41408-020-0284-7 Meikle, J. (2016, March 6). Thalidomide “caused up to 10,000 miscarriages and infant deaths in UK.”The Guardian. https:// www.theguardian.com/society/2016/mar/06/thalidomidecaused-up-to-10000-miscarriages-infant-deaths-uk Mensah, G. A. (2018). Cardiovascular Diseases in African Americans: Fostering Community Partnerships to Stem the Tide. American Journal of Kidney Diseases : The Official Journal of the National Kidney Foundation, 72(5 Suppl 1), S37–S42. https://doi.org/10.1053/j.ajkd.2018.06.026

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Merz, C. N. B., Pepine, C. J., Walsh, M. N., & Fleg, J. L. (2017).

Ischemia and No Obstructive Coronary Artery Disease (INOCA): Developing Evidence-based Therapies and Research Agenda for the Next Decade. Circulation, 135(11), 1075–1092. https://doi.org/10.1161/CIRCULATIONAHA.116.024534 Mitchell, B. D., Stern, M. P., Haffner, S. M., Hazuda, H. P., & Patterson, J. K. (1990). Risk factors for cardiovascular mortality in Mexican Americans and non-Hispanic whites. San Antonio Heart Study. American Journal of Epidemiology, 131(3), 423–433. https://doi.org/10.1093/oxfordjournals.aje.a115517 Oxford Advanced English Dictionary. (2020). Minority. In oxfordlearnersdictionaries.com. Retrieved November 30, 2020, from https://www.oxfordlearnersdictionaries.com/us/ definition/american_english/minority Reis, S. E., Holubkov, R., Smith, A. J. C., Kelsey, S. F., Sharaf, B. L., Reichek, N., Rogers, W. J., Merz, C. N. B., Sopko, G., & Pepine, C. J. (2001). Coronary microvascular dysfunction is highly prevalent in women with chest pain in the absence of coronary artery disease: Results from the NHLBI WISE study. American Heart Journal, 141(5), 735–741. https://doi. org/10.1067/mhj.2001.114198 Rosenbaum, L. (n.d.). The Hideous Truths Of Testing Vaccines On Humans. Forbes. Retrieved November 13, 2020, from https://www.forbes.com/sites/leahrosenbaum/2020/06/12/ willowbrook-scandal-hepatitis-experiments-hideous-truthsof-testing-vaccines-on-humans/?sh=3f922a12279c Solovieff, N., Hartley, S. W., Baldwin, C. T., Klings, E. S., Gladwin, M. T., Taylor, J. G., Kato, G. J., Farrer, L. A., Steinberg, M. H., & Sebastiani, P. (2011). Ancestry of African Americans with Sickle Cell Disease. Blood Cells, Molecules & Diseases, 47(1), 41–45. https://doi.org/10.1016/j.bcmd.2011.04.002 THE EDITORS. (2018, September 1). Clinical Trials Have Far Too Little Racial and Ethnic Diversity. Scientific American. https:// doi.org/10.1038/scientificamerican0918-10 Toh, N., Pawlovich, J., & Grzybowski, S. (2016). Telehealth and patient-doctor relationships in rural and remote communities. Canadian Family Physician, 62(12), 961–963.

Vlassoff, C. (2007). Gender Differences in Determinants and Consequences of Health and Illness. Journal of Health, Population, and Nutrition, 25(1), 47–61.

Zhong, J., Colicino, E., Lin, X., Mehta, A., Kloog, I., Zanobetti, A., Byun, H.-M., Bind, M.-A., Cantone, L., Prada, D., Tarantini, L., Trevisi, L., Sparrow, D., Vokonas, P., Schwartz, J., & Baccarelli, A. A. (2015). Cardiac autonomic dysfunction: Particulate air pollution effects are modulated by epigenetic immunoregulation of Toll-like receptor 2 and dietary flavonoid intake. Journal of the American Heart Association, 4(1), e001423. https://doi.org/10.1161/JAHA.114.001423

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Structural Racism: A Crisis Amidst the Pandemic

BY HUBERT GALAN-VARGAS ’23 Cover image: A young woman is holding a sign that says, “Racism is a Pandemic too,” emphasizing the point that racism and racial injustice should be taken as seriously as the ongoing COVID-19 pandemic Source: Wikimedia Commons

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Introduction In March 2020, the World Health Organization declared the outbreak of the novel coronavirus (COVID-19) a pandemic, as it swept across 115 different countries and killed, at that point, nearly 4,000 people and infected nearly 120,000. As of October 2020, the COVID-19 pandemic has led to over 1 million deaths and nearly 40 million confirmed cases of infection.

The developing pandemic has caused some nations to take serious preventative measures to limit the spread of the virus, leading to a complete stop in the rise of cases in some countries (Who, 2020). In the United States, the politicization of the pandemic and lack of governmental action has led the virus to propagate rapidly and expansively.

Currently, the United States leads the world in coronavirus cases and deaths, with 8 million confirmed cases and roughly 200,000 deaths.

While every American is experiencing a level

of vulnerability due the virus, it is clear that the virus is not affecting everyone equally. Race and ethnicity is a risk factor for contracting COVID-19: the number of cases is more than 2.6 times and 2.8 times higher for Black and Latino people, respectively (cdc.gov, 2020).

What is causing this reality? While the issue is complex, it can be understood by examining the intersection of healthcare and structural racism in the U.S.

What is Healthcare and What Does it Look Like in the U.S? Healthcare is a general term that is used to describe the processes by which a person receives health services in order to maintain or improve health. The processes most fundamentally include diagnosis, treatment and recovery, all of which are in reference to primary and secondary forms of medical treatment and other areas of health (e.g.

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Figure 1: A medical professional is wearing full PPE equipment and performing a nasal swab for a COVID-19 test Source: Wikimedia Commons

optometry and dentistry). Healthcare is delivered to patients by licensed and trained medical professionals, including doctors and nurses. In the U.S., receiving health services comes at a direct financial cost to the recipients of said healthcare. The prices that patients are exposed to are determined through the consideration of various factors, including the demand of the service, the resources required, the availability of said resources, and the labor required to perform the services. Within the financial system of the U.S., prices and payments in healthcare are meant to incentivize healthcare providers to ensure quality of care.

In this way, the privatization of healthcare has been maintained in our society to a point where many people face multiple obstacles in accessing basic forms of healthcare. The federal government has since established programs meant to alleviate the problems and inequities caused by privatized healthcare, such as Medicare and Medicaid. Medicare provides health insurance to citizens over the age of 65 and serves some younger disabled people, whereas Medicaid is a federal program that is run by state governments and serves lowincome individuals. While the presence of these programs has increased services to various vulnerable populations, the size of uninsured people remains high (hhs.gov). Aside from subsidized federal programs, many Americans (nearly half the population) receive health insurance through their employer.

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How has the U.S Healthcare System Been Impacted by the Pandemic?

Since the start of the pandemic, the extent of health insurance coverage in the U.S has been significantly undermined. This has been in part due to the rapid surge in unemployment, which has consequently caused people to lose their employer-sponsored insurance.

Moreover, the financial losses by many businesses due to the pandemic have caused employers to cut insurance as a means of alleviating financial burden. Additionally, the blow to health insurance coverage has been exacerbated due to lack of action by the federal government (Blumenthal, 2020). When the Affordable Care Act (ACA) was finalized into law, it ensured that citizens who unexpectedly lost their employer-sponsored insurance could be eligible for federal subsidies to reinsure them with individual-privatized insurance.

However, the current federal administration refuses to open new special enrollment periods to allow recently unemployed people to apply for the subsidized insurances. This means that Americans who are meant to be protected through current laws will continue to be uninsured through the span of the pandemic, which is especially dangerous given the risks of contracting the virus and the costs associated with it (Blumenthal, 2020).

"Health care providers are experiencing immense financial strain, which is preventing them from attending to healthcare emergencies due to the pandemic.

The providers who are most impacted include those in rural areas and those that primarily treat lowincome populations."

Health care providers are also experiencing immense financial strain, which is preventing them from attending to healthcare emergencies due to the pandemic. The providers who are most impacted include those in rural areas 83

Figure 2: The aftermath of a petrochemical storage site exploding.

Source: Wikimedia Commons

and those that primarily treat low-income populations. The main source of financial strain is due to increased demand for health care services and the decrease in avenues of revenues (Blumenthal, 2020). This development has been primarily due to the reduction in routine, officebased services, which have ceased in order to limit the propagation of the virus. In the U.S alone, health care providers are estimated to lose about $323 billion. The adverse effects of the pandemic on the healthcare system have reiterated the ways in which running healthcare as a business makes it vulnerable during economic recessions (Blumenthal, 2020).

What is Structural Racism and How Does it Affect Health?

"Structural racism is a broad term that is used to describe the legitimization of systems, including historical, cultural and institutional, that interact with each other to enforce and generate disadvantage for people of color (POC)."

Figure 3: An image of immigrant farm workers in the U.S standing on an agricultural field in California, wearing facemasks and other forms of PPEs. Agricultural laborers are classified as essential workers, and thus the laborers are mandated to continue working despite the ongoing pandemic Source: WIkimedia Commons

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Structural racism is a broad term that is used to describe the legitimization of systems, including historical, cultural and institutional, that interact with each other to enforce and generate disadvantage for people of color (POC) (Lawrence, 2004). While the issue is expansive and complex, structural racism perpetuates health inequalities through two primary avenues: social segregation and intergenerational drag (Gee, 2011).

Social segregation refers to the process of separating social groups, typically based on racial and ethnic identities. In the U.S., contemporary segregation is a remnant of the U.S.â&#x20AC;&#x2122;s racist history of slavery and discrimination.

It is maintained through current avenues of structural and systematic racist practices meant to limit interaction between white and POC communities (Gee, 2011). Racial segregation is the leading cause for the racial differences seen in socioeconomic status in the U.S. Segregation exacerbates limitations in educational and employment opportunities in communities of POC. The maintenance of low socioeconomic status in communities of color has concentrated poverty in a way that

also puts health at risk (Williams, 2001). First, communities with concentrated poverty isolate people from accessing resources needed to maintain adequate health, such as simple health services and healthy foods. Second, crime and inadequate living conditions are also concentrated in these areas, which can severely affect the physical and mental health of residents (Williams, 2001). Additionally, environmental racism, which refers to injustices that expose certain communities to environmental hazards, is prominent in communities of color with concentrated poverty. This may involve placing factories or other sources of pollutants in communities that are predominately POC. Environmental racism manifests itself in a variety of ways through the U.S and can increase the risks of developing health conditions such as asthma and even cancer in some cases (Holifield, 2001).

Intergenerational drag is a hypothesis that interprets contemporary disparities as being a result of cumulative issues faced by ancestors of certain social groups. The research that goes into understanding intergenerational drag as it relates to issues in health is based on the racist historical past of the U.S. Specifically, intergenerational traumas of slavery and historical racial segregation has been found to severely harm the health of Black people today to the point of making them vulnerable to diseases (Mohatt, 2014). The term coined â&#x20AC;&#x153;historical traumaâ&#x20AC;? refers to the ways in which health is influenced by biological and social factors which can be inherited from grandparents and parents. These inherited factors are influenced negatively by historical events. Historical trauma can be seen in the descendants of Indigenous, Jewish, and Black Americans in the U.S. (Mohatt, 2014).

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How the Pandemic is Impacting Black and Latino Americans The data show that Black people, despite being only 13% of the U.S. population, account for roughly 20% of coronavirus cases and over 22% of deaths. Similarly, Latino Americans make up roughly 18% of the U.S population but account for nearly 33% of the cases nationwide (Blumenthal, 2020). This contemporary issue can be best understood by looking at how structural racism perpetuates health disparities in the U.S healthcare system. As referenced above, racial segregation directly isolates communities of color from accessing educational and employment opportunities.

If access to education is curtailed, it may prevent people from gaining competitive and specialized jobs, which tend to pay more and have additional benefits such as health insurance (Blumenthal, 2020). Because of this, people of color continue to be inadequately insured, leading to the inability to easily access health services. This is also correlated with a higher prevalence of chronic illnesses, which can leave people more vulnerable to dying due to COVID-19. Additionally, people of color are also more likely to work jobs that are considered essential, leading them to be more likely to be exposed to large groups of people (cdc.gov).

Conclusion The COVID-19 pandemic has halted business as-usual and put every American in a position of vulnerability. While it is true that almost every American has been negatively impacted by the virus, it is imperative to understand that certain communities and demographics have fallen under even greater pressure.

That is, the virus is not affecting Americans equally. In the U.S., communities of color and low-income communities are most impacted by the pandemic, with deaths being nearly double in Black communities than it is in White communities. There are many circumstances that contribute to this reality. Structural racism encompasses many of the complexities that maintain and perpetuate disparity. It also facilitates contemporary social segregation and intergenerational drag, both of which create circumstances where people of color are not easily able to access adequate education, jobs, or health services. As a result, low income and predominantly communities of color are extremely vulnerable to the health and economic repercussions of the pandemic. The only way Americans will be able to overcome this pandemic is if we allocate attention,

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resources, and time to the communities and people put at risk due to structural, institutional and interpersonal racism.

References Blumenthal, David, et al. (2020). “Covid-19 — Implications for the Health Care System.” New England Journal of Medicine, vol. 383, no. 15, pp. 1483–1488., doi:10.1056/nejmsb2021088 Cdc.gov. (2020). “Health Equity Considerations & Racial & Ethnic Minority Groups." cdc.gov Gee, Gilbert C., and Chandra L. Ford. (2011). “Structural Racism And Health Inequities.” Du Bois Review: Social Science Research on Race, vol. 8, no. 1, pp. 115–132., doi:10.1017/ s1742058x11000130.

“Addressing Race Disparities in COVID-19.” (2020). hhs.gov.

Holifield, Ryan. (2001). “Defining Environmental Justice And Environmental Racism.” Urban Geography, vol. 22, no. 1, pp.

78–90., doi:10.2747/0272-3638.22.1.78.

Lawrence, Keith. (2004). “Chronic Disparity: Strong and Pervasive Evidence of Racial Inequalities POVERTY OUTCOMES.” Structural Racism Mohatt, Nathaniel Vincent, et al. (2014). “Historical Trauma as Public Narrative: A Conceptual Review of How History Impacts Present-Day Health.” Social Science & Medicine, vol.

106, pp. 128–136., doi:10.1016/j.socscimed.2014.01.043.

Redford, Gabrielle. (2020). “AAMC Releases Framework to Address and Eliminate Racism.” AAMC. Retrieved from www. aamc.org/news-insights/aamc-releases-framework-addressand- eliminate-racism.

“Rolling updates on coronavirus disease (COVID-19).” (2020). who.int Williams, David R, and Chiquita Collins. (2001). “Racial Residential Segregation: A Fundamental Cause of Racial Disparities in Health.” Public Health Reports, vol. 116, no. 5, pp. 404–416., doi:10.1016/s0033-3549(04)50068-7.

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Growing Organs in Vitro: A History of Discovery and a Future of Possibilities

BY JENNIFER CHEN â&#x20AC;&#x2122;23 Cover Image: Immunohistochemistry of a neural organoid grown from human induced pluripotent stem cells. The image shows the organoidâ&#x20AC;&#x2122;s morphology, specifically the layer of neural progenitors (red) and neurons (green, arrow).

Source: Wikimedia Commons

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Introduction and a History of Organoid Development The definition of an organoid differs across subfields. Generally, scientists have defined an organoid as an in vitro 3D structure that selforganizes, reproduces, and functions similarly to its real counterpart in vivo (Knoblich & Lancaster, 2014). These structures resemble real organs in structure and function, creating many opportunities for researchers and physicians to study human physiology. Scientists can use patient-specific organoids to test therapeutics and create personalized treatment plans, or they can delete or modify genes in organoid cells with CRISPR/CAS9 technology to understand organ physiology and disease pathology in further detail. As researchers develop more refined organoid models, physicians can potentially use organoids as a replacement for donor organs in transplants.

Experiments related to understanding the nature of tissue and organ growth, in the field of organogenesis and morphogenesis, were key to finally developing organoids. Since the beginning of the 20th century, scientists have tried to grow organs in vitro, starting with tissue fragments. Ross Harrison, a researcher at Yale University, was able to grow nerves using his hanging drop tissue culture technique, and he was the first person to grow living tissue from vertebrates in vitro (Millet & Gillette, 2012). Hanging drop tissue culture method is when a drop of liquid is allowed to hang from a coverslip which is placed on an indented microscope slide. In Harrisonâ&#x20AC;&#x2122;s original research, the drop of liquid had lymph and a piece of embryonic nerve tissue from a frog, and nerve tissue grew from it (Harrison, 1907). Researchers adapted this process to culture other tissues and have developed new methods such as the watch glass method, which uses a concave glass enclosed by a petri dish to grow a tissue DARTMOUTH UNDERGRADUATE JOURNAL OF SCIENCE

Figure 1: Diagram showing basement membrane, specifically its laminin network (blue), interacting with epithelial cells (yellow). Laminin and collagen networks (not shown) play an important role in regulating cell differentiation, especially in the epithelial tissue that grows at the beginning of organ development.

Source: Wikimedia Commons

fragment (Simian & Bissell, 2017). However, with these methods, researchers still had trouble maintaining long-term cultures of tissue due to tissue necrosis, nutrient depletion, waste accumulation, evaporation, and insufficient oxygen to the tissue (Millet & Gillette, 2012).

Research thus far focused on regenerating cells using dissociated cells in suspension collected from tissue samples. However, since these methods of suspension were not suitable for growing larger tissue structures like organs for long periods of time, scientists began experimenting with collagen, a fibrous protein in the cell basement membrane (Simian & Bissell, 2017). Basement membranes are extracellular matrix sheets that promote and regulate tissue formation (Jayadev & Sherwood, 2017). In 1956, Robert Ehrmann and George Geyâ&#x20AC;&#x2122;s research team successfully grew cells on a gel made of collagen derived from rat-tail tendons (Simian & Bissell, 2017). Around the same time, others regenerated adult mouse mammary gland tissue by using collagenase, an enzyme that breaks down collagen, to digest tissue samples and extract intact dissociated cells from the tissue of origin (Lasfargues, 1957). These cells could then be used to regenerate organspecific cells. Additionally, an experiment using a perfusion media of collagenase affirmed these results when the perfusion of a rat liver in situ produced intact, isolated hepatic cells similar in appearance and function to normal hepatic parenchymal cells (Berry & Friend, 1969). Ehrmann and Geyâ&#x20AC;&#x2122;s collagenase-based technique was also successful in growing FALL 2020

monolayers of human fetal liver cells (Bissel & Tilles, 1971). The researchers found that, in the presence of the growth medium, the liver cells began to reduce in function and organization after three days. In the absence of the growth medium, the liver cells showed increased function and organization but decreased in cell density by day 3 (Bissel & Tilles, 1971). By 1975, other scientists were able to grow liver cells that maintained their function and morphology for at least 20 days (Michalopoulos & Pitot, 1975).

They changed their technique by growing the cells on floating collagen gels instead of growing the cells completely submersed in the medium on the collagen gels, yet they still had not discerned the underlying mechanism for this success in their cultures. So, regulating and maintaining cell differentiation in long term cultures remained a mystery to scientists.

"By the 1980s, researchers began to understand the underlying mechanism that regulated tissue morphology and directed function.

A hypothesis was set forth that the basement membrane was responsible for regulating gene expression of cells."

By the 1980s, researchers began to understand the underlying mechanism that regulated tissue morphology and directed function. A hypothesis was set forth that the basement membrane was responsible for regulating gene expression of cells (Simian & Bissell, 2017). So, researchers needed to study the extracellular matrix of the Engelbreth-HolmSwarm (EHS) sarcoma to determine the specific constitution of the basement membrane. They concluded that the sarcoma has a matrix that produces similar components as basement membranes but in larger quantities, such as laminin and type IV collagen (Jayadev & Sherwood, 2017). Laminin is a protein complex that self-assembles to create a lattice structure 87

outside the cell. The protein is secreted early in development, initiating the formation of basement membranes, and it also is involved in cell differentiation and tissue formation (Jayadev & Sherwood, 2017). After the laminin network develops, collagen IV also begins to self-assemble into a network and is integrated into the basement membrane (Jayadev & Sherwood, 2017). The collagen IV network can resist tensile forces, stabilizing tissue to the basement membrane and allowing both to resist stress during movement (Jayadev & Sherwood, 2017). These components, extracted from the Source: Wikimedia Commons EHS sarcoma, are essential for regulating cell differentiation and tissue development as well as provide tissue stability. Researchers ultimately extracted components of the EHS sarcoma extracellular matrix to create Matrigel, a 3D gel containing key basement membrane proteins (Simian & Bissell, 2017).

Figure 2: An intestinal organoid growing from a single Lgr5+ stem cell, which is a multipotent adult intestinal stem cell. The image shows growth of the organoid (arrows), and the formation of the crypts at the sites of the Paneth cells. The Paneth cells are the granuleshaped yellow cells within the growths and are cells that produce enzymes and microbial related proteins. Paneth cells are also located adjacent to the intestinal stem cells in the crypts.

"Since the 1980s, scientists have now generated organoids resembling many different tissues.

Scientists have cultured stomach, intestinal, lung, thyroid, liver, kidney, hippocampal, neural, and optic cup organoids."

Finally, breakthroughs in stem cell research led to long-term cultures of organs. In 1996, scientists found that adult stem cells in organs were multipotent, so they could differentiate into various cell types depending on the organ they are harvested from (Reynolds & Weiss, 1996). By 2003, scientists had developed an appropriate method to identify and cultivate adult mammary stem cells (Dontu et al., 2003). In addition to adult stem cells, embryonic stem cells are useful in organoid research because they can divide an unlimited number of times and are pluripotent, so they can differentiate into cell types of any of the three germ layers (Thomson et al., 1998).

During embryogenesis, germ layers form and consist of cells that will ultimately differentiate into the various tissues and organs of the adult body (MacCord, 2013). So, embryonic stem cells can technically generate any organ type in organoid research. In 1998, researchers developed the methodology to culture human embryonic stem cell lines (Thomson et al., 1998).

By 2008, researchers were able to reprogram adult stem cells into pluripotent stem cells (Park, Lerou, Zhao, Huo, & Daley, 2008). This has not only allowed for more patient-specific treatments involving pluripotent stem cells, but also it opened up another option for researchers who are developing organoids.

Since these discoveries, researchers have been able to isolate the major components that allow organs to grow in the body. Researchers have also isolated multiple building blocks for organoids: adult stem cells, embryonic stem cells, or induced pluripotent stem cells. Now, researchers have developed long-term 3D

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culture systems to better understand organ physiology and pathology for its important applications in disease prevention.

Long-term organoid cultures: Intestines, Livers, and Brains Since the 1980s, scientists have now generated organoids resembling many different tissues.

Scientists have cultured stomach, intestinal, lung, thyroid, liver, kidney, hippocampal, neural, and optic cup organoids (Clevers, 2016).

This article will focus on neural, hepatic, and intestinal organoids. The first of these organoids to be developed in long-term culture was the epithelial intestinal organoid.

Intestinal Organoids Though researchers had already cultured intestinal epithelial cells, none cultured intestinal epithelium, specifically the cryptvillus axis, until 2009. Intestines consist of crypts, where adult stem cells differentiate, and villi, which extend around the crypts into the lumen of the intestine and absorb nutrients from digested food. Toshiro Sato and a group of researchers successfully cultured a rodent crypt-villus structure that resembled a normal gut from a single Lgr5 stem cell, which is an adult intestinal mouse stem cell found in intestinal crypts (Sato, 2009). The researchers were successful on multiple fronts. Firstly, they cultured all four differentiated cell types from the stem cell and maintained the polarity of the epithelium. Secondly, they designed a culture system that allowed for long-term growth of the epithelial organoidâ&#x20AC;&#x201D;the organoid grew for eight months. The researchers attributed part of their success due to their decision to develop a growth factor cocktail specific to the genes responsible for crypt and intestinal

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biomarkers of real hepatocytes such as albumin.

Furthermore, the stem cells and proliferating cells self-organized into structures, such as the canaliculi which transport bile acids, which are secreted by hepatocytes, into the bile duct.

Figure 3: Diagram of the methodology used to culture neural organoids.

Source: Wikimedia Commons

To test if these human hepatocyte organoids were functional in vivo, researchers transplanted the organoids into mice deficient in the fumarylacetoacetate hydrolase (FAH) enzyme which is expressed in hepatocytes (Clevers et al., 2013). The FAH enzyme is expressed in hepatocytes to metabolize the amino acid tyrosine (FAH gene, n.d.). Without the FAH enzyme, mice on a normal diet cannot process food and will accumulate toxins in their hepatocytes, thus slowly losing their liver cells and dying. The mice who had organoids transplanted and ate a normal diet survived, showing that the organoids were capable of acting as functioning tissue in vivo (Clevers et al., 2013).

Neural Organoids

growth. Cells that grew from the single stem cell differentiated asymmetrically, and the differentiated cell types self-organized (Sato, 2009). Furthermore, their organoid was selfrenewing. The cells generated from the stem cells in the crypts would migrate upwards in the villi, die at the tips of the villi, and accumulate in the lumen of the organoid (Sato, 2009). This process in the intestinal organoids mimics the true process in the body, where cells migrate to the top of the villi and die of apoptosis, thus being discarded in the lumen of the organ.

After the epithelial intestine was successfully cultured, other researchers applied the same methodology and basic components of the growth factor cocktail in other organoid research. Depending on the genetic constitution of the tissue culture in question, researchers have adapted the growth factor cocktail, including to grow different epithelial organoids.

Liver Organoids Researchers adapted the methods to grown epithelial organoids to grow hepatic organoids, using stem cells that grew into functional hepatocytes (Clevers et al., 2013). The researchers confirmed that the hepatocytes were functional as they produced the

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Embryonic and pluripotent stem cells have also been successful at culturing human neural organoids. In 2013, Madeline Lancaster and her team were the first to successfully culture human cerebral organoids (Lancaster et al., 2013). They let pluripotent stem cells aggregate and develop into embryoid bodies where, after six days, the three germ layers formed. Then, the researchers replaced the medium to only allow the neuroectodermal tissue to survive. The researchers placed this tissue into droplets of differentiation media, embedded it in Matrigel, and put in a spinning bioreactor or orbital shaker to increase absorption. After roughly 30 days, the researchers observed defined brain regions. The researchers confirmed that the cerebral organoids generated active neurons by observing calcium ion fluctuations. Thus, the organoid had proper neuronal differentiation and function (Lancaster et al., 2013).

"In 2013, Madeline Lancaster and her team were the first to successfully culture human cerebral organoids."

Though Lancasterâ&#x20AC;&#x2122;s team was successful in growing the parts of a brain, the arrangement of these parts was random and uncontrolled (Bagley et al., 2017). In 2017, Josh Bagley and fellow researchers developed a co-culture protocol to grow cerebral organoids that had an axis where parts of the brain were properly located relative to this axis. Instead of having unorganized and indistinct neuronal layers in a neural organoid, the researchers specifically grew dorsal organoids and ventral organoids by modifying the differentiation medium

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Figure 4: A neural organoid.

Source: Wikimedia Commons

to increase expression of dorsal and ventral biomarkers, respectively. Then, the researchers placed these two organoids together into a Matrigel droplet and differentially labeled the different cell types with reporters to track interneuron migration. When the organoids are co-cultured, they fused together over time (Bagley et al., 2017). Through this protocol, the researchers were able to create a cerebral organoid with a dorsal-ventral axis. Using this organoid model, neuron migration can be monitored in real time, as differentially labeled cells migrate between the two organoids (Bagley et al., 2017). Now, researchers can culture any pair of cerebral regions and fuse them together for further studies.

Current Uses and Advantages of Organoids Scientists have already touted the myriad of organoid applications. Researchers have used organoids to model various pathways or developmental events in organs, especially when the pathways are unique to humans.

Organoids not only allow for these differential pathways to be studied using human tissue but also provide an option that reduces animal experimentation in the lab.

"Organoid technology will open up the possibility for personalized medicine in many instances. For example, physicians can use organoids to perform differential drug sensitivity testing."

Organoid technology will open up the possibility for personalized medicine in many instances. For example, physicians can use organoids to perform differential drug sensitivity testing (Clevers, 2016). For drugs, especially cancer therapeutics, whose efficacy for each specific patient is in question, scientists can culture patient-specific organoids and test them with different drugs (Clevers, 2016). Once a physician administers the drug to the patient, the physician can compare the patientâ&#x20AC;&#x2122;s response to the predictions made based on organoid testing (Clevers, 2016). Researchers have also used organoids to understand disease development and develop therapies. They can recapitulate cancers using organoids and study the root components and mutations behind these diseases using CRISPR/CAS9 technology (Clevers, 2016).

Researchers have also used organoids to study more complex organs that differ from those of model organisms. For example, researchers have turned to neural organoids to isolate mutations that cause certain brain disorders (Lancaster et al., 2013). Microcephaly, a disorder whose symptoms most noticeably cause a smaller diameter skull, is caused by a mutation in the Nde1 gene, and it does not occur in mice.

Therefore, Madeline Lancaster and her team grew neural organoids using stem cells from a patient with microcephaly to model and

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study the disorder in culture. They found that the resulting organoids showed the small brain phenotype and that the patient organoids underwent premature neuronal differentiation.

In the control organoids without the disorder, all progenitor cells underwent symmetric division to produce more progenitor cells and proliferate (Lancaster et al., 2013). Only later did these progenitor cells undergo asymmetric division and differentiate into neuronal cells. Thus, the researchers concluded that the premature neurogenesis is likely to create a small brain phenotype because with decreased symmetric division in this early stage, progenitor cell amplification is incomplete. Once asymmetric division begins, fewer progenitor cells can divide and differentiate into neuronal cells, which explains the substantial reduction in neuron quantity in brains with microcephaly (Lancaster et al., 2013). They also performed exome sequencing on the patient to isolate the specific mutation in the CDK5RAP2 gene, which codes for the CDK5 regulator subunitassociated protein 2 and caused progenitor cells to differentiate in the early stages into neuronal cells. The protein subunit is involved in mitotic spindle orientation and the binding of microtubules to centrosomes. With this mutant mitotic spindle orientation, progenitor cells divide asymmetrically (Lancaster et al., 2013).

The researchers confirmed this hypothesis by deleting the CDK5RAP2 gene in an organoid, which showed similar effects of increased neuron production (Lancaster et al., 2013).

Scientists have also used organoids as models to study infectious diseases and their impact on these artificial organs opposed to on the cellular level using cell lines. For example, researchers were able to infect neural organoids with the Zika virus (ZIKV) and study the impact of the virus on neurons (Qian et al., 2016). They discovered that ZIKV increased cell death, decreased cell proliferation in the brain, and DARTMOUTH UNDERGRADUATE JOURNAL OF SCIENCE

reduced neuronal cell-layer volume, similar to brains with microcephaly. The researchers were able to further use organoids to test different potential ZIKV therapies.

The Future of Organoids Given the current research landscape of organoids, they will likely play a formative role in discoveries regarding developmental biology, cancer, and other tissue-related issues as researchers can develop novel therapeutic strategies. Personalized medicine will become easier to design with organoids that allow differential drug and therapeutics testing. However, as useful as organoids are now, current organoids still do not have the complexity of nerves, blood vessels, and immune cells that real organs have (Clevers, 2016). In the future, researchers can hope to tackle replicating cellular and microbial details of the human body in organoids.

Biotechnology like tissue engineering and microfabrication can help improve the culturing of organoids in the future (Simian & Bissell, 2017). For example, researchers can engineer the extracellular matrix that stem cells are cultured on to be more uniform than their naturally derived counterparts (Kim et al., 2017).

Researchers can also engineer the extracellular matrix to grow organoids more efficiently (Kim et al., 2017). Using microfabrication technology, which is technology that works on a micrometer scale, researchers can culture organoids with more precise control. As organoid models become more accurate, researchers can begin developing the multi-organoid system called a â&#x20AC;&#x153;body on a chip,â&#x20AC;? where multiple organoids of different tissue types are brought together to function as a system (Kim et al., 2017).

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Lastly, transplantation of organoids into patients may become possible in the future as organoid models become more sophisticated and realistic in function and structure. Scientists have already explored using organoids in the field of regenerative medicine. For example, researchers transplanted human fetal enterospheres, which are tissue cultured from fetal intestinal progenitor cells, into rodents with damaged colons (Fordham et al., 2013).

The cells of the organoids quickly grafted onto tissue and successfully differentiated into cell types found in the colon and presented with biomarkers only found in colon cells (Fordham et al., 2013). Thus, the researchers discovered that intestinal organoids, developed from immature progenitors, can be transplanted to differentiate and regenerate an organismâ&#x20AC;&#x2122;s organ in vivo.

Figure 5: Immunofluorescent intestinal rodent organoid that carries a mutation in the Adenomatous polyposis coli (APC) gene, leading to intestinal tumors.

Transplantation of organoids into humans, however, still remains a distant possibility.

Each type of organoid has its own technical challenges when cultured, and most organoids are still under-developed and missing key features such as blood vessels or nerves (Clevers, 2016). Furthermore, researchers are having difficulty culturing mature organoids such as kidney organoids in vitro, leaving the option to transplant the kidney organoid in its embryonic stage and wait for it to mature once it is in vivo (Naganuma & Nishinakamura, 2019).

This technique poses challenges as researchers will have to determine the optimal time to transplant the kidney. So far, researchers have cultured human organs in model organisms to mature them enough for research purposes (Naganuma & Nishinakamura, 2019).

Xenotransplantation of an organoid into model organisms, however, has its own technical and ethical issues such as rejection of the organoids and the issue of creating chimeras with humans and animals (Naganuma & Nishinakamura, 2019). Use of the organoid for further use in patients also poses issues such as the potential risk of infecting humans with unknown animal viruses.

"Transplantation of organoids into humans still remains a distant possibility.

Each type of organoid has its own technical challenges when cultured, and most organoids are still under-developed and missing key features such as blood vessels or nerves."

Source: Wikimedia Commons

Additionally, there are already debates in the scientific community around the issue of chimerism and the ethics of organoid xenotransplantation. Specifically, scientists are concerned as there is no current way for scientists to control the migration of transplanted human cells to the germ cells or into the brain (Naganuma & Nishinakamura, 2019). For example, when a group of researchers implanted a pig blastocyst containing human stem cells, the human cells were in the resulting embryo (Wu et al., 2017). Scientists have raised

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the concerns surrounding the transplantation of neural organoids into animals with the worries that the animals will become more “human” (Chen et al., 2019). As neural organoids become increasingly similar to real neural tissue in function and structure, researchers are concerned that the organoid may begin to experience consciousness and develops higher cognitive abilities such as sensitivity to pain. With these growing concerns regarding culturing brain organoids, researchers are also worried that transplanting brain organoids may cause an animal to experience self-awareness and be capable of rational thought (Chen et al., 2019). Though scientists’ own understanding of self-awareness and its origins is limited, the possibility of creating a chimera capable of self-awareness is slim with the current state of organoids (Chen et al., 2019). Ultimately, with this issue comes other ethical questions, such as finding the appropriate treatment of enhanced chimeras in providing more stimulating environments or legal protection.

References Bagley, J., Reumann, D., Bian, S., Lévi-Strauss, J., & Knoblich, J. (2017). Fused cerebral organoids model interactions between brain regions . Nature Methods, 743-751.

Berry, M. N., & Friend, D. S. (1969). High-yield preparation of isolated rat liver parenchymal cells: a biochemical and fine structural study. The Journal of cell biology, 506–520.

Bissel, M., & Tilles, J. G. (1971). Morphology and Function of Cells of Human Embryonic liver in Monolayer Culture. The Journal of cell biology, 222-231.

Chen, I., Wolf, J., Blue, R., Song, M., Moreno, J., Ming, G.-l., & Song, H. (2019). Transplantation of human brain organoids: revisiting the science and ethics of brain chimeras. Cell Press: Cell Stem Cell, 462-472 .

Clevers, H. (2016). Modeling Development and Disease with Organoids. Cell, 1586-1595.

Clevers, H., Huch, M., Dorrell, C., Bof, S., van Es, J., Li, V., . . .

Grompe, M. (2013). In vitro expansion of single Lgr5+ liver stem cells induced by Wnt-driven regeneration. Nature, 247-250.

Dontu, G., Abdallah, W., Foley, J., Jackson, K., Clarke, M., Kawamura, M., & Wicha, M. (2003). In vitro propagation and transcriptional profiling of human mammary stem/progenitor cells . Genes & development, 1253–1270.

FAH gene. (n.d.). Retrieved from Medline Plus: https:// medlineplus.gov/genetics/gene/fah/ Fordham, R., Yui, S., Hannan, N., Soendergaard, C., Madgwick, A., Schweiger, P., . . . Jensen, K. (2013). Transplantation of Expanded Fetal Intestinal Progenitors Contributes to Colon Regeneration after Injury . Cell Stem Cell, 734-744.

Jayadev, R., & Sherwood, D. (2017). Basement Membranes.

Current biology, 207-211.

Kim, G.-A., Spence, J., & Takayama, S. (2017). Bioengineering for intestinal organoid cultures . Current Opinion in Biotechnology, 51-58.

Knoblich, J. A., & Lancaster, M. A. (2014). Organogenesis in a dish: modeling development and disease using organoid technologies . Science.

Lancaster, M., Renner, M., Martin, C.-A., Wenzel, D., Bicknell, L., Hurles, M., . . . Knoblich, J. (2013). Cerebral organoids model human brain development and microcephaly . Nature, 373379.

Lasfargues, E. Y. (1957). Cultivation and behavior in vitro of the normal mammary epithelium of the adult mouse. The Anatomical record, 117-129.

MacCord, K. (2013, November 17). Germ Layers. Retrieved from The Embryo Project Encyclopedia: https://embryo.asu. edu/pages/germ-layers Michalopoulos, G., & Pitot, H. C. (1975). Primary culture of parenchymal liver cells on collagen membranes.

Experimental cell research, 70-78.

Millet, L. J., & Gillette, M. U. (2012). Over a Century of Neuron Culture: From the Hanging Drop to Microfluidic Devices . The Yale journal of biology and medicine, 501-521.

Naganuma, H., & Nishinakamura, R. (2019). From organoids to transplantable artificial kidneys . Transplant International, 563-569.

Park, I.-H., Lerou, P., Zhao, R., Huo, H., & Daley, G. (2008).

Generation of human-induced pluripotent stem cells. Nature protocols, 1180-1186.

Qian, X., Nguyen, H. N., Song, M., Hadiono, C., Ogden, S., Hammack, C., . . . Kang, E. (2016). Brain-Region-Specific Organoids Using Mini-bioreactors for Modeling ZIKV Exposure . Cell, 1238-1254.

Reynolds, B. A., & Weiss, S. (1996). Clonal and population analyses demonstrate that an EGF-responsive mammalian embryonic CNS precursor is a stem cell. Developmental biology, 1-13.

Sato, T., Vries, R., Clevers, H., Snippert, H., de Wetering, M., Barker, N., . . . Peters, P. (2009). Single Lgr5 stem cells build crypt-villus structures in vitro without a mesenchymal niche .

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Simian, M., & Bissell, M. J. (2017). Organoids: A historical perspective of thinking in three dimensions . The Journal of cell biology, 31-40.

Thomson, J., Itskovitz-Eldor, J., Shapiro, S., Waknitz, M., Swiergiel, J., Marshall, V., & Jones, J. (1998). Embryonic stem cell lines derived from human blastocysts. Science, 11451147.

Wu, J., Platero-Luengo, A., Sakurai, M., Sugawara, A., Gil, M., Yamauchi, T., . . . Soto. (2017). Interspecies Chimerism with Mammalian Pluripotent Stem Cells . Cell, 473-486.

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Socioeconomic Influence on Chronic Pain: Psychological and Neurological

BY MAEEN ARSLAN ’23 Cover Image: This image shows nerves in the arms where chronic pain can be concentrated.

Certain chronic illnesses have symptoms where chronic pain is primarily musculoskeletal with certain nerves being a site of heightened discomfort.

Examining which nerves have heightened activity when patients experience pain is vital to treating the symptoms.

Source: Wikimedia Commons

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Introduction

Overview of Symptoms

Chronic diseases affect populations across all demographics, but they arguably have more pronounced effects on individuals without a stable environment. This “stable” environment would be one that is sufficiently calm and stimulus-free to decrease stress and incidences of disease triggers. Patients with chronic illnesses must learn to adapt to their situations to minimize pain. However, the research on varying types of chronic illnesses indicates that there are environmental triggers that can affect how symptoms and that there is a link to the patient’s financial stability and disease severity (Sears & Genuis, 2012). This paper will explore the effects of socioeconomic status on the presentation of chronic pain symptoms and will characterize this relationship from both the psychological and neurological perspectives.

To understand how the environment affects chronically ill patients, it is important to first learn about the symptoms they encounter. The somatic symptoms of patients with chronic pain include “fatigue, unrefreshing sleep, dyscognition, and mood disturbances” and can also involve “chronic fatigue syndrome/myalgic encephalomyelitis and musculoskeletal pain” (Crofford, 2015). More specific chronic conditions can involve targeted pain such as headaches, interstitial cystitis/irritable bladder, and pelvic pain (Crofford, 2015). These various manifestations of pain are often found together in patients with specific chronic illnesses. For example, if a patient suffers from diabetes - either type 1 or type 2 - they are at risk for diabetic neuropathy. Diabetic neuropathy can cause pain and numbness in the patient’s legs and feet and can be accompanied by digestive problems, issues with the urinary tract, and problems in the cardiovascular system (Mayo DARTMOUTH UNDERGRADUATE JOURNAL OF SCIENCE

The Socioeconomic Perspective

Figure 1: This image shows different areas where chronic pain is concentrated for fibromyalgia patients Fibromyalgia is a common chronic condition characterized by musculoskeletal pain.

Fatigue, cognitive disturbance, psychiatric and somatic symptoms accompany the condition highlighting the various areas of chronic pain a patient can experience (Bhargava & Hurley 2020).

There is no definite cure for chronic pain, so symptoms can only be treated and managed.

A patient’s environment therefore becomes a key factor in symptom severity and how often they are present. Those of lower socioeconomic status are often unable to receive adequate treatment for any illness they may have, so symptoms of chronic illness can worsen in these individuals Lower income patients may be at a higher risk for chronic diseases and the presentation of symptoms including chronic Source: Wikimedia Commons pain since they may be met with housing insecurity or the inability to pay for healthy food, both of which can introduce stress into the patient’s life (Sears & Genuis, 2012).

Clinic, 2020). If a patient is diagnosed with Parkinson’s disease, their chronic pain will be concentrated on muscles involved with movement, such as tremors in arms and legs, but the patient will also experience non-motor related complications, including depression, anxiety, and fatigue. However, patients with Parkinson’s often have their pain overlooked, as physicians focus primarily on treating movement and cognition. After further neurodegeneration, the types of chronic pain experienced include musculoskeletal, dystonic (abnormal muscle contractions), radicular (nerve) pain, and central pain caused by damage to the central nervous system which includes the brain, brainstem, and spinal cord (has not been fully understood by researchers) (APDA, 2019).

There is data showing an inverse correlation between chronic pain symptoms and socioeconomic status; the lower a patient is socioeconomically, the greater that patient’s experience of chronic pain will be (Davies et. al., 2009). Studies also introduce correlation between lower levels of education, lower income, and higher unemployment with an increased level of reported pain (Roth et al., 2001; Portenoy et al., 2004). Continuing with this trend, patients living in a less affluent area typically encounter greater muscular pain and muscular stiffness (Brekke et al., 2002), as well as more reported widespread pain (Brekke & Hjortdahl, 2004). In a separate study in Finland, the same inverse trend between socioeconomic status and chronic pain reporting was also observed, indicating that the individuals with more stressful environmental circumstances are at greater risk of experiencing chronic pain (Saastamoinen et al., 2005).

"There is data showing an inverse correlation between chronic pain symptoms and socioeconomic status; the lower a patient is socioeconomically, the greater that patient’s experience of chronic pain will be."

This image shows how external influences affect mental health and has physical consequences.

Ongoing research has been examining these factors and presenting evidence in hopes evaluating external influences becomes widespread when assisting patients reporting chronic pain. New therapies are being implemented to assist patients with these external influences to address their symptoms more effectively Source: Wikimedia Commons

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This image shows an enhanced view of microglia (in green) and neurons (in red). Neuronal imaging has helped researchers understand synaptic signaling in chronic pain and furthering developing treatments.

Source: Wikimedia Commons

"Psychiatric disorders are highly pervasive in chronic pain patients. Psychogenic pain is pain due to mental, behavioral, or emotional factors. This type of psychological pain was first presented in the pain disorder diagnosis in the fourth edition of the Diagnostic and Statistical Manual of Mental Disorders."

The Psychological Perspective To better understand the relationship between socioeconomic status and chronic pain, it is important to examine psychological factors.

A study examining differences between the prevalence of chronic widespread pain (CWP) in patients living in lower socioeconomic areas and in patients living in higher socioeconomic areas found that comorbid psychological factors such as anxiety and depression accounted for this difference (Davies et. al., 2009). Those living in deprived areas are more likely to experience distress in their daily lives that contributes to the amount of CWP reported.

There is also research regarding how those living in such areas are more prone to musculoskeletal pain. This research discusses how this pain can be partially explained by poor living conditions, mental health issues, lack of physical activity, and particularly for this study, being an immigrant with different genetic risk factors. Moreover, this is all exacerbated by a lack of available and affordable healthcare in these areas (Brekke & Hjortdahl, 2004).

Psychiatric disorders are highly pervasive in chronic pain patients. Psychogenic pain is pain due to mental, behavioral, or emotional factors. This type of psychological pain was first presented in the pain disorder diagnosis in the fourth edition of the Diagnostic and Statistical Manual of Mental Disorders (DSM-IV, American Psychological Association) Such a diagnosis indicates that some pain conditions can be mostly or entirely explained by psychological factors instead of a physical condition. This type of pain remains an “empty concept” since therapies or criteria for its identifying are lacking, and often other diagnoses such as depression can point to more specific therapies that would be effective. However, a diagnosis of this type of pain may stigmatize the patients experiencing chronic pain, since many may consider this a byproduct of poor coping (Howe, et. al., 2015).

Psychogenic pain is an important concept to consider in chronic pain management, as it highlights the important interplay between mental and physical wellbeing.

Patients with chronic pain are often diagnosed with depression, but psychiatrists are wary of misdiagnosing a patient with major depressive disorder if the patient is simply in a temporary depressed mood. Patients themselves often push aside any diagnosis of depression, believing it is solely a reaction to their situation. Anxiety disorders, panic disorders, and posttraumatic

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stress disorders are also common, but these disorders are usually found in combinations rather than being the only diagnosis given to a patient. Substance use disorder is often a point of contention when diagnosing chronically ill patients, especially considering the use of opioids in the management of pain symptoms (Howe, et. al., 2015). Drawing the line between appropriate and maladaptive use of painkillers has certainly been a difficult task for many physicians.

From a psychologist’s perspective, pain is not directly linked to the individual’s behavior, and is rather attributable to the psychological mechanisms that govern this behavior.

Psychological treatments for chronic pain include hypnosis, relaxation interventions, mindfulness meditation, operant treatment, graded exposure in vivo, motivational interviewing, cognitive therapy, cognitivebehavioral therapy (CBT), and acceptancebased CBT interventions. It has been proven difficult to address the effectiveness of the therapies listed above; however, there have been studies showing that CBT is an effective form of psychological treatment, especially for chronic pain (Howe, et. al., 2015).

The Neurological Perspective The neurological perspective helps connect chronic pain to the clinical setting for a better and wider understanding of the experiences of chronically ill patients. In central pain, chronic musculoskeletal pain is amplified, and this pain cannot be explained fully by somatic or neuropathic processes. Instead, this pain is a result of physical changes in pain transmission and can complicate neuropathic or noiceptive pain (Crofford, 2015). Unlike neuropathic pain, which arises from damage to the somatosensory system and can be seen in clinical imaging, neurophysiology tests, biopsy

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results, and laboratory testing, acute pain arises from tissue damage and is due to the activation of nociceptive receptors (Crofford, 2015).

Certain genes are also associated with pain sensitivity. These genes include those regulating ion channels and those in the monoamine metabolic pathway; these genes have some overlap with chronic pain patients experience. Two major neurotransmitter pathways have been linked to musculoskeletal pain. The first is the adrenergic pathway, in which genetic mutations in enzyme catechol O-methyltransferase, COMT, have been linked with disordered adrenergic transmission. COMT catabolizes the catechol neurotransmitters epinephrine, norepinephrine, and dopamine, and therefore contributes to their clearance from synapses. The second system associated with chronic pain is the serotonin pathway, where a 44-base pair insertion/deletion polymorphism in the promoter region of the serotonin transporter (SLC6A4) is often associated with chronic pain. These different genetic pathways are associated with intermediate phenotypes that are measurable and present in patients with chronic pain.

Examples of these phenotypes are autonomic dysregulation, altered pain processing, sleep dysfunction, and, in the adrenergic pathway, anxiety (Diatchenko, et. al., 2013).

Due to chronic pain having various sources both psychologically and neurologically, patients face hardships on their journey to find a qualified specialist. To put this into perspective, one study showed that 40 patients suffering from intractable chronic pain had to go through 461 general physicians, 172 pain specialists, 104 psychologists/psychiatrists, and 23 universities to find a qualified specialist (Tennant, 2014). Conventional analgesic drugs are minimally effective, and chronically ill patients continue to receive inadequate care. However, the neurophysical model of care has promoted the development of more interdisciplinary management programs that are both cost and therapeutically effective (Feher, et. al., 2020).

Discussion Chronic pain accompanies chronic illness and is correlated with environmental triggers, especially for those who are of lower socioeconomic status. The inverse relationship between socioeconomic status and chronic pain prevalence can be partially accounted for by psychological problems patients face

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including depression, anxiety disorders, and substance use disorders. The latter is a contentious point considering that there is no established classification for substance abuse for chronic pain patients. The various neurological pathways through which this pain presents itself leaves patients in a situation where they have to actively find specialists who can assist them in effective pain management.

This opens areas for improvement in the chronic treatment pain and chronic illnesses.

The neurophysical model initiated this progress and is likely to inspire more effective pain management programs in the future.

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Social science & medicine (1982), 54(2), 221–228. https://doi. org/10.1016/s0277-9536(01)00018-1 Crofford L. J. (2015). Chronic Pain: Where the Body Meets the Brain. Transactions of the American Clinical and Climatological Association, 126, 167–183.

Davies, K. A., Silman, A. J., Macfarlane, G. J., Nicholl, B. I., Dickens, C., Morriss, R., . . . Mcbeth, J. (2009). The association between neighbourhood socio-economic status and the onset of chronic widespread pain: Results from the EPIFUND study. European Journal of Pain, 13(6), 635-640. doi:10.1016/j. ejpain.2008.07.003 Diatchenko, L., Fillingim, R. B., Smith, S. B., & Maixner, W. (2013). The phenotypic and genetic signatures of common musculoskeletal pain conditions. Nature reviews.

Rheumatology, 9(6), 340–350. https://doi.org/10.1038/ nrrheum.2013.43 Feher, G., Szok, D., Rodríguez-Saldaña, J., &amp; Nagy, F. (2020). Chronic Pain Hurts the Brain: The Pain Physician’s Perspective. Behavioural Neurology, 2020, 1-2. doi:10.1155/2020/3786562 Howe, C. Q., Robinson, J. P., &amp; Sullivan, M. D. (2015).

Psychiatric and Psychological Perspectives on Chronic Pain. Physical Medicine and Rehabilitation Clinics of North America, 26(2), 283-300. doi:10.1016/j.pmr.2014.12.003 Is Pain a Symptom of Parkinson's Disease? (2019, August 27).

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Margaret E. Sears, Stephen J. Genuis. (2012, “Environmental Determinants of Chronic Disease and Medical Approaches: Recognition, Avoidance, Supportive Therapy, and Detoxification”., Journal of Environmental and Public Health, vol. 2012, Article ID 356798. https://doi. org/10.1155/2012/356798 Portenoy, R. K., Ugarte, C., Fuller, I., & Haas, G. (2004). Populationbased survey of pain in the United States: differences among white, African American, and Hispanic subjects. The journal of pain: official journal of the American Pain Society, 5(6), 317–328. https://doi.org/10.1016/j.jpain.2004.05.005 Roth, R. S., Punch, M. R., & Bachman, J. E. (2001). Educational achievement and pain disability among women with chronic pelvic pain. Journal of psychosomatic research, 51(4), 563–569. https://doi.org/10.1016/s0022-3999(01)00242-2 Saastamoinen, P., Leino-Arjas, P., Laaksonen, M., & Lahelma, E. (2005). Socio-economic differences in the prevalence of acute, chronic and disabling chronic pain among ageing employees. Pain, 114(3), 364–371. https://doi.org/10.1016/j. pain.2004.12.033

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The Health Impacts of Electronic Cigarette Use

BY MANYA KODALI, HAMPTON HIGH SCHOOL Cover Image: Electronic cigarettes are battery-operated devices designed to deliver nicotine, flavorings, and other chemicals through aerosol.

Source: Wikimedia Commons

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Background on Electronic Cigarette Usage in the U.S. Over the first half of the 20th century, the world saw a steep rise in cigarette usage and dependence. Now, due to a dramatic shift in attitudes towards tobacco usage combined with irrefutable evidence of health damages caused by cigarettes, the consumption of cigarettes and related deaths have fallen substantially (Cummings, 2014). However, along with the reduction of cigarettes came the advent of electronic cigarettes (e-cigarettes) in 1965 that created a novel method of nicotine consumption along with a host of unique health concerns. The use of e-cigarettes (known as vaping) has since exploded among people of all ages, with the market growing by $4.34 billion between 2014 and 2016 (Kaplan, 2016).

E-cigarette marketers have made various claims regarding the safety of vaping products when

compared to conventional cigarettes, but these claims have little support from researchers because companies often provide incomplete information on the manufacturing, chemical makeup, and synthesis process (Goniewicz et al., 2013; Henningfield and Zaatari, 2010).

In fact, nicotine levels on packaging and labels often does not match measured levels, leaving doubts about manufacturer credibility (Goniewicz et al., 2013).

Originally designed to be a tool to help lifelong smokers quit in a healthy manner, e-cigarettes have alarmingly become increasingly popular with non-smokers, especially in younger demographics. Vaping prevalence in the 8th, 10th, and 12th grade populations more than doubled between 2017 and 2019 to 1 in 4 students in the 12th grade, over 1 in 5 in the 10th grade, and more than 1 in 11 in 8th grade.

These substantial increases in the levels of use indicate the occurrence of nicotine addiction DARTMOUTH UNDERGRADUATE JOURNAL OF SCIENCE

Figure 1: A scientist from the Centers for Disease Control (CDC) are working with multiple different electronic cigarettes.

The variety of liquids and devices seen here highlights the difficulty for comprehensive studies on the effects of e-liquids.

Source: Public Health Image Library (CDC)

within high schoolers and reflect the failure of school and government programs to limit adolescent consumption of nicotine (Miech et al., 2019). The market is still largely unregulated, and the long-term impacts of vaping remain mostly unknown due to both the novelty and complexity of these devices (Schraufnagel, 2015).

With e-cigarette use on the rise, it is critical to research the long-term effects that these devices and the chemicals they contain have on the body. This is especially relevant in 2020 due to the COVID-19 pandemic and associated lung complications that could theoretically be worsened by e-cigarettes. This paper will explore the effects of e-cigarettes on the body’s immune response and lung function.

Analyses of Electronic Cigarette Vapor When activated by the user, e-cigarettes aerosolize nicotine by using the device’s heating element to atomize the liquid inside.

This process creates an aerosolized nicotine vapor with a visible wisp of smoke that is then inhaled. Electronic cigarettes typically contain glycerol, propylene, ethylene glycol, polyethylene glycol, concentrated flavor additives, and nicotine (Hahn et al., 2014).

Although most of these ingredients (with the exception of nicotine) are typically non-toxic and non-carcinogenic, the safety of inhaling them has not been established. Additionally, new research suggests that many e-cigarettes may contain unexpected toxins created by the FALL 2020

mixing of flavorings and chemicals (Yamin et al., 2010). Chemical levels and delivery methods vary between different e-cigarettes, which makes it more challenging for researchers and doctors to measure and understand the composition and effects of the emitted vapors (Drummond and Upson, 2014).

Comprehensive studies on conventional cigarette smoke have uncovered many harmful compounds, including aldehydes, tobacco-specific nitrosamines (TSNAs), metals, volatile organic compounds (VOCs), phenolic compounds, polycyclic aromatic hydrocarbons (PAHs), and tobacco alkaloids (Tianrong, 2014).

Studies on e-cigarette vapors have found that many brands and devices also produce these harmful TSNAs, aldehydes, VOCs, and metals, providing evidence of potential e-cigarette dangers. The variance in levels of these substances can differ greatly, even between products from the same company. For example, one study found that the level of acrolein, an aldehyde, was reported to be 4.4±2.5μg/150 puffs in one model and 16.6±2.25μg in another model from the same brand (Goniewicz et al., 2014). When comparing acrolein levels across brands, levels had an even higher variance.

The same study found the acrolein level to be as high as 41.93±3.45μg/150 puffs in a similar product from a different brand (Goniewicz et al., 2014). A separate study investigated TSNAs levels in 105 e-liquids from 11 electronic cigarette companies and also found that TSNA levels varied greatly (Kim and Shin, 2013).

Despite the variance in e-liquids’ makeups, much of the existing literature agrees that

"New research suggests that many e-cigarettes may contain unexpected toxins created by the mixing of flavorings and chemicals."

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Figure 2: Some e-cigarettes, such as this device from the company MiniCiggy, are designed to imitate conventional cigarettes through coloring and shape.

The different parts A (an LED light cover), B (the battery), C (an atomizer), and D (the mouthpiece) are broken down here to give a clearer description of the components of such devices.

Source: Wikimedia Commons

vaporization of e-liquids collectively generates harmful compounds such as aldehydes at levels that exceed safety standards (Reidel et al., 2018).

"Glycol and glycerol vapors are two of the most common components of e-cigarettes and are found in most models. Both have been studied in the context of smoke used in theatre productions and have been found to severely irritate the upper airway."

Not only do compound levels vary, but the performance of e-cigarettes, as measured by the number of puffs from each device, can vary both between brand and products within a company (Goniewicz et al., 2013; Williams and Talbot, 2011; Trtchounian et al. 2010). For example, Trchunian et al. (2010) found that total number of puffs from one device ranged from 30±43 within one brand to 313±115 for another brand. The relatively high standard deviations highlight considerable variance in performance within brands. A separate study observing multiple e-cigarette models also found that significant performance variation between puffs exist (Williams and Talbot, 2011). The density of aerosols, another common measure of e-cigarette performance, also varies greatly among brands. (Sosnowski and Odziomek, 2018). Ultimately, the variance in these measurements within brands can largely be attributed to poor quality control during the manufacturing process. Such reports illustrate the difficulties in studying toxicological effects; the irregularities necessitate complex experimental designs and interpretations of data to ensure any conclusions drawn are useful.

It is important to note that these studies on the composition of e-cigarette aerosols use inconsistent methods for analyzing the liquids that haven’t been validated by the research community at large. While it is necessary to develop more standardized testing methods for future research, the few studies that already exist still provide insight into the makeup of vapors.

E-Liquid Components: Health Effects As

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discussed

above,

differences

in

the

manufacturing of e-cigarettes create challenges for comprehensive research. Much of the existing research on e-cigarettes and health comes from analyses of their chemical components.

Glycol and glycerol vapors are two of the most common components of e-cigarettes and are found in most models. Both have been studied in the context of smoke used in theatre productions and have been found to severely irritate the upper airway (Environ, 2001). Additionally, glycol mist dries out the eyes and mucous membranes; the respiratory system is lined with a mucous membrane that traps particles, so this property is particularly relevant to the effects of e-cigarettes (Raymond, 1997). Contrasting the findings of studies on theatre smokes, a study in which human embryonic stem cells, mouse neural stem cells, and human pulmonary fibroblasts were exposed to e-liquids, found that glycerin and propylene glycol caused no cytotoxic effects; this difference highlights the complexities surrounding e-liquid research (Bahl et al., 2012).

Nicotine, another component of e-liquids, is readily absorbed through both skin and mucous membranes and when tobacco smoke reaches the lung, nicotine has been shown to rapidly be absorbed through alveoli and small airways (Benowitz et al., 2010). Due to the high concentration of nicotine within e-liquid cartridges, nicotine toxicity poses an even greater risk than the risk of conventional cigarettes. An analysis of exposures to liquid nicotine solutions found that e-cigarette exposures serious enough to be reported to poison control centers are increasing for unknown reasons. While exposures don’t typically have lasting outcomes, they result in symptoms such as vomiting, nausea, headaches, dizziness, lethargy, and ocular irritation (Ordonez et al., 2015). However, as a result of the variability in e-cigarette products,

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the existing data on nicotine toxicity is inconclusive.

Lung Function and E-Cigarette Usage Scientific evidence on the effects of e-cigarettes on human health is severely limited; the little research that exists is often contradictory, with some studies finding little to no damage from vaping and others concluding that e-liquids cause permanent damage.

Some in vitro (performed on human cells in a lab setting) studies using human alveolar epithelial cells have concluded that the presence of nicotine in e-liquids does not permanently damage the genetic material of cells. A study comparing conventional cigarettes to e-cigarettes found that e-liquids do not produce any significant toxic effects in the short term (Misra et al. 2014). Similarly, researchers who observed the effects of e-cigarette usage after five minutes found no adverse health effects (Ferrari et al., 2015).

Conversely, when endothelial cells from human umbilical cord veins were exposed to different e-liquids, the researchers found that cell death increased as the concentration of e-liquid used increased (Putzhammer et al., 2016). Another in vitro study on short-term daily exposure to e-liquid vapors in mice found that the human airway epithelium barrier may be weakened by the vapors (Crotty Alexander et al. 2018).

In one in vivo (research done on human subjects) study, subjects were exposed to propylene glycol for one minute. All twentyseven subjects were found to have a significant 2% reduction in FEV1/FVC, a measurement of one’s ability to expel air from the lungs, meaning their lungs had a lower capacity after exposure (Wieslander et al., 2001). In a separate study of thirty healthy smokers, five minutes of e-cigarette use resulted in impeded respiratory function and airway resistance (Vardavas et al., 2011). Disputing the idea that vapor exposure harms lung function, another study found no change in FEV1/FVC immediately after and one hour after exposure to e-cigarette vapor (Flouris et al., 2013).

These studies highlight the contrasting results of existing research, leaving doubt as to whether or not e-cigarettes cause short-term harms or not. Further research, both in vitro and in vivo, is required to draw sound conclusions.

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Immune Response Due to E-Cigarettes As scrutiny on the potential long-term impacts of vaping increases, more studies are looking into the body’s immune response when subjected to e-liquid vapors. A 2014 study demonstrated that e-liquids containing nicotine induced the production of interleukin 6 (a pro-inflammatory cytokine) and promoted human rhinovirus infection (the infection associated with the common cold) within the airway (Wu et al., 2014). These findings indicate that prolonged exposure to e-liquid vapors may lead to immune-compromised states and increased susceptibility to infection.

Furthermore, a study that exposed mice to electronic cigarette vapors over multiple weeks found that the mice faced impaired pulmonary clearance and an increase in Staphylococcus aureus virulence; the researchers concluded that e-liquid vapors may boost drug resistance in bacteria, threatening the immune systems of frequent users (Sussan et al., 2015). A separate study performed on mice found that, over many weeks of inhaling e-liquid vapors, the mice developed higher levels of inflammatory cytokines (Crotty Alexander et al., 2018); this data suggests that continued inhalation of e-cigarette vapors may cause permanent change to the immunoregulation in the body.

One study collected mucus and saliva samples from e-cigarette users, conventional cigarette users, and nonsmokers. The study found that found that the mucus protein composition of those who consumed nicotine in any form differed from that of non-users. It also found that the proteins were more significantly changed in the e-cigarette group than even the conventional smoker group. Specifically, levels of aldehyde-detoxifying enzyme and upregulation of stress response proteins rose, highlighting the increased immunological response in the body of e-cigarette users.

Notably, the e-cigarette group was found to have an increased abundance of proteins relating to the innate defense in the body (Reidel et al., 2018).

Once again, little research exists to study the body’s immune response to e-cigarettes.

Previous studies seem to agree that e-liquid vapors create changes to the body’s proteins and immune response and make people more susceptible to other infections.

"A study that exposed mice to electronic cigarette vapors over multiple weeks found that the mice faced impaired pulmonary clearance and an increase in Staphylococcus aureus virulence; the researchers concluded that e-liquid vapors may boost drug resistance in bacteria, threatening the immune systems of frequent users."

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Conclusion The limited understanding of electronic cigarette health impacts combined with contradictory results make it difficult to draw reliable conclusions. Previous studies have shown that e-cigarette manufacturers lack regulation and create products with vastly different levels of substances. These additional challenges make it even harder for researchers to draw broad conclusions. The growing focus on the health impacts of these devices has caused an increase in research over the last few years, but much of this data is contradictory; some studies have found no short-term impacts while others have found impacts in in vivo studies. The research on immune response is slightly more conclusive with multiple studies agreeing that changes to immunoregulation and the proteins in the body are caused by exposure to e-liquid vapors.

Still, more research is required on all aspects of e-liquid effects before doctors can truly understand the detriments of usage.

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Neuroscience and Artifiical Intelligence

BY MEGAN LIU ’24 Cover Image: Long exposure of a city and the inner workings of its network.

Source: Pexels

Introduction In 1955, John McCarthy and his colleagues at a Dartmouth College conference created the field of artificial intelligence (AI), which is “the science and engineering of making intelligent machines” (Hamet, Trembay, 2017).

From medicine to big business to law, this advancement has and will lead humanity to some of the most brilliant yet simultaneously frightening changes in society.

David Sussillo, a computational neuroscientist at Google Brain Team, parallels the inner workings of artificial intelligence to a brain. In a neural network, there are connected layers of nodes (analogous to synapses between neurons). Values enter the input layer and are then adjusted with mathematical computations by several layers of hidden layers which then produce an output layer. For instance, facial recognition could be represented by a list of numbers that mathematically represent

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each pixel by their respective amount of red, green, and blue values. After the information is inputted, data is processed by the weights of each of the connections in the middle layer, and then output is returned. Training is necessary to increase the accuracy of the algorithm’s image recognition or categorization. Usually, the program’s output is compared to the true output and the difference is adjusted accordingly (Savage, 2019). This process takes a large amount of time and requires millions of training examples. To train the system to produce the correct answer more reliably, deep neural networks are used. These networks require an abundance of hidden layers, mimicking the intricacy of the brain (Savage, 2019).

However, neural networks require a certain level of abstraction compared to the brain in how they “model synapses as numbers in a matrix.” This is because its biological DARTMOUTH UNDERGRADUATE JOURNAL OF SCIENCE

Figure 1: A woman with code projected onto her. In the future, there will likely be more integration of technology into human bodies with the enhancement of desirable traits, for instance.

Source: Pexels

equivalent, the brain, receives and transmits electrochemical signals while interacting with its “neighbors in dynamic patterns” (Savage, 2019), whereas neural networks simply crunch static numbers. The differences extend past AI’s processing of data to its gaining of knowledge.

Machine learning, a method of teaching an algorithm to become a sophisticated form of AI, allows for training and eventual autonomy (Nabi, 2018). There are three types of machine learning algorithms (which are often used in combination): unsupervised (finding patterns independently), supervised (classification based upon previous examples), and reinforcement learning (using rewards and punishments to limit the scope of the AI’s responses) (Hamet, Trembay, 2017). An untrained neural network mirrors an infant in its lack of knowledge; however, babies generally absorb more of their environment through unsupervised learning. Tomaso Poggio, a computational neuroscientist at the Center for Brains, Minds, and Machines at the Massachusetts Institute of Technology, states that babies are inundated with stimulation and data (somewhere around a billion images in their first two years) and are able to independently develop an understanding and knowledge of their environment, whereas machines have significant difficulty learning the same way. In an effort to replicate the human learning process, his work is tackling how to encode curiosity, instilling an initiative to learn that will potentially lead to the machine’s own independent behavioral modification (Hamet, Trembay, 2017). Perhaps even more importantly, we need to better understand how humans develop moral values in order FALL 2020

to assuage fears of destructive machines.

By examining the emergence of morality in ourselves, we can better implement methods to build ethical artificial intelligence (Savage, 2019).

Furthermore, AI emulating human biology and neuroscience provides “a rich source of inspiration for new types of algorithms and architectures” (developed independently from traditional, passed-down mathematical and logical ideas) and allows for the “validation of AI techniques that already exist” (Hassabis et al., 2017). For example, the discovery of a new biological method could propel this biological approach to the top of the list for possible incorporation into AI. If a known algorithm is heavily used in the brain, the AI using this approach is probably nearing its maximum efficiency, as nature’s time-tested methodologies reign supreme to experimental algorithms developed in a relatively short time frame. The intertwining of these two fields, however, does not expand to the point of strict adherence to biological tendencies for AI. Instead, biology serves as an inspiration to develop efficient algorithms (Hassabis et al., 2017).

One example of an application at the intersection of these two fields is Chethan Pandarinath, a biomedical engineer at Emory University and the Georgia Institute of Technology, and his work analyzing neurons to control motor skills. He recorded the neurons necessary for arm movement and fed the data into a computer to observe patterns after manipulation. These patterns revealed latent

"If a known algorithm is heavily used in the brain, the AI using this approach is probably nearing its maximum efficiency, as nature’s timetested methodologies reign supreme to experimental algorithms developed in a relatively short time frame."

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Figure 2: Traditional western wedding garb and traditional Indian wedding garb. Western biases impacting the selection of training data for algorithms leads to the designation of Indian wedding dress as a costume rather than wedding apparel.

Source: Pexels

"Researchers at the Massachusetts Institute of Technology in 2015 found that they can predict the probability of Parkinson’s disease simply based on individuals’ keyboard typing patterns on personal devices.

Another study in 2017 was able to diagnose early indicators of Alzheimer’s disease simply based on physical mobility tracked using mobile devices."

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factors, which strongly influence the overall behavior. The precision of the technology allows for a more thorough analysis of any slight changes to neural activity to the point where “we can very precisely say, on an almost millisecond-bymillisecond basis, right now the animal is trying to move at this precise angle,” which is necessary for the creation of robotic arms (Savage, 2019).

However, while robotic arm movement may not seem like the most revolutionary advancement, there is potential and with that potential comes ethical concerns.

Ethics of AI AI requires large amounts of data to be useful to humans; however, where does the data come from? The high demand for information has brought to light concerns regarding privacy and consent. Even with surprisingly little information, meaningful conclusions can be drawn. For instance, researchers at the Massachusetts Institute of Technology in 2015 found that they can predict the probability of Parkinson’s disease simply based on individuals’ keyboard typing patterns on personal devices. Another study in 2017 was able to diagnose early indicators of Alzheimer’s disease simply based on physical mobility tracked using mobile devices (Yuste et al., 2017). These conclusions may be beneficial for some, but for others, they may be inaccurate or even dangerous because of the internal bias in the training data.

Humans are inherently flawed and subsequently biased, and may therefore humans transfer imperfections to machines, which can unintentionally embed gender, ethnic, and cultural prejudices.7 This tool could result in privileging certain groups while discriminating against others (Yuste et al., 2017). For instance, in law, scores known as risk assessments are used to assist in (and sometimes make) decisions ranging from bond amounts to who should be released in the criminal justice system (Yavuz, 2019). This system was used in 2014 in Fort Lauderdale when 18-year-old Brisha Borden and her friend stole a bike and a scooter because they were late to pick up Borden’s god-sister from school. They dropped the bike and scooter after the owner called after them (they were too small anyway as they were for the owner’s six-year-old child). However, a neighbor saw what was going on and called the police before realizing that the situation was resolved. The previous summer, another heist occurred: 41-year-old Vernon Prater stole over $80 of Home Depot goods. Despite Borden’s lack of criminal record and Prater’s abundant criminal record, the computer rated Borden at a higher risk. We can speculate that this decision was greatly influenced by race as Borden was African American and Prater was White. Based on logical reasoning, this is the reverse decision a rational human would have made. Yet, it shows the impact of training with a biased data set. Two years after those incidents, Borden had not committed any felonies while

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Prater was in the middle of serving eight years in prison for breaking into and stealing goods from a warehouse. Further research into this algorithm found that of the people predicted to commit future crimes, only 20 percent actually did. Significant racial disparities were uncovered as well: black defendants were more likely to be flagged as future criminals (labeled as such almost twice as much as white defendants with similar criminal backgrounds) and white defendants were more likely to be mislabeled as a low risk than black defendants.

The US Attorney General in 2014, Eric Holder, even commented that though this technology was developed with the best intentions, it might reverse our progress toward equality and justice while amplifying ingrained societal discrepancies (Yavuz, 2019).

ImageNet, which aids computer vision research, has collected over 45% of its information from the US, only 4% of the world’s total population, while India and China (36% of the world’s population) make up only 3% of ImageNet data. The overrepresentation and underrepresentation of certain groups in training data allow for algorithms labeling a photograph of a traditional US bride dressed in white as ‘bride’, ‘dress’, ‘woman’, ‘wedding’, but a photograph of a North Indian bride as ‘performance art’ and ‘costume’” (Zou, Schiebinger, 2018).

However, the ramifications of AI are not limited to interpersonal interaction but also extend to intrapersonal thoughts. Chiefly, people receiving deep brain stimulation through implanted electrodes report “an altered sense of agency and identity”. One individual who was using this stimulation to treat his depression noted a shift in his interaction with others and wondered if it was due to his own personal changes, his depression, or his device.

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He reflected that “[i]t blurs to the point where I’m not sure … frankly who I am” (Yuste et al., 2017). Alteration of one’s identity and behavior (potentially having an “‘auto-complete’ or ‘auto-correct’” function), on a larger scale, could lead to alarming implications through mass behavioral modification. Additionally, these increase the possibility of an altered mental experience and invasion of mental privacy by government agencies, companies, or other organizations. There is the possibility of neurotechnology becoming so ubiquitous that people intentionally modify capacities like intelligence or agility, which would lead to a shift in norms (and increased inequality split by socioeconomic status and who can afford the technology) (Yuste et al., 2017).

Despite this dreary outlook, there are methods that will enable more careful development of technology in the future of AI. Firstly, an international organization could be established in order to lay out the groundwork and boundaries that nanotechnology and machine intelligence companies must follow (Yuste et al., 2017). This would be an important step towards personal privacy being protected as a basic human right (Yuste et al., 2017).

Secondly, demographic data (like geography, gender, ethnicity, etc.) should be included in the documentation of the algorithms to give greater context to the algorithm, which would increase its transparency. Other precautionary measures could involve restricting the centralization of data collected for AI processing and the widespread usage of open-source code allowing for greater information usage transparency (Zou, Schiebinger, 2018).

AI and the Economy

Figure 3: Computer programming (above) is integral to the development of AI; however, there will be a point where this code becomes obsolete: the machine will learn to learn on its own.

Source: Pexels

"People receiving deep brain stimulation through implanted electrodes report “an altered sense of agency and identity”. One individual who was using this stimulation to treat his depression noted a shift in his interaction with others and wondered if it was due to his own personal changes, his depression, or his device."

The application of AI in the realm of economics can lead to more intentional advertising but it may also lead to rampant consumption.

Neuromarketing, the use of neurotechnologies in marketing toward consumers, accesses the brain’s response to various marketing stimuli.

One study used neuromarketing to survey people’s preferences for Coca-Cola or Pepsi.

Instead of looking at the behavioral data like the amount of product purchased, businesses believe that neuromarketing data is “in some degree truer, purer, and more unsullied than watching behavior exclusively”. This data collection might include eye-tracking studies, color and packaging preference research, or examinations of how consumers make choices (Wolpe, 2019). Neuromarketing may therefore result in the illusion and decrement of personal

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privacy for increased ease of accessibility for consumers to products and marketers to consumer data. However, most consumers do not even realize the extent to which their privacy is being violated. Businesses want to use AI to over-customize their marketing strategies to each consumer and their distinct personality types. With large data sets and enough power, the machines could be able to successfully maximize profits, yet this will most likely result in overconsumption and disregard for potential consequences (e.g. environmental) (Hamet, Trembay, 2017). Generally, history has shown that profit outweighs social obligation and betterment of society and that technologists will most likely have to solve moral issues for which they aren’t suited to answer (Yuste et al., 2017).

Conclusion Overall, the rise of AI will lead to stratifying effects in biology, society, and economics because of the potential for extreme customizability and exacerbation of previous inequalities. While it is possible that current societal problems may be amplified, there is potential for improvement of major problems.

Undoubtedly, AI will catalyze impactful changes to society through the development of new methods for quantifying biological data, whether it be genetic or behavioral (Wang, Preininger, 2019). While AI is already becoming increasingly ingrained in society through human implants, sensors (monitoring of wear of car parts, indoor dust levels, etc.), automation, and decision making, researchers must be careful of AI’s exponential growth and potential shortcomings (Howard, 2019).

In developing AI, researchers must straddle the line between breakneck advancement and careful evaluation of AI’s impact on the quality of human life in order to ensure that the net consequences are positive.

Carter, A., Fins, J. J., Friesen, P., Gallant, J., Huggins, J. E., Illes, J., Kellmeyer, P., Klein, E., Marblestone, A., Mitchell, C., Parens, E., Pham, M., Rubel, A., Sadato, N., … Wolpaw, J. (2017). Four ethical priorities for neurotechnologies and AI. Nature, 551(7679), 159–163. https://doi.org/10.1038/551159a Yavuz, C. (2019). Machine Bias: Artificial Intelligence and Discrimination. SSRN Electronic Journal, 1–97. https://doi. org/10.2139/ssrn.3439702 Zou, J., & Schiebinger, L. (2018). AI can be sexist and racist — it’s time to make it fair. Nature, 559(7714), 324–326. https:// doi.org/10.1038/d41586-018-05707-8 Wolpe, P. R. (2019). Neuromarketing and AI—Powerful Together, but Needing Scrutiny. AJOB Neuroscience, 10(2), 69–70. https://doi.org/10.1080/21507740.2019.1618414 Wang, F., & Preininger, A. (2019). AI in Health: State of the Art, Challenges, and Future Directions. Yearbook of Medical Informatics, 28(01), 016–026. https://doi. org/10.1055/s-0039-1677908 Howard, J. (2019). Artificial intelligence: Implications for the future of work. American Journal of Industrial Medicine, 62(11), 917–926. https://doi.org/10.1002/ajim.23037

References Hamet P, Tremblay J. Artificial intelligence in medicine.

Metabolism. 2017 Apr;69S:S36-S40. doi: 10.1016/j. metabol.2017.01.011. Epub 2017 Jan 11. PMID: 28126242.

Savage, N. (2019). How AI and neuroscience drive each other forwards. Nature, 571(7766), S15–S17. https://doi. org/10.1038/d41586-019-02212-4 Nabi, J. (2018). How Bioethics Can Shape Artificial Intelligence and Machine Learning. Hastings Center Report, 48(5), 10–13. https://doi.org/10.1002/hast.895 Hassabis, D., Kumaran, D., Summerfield, C., & Botvinick, M. (2017). Neuroscience-Inspired Artificial Intelligence. Neuron, 95(2), 245–258. https://doi.org/10.1016/j.neuron.2017.06.011 Yuste, R., Goering, S., Arcas, B. A., Bi, G., Carmena, J. M., 110

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A Scientific Review of the Impacts of Music on the Human Body

BY MIRANDA YU ’24 Cover Image: Music and the Brain Source: Getty Images/ iStockphoto

Introduction From many thousands of years ago to the present day, music has played a prominent role in today’s society and the world. Besides being a cultural phenomenon, music has profound impacts on its listeners. People listen to music for many reasons, such as for relaxation, entertainment, and mood regulation.

Researchers have wondered whether and how music can serve biological or evolutionary purposes. Thus, they have attempted to explain the mysteries of music and depict its effects through a scientific lens. Studies have shown that music has unique abilities to influence cognition, pain perception, and physiological development. By interacting with both the mind and the body of an individual, music can empower, teach, and heal.

The mechanisms of music go hand-in-hand with its functions. Music extends beyond its physical characteristics as sound waves.

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Humans are able to distinguish music from all the other noises we hear every day. The brain is wired to recognize the rhythm, pitches, and timbres characteristic of music. What scientists have strived to uncover about music better enables people to enjoy it to the fullest extent.

Impacts on Emotion and Thoughts The most well-known effect of music is its ability to evoke emotions. Specifically, music can affect thought patterns by altering an individual’s emotional perceptions. Music can influence both emotions and thoughts in a way to promote positive mood and wellbeing. To begin with, music can evoke several important emotional reactions that include subjective feelings, physiological arousal, and action tendencies such as smiling, dancing, playing an instrument, or foot-tapping (Koelsch, 2014).

Through these physiological reactions, music can potently moderate and alter mood.

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In addition, researchers have conducted studies on the relationship between music and mindwandering, which is a behavior of immersing oneself in self-generated thought about topics most commonly pertaining to self-importance, social relationships, future planning, and autobiographical memories. This form of selfreflection has been associated with benefits such as facilitating creativity and delaying gratification. Music has been found to enhance mind-wandering, with the type of music factoring into its content. For example, sad music increases mind-wandering and promotes relaxation more than happy music (Taruffi et al., 2018). Empowering music evokes motivating thoughts that may enhance self-confidence and increase motivation in both healthy individuals and people with mood-affecting disorders.

One study with 62 participants explored the content of thoughts of the participants after they listened to excerpts of happy music and sad music by looking at the content of self-reported thoughts after listening. These researchers in this study examined their results using analysis of variance, a procedure of using statistical models to analyze differences between samples and found that thought contents were more exciting and motivating after happy music and calmer after sad music.

The researchers also measured heart rate to control for any physiological arousal effects on thoughts (Koelsch et al., 2019). These findings corroborate the functions of music in daily life and society: individuals and groups can use music as a tool for reflection and empowerment.

Emotional processing primarily occurs in the amygdala, which regulates emotional networks and modulates an emotion from start to end. The auditory cortex also plays a role in processing emotional components of music. It contains functional connections to a range of limbic, paralimbic, and neocortical structures pertaining to specific emotions (Koelsch, 2014).

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Emotions induced by music correspond to brain activation patterns in the prefrontal cortex and right inferior parietal cortex that are similar to those for emotions induced by other modes such as real-life experiences (Daly et al., 2014).

Music-induced emotions may be processed more readily than emotions from other stimuli, especially for individuals with autistic spectrum disorder (ASD). ASD is characterized by a deficit in socio-communicate skills hypothesized to stem from impaired abilities to understand and express emotions, especially within social contexts. However, the ability for individuals with ASD to process emotions derived from music is mostly maintained, as seen in one study of 22 individuals – eight of which have ASD and fourteen of which were neurotypical control participants – who listened to excerpts of happy and sad music. The fMRI results between the two groups of participants in the brain regions involved in processing emotion are similar, with ASD individuals possessing slightly lower brain activity, particularly for excerpts of happy music (Caria et al., 2011).

Because music can modulate the brain through emotional pathways such as in this case with ASD individuals, music may affect brain structures such as the amygdala, nucleus accumbens, hypothalamus, hippocampus, insula, cingulate cortex and orbitofrontal cortex. Thus, music can potentially be used in the treatment of neurological or psychological disorders or in the alleviation of their symptoms (Koelsch, 2014).

Figure 1: Human brain responding to musical pitch, which are harmonic sounds that human brains are uniquely sensitive to.

Source: Wikimedia Commons

Cognitive Roles Music has cognitive impacts on the brain in addition to its emotional influences. Music can positively influence an individual’s auditory or language skills, especially since music and language are hypothesized to share similar underlying syntactic pathways. Neuroimaging data shows that musical syntax for musical structure and chord progression correlates to language syntax for linguistic structure and grammar (Patel, 2003). Musical syntax and harmonic sequences are processed in Broca’s area, which is an important region involved in speech and language comprehension (Maess et al., 2001).

"Music can positively influence an individual’s auditory or language skills, especially since music and language are hypothesized to share similar underlying syntactic pathways."

Furthermore, musicians experience positive cognitive impacts from their musical training and exposure. Music is one cause of neuroplasticity, which is the ability of neural networks and the brain to grow and reorganize.

Neuroplasticity is highly advantageous and is most prominent among the developing brains of younger individuals. Due to neuroplasticity, 113

Figure 2: Motor and sensory regions of the brain.

Source: Wikimedia Commons

"Music has also been found to improve impaired higherorder cognitive functions such as the processing of personally familiar items, especially if the music is familiar to the person."

musicians experience functional and structural changes in their auditory neural systems.

Musicians can more easily process music through enhanced neural responses and gain larger gray matter volume in areas that are important for playing an instrument. These include the auditory, motor, and visual-spatial regions that correspond to auditory and motor skills (CalmaRoddin & Drury, 2020). Furthermore, exposure to pitches and experience with distinguishing them leads musicians to be better accustomed to differentiating pitch contours that indicate whether a speaker is stating or questioning.

Musicians are also better prepared to detect pitch contours in unfamiliar languages, which gives them an advantage in understanding pitch patterns in their non-native languages.

Although these study results primarily apply to musicians, some of these benefits also translate to music listeners with active and constant musical engagement (Kraus & Chandrasekaran, 2010).

Music has also been found to improve impaired higher-order cognitive functions such as the processing of personally familiar items, especially if the music is familiar to the person (Castro et al., 2020). Patients with consciousness disorders seem to show slight cognitive improvements when listening to music. One study of thirteen patients â&#x20AC;&#x201C; seven with unresponsive wakefulness syndrome (UWS) and six in minimally conscious states (MCS) â&#x20AC;&#x201C; exhibited patient improvements in the expression of residual cerebral function when they listened to their favorite music, which was measured by improvements on four items of a test for basic cognitive functions called CRS-R (Coma Recovery Scale - Revised).

These patients demonstrated improved visual

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pursuit, enhanced auditory localization of their names, and more consistent commanded movements (Heine et al., 2017). In addition, through a reward pathway involving pleasure, music can help enhance memory for items encoded in the same context as the music. The events associated with music-induced pleasure correspond to enhanced memory performance (Cardona, 2020).

Music for Pleasure and Pain Reduction Pleasure and a decrease in the perception of pain are two more of the benefits that come from listening to music. Music is a trigger for dopamine release, which leads to pleasure and relates to other functions like movement, attention, mood, and motivation (Cardona, 2020). Dopamine is primarily released during peak emotional arousal as an emotional response to music (Salimpoor, 2011). The amount of pleasure gleaned from listening to music differs between individuals as differences in a trait called music reward sensitivity, which is appropriately named after the sensitivity of an individual to musical pleasure (Mas-Herrero et al., 2018). Neural imaging studies have found that listening to music activates areas of reward systems, which are involved with primary reinforcers like food and sex (MartĂ­nez-Molina et al., 2019) as well as in the dopaminergic mesolimbic reward pathway, a phylogenetically old network that operates to ensure survival and includes the ventromedial orbitofrontal cortex, pregenual anterior cingulate cortex, amygdala, anterior insula, and mediodorsal thalamus (Koelsch et al., 2016). However, music

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pain intensity corresponded to a statistically significant increase in rs-FC (Pando-Naude et al., 2019).

Figure 3: Musician Craig Chaquico at Renown Children’s Hospital in Reno, Nevada.

Source: Wikimedia Commons

Music Interventions and Music Therapy The powerful effects of music have been channeled toward several types of musicrelated interventions and music therapies.

These include improving sleep quality (Cordi et al., 2019), reducing anxiety (Koelsch et al., 2016), and helping infants in neonatal intensive care units (NICUs) (Foroushani et al, 2020).

by itself is considered a secondary reinforcer as it is an abstract stimulus not directly essential for survival (Salimpoor, 2011).

Individuals with chronic pain conditions have been found to have a decreased perception of pain when listening to self-chosen and pleasant music. This phenomenon has been coined as music-induced analgesia (MIA). A study conducted on fibromyalgia (FM) patients using MRI scanning generated data support for MIA. A group of FM patients and a group of matched healthy controls were subject to two separate five-minute auditory conditions of music and pink noise (control) separated by a wash out condition of a video documentary with sound to avoid crossover effects between trials. The researchers found decreases in the subjective ratings of perceived pain that correlated to increases in resting state functional connectivity (rs-FC) in specific parts of the brain: the amygdala and middle frontal gyrus. Since those activated areas support autobiographical processes and auditory attention, the increase in functional connectivity suggests that MIA may be due to distraction, relaxation, and positive emotion. The decreased activity in a customized pain matrix combining thirty-four regions of interest in the brain part of a so-called pain network was also measured through rs-FC to show that there was a significant correlation between pain scores and rs-FC of the pain matrix. A decrease in the change in perceived FALL 2020

Listening to relaxing music before sleeping may help improve sleep quality, where improved sleep quality is measured by a decrease in the time length of sleep stage N1, the transition stage between wake and sleep, and an increase in the amount of slow-wave sleep (Cordi et al., 2019). Listening to music is already a widespread sleep technique and is often used as a tool to help with sleep disorders. Surveys found that over 50% of individuals with sleep disorders use music to improve sleep quality. One study found that music improves subjective sleep in insomnia patients. Experiment participants were randomly selected to listen to either a music track or a track of spoken text before sleep. The text chosen was a documentary about mineral deposits and served as a control that took into account any effects of simply listening. After sleep, the participants reported their sleep quality on a scale of 1 to 5. Those who listened to music before sleep reported significantly better sleep in comparison to those who listened to the control text (3.69 ± 0.16 compared to 3.28 ± 0.18). Another study of older women found that listening to music correlated with a shorter reported sleep onset time, fewer nocturnal awakenings, and greater satisfaction with sleep quality (Cordi et al., 2019). Music is an accessible way to better sleep, and it has much fewer side effects compared with sleep aids such as medication.

In addition, researchers and clinicians have also attempted to implement music-related treatments in more formal clinical settings.

"Individuals with chronic pain conditions have been found to have a decreased perception of pain when listening to self-chosen and pleasant music.

This phenomenon has been coined as music-induced analgesia (MIA)."

Music can help decrease anxiety and has relaxing effects on individuals undergoing surgical procedures. A study with dental surgery patients used heart rate and selfreports to monitor and measure anxiety levels of patients undergoing minor oral surgery. The patients’ overall heart rates decreased over the duration of treatment along with decreases in reported anxiety; 92% of patients reported

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music that reduced their anxiety and discomfort levels (Gupta & Ahmed, 2020). Studies have also found that listening to music before, during, and after medical interventions correlates with lower cortisol levels, which indicates decreased anxiety (Koelsch et al., 2016).

Music therapy is the clinical use of music interventions to accomplish individualized goals and to treat physical and psychological conditions. It requires a credentialed professional with advanced education. Music medicine has similar targets but does not require advanced certification and does not always have a strict therapeutic plan. Both music therapy and music medicine are used in the NICU for premature infants, who are in precarious health conditions.

Music aims to improve physiology parameters, growth and feeding, and behavioral states.

Physiological parameters are measured in terms of heart rate while behavioral state is observed in terms of relaxation and pain (Foroushani et al., 2020). One systematic review of four hundred and fifty-eight clinical trials on neonatal music interventions with either live or recorded music found that the current data with regards to these effects are limited, yet music therapy and music medicine shows potential. Most of these trials used lullabies, which were found to improve respiratory rate. Heart rate was found to generally improve with music intervention, as well as maternal-infant bonding (Foroushani et al., 2020). Music is more than purely recreational uses; it can be harnessed specifically to promote wellbeing and enhance health.

Conclusion Music is beneficial for emotional, psychological, cognitive, and physiological wellbeing. It can positively influence moods, regulate thought content, and induce emotional processing.

Music can improve cognitive functions and development related to auditory, memory, and language skills. Through reward networks, music can induce pleasure through releasing dopamine. It can also serve recreational usages, best harnessed to reduce the perception of pain. Music has potential to help treat psychological and neurological disorders due to its neuroplasticity effects. Furthermore, it can reduce anxiety, improve sleep quality, and promote physiological growth. Although much is still unknown about the neural mechanisms underlying the effects of music, what we do know indicates that music as a form of treatment could be used effectively for a broad range of conditions in the future.

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References Calma-Roddin, N., & Drury, J. E. (2020). Music, Language, and The N400: ERP Interference Patterns Across Cognitive Domains. Scientific Reports, 10(1), 11222. https://doi. org/10.1038/s41598-020-66732-0 Cardona, G., Rodriguez-Fornells, A., Nye, H., Rifà-Ros, X., & Ferreri, L. (2020). The impact of musical pleasure and musical hedonia on verbal episodic memory. Scientific Reports, 10(1), 16113. https://doi.org/10.1038/s41598-020-72772-3 Caria, A., Venuti, P., & de Falco, S. (2011). Functional and dysfunctional brain circuits underlying emotional processing of music in autism spectrum disorders. Cerebral Cortex (New York, N.Y.: 1991), 21(12), 2838–2849. https://doi.org/10.1093/ cercor/bhr084 Castro, M., L’héritier, F., Plailly, J., Saive, A.-L., Corneyllie, A., Tillmann, B., & Perrin, F. (2020). Personal familiarity of music and its cerebral effect on subsequent speech processing.

Scientific Reports, 10(1), 14854. https://doi.org/10.1038/ s41598-020-71855-5 Cordi, M. J., Ackermann, S., & Rasch, B. (2019). Effects of Relaxing Music on Healthy Sleep. Scientific Reports, 9(1), 9079. https://doi.org/10.1038/s41598-019-45608-y Daly, I., Malik, A., Hwang, F., Roesch, E., Weaver, J., Kirke, A., Williams, D., Miranda, E., & Nasuto, S. J. (2014). Neural correlates of emotional responses to music: An EEG study.

Neuroscience Letters, 573, 52–57. https://doi.org/10.1016/j. neulet.2014.05.003 Foroushani, S. M., Herman, C. A., Wiseman, C. A., Anthony, C. M., Drury, S. S., & Howell, M. P. (2020). Evaluating physiologic outcomes of music interventions in the neonatal intensive care unit: A systematic review. Journal of Perinatology. https:// doi.org/10.1038/s41372-020-0756-4 Gupta, A., & Ahmed, B. (2020). Experience of listening to music on patient anxiety during minor oral surgery procedures: A pilot study. British Dental Journal, 228(2), 89–92. https://doi.org/10.1038/s41415-019-1162-1 Heine, L., Tillmann, B., Hauet, M., Juliat, A., Dubois, A., Laureys, S., Kandel, M., Plailly, J., Luauté, J., & Perrin, F. (2017). Effects of preference and sensory modality on behavioural reaction in patients with disorders of consciousness. Brain Injury, 31(10), 1307–1311. https://doi.org/10.1080/02699052.2017.1306108 Koelsch, S. (2014). Brain correlates of music-evoked emotions.

Nature Reviews Neuroscience, 15(3), 170–180. https://doi. org/10.1038/nrn3666 Koelsch, S., Bashevkin, T., Kristensen, J., Tvedt, J., & Jentschke, S. (2019). Heroic music stimulates empowering thoughts during mind-wandering. Scientific Reports, 9(1), 10317. https://doi.org/10.1038/s41598-019-46266-w Koelsch, S., Boehlig, A., Hohenadel, M., Nitsche, I., Bauer, K., & Sack, U. (2016). The impact of acute stress on hormones and cytokines and how their recovery is affected by musicevoked positive mood. Scientific Reports, 6(1), 23008. https:// doi.org/10.1038/srep23008 Kraus, N., & Chandrasekaran, B. (2010). Music training for the development of auditory skills. Nature Reviews Neuroscience, 11, 599–605. https://doi.org/10.1038/nrn2882 Martínez-Molina, N., Mas-Herrero, E., Rodríguez-Fornells, A., Zatorre, R. J., & Marco-Pallarés, J. (2019). White Matter Microstructure Reflects Individual Differences in Music

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Reward Sensitivity. The Journal of Neuroscience, 39(25), 5018– 5027. https://doi.org/10.1523/JNEUROSCI.2020-18.2019 Mas-Herrero, E., Dagher, A., & Zatorre, R. J. (2018). Modulating musical reward sensitivity up and down with transcranial magnetic stimulation. Nature Human Behaviour, 2(1), 27–32. https://doi.org/10.1038/s41562-017-0241-z Mehler, J. (2001). Language, Brain, and Cognitive Development: Essays in Honor of Jacques Mehler. MIT Press.

Maess, B., Koelsch, S., Gunter, T. C., & Friederici, A. D. (2001).

Musical syntax is processed in Broca’s area: An MEG study. Nature Neuroscience, 4(5), 540–545. https://doi. org/10.1038/87502 Patel, A. D. (2003). Language, music, syntax and the brain.

Nature Neuroscience, 6(7), 674–681. https://doi.org/10.1038/ nn1082 Pando-Naude, V., Barrios, F. A., Alcauter, S., Pasaye, E. H., Vase, L., Brattico, E., Vuust, P., & Garza-Villarreal, E. A. (2019).

Functional connectivity of music-induced analgesia in fibromyalgia. Scientific Reports, 9(1), 15486. https://doi. org/10.1038/s41598-019-51990-4 Salimpoor, V. N., Benovoy, M., Larcher, K., Dagher, A., & Zatorre, R. J. (2011). Anatomically distinct dopamine release during anticipation and experience of peak emotion to music. Nature Neuroscience, 14(2), 257–262. https://doi. org/10.1038/nn.2726 Taruffi, L., Pehrs, C., Skouras, S., & Koelsch, S. (2017). Effects of Sad and Happy Music on Mind-Wandering and the Default Mode Network. Scientific Reports, 7(1), 14396. https://doi. org/10.1038/s41598-017-14849-0

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The Universe’s Return to a Singularity: The Big Rip

BY RUJUTA PUROHIT ’24 Cover Image: A model of the growth and expansion of the universe, created according to the Big Bang theory and postulates of the Cosmic Microwave Background Radiation (CMBR).

Source: Wikimedia Commons

Introduction In 1932, Edwin Hubble published his findings about the expanding nature of the universe by observing far away stars. His research led to the Hubble law, which established one of the most fundamental truths known about the cosmos today: the universe is expanding, and it will keep expanding until some finite point in time. Hubble calculated the velocity of light coming from distant galaxies and observed that they were redshifted, meaning that those galaxies were moving away from the Earth. This conclusion is a premier supporting fact to the Big Bang. Hubble’s law (Harrison, 1992) is stated as:

Here, v is the relative velocity between the objects for which the redshift is being measured, D is the proper distance between them, and H0 is Hubble’s constant of proportionality.

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It is important to note that many scientists made discoveries about the expansion of the universe before Hubble. Vesto Slipher was the first to use a variation of the Doppler Effect to examine the relative velocity of spiral nebulae in 1912 (Slipher, 1913). The Doppler effect relates the motion of a body to the apparent change in its wavelength or frequency. This change is apparent because it is detected only by the observer. A common example of this is the change in frequency of sound that is heard as a honking car passes by. When the car is far away, the honk is heard as a faint sound.

But this sound becomes loud when the car is right in front. This change in the pitch of the sound that is observed it only apparent and is relative to the position of the observer and the source. Nevertheless, by studying the change, predictions can be made about the position of the source. Similarly, by observing the Doppler Effect for light, scientists can determine the DARTMOUTH UNDERGRADUATE JOURNAL OF SCIENCE

relative motion of any cosmological body with respect to Earth. If a body is moving away from the Earth, the wavelength is redshifted, and if it is moving towards the Earth, the wavelength is blueshifted. Slipher argued that the redshifts he observed were due to this relative motion.

This led him to conclude that some stars and galaxies are moving away from the Earth and thus, the universe is expanding. In 1922, Alexander Friedman utilized Einstein’s Theory of General Relativity to come up his own set of equations, called the Friedman equations, to hypothesize an expanding universe (Friedman, 1922). Georges Lemaître independently proved exactly what is considered Hubble’s law in 1927.

Because Lemaître’s research was published in a French journal that did not become popular until an English translation was made available, few know the importance of Lemaitre’s observations (Livio, 2011). On October 29, 2018, the International Astronomical Union voted with an overwhelming majority to rename Hubble law as the Hubble–Lemaître law (International Astronomical Union (IAU), 2018 Press Release).

The expansion of the universe was the first empirical data set that led to the development and widespread acceptance of the Big Bang model of the universe. The Big Bang sets very definite conditions for what the end of the universe will/should look like. The Big Rip is a hypothetical model for the end of the universe that is built upon the Big Bang model. It predicts that due to the expansion of the universe, there will come a time in the far future when the expansion becomes too large to sustain the fundamental physical forces of nature. When this happens, the universe will rip apart and lead to a space-time singularity similar to the one at the start of the Big Bang.

introduced, f(y, t) = density, plotted along the z-axis. This is not an accurate representation of variables on a graph, but it does make it easier to visualize the actual growth of the universe on a measurable scale.

In this argument, assume that the universe only exists in the first octant of the 3-D graph.

How do we know size of the universe at a time t = - 2 minutes? We don’t! And the Big Bang agrees. There was nothing before the singularity – even if there was, we can never know because it is impossible to go back in time. Now, let us consider for a moment, that we can go back in time. What happens to the position of our universe at t = - 2 minutes?

The size has physical significance because it is a real observable quantity and thus it cannot be negative, even if the position of an object is a vector quantity, which is why time cannot be negative. More specifically, there cannot be any ‘time’ before the singularity. This singularity was predicted and mathematically proven by Roger Penrose, Stephen Hawking, and George F. R. Ellis. They stipulated that this singularity was a necessary initial condition of the Big Bang model (Hawking et al., 1968) Many astronomical calculations and estimations about the motion of bodies in space are made using ‘relativistic’ approximation, building upon Einsteins’s theories of Special and General Relativity. The Theory of Special Relativity is not widely used in space physics, but it has two interesting postulates that are valid everywhere. These postulates apply to the Big Bang and will hold true for the Big Rip. The postulates are as follows:

The Big Bang and Cosmic Microwave Background Radiation (CMBR)

1. The laws of physics – in their simplest and most complex form – are always the same in all inertial reference frames.

2. The speed of light, c, is a constant and remains independent of the relative motion of the source.

The Big Bang is the most widely accepted model of the preliminary cosmological state of the universe. In simple words, it says that the universe began from a starting point of extremely high temperature and density. At this starting point, there is believed to be a singularity – a one-dimensional point in space where both position (that is, space) and time have no meaning because they haven’t evolved yet. A good way to visualize this is to look at the singularity as the origin of a 2-D Cartesian plane, with position on the y-axis and time on the x-axis. As time passes, the universe grows larger. To account for this, a third variable can be

These postulates tell us that irrespective of what happens in the universe at any place and any time, these things will happen (Einstein, 1905). Although it might sound vague and unnecessary, these postulates are important in narrowing down incidents that happen on a cosmic scale. For example, it is known that humans can never see a black hole on the visible spectrum of electromagnetic radiation because light of visible wavelengths cannot get past the event horizon. This famous example upholds the second postulate. Another way the postulates can be used is when determining the nature of chemical and physical reactions

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"The Big Rip is a hypothetical model for the end of the universe that is built upon the Big Bang model. It predicts that due to the expansion of the universe, there will come a time in the far future when the expansion becomes too large to sustain the fundamental physical forces of nature."

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Figure 1: An all-sky sweep of the universe, capturing the relative distribution and intensity of CMBR, captured by WMAP. These sky-sweeps are used extensively to map the universe and pinpoint locations of extreme redshift.

Source: Wikimedia Commons

that take place in the universe – in the cores of massive stars or in the centre of a nebula.

"Through their extensive research, Alpher and Herman concluded that if the Big Bang model held true, the growth of the universe had to be accelerated, and still allow for the universe to be able to cool down to its current temperature."

The Big Bang theory, thus, is our origin story.

The Big Bang theory is parametricized by the Λ-CDM model of the universe. The model seeks to explain the structure and composition of the universe using three physical quantities: Λ - the cosmological constant that denotes the energy density of vacuum or free space, CDM – a hypothetical form of dark matter called cold dark matter (CDM), and ordinary matter that makes up the visible universe. The value and origin of Λ is present in Einstein’s field equations and his Theory of General Relativity. Dark matter is heavily factored into the calculations made by this model because it is physically impossible to reach observed values of quantities like cosmic microwave background radiations (CMBR) and effects of gravitational lensing without accounting for it.

The Λ-CDM model also accounts for CMBR – one of the major discoveries of the 20th century that provides far-echoing proof of the Big Bang Theory. CMBR is the electromagnetic radiation leftover from the Big Bang that fills every nook and cranny of space and can be detected using radio telescopes. CMBR is the faint green glow often seen in radio pictures of the universe. First predicted by Ralph Alpher and Robert Herman in 1948, it was actually accidentally discovered

by Arno Penzias and Robert Wilson in 1964. The exact temperature of the background radiation is measured precisely to a value of 5 K (-268.15°C).

The average temperature of space itself is 2.7 K (-270.45°C). There are fluctuations , called anisotropies, in measurements depending on the regions of space probed, but a general average value is 2.72548 ± 0.00057 K (Fixsen, 2009). It

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is interesting to note that these fluctuations themselves are consistent. For example, all values of CMBR measured in a relatively newer (blueshifted) part of the universe would be the same (Assis & Neves, 1995). This temperature of the CMBR was related to the redshift z calculated using the Doppler Effect as (Alpher & Herman 1948):

Through their extensive research, Alpher and Herman concluded that if the Big Bang model held true, the growth of the universe had to be accelerated, and still allow for the universe to be able to cool down to its current temperature.

At the instant of the Big Bang, the temperature of the universe is believed to have been 1023 K (Noterdaeme et al., 2011). The CMBR, as the name suggests, lies in the microwave region of the electromagnetic spectrum. Thus, to get to this microwave region of the spectrum, the universe needed time to cool down. This explains why CBMR is detected more strongly in relatively older regions of space.

The CMBR can be thought of as an image of the universe at a particular time in its very early beginning. This is important because it is the “leftover” radiation, so it has been in the universe ever since that particular time.

Therefore, studying the remnant radiation from the early stages of the universe is essentially studying the early universe itself. This stage of the young universe is the time when protons and neutrons collied to form hydrogen atoms, only 100 seconds after the Big Bang explosion happened. Later, deuterons combined with each other to form helium. At this stage, the universe looked transparent instead of having

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In a scenario in which the universe keeps expanding uniformly – without any end like the Big Rip in sight (an immortal universe per se) – the CMBR will keep getting red-shifted as time goes on because cosmological bodies are rapidly moving away from us and space itself is getting stretched. At some point, the CMBR will be so immensely red-shifted that it will not be detected by the strongest telescopes (Krauss & Scherrer, 2007). At this stage, it will fade away under the strong influence of other light sources in space like massive stars (Adams & Laughlin, 1997).

Figure 2: Mass distribution of dark matter and ordinary matter in the galaxy cluster Abell 1689.

The appearance of blurred galaxies outside the purple region depends on the effects of dark energy on the geometry of the cosmos.

Source: Wikimedia Commons

Dark Energy and Dark Matter

the opacity that was earlier predicted (this is partly due to inhomogeneities in dark matter!).

Because electrons were combining with protons, there were no free electrons to scatter off photons (light) resulting in no photons, especially in the visible spectrum of the electromagnetic radiation that would produce color (Noterdaeme et al. 2011). An exact time for when this happened is calculated to be at 380,000 years after the Big Bang, meaning that was the point in time that the first particle of ordinary matter appeared. The temperature was a mere 3000 K (Fixsen, 1995). This first hydrogen atom combined with other hydrogen atoms and various other subatomic particles to create the first stars and galaxies that emerged 100-200 million years after the Big Bang. Our solar system was created only 4.571 billion years ago, 9.129 million years after the Big Bang! This means that the Big Bang happened 13.7 billion years ago.

Extensive data has been gathered about CMBR by various probes and satellites launched over the years, including the Wilkinson Microwave Anisotropy Probe (WMAP), NASA Cosmic Background Explorer (COBE), Very Small Array, Degree Angular Scale Interferometer (DASI), and the Cosmic Background Imager (CBI).

WMAP was used to make the first accurate Mollweide image of observable space. The images gave further insight into the exact distribution of CMBR and how its density affects many other cosmological phenomena (Bennett et al., 2003). The data gathered is used to study the anisotropies in measurements of CMBR, which is used to create more specialized models of the universe and better understand how the Big Bang happened.

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In cosmology, dark energy is an unknown form and amount of energy that is present in the universe on a large scale. Dark energy reportedly makes up 68% of the universe’s energy while dark matter makes up about 27% of the universe’s matter (Tanabashi et al., 2019).

There is no official definition of dark matter yet, but it can be thought of as any matter – simply not seen through the naked eye and not picked up through standard telescopes – that interacts with the gravitational forces of cosmological bodies, like stars and planets (Trimble, V. 1987, Tanabashi et al., 2019). The remaining 5% is ordinary matter, also called baryonic matter – matter we can see and touch. Everything that is photographically or analytically known about the universe – planets, stars, galaxies, supernovae, human beings, and black holes – are a part of this 5% (Tanabashi et al., 2019).

"In cosmology, dark energy is an unknown form and amount of energy that is present in the universe on a large scale. Dark energy reportedly makes up 68% of the universe’s energy while dark matter makes up about 27% of the universe’s matter."

The main reason that dark energy makes up such a large percentage of energy is that it is incredibly dilute and easily fits into empty space. It is believed that, despite previous observations, dark energy is fluid, low-density, and homogenous. Most of these properties are based on pure speculation and a general process of elimination, but they do come from logical grounds. Currently, many projects are underway to gather more data about dark energy. Promisingly, Dark Energy Survey has been using visible and near-infrared imaging through the four-meter-long Victor M. Blanco Telescope in Cerro Tololo Inter-American Observatory (CTIO) in Chile (Maeder et al., 2018).

Dark energy was discovered accidently, like so many other important discoveries made in the sciences. After receiving much credit, Hubble’s theory of the expanding universe inspired many experimental astronomers to carry out their own observations in different

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"Dark matter, like dark energy, cannot be seen but it can be detected.

Scientists first came up with the idea of dark matter after a discontinuity in math that predicted that galaxies and stars would zoom apart if they were not bound together by more than just gravitational forces."

parts of the night sky to gather data about the exact nature of this expansion. The High-Z Supernova Search Team scanned the universe for supernovae and measured the extent of their Doppler Shift. Supernovae are commonly called “standard candles” across the universe because their luminosity can be calculated using their distance to the earth. These values are then used to measure their redshift by applying Hubble’s law. The High-Z Supernova Search Team recorded their observations for a specific type of supernovae – the Type Ia supernovae (a type of supernova that is found in binary star systems in which one of the two stars is a white dwarf. The name does not have any special meaning, it is a part of the system developed by astronomers Rudolph Minkowski and Fritz Zwicky to characterize different kinds of supernovae) (Silva, 1993). In 1998, the High-Z Supernova Search Team published observations of Type Ia supernovae. Following these observations, the Supernova Cosmology Project, along with The High-Z Supernova Search Team, were the first teams to find experimental evidence in deep space that proved many theories about the expansion – including Hubble’s law – correct.

The observations of supernovae were used to create a new model of the universe that was consistent with the Λ-CDM model.

Despite these strides in understanding dark energy, the exact science behind it is still hypothetical and is mostly based on speculation.

All experiments conducted in a laboratorycontrolled environment have never produced any similarity to the Λ-CDM model or any trace of dark energy (Sabulsky et al., 2019).

There are many umbrella theories within the Big Bang that attempt to find explanations for the mysterious nature of dark energy, from Einstein’s cosmological constant predictions to Quintessence, but none have succeeded.

Einstein’s theory builds up on the mass-energy equivalence. His claims were simple – empty space is not nothing and can possess its own energy. This energy of empty space that comes from having no mass is now thought to be dark energy.

Dark matter, like dark energy, cannot be seen but it can be detected. Scientists first came up with the idea of dark matter after a discontinuity in math that predicted that galaxies and stars would zoom apart if they were not bound together by more than just gravitational forces (Siegfried, 1999). Little is known about dark matter, but it is hypothesized that it is made up of undiscovered subatomic particles, other

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than the ones currently classified. Meaning that there might be another set of subatomic particles – beyond protons, neutrons, electrons, quarks – that we have not discovered yet. However, this is disputed. Many scientists have used highly advanced detectors to scan the night sky but have never found any trace of dark matter. Experiments conducted at the Large Hadron Collider to produce or detect sub-atomic particles called Weakly Interacting Massive Particles (WIMS) which existed in the early stages of the universe have also failed.

Dark matter is not present in the form of dark clouds of ordinary matter. It is also not found in expected places like planets, stars, or galaxies.

These objects are made up of only ordinary matter. So, for dark matter to exist naturally in our cosmos and create the cosmos itself (as it is currently present) it must not interact explosively with baryonic matter (Trimble, 1987).

Cold dark matter – the type of dark matter used in the the Λ-CDM model of the universe – is actually no different than normal dark matter.

‘Cold’ here isn’t a measure of temperature but a term for the fact that dark matter moves very slowly as compared to the speed of light. The word dark is used to clarify that this matter only weakly interacts with ordinary matter and light (Peebles, 1982).

There is a class of theories about the nature of physical space that attempt to combine the concepts of dark energy and dark matter in one explanation. This is called the dark fluid theory (Arbey, 2005). The theory says that dark matter and dark energy can be thought of as two nodes of the same ‘dark fluid’. At galactic scales, dark fluid acts like dark matter while at larger scales, it behaves like dark energy (Farnes, 2018). The all-encompassing idea about the dark fluid theory is that when it is present around normal, baryonic matter, it slows down and coagulates.

The coagulation attracts more dark fluid to the baryonic matter and thus results is stronger gravitational forces around the baryonic matter (Exirifard, 2011). Thus, we can only detect the dark fluid when it is present around very heavy ordinary matter like a galaxy or star cluster. In contrast, dark energy is found in places of little baryonic matter, where it relaxes and exerts a so-called negative gravitational force. Because there is no standard model of dark energy and dark matter, theories like this have a lot of merit, both in their conception and application.

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Figure 3: An artist’s hypothetical, step-by-step collision of the Milky Way and Andromeda galaxies, as seen from Earth.

Source: Wikimedia Commons

The Big Rip Unlike the Big Bang beginning of the universe which has been investigated, explored, and supported by multiple sub-theories within astrophysics, the Big Rip theory is still relatively young and is undergoing various developments. However, it is believed to have more merits compared to the other end-of-theworld theories like the Big Crunch and the Big Freeze. Hence, even with a comparable lack of research backing it up, the Big Rip hypothesis is considered to be the most probable fate of the universe.

The Big Rip theory is easy enough to visualize.

If the universe is expanding exponentially and accelerating in all possible dimensions, there will come a point when it expands so much that it simply rips apart. This can be compared to the common model of a balloon. The process of blowing air into the balloon is what the universe looks like right now – growing larger every second. When there is too much air inside the balloon, the walls of the balloon can

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no longer survive under the pressure the air is exerting on them, causing the balloon, or the universe, to pop. The comparison of the Big Rip to this balloon comes with another assumption, one that can be viewed as a more philosophical or metaphysical question. The universe is expanding into something. If that balloon is being blown up in a room or a park, the balloon takes up space that was previously occupied by the room or the park. So, if the universe is expanding, there has to be something outside its boundaries. But, then again, the universe is not flat. It is multidimensional and abstract.

"The Big Rip theory is easy enough to visualize. If the universe is expanding exponentially and accelerating in all possible dimensions, there will come a point when it expands so much that it simply rips apart."

If the earth is considered the point of reference (a random place in space from which all measurements are carried out), then the “ends” of the universe are continually moving away (ie. they are redshifted). These redshifted areas in space cannot be observed as they are physically moving away from the reference point. This led scientists to conclude that the size of the observable universe is shrinking.

When this hypothesis holds true, it becomes

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obvious that the basic forces in nature cannot interact with each other at these unobservable areas between space. In other words, point A in the unobservable region cannot interact with point B in the same region. Because there are no forces sustaining these two points, the entire universe rips apart. This is the Big Rip – an event in the far future of the cosmos when the universe is expanding so fast that it is unable to hold itself together. It is believed that at the point of the Big Rip there will be another, final singularity, at which the universe is at size zero again. It is unclear where the singularity will be, but the most popular hypothesis say that the singularity will lie at the center of the observable universe – when everything but that center has become unobservable.

"At this instance, the Sun is slated to become a red giant on its 12 billionth birthday. When that happens, it will expand immensely to engulf both Mercury and Venus inside itself. The Earth will interact with the Sun's outer atmosphere, leading to a decrease in the Earth's orbital radius.

At some point, the Sun will probably engulf the Earth as well."

The estimated time from the present day to the day of the Big Rip is calculated using Hubble’s constant, H0 , and density of matter in the universe, Ωm as:

Here, ω is called the equation of state parameter.

It is defined as the ratio of the pressure of dark energy to the dark energy density. The team of Robert Caldwell, Marc Kamionkowski, and Nevin Weinberg, estimated the time from the present to the Big Rip by using various values of ω. Experimental evidence says that the value of ω is very close to -1, which means that the closer ω is to -1, the farther away the Big Rip is in the future (Caldwell, et al., 2003). However, if ω were exactly equal to -1, the denominator in the equation would become 0 and the Big Rip will never actually (mathematically) happen (Allen et al., 2008).

In their paper, authors Caldwell, Kamionkowski , and Weinberg used a hypothetical example, in which they calculated that the Big Rip would happen approximately 22 billion years from the present. As the universe continues to expand and the unobservable regions increase in area and move away from the future singularity, gravitational forces become too weak to hold bodies (like galaxies) together (gravitational force between two objects is inversely proportional to the square of the distance between them), and they rip apart – or disintegrate. This is predicted to happen about 50 million years before the Big Rip (Caldwell, et al., 2003). The solar system and other star-planet systems would also no longer be bound together and would move away from

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their present positions. Planets would fly off into the rapidly expanding universe. Assuming that the Earth lives this long, it would be among those planets that is flung away into space.

Once away from the Sun, life on Earth would disappear in a matter of minutes. Moreover, even if there is no life on Earth by then, the atmosphere would crunch down to the surface, the water in the oceans would wreak havoc, and the magnetic field would be disturbed. In the last minutes, stars and planets would be torn apart, and the now-dispersed atoms would be destroyed about 10−19 seconds before the end.

At the time the Big Rip occurs, space itself will be torn apart. This will happen because gravity itself will become too weak to hold cosmological bodies together, like in the expanding balloon example. After being perturbed from these steady equilibrium positions, stars, and planets, including the Earth, would collide with other free moving objects. Like matter forming in the first few minutes after the Big Bang, matter would annihilate in the last few minutes before the Big Rip. Ordinary matter would crumble to nothing by virtue of its inter-atomic forces. As grim as it sounds, everything will be destroyed. Less is known about how the universe would look close to the Big Rip because of the unanswered questions about dark matter and dark energy (Devlin, 2015). Once ordinary matter rips apart, the only things left would be dark energy and dark matter and they will greatly influence how the universe behaves as it nears the end. This is why it is of crucial importance to study the natures of dark energy and dark matter – to learn more about the behavior of the universe in not only this situation but in any other hypothetical scenario.

However, it is highly unlikely that the Earth and the Solar System will survive long enough to be a part of the Big Rip. At this instance, the Sun is slated to become a red giant on its 12 billionth birthday. When that happens, it will expand immensely to engulf both Mercury and Venus inside itself. The Earth will interact with the Sun's outer atmosphere, leading to a decrease in the Earth's orbital radius. At some point, the Sun will probably engulf the Earth as well (Schröder & Smith, 2008). If not, then, the Earth lives long enough to witness the Big Rip. (It is actually predicted that the Earth is currently on track to collide with an asteroid similar to the one that caused the K–Pg extinction 66 million years ago that resulted in the extinction of many species of Earth, like the dinosaurs)

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(Nelson, 2018).

Contenders to the Big Rip Two famous alternate theories to the Big Rip are the Big Crunch and the Big Freeze (also called the Big Chill or the Heat Death). These theories also use the Big Bang as their starting point and follow along those pre-determined conditions.

The Big Crunch is an exact opposite of the Big Bang. The end of the universe would be the exact opposite of its start. In the Big Crunch, after a point in time, the universe would stop expanding and start contracting (Perlmutter et al., 1999). Objects will rapidly move towards each other and get condensed into a single particle of incredibly high density and temperature. The CMBR temperature will increase greatly when the universe moves towards (or moves back towards) a singularity owing to the blueshift of photons that can be observed. After this, that particle or singularity will explode, leading to another Big Bang and the creation of another new universe. Whether this second universe will be same as the first one is unknown, but the same laws of physics would apply – even if the human race ceases to exist in the second universe to actually apply these laws. Some physicists even predict that the Big Crunch will happen about 100 billion years from the present day (Davies, 1997).

This Big Crunch model follows the concept of a complicated gravitational collapse – similar to the collapse of a star at the time of its death (Perlmutter, 2003). All the matter from the ends of the universe is suddenly pulled to the center.

The Big Crunch would happen in a matter of Planck seconds (10-44 seconds)!

The Big Freeze, on the other hand, states that because the universe is expanding so rapidly and cooling down as compared to its initial state, there will come a point in the far future when the universe simply becomes too cold to sustain human life. In this model, the universe keeps expanding forever, with no sudden snap like the Big Crunch or the Big Rip. By this point in time, stars would have already exhausted their supply of gases and all other bodies like planets would have been destroyed by proton decay.

In the degenerate era 100 trillion years from the present, galaxies will die out as well. The only heavenly bodies left in the cosmos would be black holes, simply drifting off into space (Adams & Laughlin, 1999). Later even black holes will die out due to a continuous emission of Hawking radiation, leaving absolutely nothing in the cold universe. Because this end of the

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universe takes place billions of years into the future, the universe will still be expanding up to that point and will look very much different than it does now. For instance, five billion years from the present, the Milky Way galaxy and the Andromeda Galaxy will collide with each other and create a composite, much larger galaxy. In this collision, there is a chance that in “Milkomedra”, our Solar System will be flung out of this composite galaxy and just float away in space until it is attracted by another galaxy or star cluster (by the time this happens, the Earth will be too hot and too dense to sustain any form of life). There is, however, a greater chance that the Solar system will still remain with Milkomedra but be three times farther away from the galaxy cluster which includes the core of the new galaxy (Cox & Loeb, 2008).

Furthermore, the galaxies in the Local Group (the galaxy cluster that includes the Milky Way and the Andromeda Galaxy), are gravitationally bound to each other and will merge into one large galaxy because of their decaying orbits.

This will happen about 1 trillion years from the present (Addams & Laughlin, 1997).

"The Big Crunch is an exact opposite of the Big Bang. The end of the universe would be the exact opposite of its start. In the Big Crunch, after a point in time, the universe would stop expanding and start contracting."

Conclusion The Big Rip theory is one of many postulated theories that predicts the ultimate of the universe. It follows along many conditions set by the Big Bang theory – the most widely accepted beginning of the world theory. Physically invisible quantities like dark energy and dark matter are abundantly present in space that are responsible for maintaining the balance of all cosmological bodies. The existence of these quantities has been confirmed through various studies and observations of different regions of space. Many experimentally determined parameters also make up the general model of the universe, such as the cosmic microwave background radiation (CMBR), dark energy, and dark matter. The Big Rip theory builds upon the Big Bang and the expansion of the universe and says that, due to this rapid and constant expansion, there will come a time in the far future when everything in space gets stretched thin. At this stage, the normal forces of gravity are not enough to hold the universe together.

As a result, it will be ripped apart from one edge to the other, like a balloon popping. There are 2 other famous theories for the end of the world – the Big Crunch and the Big Freeze. These theories use similar models but have different ideas about the ultimate fate of the cosmos.

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Markov Chain Monte Carlo Utility in Systems Biology

BY STEPHANIE FINLEY ’23 Cover Image: Chaotic systems pose challenges in mathematical modeling and parameter estimation. Markov Chain Monte Carlo can be an effective tool for estimating parameters from chaotic systems, like the energy waves shown above.

Source: Pixabay

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Introduction Ordinary differential equations (ODEs), in which variables are related to their derivatives, are widely used to model systems in many fields including biology and economics, among others. The dynamic behavior of ODE systems is determined by their parameters (ValderramaBahamóndez & Fröhlich, 2019). However, these parameters are often unknown and must be estimated from data. Parameter estimation aims to find unknown parameters which give the best fit to a known result obtained from experimental data. This is the reverse of traditional model simulations, which use a set of known parameters to predict a result. In parameter estimation, it is important that the model include both a prior (structural) and posterior (practical) parameter. The prior is the hypothesized distribution before data is taken into account, and the posterior distribution is equal to the prior plus data. If the parameter cannot be measured, then the parameter is

estimated to ensure the best fit of the model, incorporating information from experimental results. This is fulfilled through a global minimization of an objective function which measures the quality of the fit; a cost function is also optimized to find the maximum likelihood.

For nonlinear, dynamic models, this function has to be solved numerically which is quite difficult, as numerical data fitting has many issues in dynamic systems (Gábor & Banga, 2015).

Parameter estimation combats the difficulties created by fitting data numerically, but this is accompanied by limitations. Some of the issues generated by parameter estimation are ill-conditioning and nonconvexity. Illconditioning occurs in models with many parameters, little experimental data, and/or significant measurement errors. These models are subject to overfitting and have poor capability for generalization. Most mechanistic DARTMOUTH UNDERGRADUATE JOURNAL OF SCIENCE

dynamic models are prone to this overfitting, where they are severely over-parameterized or calibrated with information-poor data (Gábor & Banga, 2015). Nonconvexity causes a convergence to a local minimum that is actually just an estimation error rather than a high-quality fit for the data. Thus, suitable global optimization methods are necessary because standard local optimization methods lead to local solutions that produce erroneous conclusions (Gábor & Banga, 2015).

Markov chain Monte Carlo (MCMC) is a method of parameter estimation that allows researchers to fit more complex models to data than would be feasible with conventional methods. There is a misconception that MCMC requires an adoption of subjective Bayesian analysis techniques due to MCMC’s probability based foundation. Furthermore, an effective intuition for MCMC does not require extreme mathematical skills. MCMC is simply a statistical tool used to analyze large and complicated data sets, especially ones with a hierarchical structure. Unfortunately, due to the Bayesian flavor of MCMC, those with a classical (frequentist) training in data analysis ignore it as a method for parameter estimation. However, MCMC is extremely useful to obtain maximum likelihood, even for models with a complexity that defies conventional analysis. With the lack of familiarity and complex mathematical ideas that underlie the technique, there is a need for a clear explanation of what MCMC does and how it works (Link et al., 2002).

The primary distinction between Bayesian and frequentist analyses is the interpretation of model parameters. In Bayesian analysis, the data is drawn from a sampling distribution and governed by a parameter theta. In frequentist analysis, theta is regarded as both fixed and unknown, whereas in Bayesian analysis theta is a random variable. Frequentist analyses describe effects of variability on data by reference to hypothetical replicate data sets that are drawn from the same sampling distribution (or a hypothesized version of the sampling distribution that produced the data). P-values and unbiasedness are defined with reference to this hypothetical replicate draw strategy, and the statistical procedures are evaluated by their typical performance under similar circumstances. In frequentist analysis, a distinction must be made between an estimator and an estimate. The estimator can be thought of as a machine that produces the estimate, where the accuracy and precision are properties of this machine – not what it produces. The estimate cannot be described as FALL 2020

unbiased because unbiasedness is an inherent property of the estimator. The confidence interval convergence rates should be similarly defined as features of the machine rather than its product, where the convergence rate or desired result is obtained in 95% of similar circumstances (Link et al., 2002). In an example where a person is running from a bear with bear spray that is accurate 95% of the time while running, the person will not know if they have sprayed the bear, but the desired result (hitting the bear) is obtained in 95% of similar circumstances. The likelihood of hitting the bear is a feature of the circumstance (using the spray while running) and not of the bear spray itself.

By regarding theta as a random variable, Bayesian analysis makes direct probability statements about the parameters instead of indirect statements like frequentist analysis.

Two probability distribution functions are used to make statements about theta: the prior and posterior distributions. Thus, the same random variable can be described by two different distributions; this idea may seem strange but becomes clearer when compared to the probability of winning a game (Link et al., 2002). In this hypothetical game, each group has a fifty percent chance of winning, but then one group trades out a member for another member who is an expert, increasing their chance of winning to 80%. This variable of winning is described by two different distributions: the 50-50 distribution and the 80-20 distribution. The additional information (the expert player being added) modifies the probabilities, which is the case for parameter descriptions in Bayesian models. The prior distribution summarizes what is known about ranges and associated probabilities for theta without reference to the data (Y). The posterior distribution provides the same summaries informed by Y, but also describes the ranges of possible values for theta where probabilities are a combination of data and prior knowledge.

The inference about theta is then made based on the posterior distribution by applying a theorem to the prior and then sampling the distribution. The Bayesian paradigm provides a mechanism for combining existing knowledge with indications provided by data, where prior + data = posterior. This paradigm is useful for the analysis of complex data sets that are governed by numerous parameters (Link et al., 2002).

For Bayesian analysis to be as effective as possible, some important features must be understood. First, Bayesian analyses have to

"Markov chain Monte Carlo (MCMC) is a method of parameter estimation that allows researchers to fit more complex models to data than would be feasible with conventional methods."

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Figure 1 (MCMC Code and Graphs, 2020): MCMC code examples and graphs that yield showing the chain convergence as well as the posterior and prior distributions. Code modified from Chan & McCarthy’s code and Carsten’s code (Carstens, 2020; Chan & McCarthy, 2016).

Image taken by author.

"MCMC is an extension of ordinary Monte Carlo methods, which are used to evaluate model predictions and distributions of test statistics especially when asymptotic approximations are insufficient."

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begin with a known distribution (a specified prior), however this can be relaxed to knowing what family of distributions likely contains the prior. The specified prior is imperative as the prior and the data formulate the posterior distribution, so without a prior it is impossible to find the posterior. A positive aspect of Bayesian analysis is increased precision, but this can also be costly because performance of the estimator depends on the validity of the model specifications.

MCMC relates to Bayesian statistics as it is a tool for evaluating posterior distributions. It helps to circumvent the difficulties associated with calculation of posterior distributions, because for many models, a calculation of an impossible integral would be necessary (Link et al., 2002).

MCMC is an extension of ordinary Monte Carlo methods, which are used to evaluate model predictions and distributions of test statistics especially when asymptotic approximations are insufficient. In Monte Carlo applications, simulations are used in place of intractable mathematical calculations. Yet, there are difficulties associated with calculating the posterior distribution, so the question arises of whether Monte Carlo can be applied to Bayesian analysis. A simple way to apply Monte Carlo to Bayesian methods is to generate the independent sample from the posterior by producing a first-order Markov chain of values sampled from prior distributions without having to calculate the integral that is found when drawing independent samples from a posterior distribution (Link et al., 2002).

A first order Markov chain is a sequence of dependent observations. The chain has the property that the distribution for Xt+1, given previous observations, only depends on Xt. This means that instead of having to generate a sequence of independent observations from the posterior distribution–which is quite difficult–the analyst can simply generate a first-order Markov chain, then approximate the features of the posterior distribution (Link et al., 2002). Link and colleagues use an analogy to more clearly describe the method.

They recommend viewing a Markov chain as the activities of a bureaucrat with strong habits yet an individual who is quite absentminded (the defining Markov property) and aimless. This bureaucrat wanders from activity to activity making decisions solely on the basis of what he is currently doing. This set of activities is the state space, and the changes are the transitions. However, the bureaucrat’s strong habits are important as they make his Markov chain (his transient properties are determined by his current state, but they do not evolve over time). Assuming there is a 30% chance of the bureaucrat doing work at 8am one day, this probability carries over to the next. The probabilities determine his stationary distribution. MCMC essentially takes this information and determines whether there is a transition matrix that yields a specified stationary distribution (Link et al., 2002).

MCMC on Biological Systems MCMC can be used quite effectively on

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biological systems. ODEs are used for dynamical system modeling in almost all scientific fields, yet the challenge in biology is that biological systems often have kinetic rate parameters that must be estimated from data. The nonlinearity of these ODE systems along with noise from the data causes some issues, and noise is an inherent property of biological models as it appears in natural processes ranging from molecules to ecosystems. MCMC can estimate the distributions of rate parameters, which correspond to local maxima. Furthermore, there are often ODEs that have unidentifiable parameters in biological systems which (along with some of the local maxima) would be missed were one to use simple optimization techniques. MCMC follows the Bayesian inference paradigm and estimates the full posterior distribution of kinetic rate parameters.

Some examples of biological systems where this methodology has been applied would be for influenza transmission, cyclosporine on the Nrf2 pathway, B and T-cell dynamics induced by varicella (chickenpox) vaccines, and many others. MCMC works to define a convergent Markov chain over sampling process and limit guarantees to draw from true stationary statistical distribution, which is necessary for understanding kinetic rate parameters in systems biology (Valderrama-Bahamóndez & Fröhlich, 2019).

MCMC can also be used in other biological fields such as population genetics. Methodology developed by Kuhner and colleagues at the University of Washington showed that inference of population genetics parameters is possible for complex mutational models, and thus were the first to use true MCMC methodology in population genetics (Kuhner et al., 1995). However, MCMC’s basic properties allow it to be applied to other fields as well.

MCMC methods are developed in order to find approximate solutions. This allows for simulations that can then be used to integrate over the space of genealogies, allowing other parameters to be integrated out analytically.

The result approximates the full joint posterior density of the model parameters. Using these properties, Hey & Nielsen applied MCMC within the Felsenstein equation–an equation designed for analysis and estimation in population and evolutionary genetics. Population genetics and phylogenetic models suffer the uncertainty of an estimate for two main reasons: they are large and difficult to quantify, and it is difficult to interpret genealogy estimates explicitly in terms of evolutionary or population genetics

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models. Felsenstein conceptualized a way through these uncertainties, given the data, positioning genealogy as a nuisance variable in the definition of likelihood parameters (Kuhner et al., 1995 and Hey & Nielsen, 2007).

Hey & Nielsen’s application improves methods in population genetics. Felsenstein made a framework for assigning likelihood of a genetic data set where each possible genealogical history of data is considered in proportion to probability. However, this is not analytically solvable. Since the function is based on likelihood, one can use likelihood-based analysis. Luckily, MCMC is an example of likelihood-based analysis (Hey & Nielsen, 2007).

Hey & Nielsen applied this methodology to the divergence of chimpanzee subspecies, but it could be applied to other population genetic models. The Markov Chain can draw from the posterior density of the genealogies by using the genealogies that have been sampled (using one parameter value to estimate the relative likelihood for other values). The Markov Chain explicitly considers a prior distribution and simulates with stationary measures given by the joint posterior density. Their method runs a Markov Chain over a state space of genealogies and model parameters (Hey & Nielsen, 2007).

In population genetics, a shortcoming stems from the essential form of the result, where the result is not a function estimate and instead a record of parameter values. However, with some tweaking, Hey & Nielsen found a method that uses a Bayesian sampling strategy to generate an estimate of relative likelihood, where they can find a maximum likelihood estimate and conduct other analyses. This approach can be used for other models such as island models, where multiple populations of the same size have been exchanging genes at constant rates for long enough that the probability of a genealogy is solely a function of population sizes and migration weeks. Hey & Nielsen go through a long proof of their model and find a function that can, in principle, be maximized for all/any subset of parameters in the domain. Their study demonstrates some of the versatility of MCMC in systems biology and the method’s adaptability. Essentially, they considered the case of two chimpanzee subspecies and showed that the model fit and was effective in predicting the genealogical outcome. Their method improves access to a broad family of population genetics models, including ones that can be described with one or more population size and migration

"MCMC follows the Bayesian inference paradigm and estimates the full posterior distribution of kinetic rate parameters.

Some examples of biological systems where this methodology has been applied would be for influenza transmission, cyclosporine on the Nrf2 pathway, B and T-cell dynamics induced by varicella (chickenpox) vaccines, and many others."

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parameters, and should help to alleviate some problems that have prevented frequent use of MCMC in genetics. Model selection and testing of demographic hypotheses based on full-likelihood function have been neglected in molecular ecology and population genetics because appropriate tools for calculating likelihood ratios were not available. However, with Hey & Nielsen’s approach and computational framework, estimating likelihood functions and ratios becomes possible through mixing Felsenstein’s framework and MCMC methods (Hey & Nielsen, 2007).

"When applied to biological models, MCMC inherently becomes a method of computational biology.

Computational biology is the development of detailed mechanistic models of biological processes."

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While MCMC has been frequently utilized in some fields of biology, population genetics and wildlife research currently lack widespread MCMC use. This is not to say that it cannot be useful in these fields, as shown by Hey & Nielsen in their study, yet MCMC has generally been underutilized in wildlife applications. This is not due to an inability to apply it to this field of biology, but rather a lack of knowledge about MCMC techniques among wildlife researchers.

Link and colleagues illustrated a use of MCMC in wildlife research using an analysis of association between latent factors governing individual heterogeneity in breeding and survival rates of kittiwakes in order to understand whether tradeoffs exist between components of fitness—do more productive tend to have lower survival rates? (Link et al., 2002). They demonstrate the importance of heterogeneity for understanding population dynamics. Specifically, they analyzed the association between individual-specific latent factors governing survival and breeding rates using over 13 years of data with over 845 birds which were known to have bred at least once. This model included three parameters: two variances and one correlation. The correlation was in individual effects of special biological interest, where negative values would indicate that birds with higher survival probabilities would be less likely to attempt breeding, given that they survive. Likewise, a positive correlation would represent the idea that birds with higher survival rates would be more likely to breed.

While this is a specific use of MCMC in wildlife research, the Bayesian paradigm is useful for analysis of many complex data sets that are governed by numerous parameters. For instance, mark-recapture studies (a method used to estimate population through capturing part of a population, marking them, and releasing them, then later capturing another group and counting the number in the second group that was marked) that involve hundreds of parameters, some of which govern survival, could use MCMC

techniques to analyze parameter patterns like temporal trends in survival rates. Using a Bayesian approach involves a pattern of change reflected in the means of the posterior distribution (Link et al., 2002).

When applied to biological models, MCMC inherently becomes a method of computational biology. Computational biology is the development of detailed mechanistic models of biological processes. Often these models are stochastic and analytically intractable— there are uncertain parameters that have to be estimated from data. The inference for parameters of complex nonlinear multivariable processes is difficult, but algorithms based on particle MCMC turn out to be an effective, computationally intensive approach. MCMC can be applied to many biological systems due to their inherent noise. Golightly & Wilkinson analyzed the Lotka-Volterra (predator-prey) system and a prokaryotic autoregulatory network with MCMC methodology.

Interestingly, both of these systems are stochastic differential equations (SDEs). SDE’s are differential equations where at least one term is a stochastic (random) process thus yielding a stochastic result–meaning the result can have a random probability distribution, be defined as a family of random variables, or yield an imprecise prediction that has a statistically analyzable pattern. Golightly & Wilkinson apply MCMC methodology to infer parameters for stochastic biochemical network models, which is another way MCMC can be used in systems biology (Golightly & Wilkinson, 2011).

The theory of stochastic chemical kinetics allows for the development of Markov process models for network dynamics. Similar to other biological models, these models contain rate parameters that must be estimated from imperfect time course data. Golightly & Wilkinson show how MCMC algorithms can be applied to this class of models and do not suffer from scalability problems in the same fashion as other approaches. SDE models can be exploited in order to adapt to a basic proposed particle MCMC (PMCMC) approach (Golighty & Wilkinson, 2011). PMCMC is a combination of MCMC and sequential Monte Carlo methods– simulation based methods that compute posterior distributions (Andrieu et al., 2010).

This yields algorithms that are computationally efficient even in low or no measurement error scenarios where a likelihood-free approach tends to break down. Using a stoichiometry matrix that encodes important structural

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Figure 2 (Overview of observed exploration qualities, 2017: Result Figure from Ballnus et al. paper. Overview of exploration qualities (EQs). A depicts distributions of group sizes based on chain similarities.

B Quality by benchmark problem (in rows: M1 is mRNA transfection, M2 is Bistable switch, M3 is saturated growth, M4 is biochemical system with hopf bifurcation, M5 is Van Der Pol oscillation, and M6 is the Lorenz attractorâ&#x20AC;&#x201D;a chaotic system) and algorithm in columns (Ballnus et al., 2017). http://creativecommons.org/ licenses/by/4.0/

information about reaction networks while under the standard assumption of mass-action stochastic kinetics, they create a system that is a Markov jump process for an infinitesimal time increment. The difficulty using standard MCMC for inference in realistic data-poor scenarios is in the development of algorithms to explore huge state space with a complex likelihood structure. Methods such as likelihood-free MCMC and approximate Bayesian computation can be used to tackle these Bayesian inference problems. Furthermore, one can apply algorithms to make MCMC work for these difficult situations (Golightly & Wilkinson, 2011).

MCMC Algorithms MCMC methods are becoming increasingly popular due to their ability to rigorously analyze parameters and predict uncertainties. However, these methods can pose certain difficulties, as one must select and fine-tune the correct algorithm for the model. There are many different MCMC algorithms that can be used with models, but due to this broad spectrum of algorithms, it can be difficult to determine

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what works best. The algorithms include single-chain and multi-chain methods (Ballnus et al., 2017). Single-chain MCMC represents the process where there is a single initial guess and a single chain of samples generated from that guess. Multi-chain methods start with a set of many initial guesses and generate a chain of samples from each of these guesses (van Ravenzwaaij et al., 2018). These algorithms are necessary for using MCMC as the posterior Bayesian parameter estimation, but algorithms must be used to assess the information from the posterior (Ballnus et al., 2017).

Some of the single chain algorithms that are used in biology and other fields are Metropolis-Hastings (MH) (Hastings, 1970), Adaptive Metropolis (AM) (Haario et al., 2001), Delayed Rejection Adaptive Metropolis (DRAM) (Haario et al., 2006), and Metropolis-adjusted Langevin Algorithm (MALA) (Nemeth et al., 2016). MH, one of the more frequently used algorithms, samples from the posterior via a weighted random walk. Parameter candidates are drawn from proposal distribution and accepted or rejected based on the ratio of

"Some of the single chain algorithms that are used in biology and other fields are Metropolis-Hastings (MH), Adaptive Metropolis (AM), Delayed Rejection Adaptive Metropolis (DRAM), and Metropolis-adjusted Langevin Algorithm (MALA)."

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Figure 3 (Heatmap for the fraction of true parameters lying into the 95% Bayesian credible interval of MCMC samples, 2019): True parameter heatmap results from Valderrama-Bahamóndez & Fröhlich paper. Depicts the number of accurate parameters found within the Bayesian 95% confidence interval for each method of testing on biological model simulations (ValderramaBahamóndez & Fröhlich, 2019). creativecommons.org/licenses/ by/4.0/.

"While the algorithms for MCMC are numerous, the difficulty arises in applying and choosing the algorithms. In systems biology, the multi-chain algorithms generally perform better than the single chain algorithms."

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posterior at parameter candidate and current design parameters (Hastings, 1970). AM is an extension of MH, where the distribution is updated based on already available samples and improves sampling efficiency by aligning proposals with posterior distribution (Haario et al., 2001). DRAM is an extension of MH. When a candidate parameter is rejected, the algorithm finds a new point using information about the rejected point; this is repeated until the rejected points are accepted or the algorithm ends at a specific threshold (for example, too many tries) (Haario et al., 2006). MALA makes use of the gradient (partial derivatives at a specific point) of the posterior distribution, and the current point located in parameter space (Nemeth et al., 2016 & Ballnus et al., 2017).

While single chain algorithms are plentiful and useful in some cases, multi-chain algorithms can be more effective. Single chain algorithms are unlikely to make a transition between different posterior modes if they are separated by a low probability density area. A multi-chain method known as parallel tempering (PT has been developed to address this problem. It samples from multiple tempered versions of the posterior at the same time so that the transitions are more likely. There is also a method known as parallel hierarchical sampling (PHS). Similar to PT, this method employs several chains sampled from the posterior. It starts by sampling auxiliary chains at different points in parameter space and swaps the main chain with a random chain on each repetition. All the chains are sampled from the same distribution and the main and auxiliary swap is always accepted (Ballnus et al., 2017).

MCMC Algorithms Applied in Systems Biology While the algorithms for MCMC are numerous, the difficulty arises in applying and choosing the algorithms. In systems biology, the multichain algorithms generally perform better than the single chain algorithms (Ballnus et al., 2017; Golightly & Wilkinson, 2011; ValderramaBahamóndez & Fröhlich, 2019). However, this is not to say that single chain algorithms do not work for biological systems. Link and colleagues used Gibbs sampling in their study, which is an implementation of the MH algorithm (2002).

They found evidence showing that latent factors governing survival rates and breeding rates are positively correlated: birds that are more likely to survive are more likely to breed, given that they survive. The differences in kittiwakes’ survival and breeding probabilities were substantial, supporting the hypothesis of individual heterogeneity in vital rates (the speed at which vital statistics like age or sex change in a population). They also found patterns of age-related variation in breeding and survival rates at an individual level that differed from those observed at a population level. Using BUGS (Bayesian Inference using Gibbs Sampling) software, they were able to understand some of the processes that underlie the population dynamics. This topic is of fundamental interest to most conservation programs, and it is also important for designing management plans. The influence of individual variation on population dynamics is strongly dependent on the distribution of the parameter in the population, so describing the form of variation among individuals is critical to understanding the consequences of individual heterogeneity on the dynamics of the

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population. The development of approaches of MCMC to fitting complex hierarchical models, permitting estimation of parameter distributions in populations, is an extremely promising advance in biology. It could provide means of addressing population consequences of individual variation in life-history traits and demographic parameters using empirical data (Link et al., 2002).

Despite this application of single chain methodology, Golightly & Wilkinson, Ballnus et al., and Valderrama-Bahamóndez & Fröhlich’s studies all revealed the positive effects of using multi-chain methods and appropriate adaptation schemes in many biological systems. Ballnus and colleagues focused on ODE models for mechanistic descriptions of biological processes (2017). They studied some benchmark problems including mRNA transfection, bistable switch (gene regulation), saturated growth (population dynamics), Hopf bifurcation (biochemical system), a chaotic oscillator, and the Lorenz attractor (hydrodynamic process). In the instance of mRNA transfection, the posterior estimation problem is bimodal: exchange of the degradation rates of mRNA and protein results in the same dynamics. For mRNA transfection, PT performed the best; however, PHS, the other multi-chain method described, did well too.

PT was preferred due to its ability to perform independent of the initialization scheme.

However, when PHS was initialized with multistart optimization, the results were equally robust. They conclude that multi-chain methods clearly outperform single-chain methods, even for unimodal posterior distributions. Overall, PHS with optimization-based initialization was the top performer for uni-modal posterior landscapes, while PT performed best when regarding all posteriors (as demonstrated in Figure 2) (Ballnus et al., 2017).

These results (shown in Figure 2) show the importance of multi-chain methods and appropriate adaptation schemes, and also reveal the necessity for multiple independent runs of sampling methods from different points in parameter space, as most algorithms provide a representative sample in only a fraction of the runs. It should be noted that all MCMC algorithms exhibit some problems in sample efficiency, but in general, they yield positive results and represent an effective method to analyze complex biological models (Ballnus et al., 2017).

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Designing MCMC samplers for highdimensional or multi-modal parameter distributions is difficult. Luckily, many algorithms already exist and have been tested for some systems in biology. ValderramaBahamóndez & Fröhlich tested five MCMC models and found that the parallel adaptive method produces the best parameter estimates and the most effective optimization methods. The aim for MCMC was to have full Bayesian inference that would obtain estimates that appropriately considered the uncertainty within a framework while circumventing the non-linear optimization, thus addressing both the practical and structural nonidentifiability of parameters in ODE systems.

This is important because in high-dimensional systems the integral is computationally intractable (Valderrama-Bahamóndez & Fröhlich, 2019). Essentially, they compared different MCMC approaches for estimating kinetic rate parameters of ODE systems in biological models. They looked at the positive and negative feedback loops of the MAPK phosphorylation cascade, which contained 22 parameters with 8 species (variables). They also analyzed the ERK phosphorylation in CFU-E, which had 26 parameters and 33 species; Smad signaling with 10 species and 13 parameters; the role of receptor endocytosis in the feedback mechanism involved in type 2 diabetes insulin resistance with 18 parameters and 9 species; and B-Cell Lymphoma induced by IL13 with 22 parameters and 14 species. First, they simulated the data and then compared the MCMC methods and performances. The simulations were completed by integrating the ODE systems at 17 different time points while also finding a steady-state of each system at the initial condition. They used large-scale bound-constrained optimization to estimate the steady state, as well as an ODE solver. They also included noise levels in these simulation models (Valderrama-Bahamóndez & Fröhlich, 2019).

Valderrama-Bahamóndez & Fröhlich were investigating whether parallel MCMC methods offered an advantage for kinetic rate parameter estimation due to the theoretical ability to explore different modes of parameter distributions in parallel methodology. It follows the idea that log-likelihood–a method used to derive the parameter’s maximum likelihood estimator–is “energy” and is divided by the “temperature” T. If T becomes large, MCMC moves become more probable, but if T becomes smaller, the sampler is more

"The development of approaches of MCMC to fitting complex hierarchical models, permitting estimation of parameter distributions in populations, is an extremely promising advance in biology.

It could provide means of addressing population consequences of individual variation in life-history traits and demographic parameters using empirical data."

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likely to reject moves and just explore the local area of the parameter distribution. They performed over one million iterations for each algorithm of MCMC sampling, and applied tests to assess convergence. They found no systematic dependency between noise level and convergence failures. Unfortunately, convergence successes are difficult to verify, but one can easily test to see if convergence has failed. Their results indicated that parallel tempering models completed the most effective sampling for some models and parallel adaptive for others (see figure 3). Both these methods are multi-chain methods. Parallel adaptive MCMC was highly robust against noise, and the fraction of true parameters lying within the 95% Bayesian credible interval was not effective.

On experimental data, parallel adaptive MCMC resulted in a high fraction of the true parameters.

Parallel tempering methods showed some dependency on noise level and had a smaller fraction of the true parameters covered by the interval than parallel adaptive. The parallel adaptive approach would likely be beneficial for exploration of different modes of posterior distributions. They also suggest a manner for single chain methods to be more effective: if the priors are informative, then a high fraction of true model parameters is covered by the 95% interval (Valderrama-Bahamóndez & Fröhlich, 2019).

Conclusion "ODE systems are imperative to describing biological and medical systems. Kinetic rate parameters must be estimated from the data, and a potent method for finding these parameters is MCMC."

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The goal of Bayesian statistics is to estimate the posterior distribution, yet this is often intractable due to a high-dimensional integral in the denominator. With Monte Carlo methods, the samples have to be independently drawn from the posterior, which is impractical should the posterior distribution be unknown; it would be impossible to integrate the marginal likelihood (denominator). An easy solution to this problem is MCMC. MCMC allows for a sample draw from a proposed distribution so that each draw depends only on the state of the previous one. These samples then form the Markov chain. Using all samples is not necessary; instead, an acceptance criterion is created for each draw based on a comparison of successive states with respect to a target distribution.

This ensures that the distribution is in fact the distribution of interest. Furthermore, the target distribution simply has to be proportional to the posterior distribution, making it a constant.

It also means that the potentially intractable marginal likelihood does not need evaluation.

The target distribution is therefore characterized by posterior likelihood × prior. After some

amount of time, the Markov chain of accepted draws converges to the stationary distribution, and these samples can then be used as correlated draws for the posterior distribution.

Then, functions of the posterior distribution can be found using simple Markov chain methodology. Thus, MCMC helps to circumvent some of the problems that can arise when trying to estimate a posterior distribution, making it an extremely useful tool for analyzing ODE based models (Chan & McCarthy, 2016).

ODE systems are imperative to describing biological and medical systems. Kinetic rate parameters must be estimated from the data, and a potent method for finding these parameters is MCMC. Through extensive MCMC algorithm testing, it has been generally concluded that multiple chain algorithms are the most effective, particularly parallel adaptive and parallel tempering methods (Ballnus et al., Golightly & Wilkinson, and ValderramaBahamóndez & Fröhlich). While MCMC requires computer knowledge and the ability to run code, it is worthwhile due to its robustness–it functions for many different system types and has incredible ability to estimate parameters.

Furthermore, there are many freely available programs that can run an MCMC analysis, allowing researchers to minorly tweak these in order to use them to estimate parameters for an abundance of biological systems.

Computational systems biology aims to integrate biology and computational methods in order to understand biological phenomena.

Usually, this requires the assistance of global optimization. While there are a couple ways to accomplish this optimization including least squares methods or genetic algorithms, an effective and consistent way for optimization is MCMC methodology. This can be applied for many types of statistical inferences like parameter estimation, and it is quite suitable for the framework of Bayesian inference. MCMC can be applied in both continuous and noncontinuous objective functions, as well as when stochastic simulations are involved (Reali et al., 2017). This versatility is another benefit of using MCMC in biological systems that are immensely varied and often quite complicated.

MCMC is an effective technique for analyzing biological systems and should be used in more biological applications due to its many abilities and robustness in parameter estimation for a wide array of systems.

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References Andrieu, C., Doucet, A., & Holenstein, R. (2010). Particle Markov chain Monte Carlo methods: Particle Markov Chain Monte Carlo Methods. Journal of the Royal Statistical Society: Series B (Statistical Methodology), 72(3), 269–342. https://doi. org/10.1111/j.1467-9868.2009.00736.x Ballnus, B., Hug, S., Hatz, K., Görlitz, L., Hasenauer, J., & Theis, F. J. (2017). Comprehensive benchmarking of Markov chain Monte Carlo methods for dynamical systems. BMC Systems Biology, 11(1), 63. https://doi.org/10.1186/s12918-017-0433-1 Carstens, S. (2020). Introduction to Markov chain Monte Carlo (MCMC) Sampling, Part 2: Gibbs Sampling. https://www. tweag.io/blog/2020-01-09-mcmc-intro2/

in Applied Mathematics and Statistics, 3. https://doi. org/10.3389/fams.2017.00006 Freepik. (2019). Premium Vector | Set of energy chaotic waves.

Retrieved October 24, 2020, from https://www.freepik.com/ premium-vector/set-energy-chaotic-waves_6009479.htm Valderrama-Bahamóndez, G. I., & Fröhlich, H. (2019). MCMC Techniques for Parameter Estimation of ODE Based Models in Systems Biology. Frontiers in Applied Mathematics and Statistics, 5. https://doi.org/10.3389/fams.2019.00055 van Ravenzwaaij, D., Cassey, P., & Brown, S. D. (2018). A simple introduction to Markov Chain Monte–Carlo sampling.

Psychonomic Bulletin & Review, 25(1), 143–154. https://doi. org/10.3758/s13423-016-1015-8

Chan, C., & McCarthy, J. (2016). Metropolis and Gibbs Sampling—Computational Statistics in Python. http://people. duke.edu/~ccc14/sta-663-2016/16A_MCMC.html Finley, S. (2020). MCMC Code and Graphs. Photo taken by author on computer, code modified from code provided by Carstens (2020) and Chan & McCarthy (2016).

Gábor, A., & Banga, J. R. (2015). Robust and efficient parameter estimation in dynamic models of biological systems. BMC Systems Biology, 9(1), 74. https://doi. org/10.1186/s12918-015-0219-2 Golightly, A., & Wilkinson, D. J. (2011). Bayesian parameter inference for stochastic biochemical network models using particle Markov chain Monte Carlo. Interface Focus, 1(6), 807–820. https://doi.org/10.1098/rsfs.2011.0047 Haario, H., Saksman, E., & Tamminen, J. (2001). An Adaptive Metropolis Algorithm. Bernoulli, 7(2), 223-242. doi:10.2307/3318737 Haario, H., Laine, M., Mira, A., & Saksman, E. (2006). DRAM: Efficient adaptive MCMC. Statistics and Computing, 16(4), 339–354. https://doi.org/10.1007/s11222-006-9438-0 Hastings, W. K. (1970). Monte Carlo sampling methods using Markov chains and their applications. Biometrika, 57(1), 97–109. https://doi.org/10.1093/biomet/57.1.97 Hey, J., & Nielsen, R. (2007). Integration within the Felsenstein equation for improved Markov chain Monte Carlo methods in population genetics. Proceedings of the National Academy of Sciences, 104(8), 2785–2790. https://doi.org/10.1073/ pnas.0611164104 Kuhner, M. K., Yamato, J., & Felsenstein, J. (1995). Estimating effective population size and mutation rate from sequence data using Metropolis-Hastings sampling. Genetics, 140(4), 1421–1430.

Link, W. A., Cam, E., Nichols, J. D., & Cooch, E. G. (2002).

Of Bugs and Birds: Markov Chain Monte Carlo for Hierarchical Modeling in Wildlife Research. The Journal of Wildlife Management, 66(2), 277–291. JSTOR. https://doi. org/10.2307/3803160 Nemeth, C., Sherlock, C., & Fearnhead, P. (2016). Particle Metropolis-adjusted Langevin algorithms. ArXiv:1412.7299 [Stat]. http://arxiv.org/abs/1412.7299 Reali, F., Priami, C., & Marchetti, L. (2017). Optimization Algorithms for Computational Systems Biology. Frontiers

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The Effect of Vegetation on Mosquito Abundance and Spread of Mosquito-Borne Illnesses

BY VAANI GUPTA â&#x20AC;&#x2122;24 Cover Image: A mosquito biting a person and drinking blood.

Source: Wikimedia Commons

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Abstract Each year, approximately 700 million people contract mosquito-borne illnesses, resulting in more than a million deaths (World Mosquito Program, 2019). These mosquitoborne diseases are highly infectious and can rapidly spread within a population. Hence, this investigation explores the conditions that spur mosquito breeding and thus increase the risk of contracting mosquito-borne infectious diseases. This study investigates this by measuring mosquito abundance in a local park in Houston, Texas, the fifth worst mosquito city in the country, using oviposition traps.

This investigation found that oviposition traps placed near ground flowers had the highest number of mosquito larvae, while those placed in barren areas had the lowest. It also described the impact of weather changes, such as rainfall, on the number of mosquito larvae found.

Studying the relationship between vegetation and mosquitoes can lead to an increased

understanding of how to reduce the mosquito population in dense, urban areas.

Introduction Mosquitoes are winged insects that originate from the family Culicidae. They have a life cycle that consists of four stages: egg, larva, pupa, and adult. First, gravid female mosquitoes lay their eggs in a source of stagnant water. The eggs are laid one at a time, or they form rafts by attaching to each other. After about 48 hours, the eggs hatch into larvae, as shown in Figure 1 (Wikimedia Commons), which live in the water and consume organic matter and microbes.

The larvae shed their skin four times, each time growing into a larger one. By the fourth shedding, which occurs after seven to ten days, the larvae turn into pupae. While the pupae are in a resting and non-feeding stage, they are mobile and responsive to environmental changes, such as light. Finally, after another two DARTMOUTH UNDERGRADUATE JOURNAL OF SCIENCE

to three days, an adult mosquito emerges by breaking through the pupal skin (The American Mosquito Control Association).

In this breeding process, there are many factors that attract mosquitoes to a specific breeding site. However, one of the most important factors is the presence and type of vegetation.

Vegetation is significant, as it provides a resting habitat for mosquitoes (Chowell et al., 2019). Also, vegetation is a source of nutrients for mosquitoes; mosquitoes need sugar in order to survive and they are able to obtain it by consuming plant juices, sap, and nectar.

According to a study conducted by Weigdong Gu et al., which investigated mosquitoes from the genus Aedes and Culex, the number of female mosquitoes was four times higher in a sugar-rich site than in a sugar-poor one. This is because sugar feeding was increased in the sugar-rich site, so a larger population of female mosquitoes were able to survive long enough to reproduce (Gu et al., 2011). In addition, in order for female mosquitoes to lay eggs, they use their proboscis, an elongated sucking mouthpiece, to consume sugars and proteins.

These nutrients can be obtained by sucking the blood of animals, such as small mammals or birds. Areas surrounded with vegetation tend to attract a wide variety of animals that could serve as hosts for these mosquitoes (Capinera, 2008).

The purpose of this investigation is to explore the correlation between the type of vegetation and mosquito abundance. The number of mosquito larvae found in mosquito traps positioned in proximity to four different vegetation sites â&#x20AC;&#x201C; trees, shrubs, ground flowers, and barren (no vegetation) â&#x20AC;&#x201C; was measured.

For the purposes of this study, similar standards that were listed in a study conducted by Allison Gardner et al. were used to distinguish between trees and shrubs; this study focused

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on shrubs that were shorter than 1 meter, and Figure 1: After about 2 days, it did establish a positive correlation between mosquito eggs hatch into larvae the presence of mosquitoes and vegetation Source: Wikimedia Commons (Gardner et al., 2013). Similarly, for this research, shrubs are identified as those with a height of less than one meter and trees are identified as anything taller than that. Furthermore, to conduct this investigation, oviposition mosquito traps were constructed, as they are particularly effective in attracting gravid female mosquitoes; these traps were checked every four days. This research identified the type of vegetation conditions that promote breeding of mosquitoes endemic to the Houston area, such as Aedes aegypti, Aedes albopictus, Anopheles quadrimaculatus, and Culex pipiens, all known transmitters of diseases like malaria and West Nile Virus (Nava & Debboun, 2016).

In this experiment, it was predicted that there will be a higher mosquito abundance in sites that contain trees, shrubs, or flowers in comparison to barren sites. According to an Ohio State University study conducted

by Dr. Woodbridge A. Foster, this is because sites with vegetation provide more resources and nutrients to nourish female mosquitoes, increasing their chances of survival and likelihood of reproducing. Also, it is likely that vegetation will be home to small mammals or birds that could be potential hosts for female mosquitoes, providing a blood meal (Foster, 1995). However, this investigation also expected that the traps positioned near ground flowers will have the largest number of mosquito larvae, due to the presence of sugar-rich nectar in flowers. Flowers provide a steady supply of sucrose, glucose, and fructose, and given their smaller height (relative to trees), nectar in flowers is more accessible to mosquitoes, most of which prefer lower elevations.

"In this experiment, it was predicted that there will be a higher mosquito abundance in sites that contain trees, shrubs, or flowers in comparison to barren sites."

Figure 2: Positions of Oviposition Traps in Houston Park. All traps are placed within a 0.5 km radius of each other.

Source: Image modified from Radack

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Figure 3: Positions of oviposition traps near each vegetation type.

All traps are placed no more than 5 to 10 cm away from the vegetation source.

Methods

Source: Original image by Author

For this investigation, oviposition mosquito traps were utilized, as they best attract gravid female mosquitoes. Hence, to construct oviposition traps, black stadium cups, black socks, and 18-gauge wire were used. First, to build a single trap, two holes were drilled in a 22 oz. black stadium cup. One hole should be placed close to the top of the cup, and it must be wide enough to fit an 18-gauge wire. The second hole should be 0.25” wide, and it should be positioned at about 80% of the way up the cup. There should be two sets of these holes on opposing sides of the stadium cup. Then, silicone glue was used to paste the toe of the black crew sock to the bottom of the stadium cup. The color black is specifically vital for the socks used in these traps, since this color absorbs more heat, creating favorable hot and humid conditions that attract mosquitoes. Next, using the top of the stadium cup as a template, circles of metal screening (specifically a 2 pack TORIS stainless steel woven wire mesh of 11.8” x 8.2”) were cut. 18-gauge wire was also cut into a 1.5 ft long piece.

"For this investigation, oviposition mosquito traps were utilized, as they best attract gravid female mosquitoes."

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Construction of the Oviposition Mosquito Traps

Then, the sock was stretched to cover the mouth and bottom of the stadium cup; any excess sock at the bottom was cut, as the sock needs to be taut around the cup. Next, the circular metal screen was placed into the top of the cup, specifically positioned where the screen is right above the 0.25-inch hole. This was done by pressing the screen at the center until half of the screen was at the appropriate height, and then, rotating the cup and pressing down the other half. This will allow the uneven edges of the screen to hold onto the stadium cup. The purpose of this screen is to allow the mosquito larvae to live in the water in the trap but prevent them from escaping once they have become adults. Then, a piece of 18-gauge wire was inserted through the two small holes near the top of the cup and twisted to keep it in place. With this wire, the trap can be carried or hung anywhere. Finally, the oviposition trap was dipped into stagnant and rank water (which mosquitoes favor) from a local swamp. The 0.25” hole should drain any excess water. By dipping the trap, the sock will become moist, which will attract mosquitoes. However, a visual check of the water is necessary to ensure that there is no contamination, specifically no presence of mosquito eggs or larvae. Furthermore, four alfalfa pellets, each three grams, should be

added into the water to use as bait to increase the mosquitoes’ attraction to the trap, as well as to keep the water rank. For this study, a total of twelve oviposition traps were constructed.

Positioning of the Oviposition Traps In this study, the oviposition traps were positioned in proximity to four different vegetation sites - trees (Chamaerops humilis), shrubs (Elaeagnus pungens), ground flowers (Rosa pendulina), and barren (no vegetation).

Three oviposition mosquito traps are placed for each vegetation type. Figure 2 (Image modified from Radack) illustrates the positions of the mosquito traps in the park. As seen in this image, all oviposition traps are placed within a 0.5 km radius of each other in the local park. Because the general location of the traps is the same, any weather changes, such as temperature, will be experienced by all traps. Furthermore, each trap is placed under or behind each vegetation type and is no more than 5-10 cm away from each vegetation type, as shown in Figure 3.

This positioning would result in the traps being placed in locations with little to no sunlight, which creates a shady environment that attracts mosquitoes. To maintain consistency and ensure that each trap receives the same amount of sunlight, the negative control traps (no vegetation), in particular, will be placed outside, near the restrooms, so they have a covering that provides shade and are located away from the surrounding vegetation.

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Table 1: Mosquito Larvae for Each Vegetation State Table 1 illustrates the number of mosquito larvae collected in each trap for each vegetation type over a period of 20 days.

The uncertainty of Âą1 mosquito larvae is due to the chance of double counting a mosquito larva while collecting results.

Recording Mosquito Abundance

The time at which the number of mosquito larvae in each trap was recorded was constant.

The traps were checked every four days at 5:30 PM CST. This consistent time ensured that no one trap had more time than others for mosquitoes to lay eggs. The number of larvae was recorded from the water samples in the oviposition traps using a petri dish and an LED clip-on microscope. To check the mosquito trap for larvae, first, a sample of water from the trap must be poured onto the petri dish, which was then covered with a clear cover.

Next, by attaching the microscope to a phone, the microscope could be placed flat on the coverâ&#x20AC;&#x2122;s surface. This allows the microscope to

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be moved across the cover and allows for the water sample to be searched for mosquito larvae. However, to avoid double counting the larvae, the microscope should be slowly moved across the petri dish from left to right. After each observation, the petri dish was cleaned.

In this study, all of the water in each trap was sampled. After draining the water, the trap was refilled for the next trial using the same water source.

"This investigation does not disturb the surrounding ecosystem, as the mosquitoes are not harmed while performing the experiment."

This investigation does not disturb the surrounding ecosystem, as the mosquitoes are not harmed while performing the experiment.

The mosquito eggs simply hatch and grow into larvae within a confined space for a period of a few days before they are released into

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Figure 4: Mosquito Abundance for Each Vegetation State

the environment. The traps are placed next to vegetation or in an area with no vegetation and do not damage the surrounding area.

Results Qualitative Observations

"As seen in Figure 5, over a period of 20 days, there was an overall initial increase in the number of mosquito larvae, but around Day 12, there was a decrease in mosquito larvae among all vegetation sites."

The weather was inconsistent during the period of 20 days. For the first four days, the weather was warm, with an average day temperature of 25 °C (range is 22 to 27 °C). Then, during the next four days, the weather was still warm, with the average temperature dropping only by 2°C to an average of 23 °C (21 to 27 °C). However, there was a sudden change in the weather during the third set of four days, when the skies became cloudy and it rained over the next two to three days. In this period, the average temperature dropped to an average of 9 °C (6 to 12 °C), and it rained a total of 0.25”. However, after the fourteenth day, while the skies still remained slightly cloudy, the heavy precipitation stopped, and the temperature increased to an average of 19 °C (17 to 24 °C).

Finally, for the last four days, the skies were fully cleared, and temperature increased even further to an average of 26 °C (24 to 27 °C). During the 20 days, there was no significant change in the humidity of the environment, which averaged 76%.

Figure 4 depicts the mean number of mosquito larvae for each vegetation site; the error bars are representative of the standard deviation. As seen in Figure 4, the highest number of mosquito larvae was found near flowers, with an average of 26.6 mosquito larvae. Following flowers, shrubs had the second highest number of larvae. The lowest number was found in barren areas where

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no vegetation was present: the mean number of larvae was only 0.87.

Because this investigation focuses on mosquito larvae, it is important to note the distinguishing characteristics between mosquito larvae and pupae. Mosquito larvae have their heads pointed downwards and a breathing tube known as a siphon at the water’s surface.

However, the pupae simply float on the water’s surface and have two breathing tubes known as trumpets.

As seen in Figure 5, over a period of 20 days, there was an overall initial increase in the number of mosquito larvae, but around Day 12, there was a decrease in mosquito larvae among all vegetation sites. This decrease could be due to the changes in weather pattern, as the precipitation during this time period could have washed out and severely flooded the oviposition traps, destroying the potential larval habitat inside. However, at the same time, the precipitation nourished different vegetation sources, as well as left behind more sources of stagnant water around each site, increasing the likelihood of a mosquito coming near the traps.

This could account for the increase in mosquito larvae for all of the sites following Day 12.

Discussion It can be concluded that the vegetation type influences the number of mosquito larvae present near that site. The t-tests show that the null hypothesis is rejected, suggesting that there is a significant difference between the two mean data sets for each pair of vegetation sites – there is a correlation between the vegetation type and mosquito abundance. Figure 4

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Figure 5: Mosquito Abundance Over the Course of 20 Days

supports this, illustrating the lack of overlap between the error bars of the vegetation sites. It also shows that ground flowers had the largest number of mosquito larvae, followed by shrubs, trees, and barren areas. These results can be attributed to the importance of vegetation in mosquito growth and development. After all, vegetation is a nutrient and sugar source for mosquitoes. Flowers and shrubs have a high sugar content and are located close to the ground, making this rich source accessible to many mosquitoes. This contributes to the high number of larvae found at these sites.

Furthermore, Figure 5 charted the change in mosquito abundance for each vegetation site over a period of time. This emphasizes the impact of weather conditions on mosquito abundance. For instance, there was a decline in the number of larvae at all vegetation sites around Day 12 during the short period of heavy precipitation. However, after the rain, the number of mosquito larvae gradually increased.

The initial decline could be a result of the rain washing out larval habitats, but the following increase in larvae was a product of nourished vegetation and an increased number of stagnant water sources at each vegetation site.

In addition, the temperature decline during the period of precipitation was not conducive to large numbers of mosquito larvae, as mosquitoes prefer a warm environment. Hence, this also contributed to the decline in mosquito larvae during that period.

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In addition, aside from the method used in this investigation, there are other ways to collect mosquito larvae data. For example, in the dipping method, a dipper is used to collect mosquito larvae in different water sources.

The Culex, Aedes, and Anopheles mosquito larvae are found near the surface of the water and in proximity to vegetation. Hence, when dipping, the person must approach the water source quietly and carefully to prevent disturbance of the larvae habitat and cause the larvae to dive beneath the water surface.

Then, to do a shallow skim, the dipper must be angled at 45° and positioned one inch below the water’s surface; the dipper must move gently across the water to collect the larvae.

A complete submersion dipping method could also be used, where the dipper is quickly plunged downward and gently brought up to collect the mosquito larvae that are diving downwards (O’Malley, 1995). Compared to the oviposition traps used in this study, there are strengths and weaknesses to each method.

One strength of the oviposition traps is that they allowed for a clear management of control variables and for the production of favorable conditions, such as a shady environment and use of rank and stagnant water. These favorable conditions allow for the isolation of vegetation type. However, compared to the dipping method, a weakness of the oviposition traps is that these traps aren’t specified to a certain mosquito species. There are multiple forms of the dipping method, such as the shallow skim, partial submersion, and complete submersion,

"Figure 5 charted the change in mosquito abundance for each vegetation site over a period of time.

This emphasizes the impact of weather conditions on mosquito abundance.

For instance, there was a decline in the number of larvae at all vegetation sites around Day 12 during the short period of heavy precipitation."

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that specifically target different mosquito larvae species based on where in the water they reside.

Hence, the generalized nature of the oviposition traps could result in fewer mosquitoes being attracted to the site compared to the dipping method.

"Given the significance of this experiment in exploring the urban conditions that result in greater mosquito abundance, further research is needed to achieve greater understanding of mosquito abundance, the overall weather, and vegetative conditions that promote mosquito breeding, as well as how to reduce risk of contracting mosquito-borne diseases within crowded, urban populations."

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Beyond the collection method, there were other strengths and weaknesses in this study.

One major strength was that multiple traps were used per trial for each vegetation site.

This created a larger data set for each type of vegetation, increasing the data’s accuracy and reliability. However, a primary weakness is that the experiment was conducted only in a local park as opposed to multiple parks or throughout the city. This limits the scope of the investigation to a comparably more confined space. Another weakness was that the conditions at each vegetation site were slightly altered after the short period of precipitation.

Each site reacted in a slightly different manner to the influx of rain, specifically based on how much water each vegetation type requires and how many stagnant water sources were formed.

This slightly alters the extent of a mosquito’s attraction to the trap and vegetation site. Also, a potential limitation of this investigation was the use of multiple t-tests. Performing multiple t-tests could increase the chance of finding a false significant difference. However, because these groups were very distinct and each individual test produced t-values that were well above the critical value, this was not a primary concern and the significant difference found in the tests is likely valid.

There were also some random errors of uncertainty. One error of uncertainty was the way the traps were built, specifically the size and position of the holes created in the stadium cup. Because the holes were created by humans, there is slight uncertainty in the measurement of the radius of the hole, as well as the position of the hole on the stadium cup, among the multiple mosquito traps. This would lead to miniscule differences in each mosquito trap, specifically influencing the water level in each trap by one to two inches, especially after it was flooded with rainwater around Day 12. The water depth for each trap could influence the mosquitoes’ attraction to the traps, as some larvae prefer to stay on the surface or slightly below. Another error of uncertainty was the way the mosquito traps were positioned in the local park. While the traps were supposed to remain in a shady region, depending on the time of day, a little bit of sunlight would still come through at times.

Because mosquitoes prefer shady conditions, this uncertainty could slightly influence the mosquitoes’ attraction to the trap.

As a result, in the future, some improvements could be made. The first major improvement would be to increase the sample size. This can be done by increasing the number of traps positioned in the local park. However, it can also be done by conducting the experiment in a series of multiple parks located throughout the city. Both ways would expand the data set available and provide a more holistic view that could be applicable to a wider base.

Furthermore, instead of using alfalfa pellets as bait, fish food could also be utilized, and the small and light flakes could allow for more bait to be placed in each trap, increasing the mosquitoes’ attraction to the area. In addition, to reduce random errors, the measurements could be made multiple times and more trials could be conducted.

Conclusion Similar investigations to the present study have been conducted. David Roiz et al. found a positive correlation between the presence of mosquitoes and the normalized difference vegetation index (NDVI), which quantifies the amount of vegetation (Roiz et al., 2015).

Furthermore, researchers Louise Ivers and Edward Ryan found that following heavy precipitation and natural disaster events, there is an initial decrease in the mosquito population in the region due to high winds and flooding.

But, after the event, there is a larger number of water-holding containers, increasing the number of potential mosquito-breeding water sources and resulting in an increase in the population (Ivers & Ryan, 2006). Hence, these studies support the results of this investigation.

Given the significance of this experiment in exploring the urban conditions that result in greater mosquito abundance, further research is needed to achieve greater understanding of mosquito abundance, the overall weather, and vegetative conditions that promote mosquito breeding, as well as how to reduce risk of contracting mosquito-borne diseases within crowded, urban populations. Therefore, to further expand this exploration, an investigation that studies whether specific mosquito species are attracted to certain plant species could be conducted. Furthermore, research could explore if certain flower species can repel mosquitoes. This could be useful in identifying DARTMOUTH UNDERGRADUATE JOURNAL OF SCIENCE

areas of high mosquito abundance. In addition, based on the qualitative observations, an investigation of the effect of seasonal changes in temperature and precipitation on mosquito abundance can be carried out by recording mosquito data throughout the entire year. Also, the impact of the type of water source (artificial or natural) on mosquito abundance could be studied; to add to this topic, the time it takes for a mosquito breeding site to form, as well as how long it lasts, could be explored and defined.

These studies would increase understanding of the various factors that influence mosquito breeding and provide insight into how to prevent the spread of mosquito-borne illnesses.

Sample Calculations Calculation of Average Number of Mosquito Larvae Calculating the mean number of larvae found near flowers:

= 26.6 Mosquito Larvae

Standard Deviation of the Mean Number of Mosquito Larvae Formula: Using the data from the vegetation site, flowers: x = 26.6 ; n = 15

σ =2.13 Mosquito Larvae This standard deviation calculation is utilized for the error bars in Figure 4 above.

Running a t-test Multiple t-tests were conducted to determine if there was a significant difference between two vegetation sites.

Null Hypothesis There is no association between the type of vegetation and mosquito abundance.

There is an association between the type of vegetation and mosquito abundance.

Additional Tables Table 2 illustrates the standard deviation and average mosquito larvae for each vegetation site.

For all of the t-tests shown in Table 3, the degrees of freedom is: 30-2=28. Based on this degree of freedom and the p-value, which is 0.05, the critical value is 1.70. For all t-tests, the calculated t-value is greater than the critical value, meaning that the null hypothesis can be rejected. Hence, the idea that there is a significant difference between the means of every pair of vegetation type is accepted, and this indicates that there is an association between the type of vegetation and the number of mosquito larvae found.

However, the uncertainty of the number of mosquito larvae was ±1. Hence, it is necessary to evaluate whether the results of the t-tests hold true even when this uncertainty is applied and the gap between the means is smaller.

Therefore, the following table provides the “extreme” means that could potentially occur within the experiment.

Table 4 illustrates the standard deviation and mean number of mosquito larvae for each vegetation site after considering the “extreme” means that could potentially occur in the experiment. Table 5 shows the t-values calculated for each t-test conducted after considering the ±1 uncertainty in the number of mosquito larvae collected (considering the “extreme” means).

Once again, for the t-values in Table 5, the degrees of freedom is 28 and the p-value is 0.05, meaning that the critical value is 1.70. All of the calculated t-values, even when extreme values for the mean are used, are greater than the critical value. This again demonstrates that the null hypothesis needs to be rejected and that even when the uncertainty is applied, there is still an association between vegetation type and mosquito abundance.

Sample Calculation for t Solving for t between the mean mosquito larvae found in flowers and in barren (no vegetation) areas:

Alternative Hypothesis

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Table 2: Mean Mosquito Larvae and Standard Deviation for Each Vegetation Site Degrees of Freedom: df = 30 - 2 = 28 If df = 28 and p = 0.05, then: critical value = 1.70

As a result, the null hypothesis is rejected.

Table 3: Calculated t-values for each t-test conducted

Table 4: Mean Mosquito Larvae and Standard Deviation for Each Vegetation Site

Table 5: Calculated t-values for each t-test conducted

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Retrieved December 11, 2019, from https://www.mosquito. org/page/lifecycle Capinera, J. L. (2008). Encyclopedia of entomology. Dordrecht, Netherlands: Springer.

Chowell, G., Mizumoto, K., Banda, J. M., Poccia, S., & Perrings, C. (2019). Assessing the Potential Impact of Vector-Borne Disease Transmission Following Heavy Rainfall Events: A Mathematical Framework. Philosophical Transactions of the Royal Society B: Biological Sciences, 374 (1775), 20180272. doi:10.1098/rstb.2018.0272 Foster, W. A. (1995). Mosquito Sugar Feeding and Reproductive Energetics. Annual Review of Entomology, 40(1), 443-474. doi:10.1146/annurev.en.40.010195.002303 Gardner, A. M., Anderson, T. K., Hamer, G. L., Johnson, D. E., Varela, K. E., Walker, E. D., & Ruiz, M. O. (2013). Terrestrial vegetation and aquatic chemistry influence larval mosquito abundance in catch basins, Chicago, USA. Parasites & Vectors, 6(1). doi:10.1186/1756-3305-6-9 Gu, W., MĂźller, G., Schlein, Y., Novak, R. J., & Beier, J. C. (2011).

Natural Plant Sugar Sources of Anopheles Mosquitoes Strongly Impact Malaria Transmission Potential. PLoS ONE, 6(1). doi:10.1371/journal.pone.0015996 Ivers, L. C., & Ryan, E. T. (2006). Infectious diseases of severe weather-related and flood-related natural disasters. Current Opinion in Infectious Diseases, 19(5), 408-414. doi:10.1097/01. qco.0000244044.85393.9e Nava, M. R., & Debboun, M. (2016). A taxonomic checklist of the mosquitoes of Harris County, Texas. Journal of Vector Ecology, 41(1), 190-194. doi:10.1111/jvec.12212 Olena, A. (2017, September 15). After Harvey, Mosquito Control Ramps Up. Retrieved October 21, 2020, from https:// www.the-scientist.com/daily-news/after-harvey-mosquitocontrol-ramps-up-30917 O'Malley, C. (1995). Seven Ways to a Successful Dipping Career. Retrieved December 11, 2019, from http://vectorbio. rutgers.edu/outreach/dipping.htm Radack, S. (n.d.). Bear Creek Pioneers Park. Retrieved December 15, 2019, from http://www.pct3.com/Parks/BearCreek-Pioneers-Park Roiz, D., Ruiz, S., Soriguer, R., & Figuerola, J. (2015). Landscape Effects on the Presence, Abundance and Diversity of Mosquitoes in Mediterranean Wetlands. Plos One, 10(6). doi:10.1371/journal.pone.0128112 World Mosquito Program. (2019). Mosquito-borne diseases. Retrieved October 29, 2020, from https://www. worldmosquitoprogram.org/en/learn/mosquito-bornediseases

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Effect of Gut Microbiome Composition on Mental Health and Neurodegenerative Diseases

BY VARUN LINGADAL â&#x20AC;&#x2122;23 Cover Image: A scanning electron microscope (SEM) image of E. coli, a bacteria that is found in the gut microbiome.

Source: Wikimedia Commons

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Gut Microbiota The relationship between the gut and the brain has been a heavily studied subject for years. These two distinct regions of the body have a huge influence on the health of each other, and while it makes sense that the brain would control the gut, recent research has begun to determine that gut microbiota play an important role in influencing the brain, particularly in the emotional and cognitive centers of the brain (Carabotti et. al, 2015).

Further research has gone on to show just how important this gut microbiome composition is to the mental health of individuals.

Scientists have found distinct differences in gut microbiome composition between neurotypical individuals and those with mental health disorders and neurodegenerative diseases, suggesting a potential link between gut microbiome composition and disease.

The earliest known gut microbiome-related therapies date back to ancient China, where oral administration of fresh, dry, or fermented stool was used to treat abdominal diseases. In 1853, Joseph Leidy, an American zoologist, published a book, A Flora and Fauna within Living Animals, which is considered to be the origin of microbiota research. Microbiota research soon began to shift to studying the relationship between a host and the microorganisms within the gut. German microbiologist Robert Koch published the famous four Koch postulates that established a causative relationship between microorganism and disease in 1890, and the study of microbiology, particularly in the early 20th century, shifted to investigating the relationship between host and disease (Pariente, 2019).

A major development in microbiota research occurred in 1917 when the E. Coli Nissile 1917 strain became the first gut microorganism to DARTMOUTH UNDERGRADUATE JOURNAL OF SCIENCE

Figure 1: Kochâ&#x20AC;&#x2122;s Postulates with a diagram corresponding with each postulate.

Source: Wikimedia Commons

be successfully isolated. Around the same time, discoveries during World War I suggested the existence of protective microorganisms that live in the gut. The field of microbiota analysis took off in the 1940s and 50s with the advent of methods to culture anaerobic organisms (Pariente, 2019). One such method, a rolltube approach, was developed by American scientist Robert Hungate. His method used rubber-stoppered tubes with boiled medium and a constant flow of anoxic gases to ensure an anerobic environment (Clark, 2019).

Experiments on germ-free mice showed that they lacked much of the normal physiology observed in laboratory mice, which helped scientists further understand the relationship between an animal and its internal microbiome (Pariente, 2019). The germ-free mice had similar lifespans to mice with normal guts; however, they exhibited slower, impaired growth as well as anatomical and physiological differences, such as an enlarged cecum (Brunello, 2019).

One study found that the transfer of a strain of Bacteroides into germ-free mice helped lead to a decrease in cecum size. More specifically, FALL 2020

while the cecum of conventional mice is only about 1.6% of their body weight, germ-free mice had a cecum size of around 19% of their bodyweight. In germ-free mice transplanted with Bacteroides and other bacilli, however, cecum size decreased back down to about 4.5% of total body weight (Schadler et. al, 1965).

Schadler and his colleaguesâ&#x20AC;&#x2122; study of germ-free mice represents one of the earliest examples of research that established a link between the microbiome and effects on the host.

"There are approximately 100 trillion microbes from over 1000 species and 7000 strains that reside in the gut."

There are approximately 100 trillion microbes from over 1000 species and 7000 strains that reside in the gut (Zhang and Chen, 2019). These bacteria are found primarily in the lower bowels, both in the lumen and attached to the mucosa.

The upper gastrointestinal tract (the stomach, duodenum, jejunum, and upper ileum) has sparse concentrations of microflora, less than 104 organisms/ml. Colonization of these areas by coliform organisms is characteristic of infectious pathogens such as Vibrio cholerae and enterotoxigenic Escherichia coli (Gorbach, 1996). The large intestine, however, contains a 149

Figure 2: Various functions of the gut microbiota in the human body. (1) Protection against pathogens. (2) Synthesis of vitamins. (3) Helps in immune system development. (4) Intestinal angiogenesis. (5) Storage of fats. (6) Fermentation of dietary fibers into Short Chain Fatty Acids (SCFAs). (7) Modulation of the Central Nervous System (CNS).

Source: Wikimedia Commons

"Changes in gut microbiome composition are a natural part of development; oneâ&#x20AC;&#x2122;s gut composition changes between birth and the age of 3 as it begins to resemble the adult microbiome."

rich diversity of microflora in concentrations of around 1011 bacteria per gram of stool, with a higher proportion of anaerobes compared to facultative aerobes. The human gut microbiome is known to play countless, crucial roles in various functions throughout the human body. These bacteria produce enzymes such as Ă&#x;-glucuronidase, sulfatase, and various glycosidases that deconjugate compounds assisting in enterohepatic circulation (Gorbach, 1996). The human gut microbiome is also crucial in synthesizing nutrients and vitamins such as vitamin K, biotin, vitamin B12, and thiamine, as well as fermenting dietary fibers into shortchain fatty acids such as acetate, propionate, and butyrate that are an important energy source for the host organism (Gorbach, 1996).

As a result of the integral relationship between the gut microbiome and other parts of the body, the health of the host organism is strongly correlated to the health and composition of their gut microbiome.

The Gut Microbiome and Health Changes in gut microbiome composition are a natural part of development; oneâ&#x20AC;&#x2122;s gut composition changes between birth and the age of 3 as it begins to resemble the adult microbiome. Factors that promote healthy development of microbiota include vaginal delivery, breast feeding, and exposure to a variety of microorganisms; conversely, birth by Caesarean section, formula milk, and exposure to antibiotics as an infant have negative 150

effects on diversity of the gut microbiome.

Delayed and improper colonization of the gut microbiome have been associated with increased risk for conditions such as asthma, diabetes, celiac disease, obesity, and more.

In addition, the gut microbiome plays crucial roles in preventing pathogens from causing infections. The intestinal barrier has multiple lines of defense that include commensal bacteria that competitively inhibit the colonization of pathogenic bacteria and produce metabolically protective compounds like butyrate (Mohajeri et. al, 2018). Antibiotics, though particularly adept at killing infectious bacteria, can also damage our microbiomes due to their broad-spectrum effects. Antibiotics can block enterohepatic circulation by suppressing intestinal flora that are responsible for producing deconjugating enzymes (Gorbach, 1996). In addition, this loss of beneficial microorganisms can cause host systemic immunity dysfunction, which impairs pulmonary defenses against pathogens and decreases immunoglobin A (IgA) production (Zhang and Chen, 2019). The composition of the gut can have far-reaching effects throughout the body. In particular, the gut-brain axis has been of considerable interest, particularly the impact that gut composition can have on changes in brain chemistry and human behavior.

The gut-brain axis consists of the bidirectional communication between the central and the enteric nervous systems. This bidirectional

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Figure 3: Various known effects of the gut microbiome on diseases that affect various organ systems of the body.

Source: Wikimedia Commons

communication has been found to consist of neural, endocrine, immune, and humoral (relating to extracellular fluids) links involving the central nervous system (CNS), the enteric nervous system (ENS), the autonomic nervous system, and the hypothalamic pituitary adrenal (HPA) axis (Carabotti et. al, 2015). As a result of this connection, changes in gut microbiome composition can produce changes in behavior and brain activity. Experiments in mice have shown that administering L. rhamnosus to mice reduces stress-induced corticosterone levels and anxiety-related behaviors (Mohajeri et. al, 2018). The most compelling evidence for the existence of the gut-brain axis comes from observations finding a correlation between differences in gut microbiota and the prevalence of various central nervous disorders, functional gastrointestinal disorders, and emotional disorders. Microbial dysbiosis, as well as gastrointestinal disorders such as irritable bowel syndrome (IBS), are strongly associated with mood disorders (Carabotti et. al, 2015). Models of multiple sclerosis and stroke suggest dysbiosis may indirectly influence the CNS through effects on immune homeostasis and immune responses (Bray, 2019). Changes in gut microbiota that are seen in people with Autism Spectrum Disorder (ASD) may play a causative role in the pathophysiology of this disorder (Bezawada et. al, 2020). Additionally, in patients with Alzheimerâ&#x20AC;&#x2122;s Disease (AD), a neurodegenerative disease, gut dysbiosis is thought to play a role in producing the

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pathophysiological symptoms that present in this disease (Hirschberg et. al 2019). This paper will proceed by highlighting observations and analysis of dysbiosis in patients with ASD and AD and the potential implications of the differences between individuals with either of these conditions versus normal, healthy individuals.

Autism and Gut Microbiome Composition Rates of diagnoses of Autism Spectrum Disorder have skyrocketed in the past few decades.

This dramatic increase in ASD suggests that environmental factors, such as certain maternal and pregnancy-related conditions, may be correlated with ASD incidence (Bezawada et. al, 2020). More specifically, given the importance of the gut microbiome to the rest of the body and the fact that in several studies children with autism have been found to suffer from a range of GI symptoms with higher incidence than normal children, there is reason to believe that changes in gut microbiota may be strongly correlated with incidence of ASD (Bezawada et. al, 2020).

"In autistic children, species of bacteria such as Clostridium, Sutterella, Desulfovibrio, and Lactobacillus tend to be found in significantly higher abundance compared to normal children."

In autistic children, species of bacteria such as Clostridium, Sutterella, Desulfovibrio, and Lactobacillus tend to be found in significantly higher abundance compared to normal children (Bezawada et. al, 2020). These differences likely contribute to the pathophysiology of autism,

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Figure 4: A diagram describing the connection between gut dysbiosis and disfunction of the immune system and the brain.

Abnormal gut microbiota can result in disruption of normal brain development and lead to the expression of autistic traits.

Source: Wikimedia Commons

"Notably, similar to humans with ASD, BTBR mice have an intestinal epithelium with increased macromolecular permeability as well as delayed intestinal transit."

which is characterized by a marked decrease in social behavior capabilities as well as the common symptoms of GI distress (Svoboda 2020). By analyzing changes in GI distress that may result from dysbiosis observed in individuals with ASD, one can gain a better understanding of the changes in gut microbiota that can result in or from ASD. Utilizing BTBR mice, a strain of mice that is one of the most widely-used murine models of ASD, one study by Golubeva et al. (2017) aimed to identify any changes in GI physiology as a result of the observed differences in the bacterial taxa of these BTBR microbiota.

Utilizing BTBR mice, these researchers were able to conduct a variety of studies to observe differences in their GI physiology. BTBR mice were observed to have a 50% reduction in 5-HT tissue levels, which are mucosal serotoninreleasing tissues that trigger intestinal peristalsis (involuntary muscle contractions that push food along the intestine), leading to decreased intestinal peristalsis capabilities in both the small and large intestine.

The BTBR mice also had impaired intestinal barrier function, with a dramatic increase in epithelial permeability in the distal ileum of BTBR mice. This can be explained by a 50% downregulation of creatine kinase Ckb and Ckm genes in BTBR mice which leads to reduced efficacy of phosphocreatine metabolic shuttle turnover, a process critical to maintaining the energy supply of tight junctions (TJs) between cells. These tight junctions are crucial to maintaining a proper macromolecular permeability of the intestinal epithelium and the downregulation of these genes leads to the increased macromolecular permeability observed in BTBR mice intestinal tissues (Golubeva et. al, 2017). Increased

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macromolecular permeability allows for larger molecules such as antigens and other harmful substances to diffuse from the intestine and migrate to other parts of the body. In addition, increased macromolecular permeability can disrupt homeostasis and lead to cellular disfunction of affected tissues.

Increased intestinal permeability is also correlated with the abundance of specific bacterial taxa. The increase in macromolecular diffusion across the intestinal epithelium was found to be positively correlated with Bacteroidetes species. On the other hand, the study found a negative association between the abundance of Ruminococcaceae Incertae Sedis and increased macromolecular diffusion (Golubeva et. al 2017). Notably, similar to humans with ASD, BTBR mice have an intestinal epithelium with increased macromolecular permeability as well as delayed intestinal transit.

Gut microbiota have also been speculated to play a role in the social behavior of individuals of individuals with ASD. The EPHB6 gene belongs to the Eph family of receptor tyrosine kinases and is located on chromosome 7q.

Recent studies have suggested that this gene is ASD-associated and transcriptome analyses have shown EPHB6 to be downregulated in ASD patients. The deletion of the EPHB6 gene in mice led to autism-like behavior and gut microbial disturbance in mice. Patients with ASD often display repetitive behaviors and social deficits. In this experiment, the mice with the EPHB6 gene deleted (or â&#x20AC;&#x153;knocked outâ&#x20AC;? of their genome) were referred to as KO mice.

In a series of tests, when compared to wild-

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type mice, the KO mice spent more time selfgrooming, less time sniffing at a partition in the social partition test, and showed less preference for the social mouse in another experiment.

The results of this study demonstrate that the KO mice, altered with the deletion of the EPHB6 gene, exhibited communication deficits, social deficits, anxiety-like behavior, and autism-like behavior with increased incidence compared to wild-type mice (Li et. al, 2020). This EPHB6 gene seems to regulate ASD-like behavior in mice.

In addition, an FITC test found that these mice had increased intestinal permeability compared to wild-type mice. FITC tests involve giving mice fluorescein isothiocyanate (FITC) and recording intestinal permeability by measuring the concentration of FITC in mouse serum at certain periods of time. 16S rRNA sequencing of the fecal microbial populations of KO mice found that there was a marked decrease in the abundance of Deferribacteres and Mucispirillum bacteria, indicating that there were significant changes in gut microbial composition. Perhaps the most significant evidence supporting the potential relationship between gut microbial composition and autism-like behavior came from translating the fecal microbiota of KO mice into SPF C57BL/6J, normal, mice.

Though ASD is generally considered a neurodevelopmental disorder, autism can also occur in patients postnatally. 3-weekold SPF C57BL/6J mice were transplanted with either 8-week-old KO or wild-type (WT) mice fecal microbiota. After three weeks, the SPF C57BL/6J mice with KO fecal microbiota

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displayed increased self-grooming and partially decreased social behavior compared to the control mice (as well as the mice treated with the fecal microbiota from WT mice). Following this, another group of SPF C57BL/6J mice were treated with a mixture of antibiotics for one week, greatly disrupting their gut microbiota composition. After receiving the antibiotics, these mice were observed to exhibit decreased self-grooming and partial social deficits, supporting the notion that gut microbiota can play an important role in causing autismlike behavior. In both experiments, disruption of the normal gut microbiome, either by transplantation of another mouseâ&#x20AC;&#x2122;s fecal microbiota or through antibiotics, resulted in the SPF C5B7L/6J mice exhibiting autism-like behavior. A third experiment was run, testing the effects of fecal microbiota transplant of WT mice into KO mice. This experiment found an increase in the relative abundance of Deferribacteres and Mucispirillum bacteria in the KO mice, along with a significant increase in social behavior and a decreased tendency for self-grooming (Li et. al, 2020). These experiments seem to support that increased levels of Deferribacteres and Mucispirillum lead to a decrease in social deficits and autism-like behavior.

What does this mean in terms of treatments and therapies for individuals with autism? Fecal microbiota transplantation into individuals with ASD could have multiple benefits. Not only could it help relieve ASD-related GI distress, it could also help improve social behavior in patients with ASD. In one study, 18 patients with ASD were given Microbial Transfer Therapy (MTT) for 10 weeks. 8 weeks after the procedure, the 18 patients reported an 80% reduction in GI symptoms and a slow but steady improvement in core ASD symptoms. Two years later, both the GI and behavioral symptoms of all 18 participants had improved significantly compared to baseline measurements collected before the MTT was performed (Kang et. al, 2019). Although this research is still in the early stages, this and other studies suggest that manipulation of human microbiota can be used to not only regulate, but even diminish both GI and adverse behavioral symptoms of Autism Spectrum Disorder.

Figure 5: An image of an amyloid plaque in the hippocampus of the brain of an individual with Alzheimerâ&#x20AC;&#x2122;s Disease.

Source: Wikimedia Commons

"Fecal microbiota transplantation into individuals with ASD could have multiple benefits. Not only could it help relieve ASD-related GI distress, it could also help improve social behavior in patients with ASD."

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Alzheimer’s Disease and Gut Microbiota Alzheimer’s Disease (AD) is a neurodegenerative disease characterized by progressive decline in cognitive function and the loss of certain types of neurons and synapses. The most recognized pathophysiological features are amyloid plaques, extracellular accumulations of abnormally folded amyloid beta (Aβ) proteins, and neurofibrillary tangles, paired helical filaments consisting of hyperphosphorylated tau proteins. It has been hypothesized that AD may be associated with dysbiosis of the intestine, supported by the existence of the gut-brain axis and the influential activity of intestinal flora on the brain (Angelucci et. al, 2019).

"Prolonged neuroinflammatory processes have been shown to cause certain neurodegenerative diseases, including AD. It has been proposed that dysbiosis may be one of the factors that contributes to the prolonged neuroinflammatory process and response that is observed in patients with AD."

Prolonged neuroinflammatory processes have been shown to cause certain neurodegenerative diseases, including AD. It has been proposed that dysbiosis may be one of the factors that contributes to the prolonged neuroinflammatory process and response that is observed in patients with AD (Angelucci et. al, 2019). One key topic of research has been. It has long been believed that diet plays a role in preventing disease development, as high gluten and sugar intake as well as low healthy fat intake can cause systemic inflammation and eventually attack the CNS, which negatively impacts brain health.

Omega 3 polyunsaturated fatty acids (-3 PUFAs) are vital for neuronal and brain functions, and the consumption of -3 PUFAs has also been associated with decreasing chances of AD. Fatty acids and -3 PUFAs are both absorbed in the intestine, and tests in pigs have found that the composition of their gut microbiota changes significantly when they are fed with fatty acid and -3 PUFA enriched diets (Hu et. al, 2016).

Similar to the observed GI distress in patients with autism, low intestinal barrier permeability has been found to be important in reducing a person’s risk of developing AD. The composition of the gut microbiome has been found to be an important predictor for the development and integrity of the bloodbrain-barrier, and increased permeability of this membrane has been linked to increased Aβ protein accumulation in the brain, one of the hallmarks of Alzheimer’s Disease (Hu et. al, 2016). Calprotectin is a protein that is released from neutrophils and monocytes (immune cells) and is indicative of intestinal inflammation. One study of 22 patients with AD found calprotectin concentrations above normal, suggesting that AD patients experience disrupted intestinal

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function and that gut microbiota play a role in AD pathogenesis (Leblhuber et. al, 2015).

Lactobacillus and Bifidobacterium, two types of bacteria in the gut, produce GABA, an inhibitory neurotransmitter; diminished levels of GABA can cause cognitive impairment (Hu et. al, 2016). Gut microbial disruption, specifically a reduction in the abundance of these types of bacteria, is associated with a reduction of GABA in the CNS. Postmortem studies of AD patients found reduced GABA levels in the frontal, temporal, and parietal cortices of these patients (Hu et. al, 2016). 95% of serotonin (5HT), a neurotransmitter important in regulating cognitive function, in the human body is synthesized in the gut and gut microbiota playing an integral role in this synthesis. As a result, disturbances to the gut microbiota that changes 5-HT biosynthesis may also influence the pathological development of AD (Hu et. al, 2016).

Infection with H. pylori, a gram-negative bacterium that attaches to gastric epithelial cells, has been found to be correlated with AD (Hu et. al, 2016). In addition, AD patients infected with H. pylori have scored lower in MMSE testing, a test of mental abilities, and have shown more severe cognitive impairment (Roubaud-Baudron et. al, 2012). A wide variety of microbial infections in addition to H. pylori seem to correlate with higher risks of developing AD and other neurodegenerative diseases.

Though there is no direct evidence that gut microbiota protects against these infections, there is reason to believe that dysbiosis can lead to increased susceptibility of host organisms to these infections that promote the onset of AD (Hu et. al, 2016). The rapid increase in the prevalence of Alzheimer’s Disease in the past few decades can be correlated with changes in lifestyle, diet, and behaviors that disrupt our gut microbiota composition.

Conclusion The field of gut microbiome research is relatively young and constantly changing. The concept of the gut-brain axis is a novel one, and research in the past decade has shed light on the interconnection between the gut and the brain, two regions of the body that seem intuitively to have little effect on each other.

Changes in gut microbiota composition have been associated with various disruptions in human health, ranging from gastrointestinal DARTMOUTH UNDERGRADUATE JOURNAL OF SCIENCE

distress to changes in brain physiology and behavior. More specifically, gut microbiota composition has been correlated with autismlike behavior, and transplantation of healthy microbes into ASD-afflicted patients has shown to not only help in manage GI symptoms, but also improve social behavior. Changes in patients with Alzheimer’s Disease have also been found to have a basis in the intestine and gut. Though further research is needed before any therapies can be developed for these two particular conditions, there is already some evidence that treatment of the gut microbiome can help manage ASD symptoms and potentially slow the progression of Alzheimer’s Disease.

Kang, D., Adams, J., Coleman, D., Pollard, E., Maldonado, J., McDonough-Means, S., . . . Krajmalnik-Brown, R. (2019, April 9). Long-term benefit of Microbiota Transfer Therapy on autism symptoms and gut microbiota. Retrieved from https:// www.ncbi.nlm.nih.gov/pmc/articles/PMC6456593/ Leblhuber, F., Geisler, S., Steiner, K., Fuchs, D., & Schütz, B. (2015, February 14). Elevated fecal calprotectin in patients with Alzheimer's dementia indicates leaky gut. Retrieved from https://pubmed.ncbi.nlm.nih.gov/25680441/ Li, Y., Luo, ZY., Hu, YY., Bi, YW., Yang, JM., Zou, WJ., Song, YL., Li, S., Shen, T., Li, SJ., Huang, L., Zhou, AJ., Gao, TM., Li, JM. (2020, August 20). The gut microbiota regulates autism-like behavior by mediating vitamin B 6 homeostasis in EphB6deficient mice. Retrieved from https://pubmed.ncbi.nlm.nih. gov/32819434/

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Angelucci, F., Cechova, K., Amlerova, J., & Hort, J. (2019, May 22). Antibiotics, gut microbiota, and Alzheimer’s disease.

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Bezawada, N., Phang, T., Hold, G., & Hansen, R. (2020, January 24). Autism Spectrum Disorder and the Gut Microbiota in Children: A Systematic Review. Retrieved from https://www. karger.com/Article/FullText/505363

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Bray, N. (2019, June 17). The microbiota–gut–brain axis.

Retrieved from https://www.nature.com/articles/d42859019-00021-3 Brunello, L. (2019, June 17). Gut microbiota transfer experiments in germ-free animals. Retrieved from https:// www.nature.com/articles/d42859-019-00009-z Carabotti, M., Scirocco, A., Maselli, M., & Severi, C. (2015, Spring). The gut-brain axis: Interactions between enteric microbiota, central and enteric nervous systems. Retrieved from https://www.ncbi.nlm.nih.gov/pmc/articles/ PMC4367209/ Clark, H. (2019, June 17). Culturing anaerobes. Retrieved from https://www.nature.com/articles/d42859-019-00007-1 Golubeva, A., Joyce, S., Moloney, G., Burokas, A., Sherwin, E., Arboleya, S., . . . Cryan, J. (2017, September 21). Microbiotarelated Changes in Bile Acid & Tryptophan Metabolism are Associated with Gastrointestinal Dysfunction in a Mouse Model of Autism. Retrieved from https://www.ncbi.nlm.nih. gov/pmc/articles/PMC5652137/

Roubaud-Baudron, C., Krolak-Salmon, P., Quadrio, I., Mégraud, F., & Salles, N. (2011, December 1). Impact of chronic Helicobacter pylori infection on Alzheimer's disease: Preliminary results. Retrieved from https://pubmed.ncbi.nlm. nih.gov/22133280/ Schaedler, R., Dubos, R., & Costello, R. (1965, July 01).

ASSOCIATION OF GERMFREE MICE WITH BACTERIA ISOLATED FROM NORMAL MICE. Retrieved from https://rupress.org/ jem/article/122/1/77/3859/ASSOCIATION-OF-GERMFREEMICE-WITH-BACTERIA Svoboda, E. (2020, January 29). Could the gut microbiome be linked to autism? Retrieved from https://www.nature.com/ articles/d41586-020-00198-y Zhang, S., & Chen, D. (2019, May 20). Facing a new challenge: The adverse effects of antibiotics on gut microbiota and host immunity. Retrieved from https://www.ncbi.nlm.nih.gov/ pmc/articles/PMC6511407/

Gorbach, S. (1996, January 01). Microbiology of the Gastrointestinal Tract. Retrieved from https://www.ncbi.nlm. nih.gov/books/NBK7670/ Hirschberg, S., Gisevius, B., Duscha, A., & Haghikia, A. (2019, June 25). Implications of Diet and The Gut Microbiome in Neuroinflammatory and Neurodegenerative Diseases.

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Research on COVID-19 and COVID-19 Impacts on Research STAFF WRITERS: STEPHANIE LIBBY, CAMERON SABET, GRACE NGUYEN, AND VAANI GUPTA EDITORIAL BOARD WRITERS: KRISTAL WONG AND DINA RABADI Cover Image: NIH researcher in PPE working in a lab. During the stay-at-home orders, many labs were forced to shut down. Labs are gradually reopening, but not without precautions and rules.

Source: The National Heart, Lung, and Blood Institute Disclaimer: This article was written throughout the fall of 2020, a time period in which there was instability both in terms of the COVID-19 pandemic and U.S. politics, as the U.S. presidential election occurred this year. Due to both of these factors, some of the information presented here may have changed by the date of the articleâ&#x20AC;&#x2122;s publication. The authors worked diligently to ensure all data presented is as accurate as possible, but given the fluid nature of these situations, new information may be presented in the future.

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Introduction In December 2019, there was an outbreak of the SARS-CoV-2 virus in Wuhan, China; it has since spread throughout the world, making COVID-19 the first global pandemic since the 1918 influenza pandemic. On March 13th, 2020, the President of the United States declared a national state of emergency and by March 26th, the U.S. led the world in the number of COVID-19 cases. By the end of the month, several states across the country had issued stay at home orders, meaning that at least 265 million Americans were advised to stay at home (Taylor, 2020). As of November 23, 2020, there have been 12,175,921 total COVID-19 cases in the U.S., resulting in 255,958 deaths (CDC, 2020).

COVID-19 is a respiratory disease caused by the SARS-CoV-2 virus, a member of the coronavirus family of viruses named after the crown-like proteins on their surface. It is transmitted via

single-stranded RNA enclosed in a protein coat (Chi et al., 2020). This virus specifically impacts the upper and lower respiratory tract; symptoms include shortness of breath, coughing, fever, fatigue, headache, body ache, sore throat, and even loss of taste or smell. Symptoms of COVID-19 appear within 14 days of exposure and can range from mild, where individuals have a low fever of 100°F and fatigue, to severe, where individuals experience shortness of breath, confusion, and chest pain. In addition, while people of all ages are susceptible to COVID-19, older adults and those with pre-existing conditions such as asthma, coronary heart disease, history of smoking, and obesity are the most vulnerable to this infection (Sauer, 2020).

COVID-19 can spread via close contact with an infected individual(inhalation of respiratory droplets) or through contact with a surface that contains the virus. To reduce the spread DARTMOUTH UNDERGRADUATE JOURNAL OF SCIENCE

of the virus, individuals have been asked to maintain a 6-foot distance from one another and to wear masks to help prevent transmission (CDC, 2020b). However, research on viral transmission and prevention is still ongoing.

Currently, studies have shown that a person’s risk for contracting COVID-19 reduces by as much as 65% if they wear a mask (Kushman, 2020). Employing these measures in addition to disinfecting surfaces and hand washing can greatly reduce an individual’s risk of COVID-19.

COVID-19 has had an undeniable impact on research. The start of the pandemic halted many time-sensitive experiments and put researchers in the difficult position of caring for valuable test subjects and specimens with governmental and institutional regulations.

Animal-based research, especially those involving primates which require more care and upkeep, has been challenging, especially during the early phases of COVID-19 pandemic as in-person lab activities have been limited.

For those who can still access their labs, critical resources like these test animals are in short supply. For those pursuing COVID-19 related research, some labs may require specific breeds of animals, such as mice which produce the ACE2 protein. ACE2 is the protein which allows the virus to enter human cells, so these mice are currently in high demand, and the small labs and repositories they come from have been overwhelmed by the quantity of mice ordered.

These mice were also popular for research on Severe Acute Respiratory Syndrome (SARS), a short-lived epidemic caused by a coronavirus similar to the SARS-CoV2 virus of COVID-19.

However, once the disease faded in 2004, interest and funding of this disease, and use of the ACE2-producing mice, dried up. As early as March 2020, researchers were put on waiting lists to receive these mice. Another useful animal in drug and vaccine development is monkeys, as they seem to develop symptoms most similar to those with humans, including symptoms of COVID-19. Still, scientists must be cautious about making extrapolations to humans (Callaway, 2020).

The COVID-19 pandemic also derailed clinical research. Clinical trials around the world were required to cease enrolling new patients, and many planned clinical trials were cancelled.

In fact, up to 80% of non-COVID-19 trials in the US were halted (van Dorn, 2020). This postponement of clinical trials was done to prioritize patient safety during the time in which little was known about the severity of COVID-19. In March 2020, pulmonary cancer

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researcher Roy Herbst stated that cancer clinical trials have been cut, only reserved for patients with “exceptional need” (Maxmen, 2020).

While some trial treatments may significantly improve the lives of those severely ill, it is also important to note that those with advanced conditions are more vulnerable to infection; venturing outside for visits to clinics would also increase their risk of exposure to the deadly virus (Ledford, 2020). Additionally, it takes a large team of physicians, nurses, coordinators and other staff to conduct a clinical trial, and minimizing potential patient exposure to COVID-19 has brought on innovation, particularly in terms of telemedicine; data collection, patient recruitment, appointments, and even receipt of drugs can now be done at home via delivery services in some trials.

The exception is, of course, COVID-19 clinical trials, particularly those for drug and vaccine development (van Dorn, 2020). Many rules and regulatory processes have been expedited in order to rapidly find treatments and cures for the disease, both governmental and private.

Though these exceptions with COVID-19 are likely to return to normal after a cure or vaccine has been discovered, they were able to occur through collaboration between academic, government, and industry. Hopefully, this collaborative mindset will remain long after the pandemic.

Although laboratory and clinical research may have become slower, the era of COVID-19 has brought unprecedented accessibility and speed to scientific publishing. Dozens of journals have made their COVID-19 articles open access, regardless of subscription status to the journal, for at least the duration of the pandemic.

This, in addition to increased use of preprint servers (where scientists can post preliminary results for feedback and viewing), has made science more transparent and accessible.

While preprint data is not peer-reviewed, it is a great way to share new information and data, especially during an era of uncertainty with an urgent need for rapid discovery. Open-access is a useful way to disseminate information in the midst of a pandemic, but only larger structural changes (that could be induced by COVID-19) in the scientific publication process will incentivize researchers to make this change permanent. Changing the industry will require a seismic shift in the way scientific publishing is conducted, and this question will be explored throughout this piece.

"Although laboratory and clinical research may have become slower, the era of COVID-19 has brought unprecedented accessibility and speed to scientific publishing. Dozens of journals have made their COVID-19 articles open access, regardless of subscription status to the journal, for at least the duration of the pandemic."

An interesting juxtaposition to the shutdown of non-COVID-19 clinical trials, as well as the initial

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Figure 1: A computer rendering of the novel SARS-CoV-2 Coronavirus. The gray area is the viral wall, which contains the virus’ genetic material. The red spikes on the virus wall are sticky S (spike) proteins that attach to an individual’s cells.

After attachment, the virus is able to replicate to form millions of copies, thus infecting the individual. The yellow and orange spots are other proteins, E (envelope) and M (membrane), respectively.

Source: US Food and Drug Administration

"Considering that the modern scientific vernacular used in scientific publications today did not appear until the 18th and 19th centuries, it should not come as much of a surprise that current peer review practices— one of the most distinguishable characteristics of the entire publication process—did not emerge until postWorld War II."

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pause in research during the pandemic, is the fact that generation of scientific data is at an alltime high; this era of COVID-19-related research has even been compared to the Manhattan Project, the US-led project to develop the world’s first nuclear weapons during WWII (Drakemen et. al, 2020). An example of this is Project Warp Speed, the US government’s goal to create and distribute 300 million vaccines by January 2021 (“Fact Sheet: Explaining Operation Warp Speed”, 2020). Operation Warp Speed is just one of the ways that researchers are getting funding to conduct COVID-19 research. Tens of billions of dollars from various government organizations have gone into Operation Warp Speed, helping pharmaceutical companies develop and manufacture potential vaccines. Additionally, many grants are being targeted at academic labs studying COVID-19, though they do not qualify for Operation Warp Speed funding, These factors are leading to this massive generation of scientific data. The pressure of time is undeniable, as there are thousands of new cases and deaths each day. Since this scientific information is being generated and distributed rapidly, it is important for researchers and clinicians to understand how this will impact the scientific process and publishing post-pandemic.

This article will address the history of scientific publishing; identify key issues in scientific research and publication processes through the use of case studies; outline components of “good” science, especially in the context of COVID-19 clinical trials; identify how scientific information is disseminated both in media and politics; and lastly, explore the manners in which scientific publication may change in the future.

History of Scientific Publishing and the Modern Day The extensive process required to publish an article in a scientific journal has not been a longstanding feature of academic writing. In fact, the scientific journal itself is a relatively new concept compared to the long history of scientific development and experimentation. Scientific— and other academic—ideas prior to the 1650s were often communicated through selfpublished books or personal letters, which often sat untouched for years, as there was no official protocol for scientific publication (Swoger, n.d.).

It was not until the beginning of the scientific revolution during the 16th and 17th centuries that the first scientific journal emerged. In the mid 1660s, Henry Oldenburg chartered Philosophical Transactions through one of the first scholarly societies, the Royal Society in

England (Mack, 2015). While its publication process would be considered primitive by today’s standards, it was the success of Philosophical Transactions that paved the way for modern scientific journals, which slowly evolved from broad, qualitative observations described with elaborate, ornate language to specialized, quantitative interpretations of observations analyzed with technical language.

Considering that the modern scientific vernacular used in scientific publications today did not appear until the 18th and 19th centuries, it should not come as much of a surprise that current peer review practices— one of the most distinguishable characteristics of the entire publication process—did not emerge until post-World War II. The beginning of the peer-review process is said to have begun in 1752, when the Royal Society adopted a review procedure similar to that of the Royal Society of Edinburgh: possible publication materials were inspected by a group of specialists in the relevant field who had great influence on whether the article would be accepted for publication. Other societies, like the Literary and Philosophical Society of Manchester, also embraced similar methods alongside including disclaimers to the accuracy of the publications (Spier, 2002). As scientific knowledge diversified and more manuscripts featured specialized topics, the need for review from peers in those specialized fields increased.

The modern concept of peer review began around 1940 in English-speaking countries but was implemented gradually; Science and The Journal of the American Medical Association did not utilize outside reviewers until after 1940 and The American Practitioner did not see any in-house reviewers until 1962 (Burnham, 1990).

This form of peer review has been in use ever since, and the development of the Internet

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has made peer review far easier to coordinate online (Butler, 1999; Jirge, 2016). Consequently, journals like ScienceDirect and Springer publish electronic versions of recently peer-reviewed publications, and groups like PubMed Central offer peer-review for its internet-based articles (Butler, 1999). Today, a researcher typically sends his or her paper electronically to a journal that specializes in his or her field. Then, primary editors review the article, checking for formatting, plagiarism, and suitability to the journal (Kelly et al., 2014, Jirge, 2016). If it passes the initial evaluation, the journal will send the paper to proficient researchers in the field for a formal peer review (Kelly et al., 2014). Typically, this review process takes four to six weeks, and leaves the author(s) with an article decision which could be a rejection, an acceptance with comments, or an acceptance without changes (Jirge, 2016).

In addition to increasing access to peer review, the 20th century saw several other turning points in the scientific publication process, most notably the development of electronic printing and the possibility of open access.

The popularization of email in 1971 helped fuel the first digitization efforts to convert physical content into electronic copies, such as Project Gutenberg, the oldest digital library.

This was the beginning of a new era in scientific publication as research became easier to conduct and even more accessible to the world beyond academia—allowing anyone with an internet connection to publish any idea or observations to the masses (i.e. non-science journal areas)—and this was only heightened with the open access (OA) movement, which will be discussed in upcoming paragraphs.

With the movement’s direct contribution to the increase of scientific journal publications also came another major turning point in scientific publication: the debate over open access that accompanied the rise of the internet.

Before the arrival of the internet, scientific journals sold subscriptions to users at a very high price because the market was controlled by only a handful of publishers such as ReedElsevier, Wiley-Blackwell, Springer, and Taylor & Francis (Resnick & Belluz, 2019). However, the shift from print articles to electronic PDFs has drastically decreased the cost to publish and share information. Publication sites such as arXiv (pronounced “archive”) made it possible for researchers to publish at nearly no cost (Staddon, 2020). In addition, the timeline from submission to publication

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is no longer as lengthy, and collaboration across disciplines is much easier. However, the Internet also brought with it a high quantity of unfiltered information; this has spurred issues of plagiarism, privacy, and has allowed large publishers to stay relevant by helping to combat these issues. Publishers and journals have respected editors, associate editors, and peer reviewers who make their publications credible, which enables them to stand out amidst the jumble of more easily accessible information. However, large publishers made their subscriptions large, bundled deals, giving them justification to keep subscription prices high (Resnick & Belluz, 2019). Although the cost per research article should have decreased due to material resources no longer being needed for printing and distribution, the cost of subscriptions did not decrease. Even though the Internet made information more easily accessible to the general population, high subscription prices still made certain scientific journals only available to those able to pay a large price.

The high cost of publishing and the availability of the Internet led to Movement, another turning point in scientific publishing. The Open Access Movement aims to remove the barriers that prevent people from accessing, sharing, and re-using online scholarly research (Tennant et al., 2016). This allows a wider range of people to access research findings and take part in scholarly conversation. Arguments in favor of OA include bridging the gap between developed and developing countries, giving equal access to information to people all over the globe, making research available for smaller institutions, generating more academic citations, spreading knowledge faster, and having a greater impact on society at large (Tennant et al., 2016). Additionally, some argue that research funded by public money should be available for everyone to see (Vlokhoven, 2018). Although OA has caused many positive changes to the scientific research environment, it has also created some issues. With so much available information, it becomes harder to sift through what information is valid, and makes it harder for scientists to internally validate all scientific information getting to the public.

Open access journals also change how the publication is financed. Instead of charging those who are subscribed to the journal, the author of an article may now be responsible for an article processing charge (APC). This business model makes it more profitable to accept as many articles as possible, which

"In addition to increasing access to peer review, the 20th century saw several other turning points in the scientific publication process, most notably the development of electronic printing and the possibility of open access."

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Figure 2: President Donald J. Trump, 45th President of the United States (center), is known for his controversial statements, especially those during the COVID-19 pandemic.

Source: Wikimedia Commons

in turn has been found to lower the average quality of accepted articles (Vlokhoven, 2018).

Nonetheless, publications continue to move in the direction of open access.

"As the global pandemic continues, there have been questions about the validity of COVID-19 research being conducted. After all, there have been several instances where studies have been published in well-known journals, only to be retracted within months, or even weeks, of publication."

Today the publishing process still involves similar steps including submission, peer review, production, publication, dissemination, and archiving (de Hon, 2015). However, authors may face roadblocks at a number of these steps. Upon submission, the article may be rejected, suggested to have major changes, or suggested to be submitted to another journal.

Similarly, in the peer review phase, the article may be accepted without revisions, requested to have minor revisions, requested to have major revisions, or rejected. In general, the process from submission to acceptance takes around 100 days (Powell, 2016). However, this 100 number may be even larger because some journals report when an article was resubmitted instead of submitted for the first time. In the era of COVID-19, the time it takes for a non-COVID-19 article to be accepted is still around 100 days, but the median time it takes to accept a COVID-19 related article is 13 days, suggesting that articles related to COVID-19 are accepted 8 times faster than other articles (Barakat et al., 2020). The subsequent section will address issues with this accelerated research and publishing process.

Case Studies from acceleration in publishing during COVID-19 As the global pandemic continues, there have been questions about the validity of COVID-19 research being conducted. After all, there have been several instances where studies have been published in well-known journals, only to be retracted within months, or even weeks, of

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publication. One such example is the retraction of the article, “Cardiovascular Disease, Drug Therapy, and Mortality in COVID-19,” which was published in the New England Journal of Medicine (NEJM) (Mehra et al., 2020a). This article was published on May 1, 2020, only to be retracted one month later on June 4, 2020. This study specifically analyzed the impact of ACE inhibitors and ARB blockers, two cardiovascular drugs, on patients with COVID-19. It found that individuals with cardiovascular disease were more susceptible to COVID-19, and that ACE inhibitors and ARB blockers could be safely taken by COVID-19 patients; this research was significant, as it identified a sector of the population more vulnerable to COVID-19 and stated that individuals with COVID-19 could still take their prescribed cardiovascular drugs (Mehra et al., 2020).

This study was retracted as the validity and accuracy of the data could not be verified. The authors of the study, Mehra and colleagues, released a retraction notice, where they explained that “the authors were not granted access to the raw data and the raw data could not be made available to a third-party auditor” (Mehra et al., 2020b). The authors of this study utilized data on patients from 671 hospitals across six continents from Surgisphere, an Illinois-based company (Bauchner et al., 2020); when these authors requested a thirdparty review of the data’s validity, Surgisphere refused to release the complete dataset and ISO audit report, as doing so would have violated confidentiality agreements. Hence, Mehra and the other authors had no choice but to retract their study from the NEJM (Piller & Servick, 2020).

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The sudden retraction of this study has resulted in doubts regarding the accuracy of the research being published during the COVID-19 pandemic. It has also caused people to question the editing process of well-renowned journals, such as NEJM, as well as how much access authors and editors should be given to datasets (Piller & Servick, 2020). In fact, Chris Chambers, psychologist at Cardiff University and member of the UK Reproducibility Network Steering Group, noted that “the failure to resolve such basic concerns about the data during the course of normal peer review raises serious questions about the standard of editing” (Piller & Servick, 2020). Furthermore, the sudden retraction of this cardiovascular and COVID-19-related study impacted future research, as well as the actions taken by institutions such as the Food and Drug Administration (FDA); upon the retraction of the study, the FDA was forced to release an announcement, emphasizing that COVID-19 patients should not take cardiovascular drugs for fear that it may result in or further worsen heart and respiratory complications (Joseph, 2020).

Another world-renowned journal, The Lancet, published a COVID-19-related article titled “Hydroxychloroquine or chloroquine with or without a macrolide for treatment of COVID-19: a multinational registry analysis” on May 22, 2020, but quickly retracted it on June 4th, 2020.

Published amidst President Trump’s vocalized support for the anti-malarial drug, the article found that neither hydroxychloroquine or chloroquine, used with or without a macrolide, were effective in treating COVID-19 and that such treatments actually increased the patients’ mortality rate (Mehra et al., 2020). The results from this study had drawn on the same dataset from Surgisphere as the article published by NEJM and the two studies even had three of the same authors: Mehra, Desai, and Patel.

The conclusions from this study affected labs and companies around the world, including the World Health Organization (World Health Organization, 2020). Researchers from around the world halted laboratory operations after The Lancet publication, only to resume costconsuming research after the study was retracted. As Ian Kerridge, a bioethicist at the University of Sydney, Australia, notes, this oversight is problematic not only for the journals, but for the integrity of science, medicine, and clinical trials (Ledford & Noorden, 2020).

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This costly misstep in The Lancet caused the journal to rethink and restructure its peer review process. In a comment from the editors of The Lancet group, the journal announced that it was adopting stricter and more defined checklists and protocols for authors and editors, as well as a section regarding data-sharing to ensure that the authors have accessed and reviewed the data before submission and publishing. In addition, The Lancet will dedicate another editorial step towards data review and will ensure that a statistic specialist or other editor well versed in reviewing large datasets is involved in the review process (Editors of the Lancet Group, 2020).

In light of the controversial nature of hydroxychloroquine and the importance of well thought-out and high-quality clinical studies, the National Institute of Health (NIH) has partnered with 16 pharmaceutical and biotech companies in the initiative called Accelerating COVID-19 Therapeutic Interventions and Vaccines (ACTIV), a public-private partnership to minimize the issue of poorly conducted research studies. Here, experts at the NIH can guide these large developers, who are creating novel drugs and vaccines, in conducting the best clinical study and in evaluating data on candidate selection and testing (Kaiser et al., 2020).

The mistakes of NEJM and The Lancet have forced other leading journals towards reflection.

Nature, an internationally famous academic peer-reviewed journal based in London, UK, issued a statement in their editorial section detailing their expansion of open access during the pandemic. Yet, Nature also voiced their intention to expedite the publishing of COVID19-related media (“Coronavirus Pandemic,” 2020). Other prominent journals such as Journal of the American Medical Association (JAMA) have released messages since the pandemic in regard to publishing. Interestingly, the journal even mentioned a 10-12 day rush approval process for COVID-19-related articles. It is easy to wonder how JAMA will maintain its standards despite its 10-12 day rush approval process.

JAMA received roughly 11,000 manuscripts between January 1st and June 1st of this year.

The editors note that mistakes associated with accelerated publishing may cripple the public trust in science, but they assure authors that, from the time of submission, virtually all of these manuscripts would have been handled by full-time JAMA editorial staff. In addition, they wrote that, if a certain manuscript results

"In light of the controversial nature of hydroxychloroquine and the importance of well thought-out and high-quality clinical studies, the National Institute of Health (NIH) has partnered with 16 pharmaceutical and biotech companies in the initiative called Accelerating COVID-19 Therapeutic Interventions and Vaccines (ACTIV), a public-private partnership to minimize the issue of poorly conducted research studies."

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"Despite the randomized controlled trial being the gold standard, it still raises ethical concerns involving the selection of participants, the use of a placebo, and randomization. Those who take on the risk of participating in the trial are often not those who reap the benefits."

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are likely to influence clinical practice or public health policy, or “be of concern to the public,” JAMA will ensure that the piece be reviewed by one or more statisticians, as has always been the case. Here, JAMA is acknowledging that immediately impactful manuscripts require additional data or at least a confirmation of the experimental method to ensure accuracy and precision. In this sense, JAMA also understands that “although rapid publication of clinically actionable information during a pandemic is important, publishing results that are not valid can do harm” (Bauchner et al., 2020).

The above quote holds true for this next example where a flaw in the database of an Ivermectin study in pre-print heavily influenced the pandemic response of several Latin American countries. Ivermectin is a common antiparasitic drug primarily used on livestock and humans infected with parasitic worms (NIH, 2020). The Latin American response was catalyzed by a now retracted pre-print from SSRN which suggested Ivermectin as a treatment for COVID-19.

Coincidentally, authors Desai and Mehra were also listed as co-authors of the pre-print in April and the data was also from Surgisphere. The authors retracted this preprint in April because it was not “ready for peer review,” but by then it was already too late (Ledford & Noorden, 2020).

This unpublished piece led countries such as Bolivia, Peru, Guatemala and many others to prematurely add Ivermectin to their COVID-19 treatment guidelines, though they are no longer listed on as treatments (Ledford & Noorden, 2020). Consequently, health care workers and police officers in these countries were reported to have seized hundreds of bottles of Ivermectin for COVID-19 human treatment and people have scrambled to use human and veterinary forms of Ivermectin to treat those infected with COVID-19 (Mega, 2020). In Peru, an evangelical group were supported by the mayor to give veterinary Ivermectin to about 5,000 people in a remote region of the Peruvian Amazon, largely comprised of indigenous populations (Fowks, 2020)

Another issue resulting from this faulty preprint is that the Latin American response and wide usage of Ivermectin makes it hard for good clinical studies to report reputable data on the drug’s effectiveness on COVID-19. Since so much of the population has taken Ivermectin, it would be hard to find subjects who have not tried the anti-parasitic drug (Mega, 2020). Drug trials for Ivermectin have continued, though Alejandro Krolewiecki, a physician leading an Ivermectin

study at the National University of Salta in Orán, Argentina, warns that a Phase III clinical trial are not necessarily possible: these large trials require thousands of patients, some of which will not receive the drug and will serve as the control group (Mega, 2020).

However, there are still many who are committed towards proving Ivermectin’s efficiency. An Australian-based team led by Leon Caly has published a study that shows Ivermectin’s ability to halt replication of the virus (Caly et al., 2020). One caveat of this possible treatment is that Ivermectin would likely require a large dose (greater than that typically used to treat parasitic worms) in order to achieve an antiviral effect, and the side effects of such dosage are unclear (Pena-Silva et al., 2020). Currently, this drug has not been approved in the US for COVID-19 treatment and is not recommended for this purpose with the exception of clinical trials (NIH, 2020). Perhaps the greatest issue is Ivermectin’s “ghost effect” on Latin America. Since the retracted pre-print was not published in a journal, there is no formal statement saying that the information was wrong – instead, many are unaware and have remained proponents of Ivermectin as a COVID-19 treatment (Mega, 2020).

Importance of Study and Clinical Trial Quality in the COVID-19 Era The current gold standard for clinical studies is the randomized controlled trial (RCT) (Nardini, 2014). In an RCT, participants of the study are randomly placed into either a control group or experimental group. Performing a study in this manner helps to eliminate confounding variables that may lead to biased or incorrect results (Misra, 2012). Despite the randomized controlled trial being the gold standard, it still raises ethical concerns involving the selection of participants, the use of a placebo, and randomization. Those who take on the risk of participating in the trial are often not those who reap the benefits. The primary purpose of the trial is not to treat individual patients but to understand the efficacy of a treatment and further medical knowledge.

Past ethical breaches have involved taking advantage of vulnerable populations such as prisoners, the mentally disabled, the poor, or ethnic populations. These populations can be more vulnerable, as they may experience high pressure to accept being part of a study

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from persons who have authority or influence over them, or because they need the financial compensation that may come along with participating in a study. Additionally, a clinical trial using a placebo brings in the ethical issue of deception. Although participants consent to being part of a study in which they may randomly be chosen to receive a placebo instead of the treatment, they are taking on the risk that they may be harmed by not receiving the treatment. Still, under the Declaration of Helsinki, a set of ethical principles concerning human subjects, using a placebo is acceptable as long as there is no proven treatment that exists. On the other hand, the participant could also be randomly chosen to take a treatment that is ineffective or even harmful. Due to this randomization, those running the study must operate under what is known as clinical equipoise. This is the assumption that neither the control nor the experimental group is receiving the better treatment (Nardini, 2014). Although randomizing participants into either the control or experimental group can lead to ethical issues, not randomizing the subjects could lead to skewed or incorrect data, where one group is naturally healthier than another, falsely causing the experimental treatment to look like it had a positive or negative effect.

Not only should subjects be randomized to ensure validity, but the sample size should be representative and diversity of study participants must also be justified. Ideally, the study should reflect the diversity present in the larger population as a whole. To be a representative sample, however, the sample size must be chosen correctly. A sample size that is too large can be impractical due to cost, resources, and time, but a sample size that is too small may not carry enough statistical power, meaning real differences cannot be determined. Almost all institutional review boards require a sample size justification to ensure as few subjects as possible are exposed to potential risk, but that the sample size is large enough to identify significant results (Sihoe, 2015). When looking at a COVID-19 studies, the quality has been shown to be hindered due to factors such as sample size and lack of variation in patient backgrounds, such as race (Lee, 2020).

These ethical issues of clinical studies (selecting representative samples, good sample sizes, control groups, and clinical equipment) are presenting themselves in COVID-19 studies.

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For example, it is known that the Black, Latinx, and Native American communities are dying from COVID-19 at higher rates than what is reported in the published datasets of COVID-19 articles (Chastain et al., 2020). Nonetheless, clinical trials such as that for the COVID-19 drug Remdesivir, which has been approved to treat severe COVID-19 cases, have few individuals from minority groups in their study. This means that the moderate benefits seen in the Remdesivir clinical trials may not be generalized to minority populations, who often have the most to gain from COVID-19 treatments. This issue of inadequate representation in clinical trials is not new or surprising. A sociological study published in July 2020 reveals the extent to which American society overlooks issues affecting BIPOC communities (Chastain, 2020). An article by the Harvard Business Review revealed that communities whose members were 86% Black encountered death rates nearly ten times those of predominantly white communities. These trends, coupled with similarly disturbing hospitalization and mortality rates, reveal systemic and unjust differences in access to living and working environments (Sivashanker et al., 2020). Also, despite much lower testing rates in BIPOC communities, the positivity rate is higher than their white counterparts (though it is also possible that socioeconomic level, which has a relationship to race, plays a role in likelihood of positivity). Even from the beginning of the pandemic in April, studies have found that Black people make up only 13% of the population but comprise 30% of COVID-19 cases. Since communities of color use public transportation, are employed in jobs that cannot transition as easily to telecommunications mediums like service industries, have larger families in public or low-income neighborhoods, and are underinsured, they continue to lag behind the rest of the nation in COVID-19 testing and treatment (Artiga et al., 2020). In addition to selected samples not representing the population, many Remdesivir clinical trials have been small and have lacked control groups (Ledford, 2020c).

"The ethical issues of clinical studies (selecting representative samples, good sample sizes, control groups, and clinical equipment) are presenting themselves in COVID-19 studies. For example, it is known that the Black, Latinx, and Native American communities are dying from COVID-19 at higher rates than what is reported in the published datasets of COVID-19 articles."

The antimalarial drug chloroquine is also causing issues with COVID-19 clinical trials. Early research showed chloroquine could reduce COVID-19 infection in human cells grown in the lab. This led to a clinical trial which suggested the drug could shorten disease duration. Since then, however, other studies have reported conflicting information. Nonetheless, highprofile politicians such as President Trump

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and the French President Emmanuel Macron have voiced their support for chloroquine, causing people around the world to believe it is a sufficient treatment for COVID-19 (Ledford, Source: the National Heart, Lung, 2020b). These messages have made COVID-19 and Blood Institute clinical trials difficult because some people do not want to participate in ones that require giving up their use of chloroquine. To combat this issue, some researchers are accepting participants that are already taking chloroquine or other drugs, which makes the data obtained from these studies unreliable.

Figure 3: Dr. Anthony S. Fauci, MD, the director of the National Institute of Allergy and Infectious Diseases (NIAID).

"Even with a good sample, studies can still be inaccurate due to data manipulation and false reporting by researchers.

P-hacking refers to an unethical scientific practice in which researchers stop their data collection once their data is statistically significant and may also involve the use of small sample sizes and the measurement of many different variables to obtain a significant correlation."

Even with a good sample, studies can still be inaccurate due to data manipulation and false reporting by researchers. P-hacking refers to an unethical scientific practice in which researchers stop their data collection once their data is statistically significant and may also involve the use of small sample sizes and the measurement of many different variables to obtain a significant correlation (Harrington et al., 2019). If these scientists can establish this correlation, top journals scouring for cutting-edge research may accept the article to inflate their impact factors.

However, it is extremely important that science gets facts right the first time around, without p-hacking.

On the front lines, top journals like the NEJM are working to combat forms of misinformation in statistics like p-hacking. NEJM released their new policies in July, 2019, to combat these issues and ensure that they publish empirically sound experiments (Harrington et al., 2019). Hopefully, new regulations regarding validation of data and statistics that journals such as NEJM and the Lancet recently put in place will catalyze a revolution in the scientific journaling community toward more transparent and statistically sound articles.

It is also important to point out the impact the pandemic has had on in-person research activities. While it is true that COVID-19 has reduced the costs of some research (conducting business over the Internet has become more commonplace), it has also intensified research challenges. The pandemic has resulted in a high volume of new studies, but many of these studies do not meet clinical trial standards; the FDA has also released a new set of standards specifically for studies being conducted during the pandemic, as protocol modifications have become inevitable with new challenges like “quarantines, site closures, travel limitations, interruptions to the supply chain for the investigational product (i.e. human drugs,

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biological products, medical devices),” or trial participants becoming infected with COVID-19 (FDA, 2020). Furthermore, securing research funding has become more difficult, as COVID-19 research has become the priority for research funding. This shift in priorities, in addition to misinformation from the quickly published COVID-19 studies that are often done without peer review, has resulted in a diversion of resources from promising research already in progress (Weiner et al., 2020). Remote research is definitely attractive in some fields, as it allows researchers to contact larger research samples and is in theory more efficient, but the redirection of resources and inaccessibility of in-person visits limits further research in many fields (Tuttle, 2020).

The Impact of Media and Politics on Science Research in Relation to COVID-19 When looking at the websites of the Centers for Disease Control (CDC), the FDA, and the White House (Coronavirus.gov), they all seem to be united in their messaging on COVID-19.

On Coronavirus.gov, if one clicks on the bolded headlines such as “How to prepare and protect yourself,” “What to do if you think you are sick,” and “Updates on cases of coronavirus in the U.S.,” the user is either sent to the CDC or FDA website. At the top of the FDA website, it states that it is an official website of the US government. Despite the united front that appears online, there seems to be a disconnect between some of the actions made by the U.S. administration and statements made by the CDC and FDA. For example, the CDC and FDA strongly encourage the use of masks to reduce the spread of COVID-19, however, it has taken

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President Trump months from the beginning of the pandemic to acknowledge the true effectiveness of masks (Victor et al., 2020).

Despite such clear and persistent warnings from the scientific community and top health officials as described previously, the US government chose to reopen America, citing economic prosperity as the primary motivation. To make matters more difficult for public safety, top administration officials not only refused to wear masks but also politicized them. President Trump has shown his personal disagreements and disdain towards some of these warnings and top health officials, even suggesting that he would fire Dr. Fauci if he got re-elected (Maxwell et al., 2020). In addition, the current presidential administration has pressured governmental health organizations to make premature decisions; the FDA prematurely granted emergency authorization of convalescent plasma for COVID-19 patients even though the organization had wanted to withhold authorization until after randomized controlled trials. This was a stepping stone towards enacting stricter measures for vaccine authorization in order to strengthen public trust, however, President Trump has stopped these regulations (Gonsalves & Yamey, 2020).

This administration has also pressured, censored, and undermined these government health agencies, as can be seen in the reduced number of CDC press events. It is also important to note that the wavering from governmental agencies has apparently come from “top down.”

In August, the CDC website added a message on their COVID-19 page that asymptomatic testing is not necessary, a contradiction of CDC suggestions, but one that was eventually retracted due to public backlash (Maxmen et al., 2020).

In addition, scientists of U.S. agencies have felt themselves being marginalized and unheard.

The Trump Administration’s 2020 COVID-19 response has led to several resignations from high-up health officials. For example, NIH scientist Rick Bright frustratingly resigned in October and was removed as director of the Biomedical Advanced Research and Development Authority, a position that finances drugs and treatments for disease outbreaks. Additionally, President Trump has clashed with Dr. Robert R. Redfield, the director of the CDC, over the timeline and effectiveness of a COVID-19 vaccine. Dr. Redfield has stated the vaccine will not be widely available until the middle of 2021, however, President Trump

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continually states that the vaccine will come much sooner (Trump Again Scorns Science on Masks and Vaccines, 2020). In addition, in September, the Trump administration again went against Redfield’s suggestions to extend a ban on cruise ship passengers, even though some of the first major COVID-19 outbreaks were from these ships (Maxmen et al., 2020).

Clearly, there have been varying levels of compliance of the Trump administration with experts’ guidelines on how to handle the pandemic. In an article from Frontiers in Public Health, co-authors Lavazza and Farina suggest that experts should present suggestions that correspond to the gravity of the public health threat, limited in what is necessary to achieve a public health standard, and be scientifically justified. While it is nearly impossible to convince every individual of the importance of pandemic guidelines due to varying social and cultural dynamics, the goal of such methods is to make the plan as appealing and understandable for the majority of people (Lavazza & Farina, 2020).

For some, it is easy to blame President Trump and his administration for the perils of the pandemic, for he had once falsely claimed that the virus would “vanish like a miracle” (Naughtie, 2020). While President Trump and his administration could have certainly managed the crisis better, COVID-19 did not become a pandemic at the hands of one man (Lincoln, 2020). In general, science does not take political sides. Its values very much lie in objectiveness, knowledge seeking, and evidence-based goals (Lavazza & Farina, 2020). For this reason, it was surprising to see Scientific American release their first-ever endorsement of a presidential candidate in October 2020. They endorsed former Vice President and now president-elect Joe Biden, citing current policymakers’ neglect of well-established scientific guidelines.

This article’s tone sharply diverges from the academic diction of prior scientific literature, employing superlatives to dilute the message and reach a wider audience. For example, when citing how masks “would close no business… [and] cost next to nothing,” the editors highlight how masking would both serve our current policy makers' short-term goals of economic prosperity while still respecting the guidelines set forth by the CDC (The Editors at Scientific American, 2020) .

"Despite the united front that appears online, there seems to be a disconnect between some of the actions made by the U.S. administration and statements made by the CDC and FDA."

In addition, because the pandemic occurred during the 2020 election year in the US, there was and still is great politicization of information

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related to the COVID-19 pandemic from media outlets. This has led to increased distrust and skepticism of media outlets that do not align with an individual’s political beliefs, causing a cycle of disbelief of opposing views that is then reinforced by particular media outlets that align with an individual’s views. (Strazewski, 2020). In fact, studies have shown that individuals who follow CNN news are likely to engage in an average of 3.85 preventative measures and only 0.94 risky measures, while those who follow Fox news are likely to practice an average of 3.41 preventative measures and 1.25 risky behaviors.

There is reason to believe that political beliefs and the politicization of health information by news media outlets have greatly impacted their behavioral changes and responses to the COVID-19 pandemic (Zhao et al., 2020).

"Because the pandemic occurred during the 2020 election year in the US, there was and still is great politicization of information related to the COVID-19 pandemic from media outlets. This has led to increased distrust and skepticism of media outlets that do not align with an individual’s political beliefs, causing a cycle of disbelief of opposing views that is then reinforced by particular media outlets that align with an individual’s views."

Data from the 2020 American election also suggests that a majority of the American public is responding positively to scientists’ calls for a government that acts in accordance with science.

The American public will likely feel a radical shift in the executive branch’s attitudes toward the pandemic. Already, President-Elect Joe Biden notes how “[i]f the public-health professionals, if Dr. [Anthony] Fauci, if doctors tell us we should take it [the vaccine], I would be first in line” (Ducharme & Park, 2020). The FDA, in regards to COVID-19 vaccine testing regulations, is also maintaining its requirements for pharmaceutical companies to collect two months of “follow-up data” after second doses during clinical trials for novel vaccines (Howard & Fox, 2020). Biden also promises the formation of a pandemic task force where the US may finally mount a nationwide response to the ever-increasing threat of COVID-19 (Fottrell, 2020). Biden pledges to make decisions based on science, and he and his team hope to increase US testing and contact tracing, address COVID-19 racial inequalities, and reinstate pandemic-readiness programs cut by the previous administration (Maxmen et al., 2020; Tollefson, 2020). He also hopes to reinvest time with the World Health Organization (WHO), an Organization President Trump withdrew funds from since the WHO supported China, the place where the first cases of COVID-19 were reported (Tollefson, 2020). This coordinated response and united front will hopefully enable America to acknowledge this public health threat and save thousands of lives.

However, this task will not come easily: the Biden administration will inherit an American public with great mistrust of U.S. agencies. Yet, the Biden-Harris administration brings hope in the

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continuation of science and research, as Biden also hopes to appoint a science advisor as soon as possible. Biden is also a great supporter of cancer research, due to his late son Beau’s battle with brain cancer (Maxmen et al., 2020).

There is also hope for increased international research collaborations. Biden hopes to reverse the restrictions and travel bans from the Trump administration that limit foreign scientists and students from working and studying in the US. Many, such as Marta Wosińska, the deputy director of Duke University’s Margolis Center for Health Policy, argue that international efforts and funding would be necessary to ensure sufficient supplies and collaboration (Maxmen et al., 2020). An example of this is Project COVAX, a project led by CEPI GAVI (a vaccine alliance) and the World Health Organization, is an example of international cooperation among governments, scientists, companies, philanthropic organizations, global health groups, and civil society, in order to develop and provide two billion vaccine doses by the end of 2021, regardless of countries’ or people’s income levels. This is in contrast to Operation Warp Speed, which prioritizes American receiving vaccines before other countries.

Furthermore, American news outlets have played a significant role in keeping communities connected and well-informed during the COVID-19 pandemic. Information traveled rapidly throughout a population, and this was particularly effective in raising awareness of COVID-19, as well as promoting CDC guidelines and hygiene practices, such as social distancing, wearing a mask, and hand washing. Furthermore, studies have shown that media outlets have contributed to maintaining the mental health and emotional stability of the public; news outlets and social media platforms raise awareness about mental health, provide tips on how to best emotionally process the pandemic, as well as provide information about relaxation techniques or physical exercise (Anwar et al., 2020).

At the same time, media outlets have also spread inaccurate information or rumors related to COVID-19. In the pursuit of publishing the breaking, most up-to-date stories on COVID-19, news outlets and other media platforms release information without fully verifying the information they are reporting (Natividad, 2020). For example, at the beginning of the pandemic in March, the media highlighted how the elderly population was most vulnerable to COVID-19. This led to the perception that

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Figure 4: Former Vice President and President-Elect Joe Biden speaking in 2019 during his 2020 presidential campaign. The Biden Administration vows to utilize its Pandemic Task force and it’s new science advisor on making decisions based on science during its time in office.

Source: Wikimedia Commons

COVID-19 was not an illness that the young population needed to be concerned about. This led to many young individuals travelling, going to crowded places, and enjoying their spring break without any regard for the pandemic.

However, in reality, this only resulted in the younger population being more vulnerable and exposed to the virus. In addition, by creating the perception that COVID-19 only affected the elderly, the elderly faced increased difficulties at the hands of society, as they were removed from group homes and cases of depression and emotional abuse among the elderly rose (Anwar et al., 2020).

Furthermore, media outlets are faced with the challenge of processing large quantities of information within a short period of time.

Senior medical correspondent for NBC and MSNBC news, John Torres, MD, noted that “the biggest challenge [for media outlets] has been the amount of information and how quickly that information is changing- and trying to get across that the information is preliminary,” (Strazewski, 2020). Again, people are fed inaccurate information, such as the idea that hydroxychloroquine would be the cure for COVID-19. In this instance, the media based their stories off of a small, non-randomized trial including only 36 people from France, and the spread of falsified information resulted in multiple deaths in the US and abroad, from the misuse or overdose of hydroxychloroquine.

Similar to the case of Ivermectin in Latin America, people scrambled to stock up on hydroxychloroquine following this spread of information, leading to a shortage of the

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drug for individuals who needed it to manage autoimmune illnesses (Anwar et al., 2020).

Given the universal impact of COVID-19, countries have varied in their approaches to the virus. Countries like Vietnam and Senegal were prompt in their responses and saw a decrease in deaths only months later. Vietnam encouraged hand-washing and implemented shutdowns of schools and other large gatherings, while Senegal declared a state of emergency and established a curfew 21 days after the first case was detected (Faye et al., 2020; Nguyen & Vu, 2020). The disparity in responses likely stems from a countries’ self-perception and the concept of “exceptionalism,” or the idea that a country is an outlier to other nations. The comprehensive Global Health Security (GHS) ranked the US as one of the best well-equipped countries to combat the virus before it arrived in the nation, and this in addition to the country’s exceptionalist attitude likely contributed to the overconfidence that resulted in one of the worst COVID-19 outcomes (Lincoln, 2020).

Vietnam and its leaders, on the other hand, never presumed that they were prepared for the outbreak, and consequently, took all measures to ensure that the virus would not escalate.

"Similar to the case of Ivermectin in Latin America, people scrambled to stock up on hydroxychloroquine following this spread of information, leading to a shortage of the drug for individuals who needed it to manage autoimmune illnesses."

The cultures of the countries also played a role in the responses of the governments and citizens to COVID-19. A characteristic of many Asian and African cultures is collectivism, where emphasis is placed on a group as a whole rather than individuals within the group, whereas Western culture is known for its individualistic

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nature. Japan, for example, did not evoke outrage or controversy when face masks were urged. This was likely due not only to the preexisting mask culture in Japan, but also its collectivist culture that emphasizes the wellbeing of the community over each person’s (Rich & Hayashi, 2020). The United Kingdom (UK), however, embodied the mantra of “keep calm and carry on,” even after observing the devastating COVID-19 wave in East Asia, as the UK’s Scientific Advisory Group for Emergencies (SAGE) rejected a nation-wide lockdown due to their belief that the British population would not accept it (Hunter, 2020; Scally et al., 2020).

This reflects the individualistic stance of the UK, as a mandatory quarantine would have, as some view it, infringed on the citizens’ civil liberties; the US also followed a similar sentiment through the pushback against the face covering mandate.

Conclusion: the future of scientific publishing "The cultures of the countries also played a role in the responses of the governments and citizens to COVID-19.

A characteristic of many Asian and African cultures is collectivism, where emphasis is placed on a group as a whole rather than individuals within the group, whereas Western culture is known for its individualistic nature."

As COVID-19 spreads across the world, one interesting aspect is its impact on scientific publications. There has been a massive increase in scientific publications during the pandemic, and some estimate 20,000 papers published since December 2019 (Harper et al., 2020). One article from the New York Times elaborated on the potential ramifications of such an unforeseen increase by noting how journals’ traditional peer-review processes are stretched to the limit in these conditions (Rabin, 2020). In this sense, the scientific journaling community will either begin recruiting more peer reviewers to permanently publish more often, or maintain their current publishing processes to maintain their exclusivity and hope this influx of publications is merely a temporary phenomenon. However, this rapid increase in both submissions and publications also poses excellent opportunities for young scientists. For example, 14-year-old 3M Young Scientist Winner, Anika Chebrolu, won $25,000 for computational chemistry simulations identifying a potential COVID-19 cure (Elassar, 2020). The scientific community is now moving at such a fast pace that fresh minds are being recruited more than ever in the fight against this global pandemic. However, the way in which this information is disseminated is critical, both now and in the future.

This is an ongoing conversation, especially given issues with retracted articles, high volumes of articles, an accelerated peer review process, and much more. Experts have varying opinions

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on what the future of scientific publications will hold in a post-pandemic world. While COVID-19 is indeed increasing openness in the sharing of scientific information, Callaway argues that structural changes, rather than COVID-19, will be the key to truly transforming the field.

This structural transformation would entail an incentivizing shift to open access publications.

Another potential pitfall is reverting the rapid review process because, while highly valuable and a (mostly) positive method, it may not be sustainable and efficient long term (Callaway, 2020). While COVID-19 certainly highlights issues in the scientific publishing industry, such as openness of information, the review process, funding, and more, the pandemic itself will not change scientific publishing on its own. If open access becomes one of the main platforms of scientific communication, a balance must be struck between potential lack of oversight and their danger of spreading misinformation, as seen frequently over the past months among media and politicians. Lastly, financial support for scientific information platforms will be critical in moving the scientific community towards these methods of publication, particularly at a time when journal subscriptions are significantly dropping (Dhar et al., 2020). Ultimately, shifting scientific publication towards an open and reliable method of sharing scientific information has been catalyzed by COVID-19, but this shift will not be complete once the pandemic is over.

Trial and error, funding, and pressure from scientists, journalists, and the public will be the factors that drive this shift. The future of scientific publishing is promising, particularly at a time when citizens are more engaged in science than they ever have been, and it will remain to be seen where and how the scientific community will shift.

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org/10.1038/530148a Questions and Answers about Ivermectin and COVID-19— Blog. (n.d.). ISGlobal. Retrieved November 24, 2020, from https://www.isglobal.org/en/healthisglobal/-/custom-blogportlet/questions-and-answers-about-ivermectin-andcovid-19/2877257/0 Research, C. for D. E. and. (2020, September 21). FDA Guidance on Conduct of Clinical Trials of Medical Products during COVID-19 Public Health Emergency. U.S. Food and Drug Administration; FDA. https://www.fda.gov/regulatoryinformation/search-fda-guidance-documents/fda-guidanceconduct-clinical-trials-medical-products-during-covid-19public-health-emergency Resnick, B. (2019, June 3). The war to free science. Vox. https:// www.vox.com/the-highlight/2019/6/3/18271538/openaccess-elsevier-california-sci-hub-academic-paywalls Rich, M., & Hayashi, N. (2020, June 6). Is the Secret to Japan’s Virus Success Right in Front of Its Face? The New York Times. https://www.nytimes.com/2020/06/06/world/asia/japancoronavirus-masks.html Samantha Artiga, Rachel Garfield, and Kendal Orgera. (2020, April 7). Communities of Color at Higher Risk for Health and Economic Challenges due to COVID-19. KFF. https://www.kff. org/coronavirus-covid-19/issue-brief/communities-of-colorat-higher-risk-for-health-and-economic-challenges-due-tocovid-19/

Taylor, D. B. (2020, August 6). A Timeline of the Coronavirus Pandemic. The New York Times. https://www.nytimes.com/ article/coronavirus-timeline.html Tennant, J. P., Waldner, F., Jacques, D. C., Masuzzo, P., Collister, L. B., & Hartgerink, Chris. H. J. (2016). The academic, economic and societal impacts of Open Access: An evidence-based review. F1000Research, 5. https://doi.org/10.12688/ f1000research.8460.3 The Editors of Scientific American. (2020). Scientific American Endorses Joe Biden. Scientific American. https://doi. org/10.1038/scientificamerican1020-12 The Mess That Is Science Publishing. (2020, January 24). The James G. Martin Center for Academic Renewal. https://www. jamesgmartin.center/2020/01/the-mess-that-is-sciencepublishing/ Tollefson, J. (2020). Scientists relieved as Joe Biden wins tight US presidential election. Nature, 587(7833), 183–184. https:// doi.org/10.1038/d41586-020-03158-8 Trump Again Scorns Science on Masks and Vaccines. (2020, September 16). The New York Times. https://www.nytimes. com/2020/09/16/world/covid-coronavirus.html Tuttle, K. R. (2020). Impact of the COVID-19 pandemic on clinical research. Nature Reviews Nephrology, 16(10), 562–564. https://doi.org/10.1038/s41581-020-00336-9

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Sihoe, A. D. L. (2015). Rationales for an accurate sample size evaluation. Journal of Thoracic Disease, 7(11), E531–E536. https://doi.org/10.3978/j.issn.2072-1439.2015.10.33 Sivashanker, K., Duong, T., Ford, S., Clark, C., & Eappen, S. (2020, July 21). A Data-Driven Approach to Addressing Racial Disparities in Health Care Outcomes. Harvard Business Review. https://hbr.org/2020/07/a-data-driven-approach-toaddressing-racial-disparities-in-health-care-outcomes Spier, R. (2002). The history of the peer-review process. Trends in Biotechnology, 20(8), 357–358. https://doi.org/10.1016/ S0167-7799(02)01985-6 Strazewski, L. (2020, September 16). How news media is filling public health role during COVID-19. American Medical Association. https://www.ama-assn.org/delivering-care/ public-health/how-news-media-filling-public-health-roleduring-covid-19 Study: Hydroxychloroquine doesn’t prevent Covid-19 infection if exposed. (2020, June 3). STAT. https://www. statnews.com/2020/06/03/hydroxychloroquine-does-notprevent-covid-19-infection-in-people-who-have-beenexposed-study-says/ Swoger, B. (n.d.). The (mostly true) origins of the scientific journal. Scientific American Blog Network. Retrieved October 5, 2020, from https://blogs.scientificamerican.com/ information-culture/the-mostly-true-origins-of-the-scientificjournal/

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Viglione, G. (2020). Four ways Trump has meddled in pandemic science—And why it matters. Nature. https://doi. org/10.1038/d41586-020-03035-4 Weiner, D. L., Balasubramaniam, V., Shah, S. I., & Javier, J. R. (2020). COVID-19 impact on research, lessons learned from COVID-19 research, implications for pediatric research.

Pediatric Research, 88(2), 148–150. https://doi.org/10.1038/ s41390-020-1006-3 World Health Organization. (n.d.). WHO discontinues hydroxychloroquine and lopinavir/ritonavir treatment arms for COVID-19. Retrieved October 11, 2020, from https://www. who.int/news-room/detail/04-07-2020-who-discontinueshydroxychloroquine-and-lopinavir-ritonavir-treatment-armsfor-covid-19 World Health Organization. (2020). Coronavirus. World Health Organization. https://www.who.int/health-topics/ coronavirus#tab=tab_1 Wu, Y.-C., Chen, C.-S., & Chan, Y.-J. (2020). The outbreak of COVID-19: An overview. Journal of the Chinese Medical Association, 83(3), 217–220. https://doi.org/10.1097/ JCMA.0000000000000270 Zhao, E., Wu, Q., Crimmins, E. M., & Ailshire, J. A. (2020).

Media trust and infection mitigating behaviours during the COVID-19 pandemic in the USA. BMJ GLOBAL HEALTH. https://gh.bmj.com/content/5/10/e003323.info

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Cancer and its Treatments STAFF WRITERS: SOPHIA KOVAL, WILSON MURANE, ANDREW SASSER, OWEN SEINER, JILLIAN TROTH, JULIETTE COURTINE, BAMLAK MESSAY, AMANDA JIANG, CAROLINA GUERRERO, ANAHITA KODALI, GEORGE SHAN, ADVAITA CHAUDHARI, SAM HEDLEY, MAEEN ARSLAN, VARUN LINGADAL, MICHAEL DEL SESTO EDITORIAL BOARD WRITER: NISHI JAIN

Cover Image: Proliferating breast cancer cells Source: Wikimedia Commons

Introduction Cancer is one of the most prolific killers of the modern world. It originates within the body’s own cells and ravages the landscape of tissue, bone, and muscle, proliferating until met with an equal and opposite force. Oftentimes, the body’s own immune response is insufficient to be the reactionary force to the cancer, necessitating the use of external treatment to oppose the army of proliferating cells. It is the development of this reactionary external treatment that has demanded billions of dollars of investment from the private and public sectors and thousands of hours of in vitro and in vivo testing – and it is also the topic of this paper.

To date, researchers have identified over one hundred types of cancer. Theses cancers have the ability to originate anywhere and spread to nearly every tissue in the body, but there are only a few that actually recur. In fact, the

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top ten cancers comprise recurring cancers and account for about 75% of all cancer cases (Cooper, 2000). Additionally, the distribution of cancer types for both men and women vary, but the most lethal cancer for both in the US is lung and bronchial cancer. In 2019, lung and bronchial cancer accounted for about 24% of all cancer related deaths in men and about 23% of deaths for women. Other common cancers for men include colorectal cancer, bladder cancer, and melanoma; for women, common cancers include breast, colorectal, and uterine cancer (American Cancer Society, 2019).

Though every cancer has its own specific biological and biochemical pathways, cancer is generally characterized by uncontrollable cell growth and the inactivation of cellular death mechanisms. Cancer occurs when a cell breaks out of the traditional proliferation pattern and divides uncontrollably. Clumps of these abnormal cells are referred to as DARTMOUTH UNDERGRADUATE JOURNAL OF SCIENCE

Figure 1: Cancer is characterized by abnormal endogenous cells that proliferate uncontrollably Source: Wikimedia Commons

tumors (Sarkar et al., 2013). There are two major categories of genes that are implicated in the abnormal proliferation of cancer cells: proto-oncogenes and tumor suppressor genes.

Proto-oncogenes contain the genetic code for proteins that regulate growth pathways in cells; the signaling pathways are triggered by the production of growth proteins, which cause a cascade of cellular events that ends in cell nuclei receiving division-promoting messages and activating genes to move the cell through the division cycle. When proto-oncogenes mutate into oncogenes, proteins involved in these pathways become overactive, resulting in rapid cell division and proliferation. Tumor suppressor genes are those that typically counterbalance growth pathways. When these genes malfunction, their associated inhibitory pathways stop functioning, allowing the cell to grow unchecked (National Institutes of Health (US), 2007).

The signs and symptoms for cancer vary greatly depending on the type. However, there are a few general symptoms, including unexplained fatigue, which can be coupled with joint and muscle soreness, and lumps or “thickness” under the skin (Mayo Clinic Staff, 2018). Additionally, unplanned fluctuations in weight (typically weight loss, but can be weight gain as well), indigestion after eating, or headaches that do not respond to medication nor fade with time, all can also be symptoms of various cancers. If a patient experiences recurring night sweats, unexplained bleeding and bruising, or frequent fevers (indicative of a compromised immune system), then these may also be symptoms of cancer and necessitate an appointment with an FALL 2020

oncologist or other specialist (Mayo Clinic Staff, 2018).

There are also particular symptoms more strongly associated with certain types of cancer. One of the most common and easily observable symptoms of skin cancer include visible changes to the skin, such as the appearance of new moles or color changes.

A simple acronym to help categorize these changes to the skin is: ABCDE. The mole should be examined for Asymmetric borders, Borders that change, unnatural or fluctuating Color, a Diameter that is larger than that of a pencil eraser, and for any Evolution such as the onset of bleeding (UCSF Health, 2020).

Sores in the mouth and difficulty swallowing for more than 2 weeks can be signs of oral cancer. Cancers of the prostate, cervix, uterus, or ovaries are associated with changes in bladder or bowel habits, including constipation or diarrhea, black or red coloring of stool, more frequent urination, blood in the urine, and changes to a woman’s menstrual cycle or pelvic pain (UCSF Health, 2020). A persistent cough (especially a dry cough lasting longer than 2 weeks) or trouble breathing can also signify the onset of of lung cancer (Mayo Clinic Staff, 2018).

Tumorous cells can spread throughout the body in a stage that is known as metastasis.

Essentially, this is when a piece of the cancer breaks off from the main tumor and spreads to other parts of the body through the bloodstream or lymphatic system. The cancer travels through the system to a small blood vessel through which it can spread to the surrounding tissue, at which point a new

"The signs and symptoms for cancer vary greatly depending on the type. However, there are a few general symptoms, including unexplained fatigue, which can be coupled with joint and muscle soreness, and lumps or “thickness” under the skin."

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Figure 2: MRI scans are a common clinical technique for diagnosing cancers Source: Wikimedia Commons

"Cancers are traditionally diagnosed through a standardized procedure. Physicians begin by asking the patient about their family history, as family history of cancer traditionally means that there is an increased susceptibility to the illness for genetic reasons."

tumor form (National Cancer Institute, 2017).

The type of cancer, the rate of its growth, and a few behavioral factors indicate how likely the cancer is to metastasize (ASCO, 2019). There are cancer types more strongly associated with certain sites of metastasis, such as breast cancer being more likely to travel to the bone, lungs, brain and liver (National Cancer Institute, 2017).

However, regardless of the fact that the cancer has spread to a new location, it is still treated in a similar way. For example, breast cancer that has spread to the lungs is still treated as metastatic breast cancer, not as lung cancer (National Cancer Institute, 2017). Metastatic cancers can also have specific associated symptoms, such as headaches and unsteadiness Patients with cancer that had spread to the brain often report seizures (National Cancer Institute, 2017). Both non-spreading and metastatic cancers can manifest in distinct ways, individual to both the exact type and make-up of the tumor, and the patient themself.

Cancers are traditionally diagnosed through a standardized procedure. Physicians begin by asking the patient about their family history, as family history of cancer traditionally means that there is an increased susceptibility to the illness for genetic reasons (National Cancer Institute, 2017). After a review of family history, the physician conducts a thorough physical exam, noting the occurrence of symptoms discussed in the previous paragraphs. The doctor may also order certain lab tests and/or conduct a biopsy of the afflicted area (National Cancer Institute

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2019). Lab tests include the testing of blood, urine, stool, and tissue samples to determine if there are increased hormonal levels or other tumor markers, chemicals that are overproduced by cancer cells. Tumor markers may include genetic mutations that lead to the overproduction certain proteins or the creation of oncogenic fusion genes.

After lab tests, the physician may order certain imaging tests such as a CT scan, an MRI, a nuclear scan, a bone scan, a PET scan, an ultrasound, or an X-Ray. While a CT scan uses x-ray waves from multiple angles to create a 3-D view of organs, MRI uses a powerful magnet to take images of the body in 2D slices which are then compiled to create a whole image.

(National Cancer Institute, 2017). A nuclear scan, often called a radionuclide scan, uses an external imaging device to follow the path of a radioactive material called a tracer through the body. A bone scan is a type of nuclear scan that has the tracer injected into the skin such that the tracer travels through the bloodstream and accumulates in abnormal areas in the bone, only to be picked up by a similar external imaging device as the traditional nuclear scan.

A PET scan is another kind of nuclear scan that uses a glucose radiotracer, allowing for accurate imaging of parts of the body that take up glucose; because cancer cells take up more glucose than traditional healthy cells, cancer can be detected by noting the accumulation of glucose in certain areas of the body (National Cancer Institute, 2019). Ultrasound

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imaging uses high-energy sound waves to permeate the body echo off of certain tissues.

The echoed sound waves are then detected by a computer and used to reconstruct the tissue and organ systems and allow doctors to identify irregularities – something that is especially helpful when detecting the presence of an especially globular tumor mass. Finally, x-rays are used traditionally to identify bone abnormalities, indicative of bone cancer (which are then followed up by other means of imaging) (National Cancer Institute, 2019).

opinions and peer reviews of cancer biopsies.

These technologies improve the accuracy and lessen the time of diagnosis. However, the study warns, “in addition to demonstrating the potential benefits associated with good quality AI in the hands of non-expert clinicians, we find that faulty AI can mislead the entire spectrum of clinicians, including experts” (Tschandl, 2020). Incorrect computational opinions can muddle the proper diagnosis of cancer.

Needle biopsies are usually the final definitive test to determine whether or not an abnormality or mass that is visualized in previous testing or imaging is in fact cancerous, and if so, if the cancer is malignant (prone to growth and deadly) or benign (not prone to growth and more or less harmless). Biopsies can be performed using a needle (for instance, if bone marrow has to be tested), by endoscopy (abnormal tissue is removed), and by surgery (if the abnormality is not easily accessible via needle or endoscopy) (National Cancer Institute, 2017).

Carcinoma, one kind of cancer that occurs in the skin or the tissues that line organs, is a direct result of an abnormal division of cells, much like other cancers. Aside from epithelial skin cells, carcinomas can impact different organs such as the lungs, colon, stomach, prostate, and thyroid gland. There are many different types, the most common of which are basal cell carcinoma, squamous cell carcinoma, renal cell carcinoma, and ductal carcinoma in situ. Both basal cell carcinoma and squamous cell carcinoma are found in the skin, but squamous cell carcinomas can also affect the cells lining the digestive tract or the respiratory tract. Renal cell carcinoma is the most common form of cancer affecting kidney cells, and ductal carcinoma in situ impacts the milk ducts of the breasts. Ductal carcinoma in situ can become invasive when the cancerous cells spread through the ducts and metastasize to breast tissue or other parts of the body.

The most common forms of treatment for carcinomas include surgery, radiation therapy and chemotherapy (ACS, 2020).

While many cutting-edge clinical techniques have emerged to diagnose cancer, artificial intelligence has also come to aid in the diagnosis of cancer. The KIMIA Lab at the University of Waterloo has developed software that compares sample images from biopsies to over 30,000 digital images of 32 cancers found within 25 organs. This lab utilizes the whole-slide image (WSI) technique in which a microscope is used to create a high-resolution image of a slide of cancer cells, then a barcode-like summary of each image is generated to make searching and storage of data more efficient (Kalara, 2020). Similarly, the University of Queensland created an AI model for skin cancer employing the multiclass probabilities technique. Similar to KIMIA’s barcode-like method, the University of Queensland’s AI technique uses pairwise coupling in which a sample is compared against a calibration plot which summarizes probabilities or scores of pre-diagnosed cases (Tschandl, 2020). The Queensland study highlights both the benefits and dangers of AI diagnosis. The study concluded that, “we find that good quality AI-based support of clinical decision-making improves diagnostic accuracy over that of either AI or physicians alone, and that the least experienced clinicians gain the most from AI-based support” (Tschandl, 2020). Developing AI techniques may one day be used to negate the need for second

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Types of Cancer "Basal and squamous cell skin cancers are the most common cancers, with about 5.4 million new diagnoses each year in the U.S. alone."

Basal and squamous cell skin cancers are the most common cancers, with about 5.4 million new diagnoses each year in the U.S. alone (ACS, 2020). Within these two cancer types, about 80% of skin cancers are basal cell carcinomas and the other 20% squamous cell carcinomas (ACS, 2020). Although squamous cell carcinomas are less common, the number of reported cases has been steadily increasing in the U.S. over the years, with a 200% jump in incidence rate over the past three decades (Skin Cancer Foundation, 2020). Although the number of basal cell and squamous cell carcinomas are high, the death rate is low, with around 2,000 mortalities per year in the United States. Basal cell carcinomas get their name from the location of tumorigenesis – in the lower layers of the skin, known as the basal cell layer. Normally, these basal cells migrate upwards toward the top of the skin

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Figure 3: Cytology is a common technique to help identify characteristics of squamous cell carcinomas Source: Wikimedia Commons

and replenish the squamous cells that naturally die and are shed. When these basal cells become cancerous, however, this migration process leads to squamous cell carcinoma.

As with other forms of skin cancer, a major risk factor that often promotes oncogenesis is sun exposure. Ultraviolet radiation from the sun causes mutations in the DNA of basal cells as well as squamous cells, resulting in abnormal cell development and uncontrolled growth.

Treatments for basal cell carcinoma compared to squamous cell carcinoma vary slightly; since basal cell carcinoma has a low metastatic potential, treatment is focused on local control â&#x20AC;&#x201C; emphasizing surgical excision or a technique known as Mohs Micrographic Surgery. If surgery is not an option, radiation therapy can be very effective for smaller tumors (Kim et al., 2019).

On the other hand, treatment for squamous cell carcinomas is somewhat different if the tumor is found to be metastatic. If the primary tumor has invaded other areas, an excision of the lymph nodes is recommended to prevent additional metastasis. Chemoradiation is also a common option for metastatic squamous cell carcinoma to help destroy current tumors and prevent additional growth (Waldman et al., 2019).

Interestingly, although the direct mechanism is still unknown, human papillomavirus infections have also been found to be correlated with (and a possible precursor to) squamous cell carcinoma (Alam and Ratner, 2001).

"Sarcoma is another type of cancer that causes tumors in connective tissue, including bone, muscles, fat, nerves, and other tissues. The two primary subtypes of sarcomas are bone sarcomas, also known as bone cancer, and soft-tissue sarcomas (STS)."

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Renal cell carcinomas, which arise from the epithelial tissue of the kidneys and make up 85% of all renal cancers, have risen in prevalence since the 1990s, although the death rate has remained stable (Cohen and McGovern, 2005; ACS, 2020).

Improved accessibility to imaging tests (e.g., CT scans) have helped catch cases earlier, likely accounting for the simultaneous stable death rate and rise in incidence. Treatment of renal cell carcinoma mainly involves surgical excision, which includes removing the kidney, the adrenal gland, and sometimes even the regional lymph nodes. If the primary tumor is metastatic, a combination of Interferon Alfa-2B medication with kidney removal surgery has been found to be effective. Surprisingly, the efficacy of chemotherapy alone for metastatic cases is low due to the development of drug resistance. Drug resistance is common in cancer treatment due to the fact that tumors are heterogeneous in nature (made up of cell types with different genetic profiles). Drug therapies often target the supply of chemicals or cell signals that tumors require the most to survive, but not all cells require

these chemicals or signals. When cancer cells start dying as a result of the limitation of these chemicals or cell signals, the cells with the least dependence may survive and multiply.

Scientists have worked to develop drugs that are effective in the long-term against potential resistance; in the case of renal cell carcinoma, immunomodulatory therapies such as highdose interleukin-2 treatment have been developed that are highly effective (Cohen and McGovern, 2005).

Ductal carcinoma in situ incidence rates have remained fairly stable for a decade and patients typically have an excellent prognosis (Fu et al., 2018). If the abnormal cancer cells have not yet infiltrated the ductal lymph node system, the chances of survival are high and treatment options are very effective. In particular, adjuvant (post-surgery) whole breast radiation therapy is recommended which helps to reduce the risk of local recurrence. The long-term prognosis of ductal carcinoma in situ is excellent, with mortality rates at 10 years being less than 5%, significantly lower than any other type of carcinoma (Fu et al., 2018).

Overall, the treatment methods for these different types of carcinomas are fairly well developed and can result in complete removal of the primary tumor. As with all cancer cases, once the primary tumor becomes metastatic, it gets harder to treat, but being able to access screening tests regularly helps improve patient outcomes Sarcoma is another type of cancer that causes tumors in connective tissue, including bone, muscles, fat, nerves, and other tissues. The two primary subtypes of sarcomas are bone sarcomas, also known as bone cancer, and soft-tissue sarcomas (STS). Bone sarcoma starts in the bones while STS starts in tissues

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Figure 4: Sarcomas are tumors that are common in connective and soft tissue Source: Wikimedia Commons)

such as muscle, fat, blood vessels, nerves, and lymph vessels. While scientists are still not sure what exactly causes sarcomas, they know that mutated DNA, their root cause, is most likely to emerge during one's lifetime rather than being inherited (“What Causes Soft Tissue Sarcomas?”, 2018). That being said, inherited syndromes, radiation therapy for other cancers, intense swelling, exposure to chemicals, and subjection to viruses have been implicated as risk factors (“Symptoms and causes”, n.d.). At first, STS can cause painless lumps to form on the limbs or torso, but pain can arise if the swelling reaches a nerve. Symptoms are also dependent on location; for example, sarcoma in the heart can cause chest pain and difficulty breathing.

Sarcoma of the bone can cause pain that comes and goes, worsening with movement, and possibly cause swelling to the surrounding tissue as well. If the tumor is near or on a joint, it can cause swelling and stiffness that limits mobility.

Sarcomas are commonly discovered by the patient when they recognize the appearance of a lump, by a physician investigating symptoms, or by a surgeon performing an unrelated surgery. After a specialist has reason to investigate symptoms, they will examine the lump, perform a biopsy to test tissue samples, and scan the area. When treating low-grade tumors, a simple surgery can remove the tumor with large margins, meaning that surrounding FALL 2020

healthy tissue will also be resected to ensure the cancer will not spread. For high-grade tumors, a combination of treatments is used, including surgery, systematic therapy, and radiation therapy. Despite these efforts, of the 13,130 people diagnosed with STS in the United States this year, 5,350 will die (“Sarcoma, Soft Tissue”, 2014). Out of the 3,600 diagnosed with bone sarcoma this year, 1,720 will die (“Bone Cancer'', 2014).

Bone cancers are another devastating cancer, although it has lower incidence relative to other cancers. It can be traced back to cells that differentiate into different types of body cells from precursor cells or stem cells. There is a type of precursor cell specific to immune cells called hematopoietic stem cells, which reside in the bone marrow. Leukemia is caused by the uncontrollable proliferation of hematopoietic stem cells. In 2020, leukemia made up about 3.4% of cancers in the US, making it the tenth most common cancer in the country; approximately one in 70 people will get leukemia in their lifetime (NIH, 2020; Davis et al., 2014). The four most common types of leukemia are acute lymphoblastic, acute myelogenous, chronic lymphocytic, and chronic myelogenous leukemia.

"Sarcomas are commonly discovered by the patient when they recognize the appearance of a lump, by a physician investigating symptoms, or by a surgeon performing an unrelated surgery.

After a specialist has reason to investigate symptoms, they will examine the lump, perform a biopsy to test tissue samples, and scan the area."

Both types of acute leukemia (acute lymphoblastic and acute myelogenous leukemia) are diagnosed when a bone marrow 177

biopsy reveals an abnormally high number of blast cells, which are the earliest form of hematopoietic stem cells. Typically, acute myelogenous leukemia is identified when small structures called Auer rods are found in immune cells. Acute lymphoblastic leukemia typically occurs in children, while acute myelogenous leukemia is typically found in adults. Common treatments for acute leukemia include chemotherapy, radiation, antibody therapies, and bone marrow transplant (Davis et al., 2014). Chronic leukemias may or may not cause symptoms in patients before they are diagnosed. Sometimes these leukemias are diagnosed when a blood draw ordered for another issue reveals high levels of lymphocytes.

Chronic leukemias are found almost exclusively in adults. Chronic lymphocytic leukemia is characterized by a high lymphocyte count in peripheral blood, while chronic myelogenous leukemia is characterized by the presence of the Philadelphia chromosome, which is the shortening of the 22nd chromosome due to a translocation between the 9th and 22nd chromosomes. Some chronic leukemias do not need to be treated, while others can be treated using tyrosine kinase inhibitors (Davis et al., 2014).

"Any leukemia treatment that causes widespread cell death has the potential to cause tumor lysis syndrome. When cells lyse, they release their intracellular content into the bloodstream, which can lead to abnormally high levels of potassium, phosphorus, and uric acid in the blood."

Any leukemia treatment that causes widespread cell death has the potential to cause tumor lysis syndrome. When cells lyse, they release their intracellular content into the bloodstream, which can lead to abnormally high levels of potassium, phosphorus, and uric acid in the blood. To prevent renal failure in response to tumor lysis syndrome, patients are administered IV fluids and given drugs to facilitate uric acid breakdown. Many leukemia treatments also suppress the immune system, making patients vulnerable to infection (Davis et al., 2014). Leukemia survivors are more likely to develop other cancers and may also develop joint, bone, heart, and endocrine problems.

Long-term effects of disease vary by leukemia and treatment type (Davis et al., 2014).

Another cancer subtype in addition to carcinomas and sarcomas are lymphomas.

Malignant lymphomas refer to a range of cancers caused by the clonal proliferation of lymphocytes. Lymphomas can be broadly divided into non-Hodgkin and Hodgkin types (approximately 90 percent of the cases are of the non-Hodgkin type). Further, non-Hodgkin lymphomas are differentiated (in the WHO classification) by the cell of origin: B cell, T cell, or natural killer (NK) cell. In 2020, an estimated 77,240 people will be diagnosed with nonHodgkin lymphoma, constituting 4.3% of all

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the new cancer cases, and there will be a total of 19,940 deaths due to this cancer (NIH, 2020).

Lymphomagenesis is thought to be a multistep process in which cumulative genetic alterations throughout the different stages of cell maturation cause the autonomous growth of lymphoid cells (Müller‐Hermelink et al., 2001). In this process, lymphocytes escape regulatory control so that they become independent of the body’s anti-growth signals and grow uncontrollably. For example, follicular lymphoma, a subtype of mature B cell lymphoma, induces the (14;18) (q32;q21) translocation of BCL2 gene on chromosome 14q32, placing it under the control of immunoglobulin heavy chain (IGN) enhancer element. This misplacement causes the expression of BCL2 to be upregulated, which in turn inhibits the normal program of apoptotic cell death (Armitage et al., 2017).

The diagnosis and management of nonHodgkin lymphoma highly depends on the specific subtype because it can involve any organ in the body. A wide range of clinical presentations are possible, which might mimic many other conditions. Therefore, an adequate biopsy is necessary for a proper diagnosis.

Diffuse large B-cell lymphoma (DLBCL) is the most common non-Hodgkin lymphoma, and its most typical clinical presentation is the enlarging nodal mass, located either in the central or peripheral region (Matasar & Zelenetz, 2008). DLBCL in its early stages is curable, so patients can be treated with chemotherapy to maintain a long-term diseasefree status. Promising outcomes have seen with early-stage patients on a range of therapies from rituximab to CHOP (a combination of several chemotherapeutic agents: cyclophosphamide, doxorubicin hydrochloride (hydroxydaunorubicin), vincristine sulfate (Oncovin), and prednisone), merely after about six cycles of this chemotherapy treatment (National Cancer Institute, 2019).

Cancer Treatments on a Cellular Level Immuno-oncology is a relatively new field of cancer treatment, first gaining momentum in 2011 and developing further since due to a growing understanding of cancer’s evasion of immunosurveillance and use of chronic inflammation to support tumor growth (Finn, 2012). Much of today’s immuno-oncology research is based on the three-stage cancer immunoediting model, which describes tumorigenesis as the result of cancer cells DARTMOUTH UNDERGRADUATE JOURNAL OF SCIENCE

Figure 5: Trastuzumab is a common antibody used to treat HER2+ metastatic breast cancer Source: Wikimedia Commons

escaping the elimination and equilibrium stages, and the fittest cells eventually reaching malignancy (Martins, n.d.). In line with this model, cancer immunotherapies work on two fronts: correcting the mechanisms by which tumor cells evade cancer immunosurveillance and enhancing the immune response against the cancer (Martins, n.d.).

Immunotherapies are traditionally categorized into active and passive treatments, where the former consists of modifying host immune cells to recognize the tumor cells, and the latter entails introducing antibodies and/or cytokines to stimulate the immune response (Martins, n.d.; Finn, 2012). Despite this, scientists are recognizing that even under “passive” treatments, the activation of the immune system is essential and far from guaranteed; thus, all immunotherapies are, in a sense, “active” (Finn, 2012).

Active immunotherapies can be further categorized into cell-based and vectorbased therapies. Cell-based therapies involve harvesting patient immune cells (usually dendritic cells) and engineering them to recognize the patient’s cancer by culturing them in a lab with tumor-specific antigens and adjuvants. They are then reintroduced into the patient to target cancer cells for cell death (Martins, n.d.). On the other hand, vector-based therapies, such as Provenge (Sipuleucel-T) for metastatic prostate cancer, introduce the harvested dendritic cells to tumor proteins FALL 2020

via a viral vector, encouraging the dendrites to raise antibodies against the cancer cells (Martins, n.d.). Finally, cancer vaccines also fall under the banner of active immunotherapy.

These vaccines introduce small amounts of immunosuppressive molecules to the blood and lymphatic vessels (Finn, 2012).

Passive immunotherapies include the introduction of monoclonal antibodies or cytokines to the immune system (Martins, n.d.; Finn, 2012). Monoclonal antibody therapies, such as Avastin, Rituxan, and Trastuzumab, are typically some combination of mouse and human antibodies raised in vitro against tumor-specific antigens. They are selected for therapeutic use by assaying for the desired antibody response in cultured plasma cells equipped with the engineered antibody (Martins, n.d.). Once in vivo, these antibodies expedite tumor cell apoptosis. In Antibody Dependent Cell-Mediated Cytotoxicity (ADCC), the antibody binds immune cells to cancer cells to coordinate cell death; similarly, complement system mediated cell killing binds tumor cells to a complement pathway to form the Membrane Attack Complex (MAC), ultimately leading to cancer cell apoptosis (Martins, n.d.). Additionally, monoclonal antibodies can function as antagonists to the cancer cells by binding to key receptors and blocking lifesustaining pathways (Martins, n.d.). Cytokinebased therapies harness cell signaling to stimulate the immune system, often through the introduction of interleukins or interferons,

"Immunotherapies are traditionally categorized into active and passive treatments, where the former consists of modifying host immune cells to recognize the tumor cells, and the latter entails introducing antibodies and/or cytokines to stimulate the immune response."

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Figure 6: Mutations in cyclins and other regulatory proteins are common causes of tumorigenesis Source: Wikimedia Commons

which magnify the immune response by recruiting T-cells and lead to more interleukin production and overall immune cell activity (Martins, n.d.).

"As a diverse and relatively new cancer treatment approach, immuno-oncology has seen 233% growth in its drug pipelines between 2017 and 2020."

As a diverse and relatively new cancer treatment approach, immuno-oncology has seen 233% growth in its drug pipelines between 2017 and 2020 (Upadhaya & Yu, 2020).

As of 2020, the most common treatments in development are cell therapies, T-cell targeted immunomodulators, and cancer vaccines; the most common targets are CD-19 (a B-cell antigen) and TAAs (tumor-associated antigens) (Upadhaya & Yu, 2020). CD-19 therapies in particular have grown markedly in recent years, expanding from 90 active agents in 2017 to 245 active agents as of 2020 (Upadhaya & Yu, 2020).

Because the self-/non-self-distinction is essential to cancer treatment, immunotherapy must be tailored to the individual, making it a highly specific, non-toxic, and incredibly delicate alternative (Martins, n.d.). The field of immuno-oncology faces the challenge of striking the right balance between underand over-activation of the immune system so that it attacks the cancer, not the patient.

The most frequent obstacle is bringing the immune response to action as cancer cells tend to recruit immunosuppressive T-cells

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and myeloid-derived suppressor cells to block the immune cells and pathways that are inhibitory to tumor growth (Finn, 2012).

However, researchers are currently addressing this issue by experimenting with combinations of immunotherapies enhanced with cytokines and adjuvants (Finn, 2012).

In general, immuno-oncological therapies also face a low cure rate as they are frequently used too late in the course of cancer development; perhaps by better understanding the processes of immunosurveillance and tumorigenesis, scientists can take a preventative immunooncological approach and introduce these therapies earlier in the progression of cancer (Finn, 2012).

Many traditional cancer therapies, such as chemotherapy and radiation therapy, lack specificity for their target, causing damage to healthy cells and consequently, harsh side effects (Lavanya et al., 2014). As such, drug developers are conducting research into targeted therapy approaches, including small molecule agents and monoclonal antibodies (Lavanya et al., 2014). The goal of such therapies is to selectively target cancerous cells while mitigating the effects on healthy cells. Oncogenesis and the further progression of cancer rely on abnormalities within cellular DARTMOUTH UNDERGRADUATE JOURNAL OF SCIENCE

signaling pathways. As such, many small molecule inhibitors are designed to bind to extracellular receptors and intracellular proteins that play key roles in activating downstream signaling for these pathways (Lavanya et al., 2014). Small molecule cancer drugs typically have molecular weights under 500 Daltons, allowing them to pass through plasma membranes and access intracellular targets that are inaccessible to larger monoclonal antibodies (Lavanya et al., 2014). As such, the scope of small molecule cancer drugs is broad – they may target serine/threonine/tyrosine kinases, matrix metalloproteinases (MMPs), heat shock proteins (HSPs), proteasomes, and other proteins involved in cancer signaling pathways (Lavanya et al., 2014).

The loss of cell cycle regulatory control may cause uncontrolled cell growth (Pathak et al., 2018). This makes the proteins responsible for the progression of the cell through different cell cycle phases important targets for small molecule inhibitors. These cell cycle proteins include cyclins and cyclin dependent kinases (CDKs) (Pathak et al., 2018). Cyclins may be further divided into “G1/S cyclins” and “G2/M cyclins” depending on their role in the cell cycle; respectively, these groups contain CDK2/4/6 and CDK1 (Pathak et al., 2018). CDK1 is a protein that mediates the transition from the G1 to M phases of the cell cycle and an important target for small molecule inhibitors (Pathak et al., 2018). Some small molecule inhibitors undergoing clinical trials include TG-02 or Zotiraciclib, which was developed by Adastra Pharmaceuticals and shows anti-glioblastoma properties, and Flavopiridol, which was developed by Tolero Pharmaceuticals and shows anti-acute myeloid leukemia properties (Pathak et al., 2018).

Kinase receptors, which mediate cell growth and survival, are also linked to cancer cell FALL 2020

proliferation (Pathak et al., 2018). Researchers have observed that many cancers deregulate kinases; thus, kinase receptors are a promising anticancer drug target (Pathak et al., 2018).

There are three main types of kinases that small molecule inhibitors target: polo-like kinases (PLKs), aurora kinases, and receptor tyrosine kinases (RTKs) (Pathak et al., 2018). PLK-1, the most prominent polo-like kinase, regulates the mitotic checkpoint. Higher PLK-1 expression is linked to defective cell cycle checkpoints and genetic instability, which trigger oncogenesis (Pathak et al., 2018). Thus, researchers are investigating PLK-1 inhibitors to treat cancer, although numerous phase III clinical trials have failed to produce statistically significant improved survival rates (Wynn, 2016).

Aurora kinases also play significant roles in regulating the cell cycle; specifically, researchers are considering Aurora kinase A and B as targets for small molecule inhibitors (Pathak et al., 2018). Aurora kinase A promotes CDK1 activation and regulates spindle assembly and orientation during mitosis, whereas Aurora kinase B controls the condensation and orientation of chromosomes (Pathak et al., 2018). The overexpression of these proteins causes DNA damage and inactivation of regulatory cell cycle checkpoints (Pathak et al., 2018). Thus, the inhibition of Aurora A and B by small molecule inhibitors is a promising candidate for cancer treatments, and numerous lead compounds are undergoing different stages of clinical trials (Pathak et al., 2018).

RTKs are another significant class of kinases in oncogenesis and progression, and they play a role in cell growth, repairing tissues, and cell regeneration (Pathak et al., 2018). Oftentimes, when RTKs that express genes become mutated or amplified, those genes become oncogenes, leading to oncogenesis (Pathak et al., 2018). Moreover, researchers have observed the deregulation of RTKs in many cancers; thus, small molecule inhibitors which may regulate RTKs are a promising cancer therapy. Sorafenib, which was co-developed by Bayer and Onyx Pharmaceuticals, is one such drug and has received FDA-approval to treat hepatocellular carcinoma (Pathak et al., 2018).

Figure 7: Antibody Drug Conjugates (ADCs) are a class of therapeutic that pairs the specificity of an antibody with the cytotoxicity of a drug such that the tumor cell can be killed shortly after binding the antibody component of the ADC Source: Wikimedia Commons

"The loss of cell cycle regulatory control may cause uncontrolled cell growth (Pathak et al., 2018). This makes the proteins responsible for the progression of the cell through different cell cycle phases important targets for small molecule inhibitors."

Another method of targeted cell therapy for cancer is the use of antibody-drug conjugates (ADCs). Composed of monoclonal antibodies linked to an anti-cancer drug, these conjugates target specific antigen proteins found almost exclusively on tumor cells while ignoring healthy cells that do not have the target antigen, or express it in far lower quantities (Hamilton, 2015). Once the antibody binds to the target 181

Figure 8: Radiation therapy being applied to a cancer patient Source: Wikimedia Commons

"Some ADCs have already demonstrated incredible efficacy and selectivity in targeting and eliminating tumor cells. Many of these ADCs make use of chemotherapeutic agents that would otherwise be too toxic for direct use."

antigen, the cancer cell absorbs the ADC and it is transported to a compartment called the lysosome. Under the acidic conditions in the lysosome, the linkage between the antibody and drug is cleaved, allowing the drug to disrupt the cell’s DNA or prevent microtubule polymerization, and ultimately induce cell death (Hamilton, 2015).

Some ADCs have already demonstrated incredible efficacy and selectivity in targeting and eliminating tumor cells. Many of these ADCs make use of chemotherapeutic agents that would otherwise be too toxic for direct use. For instance, DiJoseph et al. were able to produce a CD-22 targeted conjugate to deliver calicheamicin to treat B-cell lymphoma lines (DiJoseph et al., 2004). Calicheamicin is more than 4000 times as toxic as the standard doxorubicin used in chemotherapy and, thus, cannot be used alone (Kumar et al., 2017).

However, when combined with an anti-CD-22 monoclonal antibody through an acid-labile linker, the drug was found to achieve near total tumor death at a dose of 160 μg/kg of tumor, as compared to the 7.5 mg/kg required for the unconjugated antibody. This dosage lied well within the range of tolerance for mice, which could tolerate doses up to 240 μg/kg (DiJoseph et al., 2004). Similarly, Burris et al. discovered that the trastuzumab-DM1 antibody drug conjugate had significant inhibitory effects for patients with human epidermal growth factor receptor 2 (HER2) positive breast cancer (Burris et al., 2011). The group found that 25.9% of patients experienced at least some tumor shrinkage when treated with the trastuzumabDM1 ADC, with a further 49% experiencing no further growth of the cancer. Additionally, of the 112 patients in the study, only six patients required dose reduction from the 3.6 mg/kg prescribed, and no cardiotoxicity was detected (Burris et al., 2011). Both of these studies demonstrate the potential benefits of ADCs for targeted cancer treatment, especially when used in conjunction with other therapies.

Targeted gene therapy is another type of treatment for cancer that targets specific genes and proteins that contribute to a malignant tumor’s growth. Gene therapy works by destroying the cancer cell, turning off the signals that cause the cancer cell to divide, or preventing the cancer cell from living longer than usual. The targets of this therapy are genetic changes in cancer cells that cause them to divide abnormally. These changes are identified by researchers on an individualpatient basis so that the developed treatment is specific to cells with the identified mutation and healthy cells are left untouched. Monoclonal

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antibodies and small-molecule drugs are a common type of targeted gene therapies.

Other forms of targeted gene therapy include immunotherapies, angiogenesis inhibitors, and apoptosis inducers. Targeted therapies have been used as a treatment for HER2 positive breast cancer, chronic myeloid leukemia, colorectal cancer, lung cancer, lymphoma, and melanoma. (Understanding Targeted Therapy, 2013).

Cancer Treatment from a Patient Facing Perspective Once diagnosed with cancer, patients will follow a treatment plan suited to them that consists of primary, adjunctive, and palliative treatments. Primary treatments are loosely defined as the most promising way to treat and cure the patient’s cancer. Because of this, primary treatments consist of a large variety of therapies including surgery to remove the cancerous tumors and, in certain cases, cryoablation (the use of extreme cold to destroy cancerous tissue). However, if primary treatments don’t cure the patient entirely, adjunctive treatments will follow. These treatments are meant to remove any remaining cancer and lower the risk of the cancer coming back. Adjunctive treatments include some common types of cancer treatment such as chemotherapy, hormone therapy, and radiation therapy. Adjunctive treatments can last DARTMOUTH UNDERGRADUATE JOURNAL OF SCIENCE

Figure 9: Cryoablation is occasionally used as a technique to combat cancers such as cervical cancer when traditional surgical methods don’t work Source: Wikimedia Commons

anywhere between just a few weeks after the primary treatment to several years. Primary and adjunctive treatments can take large physical and mental tolls on the patients receiving them. For instance, chemotherapy can cause nausea, infections, issues with concentration, and hair loss. In order to combat side effects, patients may also choose to undergo palliative treatment. Palliative treatment is typically thought of as synonymous with hospice care, but it really encapsulates much more.

Palliative treatments are meant to improve the quality of life of cancer patients by managing the symptoms of cancer treatments. This can include anything from taking medication to lessen the side effects of certain treatments to providing patients with proper emotional support to help them get through treatment.

Surgery is a physically and financially strenuous cancer treatment. Focusing on the psychosocial aftermath of cancer, patients experience lasting emotional tolls. One cancer patient demonstrates this when recalling the date of her surgery, “I also get a sick feeling in my stomach every April 15, the day of my surgery” (Kemp & Zars, 2016). Patients sometimes handle these feelings of hopelessness and anxiety through religion. This same patient reported turning to faith and discussed how praying helped her gain the emotional strength to get through surgery and follow up appointments (Kemp & Zars, 2016). Surgery also creates fears of going out and facing social rejection if the patient has scars or other physical deformities as a result.

Furthermore, patients often have issues being intimate and avoid expressing their concerns about their changes in physical appearance (Facing Forward: Life After Cancer Treatment, FALL 2020

2010). Age is a psychosocial factor in and of itself, since older adults tend to have preexisting conditions that can worsen the psychological effects of surgery. As a consequence, older adults that undergo surgery tend to have a higher demand for psychosocial services (Adler 2008). The psychological aftermath is not always just due to surgery. It is often coupled with chemotherapy or radiation depending on what the physician recommends, creating an even more stressful environment.

The financial and psychosocial impacts of surgery are not independent of one another.

Surgery leaves the patient feeling overwhelmed with a fear of rejection that can manifest as an inability to work, and consequently, a reduced income (Adler 2008). Narrowing in on the financial aspect of cancer surgery, the cost is coupled with prior preventative prescription medication, adjunctive treatments, and palliative medications to alleviate the side effects of surgery and adjunctive care. Patients are often forced to make difficult decisions to trade off quality for cost. For example, fluorouracil with leucovorin administered through an IV for six months costs between $545-$1970 depending on the amount, while a regimen considered more effective, such as 5-FU combined with leucovorin or levamisole, can be $12,000 for eight weeks (Adler 2008).

The former course is often chosen because it is cheaper. If a patient is undergoing such treatment but later needs surgery, the costs become higher. Colorectal cancer has the second highest expenditure which has been explained by surgery being the most effective treatment for this specific cancer (Park 2019).

"The financial and psychosocial impacts of surgery are not independent of one another.

Surgery leaves the patient feeling overwhelmed with a fear of rejection that can manifest as an inability to work, and consequently, a reduced income."

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"Radiation therapy is a common component of cancer therapy as two thirds of cancer patients undergo a radiation therapy regiment as a part of their treatment plan."

Radiation therapy is also physically and financially burdensome. This therapy uses x-rays, gamma rays, or other high energy particles and waves to eliminate cancer cells.

Essentially, these damaging waves damage DNA within dividing cancer cells, preventing the DNA from replicating and the cells from proliferating further. There are two ways to deliver radiation to the tumor. The first, external beam radiation, is delivered from outside the body. This is the most common approach in the clinical setting. The second, internal radiation/brachytherapy, is delivered from inside the body by radioactive sources sealed and implanted directly adjacent to the tumor site (Baskar et al. 2012). Depending on the type of cancer, the size of the tumor, the tumor’s location, and the patient’s age and overall health, one or both of the treatments may be recommended. Furthermore, as opposed to chemotherapy and other forms of cancer treatment which expose the entire body to cancer fighting drugs, radiation therapy is focused solely on the cancer-containing area of interest. This limits the tissue and cell death around the body. Since it is a localized therapy, however, it’s rarely useful in treating cancers that have spread throughout the body.

In addition, radiation therapy is often paired with other cancer treatment techniques. If used before surgery (neoadjuvant therapy), radiation will aim to shrink the tumor. If used after surgery (adjuvant therapy), radiation will destroy microscopic tumor cells that may have been left behind. It also functions in palliative treatment. “Palliative radiotherapy offers a quick, inexpensive, and effective way of reducing many of the focal symptoms of advanced, incurable cancer, whether these arise from the primary tumor or from metastatic deposits (Spencer, 2018).”

Radiation therapy is a common component of cancer therapy as two thirds of cancer patients undergo a radiation therapy regiment as a part of their treatment plan (Berkey et al. 2010), and it contributes towards 40% of curative cancer treatments (Baskar et al. 2012). Like most cancer therapies, side effects are often a concern.

Fatigue, hair loss, skin changes, and depression are commonly reported amongst patients undergoing radiation therapy, regardless of the part of the body being targeted. Furthermore, cardiovascular complications involving the pericardium, myocardium, valves, coronary arteries, and conduction system are reported frequently during treatment and following the conclusion of treatment (Gegechkori et al. 2017). Finally, there exists a tremendous amount of variation in radiation therapy costs.

Based on Medicare reimbursements, one study

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estimated that the average cost of radiation therapy among ~56,000 Medicare patients outof-pocket was $8,600 ($7,300 to $10,300) for breast cancer, $9,000 ($7,500 to $11,100) for lung cancer, and $18,000 ($11,300 to $25,500) for prostate cancer (Paravati et al. 2015).

Furthermore, “the type of radiation therapy a patient received accounted for a large portion of the variation of cost, ranging from 15% with prostate to 27% with breast and 30% with lung cancer.” Costs differ by region, insurance provider, and individual clinic as well. Overall, radiation therapy has been a critical tool for improving cancer outcomes across the board.

Next, cryoablation is a surgical technique that uses a cryoprobe (a thin, wand-like needle) to freeze cancerous tissue with a steam of gas and then remove the malignant solid mass (MayoClinic, n.d.; NCI, n.d.). The cyclical process of freezing and thawing the malignant tissue kills the cells (MayoClinic, n.d.). The gas used varies from argon, liquid nitrogen, and sometimes carbon dioxide, all of which are capable of bringing the cell temperature down to the -40° Celsius. Other gases are capable of inducing even lower temperatures (Surtees et al., 2019).

If typical cancer surgery does not work for patients, cryoablation is sometimes proposed as an alternative procedure, especially for bone cancer, cervical cancer, kidney cancer, and eye cancer patients (MayoClinic, n.d.). However, this is not an exhaustive list and the procedure is also used for cancer pain and symptomatic relief (MayoClinic, n.d.). In addition, this treatment can be utilized for precancerous conditions such as actinic keratosis or cervical intraepithelial neoplasia. The benefits of this procedure include its minimally invasive nature, precision, and less “pain, bleeding, and [a shorter] recovery time” post-op for the patient. Typically, less medicine is required post-op as well (NCI, n.d.; Cleveland Clinic, n.d.).

The biggest limitation of this surgery is that it cannot be used to treat wide-spread cancers due to its high precision (NCI 2, n.d.). At the same time, it can fail to remove microscopic cancers as they are not detected by imaging tests that the physician orders (NCI 2, n.d.).

Some of the side effects of the treatment arise due to the complex nature of the tissue where the cancer is located (NCI 2, n.d.). Other complications include obstruction of urine flow or impotence for patients with prostate cancer.

Sometimes, when cryoablation is used for skin cancer, individuals may have residual scars or nerve damage (NCI 2, n.d.). Other times, when cryoablation is used for bone cancers, patients may have weaker or destroyed bone tissue near the site of ablation (NCI 2, n.d.). The cost of this DARTMOUTH UNDERGRADUATE JOURNAL OF SCIENCE

procedure has been a barrier for low-income and middle-class communities. A typical cryoablation procedure can cost the patient up to $10,000 (Surtees et al., 2019). However, a study published in 2019 by Bailey Surtees et al. shows that by using carbon dioxide as the cryogen instead of liquid nitrogen or argon gas in breast cancer rat models, the efficiency of the technology is preserved while dramatically reducing the cost of using the gas.

After further research is completed in larger animals and humans, this altered technology will make it less expensive and therefore more accessible to socioeconomically disadvantaged communities (Surtees et al., 2019). In the near future, scientists suggest the use of cryoablation in tandem with immunotherapies to maximize the benefits of the procedure. In addition, to strengthen the effects of the freezing gas, scientists have found that adding hydrogen gas will allow the treatment to increase the function of mitochondria which has shown to aid immune cells like T cells in fighting the cancer. This will ultimately help the patient lengthen the period of time where their cancer cell growth is stagnant (Chen et al, 2020).

In contrast to cryoablation, radiofrequency ablation (RFA) utilizes modified electrocautery techniques in order to perform minimally invasive tissue ablation of cancer cells (Friedman et al., 2004). This technique involves resistive heating, the process of producing heat by passing an electric current through a conductor, which causes cancer cells to undergo coagulation necrosis. Typically, temperatures range between 50°C and 60°C (Friedman et al., 2004). RFA utilizes imaging guidance systems such as CT or MRI to guide a needle directly into a tumor (“Radiofrequency Ablation,” n.d.).

Several thin electrodes extend from the needle allowing a doctor to deliver heat and kill tumor cells in only a few minutes (“Radiofrequency Ablation,” n.d.). This percutaneous technique is advantageous as it requires only localized anesthesia. Laparoscopic RFA involves several incisions to insert the RFA as well as imaging probes, and the procedure requires general anesthesia (“Radiofrequency Ablation,” n.d.).

Though RFA is generally a non-surgical method of cancer treatment, surgical approaches to performing RFA allow for more accurate evaluation of the cancer as well as less risk to adjacent organ systems (Friedman et al., 2004).

There are, as with any technologies, limitations to RFA. Notably, RFA cannot be performed on tumors with close proximity to the bowel or with other organs that are at risk of being damaged by thermal conduction (Friedman et

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al., 2004). In addition, radiofrequency ablation becomes difficult to perform on tumors in close proximity to arteries and veins larger than 3 mm in diameter. The transfer of heat from the electrodes can present a risk to blood vessels, necessitating either temporary clamping or the creation of a chemical embolism in local blood vessels in order to complete the procedure (“Radiofrequency Ablation for cancer,” n.d.).

RFA has been seen as an extremely attractive alternative for patients with primary and metastatic liver candidates, as they are generally not candidates for surgery. In patients with Hepatic Cell Carcinoma (HCC), a disease with a median life expectancy of 1-18 months, successful ablation has led to 5-year survival rates of 40-50% (Friedman et al., 2004). In addition, successful ablation of hepatic, adenocarcinoma, sarcoma, and neuroendocrine cell metastases lesions under 3.0 cm in size was associated with improved survival rates (Friedman et al., 2004). RFA may be an alternative for palliative care. 43 patients with single, painful bony metastases that were resistant to both chemotherapy and radiotherapy were treated with RFA in a large, multicenter study. The study reported significant decreases in both pain and analgesic use (Friedman et al., 2004).

Conclusion Taking a step back, there are a few preventative measures to help individuals prevent the onset of certain cancers. The use of tobacco is one of the most dangerous and well-established contributors to cancer. It has been proven that carcinogens in cigarette smoke can attach themselves to DNA, causing mutations in important genes, resulting in tumor growth and the development of extra mutations that may lead to cancer (National Cancer Policy Forum, 2013). Additionally, smoke from tobacco, among other environmental factors, may lead to carcinogenesis, turning precancerous abnormal cell growth into metastatic lung cancer (CDC, 2010). Not only can tobacco cause cancer but it can also make it more difficult to treat by activating nicotinic acetylcholine receptors, which promote cell survival and decrease the efficiency of chemotherapy and radiation (Peters et al. 2012, Brody et al. 2006).

"In contrast to cryoablation, radiofrequency ablation (RFA) utilizes modified electrocautery techniques in order to perform minimally invasive tissue ablation of cancer cells (Friedman et al., 2004). This technique involves resistive heating, the process of producing heat by passing an electric current through a conductor, which causes cancer cells to undergo coagulation necrosis."

In addition to not smoking, maintaining a healthy body weight helps to prevent cancer, as obesity is the second leading environmental factor for cancer risk. Research suggests that the chronic inflammatory physiology caused

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by obesity-associated metabolic syndrome leads to eventual carcinogenesis in epithelial cells (Colacino, Djuric, and Brenner, 2020). Beyond maintaining a healthy weight and avoiding tobacco products, other—more specific—tips readers could employ to prevent cancer include using sunscreen, getting the HPV and hepatitis vaccines, and sharing family medical information with a trusted doctor.

Despite the possibility of prevention, there are cases that no amount of healthy behavior could prevent – ones that owe to genetic predisposition, unwitting exposure to environmental carcinogens, or to a ubiquitous and unavoidable risk factor for cancer: old age. Cancer touches thousands of human lives every year, not just patients, but the loved ones watching their illness progress, or the physicians and nursing treating them. The most difficult aspect of the illness is that it is borne of the patient’s own cells. Treatment and recovery is predicated on the elimination of the cancer while aiming to maintain the landscape that it ravages. The cancer surgeon is like a delicate general, trying to launch an artillery barrage without scorching the earth beneath the enemy soldiers’ feet (or torching his own troops). But the significant investment of time, energy, and money on behalf of the academic and industry stakeholders has led to significant improvements in the form of developed therapies that are promoting remission and hold the promise for patients of a new lease on life. Discoveries continue every day with new approved therapies and treatment regimes.

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Radiofrequency Ablation of Cancer. Cardiovascular and Interventional Radiology, 27(5), 427–434. https://doi. org/10.1007/s00270-004-0062-0 Gegechkori, N., Haines, L., & Lin, J. J. (2017). Long Term and Latent Side Effects of Specific Cancer Types. The Medical Clinics of North America, 101(6), 1053–1073. https://doi. org/10.1016/j.mcna.2017.06.003 Hamilton, G. S. (2015). Antibody-drug conjugates for cancer therapy: The technological and regulatory challenges of developing drug-biologic hybrids. Biologicals, 43(5), 318–332. https://doi.org/10.1016/j.biologicals.2015.05.006 Kemp, J., &amp; Zars, C. (2016). A Tale of Two Perspectives on Cancer: What I Wish I Knew Before Cancer—Radiologist and Patient Perspectives. Journal of the American College of Radiology, 13(12), 1625-1627. doi:10.1016/j.jacr.2016.09.014 Kolodych, S., Koniev, O., Baatarkhuu, Z., Bonnefoy, J.-Y., Debaene, F., Cianférani, S., Van Dorsselaer, A., & Wagner, A. (2015). CBTF: New Amine-to-Thiol Coupling Reagent for Preparation of Antibody Conjugates with Increased Plasma Stability. Bioconjugate Chemistry, 26(2), 197–200. https://doi. org/10.1021/bc500610g

immuno-oncologynews.com/immuno-oncology/ Radiofrequency Ablation for Benign and Cancerous Tumor Treatment. (n.d.). Retrieved October 30, 2020, from https:// www.umms.org:443/bwmc/health-services/cancer/surgery/ radiofrequency-ablation-benign-cancerous-tumor-treatment Reardon, S. (2020). Step aside CRISPR, RNA editing is taking off. Nature, 578(7793), 24–27. https://doi.org/10.1038/ d41586-020-00272-5\ Sarkar, S., Horn, G., Moulton, K., Oza, A., Byler, S., Kokolus, S., & Longacre, M. (2013). Cancer Development, Progression, and Therapy: An Epigenetic Overview. International Journal of Molecular Sciences, 14(10), 21087–21113. https://doi. org/10.3390/ijms141021087 Shivam Kalra. (2020). Pan-cancer diagnostic consensus through searching archival histopathology images using artificial intelligence. Nature, npj Digital Medicine(3), 31.

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Kumar, A., White, J., James Christie, R., Dimasi, N., & Gao, C. (2017). Chapter Twelve—Antibody-Drug Conjugates. In R. A. Goodnow (Ed.), Annual Reports in Medicinal Chemistry (Vol. 50, pp. 441–480). Academic Press. https://doi.org/10.1016/ bs.armc.2017.08.002

Surtees, B., Young, S., Hu, Y., Wang, G., McChesney, E., Kuroki, G., Acree, P., Thomas, S., Blair, T., Rastogi, S., Kraitchman, D. L., Weiss, C., Sukumar, S., Harvey, S. C., & Durr, N. J. (2019).

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Lavanya, V., Mohamed, A. A. A., Neesar, A., Arun, K. R., & Shazia, J. (2014). Small molecule inhibitors as emerging cancer therapeutics. Integrative Cancer Science and Therapeutics, 1(3), 39–46. https://doi.org/10.15761/ICST.1000109 Leukemia—Cancer Stat Facts. (n.d.). Retrieved October 11, 2020, from https://seer.cancer.gov/statfacts/html/leuks.html Müller‐Hermelink, H. K., Zettl, A., Pfeifer, W., & Ott, G. (2001).

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Onward to Mars: The Past, Present, and Future of Human Space Travel STAFF WRITERS: DEV KAPADIA, AUDREY HERRALD, ANAHITA KODALI, KRISTAL WONG, AMITTAI WEKESA, ISAIAH MENNING EDITORIAL BOARD WRITER: SAM NEFF

Cover Image: The Space Shuttle Atlantis, shown soon after it undocked from the International Space Station in 2006. The Era of the Space Shuttle is not over, and the story of human space exploration has much left to be written. A slew of private companies (with the backing of NASA) have set their eyes on the Moon, Mars, and beyond.

Source: Wikimedia Commons

Introduction In the 20th century, humanity took to the sky.

After little more than a half-century, aerospace exploration evolved from the first flight of Orville and Wilbur Wright to the Apollo 11 Moon landing. Yet even before the pace of change became so rapid, flight had been dreamed up as a concept for millennia. Glider flight, in fact, is thought to have been attempted (successfully) by the Andalusian polymath Abbas Ibn Firnas in 9th century AD. But autonomous air flight powered by an engine was a relatively new invention. And like all successful inventions, it was applied to meet the demands of a particular historical moment.

After the Wright brothers, air travel developed in leaps and bounds because aerospace research was stimulated by Two World Wars and a Cold War - and heaps of government funding.

Rocketry, pioneered in the early 20th century, arrived at center stage in the 1950s: Sputnik

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launched in 1957, NASA was founded in 1958, the Mercury and the Apollo missions played out in the 1960s. The Shuttle program progressed throughout the 70s and 80s, and thenâ&#x20AC;Ś the Cold War suddenly stopped. On Christmas Day 1991, Soviet Premier Mikhail Gorbachev simply resigned, and the Soviet Union, for all intents and purposes, ceased to exist. Three decades of relative peace have followed. The United States and Russia even lodge together in the International Space Station.

In recent years, though, space exploration has lit up with a new intensity, and this time the competition is between private companies the main contenders are not political figures like Reagan and Gorbachev, but private aerospace magnates: Bezos, Branson, and Musk. Regardless, there is still plenty of work for the politicians to do. As space becomes subject to more frequent and extensive exploration, international cooperation (and contest) will DARTMOUTH UNDERGRADUATE JOURNAL OF SCIENCE

surely follow. The following pages tell the stories of the space race from its 20th century origins to today. Discussions about the science of space flight and the impact of space-based research, will accompany this history.

A Brief History of Human Spaceflight: From the Origins of Rocketry to the Challenger Disaster Modern day space programs arose independently in three different countries during the early 20th century. The American father of modern rocketry is Dr. Robert Goddard. He was a physicist whose work largely contributed to the development of rocket propulsion techniques. In 1914, Goddard patented a rocket using liquid fuel; he additionally patented a two- or three-stage rocket that used solid fuel. He then began to explore the possibility of reaching extreme altitudes with rockets, and in 1920, he outlined the possibility of reaching the moon with rockets. Goddard spent the next two decades making several engineering advances in rocketry. In 1929, he created the first rocket to carry a scientific payload, a barometer, and a camera. During the 1930s, he was recruited by the American military to develop several new capabilities for rockets. In 1932, he developed techniques for the use of vanes during motor blast-off for guidance. Additionally, he developed a gyro control apparatus for rocket flight in 1932; in 1937, he was able to translate his work with gyro control into a full rocket launch. Throughout his lifetime, Goddard’s work was consistently underappreciated and met with skepticism, especially his work on sending a rocket to the moon. Despite this, Dr. Goddard is known today as one of the first American scientists who not only recognized the potential of space flight but also made significant progress to making it a reality (“Dr. Robert H. Goddard,” n. d.).

The Russian father of rocketry is Dr. Konstantin Tsiolkovsky. He made several significant theoretical contributions to the field of modern rocketry. After studying chemistry, mathematics, astronomy, and mechanics in university, he spent several years studying air friction and dynamics in handmade wind tunnels. He was able to develop advanced aircraft designs from his work. He then turned his attention towards the cosmos. At the end of the 19th century, he published the book Gryozy o zemle i nebe (Dreams of Earth and Sky) and an article on communication with inhabitants of other planets; in these texts, he theorized FALL 2020

about the possibility of space travel. In 1896, he wrote his seminal paper “Exploration of Cosmic Space by Means of Reaction Devices,” in which he discussed several mechanics that he believed would be critical in space exploration, including heat transfer, air friction, fuel supply maintenance, and navigation. Throughout the early 20th century, Tsiolkovsky continued to make several theoretical contributions to space flight with an emphasis on exploration of the stratosphere and interplanetary space. He was elected to the Socialist Academy of the USSR for his work in 1919 (Arlazorov, 2020).

The German father of rocketry is Dr. Hermann Oberth. His contributions mainly deal with the use of multi-stage rockets and theoretical work regarding the effect of the gravitational field on rocket launches. A student of mathematics and physics at university, Dr. Oberth taught himself rocket science and tested theories on the use of liquid rocket fuel through the early 20th century. In his work, he discovered the importance of breaking down rocket travel into multiple stages by recognizing that when a smaller rocket positioned on top of a larger one ignites while the larger rocket is in the air, their speeds will add together. Though his doctoral thesis in 1922 was rejected, Dr. Oberth continued to study rocketry and began to work on his book The Rocket into Planetary Space; the final draft, published in 1929, described how rockets might be able to break the Earth’s gravitational field to reach space. He launched his first rocket in 1932 and spent the rest of his life conducting rocketry research for both Germany and the U.S. (“Hermann Oberth,” n. d.)

"Modern day space programs arose independently in three different countries during the early 20th century."

Forays into space would not rise to the level of manned rocketry until the early 1960s, but the seeds for U.S. space travel were sown in the 1910s, long before the onset of the Cold War and the launching of Sputnik prompted the American political establishment to focus on space. In 1911, not long after the Wright Brothers’ historic flight, the American Aeronautical Association organized its first meeting, calling for the construction of a new aviation laboratory at the Smithsonian. What they got, in 1915, was the formation of a new agency with federal backing: the National Advisory Committee for Aeronautics, or NACA. Although the inception of the agency was rather modest – it was birthed out of two paragraphs in the 1915 Naval Appropriations Act and granted a measly $5,000 starting budget – the agency’s budget quickly expanded as it attracted support from the U.S. military. Their first benefactors were the army, and later on, more extensive support 189

Figure 1: An illustration of Robert Goddard, the American father of rocketry.

Source: Wikimedia Commons

came from the Navy. Both military bodies would send formal research requests to NACA through the 1930s. This research centered largely around engine supercharging and pressure distribution, for advances in engine design would contribute mightily to a United States military that increasingly fought its battles in the air (Gorn, 2011).

"The onset of the Cold War and its emphasis on mutually-assured destruction all but required aerospace research as a vital element of national defense: not just faster and higherflying planes, but satellites that were capable of launching missiles (ICBMs, or intercontinental ballistic missiles) from one continent to the next."

Aeronautical R&D was certainly applicable during the Second World War, and later on, in America’s “forgotten” Korean War. Throughout the 1940s and 50s, new jet turbine engines and the advent of the afterburner rendered fighter craft increasingly speedy and allowed them to soar higher and traverse greater distances (Lorell and Levaux, 1998). These new innovations needed enterprising pilots to test them, giving rise to a generation of daring fighter pilots who possessed great grit. Historian Tom Wolfe coined the term “the right stuff” to describe the qualities of these pilots, many of whom he interviewed leading up to the publication of his book (the book was made into a critically-acclaimed movie in 1983, and is the subject of a new television series that premiered this October) (Wolfe, 1979). Among those he met was the former U.S. Air Force Officer Chuck Yeager. Piloting the Bell X-1, a rocket-powered aircraft, Yeager famously broke the sound barrier on October 14, 1947: a stunning demonstration of the enormous potential for rocket-based flight (“Chuck Yeager,” n.d.)

The onset of the Cold War and its emphasis on mutually-assured destruction all but required aerospace research as a vital element of national defense: not just faster and higher-flying planes,

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but satellites that were capable of launching missiles (ICBMs, or intercontinental ballistic missiles) from one continent to the next (Lorell and Levaux, 1998). Indeed, the stage was set for an acceleration in aerospace spending, and an increased focus on outer space in the waning days of the Second World War. Air Force General Henry Arnold proclaimed in his ‘Third Report to the Secretary of War’ (1945) that “if defenses which can cope even with such a 3,000-mileper hour projectile are developed… we must be ready to launch them from unexpected directions. This can be done from true space ships, capable of operating outside the earth’s atmosphere. The design of such a ship is all but practicable today; research will unquestionably bring it into being within the foreseeable future.” Command of space, it was believed, would be the crucial factor in maintaining both defensive and offensive military hegemony (Rothstein, 2000).

Although the vision Arnold set forth was limited to unmanned aircraft – satellites armed with ICBMs – the focus would turn to manned spacecraft by the end of the next decade (Rothstein, 2000). In 1957, the Soviet Union launched Sputnik, the first (unmanned) artificial satellite to break the bounds of Earth’s atmosphere and enter space. This beachball sized object publicly launched the two dominant world powers, the United States and the Soviet Union, into the ‘Space Race.’ It might be said, however, that the race had started covertly more than a decade prior. In 1945, a team of Soviet rocket scientists infiltrated Peenemünde, the facility where Nazi scientists had developed their infamous V2 rockets. The

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Soviets took as much equipment as they could carry, including the rockets themselves and any documents that the Germans had left behind (Sagdeev, 2007). But American Special Forces were not left out of this game to reap the spoils of Nazi aerospace research. CIA Operation Paper Clip brought Werner Von Braun, the lead figure in the development of the V2 rockets, and 120 of his fellow German scientists and technicians to the United States (Watkins, 2014). They would be heavily involved in NASA missions – Mercury, Gemini, and Apollo – throughout the 1950s and 60s (Wolfe, 1979).

What about NASA? NASA was created in 1958 as a product of the National Aeronautics and Space Act. The bill was borne out of an atmosphere of intense and bipartisan anxiety in political circles following the launch of Sputnik. Senate Majority leader (and later Democratic President) Lyndon Johnson chaired the ‘Preparedness Investigating Subcommittee of the Senate Armed Services Committee’ in late 1957 that led to the establishment of a Senate Special Services Committee on Space and Aeronautics in February 1958.

Around the same time, Republican President Dwight Eisenhower asked his science advisor James Killian Jr. to convene a Presidential Science Advisory Committee on the matter of space travel. Released on March 5, 1958, a memorandum from the committee set forth a proposal to build a civilian space agency around the existing framework of NACA. Eisenhower sent draft legislation to Congress in April and the National Aeronautics and Space Act was easily passed into law on July 29th. NASA set up shop on October 1st with the following aims (direct from section 102 of the act): the “improvement of usefulness, performance, speed… of aeronautical and space vehicles,” the “preservation of the role of the United States as a leader in aeronautical and space science and technology,” and the “cooperation by the United States with other nations… in the peaceful application of the results thereof.”

Clearly, NASA’s organizational objectives were crafted with Cold War imperatives in mind (Dick, 2008).

It was not just the political environment that was affected by the launching of Sputnik, but the culture of the United States at large.

Historians have noted immense changes in U.S. educational policy following the Soviet launch: increased funding and support for technical development, particularly courses in science and mathematics, that would render the U.S.

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more globally competitive. The great fear was that the Soviet Union would churn out more science-minded students that could contribute to the Russian Space program, and that the United States would be left intellectually inferior (Steeves et al., 2009). Beyond changes to schooling, public libraries were engaged in partnership with NASA to provide space and rocket-related novels, museum-style exhibitions, and even reading clubs that would teach the public about space and its importance to national security and American identity (Spencer, 2016). Given this cultural climate, it is no surprise that the American public viewed the ‘Mercury Seven’ – the group of men chosen as pilots for NASA’s first rocket program – as national heroes (Wolfe, 1979).

All seven astronauts were military men: Alan Shepard, Wally Schirra, John Glenn, and Scott Carpenter former members of the US Navy; Gordon Cooper and Gus Grissom of the Air Force; and Deke Slayton of the US Army Air Corps (Wolfe, 1979). Yet the pilots of the first Mercury rockets were actually not these astronauts, but primates in space suits. Unlike Laika the dog, who likely died of overheating during the orbital flight of Sputnik 2, the monkey (Sam) and two chimpanzees (Ham and Enos) made it back to earth safely in Mercury test missions during 1959 and 1960 (Sagdeev, 2007; “The Space Race,” n.d.). This reassured NASA officials that it was safe to send humans to space.

"NASA was created in 1958 as a product of the National Aeronautics and Space Act. The bill was borne out of an atmosphere of intense and bipartisan anxiety in political circles following the launch of Sputnik."

Unfortunately for the Americans, the Soviets got there first, launching Yuri Gagarin out of Earth’s atmosphere aboard Vostok 1 (April 21, 1961). Gagarin was the first human to enter outer space, and NASA countered by sending up Alan Shepard as the first American into space (aboard Freedom 7 in May, 1961), and John Glenn as the first human of any country into orbit, lapping the earth three times in 1962 (“The Space Race,” n.d.). However, not all Mercury flights were brilliant success stories.

Gus Grissom’s crash landing in the Atlantic Ocean ended with the loss of a rocket (The Liberty Bell 7), and he personally faced most of the blame from political figures and the media (it is now largely believed that a malfunction of the rocket itself, not the failures of the operator, was truly at fault) (Wolfe, 1979). The treatment of Grissom underscores the high stakes of NASA’s endeavors – from both a military and an economic perspective – and the great importance that the public placed on successful flights. The American people were the ones

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Figure 2: (a) The Crew of Apollo 11 (Pictured left to right: Neil Armstrong, Michael Collins, and Buzz Aldrin). (b) Astronaut Neil Armstrong, of Apollo 11, taking the first steps on the moon in 1969.

Source: www.nasa.gov

footing the bill, after all, and rocket catastrophes were a demoralizing blow to national pride.

"Arguably one of the most famous Apollo missions is Apollo 13, in which an explosion 200,000 miles from Earth prevented the team from reaching the moon."

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Simultaneously, NASA built its X-Plane Program, a series of missions consisting of diverse aircrafts that started in the 1940s. On October 14thth, 1947, the X-Plane became the first rocket powered airplane to break the sound barrier.

Since then, the X-Plane aircrafts pioneered the variable-sweep-wing in flight, the usage of exotic alloy metals for the primary structure of a plane, the 180-degree turn using a post-stall maneuver, the testing of boundary-layer-airflow control theories over plane wings at transonic speeds, and the intercontinental flight range (1952).

These aircraft were able to reach speeds of up to 6 times the speed of sound and were the first to fly at altitudes upwards of 90,000m (NASA, 1997).

Throughout the course of the ongoing X-Plane Program, aircrafts launched from various U.S. Air Force Bases, most frequently at Edwards Air Force Base, which includes the Air Force Flight Test Center and the Dryden Flight Research Center. The 20th century saw 15 major accidents and 4 fatalities during the program’s testing.

Due to strict safety precautions, the X-Plane program did not cause any civilian property losses or fatalities. One of the most lauded aircraft is the X-33, the product of an industrygovernment partnership with Lockheed Martin. Unfortunately, issues surrounding costs of rebuilding certain parts of the X-33 led to NASA defunding the project in 2001. However, many technologies from the X-33 continued to influence new rockets, especially with regard to cost control (Connor, 2016). Their legacy still holds today: most recently, X-61A Gremlins were developed in 2019 to be an unmanned air vehicle (UAV) through the Defense Advanced Research Projects Agency (DARPA) Gremlins programme for quick launching and recovery of UAVs (Cohen, 2020).

In 1965-1966, NASA created the Gemini Program, a series of ten missions. The primary goals of these missions were to prepare man’s landing and understanding of the moon.. The mission’s namesake alludes to the two-person capacity of the rocket ship, an improvement from the one-person Mercury vessels. These small victories gained sufficient confidence from scientists, paving the way for the Apollo lunar missions (NASA, 2011).

Perhaps the most famous quote in space history is “That’s one small step for a man. One giant leap for mankind.” It was coined by Neil Armstrong, the first human to set foot on the moon in 1969 during the Apollo 11 mission.

The program was named Apollo after the Greek mythical god of the sun, archery, music and dance, and truth and prophecy. Each Apollo spacecraft was launched on top of a Saturn rocket; the earlier missions launched from a two-stage Saturn I B rocket and later missions used a three-stage Saturn V rocket. After the first human-testing of the command module in October 1968, Apollo 8 became the first manned mission to orbit the moon and return safely to Earth that December. Less than seven months later, Armstrong, Michael Collins, and Buzz Aldrin comprised the first crew to land on the moon on July 20th (NASA, 2019).

Arguably one of the most famous Apollo missions is Apollo 13, in which an explosion 200,000 miles from Earth prevented the team from reaching the moon. Five years before the mission, the CM underwent renovations to increase the permissible voltage in the oxygen tanks; however, thermostatic switches in the heater weren’t adapted for this change. Thus, the high temperatures degraded the Teflon insulation and the thermodynamic switches wielded shut, resulting in an explosion in tank No. 2 during its subsequent use. Signs of faulty heating went unnoticed during pre-mission

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testing. Despite the struggle to return the spacecraft into orbit, the small timeframe to power up the command module, the scarcity of food and water, issues with carbon-dioxide removal, and 38°F temperatures, the Apollo 13 crew luckily landed back on Earth safely (Mansfield, 2017).

The Skylab, launched in May of 1973, was the first American Space Station – a home and a laboratory in space that involved the collaboration of scientists from 28 countries.

The spacecraft consisted of a multiple docking adaptor, a command and service module, a solar observatory, the Airlock Module and the Orbital Workshop (Whiting, 2018). It was crucial that the Skylab be self-sufficient in energy generation for extended periods of time and be a reliable station for communication, data collection, experimentation, living, and control systems. Skylab included four missions, the first of which was unmanned. The Skylab allowed astronauts to study the sun from new vantage points via x-ray photography and generate high quality solar and terrestrial data. The program challenged astronauts to work on in-space repairs and strengthened the relationship between on-site astronauts and ground crew. It tested man’s capability to withstand the zerogravity conditions of space and revert to gravity conditions on Earth, pushing the biological limits of the human body. In addition, the Skylab experimented with manufacturing crystals in space (George C. Marshall Space Flight Center, 1997). The Skylab was the first spacecraft to rescue another mission: a two astronaut Apollo capsule (a modified capsule of the Apollo spacecraft) collected a threeperson crew, with all five members making a successful return to Earth (Whiting, 2018). As Leo Goldberg, Director of Kitt Peak National observatory, stated, Skylab “proved the value of men in space as true scientific partners in space science research” (George C. Marshall Space Flight Center, 1997).

Soon after the launch of the Skylab, the ApolloSoyuz Test Project launched into space on July 15th, 1975; it was the first international partnership for space travel and was intended to test the compatibility of docking systems and the ability of separate spacecrafts to meet in outer space. The nine-day mission consisted of five Soviet and American astronauts (Loff, 2015).

The crews launched and docked separately, with the American three-person crew flying a remodeled U.S. Apollo spacecraft and the Soviet team of two traveling on the remodeled

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Soyuz. Both used a jointly designed Docking module. This collaboration tested the limits of international collaboration: the Americans learned Russian, and the Soviets learned English, and the teams met several times beforehand to become comfortable with each other and the other spacecraft. Communication between the crew was in the language of the listener (e.g., Americans spoke to the Soviets in Russian). The Apollo-Soyuz Test Project was the first Russian launch that was broadcasted in the Soviet Union (Redmond, 2004). After a successful docking, the team was able to conduct experiments on board and complete 110 earth-observation tasks involving ocean currents, pollution, desert geography, erosion, vegetation patterns, and iceberg movement (Redmond, 2004). This successful mission and partnership paved the way for future international space collaborations (Loff, 2015).

The goal of NASA’s Shuttle space program was to develop a reusable space shuttle that could provide “routine access to space.” However, this program did not come without its struggles: at the time, there was a lack of political support as politicians were more concerned with funding programs with quick payoffs – it would take decades until the payoffs of space exploration would be felt. The U.S. government argued that after spending $24 billion dollars on lunar travel, the Shuttle should be financially selfsufficient (Launius, 1992). Ultimately, the 135 mission-program, starting with the Columbia in April 1981 and ending with the Atlantis in July 2011, cost $113.7 billion dollars. The first space shuttle was named Enterprise, though it never was used for space travel. The first shuttle to space was the Columbia, which flew on the Space Transportation System I (STS1), deployed satellites, and served as a space laboratory. The infamous Challenger was the second shuttle created by NASA which made its first launch on April 4th, 1983. The Challenger missions included the first jetpack-powered spacewalks and the mission was the first to fix an out-of-orbit satellite. The Challenger also saw the first American woman to travel into space, Sally Ride, in 1983 (NASA, 2012).

"The Skylab, launched in May of 1973, was the first American Space Station – a home and a laboratory in space that involved the collaboration of scientists from 28 countries."

However, during the tenth mission of the Challenger in 1986, the crew of seven perished in an explosion. The Challenger’s disaster can be traced back to numerous causes. The most famous investigation of the accident is the Roger report (officially known as the Report of the Presidential Commission on the Space Shuttle Challenger Accident), which

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revealed that the accident was caused by an engineering failure that had been found years prior. Other investigations cite the pressures on NASA to launch the Challenger despite caution and debates from engineers. The loss of the Challenger in January 1986 was a pivotal point for space science, with some arguing that the field was set back 38 years as a result (Launius, 1992).

With the Challenger disaster came the deterioration of the Shuttle Program: funding was lacking, and NASA was forced to take shortcuts and minimize costs for its shuttles while being incentivized to increase the number of launches. With these dangerous constraints, warning signs for malfunctions and complications were frequently ignored and the program could not retain all of its initial goals. Hundreds of experiments for the Shuttle program were indefinitely delayed and the program spent two years redesigning rocket boosters and changing its leadership structure (Launius, 1992).

"To investigate the events leading up to the disaster, a group of experts in physics, aerospace, spaceflight, and more was assembled and named the Rogers Commission.

Notable members of the commission included former US Secretary of State William Rogers, retired astronaut and first person to walk on the moon Neil Armstrong, first woman in space Sally Ride, and renowned theoretical physicist and Nobel laureate Richard Feynman."

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Next, NASA launched the Discovery Program in 1992 with the mission to explore our solar system.

Within the Discovery Program’s 13 missions, many milestones including the first spacecrafts to orbit and land on an asteroid (Near-Earth Asteroid Rendezvous, 1996), the first rover to land on another planet and on Mars (Pathfinder, 1996), and the first spacecrafts to return samples from a comet to Earth (Stardust, 1999) were completed. The Discovery Program is ongoing: The Lunar Reconnaissance Orbiter (launched in 2009) continues to orbit the moon and collect information, and the Insight (launched in 2018) studies the interior of Mars. As for the future of the Discovery Program, NASA has three missions planned: the Lucy (2021) will visit seven asteroids orbiting around Jupiter, the Psyche (2022) will study the mineral-rich asteroid 16 Psyche, and the MEGANE (2024) will investigate Phobos, the Martian moon (Harbaugh, 2020).

In 1987, Congress granted NASA funding to build the Endeavour (OV-105), a replacement for the Challenger. The name Endeavour was the winning submission name from elementary and middle schools across the US and represented British explorer James Cook’s first commandant ship whose mission was to observe the movement of Venus from Tahiti, ultimately leading to the accurate calculation of the distance between the sun and the Earth. The primary mission of the Endeavor was to capture and repair INTELSAT VI, a broken communications satellite. This mission

was the first to manage four spacewalks and the first to conduct a three-person spacewalk.

Before landing back on Earth safely, the crew was able to conduct a Protein Crystal Growth experiment in the microgravity conditions of space (Marconi, 2013).

The Science of Spaceflight Though the events of the Space Shuttle Challenger were widely covered in the weeks following the disaster, it was a mystery as to why the launch had failed. The country was sent into sorrow and depression; President Reagan postponed his State of the Union, schools were let out, the stock market tumbled. There are many factors that go into deciding and executing a launch, including the orientation of celestial bodies, the rotation of the Earth’s orbit, the amount of fuel loaded into the engine, the type of material used to build the shuttle, and many more important considerations: any of these can go wrong.

To investigate the events leading up to the disaster, a group of experts in physics, aerospace, spaceflight, and more was assembled and named the Rogers Commission.

Notable members of the commission included former US Secretary of State William Rogers, retired astronaut and first person to walk on the moon Neil Armstrong, first woman in space Sally Ride, and renowned theoretical physicist and Nobel laureate Richard Feynman (“THE SHUTTLE FINDINGS,” 1986).

The commission had their own schedule of interviewing engineers and executives at NASA, its contractors, and more, but Richard Feynman was one member that never liked abiding by the rigid and, in his opinion, inefficient processes of William Rogers.

Instead, Feynman conducted many of his own interviews and eventually discovered the cause of the Challenger disaster—the O-ring.

In many of his interviews with engineers who had worked on the shuttle, he discovered two large issues with NASA’s understanding of risk.

Firstly, NASA was using what are now known as product-based risk assessments (Altabbakh et al., 2013). These types of assessments involve assigning individual risk probabilities to the components of the final product; for example, an engineer would assign a failure probability of 1 in 100,000,000 to an individual screw as well as every other part of the shuttle. This tricked engineers into thinking that they were being thorough, but, in reality, it disillusioned

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them from the fact that the parts of the shuttle are interconnected. A failure in one spot can drastically increase the failure in another, so when looking at the individual failure probabilities, engineers at NASA and its contractors saw a near impossible fail rate.

However, when Feynman interviewed these people individually on what they predicted the failure rate of the space shuttle actually was on a holistic basis, they responded with the 1 in 50 to 1 in 200 range (Heimann, 1993). While these might be okay odds for a raffle, they are much too high when unnecessarily risking lives.

Though the improper interpretation of risk was one major problem with the design of Space Shuttle Challenger and its launch, the root cause of the problem was NASA’s failure to address a serious flaw in the design of the O-ring. The O-ring was used as a seal on the rocket booster and was vital to ensuring the structural integrity of the booster with its external fuel tank. The O-ring that was used was only cleared for temperatures above fifty degrees Fahrenheit.

On the day of the launch, the temperature dropped to the thirties, which weakened the sealant on the O-ring. Subsequently, the flame from the boosters passed through the ring and reached the external tank. Perhaps the most disturbing element of this failure by NASA was the fact that Feynman was not the first one to suspect that the O-ring design was flawed (“THE SHUTTLE FINDINGS,” 1986).

Roger Boisjoly, one of the head engineers at Morton Thiokol, along with several other

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engineers, found that the O-rings had failed multiple times during their testing. In several reports to his superiors, Boisjoly recommended that the O-ring be re-designed as the current design, if left alone, could put the astronauts’ lives in danger. Unfortunately, scheduled flight deadlines weighed heavily on the mins of NASA administrators in the mid 1980s, and this concern went unaddressed (Boisjoly et al., 1989). With the Soviets beating the United States in space exploration as well as Reagan’s plan to announce that one of the astronauts on the Challenger was a schoolteacher during his State of the Union address, after the team was in space, NASA entrusted that the failure probability of the individual parts was so low that a disaster would be impossible. As Feynman and the Rogers Commission found, not only was this view severely mistaken but the rationale for these safety considerations was fundamentally flawed. This mistake was so severe that it led Feynman to write Appendix F in the Rogers Commission report: an over 5,000word critique of the NASA safety protocol (“THE SHUTTLE FINDINGS,” 1986).

Figure 3: The above diagram depicts a cross-section of the field joints between the rocket boosters of the Challenger Space Shuttle. Letters “B” and “C” on the diagram point out the O-ring gaskets that failed on the day of the launch due to low temperatures, leading to the infamous disaster.

Following the incident, stocks prices fell. This was particularly true for those companies that had contracts with NASA. On January 28, 1986, building material company Martin Marietta fell 3%, aerospace company Lockheed Corporation was down 5%, and industrial manufacturer Rockwell International lost 6% (Sutter, 2016).

However, the NASA contractor that lost the most on that day was Morton Thiokol, the corporation that produced the flawed O-rings.

On January 28, 1986, Thiokol stock fell 12% (Blose et al., 1996). The only reason that the stock did not fall more that day was that the trading for the stock was halted to prevent selloffs much like those during the Great Depression (later, regulators installed circuit breakers to do this automatically). NASA contracts made up over 18% of Thiokol’s total sales, more than any other NASA contractor, but not far off from the 17.52% of Planning Research Corporation or 12.16% of Computer Sciences Corporation.

Planning Research stock barely lost anything while Computer Sciences stock actually resulted in a gain for the day (Blose et al., 1996)!

Therefore, while it can be assumed that some selloff was due to the disaster and assessment of Thiokol’s dependence on NASA contracts, it is believed that some astute traders identified the company’s heavy involvement in shuttle design and pinned the disaster on them, months before the Rogers Commission submitted their report to Ronald Reagan (Blose et al., 1996).

"Though the improper interpretation of risk was one major problem with the design of Space Shuttle Challenger and its launch, the root cause of the problem was NASA’s failure to address a serious flaw in the design of the O-ring."

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Figure 4: The image depicts a Soviet Rocket Thruster from 1963, one of the first propulsion systems of its kind that has now given rise to nuclear pulse projection, liquid-air-cycle, or nuclear-thermal rocket thrusters that are used today.

Source: Wikimedia Commons

"Aerodynamics requires calculating the physics behind virtually every point of space travel. Scientists must ensure that the shuttle is using its fuel efficiently upon liftoff, ascent, abort, and re-entry scenarios and that there is not too much stress on any one part of the shuttle."

While Feynmanâ&#x20AC;&#x2122;s understanding of the faults of the space shuttle could be derived simply from experimentation, intuition, and interviews, actually planning, building, and testing these structures requires a much deeper knowledge of the science of spaceflight. Engineers and scientists who work at NASA, SpaceX, Virgin Galactic, Blue Origin, and other innovation hubs for space travel often undergo years of schooling and practice in the fields of mathematics, physics, aerospace engineering, and more.

However, the key knowledge points that are fundamental to an aerospace engineer's work are propulsion, aerodynamics, performance, and aircraft stability (Corda, n.d.).

Studying rocket propulsion is simply understanding how to make the rocket move the spacecraft forward. Engineers must build a device that can overcome both gravity and the drag of the atmosphere. Propulsion systems began as propellers on airplanes and quickly evolved into jet engines during the Second World War. Now, many space shuttles and satellites use more than a dozen rocket engine thrusters as their propulsion systems. These propulsion systems mix fuel with oxidizers (e.g., liquid hydrogen and liquid oxygen) in order to stimulate quick combustion that propels large spacecraft forwards (mars.nasa.gov, n.d.). Engineers measure key metrics including propulsive efficiency, engine performance, and engine noise (Govinda Raju, 2009).

Aerodynamics is a field of aerospace engineering that has greatly improved with the invention of computers. Aerodynamics requires calculating the physics behind virtually every point of space

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travel. Scientists must ensure that the shuttle is using its fuel efficiently upon liftoff, ascent, abort, and re-entry scenarios and that there is not too much stress on any one part of the shuttle. For instance, scientists must estimate the drag acceleration and relative velocity of the shuttle upon re-entry and protect against an undershot (which can bring high temperature and high drag), an overshot (which can bring loss of control from lack of sufficient drag), and a pressure limit to the shuttle. This field has rapidly improved with computational methods that make the calculations much more precise, but scientists still must ensure that their margin of error is well within safety guidelines for the spacecraft (Bordano et al., n.d.).

Spaceflight is a delicate practice. The rocket needs to attain an absolute velocity to escape gravity, but all the required scientific instruments on space missions mean that engineers have to work with heavy loads.

For example, the space shuttle on a typical mission weighs around 4.5 million pounds.

The challenge is to minimize additional weight (as a greater mass translates to a higher thrust requirement) and still retain enough propellant to power the rockets to the required speeds.

To tackle this, scientists employ two main strategies: using multiple phases of flight and using propellants with specific characteristics that make them ideal for spaceflight. Many rockets - such as the Pegasus XL currently used to launch satellites into space and the Saturn V that first put men on the moon - are designed to use three phases in their ascent into space.

By using three phases, the rocket is able to achieve higher velocities.

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Figure 5: The image shows the attachment of Solid Rocket Boosters to a rocket. The Solid Rocket Boosters provide additional thrust during liftoff.

Source: Wikimedia Commons

The first phase of spaceflight is liftoff. Large rockets called the Solid Rocket Boosters (SRBs) are used to propel the rocket and provide the thrust needed to lift the shuttle off the launchpad. These SRBs operate in tandem with the main rocket engines for the first two minutes to give the additional thrust necessary to escape Earth's gravitational pull. The SRBs support the system's entire weight - the shuttle, the fuel tanks, the orbiter, and additional rockets - and provide an estimated 71 percent of the total thrust (Kaur et al., 2014). To achieve such amounts of thrust, the solid rocket boosters have to be powerful and therefore massive. It soon becomes necessary to drop the SRBs after all their propellant is depleted. This is done at an altitude of about 45 km. Once released, the boosters descend on parachutes, usually into the ocean, and are recovered for reuse (Kaur et al., 2014).

The next phase of spaceflight is fuel tank separation. The external tank's three main components are an oxygen tank, a hydrogen tank, and an inter-tank connecting the two propellant tanks, which houses processing equipment. When the SRBs separate, the orbiter, with the main engines still burning, carries the external tanks up to a height of around 113 km, at which point all the propellant in the tanks is fully used. The empty tanks are then jettisoned and fall in a pre-planned trajectory. Unlike the SRBs, the fuel tanks are not recovered for future reuse (Kaur et al., 2014). Once in space, the shuttle orbiter houses the astronauts for 7 to

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14 days. The orbiter can be oriented with the cargo bay doors facing toward or away from the Earth, depending on the mission's objectives.

Another unique challenge presents itself during re-entry into Earth’s atmosphere. The orbiter will usually be flown nose-down until a specific height. The crew will then fire up the OMS engines to slow the orbiter down. It then takes about 25 minutes to reach the edges of the atmosphere. During this time, RCS thrusters are fired to turn the orbiter so that it is moving nose-up again like it did during ascent. The leftover fuel in the forward RCS thrusters is burned as a safety precaution because this area of the orbiter experiences the highest heat in re-entry. During re-entry, the orbiter is moving at about 17,000 mph, and air friction builds up to about 1650°C (3000°F). To counter this, the orbiter is designed with a coating of ceramic insulation. At around 610 meters above the ground, the commander pulls up the nose to slow the descent rate. A parachute then helps stop the orbiter. After landing, the orbiter is powered down and taken for servicing (Kaur et al., 2014).

"The orbiter will usually be flown nose-down until a specific height. The crew will then fire up the OMS engines to slow the orbiter down. It then takes about 25 minutes to reach the edges of the atmosphere.

During this time, RCS thrusters are fired to turn the orbiter so that it is moving nose-up again like it did during ascent."

Despite the enormous complexity of rocket flight, the journey of a rocket from the surface of the Earth to Earth’s orbit may be grasped with a basic understanding of Newtonian mechanics. Consider a rocket on the launch pad. It remains at rest because the force of gravity acting downwards towards the center of the Earth is balanced by the normal force of

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the launch pad pushing up on the rocket from below. The static state of the rocket is described

by Newton’s first law: Every object persists in its state of rest or uniform motion in a straight line unless it is compelled to change that state by forces impressed on it.

In order to get the rocket into the air, there needs to be a strong upward force to unbalance the equilibrium of the gravitational and normal forces and accelerate the rocket upward. This upward acceleration is provided by thrust – the force produced by the ignition of fuel in the rocket’s engine (Hall, 2015). Once the rocket lifts off above the ground and begins soaring into space, its behavior may be described succinctly

by Newton’s second law: the net force acting on the rocket is equal to its mass multiplied by its acceleration.

"The dynamics of rocket flight are complicated because a rocket is a body of changing mass; as it climbs farther and farther into space, it burns more fuel, and the consequent loss of mass is significant.

The typical mass fraction of a rocket – its propellant mass divided by its total mass – is 0.8, meaning that 80% of the rocket mass is propellant."

The dynamics of rocket flight are complicated because a rocket is a body of changing mass; as it climbs farther and farther into space, it burns more fuel, and the consequent loss of mass is significant. The typical mass fraction of a rocket – its propellant mass divided by its total mass – is 0.8, meaning that 80% of the rocket mass is propellant (Man-Vehicle Laboratory MIT, 1996).

This means that over time, the gravitational force (equal to mass times the gravitational acceleration constant) decreases, and the force in the upward direction further outweighs that in the downward direction. Thus, the acceleration of the rocket increases steadily as it climbs. The rapid burning of fuel is critical so that the rocket can accelerate to a high enough speed. Entering lower Earth orbit requires a speed of over 28,000 km/hour. Exiting Earth’s orbit requires a much higher speed of 40,250 km/hour (Benson, 2014).

Like a rubber balloon, a rocket is a chamber enclosing gas under pressure. The difference is that while a balloon is filled with the carbon dioxide exhaled from one’s breath, or on some occasions the inert gas helium, rocket combustion chambers are mixing sites for highly combustible fuels – ones that will react explosively and produce large quantities of gas. The release of this gas is what provides the rocket with thrust. Newton’s third law, that for every action [in this case the release of gas from the bottom of the rocket] there is an equal and opposite reaction [the propulsion of the rocket upwards into space]” explains this phenomenon (Benson, 2014).

Rocket propellant is not just fuel, but the combination of fuel and oxygen, which is

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necessary for the fuel to burn. Propellant comes in several varieties. It may be solid, in which case the fuel is typically a hydrocarbon. Alternatively, it may be a liquid, typically kerosene or liquid hydrogen mixed with oxygen. The components of a solid propellant are usually held together in a single loading chamber, whereas the components of a liquid propellant (liquid fuel and liquid oxygen) are held separately. In either case, the propellant is forced through a nozzle or nozzles into the combustion chamber where the fuel ignites. The resulting gas is then allowed to escape through a nozzle at the bottom of the rocket (Man-Vehicle Laboratory MIT, 1996).

There are different classifications of rocket propulsion engines depending on the gas acceleration mechanism, the energy source, and the thrust level per unit mass (MartinezSanchez, 2005). All of these classifications hint at the physics and chemistry behind rocket propulsion, which inform the choice of a suitable propellant. By gas acceleration mechanism, a rocket engine can be classified as either (1) thermal if it uses pressure to drive gas, (2) electrostatic if it uses electrostatic force to accelerate gas across a magnetic field, or (3) electromagnetic if it uses a combination of electric and magnetic fields across an electric conductor to create an electromagnetic force used to accelerate the gas. By the type of energy source used to drive propellant, a rocket engine can be either chemical, nuclear, or solar.

A rocket engine can also either be high thrust or low thrust (Martinez-Sanchez, 2005). For any rocket system, the propellant choice will depend mainly on the type of engine being used. Propellants can be either solid, liquid, or hybrid (Braeunig, 2008).

Solid propellants are a mixture of solid compounds (fuel and oxidizer) that burn at a rapid rate, producing hot gases. These hot gases are then forced through a tight airway to produce thrust. Solid propellants can be homogeneous or composite (MartinezSanchez, 2005). Homogeneous propellants consist of either a single compound with oxidation and reduction capabilities (known as simple base) or a mixture of nitrocellulose and nitroglycerine (known as double base), on which plasticizer is added. Homogeneous propellants do not produce any traceable fumes, making them ideal for applications that require secrecy such military operations.

Homogeneous propellants are also commonly used to perform subsidiary actions, such as jettisoning spent parts while transitioning

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between spaceflight phases (McCormack, n.d.).

On the other hand, composite propellants use a crystallized or finely ground mineral salt as an oxidizer and an element, usually aluminum, as fuel. The oxidizer will make up about 60% to 90% of the propellant, with the fuel constituting as little as 10% of the total mass. The propellant is contained in a polymeric binder such as polyurethane, which is also consumed as fuel. Sometimes additional compounds are added as catalysts. Composite propellants are classified by the type of binder used, the most common of which are olybutadiene acrylic acid acrylonitrile (PBAN) and hydroxy-terminator polybutadiene (HTPB). (Braeunig, 2008).

For liquid propellant rockets, the different components of the propellant (fuel and oxidizer) have to be stored in separate tanks due to higher volatility. During space flight, the separate fluids are pumped into a combustion chamber, mixed, and combusted to produce thrust. This set-up leads to a significant advantage over solid-propellant engines: the controlled flow and combustion of the propellant allows liquid-propellant engines to be throttled, stopped, and even restarted.

Several features specific to different liquid propellants are significant in deciding which liquid propellant to use. A suitable liquid propellant should have a high specific impulse (speed of exhaust gas ejection), high density, ability to withstand high storage temperatures, low toxicity, and low corrosion.

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Liquid propellants can be either petroleumbased, cryogenic, or hypergolic. Petroleumbased propellants are obtained from crude oil and mostly consist of hydrocarbon liquids and gases. The most common petroleum-based rocket fuel is a highly refined kerosene called RP-1, which is oxidized by liquid oxygen. On the other hand, cryogenic propellants are usually made up of liquefied gases. For example, liquid hydrogen and liquid oxygen are often used as a fuel-oxidizer pair. The caveat with cryogenic propellants is that such gases only exist as liquids at extremely low temperatures. Hence, the fuel tanks must be accordingly configured, which poses both a challenge and a safety hazard in case of leakage or badly sealed storage tanks (McCormack, n.d.). Hypergolic liquid propellants consist of an oxidizerfuel pair that reacts upon contact and does not need external combustion. Hypergolic reactions are easy to start and restart, which is ideal for spacecraft maneuvers. Furthermore, hypergolic fuels remain liquid at standard temperatures and thus do not require specially designed storage tanks or have the risks posed by cryogenic propellants (Braeunig, 2008).

Figure 6: The image shows the compartmentalization of fuel tanks in liquid-propulsion systems. The fuel and oxidizer are stored in separate tanks due to high volatility - unlike in solid propulsion systems where the fuel and oxidizer are stored in the same chamber.

Hybrid propellant engines use a mixture of solid and liquid fuel-oxidizer pairs. The fuel is usually solid. The liquid oxidizer is then pumped into the fuel storage chamber, which also acts as the reaction chamber. Hybrid propellants generally offer the combined advantages of solid and liquid propellants, such as high performance (an advantage of solid-propulsion systems) and the ability to control the combustion and reaction rates (a benefit of liquid-propulsion systems). (Braeunig, 2008).

"Even with the myriad of mechanical complexities confronted during spaceflight, physiological stress on astronauts remains one of NASA’s most significant concerns."

Even with the myriad of mechanical complexities confronted during spaceflight, physiological stress on astronauts remains one of NASA’s most significant concerns (Abadie et al., 2020). The first challenge to overcome is liftoff, when astronauts experience gravity forces up to twice that which a typical human can withstand without training (Lee et al., 2015). The perpendicular acceleration places particular strain on the head and neck, and blood can quickly gather near the bottom of the body. To mediate these challenges, astronauts undergo extensive training in “g-force withstanding,” during which they slowly build their capacity to remain conscious—even as blood fails to reach the upper regions of the body, which often results in temporary blindness (Burton, 1988).

Source: Wikimedia Commons

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"Unsurprisingly, liftoff is only the beginning when it comes to the physiological challenges of space flight. Even shorter (1-3 month) visits to space take a harsh toll on the bodies of astronauts. A few of the most worrying physiological effects of space travel include muscle atrophy and losses in bone density."

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Unsurprisingly, liftoff is only the beginning when it comes to the physiological challenges of space flight. Even shorter (1-3 month) visits to space take a harsh toll on the bodies of astronauts. A few of the most worrying physiological effects of space travel include muscle atrophy and losses in bone density. Weightless existence inside the spacecraft leaves astronauts lacking the day-today strain on the musculoskeletal system that Earth’s gravity provides (Orwoll et al., 2013).

Consequently, even with a strict requirement of two hours of exercise per day while in space, astronauts on 1-3 month missions usually require 2-3 years to recover the muscle mass and bone density lost during their time away from Earth (Fitts et al., 2010). Other physiological concerns include severe deficits in the quality and quantity of sleep, decreased production of red blood cells, fluid retention in the head and chest, sub-optimal nutrition, and even neurological changes that some scientists warn could lead to the early onset of neurodegenerative conditions like Alzheimer’s disease (Acharya et al., 2019).

As space explorations lengthen in duration, understanding the physiological effects of prolonged periods of weightlessness has become a central focus of NASA scientists. However, these investigations survey astronauts’ wellbeing in the best possible scenario: the vacuumsealed and carefully monitored atmospheric conditions of a fully functioning spacecraft.

Outside the craft, environmental conditions are nothing short of deadly. Spacesuits must protect their occupants from flying bits of space junk called micro-meteors, harmful ultraviolet rays, and extreme temperatures—all in addition to the vacuum conditions that can boil bodily fluids and deprive an astronaut of oxygen after only moments of exposure (Abadie et al., 2020). In the event that an astronaut did require medical attention while in space, their crewmates serve as their care providers. Astronauts undergo extensive training in first aid and emergency medical care for this purpose, and spacecraft are outfitted with medical care items ranging from liters of saline to high-quality ultrasound machines (Stewart et al., 2007). As space flight continues, NASA anticipates noteworthy advances in the quality of on-craft medical care—advancements, like ultra-high-speed telemedicine and programmable surgeons, that might be just as beneficial in under-resourced communities down on Earth as they are in the remote expanse of space.

History Continued: The End of the Shuttle Program and the Genesis of Private Rocketry Despite the major setback that the Challenger disaster caused the shuttle program, it was only two and a half years later on September 29, 1988 that the Discovery launched a communications satellite which replaced the one lost in Challenger. With Ronald Reagan’s note that “America is back in space,” this relaunched a productive era of American space travel (Norcross, 2019). In the following year, 1989 saw the deployment of the Magellan to Venus and the Galileo to Jupiter by the shuttle Atlantis, providing invaluable future data on extraplanetary function and marking the first interplanetary mission in nearly eleven years.

Perhaps more invaluable was Discovery’s launch of the Hubble Telescope on April 24, 1990, whose later research on background radiation led scientists to estimate the universe’s age at 14 billion years and conclude dark matter to be the driver of the universe’s expansion, among other discoveries (Stillman, 2020). Six years later, Columbia would be launched, carrying the largest satellite ever launched, the Chandra X-Ray Observatory, which expanded humanity’s view of the physical universe (Howell, 2018).

The International Space Station was the next large step in human space exploration. What would become a symbol of international cooperation was first ordered as an American project by Ronald Reagan in 1984 to be completed within the decade (ISS National Laboratory, n.d.). However, the Space Station, which had originally been a U.S. project dubbed Freedom, was changed going into the 1990s to expand international cooperation and increase funding, notably incorporating Russian plans, but also drawing on collaboration from Japan and the European Space Agency (Harland, 2020). The 1993 invitation for Russia to join the international effort was particularly significant following the collapse of the Soviet Union just prior, as this effectively united the two main contenders in the “space race” facet of the cold war. However, it was not until November 2, 2000 that the American astronaut Bill Shepherd and two Russian cosmonauts, Yuri Gidzenko and Sergei Krikalev, became the first of a continuous, rotating crew to attend the assembled station more than a decade in the making (ISS National Laboratory np).

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Although much of the important work on the ISS focuses on scientific study, a primary task of crewmembers is the simple maintenance of the facility. Indeed, following the 2003 Columbia shuttle disaster to be discussed later, the ISS reacted by reducing the crew size to two members who were mostly relegated to maintaining the station (Harland np). Construction subsequently resumed in 2006 with notable additions including the American Destiny module, which can simulate a nearly weightless environment for further study on the station (Harland 2012; Harland 2020). Since its inception, crewmembers have always remained on the station to maintain the system and perform experiments, with replacements of personnel every three months in the form of astronauts flying back on the Russian Soyuz shuttle to be sent back to the station with a new crew. Some of the more recent experiments have included research on capillary flow function aimed at improving and cutting costs of infectious disease tests (e.g., those for HIV/AIDS) (Gaskill, n.d.). Although the history of the ISS has largely been one of success, both scientifically and geopolitically, it, too, has an expiration date for government funding. American funding is set to expire in 2024, which is the same year NASA projects to land again on the moon. Notably, though, private space companies will be allowed to potentially use the station for commercial purposes (Weiterung, 2019).

In 2003, NASA experienced its first loss of life since the Challenger disaster. The seven astronauts aboard the Shuttle Columbia had completed their mission, restocking the ISS and staging a series of scientific experiments en route. They had studied the effect of space conditions on bacterial respiration (cellular utilization of oxygen and organic compounds to produce chemical energy) and assessed their own physiological conditions while riding on the shuttle. The mission made it as far as orbital reentry before the shuttle broke apart and killed everyone aboard (Cowen, 2003). It was a catastrophe of a different nature; less sudden and immediate than the Challenger explosion – the Columbia astronauts could literally feel the warmth of Earth’s embrace – but no less shocking and bitter a tragedy. In the 400-page report that detailed the astronauts’ plight in their final seconds, it was determined that the depressurization of the shuttle would have rendered them all incapacitated within seconds and unable to take any corrective action as the shuttle began to break apart. In reality, there

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was nothing the astronauts could have done even if they had regained consciousness. The report found no evidence whatsoever of crew member error (“Report: Columbia Astronauts Killed,” 2008).

As was the case after the Challenger disaster, NASA put a halt to all further shuttle launches and set up a commission to investigate what went wrong. The investigation centered around a piece of insulation surrounding the fuel tank.

The insulating foam had broken free during launch and punched a hole in the heat shield covering Columbia’s wing. This is thought to have caused the disintegration of the shuttle upon re-entry, as it would have allowed for superheated atmospheric gas to penetrate the wing (“Report: Columbia Astronauts Killed,” 2008). Columbia was the oldest existing shuttle at the time, and in the aftermath of its explosion, many suggested that NASA should have either refurbished or decommissioned Columbia long before its eventual demise (Lawler et al., 2003).

Alongside this critique, the long-standing criticism of the Shuttle Program’s mission – that it was far too expensive and inefficient to allow for its stated aim of frequent, regular launches – was spoken with even greater force (Logsdon, 1986; Center for the Study of Technology and Society, 2006).

"On the day of the Columbia disaster, President Bush vowed that “our journey to space will go on.” And so it did.

In the aftermath of the disaster, there was broad bipartisan consensus that NASA ought to continue receiving public support, but with a new focus on enhanced safety standards and new technology that would make flights safer and more capable of delivering On the day of the Columbia disaster, President payloads or gathering Bush vowed that “our journey to space will scientific data." go on.” And so it did. In the aftermath of the disaster, there was broad bipartisan consensus that NASA ought to continue receiving public support, but with a new focus on enhanced safety standards and new technology that would make flights safer and more capable of delivering payloads or gathering scientific data (Lawler et al., 2003). In 2005, shuttle flights resumed. The official vision birthed out of the Columbia Disaster, set forth by Bush in his “Vision for Space Exploration” (2006), called for the completion of the ISS and retirement of the shuttle program by 2010. Its replacement was to be the smaller, more cost-effective Crew Exploration Vehicle (CEV) (The New Atlantis, 2006).

Despite these intended changes, NASA’s budget was increasingly strained. Its funds were spread thin to cover both the aging shuttle program and the new CEV program at once – with significant funds also going towards ISS construction (which was not completed until 2011), planetary probes (Cassini, Messenger, New Horizon) and Mars rovers (Spirit,

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Figure 7: An image of SpaceX’s Dragon spacecraft, used to carry seven passengers or cargo between Earth and its orbit.

Source: Wikimedia Commons

Opportunity) (The New Atlantis, 2006). The onset of the Great Recession in 2008 further diminished prospects of a budget increase to support NASA’s space-bound endeavors. Obviously, there were plenty of problems that required government funding on Earth. In 2011, the Shuttle Program came to an end, with the final flight of Atlantis in July of that year. It marked the conclusion of a three-decade-long program that supported 133 successful launches (Witze, 2011). This was not the end of American space travel, however, but the conclusion of a single chapter in a long and storied history. In fact, a new era in American Space Flight had its roots well before the last shuttle launch.

The New Titans of Space Travel SpaceX

"Musk has pursued his goal of decreasing costs and increasing the reliability of spaceflight by developing reusable rockets and launch systems. At the date of writing, Falcon 9, SpaceX’s reusable,

Elon Musk, widely known as the founder of Paypal and Tesla, extended his business dominance to space when he founded and became the Chief Executive Officer of Space Exploration Technologies Corporation (SpaceX) in 2002. SpaceX has the broad mission of making spaceflight more inexpensive and reliable with Musk’s ultimate goal being the colonization of Mars. SpaceX’s achievements are extensive; it is one of the first private companies to venture into the world of spaceflight. Some of SpaceX’s most notable feats include being the first private company to successfully launch, orbit, and recover a spacecraft, send a spacecraft to the International Space Station, send a human-rated spacecraft to space, and autonomously dock a spacecraft to the International Space Station (SpaceX, n.d.). These accomplishments are all more impressive when considering that Musk never received formal training in rocket science, instead graduating with degrees in economics and physics from the University of Pennsylvania.

His aerospace consultant, Jim Cantrell, claims that Musk taught himself everything he knew by reading textbooks and talking to those in the industry (Feloni, 2014).

Musk has pursued his goal of decreasing costs and increasing the reliability of spaceflight by developing reusable rockets and launch systems. At the date of writing, Falcon 9, SpaceX’s reusable, two-stage rocket has had 94 total launches, 55 successful landings, and 40 reflown rockets. The initial launching of the Falcon 9 used uses Merlin engines, one of SpaceX’s engine families designed for its Falcon launch vehicles. Those Merlin engines used in the initial launch were specifically designed for a sea-level launch. Once beyond the dense atmosphere, the

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Merlin Vacuum Engine then propels Falcon 9 to its orbit. The first and second stages separate, and the Merlin Engines are recovered for reuse (SpaceX, n.d.). Lastly, the payload is released for its final destination. If the payload is a satellite, it is released with a protective case. If the payload is a crew or cargo, they are released in Dragon, SpaceX’s spacecraft intended to carry humans and cargo from Earth to and from orbit and, in the future, beyond. Both the protective fairing and the Dragon spacecraft can be reused; the Dragon has had 23 total launches and 9 reflown missions to date (SpaceX, n.d.).

Along with Falcon 9 and Dragon, SpaceX has two newer vehicles, Falcon Heavy and Starship.

Falcon Heavy is considered the world’s most powerful rocket and can be used to transport almost forty-thousand pounds of payload to Mars and even greater masses for shorter destinations. The Falcon Heavy uses 27 sea level Merlin engines and has the capacity to produce more than five million pounds of thrust at liftoff, the equivalent of about eighteen 747 aircrafts at full power. The Starship rocket currently has not yet been tested, but it is expected to allow for interplanetary travel to Mars and beyond with a payload capacity even greater than that of Falcon Heavy (SpaceX, n.d.).

Unlike other space companies, SpaceX has seen much success in its operations, with about two billion dollars in revenue for 2019 (CBS News, 2018). Virtually all revenue comes from SpaceX making cargo deliveries to the International

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Figure 8: The New Titans of space flight: Jeff Bezos, Elon Musk, and Richard Branson Source: Wikimedia Commons

Space Station, but Musk recently started the “ridesharing” program for space that allows for multiple cargo delivery contracts to be filled by one spaceflight. While this is an exciting development for SpaceX, there is much more anticipation around the completion of Starship.

Starship is expected to be completed in the early 2020s and replace Dragon and Falcon 9, thus becoming SpaceX’s main form of transportation (SpaceX, n.d.).

Blue Origin SpaceX’s most direct competition is Blue Origin, a rapidly growing rocketry company founded and funded by Amazon CEO Jeff Bezos. Though Bezos keeps his interests in space generally quiet, he has stated before that Blue Origin is his most important work. The company was founded in 2000 in Kent, Washington, has a launch facility in West Texas, and also has a lease in Cape Canaveral (“Everything you need to know,” 2019). For the first several years of its existence, the company remained largely unknown and did not make any revenue.

It is entirely financed by Bezos’s personal investment; in 2017, the CEO announced that he had been selling one billion dollars in Amazon stock annually to fund Blue Origin’s work (Fleur, 2017). Blue Origin’s goal is to give humans access to space affordably and reliably.

Bezos does not believe that humans should entirely abandon Earth in favor of interstellar colonization; rather, he believes that space travel and exploration is a necessary next step in maintaining life on Earth. He envisions that humans will harvest resources from space to make sure that progress on Earth does not become stagnant and believes that through space colonization, Earth will have enough resources to support one trillion individuals (“Jeff Bezos: reusable rockets,” 2017).

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Blue Origin has two famous rockets. The first is New Shepard, which is being developed as a sub-orbital rocket meant for tourism and research. Though it can be piloted remotely, it is meant to carry passengers up to around 100 kilometers into the air. Early stages of development began in 2006, and its first flight was in April of 2015. This test was deemed a partial success by the company - the flight itself was successful, as it reached 93.5 kilometers in altitude. Additionally, the developers were able to recover the capsule. However, the propulsion module was unable to be recovered after the flight due to a failure in the hydraulic system, so the vertical landing of the shuttle was compromised (“Blue Origin’s New Shepard,” 2015). In November of 2015, Blue Origin launched a second version of New Shepard.

This flight was a complete success. Not only was the rocket able to reach an altitude of over 100 kilometers, but both the capsule and the booster system worked, allowing the rocket to successfully perform a vertical landing. The flight was a historic one - it was one of the first rockets to perform this kind of landing successfully (“New Shepard: Bezos Claims Success,” 2015). Just 61 days later, the rocket was able to be launched again. Ultimately, this second version of New Shepard launched and successfully landed for relaunch 5 times before it was retired (“Blue Origin successfully tests New Shepard abort system,” 2016). New Shepard 3 was given several modifications to increase thermal protections and reusability; it was meant only to ship cargo and was not intended for any kind of passenger or commercial use. New Shepard 3 was flown from 2017 to 2019 and has flown a total of four times (“Blue Origin Delays Next New Shepard,” 2018).

The fourth version of New Shepard is currently under development - it is the version that Blue Origin intends to be its commercial rocket, and the first flight is expected to occur in 2021.

"Blue Origin has two famous rockets.

The first is New Shepard, which is being developed as a sub-orbital rocket meant for tourism and research. Though it can be piloted remotely, it is meant to carry passengers up to around 100 kilometers into the air."

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Figure 9: WhiteKnightTwo is a twin mast aircraft used by Virgin Galactic to carry SpaceShipTwo through the atmosphere.

SpaceShipTwo is positioned on top of the middle wing, and the combined structure flies from horizontal takeoff to space.

Source: Wikimedia Commons

"The technology most similar to that of Blue Origin is Virgin Galactic’s.

Also focusing on sending customers into suborbital space, Virgin Galactic was founded in 2004 by Sir Richard Branson, the founder of Virgin Atlantic airlines and the Virgin Group."

Blue Origin’s second main rocket is New Glenn.

The company started to design New Glenn in 2012 and originally intended for its maiden flight to be in 2020. In 2018, they announced that they would be pushing back the first flight to 2021.

Like New Shepard, New Glenn is meant to have a reusable first stage booster. This booster is meant to push the astronauts to suborbital space, where there would be stage separation.

An upper stage booster would then take the company’s Space Vehicle capsule, which would carry astronauts and cargo goods, into orbit,.

Both the first stage and upper stage booster would return to Earth to be refueled and reused. (“Blue Origin - About Blue,” n.d.).

Blue Origin still has a ways to go before it catches up to SpaceX. However, as it rapidly approaches several critical deadlines in the upcoming years, it will be able to directly compete with Musk and his rockets and propel the modern Space Race into a new age.

Virgin Galactic The technology most similar to that of Blue Origin is Virgin Galactic’s. Also focusing on sending customers into suborbital space, Virgin Galactic was founded in 2004 by Sir Richard Branson, the founder of Virgin Atlantic airlines and the Virgin Group. Branson started Virgin Galactic to materialize his interest in space, and set out to not just control the process of sending customers to space but also the process of building the rockets to do so. In 2005, he, along with Burt Rutan, founded The Spaceship Company, which designs and manufactures airships for space

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travel. The Spaceship Company was eventually established as a subsidiary under Virgin Galactic (Encyclopedia Britannica, 2020).

Virgin Galactic’s main assets include the main spaceship, SpaceShipTwo; the carrier aircraft that will carry SpaceShipTwo, WhiteKnightTwo; and the location that will train and launch customers into space, Spaceport America. After launch, a WhiteKnightTwo aircraft is used to carry SpaceShipTwo through the high density atmosphere. Using the larger WhiteKnightTwo for its 4 turbofan engines that each supply 6,900 pounds of force at launch, Virgin Galactic can reduce the total energy needed for launch.

This reduced energy allows the aircraft to launch more smoothly and horizontally, like an airplane, instead of vertically like traditional spacecrafts and their direct competitor Blue Origin (Virgin Galactic Holdings, Inc., 2020).

But Branson’s long history in the aviation industry has led his words to carry more believability than they should. In 2007, an explosion during rocket testing of SpaceShipTwo was expected to severely set back the timeline of space flight (David, 2007).

However, Branson claimed in July of 2008 that the maiden voyage would occur by the end of 2009. Then, in October 2009, Branson promised that flights would start within two years. In December of 2009, Branson claimed that flights would begin in 2011, and in April 2011, Branson announced that flights would start 18 months later (Garside, 2014). The promises have continued; Branson currently projects that flights will be ready by the summer of next

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year at the latest, and even critics have to admit that he might actually be right this time. By 2019, WhiteKnightTwo had already undertaken over 250 test flights, over 50 of which were with SpaceShipTwo. At the end of 2020, Virgin Galactic expects to complete two manned tests of SpaceShipTwo and receive its license from the Federal Aviation Administration (Virgin Galactic Holdings, Inc., 2020). So, while Branson has been known to over-promise and underdeliver, that dynamic could very well flip soon.

One of the most unique defining features of Virgin Galactic that sets it apart from other space companies is that it is a public company, meaning that anyone can invest in the company’s stock. It all started in 2017 when Social Capital Hedosophia was listed as a publicly traded Special Purpose Acquisition Company (SPAC). A SPAC is an individual or a group of individuals that decides to become publicly traded, with anyone allowed to invest, but does not actually have a product to sell.

It may sound foolish for people to invest in a company without a product, but SPACs like Social Capital Hedosophia enter public trading in order to secure funding to then acquire a private company that takes its place in the public sector, meaning the shareholders now own part of the new public company and could profit if the SPAC acquires a successful company.

One important detail to understand how Virgin Galactic became a publicly traded company is that they are currently losing significant amounts of money. The company’s main expected service, spaceflight, is not ready, but they have to keep funding research and development to make their plans a reality. In 2019, the company realized that they had to start earning revenue or else they would quickly run out of money. As a result, they started providing engineering services in addition to their core spaceflight development operations, but they were only able to generate about $4 million in revenue in 2019 and currently no revenue in recent quarters. Compared to the over $210 million they lost from their operations in the same year, $4 million is extremely small. With a little over $450 million left in the bank even after becoming publicly traded, Virgin Galactic has only about two to three years of funds left until they run out (Virgin Galactic Holdings, Inc., 2020).

This pattern of losing money started at and has continued since its founding. Branson never

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expected to take so long until spaceflight, so when Social Capital Hedosophia approached him with the offer to buy his company and take it public, Branson accepted at the end of 2019. This acquisition infused the company with much needed cash and created the first publicly traded spaceflight company (Renaissance Capital, 2019). With the company being publicly traded, many space enthusiasts, including many on Wall Street, have flocked to the stock and pushed the price upwards. In September 2020, when the stock was trading at about $16, analysts at Bank of America, a major banking firm, and Susquehanna, a leading global quantitative trading company, both rated Virgin Galactic stock as a ‘buy’. Bank of America actually set a hefty price target of $35. These ratings, along with buy ratings from almost all other Wall Street firms that cover the stock (Morgan Stanley, Vertical Research Partners, Cowen, UBS, Credit Suisse, and Alembic Global Advisors), have dramatically increased the price (Sheetz, 2020). However, these high price targets are mainly driven by the high price of a seat on a Virgin Galactic: $250,000. The belief is that once Virgin Galactic develops the technology, they only need a few sales to return a huge profit. The company also already has a couple hundred reservations for seats, making shareholders optimistic. However, there are many risks. Primarily, there is risk that the technology will never be developed. Even if it is developed, the company can suffer from increased regulation, fierce competition, and a loss of public favor if one of the launches fails.

These concerns led Goldman Sachs analysts to recommend a hold on the stock, resulting in the only non-buy rating from Wall Street firms.

So, while some Wall Street firms can price the stock at prices 100% over its current value, it essentially comes down to one question: do you believe what Branson is promising?

"One of the most unique defining features of Virgin Galactic that sets it apart from other space companies is that it is a public company, meaning that anyone can invest in the company’s stock."

Launching Advancements in Science and Technology Down on Earth Technological Advancements Born in Space Though space exploration’s advancements led to well-known innovations in healthcare and the environment, potentially the most widelyknown and underappreciated inventions have come from the technology field. The most well-known advancement from research and development in space programs is modern communication with satellites. Because of space exploration, NASA and other government organizations around the world launched satellites into space and decided to allow

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Figure 10: The image depicts the MS-50 headset, the lightweight headset developed by Courtney Graham and Keith Larkin for pilots of United Airlines. Graham and Larkin soon after worked with NASA to incorporate this technology into the astronaut helmet, creating the first wireless headset.

Source: Wikimedia Commons

"Above all, potentially the most underappreciated technological advancement arising from space exploration efforts is the cell phone camera.

The Jet Propulsion Laboratory (JPL), a laboratory owned

by NASA to house its cutting-edge rocketry research, was actually the initial site for the technology of photosensors and light signals that would then be developed into the digital camera built

by Eastman Kodak in 1975."

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companies and other government organizations to use the satellite bandwidth to facilitate cell, Internet, GPS, and other types of communications (Garner, 2017). Without these introductions, we certainly would not be as advanced as we are today. In fact, the enthusiasm behind satellite usage in Earth Internet has given rise to NASA starting its development of a â&#x20AC;&#x153;Space Internet.â&#x20AC;?

The goal is to use Laser Communications Relay Demonstration to facilitate faster communications between shuttles and Earth; the technology builds upon the past Lunar Laser Communications Demonstration that was effective at large distances and widely successful in demonstrating beyond low-Earth orbit highdata-rate laser communications. However, the most interesting advancements stemming from space travel and NASA in particular are those that are unknown to most individuals who use them every day (Garner, 2017).

One advancement in technology spurring from space exploration is modern water purification systems. While this technological advancement goes unappreciated, many of the water purification systems in developing nations use technology originally developed for NASA (Marconi, 2004). It started in the 1960s and 1970s when NASA wanted to purify drinking water for the Space Shuttle, and turned to the small Myrtle Creek business, Umpqua Research Company.

The company developed an electrolytic silver iodizer called the Microbial Check Valve (MCV) cartridge. The company later developed the Regenerable Biocide Delivery Unit that extended the durability of the cartridge so that it could be used more than 100 times before replacing. The technology was so successful in serving astronauts that it has since been used on every Shuttle flight, and, in 1993, Umpqua Research was selected as the recipient of NASAâ&#x20AC;&#x2122;s Government and Commercial Invention of the Year awards (Marconi, 2004).

Another invention that directly resulted from space travel collaboration was wireless headsets. In 1961, the United Airlines was experimenting with alternatives to the bulky and uncomfortable headsets that were usually worn by pilots (Center, 2006). Courtney Graham and Keith Larkin developed the MS-50 headset that used an acoustic tube as the headband and transducers commonly used in hearing aids as the microphone and receivable. The result was a lightweight effective headset that the Federal Aviation Administration readily accepted in 1962.

Graham and Larkin also found that astronauts were suffering from similar problems. Later that

year, the two and their new company, Pacific Plantronics, worked with NASA to develop a working microphone, noise cancellation, and more into an astronaut helmet that became the first-used wireless headset (Center, 2006).

Above all, potentially the most underappreciated technological advancement arising from space exploration efforts is the cell phone camera. The Jet Propulsion Laboratory (JPL), a laboratory owned by NASA to house its cutting-edge rocketry research, was actually the initial site for the technology of photosensors and light signals that would then be developed into the digital camera built by Eastman Kodak in 1975. However, the jump to the miniaturization of this camera was also founded in the JPL by Eric Fossum (NASA - A Picture of Innovation, 2012). The development of the complementary metal-oxide semiconductor (CMOS) image sensors was the key, and Fossum acted on the opportunity by inventing the CMOS active-pixel sensor (CMOS-APS). Though the technology was intended for low power imaging in space when resources were limited, Fossum realized that it could be used for Earth applications. In 1995, he founded Photobit, licensed the CMOSAPS technology, and started to commercialize CMOS image sensors. Photobit went on to sell the technology in a variety of applications, including Web cameras, dental radiography, automotive applications, and most notably the phone camera (NASA - A Picture of Innovation, 2012).

Advancements Born in Space: Healthcare and the Environment The technological advancements that have emerged from space exploration are plentiful, but these developments do not come close to encompassing the broad range of innovations

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Figure 11. The International Space Station, Courtesy of NASA, 2020; Source: Wikimedia Commons

stemming from our extraterrestrial endeavors.

In particular, space exploration has brought a number of improvements in two critical areas of science: healthcare and the environment.

As for healthcare, space-related findings have contributed significantly to fields ranging from pharmaceutics to bioimaging.

In many cases, even non-healthcare-related research endeavors have led to noteworthy advancements. Two of the most prominent examples include the development of Magnetic Resonance Imaging (MRI) and the Left Ventricular Assist Device (LVAD). Both technologies are critical to medical care, and it is likely that neither would have emerged when they did in the absence of NASA-led space exploration (“Left Ventricular Assist Device,” n.d.).

In 1977, NASA’s Jet Propulsion Laboratory developed advanced processing mechanisms for the digital images that their craft had obtained from the moon. In addition to aiding scientists as they charted craters and crevices on the moon’s surface, this imaging technology would become the basis of MRI for clinical use in years to come (“Did NASA Invent MRI,” n.d.).

Likewise, NASA researchers did not set out to develop an artificial heart pump when they created technology that would eventually give rise to the LVAD, a critical piece of medical equipment that keeps patients healthy as they wait for heart transplants. However, when FALL 2020

a team of engineers at the Johnson Space Center in Houston set out to build a medical device with the capacity to pump life into a half-beating heart, they referred back to the pioneering design of space shuttle fuel pump (NASA, 2002).

More recently, NASA-related research endeavors have played a role in developing a light-based treatment for cancer patients who are experiencing the painful side effects of chemotherapy. The treatment, developed from luminescent technology initially applied to the growth of plants in space, would help reduce the pain associated with bone marrow or stem cell transplants. Pain-reducing UV-light treatment j a vast array of NASAfacilitated medical innovations—a list too extensive to describe here, though replete with critical everyday medical devices such as ear thermometers, automatic insulin pumps, and even implantable heart defibrillators (Rainey, 2017).

"In 1977, NASA’s Jet Propulsion Laboratory developed advanced processing mechanisms for the digital images that their craft had obtained from the moon. In addition to aiding scientists as they charted craters and crevices on the moon’s surface, this imaging technology would become the basis of MRI for clinical use in years to come."

In addition to advancements in the medical field, space-originating findings have also contributed greatly to environmental causes in the U.S. and globally. One area of focus for environmentally impactful research in space is the health of Earth’s atmosphere. The Clean Air Act of 1970 designated six pollutants—nitrogen dioxide (NO2), ground-level ozone, carbon monoxide, particulate matter (microscopic 207

Figure 12: With eyes on the future – NASA engineers and private entrepreneurs alike are gearing up for the first human journey to Mars. If the ambitions of Elon Musk and others come to fruition, the future may hold Martian colonization, and see the rise of humanity as a multiplanet species.

Source: Wikimedia Commons

"Finally, perhaps the most elusive class of space-borne advancements must be noted: global cooperation.

Neither the medical innovations nor the environmental discoveries that have come as a result of space exploration could have been achieved without notable collaboration between many different agencies, scientists, foundations, and governments."

specks of solid or liquid material in the air), sulfur dioxide, and lead—as atmospheric pollutants that warrant continuous monitoring to track and maintain our atmospheric quality (EPA, 2017). Unsurprisingly, space-borne satellites have emerged as some of the most effective instruments for these monitoring efforts. NASA's Health and Air Quality applications program manages the data-collecting devices, analyzes their findings, and disseminates the research globally to aid in worldwide environmental protectionism. Most recently, the Health and Air Quality applications program has contributed to a fascinating global finding: China's large-scale response to the COVID-19 pandemic, which included limitations on industrial activities and travel, appears to have resulted in a significant decrease in atmospheric levels of nitrogen dioxide (NO2) (Myllyvirta, 2020). A NASA imaging craft named Aura partnered with the European Space Agency's Sentinel-5 satellites to provide the underlying data, just one example of the numerous advancements in environmental understanding that have originated from space exploration.

Finally, perhaps the most elusive class of spaceborne advancements must be noted: global cooperation. Neither the medical innovations nor the environmental discoveries that have come as a result of space exploration could have been achieved without notable collaboration between many different agencies, scientists, foundations, and governments. International collaboration is at an all-time high—both literally and figuratively—in the International Space Station, where astronauts from the United States join colleagues from Russia, Europe, Japan, and

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Canada on board a space station with about as much internal volume as a Boeing 747 (“International Cooperation,” n.d.). The ISS and the international collaboration that takes place inside both serve as marks of the remarkable global cooperation that space exploration requires; the station is governed and maintained via five international treaties and five sets of principles on space-related activities, each facilitated by the United Nations’ Committee on the Peaceful Uses of Outer Space (“Space Law Treaties and Principles,” n.d.). Undoubtedly, whether space-borne advancements come in the form of new medical devices, enhanced environmental protection, or unprecedented global cooperation, the benefits of space exploration surround us here on Earth.

Conclusion It is the destiny of humanity to carve out a home amongst the stars. That is the vision, at least, which today’s space-flight leaders are edging towards. The notion that humanity ought to expand into space has actually been around for quite a long time. The real estate magnate John Jacob Astor IV wrote a fictional book in 1894 titled ‘Journey in Other Worlds: A Romance of the Future’. In it he depicts life on Jupiter and Saturn in the year 2000. We haven’t quite met the mark, but life on Mars at least is not far outside the realm of possibility from the perspective of the present day. Setting forth a more concrete vision, American physicist and space activist Gerard described in his book ‘The High Frontier’ (1977) the idea that industrial activity ought to be transplanted from Earth to the moon – both to lessen the burden on Earth’s environment and to establish the moon

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as a waystation for further extra-terrestrial exploration (Simberg, 2018).

While O’Neill’s plans were labeled by one Congressman (WI senator William Proxmire) as a “nutty fantasy” in the 1970s, the world may not be that far off from a more extensive and popular exploration of space (Simberg, 2018). Even NASA, whose space program had waned in the late 2000s/early 2010s, has gone back into the business of preparing to send astronauts to space. The Artemis program in particular plans to put the first woman on the moon by the year 2024 (Drake, n.d.). Artemis objectives are being supported by private contracts geared towards the construction of a lunar lander (both Blue Origin and Space X are involved), and the construction of Orion– a large spacecraft developed by Lockheed Martin that is considered to be safer and more reliable than the space shuttles ever were (“Orion Overview,” n.d.). NASA has ambitious plans for human travel to Mars as well – although the Institute for Defense Analysis, in a 2019 report, has labeled these plans a bit too far-fetched.

In their estimation, without significant budget increases and further government investment in Space R&D, 2037 is the earliest possible date for a feasible human launch to Mars (Linck et al., 2019) The private space pioneers are not so limited by budget considerations, though. And if nothing else they have very high aspirations.

Virgin Galactic is working on a craft that would inaugurate the space tourism industry – offering a joyride for paying customers that would provide six-minutes of weightlessness.

Branson and the other private space magnates are interested in space colonization as well.

Musk is perhaps best known for his focus on the planet Mars. Branson and Bezos have expressed similar intentions – musing about colonization of other planets, or even the construction of vessels that could support life within space itself (Simberg, 2018). All of these endeavors, if they do come to fruition, will necessitate legislative action. Regulations would be needed to govern space-flight patterns for example, and ensure that collisions with satellites or other space-faring craft are avoided (just as there are regulations of the same type for planes traveling within earth’s atmosphere).

International laws will need to be devised that address the utilization of planetary resources, and the demarcation of territory on the moon, Mars, and beyond. It will be a long road, yet the technology necessary to inaugurate this new

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era of human space travel, and the ambition to carry it out, are both increasing in supply.

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Thinking Small: Applications of Nanotechnology STAFF WRITERS: AKSHETA KANUGANTI, MARY-MARGARET CUMMINGS, ANNA KOLLN, ANDREW SASSER, DINA RABADI, BAMLAK MESSAY EDITORIAL BOARD WRITERS: ANNA BRINKS AND MEGAN ZHOU Cover Image: A computer rendering of the inside of a carbon nanotube. Carbon nanotubes are an ongoing area of research and are one of the many examples of exciting advancements in the field of nanotechnology.

Source: Wikimedia Commons

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Introduction The idea of ‘thinking small’ may bring to mind an image of someone peering through a microscope, examining the stages of mitosis or attempting to discern specific organelles of a cell. However, these features defined as ‘small’ are on the micrometer scale; the nanometer scale is in fact far tinier. Nanoscience and nanotechnology are the study and applications (respectively) of matter at the nanoscale, and it has been used across various fields such as chemistry, biology, engineering, physics, and materials science. At one-billionth of a meter, a nanometer is so small that scientists have had to develop extremely high-powered microscopes to see and manipulate material at this scale.

The possibility of even viewing material at the nanoscale level was introduced by Richard Feynman’s “There’s Plenty of Room at the Bottom,” in which he laid out the foundational concepts of modern nanotechnology. At this

lecture during the 1959 annual meeting of the American Physical Society at Caltech, Feynman shared that while he may not know how use this small scale in a practical way, he could imagine how machinery could be made considerably smaller and more compact (Hulla et al., 2015). As such, he has been credited as the father of modern nanotechnology; he also studied quantum electrodynamics and was later awarded the 1965 Nobel Prize in Physics.

The Chemical Basis and Synthesis of Nanotechnology The production of nanomaterials for nanotechnology applications has its basis in complex supramolecular chemistry and self-assembly techniques. Many commonlyused nanomaterials have been developed through the application of directed chemical synthesis¬—using external forces such as light and heat to build larger structures from smaller chemical units. One of the most diverse DARTMOUTH UNDERGRADUATE JOURNAL OF SCIENCE

Figure 1: A depiction of several types of nanomaterials, including a liposome, fullerene, dendrimer, carbon nanotube, and graphene. For reference, the example nanomaterials are placed within a broader scale stretching from a water molecule to a baseball.

Source: Wikimedia Commons

groups of nanomaterials targeted by synthetic chemists are carbon nanotubes. Through the sp2 hybridization of carbon, nanotubes assume cylindrical shapes composed of hexagonal faces. Additionally, through weak van der Waals forces, they form multiwall nested nanotubes (Eatemadi et al., 2014). Although these materials were historically synthesized through arc discharge between graphite electrodes or laser ablation of graphite blocks, modern methods focus on direct synthesis through chemical vapor deposition. In this method, a gas containing carbon atoms is passed over a catalytic nanoparticle¬–typically a transition metal–that allows the growth of nanotubes on its surface (Wang et al., 2019). These carbon nanotubes can then be modified with noncarbon functional groups to achieve desired properties and enhance solubility in polar solvents. For instance, treatment of carbon nanotubes with peroxytrifluoroacetic acid produced trifluoroacetic functional groups on the nanotubes, which are important for greatly improving solubility (Liu et al., 2005). Similarly, through electrophilic addition of alkyl groups, single-walled carbon nanotubes can have greater interaction with polymer molecule chains, allowing greater integration into metallic and biological systems (Xu et al., 2008).

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Another, more diverse, form of nanotechnology is that of nanoparticles—particles that typically range in size from approximately 1 to 100 nanometers (Vert et al., 2012). Generally produced from larger metal precursors such as copper, silver, and gold, these nanoparticles exhibit many interesting properties atypical of larger structures. For instance, due to surface stress inside small nanoparticles with high radii of curvature, the resulting lattice strain greatly increases the hardness of the material (Vollath et al., 2018). As a result, materials such as gold nanoparticles are harder than the bulk material (Ramos et al., 2013). Similarly, due to quantum mechanical effects associated with nanoparticles, the melting temperature of gold also decreases in nanoparticles in comparison to the bulk material (Buffat & Borel, 1976).

"Nanoparticles are produced through two primary methods: “top-down” and “bottom-up” synthesis."

Nanoparticles are produced through two primary methods: “top-down” and “bottomup” synthesis. In top down synthesis, larger bulk materials are crushed under mechanical forces or cut via lasers to create nanomaterials.

The application of force is directly correlated to the size of nanocrystals; the more time spent crushing the larger materials, the smaller the resulting nanoparticles (Khan et al., 2019). Although a more expensive method 215

Figure 2: DC Plasma can be used to produce carbon nanotubes through chemical vapor deposition. As a more modern method of producing nanomaterials, chemical vapor deposition is effective in building materials using the “bottom-up” approach of developing more complex nanotubes from simple carbohydrates.

Source: Wikimedia Commons

"By the 1980s, nanotechnology reached a “Golden Era” with the discovery of fullerenes by scientists Kroto, Smalley, and Curl.

Fullerenes are an allotrope of carbon that can form pentagonal and hexagonal rings that Kroto and his colleagues produced by laser-induced vaporization of graphite."

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than standard milling techniques, lasers are an efficient means of producing nanoparticles using the top-down method.

In the case of the bottom-up technique, nanoparticles are created from smaller and simpler materials. These methods include atomic layer deposition, physical and chemical deposition, and self-assembly. In these types of processes, simple units such as methane and silane are deposited over a metal surface and, under heat, combine to form longer chains and more complex shapes. The deposition methods are generally slower and more expensive compared to self-assembly techniques as they require more energy to build, but they are easier to design and fabricate due to the aid of mechanical force (Khan et al., 2019).

Finally, one of the most important techniques used in the development of nanomaterials and nanoparticles follows from the principle of molecular self-assembly. Defined as the “autonomous organization of molecular subunits to form an aggregate” with unique properties, self-assembly is crucial in the production of nanotechnology (Subramani & Ahmed, 2012). The assembly process is primarily governed through weak non-covalent bonding interactions, such as hydrogen bonding, electrostatic interaction, and van der Waals forces (Fung et al., 2005). Self-assembly processes can be seen in biological systems— like chromatin condensation and antibody recognition—but also are crucial in nanoparticle synthesis (Subramani & Ahmed, 2012).

Molecular self-assembly is broken down into two categories: static and dynamic self-assembly. In static assembly, molecules naturally assume an ordered state at thermodynamic equilibrium, as seen with lipids forming oil droplets in water caused by hydrophobic effects (Subramani & Ahmed, 2012). Conversely, dynamic assembly requires energy to achieve structures that are not at thermodynamic equilibrium. Through the application of external forces like magnetic fields and ultrasound, molecular components can assume less energetically favorable but more desirable structures that can be manipulated under certain external conditions, as compared to static assembly structures which maintain the lowest energy conformation (Wang et al., 2019).

For example, Zhang’s research team recently demonstrated that the application of a magnetic field during the growth of Fe3O4 nanoparticles greatly increased the removal of heavy ions because of its ability to create a “swarm” to trap

these heavy ions (Zhang et al., 2018). Similarly, Kralj and Makovec reported that through the use of a magnetic field, iron oxide nanoparticle clusters could be assembled into nanochains of either 6 or 14 clusters (Kralj & Makovec, 2015).

Notably, under low frequency magnetic fields, these nanochains are capable of increasing the bioactivity of many insoluble drugs through their ability to guide drugs to their targets under magnetic field conditions (Arruebo et al., 2007).

A Brief History and Key Breakthroughs Feyman’s promise of nanotechnology was not fulfilled until long after his 1959 lecture.

It was nearly fifteen years afterwards that Norio Taniguchi, a Japanese scientist, brought up nanotechnology again in the context of describing semiconductor processes. By the 1980s, nanotechnology reached a “Golden Era” with the discovery of fullerenes by scientists Kroto, Smalley, and Curl. Fullerenes are an allotrope of carbon that can form pentagonal and hexagonal rings that Kroto and his colleagues produced by laserinduced vaporization of graphite (MateoAlonso et al., 2006). They went on to receive the Nobel Chemistry Prize in 1996 for their work, and fullerenes were crucial for later discoveries. Around this time, Eric Drexler of the Massachusetts Institute of Technology envisioned a nanoscale ‘assembler’ that could

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build copies of itself and other complex items at a nanoscopic scale (Hulla et al., 2015).

This concept was advanced further with Iijima’s development of carbon nanotubes: needles that ranged from a few to a few tens of nanometers in diameter (Iijima, 1991).

The syntheses of these carbon nanotubes were made possible by the discovery of the aforementioned fullerenes: a similar method using an arc-discharge evaporation allowed for the needles to grow at the negative end of the electrode.

Beyond the key scientific breakthroughs themselves, nanotechnology was spurred to the national stage as President Bill Clinton became an advocate for this emerging technology in 2000 (Hulla et al., 2015). President George W. Bush further prioritized nanotechnology research with the 21st Century Nanotechnology Research and Development Act, creating the National Nanotechnology Initiative. This Act set the foundation for many years of basic nanoscience research; today, nanotechnology is helping to improve many industry sectors, including materials, electronics, medicine and health, energy, environmental science, and more.

Case Studies: Applications of Nanotechnology Medical Applications: COVID-19

The severity of the COVID-19 pandemic has led to a huge commitment to research focused on the development of nanomaterials with regard to detection, sanitation, therapies, and vaccines. Nanomaterials can be utilized for detection protocols of SARS-CoV-2; for example, the rapid bioassays for detecting the virus have been developed by modifying nanoparticles. Additionally, the coronavirus pandemic has brought poor sanitation practices to the forefront of public consciousness, and nanotechnology has applications for efficient and effective disinfection with the use of selfsanitizing surfaces of nanoparticles that release antimicrobial actives (Ruiz-Hitzky et al., 2020).

While this may not be currently feasible at the large-scale, such nanostructured surfaces may become the norm in the future.

Also, with no current vaccine available, synthetic nanoparticles have been considered as carriers to administer viral vaccines as they

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become available (Ruiz-Hitzky et al., 2020).

Furthermore, nanoscale materials are effective platforms to impair the viral infection cycle itself with the ability to activate the immune response. Ultimately, since nanoparticles and viruses operate at the same nanometric scale, these approaches in vaccine development can be incredibly powerful (Shin et al., 2020). But while these innovations are highly promising, they are unfortunately several years away from deployment and widespread use. For now, treatment options such as a nanomedicine formulation demonstrate the power nanotechnology has on medicine and health in the context of the coronavirus pandemic such as targeting inflammation sites and increasing the efficacy of alveolar macrophages or phagocytes (Nature Nanotechnology, 2020).

Nanoprinting Organs Nanotechnology has entered the future with the creation of the ‘organ-on-a-chip’ (OOAC) (Wu et al., 2020). OOAC is a microfluidic chip whose structure and components mimic biological organ systems in functionality. The applications of such a technology are vast, including the likes of drug toxicity testing.

OAAC can provide a substitute for animal models and furthermore can more accurately predict how certain compounds may react in the human body.

The OAAC is approximately the size of a SD memory card and is made of a transparent polymer with embedded malleable and selectively permeable channels containing microfluidics. The inner surface of these channels is covered by living human cells that correspond to the organ that the OAAC is mimicking (Wyss Institute, 2017).

"The severity of the COVID-19 pandemic has led to a huge commitment to research focused on the development of nanomaterials with regard to detection, sanitation, therapies, and vaccines."

The OAAC has “mechanical forces, fluid shear, concentration gradients,” and cell patterning to mimic the microenvironment of the specific biological organ (Wu et al., 2020). The OAAC’s mechanical forces use microfluidics in the form of the permeable channels used in cell differentiation. The fluid shear is represented in the OAAC by the application of pressure on the receptors of endothelial cells that induce cell signaling and the execution of other typical cellular processes. The OAAC incorporates concentration gradients through the use of micropumps and microvalves. Cell patterning in the OAAC is possible due to alterations on the chip’s surface by 3-D printing and ablation techniques on mediums such as glass using

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Figure 4: Several physical representations of an OAAC.

living cell templates to accurately represent the living cell’s surface (Wu et al., 2020).

Source: Wikimedia Commons

The OAAC has a variety of applications due to its four constituents: “microfluidics, living cell tissues, stimulation or drug delivery, and sensing” (Wu et al., 2020). Microfluidics help keep the chip at its nanoscopic size and are also used for waste management purposes. The living cells in the OAAC are used to create the physical spatial arrangement that matches what one can find in an in vivo organ. Stimulation comes in the form of chemical and sometimes physical signals which induce maturation of the living cells, allowing the cells in the microchip to resemble the microenvironment of typical biological organs. Lastly, sensing technologies monitor the changes occurring in the microchip due to any potential experimental changes (Wu et al., 2020).

"Nanoparticles have many properties that make them uniquely good candidates as drug-delivery vehicles. Many are eco-friendly, cheap, and chemically stable."

The OAAC truly comes ‘alive’ as a functional organ system when its living human cells are given blood supply via artificial blood vessels (Wyss Institute, 2017). In the OAAC, mechanical adjustments known as shear force capability are added to reproduce the niche characteristics of the microenvironment present in in vivo organs (Wyss Institute, 2017; Wu et al., 2020).

One of the major uses of this technology has been testing the toxicity of drugs in a medium containing a liver OOAC. Lung-on-a-chip has also been used to investigate the factors that induce chronic lung disease. The lung OAAC has been used in preterm infants to aid respiration function. Typically, infants exchange respiratory gases via the placenta, but in times of respiratory failure, this is not possible so the lung OAAC sufficiently exchanges oxygen and carbon dioxide (Wu et al., 2020). Additionally, other OOACs have also been created such as the kidney OOACs which have a variety of uses including “nephrotoxicity assessments, therapeutic development, regenerative medicine, and kidney development and disease” (Wu et al., 2020). The kidney OAAC uses microfluidics to replicate the structures that enable the filtration and reabsorption function of the nephron.

There is also work being done to integrate all of these organ-specific OOACs into an externally connected “human Body-on-Chips” which would represent how all of the organ systems in the human body work in tandem (Wyss Institute, 2017). After further studies are completed, this technology will perhaps be an improved alternative to the limited application of 2D tissue

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studies, failure-prone animal experiments, and human clinical trials (Wu et al., 2020).

Drug Delivery: General Drug Delivery As mentioned in the context of the coronavirus pandemic, nanoparticles have many properties that make them uniquely good candidates as drug-delivery vehicles. Many are eco-friendly, cheap, and chemically stable. Importantly, it is the small sizes that are responsible for clinical advantage in drug delivery. Small size helps enable cell and tissue specificity, easy transport into the target cells, and increased solubility.

As such, they are especially promising subjects in the development of new disease therapies (Khan et al., 2020).

When considering arrival at the target cell, researchers can tailor nanocarriers to either passively or actively target diseased cells.

Passive targeting, which relies on permeation of the drug throughout tissues, tends to have greater success when the cells of interest

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are in a focused area, such as a solid tumor.

For example, since most nanocarriers are pH unstable entities, when they are entering a target cell with a lower intracellular pH, the nanocarrier degrades and releases the drug. If the target cells are more dispersed, however, a form of â&#x20AC;&#x153;active targeting,â&#x20AC;? which depends upon a ligand binding to a receptor, is needed for the drug to reach target cells. Thus, a targeting ligand could be affixed to the surface of the nano-carrier, making the nanoparticle hunt for diseased cells that overexpress the corresponding receptor (Majumder et al., 2019).

Once the nanocarrier arrives at the target cell, since its charges and surface ligands are designed to correspond to receptors of its target cells, it can easily diffuse into the cells.

Their small sizes also allow them enhanced solubility. Since their surface area to volume ratio is large, nanocarriers have plenty of space to which drugs and ligands can be tethered.

Ultimately, confluence of these elements leads to the quick, efficient arrival of the drugs to their target cells, allowing for increased therapeutic effect (Majumder et al., 2019).

ADCs: Targeted Drug Delivery to Cancer Cells Antibody drug conjugates (ADCs) are a type of nanoscale therapeutic that deliver cytotoxic payloads for cancer treatment. These payloads are supplied via monoclonal antibodies (mAb), an antibody that can bind to only a single epitope, bound to the payload by a linker.

A well-known hurdle to efficacious cancer therapeutics is specificity, and ADCs overcome this hurdle through the use of the mAb, which allows for highly specific delivery of potent drugs. However, ADCs can cause unintended

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and potentially detrimental side effects to the patient. Over the past two decades, development of first- and second-generation ADCs faced many challenges, such as low tumor microenvironment penetration, low efficacy, immunogenicity, off-target toxicity, drug resistance, and lack of stability in the bloodstream (Nejadmoghaddam et al., 2019).

Today, only four ADCs are approved for use in the clinic; over eighty have been investigated in clinical trials with dozens more trials of ADCs halted due to unforeseen side effects (Zhao et al., 2020).

Figure 3: The structure of a classical antibody-drug conjugate, which is composed of the antibody, linker, and cytotoxic drug. ADCs are also being developed beyond their original use of cancer, so, in some cases, the cytotoxic drug is replaced by anti-inflammatory drugs.

One of the main components of the ADC is the payload, which is a small-molecule cytotoxic drug that is often some component of chemotherapy. When delivered to the tumor cell, the payload is taken up and ideally released within the cell itself, rather than in the bloodstream or before internalization.

Internalization is critical to kill the cancer cell from within and to prevent off-target effects.

Certain challenges arise when designing a payload, such as potency and stability. Potency becomes an issue because only about 2% of ADCs will infiltrate the tumor, so the ADCs that do arrive must be strong enough to kill the tumor cells on their own (Peters & Brown, 2015).

When choosing a cytotoxic agent, stability at physiological as well as the acidic tumor microenvironment must be considered. The final consideration involves ability to be linked to the antibody via the linker. Typical payloads are often highly potent anti-microtubule agents, alkylating agents, and DNA minor groove binding agents. Thus, there are many constraints in the development of effective nanoscale ADCs therapies.

"Antibody drug conjugates (ADCs) are a type of nanoscale therapeutic that deliver cytotoxic payloads for cancer treatment."

Source: Wikimedia Commons

The antibody provides specificity to the ADC and guides the payload to its correct target. The mAb of the ADC permits binding only when a cell has the appropriately matching antigen (or receptor) that is tumor-specific. The challenges of antibody design include specificity as well as heterogeneity of antigen expression and receptor-mediated internalization of the ADC. If an antibody binds a widely expressed receptor, then the cytotoxic drug will be delivered to all cells that express that antigen, which highlights the importance of minimizing offtarget effects. The challenges of heterogeneity of expression and internalization occur after the antibody binds the tumor cellâ&#x20AC;&#x2122;s receptor (Nejadmoghaddam et al., 2019).

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"When scientists discuss relatively high efficacy in drug delivery, they commonly mention chitosan nanoparticles due to their far-reaching applications in nanomedicine, biomedical engineering, and oncological technology. Chitosan derives its natural properties from chitin, the second most abundant natural biopolymer in the world found in the exoskeleton of arthropods."

The linker is the portion of the ADC that covalently connects the payload to the antibody.

The linker design is critical, as its makeup will prevent the payload from being released or broken off at an off-target location or in the bloodstream, causing release of cytotoxic drugs that would kill healthy cells. Furthermore, linker design is the key to releasing the drug inside the tumor cell in the correct location after lysosomal degradation. Linkage chemistry is complex and entails consideration of the drug-antibody ratio (DAR) and avoidance of heterogeneity. DAR is an important consideration in ADC development because it’s possible that multiple ADCs with some variation in DARs are generated during synthesis. If the DAR distribution is wide, there is risk for increased off-target effects such as premature payload release and aggregation (Tsuchikama et al., 2016). Heterogeneity in linkers is caused by variations in the ADCs due to small, but significant, residue alterations that occur during linker synthesis (Nejadmoghaddam et al., 2019). This issue can be circumvented via various site-specific engineering biochemical techniques.

ADCs are now beginning to expand as therapeutics beyond cancer into autoimmune diseases, difficult-to-treat bacterial infections, and atherosclerosis (Gingrich, 2020).

For example, a widely used therapeutic in autoimmune diseases include TNF-inhibitors and corticosteroids. An issue with these drugs, however, is that their effects are frequently shortterm. A TNF-inhibitor ADC has been proposed as a solution and is under development to treat rheumatoid arthritis; the inhibitor has been shown to completely restore normal joint architecture in mouse models at a rate of at least 40% for greater than thirty days (Waegell et al., 2019). This is just one example out of the dozens of research groups and biotech companies that are working on applying ADCs to areas beyond oncology.

Drug Delivery in Alzheimer’s Disease (AD) Neurological diseases are especially challenging to treat because the Blood Brain Barrier (BBB) prevents most foreign objects from entering the brain. Nanotechnology-based drug delivery systems are being widely studied as potential treatments for brain-based diseases because many of nanoparticles’ unique characteristics, such as their small size, not only make them the most opportune candidates for gaining access to the brain, but they also may do so without damaging the BBB (Fonseca-Santos et al., 2015).

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One strategy involves coating the nanoparticles with polyethylene glycol (PEG).

Derived from ethylene oxide, PEG is a synthetic, water-soluble, non-toxic compound used for medical applications. Thus, it was used by Zhang’s research team to develop a PEGylated polylactic acid (PLA) polymer-based dualfunctional nano-drug delivery system to treat AD (Zhang et al., 2014). PEG-PLA was used as a nano-delivery system because it is a safe, biodegradable material that does not easily provoke an immune response. PEG is a hydrophilic shell that wraps around PLA, the stable, hydrophobic core. The PEG-PLA complex needed targeting peptides so that it could penetrate the BBB and target the amyloid plaques caused by AD. Thus, the researchers took two targeting peptides (TGN and QSH) and conjugated them onto the surface of the nanoparticles. TGN targeted ligands of the BBB, while QSH targeted〖 Aβ〗_(1-42), a critical component of amyloid protein plaques (Zhang et al., 2014). This system was administered to AD model mice, and it showed “enhanced and precisely targeted delivery” to the amyloid plaques in the mice’s brains. Additionally, little cytotoxicity was found in their model (Zhang et al., 2014).

Chitosan Nanotechnology for Drug Delivery When scientists discuss relatively high efficacy in drug delivery, they commonly mention chitosan nanoparticles due to their far-reaching applications in nanomedicine, biomedical engineering, and oncological technology.

Chitosan derives its natural properties from chitin, the second most abundant natural biopolymer in the world found in the exoskeleton of arthropods (Croiser, 2013).

Researchers were initially interested in delving deeper into finding the optimal method of chitosan nanotechnology production because of its biodegradability and bacteriostatic and mucoadhesive properties. Not only can chitosan nanoparticles effectively adhere to medical drugs, but they are also easily digestible and can potentially put a stop to the multiplication of bacteria (Divya, 2018). Chitin can be seamlessly transformed into chitosan by chemically removing acetyl functional groups; however, optimizing the transition from chitosan to stable chitosan nanoparticles has proved to be one of scientists’ biggest challenges (Divya, 2018).

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Figure 5: Schematic of a complete electrochemical water cycle, in which hydrogen is produced by the electrolytic cell and used to generate energy by the fuel cell.

Source: Adapted with permission from Jin, H., Guo, C., Liu, X., Liu, J., Vasileff, A., Jiao, Y., Zheng, Y., & Qiao, S.-Z. (2018). Emerging Two-Dimensional Nanomaterials for Electrocatalysis. Chemical Reviews, 118(13), 6337–6408. https://doi.org/10.1021/acs. chemrev.7b00689. Copyright 2018 American Chemical Society.

Since 1994, three main methods of chitosan nanoparticle preparation have been developed, namely ionotropic gelation (IG), polyelectrolyte complexes (PEC), and microemulsion method (MM) (Divya, 2018). Simply put, IG is a technique for the production of nanoparticles that takes advantage of electrostatic interactions between positively charged chitosan and negatively charged phosphate groups to form a network of polymeric chains, called hydrogels.

The hydrogels of the nanoparticle chains can trap medical drugs, formulating a system with increased bioactivity and targeted, controlled release of the medication (Pedroso, 2020). In a similar process, the PEC method involves polyelectrolytes disassociating in aqueous solutions and electrostatically adhering to chitosan and medical drugs to form polymerpolymer, polymer-drug, and polymer-drugpolymer combinations (James, 2016). The main disadvantage with the PEC method is the high cost and large drug loss during the final bead preparation. Next, the microemulsion method takes advantage of the relationship between N-hexane and acetic acid, similar to the immiscibility of oil and water. A surfactant forces the chitosan-acetic acid solution and N-hexane induced with a medical drug together to form chitosan nanoparticles. However, this method is ineffective as the surfactants destroy its antigenicity properties which does not allow for the site-specific release of medication.

Due to the drawbacks associated with the PEC and MM method, such as high cost, drug loss, and inefficient targeted release of drugs, most researchers decided to focus on optimizing the IG method. Results from a study published at the beginning of this year showed that 0.4mg/ mL concentration of chitosan undergoing IG at 4ºC produced the highest yield and the smallest

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nanoparticles in comparison to the production of nanoparticles using the IG method at other temperatures and concentrations (Duan, 2020). These results are highly significant for the multiple arenas that chitosan nanotech is involved in.

The most fundamental use of chitosan nanoparticles is as a targeted drug carrier, as chitosan’s miniscule size allows it to cross biological barriers. If the size of the nanoparticle can allow it to enter certain cells, the nanoparticles can deliver drugs to that specific site (Divya, 2018). Recently, chitosan nanoparticles have been used for cancer diagnosis as well. Initially, nanocrystals were used for cancer diagnosis, however, its cytotoxicity became a primary concern. Due to chitosan’s biodegradability and targeting specificity, chitosan nanoparticles with fluorescence for color detection became the perfect substitute to detect cancer cells (Divya, 2018). Furthermore, chitosan nanoparticles can also replace and heal tissue because they are highly compatible with the human body and their adhesivity can promote cell attachment (Aminabhavi, 2017).

"The most fundamental use of chitosan nanoparticles is as a targeted drug carrier, as chitosan’s miniscule size allows it to cross biological barriers."

Energy:

The threat of climate change due to carbon emissions is a significant, longstanding challenge. As energy consumption is expected to increase, the conversion to sustainable energy systems in the coming decades is crucial. Hydrogen fuel cells are an extremely promising source of clean energy as their only emission is water. A system encompassing both the electrochemical production of hydrogen via water-splitting reactions and its subsequent use in hydrogen fuel cells would provide a closed

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loop, zero-emissions energy source (Figure 5).

However, the chemical reactions involved in this cycle are not all energetically favorable, so catalytic materials are used to drive the reactions forward. The current benchmark catalysts for water-splitting reactions are rare-earth elements such as platinum, iridium, and ruthenium Source: Pixnio (Li et al., 2016). Thus, the search for chemical materials that are both more readily available than precious metals and still high-performing catalysts is vital to making electrochemical fuel cells viable for wide use in renewable energy.

Nanomaterials are a highly favored candidate, as their controlled morphology and high surface area provide more electrochemically active sites per area (Zheng et al., 2015). In other words, researchers can maximize the catalytic capability of nanomaterials to benefit the energy industry substantially.

Figure 6: Microscopy image of a norovirus infection, the most common cause of foodborne illness. Nano-based sensing approaches can be used to assess food safety and detect contaminants like the norovirus

"Nanotechnology can impact the food industry at many steps in the process, whether it be production, processing, safety, packaging, transportation, storage, or delivery."

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Scientists are investigating a wide variety of nanomaterials for applications in energy. A number of metal nanoparticles have been found to have unique catalytic abilities.

Although the performance of nanoparticles can deteriorate as the materials consolidate over time, researchers are developing methods to encapsulate nanoparticles within shells or pores of other materials to improve their longterm stability (Gao et al., 2020). One-dimensional nanostructures such as nanowires, nanorods, and nanotubes have been shown to be versatile and can be constructed from earth-abundant elements, especially using transition metals such as iron and nickelâ&#x20AC;&#x201D;which are promising due to their abundance. Carbon-based materials, such as carbon nanotubes, are also composed of an abundant element and can be produced through relatively simple syntheses (Li et al., 2016). Additionally, carbon-based materials can be modified to enhance their catalytic efficiency. Nitrogen-doped materials, in which some of the carbon atoms are replaced by nitrogen, have been shown to outperform platinum-carbon catalysts (Inagaki et al., 2018).

Metal nanoparticles can be attached to carbon structures as another enhancement method (Li et al., 2016). Two-dimensional nanomaterials such as graphene can be manipulated in a similar manner (Jin et al., 2018). Metal-organic framework materials (MOFs) are another class of nanomaterial being explored for its catalytic benefits. MOFs are constructed from an extended structure of metal ions linked together by organic ligands. Since both the metal and ligand components can be switched out to create new compounds, MOFs are extremely tunable and versatile materials. They are also

porous, allowing for a large surface area for chemical reactions to take place (Mahmood et al., 2016). Overall, investigation of the evergrowing pool of known nanomaterials has just begun, with many candidates emerging for widespread application in hydrogen fuel cells.

The Food Industry: Nanotechnology can impact the food industry at many steps in the process, whether it be production, processing, safety, packaging, transportation, storage, or delivery (Rossi et al., 2014). One potential application for nanotechnology is in the use of nanoemulsions.

An emulsion is the combination of two or more liquids that are immiscible. A nanoemulsion has droplets that measure 500 nm or less dispersed in solution (Thiruvengadam et al., 2018). In cosmetic, food, and pharmaceutical products, emulsions can provide a dispersible platform that allows active ingredients or flavor compounds to be solubilized while desirable mechanical properties are maintained (Sheth et al., 2020). One study found that nanoemulsions containing lemongrass oil could be used to coat plums, inhibiting the growth of dangerous bacteria such as salmonella and E. coli and better preserving various physicochemical qualities of the plumbs such as firmness, extending their shelf life (Kim et al., 2013).

Another group of researchers developed a nanoemulsion-based ice cream with lower fat content (Thiruvengadam et al., 2018).

Nanoemulsions can be formed by high-energy methods and spontaneous methods (Sheth et al., 2020). High-energy emulsification involves applying large fluid stresses to a biphasic liquid mixture, such as vortexing, highpressure microfluidics, and ultrasonication.

This mechanical energy is necessary because the Laplace pressure (the pressure jump

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across a liquid interface induced by surface tension) scales with the curvature of an interface, so deforming and producing smaller droplets requires a corresponding higher level of fluid stresses (Sheth et al., 2020).

Conversely, spontaneous emulsification relies on the internal energy of the non-equilibrium mixture rather than mechanical energy to drive emulsification. This can be achieved when a monophasic mixture is driven across a phase boundary by dilution with the desired dispersed or continuous phase. It can also occur by changing surfactant concentration or temperature (Sheth et al., 2020).

example, polymer composites that include the nanoclay montmorillonite can limit the permeation of gases while metal or oxide nanoparticles have been developed for antimicrobial packaging, increased strength, and UV absorption (Rossi et al., 2014).

Advances in nanotechnology for packaging can also improve the biodegradability of wasteful packaging products. For example, the heteropolysaccharide chitosan has antimicrobial activity and can be made into edible films and coatings, reducing the need for non-biodegradable plastic packaging (Sharma et al., 2017).

Food safety is also a critical issue that can be impacted by nanotechnology. Each year in the United States there are 9.4 million episodes of foodborne illness, 55,961 hospitalizations, and 1,351 deaths. The most common causes of illness were the norovirus (58% of cases), followed by nontyphoidal Salmonella (11% of cases), and Clostridium perfringens (10% of cases) (Scallan et al., 2011). Globally, food contamination is an even bigger problem: the World Health Organization (WHO) estimates that each year there are 420,000 deaths attributable to unsafe food, with 30% of these deaths occurring among children under 5 years of age. This corresponds to 33 million years of healthy lives lost due to eating unsafe food each year (WHO, 2020). Nano-based sensing approaches can be used to assess food safety and detect contaminants including pesticides, heavy metals, bacterial pathogens, and natural toxins (B端lb端l et al., 2015). For example, gold nanoparticles are ideal for such sensing approaches because they can be tuned by changing the size, shape, local environment, and the synthesis method. They can also act as carriers for biorecognition elements such as antibodies or aptamers that can recognize harmful bacteria. There is considerable effort to ensure affordability and portability of the technology, allowing for greater access around the world and rapid assessment of food safety (B端lb端l et al., 2015).

Limitations:

Nanotechnology derived food packaging materials are also an increasingly important part of the food sector. Relatively low levels of nanoparticles are sufficient to impact the properties of packaging materials without causing significant changes in density, transparency, and processing characteristics.

Adding certain nanoparticles can help with increased fire resistance, improve mechanical strength, and reduce gas permeability. For

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Despite these promising nanomaterial applications that benefit the environment, it is also important to evaluate possible toxicity that can result from nanomaterials. In order to prevent environmental and human health effects after long exposure, judicious research needs to clarify and outline how nanomaterials can be handled safely and used correctly (Paralta-Videa et al., 2011). Nanomaterials are currently used extensively in applications such as the use of metal nanoparticles for groundwater remediation; arsenic removal and groundwater treatment using iron oxide nanoparticles; titania nanoparticles for sunscreens and paints; fullerene nanotubes for tennis rackets; silica nanoparticles in electronic industries; and much more (Ganguly et al., 2018). Because of the diversity of nanomaterials in use, it can be difficult to accurately assess their impact on the environment and humans.

To complicate issues, the diverse and dynamic nature of the environment the nanomaterial enters may also induce modifications that could increase or decrease the toxicological profile of the material (Ganguly et al., 2018).

"Relatively low levels of nanoparticles are sufficient to impact the properties of packaging materials without causing significant changes in density, transparency, and processing characteristics.

Adding certain nanoparticles can help with increased fire resistance, improve mechanical strength, and reduce gas permeability."

Manufactured nanomaterials can enter the environment through intentional releases as well as unintentional releases such as atmospheric emissions and solid or liquid waste streams from production facilities (Ray et al., 2009). Although usually not intentionally manufactured, the accumulation of nanoplastics in aquatic environments is becoming increasingly concerning.

Nanoplastics may be released from products or from the nanofragmentation of larger particles. These particles may pose a danger to marine wildlife or even impact sedimentation processes (Bergmann et al., 2015).

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Nanomaterials may also pose a risk to humans.

Research indicates that some nanomaterials may be linked to diseases such as asthma, dermatitis, rhinitis, interstitial lung disease, lung contaminations, tuberculosis, respiratory embolism, and immune system illnesses (Ganguly et al., 2018). Characteristics such as size, morphology, surface charge, and coating can all impact toxicity. The small size of nanomaterials can facilitate their introduction to the human body, and nanomaterials may subsequently enter cells through endocytosis, clathrin-mediated endocytosis, phagocytosis, pinocytosis, and other methods (Ganguly et al., 2018). Although this may be beneficial in controlled and intentional cases such as with drug delivery, it may cause issues when the nanomaterial is not designed for human contact.

Inhalation exposure is also a concern due to the small size of engineered nanomaterials, which may become airborne particles covering a size range from a few nanometers to several micrometers in diameter (Ray et al., 2009). The proportional surface area of materials also increases with the decrease in size, providing greater opportunity for interaction with the cellular environment (Ganguly et al., 2018).

Park’s research team investigated cytotoxicity in L929 murine fibroblasts and RAW 264.7 murine macrophages using assays for cellular metabolic activity, membrane integrity, generation of ROS, markers of inflammation, developmental toxicity, and genotoxicity. They found that silver nanoparticles of 20 nm were more toxic than larger nanoparticles (Park et al., 2011).

Ensuring rigorous investigation into the risks of nanomaterials will allow researchers to pick materials which are benign to both the environment and human health (Ganguly et al., 2018). To assess the safety of complex multicomponent and multi-functional nanomaterials, scientists will need to develop validated models capable of predicting the release, transport, transformation, accumulation, and uptake of nanomaterials in the environment (Bergmann et al., 2015). These models can inform predictions about biological impacts, ecological impacts, and degradation at end-of-life, allowing nanomaterials to provide their many benefits without risking the wellbeing of the environment, animals, and humans (Bergmann et al., 2015).

Conclusion Nanotechnology is clearly a rapidly expanding field. As scientists and researchers continue to better understand the enhanced properties of

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this material, its applications continue to grow.

From medicine to agriculture and all the way to energy, nanotechnology has already made an enormous impact in many disciplines beyond the obvious electronics and IT applications.

Future research will elucidate many more game changing benefits in transportation, environmental remediation, and healthcare.

Nonetheless, there still remains many open ended environmental, health, and safety issues that have yet to be addressed.

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Alzheimer’s Disease: Molecular Mechanisms, Clinical Manifestations, and Treatments STAFF WRITERS: AUDREY HERRALD, GEORGIA DAWAHARE, VISHI AGRAWAL, AYUSHYA AJMANI, DHASIYA ANDERSON, SOPHIA ARANA, MAEEN ARSLAN, ANUSHKA BHATIA, BENJAMIN CHEN, SOYEON (SOPHIE) CHO, MICHAEL DEL SESTO, AARUN DEVGAN, ARSHDEEP DANOA, VALENTINA FERNANDEZ, AIDAN FERRIN, ABIGAIL FISCHER, VAANI GUPTA, ANDREW GOYETTE, REGAN HARNOIS, SREEKAR KASTURI, VAISHNAVI KATRAGADDA, AKSHAY KELSHIKER, ASHNA KUMAR, LAUREN LEE, CALLIE MOODY, ANNALIESE OUYANG, NOA PHILLIPS, JULIA PICKER, JULIA ROBITAILLE, GEORGE SHAN, WHITNEY THOMAS, LOVE TSAI, KATIE WALTHER, BRYN WILLIAMS, MIRANDA YU EDITORIAL BOARD WRITER: LIAM LOCKE

Cover Image: Alzheimer’s disease is a neurodegenerative disorder which leads to memory loss, impairments in judgment and cognitive function, as well as changes in mood and behavior. Aggregation of the proteins amyloid beta and tau have been consistently linked to Alzheimer’s disease, but the exact molecular pathology of this disorder remains elusive. Treatments have been developed to improve cognitive and behavioral symptoms, but a cure has yet to be discovered Source: Store Medisinske Leksikon

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Introduction Alois Alzheimer was born in 1864 in southwest Germany. Late in his studies, he developed a strong passion for anatomy and microscopy and went on to attend multiple colleges, including the Eberhard Karls University of Tübingen, Humboldt University of Berlin, and Julius-Maximilians-Universität.

Alzheimer eventually graduated with a medical degree in 1887 (Jensen, 2019). After graduation, he began working at the Community Hospital for Mental and Epileptic Patients in Frankfort, Germany under the distinguished neurologist Franz Nissl. Nissl served as a mentor to Alzheimer throughout their joint research of nervous system pathology. Although Alzheimer was primarily a clinical psychiatrist, Nissl encouraged Alzheimer to continue researching alongside his clinical work. Alzheimer’s research spanned a range of topics including general paresis, epilepsy, and dementia (Hippius & Neundörfer, 2003).

The year 1901 was a turning point in Alzheimer’s personal and professional life. Following the death of his 41-year-old wife, Alzheimer was left with three young children. Alzheimer coped with his wife’s death by devoting himself to his work, as one of his sisters helped raise his children (Hippius & Neundörfer, 2003). That same year, Auguste Deter, the patient that would lead to the discovery of Alzheimer’s disease, was admitted to the hospital where Alzheimer worked. Auguste was a woman in her fifties that had symptoms of memory loss, disorientation, and hallucinations. Postmortem analysis of her brain revealed a thin cerebral cortex and histologically visible structures now known as neurofibrillary tangles and senile plaques (Jensen, 2019).

At first, Alzheimer’s discovery was poorly received and failed to gain much attention.

However, in 1910, the influential German psychiatrist Emil Kraepelin coined the term DARTMOUTH UNDERGRADUATE JOURNAL OF SCIENCE

“Alzheimer’s disease” in his writings. Alzheimer, unfortunately, had little time left to enjoy this burgeoning interest in his work, as he died in 1915 from a severe cold and heart infection (Jensen, 2019). By 1976, neurologist Robert Katzam determined that Alzheimer’s disease is the most common cause of dementia. Since then, an immense amount of research has been conducted to understand how the disease manifests and progresses so that it may be slowed or prevented.

Alzheimer’s disease (AD) is characterized by the presence of senile plaques formed by aggregation of the protein beta amyloid (Aβ) and neurofibrillary tangles created by aggregation the microtubule-associated protein tau (Octave, 2005). The amyloid hypothesis of AD proposes that the abnormal accumulation of Aβ plaques in different parts of the brain causes the neurodegeneration seen in Alzheimer’s disease, and a great amount of research has been dedicated to characterizing the pathway leading to the formation of these plaques. However, the mechanisms by which these plaques cause neuron death remains unknown, and recent research suggests that smaller, soluble Aβ oligomers that form prior to senile plaques may be the main culprits for amyloid toxicity (Stavljenic-Rukavina, 2004; Loera-Valencia et al., 2019). In contrast, the tau hypothesis proposes that improper functioning of tau destabilizes microtubules and lead to the deterioration of the neuronal cytoskeleton (Iqbal et al., 2010). There are also many other molecules that have been implicated in Alzheimer’s disease that either contribute to the formation of these protein aggregates or are implicated in central neuronal processes such as synaptic plasticity and neurogenesis; these molecules are frequently kinases (e.g. fyn kinase, glycogen synthase kinase-3β, and cyclin-dependent kinase-5) or similar regulatory proteins (Crews & Masliah, 2010).

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By 2011, the National Institutes of Health and the Alzheimer’s Association revised the diagnostic criteria for Alzheimer’s disease to replace those from a similar 1984 conference (Clifford et al., 2011). These changes helped clarified boundaries between the three stages of the disease: the preclinical (asymptomatic) phase, the Mild Cognitive Impairment (MCI) phase, and fully developed Alzheimer’s Dementia. Preclinical Alzheimer’s is the span of time between the appearance of the first brain lesions and the onset of the first clinical symptoms (Dubois et al., 2016). Elevated levels of tau in cerebrospinal fluid have been found to occur as early as 15 years before the onset of any neuropsychiatric symptoms, and as many as 36 million U.S. adults over the age of 50 have elevated levels of cerebral amyloid. However, symptoms can manifest so slowly that 70%-80% of those with higher tau concentrations will die of old age or other conditions before the onset of clinical Alzheimer’s (Langa & Burke, 2019). It is difficult to discern when the Mild Cognitive Impairment (MCI) phase begins because there are no definitive diagnostic criteria. Most medical professionals base their conclusions on whether or not the patient has memoryrelated complaints (Kelley & Petersen, 2007).

Some patients in the MCI stage of the disease remain stable or even recuperate normal cognitive function over time, but more than half progress to Alzheimer’s Dementia within five years (Gauthier et al., 2006). Eventually, neurofibrillary tangles and senile plaques begin to form, which presumably contribute to the well-known symptoms of memory loss and cognitive decline observed in the later stage of the disorder (Kumar et al., 2014). Given the current diagnostic techniques, the only way to diagnose a patient with full certainty is to perform a postmortem examination of the brain. For living patients, tests of cerebrospinal fluid, PET scans with amyloid beta or tau tracers, and neurocognitive assessments are used by clinicians to deliver a diagnosis (Weller & Budson, 2018).

Figure 1: Alois Alzheimer’s memorial located at his final home in Wroclaw, Poland. The inscription is in German on the left and Polish on the right. It reads: “in memory of the great psychiatric neuropathologist who lived in this building in the years 1912-1915. The Polish Society for Psychiatry, and the German Society for Psychiatry, Psychotherapy and Neurology.” Alzheimer is credited as the first to characterize the neurodegenerative disorder known today as Alzheimer’s disease Source: Wikimedia Commons

"The Center for Disease Control and Prevention lists Alzheimer’s disease as the sixth leading cause of death in adults. From 20002018, the number of deaths caused by AD increased by 146.2% and is expected to increase in the future."

The Center for Disease Control and Prevention lists Alzheimer’s disease as the sixth leading cause of death in adults (CDC, 2020). From 2000-2018, the number of deaths caused by AD increased by 146.2% and is expected to increase in the future (Alzheimer’s Association, 2020). By 2060, it is expected that one in four people residing in the U.S. will be 65 or older, and the current rate of Alzheimer’s disease in this age group is about 10%. This means that by 2060, 2.5% of the U.S. population will likely be suffering from Alzheimer’s disease (CDC, 229

Figure 2: (Left) Thioflavin stained hippocampal section from a patient suffering from Alzheimer’s disease showing senile plaques (SP), neurofibrillary tangles (NFT), and lipofuscin granules (LP: lysosomal inclusions which form during normal aging). Thioflavin is a fluorescent molecule that associates strongly with beta sheets, and it can be used to study protein aggregation in beta sheet dominated structures like amyloid plaques and tau tangles.

(Right) Immunohistochemical labeling of beta amyloid in a hippocampal section from the same patent. This technique uses an antibody that recognizes beta amyloid to mark the location of senile plaques

2020). This may even be an underestimate, as there are also a significant number of Source: Wikimedia Commons undiagnosed cases (Alzheimer’s Association, 2020). Because so many people are afflicted with the disease, the costs to the healthcare industry are astronomical; in 2018, AD in the U.S. alone had an estimated cost of $277 billion.

Currently, Medicare pays for almost half of the total costs associated with dementia, and those 65 or older often pay more than $11,000 per year "People often look for costs not covered by Medicare (CDC, 2020; to family history Alzheimer's Association, 2020). The cost of care for clues about the for a patient with dementia is more than double risk of developing a the cost for an elderly patient without dementia, and despite the work of more than 16 million particular disease, unpaid caregivers, the associated labor costs in and Alzheimer’s 2019 were estimated at $244 billion (Alzheimer’s disease is no Association, 2020). It is projected that the costs exception. AD associated with this disease will not be met by is a heritable current funding in the global healthcare system, so continuing to understand the progression of disorder, meaning this disease should be a priority in managing the probability of global healthcare (El-Hayek et al., 2017).

affliction depends largely on an individual’s genetics."

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In this article, three central aspects of Alzheimer’s disease will be addressed: biological mechanisms, clinical manifestation, and treatments. The biological mechanisms section includes an introduction to Alzheimer’s disease heritability and genetics, thorough analysis of the amyloid beta and tau hypotheses of the disease, the mechanisms by which protein aggregates contribute to neuron death, and an exploration of the neuroscience behind Alzheimer’s symptomatology. The clinical manifestation section gives an in-depth treatment of Alzheimer’s symptoms including memory loss and behavioral changes as well as the diagnostic tests and screening that can be used to diagnose patients with the disorder. The treatments section will discuss pharmacological interventions for treatment of memory and behavior and also

explore alternatives to drug therapy including electromagnetic stimulation, stem cells, and neural prosthetics. The conclusion of this article will consider homeostatic mechanisms promoting Alzheimer’s resistance as well as possible preventative measures.

Molecular Mechanisms People often look to family history for clues about the risk of developing a particular disease, and Alzheimer’s disease is no exception. AD is a heritable disorder, meaning the probability of affliction depends largely on an individual’s genetics. Genome wide association studies (GWAS), in which the genetic sequences from thousands of patients with a disease are compared to find shared genes, have given a heritability estimate between 58-79% for lateonset Alzheimer’s disease (LOAD) (Rebecca Sims et al., 2020). This means that 58-79% of the risk associated with LOAD is attributable to genetics, while the remaining 21-42% is determined by environmental risk factors encountered during an individual's lifetime.

Twin studies have corroborated this range and provide convincing evidence that AD has a significant genetic component (Gatz et al., 1997).

Early-onset Alzheimer’s, however, shows heritability of over 90%, indicating a much stronger dependence on genetic factors (Sims et al., 2020). The strong genetic dependence of both early and late-onset AD allows clinicians and researchers to construct polygenic risk profiles, which examine specific gene variants within an individual to determine if they are high risk for developing AD (Mez et al., 2016).

There are also a number of environmental risk factors that interact with risk genes to influence an individual’s AD susceptibility including

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Figure 3: Cleavage of the amyloid precursor protein (APP) by both beta and gamma secretases is required for beta amyloid (Aβ) production. Cleavage by alpha secretase occurs in the middle of Aβ, so activity of this protease reduces Aβ production.

Following cleavage by beta and gamma secretases, Aβ diffuses into the extracellular space where it may aggregate to form extracellular beta amyloid plaques. Imbalance between Aβ production and clearance is at the center of amyloid pathology in Alzheimer’s disease Source: Wikimedia Commons

diet, cognitive stimulation, and other lifestyle choices (Grant et al., 2002).

Marioni and colleagues used GWAS to identify several protein-coding genetic loci associated with LOAD including ADAM10, BCKDK/ KAT8, ACE, and APOE (Marioni et al., 2018).

ADAM10 is involved in the cleavage of the amyloid precursor protein and is thought to seed the initial aggregation of beta amyloid plaques (Suh et al., 2013). The BCKDK/KAT8 locus includes the VKORC1 gene, the drug target of the anticoagulant warfarin which has shown therapeutic potential in treating LOAD (Takeuchi et al., 2009). ACE is involved in regulating angiotensin II levels and cerebral blood flow, and it is also implicated in the atrophy of the hippocampus and amygdala in AD. Mutations in the ACE gene also correlate with CSF tau concentrations, suggesting a connection between this protein and the formation of neurofibrillary tangles (Sleegers et al., 2005). The APOE gene codes for the protein apolipoprotein E involved in fat metabolism and is strongly associated with the formation of beta amyloid plaques (Marioni et al., 2018).

Marioni’s research team also found that genes linked to beta amyloid production, neurofibrillary tangle assembly, immune response, or cholesterol and lipid transport were implicated in LOAD (Marioni et al., 2018).

Groups of genes associated with the assembly of protein-lipid complexes or high-density lipoprotein particles have also been associated

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with AD (Jansen et al., 2018). Using ChIP and LDscore regression, the Tansey Research Group found that malfunctioning immune cells (macrophages and microglia) were also linked to LOAD, although it is unclear if this malfunction is a cause, consequence, or coincidence (Tansey et al., 2018). It should be noted that the maximum predictive power of genomic analysis is finite. The Price group used receiver operating characteristic analysis and area under the curve analysis to determine that the maximum predictive accuracy of genomic profile analysis is 82% (Price et al., 2017). Regardless, the identification of genes associated with Alzheimer’s provides important insight into the molecular pathology of the disease and possible therapeutic targets that can be examined in the lab.

"In addition to genomic risk factors, there are other biological factors that may influence AD susceptibility. Some studies have found that epigenetics, in which environmental events regulate gene expression, are implicated in lateonset Alzheimer's disease (LOAD)."

In addition to genomic risk factors, there are other biological factors that may influence AD susceptibility. Some studies have found that epigenetics, in which environmental events regulate gene expression, are implicated in LOAD (Jansen et al., 2018). These epigenetic factors include histone deacetylation and DNA hypermethylation of protective genes for Alzheimer’s-related neurodegeneration, as well as histone acetylation and DNA hypomethylation of genes that increase Alzheimer’s risk (Esposito & Sherr, 2019).

Chromatin interactions, in which distant regions of DNA interact and influence one another, may also affect epigenetic regulation of Alzheimer’s-associated genes (Jansen et

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Figure 4: Two crossed beta sheets stack on top of one another to form an amyloid fibril. Steric zippering and hydrophobic interactions facilitate tight packing of amyloid peptides in the crossed beta sheet. The beta strands run perpendicular to the fibrillar axis, giving a favorable conformation for packing of crossed beta sheets into an amyloid fibril Source: Wikimedia Commons

al., 2018). Ultimately, there are genetic and environmental risk factors for Alzheimer’s disease, and it is often the interaction between them that contributes to the manifestation and progression of the disease.

The Beta Amyloid Hypothesis

"The discovery that beta amyloid was the core component of senile plaques in 1985 spurred an incredible amount of research on this protein, and beta amyloid has remained at the center of Alzheimer’s research ever since."

The discovery that beta amyloid was the core component of senile plaques in 1985 spurred an incredible amount of research on this protein, and beta amyloid has remained at the center of Alzheimer’s research ever since (Masters et al., 1985; Hardy & Selkoe, 2002). As mentioned before, the beta amyloid hypothesis suggests that the Aβ protein is the principle causal factor underlying neurodegeneration in AD, and that other molecular changes that occur during the disease (such as the formation of neurofibrillary tangles of tau) are a consequence of Aβ accumulation in the brain (Hardy & Selkoe, 2002). This hypothesis has received a great deal of scrutiny in recent years, largely due to the failure of Aβ-targeting drugs to show efficacy in clinical trials, as well as the lack of a clear causal connection between Aβ accumulation and neurodegeneration in the lab (Loera-Valencia et al., 2019). Nonetheless, the beta amyloid hypothesis has dominated AD research, with over 60,000 studies published about this protein in the PubMed database as of November 2020.

Amyloid beta is created by proteolytic cleavage of an integral membrane protein called amyloid precursor protein (APP) by enzymes known as secretases (MacLeod et al., 2015). In normally functioning neurons, APP plays roles in microbial response and the coagulation cascade (Stakos et al., 2020). Turnover of APP is necessary for the proper cell function, but its proteolytic cleavage may lead to the production of excess extracellular Aβ which, when not effectively cleared, can lead to the formation of senile plaques (Hardy & Selkoe, 2002). There are three protease complexes that are implicated in the production of Aβ: α-secretase, β-secretase, and γ-secretase. α and β-secretases are fully secreted enzymes, while γ-secretase is itself an

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integral membrane protein and thus cuts APP at a site located within the phospholipid bilayer (MacLeod et al., 2015). Cleavage of APP by β and γ-secretase forms Aβ, while α-secretase cuts at a site within the Aβ protein and therefore reduces its production (Figure 3). Mutations in APP as well as α, β, and γ-secretases have been associated with increased risk of developing AD (Hardy & Selkoe, 2002).

After Aβ is cleaved from APP, monomers may oligomerize and begin to form senile plaques.

The basic structural motif from which Aβ aggregates are formed is known as a crossed β-sheet. In this structure, β-sheets of two Aβ polypeptides stack on top of one another in a regular pattern, resulting in a supramolecular protein complex known as an amyloid fibril (Figure 4) (Reik, 2017). The individual β-stands that comprise the crossed-β-sheet run perpendicular to the fibril axis, allowing for thousands of Aβ polypeptides to pack into a small volume. To discover the structure of Aβ, researchers have utilized nuclear magnetic resonance (NMR) and X-ray crystallography (Chen et al., 2017; Jeol, 2020). NMR spectroscopy allows for the determination of protein structure because nuclei close together in space influence each other (a phenomena in NMR known as the nuclear Overhauser effect); information on the distances between different parts of the protein can then be used to determine the protein’s three-dimensional structure (Chen et al., 2017). Additionally, X-ray crystallography can resolve protein structure because X-rays diffract in predictable ways; this information is used to generate an electron density map of the protein (Jeol, 2020; Krishnan & Rupp, 2012). NMR-based models have revealed the structure of the Aβ monomer: four β-strands linked by two loops, an asparagine ladder, and a C-terminus which folds back into the core of the peptide. These pieces result in the characteristic β-sheet folds of beta amyloid (Riek, 2017).

As noted above, the individual β-strands of a crossed-β-sheet run perpendicular to the fibril axis, allowing for tight packing of thousands

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Figure 5: Long term potentiation (LTP) and long term depression (LTD) of glutamate synapses involves insertion or removal of AMPA receptors at the post-synapse, respectively.

This process is mediated by calcium influx through NMDA receptors. However, increased membrane permeability to calcium chronically increases intracellular calcium levels, and in a homeostatic mechanism, calcineurin removes phosphates from AMPA receptors and triggers their removal from the post-synapse. Aβ-mediated increase in membrane permeability to calcium may facilitate synaptic depression and memory loss in Alzheimer’s disease Source: Wikimedia Commons

of Aβ polypeptides. The repetitive nature of Aβ means that the complex has some destructive properties. Specifically, the crossed β-sheets can grow through amyloid seeds by recruiting soluble amyloid, which causes it to spread. The potential for spreading depends on several factors including the concentration of soluble amyloid, the growth rate of the amyloid aggregate, as well as the rate of amyloid breakage into seeds. This is similar to prion diseases, which are caused by misfolded proteins that catalyze further misfolding of native proteins they encounter. It is important to note, however, that prions can be transmitted between living organisms, while amyloid is only transmissible between cells in a single individual. As such, beta amyloid is classified as a prionoid, a protein with prion-like growth, due to its ability to jump between cells (Harbi & Harrison, 2014; Riek, 2017).

in individuals with high cholesterol, which is another risk factor for LOAD (Lai et al., 2010).

Amyloid aggregates are not inherently toxic, despite their association with many diseases; instead, it is believed that its toxicity depends on the conformational state of the amyloid protein.

Aβ variants associated with AD often have hydrophobic patches on their surface which may result in toxicity due to oligomerization (clumping together) of amyloid monomers through hydrophobic interactions. Studies also indicate that the toxic amyloid aggregates have intermolecular β-sheet secondary structures (Riek, 2017). Furthermore, extracellular Aβ peptides commonly bind onto lipid rafts, which may serve as catalysts for beta amyloid aggregation. Lipid rafts are more prevalent

There is a growing body of research suggesting that synaptic plasticity is the biological process mediating Alzheimer-related neurodegeneration. Synaptic plasticity refers to the strengthening and weakening of synapses through a variety of mechanisms, one of which is the insertion and removal of receptors at the postsynaptic cleft (Loera-Valencia et al., 2019).

The AMPA and NMDA receptors are glutamategated ion channels important for excitatory signal transduction in neurons (Roa & Finkbeiner, 2007). These receptors are trafficked into the synaptic cleft in response to calcium influx, which subsequently strengthens the synapse; removal of these receptors from the

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One proposed mechanism underlying beta amyloid toxicity implicates the immune system.

Studies suggest that beta-amyloid aggregates can cause sensitization of Toll-like receptor 4 (TLR4) (Craig et al., 2020). Toll-like receptors are responsible for detecting invading pathogens and initiating an immune response. In addition, activation of TLR4 can increase expression of the proinflammatory cytokine TNFα. When Aβ aggregates are present in Alzheimer’s patients, there is an increased production of TNFα, causing long-term potentiation deficits in the hippocampus which can lead to neuronal death (Jin et al., 2008). In this view of the beta amyloid hypothesis, neuron death is caused by immune activation, inflammation, and dysregulated synaptic plasticity.

"One proposed mechanism underlying beta amyloid toxicity implicates the immune system.

Studies suggest that beta-amyloid aggregates can cause sensitization of Toll-like receptor 4 (TLR4)."

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Figure 6: Tau phosphorylation by a variety of kinases promotes aggregation and dysfunction of this microtubule-associated protein. Wang and colleagues have developed an inhibitor (MK-8719) for the enzyme O-GlcNAcase (OGA) which removes O-linked sugars from the tau protein (Wang et al., 2020). This figure shows that the activity of OGA and kinases promotes tau aggregation, while the activity of phosphatases and O-GlcNAc transferase (OGT) reduces tau aggregation.

Source: Wikimedia Commons

synaptic cleft weakens the synapse (Figure 5).

This strengthening and weakening of synapses is a crucial process in memory formation and extinction, so it is unsurprising that synaptic plasticity is dysregulated in AD (Guntupalli et al., 2016).

"Tau is a highly soluble microtubuleassociated protein (MAP) that regulates microtubule stability, axonal transport, and neurite outgrowth."

Notably, death of neurons in AD patients occurs before the appearance of histologically visible Aβ plaques (Klein, 2006), and researchers have shown that nanomolar concentrations of soluble Aβ oligomers can have a toxic effect on dendritic spines (Lacor et al., 2007). One hypothesis for why soluble Aβ can lead to neuron death before the appearance of plaques is that Aβ oligomers increase membrane permeability to calcium.

Lacor’s research team showed that nanomolar concentrations of solubilized Aβ aggregates can trigger AMPA receptor endocytosis in cultured hippocampal neurons, weakening these synapses (Lacor et al., 2007). This weakening of synapses in the hippocampus is thought to depend on the calcium-dependent phosphatase calcineurin. Increased membrane permeability to calcium increases steady-state intracellular calcium levels, increases calcineurin expression, and decreases postsynaptic concentration of excitatory glutamate receptors, leading to memory erasure (Wang et al., 2017). Thus, calcineurin antagonists have been proposed as a possible molecular target for Alzheimer's treatment and prevention (Loera-Valencia et al., 2019).

The complexity and diversity of Aβ pathogenesis has made it difficult to determine a causal link between Aβ and neuron death in Alzheimer’s disease, and additional research remains to be done. It is also likely that the mechanisms of Aβ toxicity varies between brain areas and neuron types. The preferential loss of excitatory (glutamatergic) cells in the hippocampus and the cerebral cortex likely implicates glutamate receptor dynamics in Aβ-mediated cell death; it

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is likely that Aβ oligomers disrupt intracellular calcium signaling and cellular homeostasis, causing synaptic inhibition and the eventual death of entire neurons.

The Tau Hypothesis Tau is a highly soluble microtubule-associated protein (MAP) that regulates microtubule stability, axonal transport, and neurite outgrowth (Johnson & Stoothoff, 2004).

Microtubules are highly concentrated in neurons, especially in the axon; in fact, the first biochemical studies of microtubules were conducted on axoplasm extracted from squid giant axons (Kobayashi et al., 1986). Tau binds to and stabilizes microtubules in neurons, helping provide the neuron with structure as well as a network used to transport cargo to different subcellular compartments (Ellison, 2019). Furthermore, tau is expressed all over the brain, most strongly in hippocampal neurons, but it is also found in the brain’s glial cells (specifically oligodendrocytes and astrocytes), as well as the peripheral nervous system (PNS) (Johnson & Stoothoff, 2004).

Morphological and biochemical studies have found that normal tau is typically present in both presynaptic and postsynaptic terminals, and when hyperphosphorylated, it will misfold at both of these sites (Tai et al., 2012) As a MAP, tau interacts with the protein tubulin (the core component of microtubules), specifically at the microtubule-binding domain (Kent et al., 2020). The amount of tubulin found in mature neurons is over ten times the concentration of tau, so practically all tau is microtubule-bound in the cell (Ackmann et al., 2000). To confirm the function of tau in mature neurons, tau knockdown experiments have been conducted in which a mutant ‘pseudo-hyperphosphorylated’ tau was studied. The results of these experiments

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showed a reduction of neuronal outgrowth and microtubule density, as well as disruption of axonal extensions (Kent et al., 2020). This shows that hyperphosphorylation of tau results in an inability to properly stabilize microtubules, highlighting a possible AD-related alteration of tau function upon phosphorylation.

In normal brains, the optimal measured phosphorylation of tau is usually 2-3 moles of phosphate per mole of tau (Iqbal et al., 2010).

AD patients have about 3-4 times more tau phosphorylation than this, leading to improper interactions of tau with tubulin and eventually to the formation of the intracellular neuronal inclusions known as neurofibrillary tangles (Wittmann et al., 2001). These large aggregates act as physical barriers to axonal transport in the neuron, disrupting communication through synapses with toxic effects (Witmann et al., 2001) Tau phosphorylation is catalyzed by a variety of protein kinases. Phosphorylation sites on the tau protein are divided into two major classes: the Ser/Thr-Pro sites and the non-Ser/Thr-Pro sites. The majority of the kinases involved in phosphorylation of the first class are prolinedirected protein kinases (PDPK) and include the mitogen and stress-activated protein kinases, glycogen synthase kinase 3 (GSK 3) and cyclindependent kinases (CDC 2 and CDK5) (Drewes et al., 1992; Roder et al., 1997; Goedert et al., 1997; Braudier and Cole. 1987). The kinases involved with the second class include microtubule affinity-regulating kinase (MARK), calciumcalmodulin dependent protein kinases (CaMPK II), cyclic AMP dependent kinase (PKA), casein kinase II, and phosphorylase K (Paudel, 1997).

To achieve phosphorylation of recombinant Tau, numerous kinases can be used. On the other hand, the dephosphorylation of Tau is regulated by protein phosphatases, which are enzymes that cleave phosphate groups from proteins. Notably, in vitro dephosphorylation of neurofibrillary tangles will cause the tau aggregates to dissolve and restore tau function (Chohan et al., 2007). There is no doubt that hyperphosphorylated tau leads to the formation of NFTs, so they have been characterized as a “reliable and early marker of the degenerating process” (Buee & Delacourte, 2001). Several immunoblot experiments have measured levels of tau in different cortical areas; tau phosphorylation was found in all of them, with the exception of the primary motor cortex and the visual cortices (Brodmann areas 4 and 17) (Vermersch et al., 1992; Holzer et al., 1994).

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New research suggests that O-linked glycosylation of tau may also play a role in its aggregation. Wang and colleagues at Merck & Co. and Alectos Therapeutics recently published an article about a new drug (MK8719) that inhibits the removal of O-linked sugars from the tau protein (Wang et al., 2020).

Notably, these sugars are added to serine and threonine residues in the tau protein, which effectively blocks the phosphorylation sites of Ser/Thr-Pro kinases. By blocking the removal of the sugars from the tau protein, Wang’s research team hopes to decrease levels of tau hyperphosphorylation, reduce tau aggregation, and prevent NFT assembly (Wang et al., 2020). This study highlights the importance of posttranslational modifications in protein function and suggests many different pathways and molecules that are implicated in Alzheimer’s disease.

Structural studies of tau have focused on elucidating Tau’s pathogenic mechanisms.

There are six isoforms of the tau protein that may be generated through alternative splicing, and each of these can be further modified via post-translational modification, giving tau a tremendous amount of structural variety in the human brain (Fichou et al., 2019).

There are two common features of these tau isoforms that facilitate their pathogenic function: a proline rich sequence which acts as the main site for phosphorylation and a microtubule binding domain which facilitates tight packing of phosphorylated tau into tau filaments (Barthélemy et al., 2016; Seidler et al., 2018). Native tau is an intrinsically disordered protein, meaning that it lacks a well-defined tertiary structure, making it difficult to study through traditional techniques like X-ray crystallography and NMR (Fichou et al., 2019; Ambadipudi et al., 2017). However, cryogenic electron microscopy, in which electron diffraction patterns from a frozen sample can give structural detail, have characterized tau aggregates and tau-microtubule complexes (Kellogg et al., 2018). Similar to amyloid beta plaques, the main component of tau filaments is a crossed-β-sheet. It has been found that two homologous hexapeptide sequences (PHF6 & PHF6*) located in the microtubule binding domain form steric-zippers and seed tau aggregation (Seidler et al., 2018). While native tau proteins are highly soluble and show preference for microtubule association and neuron cytoskeleton stabilization, the hyperphosphorylated form of this protein

"Structural studies of tau have focused on elucidating Tau’s pathogenic mechanisms. There are six isoforms of the tau protein that may be generated through alternative splicing, and each of these can be further modified via post-translational modification, giving tau a tremendous amount of structural variety in the human brain."

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Figure 7: Aggregation of hyperphosphorylated tau destabilizes microtubules and causes depolymerization of tubulin subunits.

Microtubules are necessary for neuronal function, and the disassembly of the microtubule cytoskeleton is the mechanism behind Alzheimer’s-related neurodegeneration according to the tau hypothesis Source: Wikimedia Commons

commonly aggregates in crossed-β-sheets. The mechanisms of this transition are still being actively studied, and many researchers are focusing on inhibition of tau phosphorylation and aggregation as a possible Alzheimer’s treatment (Seidler et al., 2018; Pradeepkiran & Reddy, 2019).

"Tau’s disorderly nature causes it to be both unstable and reactive with other molecules, and it means it can take up 27 times more space than an equivalent compact molecule in solution."

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Tau’s disorderly nature causes it to be both unstable and reactive with other molecules, and it means it can take up 27 times more space than an equivalent compact molecule in solution (Mylonas et al., 2008). This ultimately allows the protein to make transient interactions with surrounding proteins in the crowded environment of a cell. It is this hyper-reactivity that leads to interactions with kinases, tau hyperphosphorylation, and the development of neurofibrillary tangles (Mandelkow & Mandelkow, 2012). The transition between solubilized to aggregated tau and the spreading of tau filaments depends on a variety of factors.

Enzymes which modify the structure and concentration of tau protein – including kinases, phosphatases, and proteases – may contribute to the initial formation of aggregate seeds (Fichou et al., 2019). Notably, truncated tau variants with C-terminal deletions after Asp421 or Glu391 have been shown to accelerate formation of neurofibrillary tangles in a mouse model of AD, suggesting a potential role of caspases (proteases which cut after these residues) in the initial formation of tau filaments (Yin & Kuret, 2006). Solid-state NMR spectroscopy studies have shown that only a 19 amino acid stretch between residues 306-324 consistently forms β-sheets in its solubilized state, suggesting that

C-terminal truncation may reduce flexibility of intrinsically disordered domains and facilitate intermolecular β-sheet steric-zippers (Daebel et al., 2012).

Once these truncated tau seeds begin to form, they can jump between neurons and catalyze the aggregation of native, solubilized tau in these cells. Trans-synaptic spreading of proteopathic tau seeds through vesicle fusion has been observed in mouse neurons, suggesting that these aggregates may be spread through synaptic connections between connected brain nuclei (Dujardin et al., 2014). In patients with Alzheimer’s, immunohistochemistry has been used in post-mortem brain tissue to show the extensive spreading of hyperphosphorylated tau between pyramidal neurons of the neocortex (Braak & Del Tredici, 2018). Ultimately, it is the dissociation of tau from these microtubules that is thought to facilitate neuron death in the tau hypothesis of AD, and this dissociation is facilitated by hyperphosphorylation, deglycosylation, tight packing into a tau fibril, and aggregation of tau fibrils into neurofibrillary tangles (Fulga et al., 2007; Minamide et al., 2000). Additional research is needed to better understand the extensive posttranslational modifications that occur with the tau protein, as well as the factors leading to the initial formation of NFTs. A better understanding of tau’s molecular pathology may result in novel AD therapeutics in the future.

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Figure 8: Atrophy of a wide variety of brain areas is observed in Alzheimer’s disease, but areas with high concentrations of cholinergic neurons seem to be preferentially impacted.

Shrinkage and improper functioning of the hippocampus is likely the source of memory impairments in Alzheimer’s disease, while neuron death in the cerebral cortex may explain various cognitive and behavioral changes (Source: Wikimedia Commons

Neuron Subtypes and Brain Regions Impacted

by AD A consistent finding in patients with Alzheimer’s disease is that cholinergic neurons, which use the neurotransmitter acetylcholine (ACh), are some of the first cells to die during the disease (Schliebs & Arendt, 2006). A metabolic cascade for the maturation and degradation of nerve growth factor (NGF), one of the neurotrophic factors that regulate synapse formation, could explain the cholinergic system’s vulnerability (Debeir et al., 1999). During maturation, precursor nerve growth factors are continually converted into mature nerve growth factors which then bind to receptors on cholinergic neurons (TrkA receptors), stimulating the release of ACh and activation of muscarinic receptors (M1, M3) on the post-synapse. Maturation of NGF favors the non-amyloidogenic pathway (α-secretasemediated, Figure 3) and therefore reduces Aβ production (Bruno & Cuello, 2006; Nitsch et al., 1992). The enzyme matrix metalloproteinase-9 (MMP-9), which facilitates NGF degradation, is highly concentrated in cholinergic neurons and may explain why Aβ accumulates preferentially at cholinergic neurons (Cuello & Bruno, 2007).

The expression of the p75 neurotrophic receptor (p75NTR) may also contribute to the vulnerability of cholinergic system to Aβ peptides (Perini et al., 2002). p75NTR mediates NGF-induced survival during early cholinergic cell development but plays a role in apoptosis for mature cells (Barrett & Bartlett, 1994).

Activation of p75NTR is thought to facilitate NGF degradation and increase activity of the amyloidogenic pathway (Clewes et al., 2008).

Because cholinergic neurons impacted by early stages of AD express high levels of p75NTR, this receptor could potentially be used as a clinical biomarker for early AD detection (Woolf & Butcher, 1989).

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"During the course of Alzheimer’s disease, plaques and NFTs accumulate to varying degrees in different brain areas.

One of the first areas where Aβ plaques begin to accumulate is in neocortical regions, which have a high density of excitatory pyramidal neurons and are responsible for higher order functions such During the course of Alzheimer’s disease, plaques and NFTs accumulate to varying as decision making."

Studies also demonstrate that cholinergic neurons are particularly vulnerable to the betaamyloid toxicity. Inhibition of synaptic plasticity

by Aβ oligomers has been observed in the rat hippocampus and cortex (cholinergic neuron dense regions), but not the striatum (far fewer cholinergic neurons), suggesting a higher susceptibility of ACh-expressing neurons to the toxic effects of Aβ (Kar et al., 1998). Long term exposure to Aβ may also decrease activity of choline acetyltransferase (ChAT), an enzyme required for ACh synthesis, and also inhibit ACh release (Pedersen et al., 1996). These impacts on the cholinergic system decrease neural activity in cognitive-related regions of the brain, demonstrating the connection between neurodegeneration and the dementia phenotype in AD (Hasselmo et al., 1992).

degrees in different brain areas. One of the first areas where Aβ plaques begin to accumulate is in neocortical regions, which have a high density of excitatory pyramidal neurons and are responsible for higher order functions such as decision making (Arriagada et al., 1992).

Aβ plaques next accumulate in the limbic system, the region of the brain containing the hippocampus and other structures regulating memory and emotion. Next, Aβ plaques affect the diencephalon, a region containing the thalamus, hypothalamus, and the basal forebrain. Aβ plaques accumulate lastly in the cerebellum, which is the center for voluntary movement (Mrdjen et al., 2019). However, it should be noted that the density of Aβ plaques does not necessarily correlate with the severity of neuron death in a specific brain area (Mufson et al., 2015), and several mouse models have failed to find a relationship between the number of Aβ plaques and neuronal loss in the hippocampus (Shmitz et al., 2004).

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Neurofibrillary tangles of tau also show a stereotypical appearance in different brain areas.

NFTs first accumulate in the hippocampus and the entorhinal cortex, which serves as a physical link between the hippocampus and the neocortex (Mrdjen et al., 2019). The hippocampus, which is one of the first regions to be affected by AD, develops slowly during infancy and is a highly neuroplastic region in adulthood, highlighting a link between synaptic plasticity and neuron death (Figure 5) (Arriagada et al., 1992; Li et al., 2014). This area suffers significant synaptic loss in those with AD and accumulates far more NFTs than Aβ plaques in most patients, giving strong support for the tau hypothesis of AD (Loera-Valencia et al., 2019). NFTs next affect the Source: Wikimedia Commons locus coeruleus, then the basal forebrain, and finally the neocortex (Arriagada et al., 1992). It is thought that neuron death in the hippocampus is the primary mechanism underlying memory loss in Alzheimer’s disease, while death of neurons in the cortex may explain behavioral changes (Li et al., 2014).

Figure 9: The Wisconsin Card Sorting Test (WCST) is a cognitive test used worldwide as a measure of neuropsychological functioning. Patients are asked to sort stimulus cards according to different principles - by color, form, or number of shapes shown. Because the patient must implement problem-solving strategies across changing conditions to achieve a goal, the WCST is considered a measure of executive function, abstract reasoning, and neuropsychological impairment (Grant, n.d.). Patients with Alzheimer’s disease often find the WCST to be difficult

Clinical Manifestation "Brain atrophy occurs slowly in healthy individuals, with about 0.2-0.41% of brain volume disappearing every year. However, in individuals with AD, that rate may be magnified tenfold."

The clinical manifestation of Alzheimer’s disease can be an incredibly useful tool in predicting the speed of the disease’s progression. Memory loss, the most well-known symptom of AD, is often tested in a clinical setting for diagnostic purposes. Neurocognitive tests can shed light on a patient’s cognitive dysfunction and indicate which regions of the brain have been affected.

While the onset of AD is rare in the majority of the population, AD is one of the leading causes of death for individuals above 65. Age is the greatest risk factor for AD, but scientists are still attempting to understand why. Researchers and clinicians agree that it is crucial to diagnose AD patients early in order to implement effective interventions to slow the progression of the disease. Efforts towards improved diagnostic technology such as clinical biomarkers and PET scans demonstrate progress towards earlier diagnoses of AD. Today, researchers and clinicians are continuing to study the clinical manifestations of Alzheimer’s disease to develop efficient and standardized methods for the AD diagnosis, treatment, and prevention.

Brain Atrophy and Cognitive Decline Brain atrophy occurs slowly in healthy individuals, with about 0.2-0.41% of brain volume disappearing every year. However, in individuals with AD, that rate may be magnified tenfold (Jahn, 2015). Alongside accelerated brain

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atrophy, there are six cognitive domains that are negatively affected in patients suffering from AD: memory, executive functioning, language, visuospatial functioning, attention, and affect (Gold, 2008).

Clinical trials have indicated that the atrophy process typically starts with memory complaints. Specifically, memory complaints may include impaired episodic memory, speech production, or even visual orientation.

The disruption of semantic memory is associated with disturbances in the anterior and inferolateral temporal lobes, and the loss of neuronal dendritic trees in the frontal lobe has been associated with lower levels of cognitive activity (Gold, 2008). Further cognitive functions associated with the frontal subcortical circuits such as the ability to problem-solve, create goals, deploy response alternatives, and modify behavior are also impaired in individuals with AD (Jahn, 2015). Cognitive tests including the Wisconsin Card Sorting Test, the Stroop Test, and the Tower of London Test, centered around problem-solving and cognitive flexibility, are difficult for AD patients (Jahn, 2015).

In addition to memory deficits, AD is accompanied by a multitude of behavioral changes ranging in both variety and severity; depression, aggression, apathy, and psychosis are among the core neuropsychiatric symptoms.

Although certain genes and biomarkers have been recognized as associative links between AD pathology and behavioral disturbances, there is a wide variation of AD symptoms.

Furthermore, levels of familiarity with the patient’s environment can either exacerbate or mitigate disease progression, with less familiarity being detrimental. The presence of neuropsychiatric symptoms (NPS) and behavioral anomalies are indicative of poor DARTMOUTH UNDERGRADUATE JOURNAL OF SCIENCE

disease outcomes due to significant impacts on quality of life and functional independence (Li et al., 2014).

AD is the principal cause of dementia in the elderly. Between 30% and 90% of all dementia patients suffer from the NPS listed above, with personality changes affecting nearly 70% of all AD patients. Frontotemporal dementia (FTD) in particular causes emotional blunting and declines in social interpersonal conduct and social awareness (Müller-Spahn, 2003).

Behavioral changes and their evolutions over the patient’s lifetime differ in severity more frequently than disorders involving only cognitive decline (Gauthier et al., 2010).

Nonetheless, certain behavioral changes worsen in tandem with cognitive decline. Aggression, for example, has been found to increase as cognitive impairment increases (MüllerSpahn, 2003). Both aggression and agitation are perhaps the most arduous symptoms for caregivers. They, along with depression and psychosis, are hallmarks of institutionalized Alzheimer’s patients (Gauthier et al., 2010).

The presence of such NPS is indicative of rapid cognitive deterioration caused by various degenerative processes associated with AD. Since Alzheimer’s is a diagnosis that can only be confirmed via autopsy, many studies classify NPS as “presumed AD,” possibly contributing to low consistency among behavioral diagnoses and therefore high variability in disease outcomes (Li et al., 2014).

While AD can only be confirmed via autopsy, there are diagnostic criteria for AD in living patients. According to the Diagnostic and Statistical Manual of Mental Disorders, a person with AD must have memory impairment and progressively deteriorating cognitive deficits that are not attributable to other forms of dementia that affect the person’s daily life.

Additionally, one or more of the following must

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be present: deterioration of language abilities, impaired ability to recognize and/or identify objects, difficulty executing motor activities, or difficulty with daily life and holding a job (George et al., 2011).

An MCI diagnosis requires change in cognition and impairment in at least one cognitive domain, but the impairment does not (at this stage) interfere with the social or occupational activities nor the ability to live independently with minimal assistance (Albert et al., 2011).

Alzheimer’s dementia is diagnosed when a patient meets the criteria for all-cause dementia as well as criteria specific to AD. These include gradual onset and documented history of worsening cognition with the most prominent deficits being either amnestic presentation (impairment in learning and recall) or non-amnestic presentation (language presentation, visuospatial presentation, or executive dysfunction) (McKhann et al., 2011). There is currently no way of predicting which individuals will progress from MCI to Alzheimer’s dementia, but tests for the presence of Aβ plaques and hyperphosphorylated tau in CSF can aid in diagnosis (Alzheimer’s disease Diagnostic Guidelines, 2020).

Figure 10: Aggression is associated with several neurochemical and neuropathological factors in Alzheimer’s patients. One study found a correlation between aggression in Alzheimer’s patients and damage to the brain’s locus coeruleus. Since the locus coeruleus is a source of norepinephrine, a damaged locus coeruleus suggests that there are changes elsewhere in the brain to compensate for reduced norepinephrine levels which contribute to aggression Source: Wikimedia Commons

Behavioral Comorbidities in AD The lack of clear clinical definitions and neuropsychiatric diagnostic tools makes it difficult to determine specific behavioral changes. This is an area of much-needed research as behavioral changes are ubiquitous in Alzheimer’s patients, with one study estimating that 88% were affected (Mega et al., 1996).

Depression is one of the most common comorbidities, with 40% of Alzheimer’s patients exhibiting symptoms of depression within 5 years, although recent studies suggest this number may actually range from 25% to 75% (Li et al., 2014). Evidence shows that Alzheimer's patients diagnosed with clinical depression are likely to experience worse clinical outcomes.

However, few controlled clinical trials have been conducted to study the use of antidepressant therapy for depressed Alzheimer’s patients.

Still, it is unclear whether depression is a cause or consequence of Alzheimer’s disease. Studies of molecules such as Aβ and APOE have indicated possible overlap in the genetic risk of AD and depression. For example, one study found that higher serum concentrations of Aβ at baseline were predictive of both depression

"Depression is one of the most common comorbidities, with 40% of Alzheimer’s patients exhibiting symptoms of depression within 5 years, although recent studies suggest this number may actually range from 25% to 75%."

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and Alzheimer’s disease over 5 years (Li et al., 2014).

Apathy is another comorbidity of Alzheimer’s associated with decreased blood flow to the prefrontal cortex. Researchers also attribute apathy to hypometabolism (decreased glucose consumption) in the left orbitofrontal areas. A similar hypometabolism of the left dorsolateral prefrontal regions is associated with depression.

While Alzheimer’s patients may exhibit both apathy and depression, the two disorders bear different implications for a patient’s future.

Apathy is associated with a decline of MCI to a diagnosis of Alzheimer’s, with one study finding that MCI patients with apathy were seven times more likely than those without to progress to Alzheimer’s disease; depression does not bear this association. Furthermore, Alzheimer’s patients may experience a stabilization of depression symptoms but an increase in apathy (Li et al., 2014).

Early intervention in AD has shown potential in slowing cognitive deterioration, but early-stage diagnosis of AD has proven difficult. Many early symptoms of Alzheimer’s disease are also associated with other neurodegenerative disorders, and in some cases, early-stage Alzheimer's can be challenging to distinguish from typical aging (Leifer, 2003). Thus, medical professionals need tests that will detect earlystage AD before the onset of more serious symptoms. Although brain-imaging tests alone cannot diagnose AD, they can help rule out other potential diagnoses such as hemorrhages, brain tumors, and strokes. PET scans are particularly useful in detecting amyloid aggregation, but these tests can be costly.

Cerebrospinal fluid testing is a more financially favorable alternative that can distinguish AD from other neurological diseases by assessing levels of beta-amyloid and tau (Budson, 2019).

Another option is through genetic analyses and polygenic risk profiles, which help to gauge a person’s susceptibility to developing AD given their age and family history (Zick et al., 2005).

One gene that is commonly screened in these tests is the APOE gene; the presence of the APOE risk allele is not necessary nor sufficient to cause AD, but the presence of one APOE allele increases risk two- to three-fold, and the presence of two APOE alleles increases the risk to fifteen-fold or higher for the Caucasian population. More than half of clinically diagnosed patients have the APOE risk allele, however, APOE genotyping is not currently recommended, as it may not provide accurate information to clinicians and patients in the absence of other tests (Zick et al., 2005).

Like depression and apathy, aggression and agitation have been associated with several neurochemical and neuropathological factors in Alzheimer’s patients. Researchers have found hypoperfusion in the mesial temporal lobe and APOE 4 allele frequency to be associated with aggression in Alzheimer’s patients. One study showed a correlation between patient aggression and damage to the brain’s locus coeruleus, which is a small area in the pons that is a source of norepinephrine. This suggests that changes elsewhere in the brain to compensate for reduced norepinephrine levels could contribute to aggression. Another study found the ratio of phospho-tau to tau to be higher in aggressive Alzheimer’s patients compared to non-aggressive Alzheimer’s patients (Li et al., 2014).

Scientists are hopeful that clinical biomarkers may be used in the future for early diagnosis of AD. Researchers studying blood plasma have identified 18 signaling proteins that form a tentative plasma biomarker phenotype that is highly specific to Alzheimer’s dementia, and they are often present in blood before a clinical diagnosis is given (Ray et al., 2007).

These protein expression patterns were shown to distinguish patients with AD and subjects with other forms of dementia, as well as control subjects. Dysregulation of these 18 signaling proteins is also involved in hematopoiesis and apoptosis, both of which are linked to AD, as well as deficits in neuroprotection and neurotrophic activity (Ray et al., 2007). This field is still actively searching for biomarkers that can be used for early diagnosis of AD.

Another study yielded similar results, finding personality changes in subjects with cerebrospinal fluid markers of Alzheimer’s disease. These subjects were found to have an increase in neuroticism and a decrease in conscientiousness over time when compared to subjects without these markers (Tautvydaite et al., 2017). Morphologically, Alzheimer’s patients with depression are shown to have greater hypoperfusion, or reduced blood flow, to the left frontal lobe of the brain in comparison to Alzheimer’s patients without depression. Overall, patients with depression and Alzheimer’s exhibit significantly more grey and white matter atrophy when compared to Alzheimer’s patients without depression (Li et al., 2014).

"Early intervention in AD has shown potential in slowing cognitive deterioration, but early-stage diagnosis of AD has proven difficult. Many early symptoms of Alzheimer’s disease are also associated with other neurodegenerative disorders, and in some cases, earlystage Alzheimer's can be challenging to distinguish from typical aging."

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Diagnostic Tools Used to Identify AD

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Some of the most useful clinical biomarkers are found in the cerebrospinal fluid (CSF) which bathes and nourishes the cells of the brain and spinal cord. Within the CSF, three biomarkers that have been found to be sensitive and specific indicators of AD are Aβ and phosphorylated tau proteins (Blennow et al., 2015). Using cerebral fluid testing, scientists find that AD alters the CSF concentration of these biomarkers. The Aβ peptide, for example, accumulates in the brain of patients with AD and creates amyloid plaques when there are failures in the drainage pathway (Weller et al., 2017). As such, a low concentration of Aβ in the CSF is indicative of AD since the protein remains in the brain instead of being drained into the CSF. This test is fairly accurate with an average specificity of 89% (Counts et al., 2017). Similarly, phosphorylated tau proteins dissociate from neuronal microtubules and are present in a much higher quantity in the CSF of patients with Alzheimer’s. This test has a mean specificity of 91% (Counts et al., 2017). Together, the concentrations of Aβ and phosphorylated tau in the CSF are a very sensitive and specific biomarker for AD (Blennow et al., 2015).

However, testing CSF involves the lumbar puncture procedure in which a hollow needle is inserted into the spinal canal to obtain a CSF sample. However, this procedure is too invasive and risky to be used for widespread diagnostic screening.

Functional imaging using fluorodeoxyglucose positron emission tomography (FDG-PET) is a less invasive than lumbar puncture and provides similar specificity in AD detection. FDG-PET

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uses radioactively tagged glucose analogue (FDG) to measure the rate of glucose uptake by specific neuron populations (Berger, 2003).

As mentioned previously, patients with AD have reduced cerebral metabolism, meaning that their brains consume less glucose than the brains of healthy individuals. Therefore, the FDG uptake should be reduced in brain areas affected by Alzheimer’s disease, which allows scientists to identify where neuronal dysfunction is occurring (Counts et al., 2017).

Overall, CSF biomarker testing and FDG-PET are some of the most specific, well defined early detection techniques available. However, there are many more methods, including retinal vascular, blood-based, and autoantibody biomarkers that may become more prevalent in the upcoming years. Compared to these other techniques, PET scans are non-invasive, accurate, and present few risks to patients.

Because of this, it is the current standard used to test people with MCI for Alzheimer’s-specific biomarkers.

Figure 11: PET scans are often used to test patients presenting Alzheimer’s symptoms. This image shows a Pittsburgh Compound-B positron emission tomography (PiB-PET) scan of a patient with Alzheimer’s disease on the left and an elderly person with normal memory on the right. Pittsburgh Compound-B (PiB) is an in vivo amyloid imaging agent (Cohen & Klunk, 2014). Areas of red and yellow show high concentrations of PiB in the brain and suggest high amounts of amyloid deposits in these areas Source: Wikimedia Commons

The Correlation Between Age and AD As previously stated, age is the greatest risk factor for AD, and scientists are attempting to understand why (Xia et al., 2018). There are two theories behind what causes aging. One group, known as the “stochastic group,” suggests that aging is associated with molecular degradation caused by the production of free radicals. The second group, known as the “non-stochastic group,” believes that the environment and genetics work together to cause cellular aging (Trevisan et al., 2019). It should be noted that aging does cause AD. While some symptoms of AD are present with normal aging, AD presents symptoms like widespread neuronal network destruction and hippocampal atrophy that differentiate AD from normal aging (Trevisan et al., 2019). Scientists have been researching how the brain changes as it ages and how it changes for AD patients. One interesting aspect of the brain is how it responds to increased activity.

Typically, greater use of an organ would lead to aging; for example, the muscles of athletes seem to be older than those of the average person. However, unlike the rest of the body, more cognitive stimulation has actually been shown to prevent AD (Trevisan et al., 2019).

Scientists are aware, however, that there is a deep link between aging and AD. Trevisan’s research team believes that “the true solution to this complex disease lies in understanding what causes aging” (Trevisan et al., 2019).

"Some of the most useful clinical biomarkers are found in the cerebrospinal fluid (CSF) which bathes and nourishes the cells of the brain and spinal cord.

Within the CSF, three biomarkers that have been found to be sensitive and specific indicators of AD are Aβ and phosphorylated tau proteins."

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Treatment "Many pharmacological treatments for AD work by increasing the levels of a neurotransmitter called acetylcholine (ACh)."

Currently, there is no cure for Alzheimer’s disease. However, a wide array of drug and nondrug treatments can slow cognitive decline and improve the quality of life for Alzheimer’s patients. Pharmacological (drug) treatments are one of the most common treatment types, though emerging technologies have shown promise in delaying disease progression through alternative mechanisms. In the following section, both pharmacological and alternative Alzheimer’s disease treatments are outlined. Due to the prevalence and variety of pharmacological treatments, discussion of drugbased treatments has been divided into two categories: (a) pharmacological treatments for memory impairment and (b) pharmacological treatment for mood and behavior. Cognitive decline and behavioral deficits are both exacerbated as the disease progresses, and many drugs function by targeting one or the other of these symptom categories. The following section will also address the growing array of non-drug treatments for Alzheimer’s disease, and the final section outlines the prospective future of Alzheimer’s disease treatment.

Pharmacological Impairment

Treatments

for

Memory

Acetylcholinesterase (AChE) inhibitors

Cover image: Artist’s impression of Planet Nine. The yellow ring around the Sun is Neptune’s orbit.

Source: Wikimedia Commons/ nagualdesign and Tomruen, CC-BY-SA 4.0

Many pharmacological treatments for AD work by increasing the levels of a neurotransmitter called acetylcholine (ACh) (Ferreira-Vieira et al., 2016). As mentioned, the cholinergic system is preferentially impacted in Alzheimer’s disease and is strongly associated with a decline in cognitive function. Therefore, researchers have focused their attention towards increasing acetylcholine levels in the nervous system by inhibiting certain catabolic enzymes, such as acetylcholinesterase and butyrylcholinesterase, which break down ACh. Inhibition of these enzymes should raise the synaptic concentration of acetylcholine, thereby improving memory and “goal-directed thought” (Sadock et al., 2005). Among the most widely administered acetylcholinesterase inhibitors (AChE inhibitors) are donepezil, galantamine, and rivastigmine.

Donepezil is the first AChE inhibitor that was available by prescription to treat AD. This inhibitor targets the central nervous system and is more selective for acetylcholinesterase than butyrylcholinesterase. Not only does this drug inhibit acetylcholinesterase, but it also

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reduces some of the physiological changes that appear during AD pathogenesis. For instance, donepezil reduces early release of inflammatory cytokines and inhibits certain parts of glutamate-induced excitotoxicity (Sharma, 2019). In terms of its efficacy, a study has found that upon administering 10 mg of the drug over the course of 24 weeks, 53.5% of cases showed significant improvement in cognitive function, while only 26.8% of the individuals on placebo illustrated improvement (McGleenon et al., 1999). However, donepezil does cause side effects such as insomnia, loss of appetite, muscle weakness, low blood pressure, and bradycardia. Furthermore, its beneficial cognitive effects only last up to 1 year in patients who have moderate to severe Alzheimer’s disease (Ferreira-Vieira et al., 2016).

Rivastigmine is another AChE inhibitor. Unlike donepezil, this drug is highly selective for both acetylcholinesterase and butyrylcholinesterase.

It can deactivate either enzyme for a period of time by mimicking the acetylcholine molecule and binding to the enzyme. It is therefore considered to be a pseudo-irreversible inhibitor of the central nervous system (McGleenon et al., 1999). The drug has demonstrated moderately good efficacy, with 24% of patients on a high dosage of rivastigmine (10.4 mg per day) showing significant improvement in AD symptoms (McGleenon et al., 1999).

Unfortunately, a severe set of side effects— among them vomiting, weight loss, difficulty breathing, chest pain, and irregular heartbeat— limits large-scale rivastigmine prescription.

A third AChE inhibitor is galantamine. This drug not only serves as a reversible inhibitor to acetylcholinesterase, but also increases acetylcholine activity in the central nervous system by binding to nicotinic cholinergic receptors. Galantamine can result in cognitive improvements in patients who suffer from mild to moderately severe Alzheimer’s disease. Like the other AChE inhibitors, side effects of the drug include nausea, stomach cramps, irregular breathing, and confusion (Razay & Wilcock, 2008).

Glutamate antagonists and AChE-glutamate combination drugs In addition to AChE inhibitors, a class of drugs known as glutamate antagonists are widely prescribed to patients with Alzheimer’s disease.

In general, antagonists bind to a receptor site in place of the intended signaling molecule,

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Figure 13: The third column offers a visual representation of the mechanism through which antagonist drugs, like memantine, block cellular activity. In the case of memantine, the drug protects NMDA receptors from excessive glutamate signaling Dolleyj, 2014; Wikimedia Commons

thereby modulating neural transmission (Figure 13). In moderate to severe cases of AD, the drug memantine has been prescribed as an antagonist for glutamate receptors. By inhibiting ionotropic N-methyl-D-aspartate receptors (NMDARs), memantine protects cell structures such as the cytoskeleton, membrane, and DNA from the effects of high ion concentrations within the cell (Loveman et al., 2006). While glutamate is critical to proper learning and memory, pathological changes in AD can result in harmful glutamate accumulation (van Marum, 2009). Memantine blocks the activation of NMDA receptors via an open-channel blockade in which its agonists remain partially trapped in the ligand-gated calcium ion channels of glutamate receptors (Jaris et al., 2003). Memantine treatments in past studies suggest statistically significant improvement in AD symptoms, with patients receiving treatment scoring nearly 30% higher on the Clinical Global Impression of Change (CGI-C) scale than those who did not.

In another study, AD patients needed 51.5 hours less of caregiver attention per month while taking memantine than those administered a placebo. However, the cost-effectiveness of memantine remains controversial. The NICE Committee of the UK concluded that memantine could not be ruled as a cost-effective therapy for moderately severe to severe AD because the clinical effects on cognition, global functioning, and daily activities were too limited. Furthermore, adverse effects (though

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mild to moderate) include dizziness, headache, constipation, somnolence, and hypertension (van Marum, 2009). Due to the inconclusive cost-effectiveness of memantine and limited clinical results, patients with moderate to severe AD are advised to first consider cholinesterase treatments before pursuing memantine therapy.

Namzaric is a marketed combination treatment of both AChE inhibitors and NMDA receptor antagonists. It is used to treat patients with moderate to severe dementia caused by AD who are already stable on memantine and donepezil treatments. In a randomized, controlled 24-week study, the mixed combination of AChE inhibitor and NMDA antagonist showed significant improvement in memory and cognitive function as compared to the sole administration of an NMDA antagonist.

The combination treatment, comprising 20 mg memantine and 10 mg donepezil, was effective for patients with dementia due to moderate to severe AD in the short term. However, the treatment did not show significant improvements in a longer 52-week study (Elliott, 2015). More research has to be done to prove the efficacy of Namzaric as a long-term treatment for patients with AD.

"Memantine treatments in past studies suggest statistically significant improvement in AD symptoms, with patients receiving treatment scoring nearly 30% higher on the Clinical Global Impression of Change (CGI-C) scale than those who did not."

Anti-amyloid and tau-targeting drugs Despite some advances in treatment for Alzheimerâ&#x20AC;&#x2122;s disease, extensive scientific research is still needed in clinical trials to

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identify safe and effective treatments to ameliorate symptoms and slow disease progression. Currently, over 121 compounds are being examined in clinical trials, the majority of which involve anti-amyloid therapy (Cummings et al., 2020). One particularly promising antiamyloid agent is aducanumab: a monoclonal antibody that targets Aβ aggregates (Huang et al., 2020). Several studies have demonstrated the antibody’s ability to significantly reduce the accumulation of Aβ in multiple regions of the brain. An early trial revealed that aducanumab reduced Aβ aggregates in a “dose- and timedependent manner” (Sevigny et al., 2016).

Although some measurements suggested an improvement in cognitive abilities after a year of treatment, most of the results analyzing its impact on cognitive capabilities were still unclear (Sevigny et al., 2016). In 2019, aducanumab’s potential to slow cognitive decline was reexamined in Biogen’s phase 3 EMERGE trials.

A post-trial data reanalysis determined that several patients (particularly those receiving a high dose) exhibited a “significant reduction” in the decline of cognitive capabilities compared to baseline readings (Huang et al., 2020). Due to these encouraging findings, the antibody was granted priority review by the FDA in August 2020.

"Antipsychotics are some of the most popular medications used to treat behavioral symptoms in Alzheimer’s disease, mostly agitation and aggressiveness."

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In recent years, anti-amyloid methods have been joined by explorations of treatments that target non-amyloid pathways (Huang et al., 2020; Cummings et al., 2020). Several tau inhibitors have undergone trials whose results are still inconclusive. For instance, TRx0237, which is currently in a Phase 3 trial through December 2020, reduces aggregated tau levels to diminish neuronal damage caused by the protein. AADvac1 also inhibits tau aggregation by stimulating an immune response that targets tau’s epitopes (Huang et al., 2020). The effects of these agents are still to be determined. Clinical trials have also studied cognitive enhancers to mitigate AD’s progression. These compounds, including intepirdine and EVP-6124, increase release of multiple neurotransmitters – particularly acetylcholine, glutamate, and dopamine – to improve neuronal communication. Several trials involving cognitive enhancers, including intepirdine and EVP-6124, have been terminated due to inconclusive results or adverse health effects (Huang et al., 2020). The lack of success in clinical trials in identifying suitable candidates to mitigate memory impairment indicates the necessity for further research on potential treatments.

Pharmacological Treatments for Behavior and Mood In addition to treatments seeking to ameliorate memory impairment, other treatments have emerged to control behavioral and physiological symptoms (BPSD) caused by AD. These symptoms are a group of behavior, mood, perception, or thought disturbances that manifest with anxiety, agitation, delusions, and hallucination (Abraha et al., 2017).

Antipsychotic and mood-stabilizing drugs are among the most common pharmacological treatments for severe behavioral and psychological symptoms of Alzheimer’s disease. For milder cases, benzodiazepines can help regulate sleep schedules and reduce anxiety, while antidepressants can improve quality of life for AD patients by aiding in mood regulation.

Antipsychotics and mood stabilizers Antipsychotics are some of the most popular medications used to treat behavioral symptoms in Alzheimer’s disease, mostly agitation and aggressiveness (Schneider et al., 1990).

Antipsychotics are divided into two types: typical and atypical. Typical antipsychotics are high affinity antagonists of the dopamine D2 receptor, while atypical antipsychotics may interact with other receptors besides D2 including the 5-hydroxytryptamine-A (5-HT2A) receptor (Ballard & Howard, 2006). There is a growing interest in atypical antipsychotics such as risperidone and olanzapine over typical treatments like chlorpromazine and levomepromazine for the treatment of behavioral changes in AD. The shift can be attributed to the discovery of adverse side effects (movement disorders, in particular) associated with dopamine blockade (da Silva et al., 2011).

One study that shows promise for atypical solutions is the CATIE-AD clinical study, which included older individuals with Alzheimer’s and neuropsychiatric symptoms randomized into groups receiving olanzapine, quetiapine, risperidone, or a placebo. The first endpoint was time until discontinuation of the medicine, the second was improvement on the Clinical Global Impression of Change scale, and the third was time until discontinuation due to ineffectiveness. The results demonstrated that olanzapine and risperidone were significantly more effective than quetiapine and placebo (Schneider et al., 2006). A second publication

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AD. More research may eventually establish mood stabilizers as a reliable treatment for behavioral and psychological symptoms in patients with AD.

Benzodiazepines

interpreted the data from Phase 2 and evaluated multiple parameters at varying weeks. These results reaffirmed the earlier study, showing a benefit from olanzapine and risperidone in neuropsychiatric inventory and the brief psychiatric rating scale for hostile distrust (Sultzer et al., 2008). Such findings indicate that olanzapine and risperidone have the potential to reduce aggression and psychosis, respectively. Despite the treatments’ apparent efficacy, numerous reports of adverse side effects drive the general consensus among physicians that antipsychotics should only be used if people around the patient find themselves at severe risk due to the patient’s aggressiveness or agitation (Ballard et al., 2006).

Though antipsychotics have emerged as a primary treatment for severe behavioral and psychological symptoms of AD, mood stabilizing drugs like lithium are also often prescribed—both in place of and in tandem with—these antipsychotic drugs for the treatment of severe behavioral and psychological AD symptoms (Devanand et al., 2017). Recently, a nonclinical six-person study showed that lithium, when used in conjunction with antipsychotics, improved symptoms associated with BPSD. While lithium shows promise, further study of lithium as an independent mood stabilizer is needed, as other studies have proved less promising. The ANCP White Paper found that the mood stabilizers valproic acid and carbamazepine failed to show any improvement in the BPSD of AD patients.

Since the publication of that ANCP White Paper in 2007, there have been only three randomized clinical trials studying mood stabilizers as a treatment for BPSD (Rayfield et al., 2014). These additional studies of valproic acid, Topiramate, and Oxcarbazepine suggested that they were all ineffective treatments for agitation and aggression in patients with moderate to severe

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Two common symptoms of Alzheimer’s disease are sleeplessness and anxiety, both of which can be treated by benzodiazepines.

This class of drugs functions by blocking neural transmission to GABAA receptors, which normally send inhibitory signals to surrounding neurons. Some of these surrounding neurons are known as dopaminergic neurons, and the neurochemicals that they release can help reduce anxiety. When benzodiazepines limit inhibitory GABA signals, dopaminergic neurons experience less inhibition (Sigel & Ernst, 2003). This chain of events leads to increased dopamine release, which then contributes to a strong anxiety-reducing effect (Wise et al., 1972). For Alzheimer’s patients, benzodiazepines are often prescribed in the early stages of the disease when anxiety about declining cognition can peak (Porter et al., 2003). However, the treatment is also prevalently prescribed to mid- and late-stage patients as a means of managing eccentric behaviors and normalizing sleep schedules (Johansson et al., 2010).

In recent years, some concern has emerged regarding a possible link between the onset of Alzheimer’s disease and benzodiazepine use (Billioti et al., 2014; Gallacher et al., 2012). While some research suggests that Alzheimer’s disease patients who are prescribed benzodiazepines may experience higher mortality rates than the average AD patient, multiple case-control studies reject this claim (Bierman et al., 2007; Imfeld et al., 2015). A recently published cohort study, controlling for factors like alcohol and substance use, psychiatric drug prescription, and sociodemographics, concluded that their work revealed no association between the use of benzodiazepines and subsequent dementia (Olser & Jorgensen, 2020). Still, as research progresses, official recommendations from the Clinical Manual of Geriatric Psychiatry urge low-dosage benzodiazepine prescriptions for as brief a period of time as possible in AD patients (Jacobson, 2014).

Figure 14: Benzodiazepines bind to the GABAA receptor and exert an allosteric effect on receptor channels, which enables increased GABA transmission.

The GABA neurotransmitter is inhibitory, and its increased influx results in strong anxietyreducing effects upon further neural propagation Source: adapted from Hiis, 2020

"Two common symptoms of Alzheimer’s disease are sleeplessness and anxiety, both of which can be treated by benzodiazepines.

This class of drugs functions by blocking neural transmission to GABAA receptors, which normally send inhibitory signals to surrounding neurons."

Antidepressants Like benzodiazepines, antidepressants are a class of common behavior-regulating drugs

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Figure 15: The scheme shows the general mechanism of serotonin selective reuptake inhibitors (SSRIs), a common type of antidepressant. The SSRI prevents reuptake of serotonin upon its release into the synaptic gap, thereby enhancing its signaling capacity Source: Store Medisinske Leksikon

"Drugs that fall into the selective serotonin reuptake inhibitor (SSRI) class are among the most commonly prescribed antidepressants for AD patients.

Examples of these drugs include fluoxetine, citalopram, paroxetine, sertraline, and fluvoxamine."

that have successfully mitigated some adverse behavioral and psychological symptoms of Alzheimer’s disease (Thompson et al., 2007).

In general, many antidepressants function by inhibiting the reabsorption of certain neurotransmitters into the nerve cell from which they came. Inhibition of this reuptake process can lengthen the duration of interactions between signaling molecules and their targets, often enhancing the positive effects of this signaling process on mood or behavior (Figure 15). More specifically, antidepressants tend to fall into one of four classes: non-selective monoamine reuptake inhibitors (NSRIs), selective norepinephrine reuptake inhibitors (SNRIs), selective serotonin reuptake inhibitor (SSRIs), and monoamine oxidase inhibitors (MAOIs)—all having varying influences on patient sentiment and AD levels (Tardito et al., 2016).

Firstly, looking at one of the older antidepressant classes, the non-selective monoamine reuptake inhibitor (NSRI) group includes the tricyclic antidepressants (TCAs), a set of antidepressants introduced in the 1950s that inhibit the reuptake of both serotonin and noradrenaline. Examples of this class are clomipramine, desipramine, amitriptyline and imipramine. With the presence of dual inhibitors, some reports suggest that TCAs may have superior efficacy and earlier response than selective reuptake inhibitors (SNRIs and SSRIs) for a single monoamine (Aboukhatwa et al., 2010). However, despite the therapeutic effects of TCAs, its antihistaminic, cardiotoxic and anticholinergic side effects have caused TCA prescriptions to be less favored. Suffering from

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similar side-effect-related drawbacks are drugs like maprotiline and reboxetine, which represent another common class of antidepressants: selective norepinephrine reuptake inhibitors (SNRIs). This class of antidepressants selectively inhibits the reuptake of norepinephrine. While maprotiline causes side effects similar to those of TCAs, including dry mouth, fatigue, and weight gain, reboxetine’s primary side effects involve the cardiovascular and urinary systems. Both SNRIs and NSRIs show promise in improving mood, though their associated side effects tend to make prescription of these drugs less common than prescription of SSRIs, which are subsequently discussed (Aboukhatwa et al., 2010).

Drugs that fall into the selective serotonin reuptake inhibitor (SSRI) class are among the most commonly prescribed antidepressants for AD patients. Examples of these drugs include fluoxetine, citalopram, paroxetine, sertraline, and fluvoxamine. Introduced in the 1980s, one of the most significant advantages of SSRIs is their tolerability; one of the few commonly reported side effects is mild sexual dysfunction (Balon et al., 2006). Lastly, the drug tranylcypromine is an example of a monoamine oxidase inhibitor (MAOI). This class of antidepressants inhibits monoamine oxidase (MAO), the enzyme responsible for the metabolism of monoamines. The presence of MAO-A inhibitors within the drug helps metabolize the amines that play a large role in depression etiology. Due to dangerous dietary and drug interactions, the use of

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alternative treatment has gotten recently, there are still many unanswered questions in regard to stimulation parameters such as frequency, intensity, localization, and length (Marron et al., 2018).

MAOIs is generally reserved as a last resort for those AD patients who do not respond well to other antidepressants or suffer from atypical depression (Aboukhatwa et al., 2010). While much remains to be discovered about the intentional and definitive links between the use of antidepressants and AD, researchers are hopeful that the use of antidepressants can positively impact AD patients.

Alternative Treatments One of the most thoroughly investigated nondrug treatments for Alzheimer’s disease is an electrical-stimulation process known as deep brain stimulation (DBS). Typically, DBS is used for treating disorders such as Parkinson’s and dystonia, both of which are characterized by uncontrollable muscle contractions. Recently, the low complication rate and non-invasive nature of DBS have driven researchers to investigate DBS as a potential treatment for Alzheimer’s disease (Yu et al., 2019). Hamani and colleagues, for example, recently observed improved memory for a patient being treated for obesity with DBS. This patient was stimulated in the anterior portion of the fornix near the hypothalamus. Their research spurred a study where continuous stimulation of this target area for one year led to increased glucose metabolism for AD patients with no significant clinical or behavioral effects (Fried, 2016).

Further studies have mimicked this increased glucose metabolism as well as increased neurotransmitter release and neurogenesis.

These findings suggest a direct effect of DBS at the neurocircuitry level. Network level effects of DBS on AD patients show additional promising results. If researchers are able to find target areas for DBS that save neurons from the entorhinal cortex and the hippocampus, it may in fact slow the progression of AD (Yu et al., 2019). Despite the recent attention this FALL 2020

Another promising non-drug treatment for Alzheimer’s disease is stem cell therapy. Unlike many drug-based treatments, stem cell therapy has the potential to go beyond symptomquenching to directly alter the pathogenesis of AD. While stem cell therapies have thus far been primarily tested through in vitro experimentation and animal models, these studies have shown promising results (Tang, 2012). Three types of stem cells, embryonic stem cells (ESCs), mesenchymal stem cells (MSCs) and neural stem cells (NSCs), have been used to successfully generate neurons and glial cells. In theory, these stem-cell-generated neurons and glial cells would harbor protective characteristics against the cascade of harmful neural events that characterize Alzheimer’s disease. Most stem cell therapies have two possible goals: either to induce the activation of endogenous stem cells or to regenerate damaged tissues through transplantation (Choi et al., 2014). For the treatment of neurodegenerative diseases like Alzheimer’s, researchers tend to focus on the latter (regeneration of damaged tissues).

Sung Choi and colleagues examined the potential for stem cells to treat Alzheimer’s disease using in vitro models and discovered that stem cells can contribute significantly to functional recovery from AD. Transplantations of human and mouse derived MSCs have reduced Aβ plaque deposits, improved memory, and alleviated AD pathology. More specifically, stem cells have been shown to increase acetylcholine levels, decrease proinflammatory factors, and increase the expression of neprilysin, an enzyme that degrades Aβ (Choi et al., 2014). Furthermore, transplantation of NSCs in animal models of neurodegenerative diseases has led to clinical improvement and life extension of those animals (Kim et al., 2013). However, further investigation and advancement are required to develop stem cell therapy for neurodegenerative diseases to the point of clinical implementation (Tang, 2012).

Figure 16. An X-ray image of the electrodes that facilitate deep brain stimulation—in this case, for Parkinson’s disease (Hacking & Gaillard, 2013). The use of DBS for Alzheimer’s disease treatment remains nascent, but a recent study replaced the electrodes pictured above with small electrical stimulation devices implanted between the hippocampus and hypothalamus of AD patients. The devices delivered continuous stimulation at 130 Hz between 3 and 3.5 V, and though the study will require replication, the DBS devices appeared to effectively slow cognitive decline in latestage AD patients Source: Wikimedia Commons

"Recently, the low complication rate and non-invasive nature of DBS have driven researchers to investigate DBS as a potential treatment for Alzheimer’s disease."

As a final example of non-pharmacological treatments for Alzheimer’s disease, a signalemitting silicon implant has shown promise in alleviating Alzheimer’s-related cognitive impairment. Dr. Thomas Berger’s “Berger Chip” mimics neuron function by communicating directly with living brain tissue (Solis, 2017).

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"Extensive research is being conducted on disease-modifying drugs that aim to decrease betaamyloid in the brain through inhibiting β- or γ-secretase activity as well as active or passive immunization."

The Berger Chip is a silicon chip that relies on a complex algorithm developed by Dr. Dong Song called the multi-input multi-output (MIMO) prediction model (Cutsuridis, 2019). MIMO aims to embody all hippocampal computations by performing the same tasks as a healthy hippocampus. The algorithm allows the Berger Chip to translate messages passed between the CA3 and CA1 regions of the hippocampus by delivering electrical signals (Hampson et al., 2018). Rats with lesions in the CA3-CA1 connection area had less than a 50% success rate in a specific memory task, which increased to over 90% with the chip implant (Cutsuridis, 2019).

The Berger Chip does suffer from limitations— namely its non-adaptive model, which means that the chip cannot learn and improve through experience the way that a healthy brain would (Cutsuridis, 2019). The chip also addresses a symptom of disease (cognitive impairment) without targeting its underlying cause, which means that this electronic treatment method might be best suited for use in-tandem with other treatments and cannot be regarded as a pathway towards a cure. However, preliminary clinical testing suggests that the chip could help delay or temporarily alleviate cognitive decline in Alzheimer’s disease patients.

The Future of AD Treatment

Cover image: Artist’s impression of Planet Nine. The yellow ring around the Sun is Neptune’s orbit.

Source: Wikimedia Commons/ nagualdesign and Tomruen, CC-BY-SA 4.0

One of the most important takeaways from research is that Alzheimer’s is often driven by a multitude of genetic and environmental causes that can develop over the course of one’s life.

Scientists expect future therapies to have a more targeted approach in the subcategory of patients it is designed to benefit, because one drug cannot be generalized to all patients who experience different sets of underlying causes.

Current approaches to treating Alzheimer’s such as acetylcholinesterase inhibitors offer symptomatic improvement in the short-term through counterbalancing neurotransmitter disturbance, but do not stop or alter the progression of the disease (Yiannopoulou & Papageorgiu, 2013). There has been a recent focus on developing drugs that target amyloid beta, tau, and inflammation, factors that cause late-onset Alzheimer’s disease.

Extensive research is being conducted on disease-modifying drugs that aim to decrease beta-amyloid in the brain through inhibiting βor γ-secretase activity as well as active or passive immunization. Beta and gamma secretase are enzymes that cleave the amyloid precursor protein into Aβ. By developing treatments that

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target every point of the amyloid processing pathway, including inhibiting β- or γ-secretase, the Aβ plaque buildup that is a hallmark of AD can be prevented or slowed (Venugopal et al., 2010).

Another target is the tau protein which is involved in maintaining neuron structure, but collapses and twists in AD, destroying nutrientdelivering microtubules as well as the neurons.

AADvac1 is a vaccine in development that elicits the immune system to respond against modified forms of the tau protein. Clinical trial results showed a change in biomarkers for AD and positive cognitive endpoint changes, implying the treatment may slow AD progression. This treatment approach will advance to new stages of clinical trials (Novak et al., 2019).

Inflammation is a central mechanism of AD, caused by Aβ plaques and tau tangles, which spurs microglia cells to serve as immune defense. However, the overactivity of microglia can lead to the creation of compounds that damage surrounding cells. The drug sargramostim, for example, shows potential in protecting neurons located in the brain from toxic proteins (Potter et al., 2020). There are several drugs that target amyloid beta, tau, and inflammation undergoing clinical trials, but no drugs or disease-altering nature have been approved for use by the FDA yet.

Conclusion With a growing elderly population, there will likely be a compensatory increase in AD cases in the future. A recent study using the R statistical coding language and linear regression techniques sought to determine if there were significant differences in age of Alzheimer’s symptom onset. Using data from the Dominantly Inherited Alzheimer Network (DIAN) database and comparing mutations in amyloid precursor protein, presenilin 1, and presenilin 2, the study found the different mutations resulted in significantly different ages of AD onset. This finding is instrumental in the increased control that it offers patients; now, screening for Alzheimer’s mutations can help physicians determine when to begin preventative care by considering the average age of onset for a certain mutations. DIAN recommends treatment to begin 15 years before the predicted onset of the disease (Ryan et al., 2014). The researchers note that “given these findings, the potential predictability of

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symptom onset in AD can provide powerful advantages for prevention trials in presymptomatic [AD]” (Ryan et al., 2014). Although there remained some variation in age of onset for individuals with similar genomic profiles, screening for Alzheimer’s mutations could help physicians give earlier AD diagnoses.

There are also mechanisms built-in to the biology of the neuron which many also help prevent neurodegeneration in Alzheimer’s disease. An individual’s rate of homeostatic synaptic plasticity, the rate at which cells repair degeneration and other perturbations, may determine the severity of neuronal degeneration and symptoms. The theory of presynaptic homeostatic plasticity (PHP) claims that when neurons begin to degenerate, they modify aspects of their synaptic junctions such as neurotransmitter release or the amplitude of excitatory presynaptic potentials in order to maintain equilibrium. The search for regulatory pathways and inter-synaptic signaling molecules of PHP and other plasticity mechanisms has begun. It was found that in mice genetically engineered to have increased neuronal degradation, blockage of the ENaC sodium channels in the neuromuscular junction with the drug Benzamil blocked PHP (Davis, 2020). In other words, once degeneration has begun (in this case due to genetic manipulations), ENaC channels are needed for compensatory mechanisms in counteracting this degeneration. More specifically, the study found that the ENaC Scnn 1a subunit factored into PHP as Scnn1a knockout mice failed to initiate PHP. Variations in the strength of PHP among individuals may allow some individuals to exhibit better resistance to AD and understanding these mechanisms may lead to possible preventative treatments in the future.

Regardless of the age of symptom onset, Alzheimer’s is a devastating disease that impedes cognition and memory. The five drugs currently approved by the FDA are able to treat symptoms but cannot halt the progression of the disease, leaving patients with very little agency within the last phases of their life. Therefore, a significant portion of Alzheimer’s research today is dedicated to its possible prevention to ward off the disease from manifesting.

The two types of Alzheimer’s (late-onset and early-onset) have slightly different causes and thus are treated independently. LOAD accounts for 95% of AD cases, and there are more options

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for treatment (Mendiola-Precoma et al., 2016).

However, there are certain genetic factors that may increase an individual’s risk. Certain studies have found that as many as one-third of patients with AD may display modifiable risk factors (Livingston et al., 2017). These sorts of non-inherited risk factors include high cholesterol, hyperhomocysteinemia (high homocysteine, which may be linked to vitamin B12, folate, and pyridoxine deficiencies), hypertension, obesity, type II diabetes, and the composition of the gastrointestinal microbiota.

Therefore, prevention for patients with an increased risk for LOAD often includes lifestyle strategies such as an increase in physical activity, diet, decreased alcohol consumption, vitamin supplements, and mental stimulation (Mendiola-Precoma et al., 2016).

The implementation of this kind of preventative treatment can be aided by personalized medicine. A one-size-fits-all approach is not adequate because it neglects the patient’s history and unique profile. For example, for a woman working in an academically stimulating job with low physical activity and no risk of high cholesterol, obesity, or hypertension, increased mental stimulation or diet changes may not be effective, even though they might be beneficial for a majority of the U.S. population (Isaacson et al., 2018). Clinical precision medicine works to use a complete history of the patient coupled with bioinformatics and public genetic databases to understand, predict, and work with each individual patient’s circumstance.

While such strategies may improve quality of life and symptoms for patients with LOAD, little can be done to stop the disease once symptoms start to appear. However, a growing body of research still suggests that measures to ward off progression confers a greater quality of life for the patient by delaying the onset of Alzheimer’s by a few years (Crous-Bou et al., 2017).

The history of Alzheimer’s disease research has been filled with “eureka” moments that have come to no avail in the context of curing the disease. Since the discoveries of amyloid beta and tau, a significant amount has been learned about the complicated neurobiology of Alzheimer’s disease, yet a causal link between specific molecules and disease has not been found. It is likely that the molecular pathology of Alzheimer’s disease may be pleiotropic (depending on many genes), and the drugs needed to treat the disease may therefore need to be personalized to the individual (Frautschy

"Regardless of the age of symptom onset, Alzheimer’s is a devastating disease that impedes cognition and memory. The five drugs currently approved by the FDA are able to treat symptoms but cannot halt the progression of the disease, leaving patients with very little agency within the last phases of their life."

Cover image: Artist’s impression of Planet Nine. The yellow ring around the Sun is Neptune’s orbit.

Source: Wikimedia Commons/ nagualdesign and Tomruen, CC-BY-SA 4.0

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& Cole, 2010). Nevertheless, progress is being made in improving diagnostic and therapeutic interventions for AD; continuing to develop these interventions is not only important, but obligatory in saving the healthcare system, global economy, and countless lives.

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