PennScience Spring 2019 Issue: Robotics

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Bio-Inspired Robots: Relieving the Burden of Climate Change page 20

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robotic warfare: dissecting the autonomization of world combat 04 page 23

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robotic telescopes and astronomy: interview with dr. cullen blake page 29

robotics


PENN SCIENCE spring 19 vol 17 issue 2

PennScience is a peer-reviewed journal of undergraduate research and related content published by the Science and Technology Wing at The University of Pennsylvania and advised by a board of faculty members. PennScience presents relevant science features, interviews, and research articles from many disciplines, including the biological sciences, chemistry, physics, mathematics, geological science, and computer science. PennScience is funded by the Student Activities Council. For additional information about the journal including submission guidelines, visit www.pennscience.org or email pennscience@gmail.com.

EDITORIAL STAFF

/DIR_20.3: Jenny (JiCi) Wang

writing managers

editing managers

design managers

Hiab Teshome

Brian Zhong

Farhaanah Mohideen

Roshni Kailar

faculty advisors

Kenny Hoang

editors in chief

Brian Song

tech manager

Roshan Benefo

Rounak Gokhale

business managers

Helen Jiang

Rachel Levinson Catherine Ruan

Dr. Jorge Santiago-Aviles Dr. M. Krimo Bokreta

student advisors

Mia Fatuzzo Donna Yoo

T9_RadarSweep

writing

editing

design

business

Tamsyn Brann Roshni Kailar Rosie Nagele Emily Lo Andrew Lowrence Neelu Paleti Michelle Paolicelli Celia Zhang

Elly Choi Abraham Frey Billy Hasley Kelly Liang Mimi Lu Emma O'Neil Dan Rodriguez Sumant Shringari Kathy Wang

Olivia Myer Amara Okafor Lindsay Smith Hannah Wang Felicity Qin Winnie Xu

Alex Massaro Glen Kahan Cal Rothkrug Aaron Zhang

SYS_22.47:ACtive


TABLE OF CONTENTS Calibration

collision_avoidance: active

Andrew Lowrance

6 Emily Lo

16 Neelu Paleti

14

Automobile intelligence

T9 03

Nanobots in medicine: small devices making big strides

S2 01

Deep Learning AI: A New Eye for Medical Diagnostics

lidar Michelle Paolicelli

17

D1

The Sense of Touch: Now a Teachable Skill

radar

SYS:\_energy_Storage Mode_S: Low convective heat loss

Rosie Nagele

20 Pranshu Suri

23

Bio-Inspired Robots: Relieving the Burden of Climate Change Robotic Warfare: Dissecting the Autonomization of World Combat

SYS:\_Seaglider/divedata

Celia Zhang

26

Seagliders to The Rescue

Tamsyn Brann

29 james nassur

33 Fiona O'Neill

38

Interview with Dr. Cullen Blake

THBS2 as a candidate modifier of liver disease severity in alagille syndrome Establishing a laboratory infection model for Dirofilaria Immitis in the vector mosquito Aedes Albopictus


Dear readers, On behalf of the entire PennScience team, we are pleased to present the spring issue of the seventeenth volume of the PennScience Journal of Undergraduate Research. For many years, this journal has been a medium for the deep exploration into a particular fields of science, technology, and engineering, along with incredible original research. This semester, we decided to explore the grappling field of Robotics, with critical applications ranging from improving our daily lives to exploring the yet to be explored. In this issue, Andrew Lowrance examines the advancements in automobile intelligence and how tomorrow’s vehicle will be miles ahead of today’s in terms of safety and efficiency. Emily Lo looks into how nanorobots could hold the key to a cure for many of the world’s illnesses. Neelu Paleti examines the growing interplay of artificial intelligence and medical diagnostics. Michelle Paolicelli discusses how myoelectric prosthetics are returning the sense of touch to amputees. Rosie Nagele investigates bio-inspired robots and how they are helping to combat climate change. Pranshu Suri reviews military robotics and their growing usage on the frontiers of battlefields. Celia Zhang explores underwater robots and their role in exploring the depths of the ocean and study of crumbling Antarctic ice shelves. Finally, Tamsyn Brann sits down with Dr. Cullen Blake, an observational astronomer at the University of Pennsylvania, for a discussion on his current research involving robotic telescopes. We received a number of truly excellent original research submissions and are proud to present the work of two students - Fiona O’Neill and James Nassur, both students here at the University at the Pennsylvania. Over the past semester it has truly been an honor to lead such a passionate group of students and we would like to extend a sincere thank you to the many groups and individuals who have made PennScience possible. First, we would like to thank our incredible journal staff -- the members of our writing, edigin, design, and business committees -- for their hard work, dedication, and infectious enthusiasm. PennScience is entirely student-run and relies on the efforts of our scientifically curious undergraduate members. We would also like to acknowledge the Science and Technology Wing of the King’s Court College House and the Student Activities Council for their generous funding. A huge thank you goes to our faculty mentors, Krimo Bokreta and Jorge Santiago-Aviles for their constant guidance and support. Lastly, we would like to thank you, the reader, for your continued support of PennScience and curiosity for science. We hope you enjoy the journal. Sincerely, Kenny Hoang (ENG’21) and Jenny (JiCi) Wang (C’19) Co-Editors-in-Chief


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Features

WRITTEN BY ANDREW LOWRANCE

EDITED BY KATHY WANG AND ELLY CHOI DESIGNED BY FARHAANAH MOHIDEEN

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Features ith the advent of technology and a new status quo of increasing user engagement, there seems to be greater emphasis placed on the ideals of mechanical advancement and societal efficacy. That is, to turn one’s head to the rapidly-proliferating wave of artificial intelligence is but a nod to today’s integrated world. Likewise, our lives are maintained by various forms of machinery that have already been well-established, one of which is notably the automobile. Technologies like these have allowed for new frontiers to be established in the realm of transportation safety and efficiency. For a more historical outlook on the trends in the automobile industry since the earlyto-mid twentieth century, one must look to the

series of developments that have allowed for the progression of faster, safer, and more practical travel from what was an era of dangerous roads. Such a process was initiated with the internal combustion engine, functioning as any new and improved twentieth-century engineering makeup would – quite terribly. In fact, injury and death rates rocketed from not only the vehicle’s sole engineering specs, but also its poor usage by any lively soul who possessed a considerable amount of money and adventurism. Of course, such possibilities are no longer a concern but rather a lesson to be learned, for now we see the potential for safer travel through technological advancement.

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Now, it seems as though the tides have shifted yet again. That is, with focus being driven toward fuel efficiency and customizable features, the possibility of self-driving and electric vehicles has now become a reality. Technological innovations in seat belt security, external detections for path delineation, and integrated systems of vehicle health maintenance have all led towards an increasing focus on intelligent, computerized machines. More particularly, in recent years, studies have been conducted to explore the relationship between seat belt installation, airbag deployment, and quantified safety approximations in motorized accidents. Statistician Dr. Paul L. Zador and Michael Ciccone looked toward possible differentiation in the types of collisions brought on by two vehicles.1 Head-on collisions typically deploy an airbag with little possibility of malfunction. However, an airbag can deploy in the event that no damage is sustained by a vehicle, as with side collisions. This occurs when the integrated computer system within 8

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the vehicle miscalculates the degree to which the impact is effective, interpreting it as one crossing the deployment threshold. For a more accurate interpretation of collisions, sensors are redistributed about the vehicle’s body to account for full environmental detection. In a sense, one can conceptualize this sensory redistribution as an increased window of perception for the vehicle, which in effect increases the period by which the vehicle is capable of responding to an incident. Following detection, an electronic signal is sent to the aperture responsible for detonating an ignitor powder, which in turn activates the airbag. Within this aperture, there is a module that incorporates a diffuser made from sheet metal stamping. The sheet metal cushioning is responsible for maintaining adequate separation within the module. This separation is what determines the force with which the airbag is deployed. In particular, the concept behind the advanced airbag system came with dual-stage airbags, which detect the necessity of deployment prior to impact and are capable of controlling the amount of force utilized by an airbag through modulating the sheet separation within the aperture.2 Ultimately, these advanced methods of collision safety all contribute to the development of technological innovation in the automobile industry, as it is related to maximizing user comfort.3 Likewise, in the realm of user engagement, path-tracking has been a feature utilized by car manufacturers to aid in the maintenance of vehicle course evaluation. Software is now utilizing path tracking, kinematic, and geometric vehicle modeling to outline the approximate course in which a vehicle is taking to ensure stability maintenance in the event of user malfunction.4 An example of how a tracking model may work is the utilization of a probability distribution function to statistically outline the next destination of a given object. This is incorporated in the current plans to integrate artificial intelligence into computer systems to make driverless transportation a possi-


bility on the road. Such a feature works in conjunction with the safety parameters established with seat belt and airbag innovation, where the direction of the automobile industry continues to be toward user engagement. Alas, when considering one’s engagement with a vehicle, the question of security and optimal functionality with the user comes into play. Luckily, Hyundai has answered this question for us. At the Consumer Electronics Show in Las Vegas, the automobile giant announced a smart mobilities chair that transports one from the vehicle to the home while also controlling different appliances within the vehicle, such as security, video, lighting, and even atmospheric fragrance regulation.5 Of course, with all these new developments in user engagement, one must also consider the heavy reliance on AI development, security, and interoperability among Internet of Things (IoT) networks, which are systems of interrelated computers utilized by car manufacturers for data analytics. Because of this, vehicle companies are working with the IT industry to produce advanced driver assistance systems (ADAS) and next-gen mobility experiences to ensure protocols in such areas are met. With these developments, it seems inevitable that we are headed towards a more user-friendly world without manual localized transportation. This shift towards increased system intelligence and optimization will continue to pave the way for a world of safety assurance through technological reliability, a world where the uncertainty of a motor vehicle will perhaps be a thing of the past.

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Technological innovations in seat belt security, external detections for path delineation, and integrated systems of vehicle health maintenance have all led towards an increasing focus on intelligent, computerized machines.

1. Zador, P. L., and Ciccone, M. A. (1993). Automobile driver fatalities in frontal impacts: air bags compared with manual belts. American Journal of Public Health 83, 661-666. 2. Malczyk, A., Franke, D., and Adomeit, H.(1998). A study on the benefits of dual-stage inflators linder out-of-position conditions. International Research Council on Biomechanics of Injury. http://www.ircobi.org/wordpress/downloads/ irc1998/pdf_files/1998_33.pdf 3. Segovia-Vargas, M., Camacho-Miñano, M., and Pascual-Ezama, D. (2015). Risk factor selection in automobile insurance policies: a way to improve the bottom line of insurance companies. Revista Brasileira de Gestão de Negócios 17, 1228-1245. 4. Gerdes, A. (2006). Automatic maneuver recognition in the automobile: the fusion of uncertain sensor values us ing bayesian models. Proceedings of the 3rd International Workshop on Intelligent Transportation. https://elib. dlr.de/22833/1/AU_FS_ManeuverRecognition_Gerdes_060316.pdf 5. (2017). Artificial intelligence in the next-gen automobile. PC Quest. http://link.galegroup.com/apps/doc/ A481898038/ITOF?u=upenn_main&sid=ITOF&xid=dbc082f5.

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eople often say that you should not let small problems become big ones. While this advice is relevant to many issues we face, it perhaps applies most literally to the field of medicine, in which conditions stem from abnormalities and disruptions on the molecular level. The millenia-old practice of preventing and treating illnesses represents our continual battle against cellular dysfunction and pathogens that can harm a victim millions of times larger than themselves. All too often, diseases are diagnosed too late because the problem is undetected until it has progressed to the point at which it can be seen or felt. Centuries of research have helped scientists develop today’s vaccines, drugs, and other tools for tackling microscopic problems in the human body. However, diseases would be undeniably easier to address if we were small enough to see them with the naked eye and eliminate them directly. While we can only fantasize about the ability to physically shrink to combat diseases, researchers are investigating microscopic, autonomous devices that could perform this job for us and revolutionize medicine: nanorobots. Recent studies suggest that the small, intelligent machines could be a valuable tool in the biomedical field, as they could approach problems more directly and precisely than current therapeutic treatments. For instance, in February 2018, researchers from Arizona State University and the Chinese Academy of Sciences published a study in Nature that demonstrated that nanorobots could inhibit cancer tumor spread.1 The scientists created a mouse tumor model by injecting mice with cancerous human cells to provoke tumor growth. Afterwards, they injected the mice with nanorobots made of 90x60 nanometer sheets of DNA origami, single-stranded DNA that had been folded into planar nanostructures.2 The devices were also attached to four molecules of thrombin, a blood clotting agent that inhibits blood vessels

small devices making

big strides By Emily Lo Edited by Emma O’Neil Designed by Amara Okafor 10 PENNSCIENCE JOURNAL | spring 2019


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Nanorobots are microscopic autonomous machines that are being researched in medicine for various purposes such as drug delivery, the combat of various diseases such as cancer, and for diagnosis.

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supplying nutrients to cancerous tumors. As the nanorobots were programmed to deliver the thrombin to tumor blood vessels, this treatment increased the median survival time of melanoma mouse models from 20.5 to 45 days and shrunk tumor tissues in a primary mouse lung cancer model after two weeks of treatment.3 These results suggest that nanorobots can be a valuable vehicle for delivering drugs to target locations. Moreover, if they were able to navigate human tissue and hard-to-reach areas of the body such as the brain, nanorobots can gather data to help scientists map the human body and further facilitate the development of cancer therapies. In addition, a study conducted by researchers at the University of California, San Diego suggests that nanorobots have the ability to target pathogens and

This finding indicates that nanorobots could effectively decontaminate biological fluids, thereby combating pathogens in the bloodstream and facilitating other broadspectrum bio-detoxification efforts.

detoxify the bloodstream.4 The experiment, published in Science in May 2018, involved the usage of nanorobots made of gold wire coated with membranes of platelets that bind pathogens and red blood cells that neutralize toxins. Moving in response to ultrasonic frequency vibrations, these nanorobots navigated through human blood infected with methicillin-resistant Staphylococcus aureus (MRSA) bacteria. Despite being only 25 times the width of a human hair, the nanorobots yielded blood samples with three times 10 PENNSCIENCE JOURNAL | spring 2019

fewer bacterial toxins and MSRA compared to the control blood sample.5 This finding indicates that nanorobots could effectively decontaminate biological fluids, thereby combating pathogens in the bloodstream and facilitating other broadspectrum bio-detoxification efforts.4 While exploring the innovative biomedical applications of nanorobots, scientists have acknowledged the need to consider how the implanted devices will move through the human body. In current studies, nanorobots are typically designed to travel through fluids in the body such as blood by way of ultrasound vibrations or micromotors. However, given their small size, nanorobots must often be used in groups of thousands at a time, raising the question of how the devices should be designed to collectively divide and conquer complex tasks. To address this issue, researchers at the Chinese University of Hong Kong have developed nanorobots whose movements can be controlled using programmed oscillating magnetic fields. Using the behavioral patterns of bird flocks and insect swarms as a model, the researchers designed the nanobots to have microswarming capabilities and demonstrated that the devices have the ability to alter their size and configuration as part of a group.6 These findings have promising implications: nanorobots can potentially assist in medical tasks such as surgeries, targeted drug delivery, and tissue repair.6 Despite recent breakthroughs that highlight the potential of nanorobotics in the medical field, it is necessary to consider potential risks tied to the usage of these devices. For instance, due to the novelty of nanotechnology, we do not fully understand the long-


term adverse effects that nanorobots can have on our health. It is possible that nanorobots can weaken our natural defense systems if we depend on them for medical tasks.7 In addition, while gold is widely regarded as a biocompatible material for nanoparticle synthesis, a study conducted by researchers at University of Bern, Switzerland found that epithelial cells were characterized by inflammation when exposed to nanoparticles with excess concentrations of gold.8,9 The importance of examining nanoparticle toxicity has inspired researchers including Dr. Katie Whitehead, a professor at Carnegie Mellon University studying the human body’s immune response to nanoparticles. Whitehead argues that this field of study is often undervalued due to its complexity and cost, but is necessary.10 Given the need to account for chemical composition and structural design, scientists are still striving to develop designs that optimize the biocompatibility of nanorobots. As humans, we are often limited by an inability to tackle problems that are beyond our natural reach. Nanorobots are a tool that could lessen the gap between our physical capabilities and the microscopic nature of many health problems. While researchers are still

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exploring the ways in which this technology could enhance current medical treatments, many studies highlight useful applications that could soon be feasible. As we continue to learn how nanorobots could be properly designed for usage in our bodies, the devices are undeniably promising: few other developing technologies share the same potential to play such a versatile and meaningful role in our lives.

Another potential application of nanobots: health monitoring and security. References 1. Eveleth, R., 2015, “Why We Don’t Have Fully Operational Nanobot Doctors Yet,” The Atlantic [Online]. Available: https://www.theatlantic.com/technology/archive/2015/08/nanobot-treatment-doctors-cancer/400613/. 2. Hanson, J., “Nanotechnology Risks,” Weather Control Technology | Controlling the Weather [Online]. Available: https://www.futureforall.org/nanotechnology/risks.htm. 3. “How does your immune system react to nanomedicine?,” Phys.org - News and Articles on Science and Technology [Online]. Available: https://phys.org/news/2016-10-immune-react-nanomedicine.html#jCp. 4. “Nanotechnologies,” Artificial Light: 3. How does light affect living organisms? [Online]. Available: https:// copublications.greenfacts.org/en/nanotechnologies/l-2/6-ealth-effects-nanoparticles.htm. 5. 2014, “Nanotechnology: Potential Pros and Cons for Humanity,” Conscious Life News [Online]. Available: https://consciouslifenews.com/nanotechnology-potential-pros-cons-humanity/1172870/#. 6. PhD, C. P., 2012, “Nanotechnology In Medicine: Huge Potential, But What Are The Risks?,” Medical News Today [Online]. Available: https://www.medicalnewstoday.com/articles/244972.php.

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De e p L ea r ni n g A I :A N ew Eye fo r Medi cal Diagn os ti cs WRITTEN By Neelu Paleti EDITED BY ABRAHAM FREY AND SUMANT SHRINGARI DESIGNED BY LINSDSAY SMITH

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You wake up with a pounding headache. After experiencing a loss of appetite and chills, you decide to go to the doctor, not knowing the lengthy, arduous process of obtaining a diagnosis. You arrive at the hospital only to be given mountains of paperwork with questions probing your family’s history of disease, habits, and more. When you finally see the doctor, the physician orders blood tests, an X-ray, and urine samples. Each of these tests requires a 1-2 day wait, so without a diagnosis at hand, you are forced to return home with a follow-up appointment. What if this entire process could be cut down to minutes? With artificial intelligence (AI), it can. Year after year, medical schools train thousands of new students to become doctors. Yet nowadays, students are not the only ones being taught to work in medicine; computer algorithms are being trained alongside doctors. Robots are venturing into medical diagnostics using deep learning AI, a set of machine learning algorithms that can learn and analyze patterns within large data sets.1 Using a wide range of medical records, imaging results, and physician notes, AI and machine learning algorithms can improve the efficiency and accuracy of medical diagnostics. Deep learning AI streamlines patient check-in by expediting medical history write-ups with a simple scan of medical documents. Instead of developing patient risk scores using manual reviews of patient electronic health records, AI Natural Language Processing (NLP) systems are employed to efficiently review data charts, consolidate patient health information, and enable physicians to make informed care decisions.2 NLPs scan doctor’s notes or relevant clinical trial research papers to identify key elements and summarize information in a concise way. This program enables efficient synthesis of multiple sources of patient data to compile a coherent pool of knowledge. These algorithms then use statistics to determine whether this information is what the doctors desire.1 By feeding them more data, these probabilities can be adjusted to accurately fetch the relevant data. One key commercial example is Amazon Comprehend Medical.2 This service supports physicians when making clinical decisions for their patients, as it allows doctors to sift through the fine details within years of accumulated medical history. This rapid analysis method has proven AI to be an efficient

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way to pair patients with treatment. In fact, the CIO of Fred Hutchinson Cancer Research Center in Seattle has even adopted this technology in identifying the best clinical trials for cancer patients.3 Instead of spending time collecting medical history to be reviewed, AI will allow physicians to see general trends in medical history. Once a patient’s medical records are processed and analyzed, doctors can then use AI to pinpoint genetic disorders using a facial recognition software trained with machine learning. Face2Gene, a diagnostic app that uses deep learning algorithms, analyzes pictures of human faces for patterns that allow it to identify possible diagnoses.4 FDNA, a Boston digital health company, has trained this algorithm with over 17,000

” This trained algorithm was able distinguish between two common types of lung cancer with 97% accuracy.” pictures spanning 216 health conditions to curate a list of ten possible diagnoses that includes the correct condition 90% of the time.4 Karen Gripp, a medical geneticist, described her experience diagnosing a child with Wiedemann–Steiner syndrome, a rare genetic disorder.4 Never having seen this disease before, Gripp struggled to find key physical features and biomarkers. Uploading a picture to this app allowed the algorithm to detect the correct genetic disorder and affirm Gripp’s initial diagnosis. While this form of AI cannot be used alone in diagnostics, it supports the findings of the physician or acts as a starting point for physicians to test. This application of AI can often save patients the time and money of multi-gene panel testing and other bloodwork that take days to diagnose. Using a larger database of more pictures from a diverse population, this algorithm can be trained to support doctors in a faster, more accurate manner.4 Following scans of patient health records and facial recognition applications, AI can then assist closely in clinical diagnoses. Using X-rays or MRI scans, AI can decode specific parts of the patient’s spring 2019 | PENNSCIENCE JOURNAL 15


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body to accurately offer a diagnosis. Specifically, 4D MRI scans reveal 3D images of the heart in real time to extract visual data on blood flow and tissue scarring to quantify the magnitude of the diagnosis. This analysis presents all key information needed from MRI scans in just under 25 minutes, accommodating a larger patient population within a day.5 Besides trying to deduce the severity of an anatomical defect in the heart, machine learning algorithms can connect MRI scans of hearts with previous data on prognoses and treatment outlooks. In another application, Google AI tools use a picture of a lung to identify types of tumor and prognosis indications. Google’s trained algorithm is able to distinguish between two common types of lung cancer with 97% accuracy.4 Reaching farther than current human capabilities, this technology can even scan for the presence of microscopic changes resulting from genetic mutations from just a picture of the tumor.4 By minimizing the need for lengthy pathologist lab work, doctors will be able to act quickly on diagnoses and prescribe the appropriate treatment. Furthermore, this tool supports doctors with an extra layer of diagnosis, which can be especially beneficial for rare disorders that doctors do not identify or treat on a regular basis. As these algorithms are trained with more images and annotations of additional cellular features, this technology may see widespread usage with greater accuracy.

As the demand for doctors and healthcare is increasing, these machine learning algorithms can greatly increase efficiency and support the work of doctors. Such applications have the potential to increase access to disease treatments in rural areas with fewer medical professionals and low-quality care. Working together, doctors and machines can improve healthcare with better efficiency, accuracy, and outcomes.

>Your diagnosis is ready. >>View >A prescription has been written for you. >Accept? Y or N >y >Your blood pressure has spiked recently. I have made an appointment with the cardiologist. Potential applications of technology in healthcare offer the possibilities of diagnosis and treatment informed by artificial intelligence.

>>references 1. Quer, G., Muse, E., Nikzad, N., Topol, E., and Steinhubl, S. (2017). Augmenting diagnostic vision with AI. The Lancet 390, 221. 2. (2019). Amazon Comprehend Medical. 3. (2019). Fred Hutch, Microsoft partner to improve cancer care delivery. 4. Dolgin, E. (2019). AI face-scanning app spots signs of rare genetic disorders. Nature. 5. (2019). Cardio - Arterys.

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The Sense of Touch: Now a Teachable Skill Written by Michelle Paolicelli EDITED BY MIMI LU DesignED by Winnie Xu

H

ave you ever tried to hold a pencil after being out in the cold? The lack of feeling makes it difficult to do. Now imagine this frustrating scenario being a part of your daily reality. Alongside the inability to perform actions that require fine motor skills, many upper limb amputees live in a world without the sense of touch. Lower limb prostheses have allowed amputees to return to a typical routine and even excel at sports.1 However, the same cannot be said of upper limb prostheses due to the complexities of the human hand, but there are many promising technologies on the rise that could one day revolutionize the lives of these amputees. Currently, the most widely available upper limb prostheses in the market provide a severely reduced range of motion to the wearer and lack haptic feedback, a technology that uses force to recreate the sense of touch.1 The least expensive options operate on a rudimentary system of wires and pulleys, requiring the wearer to use their other arm to control it. In the interest of efficiency and quality of life, alternate options are of great interest to engineers today. By combining the expanding field of robotics with traditional prosthetic materials, more suitspring 2019 | PENNSCIENCE JOURNAL 17


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able upper limb replacements will be made available. The function of a human hand is made possible through a complex structure of nerves, muscles, tendons, and bones that allow for maximum dexterity. Replicating this is no small feat, but through the combination of myoelectric technology and targeted muscle reinnervation, it may soon be possible. Throughout this process, the consideration of a patient’s specific lifestyle needs are of utmost importance. The term myoelectric describes the electric signals that are naturally generated by muscles and are sent to the brain when muscles contract.2 In an amputee, these signals can still be produced despite the loss of the limb. The challenge lies in properly directing these signals to the brain to be processed.

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By re-harnessing the myoelectric properties of the residual limb, amputees could control a prosthesis through voluntary muscle control, greatly improving their dexterity. Additionally, this integration of natural muscle with artificial limb leaves the user free from straps or other mechanical controls. An obstacle to the widespread implementation of this technology is the complicated algorithms required to maximize the wearer’s degree of control.2 For this reason, more resources need to be put toward developing these algorithms so that the software side of myoelectric technology can catch up to the mechanical portion. “...THE INTEGRATION OF NATURAL MUSCLE WITH ARTIFICIAL LIMB LEAVES THE USER FREE FROM STRAPS OR OTHER MECHANICAL CONTROLS...” In order to return the sense of touch to an individual who has lost a limb through myoelectric technology, the relevant nerves and pathways to the brain must be re-established. Currently, this is best done through a procedure called targeted muscle reinnervation. In this process, residual nerves from the point of amputation are physically transferred to a location further up on the arm or shoulder, depending on the specific amputation type.5 By pairing this with the previously discussed myoelectric technology, patients can learn to interpret electric signals as touch. Unfortunately, muscle reinnervation is currently a very invasive procedure and only a small group of amputees qualify. Typically, muscle reinnervation is restricted to patients who have undergone an amputation fairly recently, but the procedure has found success in patients who underwent amputation as long as forty years ago. One such case is that of Les Baugh, a man who lost both of his arms to an electrical accident. After muscle reinnervation surgery, Baugh worked with researchers to develop pattern recognition algorithms that could identify how his muscles contracted and communicated to each other. These algorithms were then translated into actual physical movements for Baugh’s custom fitted prosthetic arms. After just ten days of training, Baugh was able to complete a variety of simple, everyday tasks, like picking up a cup, that he had been unable


to perform for forty years. Clearly, Baugh was able to benefit immensely from the combination of muscle reinnervation, myoelectric technology, and advanced prosthetics.4 However, if this procedure could be made less invasive, faster, and less expensive, it would be truly revolutionary for the amputee community. Like most things in life, upper limb prostheses are not one size fits all. Each individual has a unique amputation and lifestyle. An upper limb prosthesis for a young boy who wants to play tennis would look very different from one for a stay at home mom who cares for her children full time. Considering the patient’s individualized “MAKING AFFORDABLE PROSTHETICS THAT ARE ABLE TO GROW WITH THE USER CONTINUES TO BE A GREAT OBSTACLE IN THE PROSTHESES INDUSTRY” needs for a prosthesis is one of the most important aspects of the field, as well as one of the most challenging. One way this is being done is through the integration of Bluetooth technology and prostheses.3 This practical application allows the wearer to listen to music and other audio directly through the artificial limb. An additional advantage of this is that it removes the necessity for an amputee to physically hold their phone: a seemingly small task that may be very difficult for them. Although a relatively simple addition to a prosthesis, Bluetooth technology allows amputee to make their new limb their own. The technology now exists to make advanced, capable prosthetics, but this technology can often be too expensive to be practical. This is especially true for young am-

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putees who are still growing and require new fittings every few years. Making affordable prosthetics that are able to grow with the user continues to be a great obstacle in the prostheses industry. 3D printing and its affordability may have the ability to ameliorate this problem in the near future. Upper limb prosthetics have evolved greatly from the days of passive, manually powered devices that were often more cumbersome to the wearer than they were helpful. The combination of myoelectric technology, muscle reinnervation, and advanced mechanical systems has allowed for the creation of impressive, life-like artificial limbs. Great success has been achieved with lower limb prostheses, allowing amputees to return to activities like dancing, skiing, and running, all at the professional level. Now, the recent shift in focus to the development of upper limb prostheses will help to change the perception of amputation from one of disability to one of renewed possibilities.

REFERENCES

1. Cordella, F., Ciancio, A. L., Sacchetti, R., Davalli, A., Cutti, A. G., Guglielmelli, E., & Zollo, L. (2016). Literature Review on Needs of Upper Limb Prosthesis Users. Frontiers in Neuroscience,10. doi:10.3389/fnins.2016.00209 2. Parker, P. (2006). Myoelectric signal processing for control of powered limb prostheses. Journal Of Electromyography and Kinesiology,16(6), 541-548. doi:10.1016/j.jelekin.2006.08.006 3. Fairley, M. (2009, October). State-of-the-Art: Upper-Limb Prosthetics Technology. Retrieved from https://opedge.com/Articles/ViewArticle/2009-10_01?mf=0 4. Smith, D. (2014, December 18). A Man Who Lost Both Arms 40 Years Ago Is Making History As The First Person With Two Mind-Controlled Robotic Arms. Retrieved from https://www.businessinsid er.com/les-baugh-is-the-first-person-with-two-mind-controlled-robotic-arms-2014-12 5. Kuiken, T. A. (2009). Targeted Muscle Reinnervation for Real-time Myoelectric Control of Multifunction Artificial Arms. Jama,301(6), 619. doi:10.1001/jama.2009.116

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Bio-inspired

Relieving the Burden of Clima te change

By Rosie Nagele Edited by dan rodriguez Designed by Olivia Myer

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hen it comes to inspiring life-forms, sloths usually aren’t the first species that come to mind. With their low nutrient intake and penchant for naps, sloths are mainly known for being one of the world’s slowest-moving mammals.¹ Yet even lethargy, as at least one scientist argues, has its advantages. Ronald Arkin, roboticist at the Georgia Institute of Technology, uses sloths as inspiration for slow-moving robots.² By minimizing energy expenditure and disruption to their surroundings, Arkin anticipates deploying these SlowBots for prolonged periods, opening up novel applications in environmental monitoring.³ Arkin is not the only roboticist taking notes from the natural world. Having mastered the basics of locomotion and sensory processing, the field of robotics has moved in recent years to the challenge of diversifying the functionality of their machines.⁴ Biological systems provide valuable models for nuanced robotic design. Though evolution has no end goal, species are under constant pressure that refines their physiological or behavioral survival strategies for particular environmental conditions. The concept of using features of individual organisms as well as intra- and inter-species relationships as models to design and produce new technology is called biomimetics.⁵ In the field of robotics, biomimetics can improve the ability of machines to navigate uneven surfaces, withstand harsh environmental conditions, and function with less human supervision. All of these features can be useful when developing robots to help humans respond to anthropogenic climate change. While there will be no one solution to mitigating or adapting to climate change, bio-inspired robots can help monitor its impacts in different ecosystems, alleviate its immediate burden on human communities, 20 PENNSCIENCE JOURNAL | spring 2019


and contribute to long-term strategies for reducing carbon Features dioxide emissions. Take Arkin’s sloth-inspired, slowmoving robots, for example. One function for these SlowBots is in precision agriculture, the use of information technology to increase agricultural efficiency.⁶ By collecting information on increasingly specific spatial and temporal scales, farm labor can be tailored to the needs of a crop at any particular time.⁷ With the frequency of extreme weather events on the rise, agricultural productivity and the safety of farm laborers depends on more precise and efficient agricultural practices.⁸ Robots that monitor field conditions reduce the amount of time workers spend in harsh, outdoor conditions. Traditional robots, however, are unable to sustain continuous measurements and threaten to damage the crops as they move around, operating as “an invading force,” as Arkin puts it.⁹ Agricultural robots will need to be selfsufficient, functional over extended periods of time, and minimally disruptive to the surrounding crops--all traits found in the physiology and behavior of sloths.¹⁰ Arkin hopes a sloth-inspired SlowBot can become “a semipermanent member of the ecosystem.” Another bio-inspired design feature that enhances the compatibility of robot and environment is circadian rhythms. Responding to unpredictable external conditions is a key feature of robotic function, and anticipating regular environmental fluctuations can increase the efficiency of their response. Circadian rhythms are chemical oscillations that occur on a roughly twenty-four hour cycle. They modulate organisms’ behavior and physiology to align with the rise and set of the sun. Cyclical changes in behavior and physiology also occur on seasonal and annual patterns. In 2018, Arkin co-authored a paper discussing how to adapt robot behavior to cyclical environmental changes on several scales, inspired by circadian rhythms.¹¹ Arkin’s team programmed a solar-powered SlowBot with information about solar cycles and aphid population dynamics to increase its efficiency at detecting and responding to pests. Besides farmland, bio-inspired robots can improve the monitoring of other environments sensitive to climate change. Subsurface environments– subterranean and aquatic--have important roles in global carbon accounting but have been particularly difficult to monitor. On land, soil presents the challenge of being unstructured and vulnerable to disruption by traditional probes. Many biological systems, however, have developed strategies to navigate soil. The PLANTOID Project, an endeavor of the Instituto Italiano di Tecnologia, uses plant biology to develop robots to navigate soil.¹² Though their stalks are sessile, plants are extremely mobile in their roots. By adding

“While there will be no one solution to mitigating or adapting to climate change, bio-inspired robots can help monitor its impacts in different ecosystems, alleviate its immediate burden on human communities, and contribute to long-term strategies for reducing carbon dioxide emissions.” spring 2019 | PENNSCIENCE JOURNAL 21


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cells at their tips, roots penetrate soil with minimal friction or disruption of soil stability.¹³ Sensory mechanisms allow them to tune their growth to local conditions of moisture, temperature, nutrient content, toxicity, texture, and more. Scientists with the PLANTOID Project are using 3D printing to develop robots that mimic plant root movement through different materials.¹⁴ One of the many possible applications of such technology is the capacity to monitor environments for contamination or nutrient composition.¹⁵ The ocean poses a different set of challenges to monitoring robots than soil, not the least of which is its vast size and incredible heterogeneity. Several roboticists have turned to biology to navigate this space. Robotic swarms, inspired by the swarming behavior of fish, involve the deployment of several submarine robots all in communication with each other. The Venus Swarm, for example, can collect data about temperature, salinity, currents, coastal erosion, and more.¹⁶ Individual robots communicate using light and sound systems designed for speed through water, allowing them to coordinate swimming patterns for efficient data collection. Other swarming submarine robots are based off of small, widely dispersed organisms that capture a more comprehensive picture of ocean conditions. These tiny, plankton-like robots are being deployed to monitor ocean currents, the distribution of larvae and microorganisms, the dispersal of oil following spills, and the movement and accumulation of marine debris.¹⁷ How ocean ecosystems will be impacted by climate change, however, is still largely unknown. In addition to monitoring environmental conditions and providing immediate relief, biomimicry in robotic design can improve technology aimed at reducing carbon emissions. Specifically, biomimicry can inform systems of generating renewable energy, such as tidal harvesting machinery.¹⁸ One major obstacle for harnessing tidal energy is the rapidity with which tidal environments degrade underwater machinery. Salt water corrodes commonly used materials, while encrustations and seaweed accumulation impede movement. Many organisms, however, move through these same environments without these issues. A group of scientists in Japan experimented with adapting bio-inspired fish robots into machinery for harvesting tidal energy. Efficiently harvesting energy from tidal forces would go a long way toward helping coastal regions transition away from fossil fuels. Whether for monitoring, providing relief from, or slowing down climate change, biomimicry can be a powerful tool. With some 1.5 million known species and an estimated total of 2 billion, nature has already designed many systems of surviving, navigating, and responding to different conditions on Earth.¹⁹ These species themselves are under increasing pressure from changing environmental conditions. It remains to be seen which species, behaviors, interactions and biological systems will be most resilient to these changes. As such, collaborations between biologists and roboticists will become increasingly important in the face of environmental change. 22 PENNSCIENCE JOURNAL | spring 2019

In addition to monitoring environmental conditions and providing immediate relief, biomimicry in robotic design can improve technology aimed at reducing carbon emissions.”

References 1. Why are sloths slow? And six other sloth facts. World Wildlife Fund. https://www.worldwildlife.org/stories/why-are-slothsslow-and-six-other-sloth-facts 2. Ronald Arkin. Georgia Tech College of Computing. https://www.cc.gatech.edu/aimosaic/faculty/arkin/ 3. Arkin, A. C. (2015). Bio-inspired slow for robotic systems. Georgia Tech Mobile Robot Lab. https://www.cc.gatech.edu/ai/robot-lab/onlinepublications/Arob2.pdf 4. Thorpe, C., and Durrant-Whyte, H. (2006). Field robots. Carnegie Mellon University Robotics Institute. https://www.ri.cmu.edu/pub_files/pub3/thorpe_charl es_2001_1/thorpe_charles_2001_1.pdf 5. Biomicry 101. Biomimicry Institute. https://biomimicry.org/what-is-biomimicry/ 6. Zhang, N., Wang, M., and Wang, N. (2002). Precision agriculture-a worldwide review. Computers and Electronics in Agriculture 36, 113-132. 7. UK Robotics & Autonomous Systems. (2018). Agricultural robots: The future of robotic agriculture. https://arxiv.org/pdf/1806.06762.pdf 8. Zeldovich, L. (2018). Do we really need robotic farmers? JSTOR Daily. https://daily.jstor.org/do-wereally-need-robot-farmers/ 9. Arkin, C. R., and Egerstedt, M. (2015). Temporal heterogeneity and the value of slowness in robotic systems. 2015 IEEE International Conference on Robotics and Biomimetics. https://doi.org/10.1109/ROBIO.2015.7418902 10. Velayudhan, L., and Arkin, C. R. (2017). Sloth and slow loris inspired behavioral controller for a robotic agent. 2017 IEEE International Conference on Robotics and Biomimetics. https://doi.org/10.1109/ROBIO.2017.8324693 11. O’Brien, M. J., and Arkin, C. R. (2018). An artificial circadian system for a slow and persistent robot. From Animals to Animats 15. https://doi.org/10.1007/978-3-319-97628-0_13 12. The project. Plantoid. https://www.plantoidproject.eu/index.php/theproject/project-details 13. (2014). Building a robot to mimic plants. ResearchEU. https://www.plantoidproject.eu/images/pdf_files/Rese archEU_%20ResultsMag_March30_2014.pdf 14. Barbieri, A. Plant roots inspire 3-D printed automotive sensors. CORDIS. https://cordis.europa.eu/news/rcn/130433/en 15. Fadelli, I. (2017). The plantoid project: How robotic plants could help save the environment. Engineering & Technology. https://eandt.theiet.org/content/articles/2017/07/the -plantoid-project-how-artificial-plants-could-help-savethe-environment/ 16. (2016). Climate: At the UN headquarters advanced Italian-made technology to tackle climate change. Italian National Agency for New Technologies, Energy and Sustainable Economic Development. http://www.enea.it/en/news-enea/news/climate-atthe-un-advanced-italian-made-technology-to-tackleclimate-change 17. Augliere, B. (2019). Eyes in the sea: Swarms of floating robots observe the oceans. Earth. https://www.earthmagazine.org/article/eyes-seaswarms-floating-robots-observe-oceans 18. Yamamoto, I., Rong, G., Shimomoto, Y., and Lawn, M. (2017). Numerical simulation of an oscillatory-type tidal current powered generator based on robotic fish technology. Applied Sciences 7, 1070. 19. University of Chicago. (2017). A new estimate of biodiversity on earth. Phys.org. https://docs.google.com/document/d/11JXYKEacgv NClufOvR1r9dHuX3tE4v9EMRMgKWjcQ9Q/edit


Features

ROBOTS AT WAR AUTHOR PRANSHU SURI EDITED BY BILLY HASLEY DESIGN FELICIT Y QIN

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he first wars of this world were fought on foot with swords, spears, and javelins. Later on, guns were introduced into the sphere of combat, followed by tanks and military aircraft.1 Today, smart robots and artificial intelligence are being increasingly integrated into the fabric of our everyday lives; it seems only natural that these emerging technologies are integrated into war and national defense as well. As it turns out, military robotics is a huge global industry. The world’s militaries spend a total of over $7.5 billion on robotics, and many countries are doing extensive research on how they can implement these sophisticated technologies on the battlefield.1 As of 2014, the Pentagon has actively deployed over 11,000 unmanned flying drones and 12,000 ground robots for use in military operations, putting the U.S. at the forefront of this movement, alongside China and Russia.1 These numbers are projected to increase exponentially in coming years.1 There are two major classes of military robots that may be implemented in warfare— unmanned ground vehicles (UGVs) and unmanned aerial vehicles (UAVs)—each of which functions as their names imply.2 Most of these machines share three fundamental characteristics, regardless of their further specified function: sensors to gather information from their environment, some form of mobility/means of movement, and a power source.2 Most are also controlled remotely by humans as fully autonomous robots are still a few years away from being implemented in war.2 In terms of favorable attributes in combat, many are small, making them easy for soldiers to move around and position on the battlefield, and many are able to operate both on land and in water.2 Military robots rely heavily on preprogrammed algorithms and software in order to recognize and acquire targets. This software is based largely in machine learning, a burgeoning branch of AI that involves building statistical models of patterns in data sets meant to

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“teach” a robot how to make its own decisions or perform a task without explicit instructions.3 In addition to these algorithms, most military robots that exist today rely to some degree on humans to dictate certain aspects of their function; for instance, a human may control the geographical boundaries in which a robot operates, and its algorithms may dictate the location of the enemy target within these boundaries. There are two types of machine learning algorithms—supervised and unsupervised. In supervised machine learning, a predetermined structure is imposed on a data set, and the computer system must learn how to classify elements of the data set based on this structure.4 In unsupervised machine learning, there is no structure to the data set, and the computer must determine its own structure based on trends and patterns it identifies, which it uses to make sense of the data and further perform an informed action.4 Military robots utilize the latter in their software, taking in information from their surroundings and parsing it for an identifiable target.1 This function of military robots is precisely why fully automating these systems is so controversial—one misstep in an algorithm could be the difference between life and death. That being said, if governments could find a way to automate military robots successfully and reliably, the applications are innumerable. Automated surveillance, reconnaissance, direct attacks, border protection, locating and defusing roadside bombs, destroying incoming missiles, and search & rescue operations are some of the many potential implementations of UAVs and UGVs in combat.1 Although the endless applications of military UGVs and UAVs are evident, one would be remiss not to address the risks and challenges that may accompany the implementation of these autonomous vehicles. Many have argued that autonomizing war crosses a certain moral threshold for every party involved. In branches where military robots have been implemented to attack enemy targets, there have been high rates of PTSD among the soldiers controlling these robots remotely; they report feeling a


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stark disconnect between the remote operation of the drones and the fact that these robots are actually killing people on the other side of the screen.1 Additionally, the software that controls robotic target recognition is not foolproof, and some operations end up killing more civilians than enemy targets as a result.1 The machines themselves are also very affordable and highly commercialized, so militaries are actually incentivized to implement them at the risk of being “left behind� in the race to autotomize war. Removing humans entirely from the war scene, as many countries have proposed, poses many complications and questions to consider. Governments probably would not consider going to war with as much caution if they are sending robots to fight rather than humans.5 Thus, we as a population would gradually grow more tolerant of armed conflict, which is dangerous for both civilians and soldiers.5 Many questions arise: if war becomes robots-vs-robots, where do we draw the line in combat?5 What constitutes a win? And perhaps the biggest and most controversial question in this sphere of development—is it morally sound to delegate life and death decisions to an unthinking, unfeeling

machine?5 Although military robotics offers unequivocal potential for the future of warfare, we must be cautious in implementing these emerging technologies, considering all ethical questions and complications that may arise in the process.

References 1. Horowitz, C. M. (2014). The looming robotics gap. Foreign Policy. https://foreignpolicy.com/2014/05/05/ the-looming-robotics-gap/ 2. Grabianowski, E. How military robots work. How Stuff Works. https://science.howstuffworks.com/military-robot.htm 3. What is machine learning. Carnegie Mellon University School of Computer Science. https://www.ml.cmu.edu/ 4. Soni, D. (2018). Supervised vs. unsupervised learning. Medium. https://towardsdatascience.com/supervised-vs-unsupervised-learning-14f68e32ea8d 5. Brown, A. S. (2011). Risks of robotic warfare.The American Society of Mechanical Engineers. https:// www.asme.org/engineering-topics/articles/robotics/ risks-of-robotic-warfare

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EDITED BY KELLY LIANG Design by Hannah Wang

Written by Celia Zhang

SEAGLIDERS TO THE

RESCUE

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e are walking on thin ice. As ice shelves in Antarctica weaken due to global warming, sea levels are rapidly rising. Ice shelves are remnants of glaciers and their role is to reinforce the ice on nearby land. However, warming temperatures bring upon the collapse of these ice shelves and hasten their advancement towards the sea. Instead of resting on land, they flow into the ocean and increase sea 1 levels. There is a pressing need for new ways to research the world’s coldest oceans to fight these threats.

Making further progress in understanding ice shelf ocean interaction requires much more extensive technology to strengthen the current data on the Antarctic ice.2 One way to gain more insights into the melting of ice shelves in Antarctica is researching the topography and properties of these ice shelves and paying attention to their gradual movements. Advancements in understanding ice shelves have been hampered by the minimal accessibility of the area beneath the ice shelves to be 26 PENNSCIENCE JOURNAL | spring 2019


Features How do we overcome the tradeoff between power and speed? Should we sacrifice agility for more technological capabilities? measured. Boreholes through the ice have provided accurate measurements; unfortunately, they involve high costs which have capped the number of access points across Antarctica to less than twenty. Making further progress in understanding ice shelf-ocean interaction requires much more extensive technology to strengthen the current data on the Antarctic ice.2 In looking back at the development of underwater robots, the first step of this new era of arctic climate research mostly employed large autonomous underwater vehicles. Though they greatly enhanced the breadth of knowledge on the water flow, salinity, temperature, and velocity of ice shelves,2 the downside of these autonomous underwater vehicles was their large submarine-like build, bringing up crucial issues. How do we overcome the tradeoff between power and speed? Should we sacrifice agility for more technological capabilities? This is where Seagliders come in. These robots are small, but have the endurance to sample the ocean interior

The key to their powerful performance is that instead of relying on motors and propellers, Seagliders move by “changing their buoyancy and using lifting surfaces, such as wings, to translate vertical into horizontal motion.”4 remotely.3 They have a small torpedo-like body with wings and rudders and a tail with antennas, perfect for efficient hydrodynamics. In recent years, this technology has provided critical clues and data, leading to predictions of the underlying processes that contribute to weakening ice shelves. Researchers at the University of Washington Applied Physics Laboratory and School of Oceanography have turned to Seaglider underwater robots as their newest innovative project to delve further into the ice. The outlook is to continue developing informative models of the Antarctic ice shelves to control sea level rise. The key to their powerful performance is that instead of relying on motors and propellers, Seagliders move by “changing their buoyancy and using lifting surfaces, such as wings, to translate vertical into horizontal motion.”4 Similar to wings on an airplane, the wings on Seagliders provide lift as the vehicle propels itself forward. Its additional self controlled buoyancy ability allows their volume to be adjusted relative to that of an equal mass of seawater to provide a smooth gliding climb or dive.5 Seagliders exhibit complete independence during each 1-km deep descent. They are capable of collecting information on a wide time and spatial scale, ranging from hours to decades and from one to thousands of kilometers. With its onboard GPS, the Seaglider maps out where to dive by sending out its own acoustic range and signaling its depth beneath an ice shelf.5 The antennas act as a source of communication to receive GPS signals or transmit data it has collected to the surface. Once there it can transmit measurements to a base station computer on land or receive its own files.6 In addition to sensors that collect data such as temperature, sa-

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Features linity, and current flow changes, Seagliders have added capabilities to detect oxygen and chemical content near the ice. Seagliders can also cover a greater range at almost half the energy cost. Its 17-megajoule batteries allow a seaglider to operate at only $400 a day. In comparison, a research ship may cost an average of $40,000 a day.7 The release of Seagliders into the ocean began back in the early 2000’s, but those were only short-lived trials. Between 2004 and 2005, Seagliders were released in powerful and rough ocean currents for a few months to test their range and survey oxygen and plant distribution. From these tests, the Seagliders confirmed their ability to surface every few hours to relay information through satellite call. Since then, over 70 Seagliders have been sent on missions across Earth’s waters. In January 2018, the mission to test Seagliders beneath the frigid

These ice shelves are some of the last frontiers on our planet, and it is imperative that we gather as much as we can to protect the coldest areas of the Earth. Antarctic Dotson Ice Shelf began.8 These Seagliders embarked to test a novel approach to collect data underneath the precarious ice shelves. By January 2019, the Seagliders had endured one year of continuous operation near the ice shelf. From that, a new milestone was set. Traveling over 3800 km on a mission, the Seagliders are setting record upon record as they swim through the Antarctic oceans, acting as curious little creatures embarking on a scientific journey in regions that are beyond the scope of human tolerance. The Seaglider project has opened new doors for exploring ocean worlds under remote ice shelves. Its unprecedented feats have illuminated crucial data for the scientific community as they examine the movements of these critical ice shelves.9 These ice shelves are some of the last frontiers on our planet, and it is imperative that we gather as much as we can to protect the coldest areas of the Earth. For decades, scientists have fantasized about a global network of economically and environmentally friendly robots in the ocean, and now it’s here. As we continue to seek out a map of the ocean and the ice shelf interior, we are getting closer to creating effective models to represent the growing threat of climate change. Seagliders are one aspect of a much larger world of robotics that work together to develop new and novel ways to explore places deemed impossible to reach in the past. 1. (2019). Quick Facts on Ice Shelves | National Snow and Ice Data Center. 2. Nicholls, K., Abrahamsen, E., Buck, J., Dodd, P., Goldblatt, C., Griffiths, G., Heywood, K., Hughes, N., Kaletzky, A., aLane-Serff, G. et al. (2006). Measurements beneath an Antarctic ice shelf using an autonomous underwater vehicle. Geophysical Research Letters 33. 3. Institute, E. (2019). Autonomous Robots Carry Out First Long-Term Missions Under Antarctic Ice. 4. (2019). A Team of Autonomous Ocean Robots Deployed in January 2018 Has Carried out the First Year-Long Observations under an Antarctic Ice Shelf. | Lamont-Doherty Earth Observatory. 5. Eriksen, C., Osse, T., Light, R., Wen, T., Lehman, T., Sabin, P., Ballard, J., and Chiodi, A. (2001). Seaglider: a long-range autonomous underwater vehicle for oceanographic research. IEEE Journal Of Oceanic Engineering 26, 424-436. 6. Eriksen, C., and Perry, M. (2009). The Nurturing of Seagliders by the Nation al Oceanographic Partnership Program. Oceanography 22, 146 157. 7. Staff, R. (2019). iRobot’s Economical Seaglider for Budget-friend ly Research - Robotics Business Review. 8. Rotkop, N. (2019). Seagliders Explorers - TFOT. 9. (2019). Seagliders Illuminate Effects of Climate Change on Antarctic Ice Shelf | Paul Allen.

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Interview

DR. CULLEN BLAKE Interview by Tamsyn Brann Design by Farhaanah Mohideen Dr. Cullen Blake is an observational astronomer at the University of Pennsylvania whose work focuses primarily on developing techniques to detect and characterize Earth-like planets orbiting brown dwarf stars. These stars are much bigger than Jupiter but not large enough to generate their own energy through fusion; they are essentially failed stars. Though they may not be analogs to our own Sun, brown dwarf stars still give off heat and often have planets, which may be habitable for human life, orbiting them. Dr. Blake observes these brown dwarf stars using robotic telescopes, which he believes play a vital role in modern astronomy since they have both optical and infrared capabilities with which to observe the universe. He also uses spectroscopic and photometric data from his research to learn more about low-mass stars and brown dwarf stars and to study other astronomical phenomena. spring 2019 | PENNSCIENCE JOURNAL 29


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What is the focus of your current research? Right now, we’re working on a lot of astro-engineering and a lot of building things in the lab and working with different devices. That’s been a big focus for a while and that’s why I’ve been away a lot this semester – I’ll be taking those instruments to the mountains. That’s taken up most of the lab’s attention lately: we’ve been focusing on that for the past couple of years. Where did your passion for astronomy come from? I was pretty interested in the stars and planets in elementary school and just kept at it – I went to college with the intention of studying that and just sort of liked it and I’ve enjoyed it. It’s sort of a privilege where you can have a job where you get to do things like this, go to mountains, build fun instruments, and things like that. What does your day-to-day work consist of? Teaching is a substantial part of my job – I usually teach ASTR 001 or some

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variant of that, a big introductory class. I’ve done that almost every semester – me and others rotate in and out of that job. I also advise graduate and undergraduate students and work in the lab, which takes up most of my time. We also do a lot of data crunching now. Astronomy has gone towards being more of data science, and a lot of our graduate students have a strong background in dealing with these enormous data sets that we have to work with. But we literally tinker with things. It’s very hands-on, where we make sure a gizmo is doing what it’s supposed to be doing or measure the properties of another gizmo. Tell me more about the robotic telescope project that you’re working on currently. One of my projects is a robotic telescope in Arizona that knows when to open and close, which is great because it can gather its own data for us – it stays open during the day and closes when it’s dark or raining. This telescope will be used to carry out a search for planets around the nearest low-mass stars: if we made a list of the five closest stars to the sun, they’ll be these tiny little things – not proper brown dwarfs but the smallest a star can be, stars that have names instead of numbers. This telescope will be used to look for planets around those stars with an instrument we’re building here in DRL. We build spectrographs. The idea of a spectrograph is that we take the light from the star and disperse it – it’s not


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exactly like a prism but it’ll split the light into the colors of the rainbow and imprinted on that rainbow from the star are these tiny little markers of chemicals. You can look up the wavelengths of the chemical fingerprints in any high school chemistry textbook. Then, we look for these markers moving in time and in concert: that’s the tell-tale signature of a planet orbiting the star, which is found using

what’s called the wobble method. The spectrograph is designed to detect exoplanets using the wobble method. Historically, I’ve been researching a bunch of different things, but right now I’m focusing on the wobble method. This is the original way that people have been looking for planets, and we’re right on the cusp of not necessarily a technological breakthrough but a new generation of

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these instruments are going to come online in the next year. I think there’s going to be a big, factorof-ten improvement in our ability to make these measurements in this way. I think it’s kind of an exciting time to be involved in that. The instruments themselves limit your ability to measure whatever you’re measuring – they have some characteristic that’s not ideal. Right now, the instrument itself is much better than what people were doing five years ago – they incorporate a whole bunch of new technologies that people are using to make them better-controlled; we’ll be able to detect things that were undetectable five years ago. I think in a few places around the world, a couple of these next-generation instruments are about to go into the field and start operating, whereas over the past ten years it’s basically been one instrument in Chile built by a Swiss university that’s been doing most of the science. What’s the significance of the locations of the robotic telescopes? The locations are all high and dry places – you want your observatory as high as possible and as dry as possible and away from city lights, so there are a few places around the world that are clearly the best for this. You also want to be high up to get through as much of the atmosphere as possible. Our sites in North America are not great, but the tradeoff is that they’re the most accessible. The cost of doing business, if you want to think about it like that, is just lower – people can get there easily from Tucson or Phoenix. If you’re building something in a remote site in Chile, it’s a much more complicated proposition to get the equipment and the people down there. What is the advantage of having a robotic telescope over a non-robotic telescope? Does the robotic aspect involve specific complications that lead to better data?

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The robotic telescope allows for very efficient data collection and greatly reduces the number of person hours required to collect our data. With a non-robotic telescope, somebody needs to physically go there to collect the data, which puts a big burden on astronomers. One advantage of robotic telescopes is that you can program it to use its time very efficiently, particularly for observations of things on the sky that occur at a specific time. The robotic telescope can also react very quickly to “chase” things on the sky (explosions of various sorts). One drawback is that they may not react to changing weather conditions as well as a person on-site would. Does it already or will it involve artificial intelligence, and in what way? At some level, the telescopes can ingest weather information and make decisions about what to observe, but I don’t think that really counts as AI. They can also decide what to observe based on what has recently observed, user priorities, etc. Where do you see the future of the field of robotic telescopes going? What role will robots play in the future of astronomy in regard to brown dwarf exoplanet research, or even in the field in general? I think that there will be more and more robotic telescopes in sizes around 1 meter in the future. There are a lot of older telescopes of this size around the world, and the costs (in person time) to keep them running are high. If they are robotic, one person can oversee many telescopes. I think that we will see more and more networks of robotic telescopes all around the world doing lots of exciting science.


Research

THBS2 as a Candidate Modifier of Liver Disease Severity in Alagille Syndrome James Nassura, Dr. Nancy Spinnerb, Dr. Mia Levinec a Department of Pathology and Laboratory Medicine, Children’s Hospital of Philadelphia b Department of Pathology and Laboratory Medicine c Department of Biology, University of Pennsylvania

Abstract: Alagille syndrome is an autosomal dominant disease caused by mutations in either JAGGED1(JAG1) or NOTCH2, which are both genes that code for members of the Notch signaling pathway. Alagille syndrome exhibits a liver phenotype (too few bile ducts resulting in lack of bile flow and resulting liver damage), which ranges from mild to severe in different patients. Previous work in our laboratory identified the gene THROMBOSPONDIN2 (THBS2) as a candidate modifier of liver disease severity in patients with Alagille syndrome who also have a JAG1 mutation, with subsequent follow-up suggesting that this effect is likely due to THBS2 overexpression. The goal of this project is to use zebrafish as an animal model to observe the effects of THBS2 overexpression in fish with jagged gene mutations, which exhibit features of Alagille syndrome. We examined RNA extracted from mutant zebrafish with jagged mutations and overexpression of THBS2, to analyze expression of downstream Notch signaling genes (hey1 and hnf4γ) using droplet digital PCR. Additionally, we analyzed the expression of hey1 and hnf4γ in zebrafish raised in N-[N-(3,5-difluorophenacetyl)- L-alanyl]-S-phenylglycine t-butyl ester (DAPT), a chemical that inhibits Notch signaling similarly to jagged gene mutation, as a secondary model. Changes were observed in both genes in the jagged transgenic and DAPT models in fish with THBS2 overexpression compared to fish with either jagged mutation or DAPT treatment

Introduction: Alagille syndrome is an inherited, autosomal dominant disease that primarily impacts the liver, along with other organs. The disorder is caused by mutations within the JAGGED1 (JAG1) and NOTCH2 genes of the Notch signaling pathway.6 The interaction between JAG1 and NOTCH2 leads to proteolytic cleavage and nuclear translocation of the NOTCH2 intracellular domain, where activation of downstream target genes occurs.2 There is great interest in identifying putative genetic modifiers of ALGS that could explain the variability in severity of clinical features in Alagille Syndrome, particularly with the associated liver disease. Some individuals have very mild liver disease while others have very severe liver disease, necessitating liver transplantation. Although the genetic cause of Alagille Syndrome is known, the explanation for the widely ranging liver phenotypes (which are observed in patients with similar mutations) is yet to be determined. Post-translational processing of JAG1 and NOTCH2 proteins has been widely studied as a possible mechanism to explain variability, with particular focus on fringe genes and POGLUT1.1 Following

a genome-wide association study (GWAS) performed to compare patients with severe liver disease to patients with mild liver disease in our laboratory, a nucleotide polymorphism was located upstream of the gene THROMBOSPONDIN2 (THBS2) that is more common in people with severe liver disease, suggesting that it may function to modify the phenotype of patients with JAG1 mutations.5 The aim of this project is to study the functional role of THBS2 as a modifier of Alagille syndrome. It is hypothesized that increased levels of THBS2 are responsible for more severe liver disease in patients with Alagille Syndrome (Figure 1).

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Figure 1 Proposed Model of THBS2 as a Modifier: This figure demonstrates the hypothesis behind the role of THBS2. The leftmost figure demonstrates wildtype NOTCH signaling, where JAG1 and NOTCH2 interact, leading to development of normal bile duts in the live. In the middle, mutation in JAG1 causes less interaction of JAG1 and NOTCH2 with a decrease in bile ducts in the liver. In the image on the right, THBS2 prevents even more JAG1 and NOTCH2 from interacting, resulting in even fewer bile ducts and presumably a more severe phenotype.

Materials & Methods: (1) Transgenic Animal Model Zebrafish were used as a model to test whether increased levels of THBS2 induce a stronger liver disease phenotype given the ease in identifying a liver phenotype (Figure 2). The first step in creating desired zebrafish lines was to reduce Notch signaling in fish using jag mutant strains. Due to a partial whole-genome duplication after teleost-mammalian divergence, multiple Jagged genes exist in zebrafish. Previous knockdown of jag1b and jag2b by morpholino oligonucleotides showed biliary developmental defects, and genetic deletion of these two genes completely eliminates intrahepatic bile duct development.4,7 Two lines of wildtype zebrafish, AB and TLF, along with two mutant lines jag1bla018582 (jag1b) and jag2bsa13408 (jag2b) were obtained. In-crosses and outcrosses of these mutants have also been made in order to observe which genotypes produce an observable mild biliary phenotype. Following creation and stabilization of these lines, transgenic constructs encoding human THBS2 were injected into the mutant lines to overexpress THBS2 in jagged-deficient zebrafish.

Figure 2 Liver Phenotype of Zebrafish with Muttion in NOL11: This figure demonstrates the morphology of a normal zebrafish embryo, showing the prominent liver (arrow) at 6 days of age (top), and a zerafish with a NOL11 mutation at the same age. NOL11 (a component of the human ribosomal small subunit), is implicated in another form of liver disease in humans (North American Indian Childhoood Cirrhosis). Note that the mutant fish has a clearly malformed liver.

(2) DAPT Animal Model N-[N-(3,5-difluorophenacetyl)- L-al34 PENNSCIENCE JOURNAL | spring 2019

anyl]-S-phenylglycine t-butyl ester (DAPT) is a pharmacological inhibitor of gamma secretase in the Notch signaling pathway. Inhibition of gamma secretase will mimic the effect of jagged mutation in zebrafish by preventing NOTCH2 protein cleavage and translocation of the intracellular domain, and will be used as a secondary model in this study. Bile duct morphogenesis is completed in zebrafish at 48 hours post-fertilization (hpf). Usage of 50µM DAPT at various time points has demonstrated ideal ranges of application throughout development. DAPT treatment at 24 hpf induces severe developmental defects and delays in zebrafish, preventing ability to study liver morphology within embryos; therefore, we performed treatment at later stages. Upon DAPT treatment, biliary development appears to cease, and once removed, biliary development is reinitiated, regardless of time point. DAPT proves to exhibit a potent effect on both the intrahepatic system and canalicular development.3 Through serial dilution with DMSO and E3 media, DAPT will be diluted to 50µM (concentration used in Lorent, 2010) and 25µM, optimizing a concentration that minimizes death and causes mild biliary damage. For the purposes of experimentation here, 4 samples will be run concurrently: Control E3 Media, Control E3 Media with DMSO, E3 Media with DMSO and 25µM DAPT, and E3 Media with DMSO and 50µM DAPT. (3) RNA Extractions Mutant and control zebrafish were prepared for RNA extraction after 5 days post fertilization (dpf) in E3 embryo medium. Fish were anesthetized using tricaine/MS-222 (4mg/mL); tricaine is added until movement ceases. Fish were homogenized with an insulin needle using the NucleoSpin RNA, which avoids the use of TRIzol/chloroform, and instead lyses cells with Buffer RA1 and Beta-mercaptoethanol. RNA is captured using a spin column after ethanol precipitation. Salt is removed using Membrane Desalting Buffer, and DNA is digested with DNase. Finally, the sample undergoes several wash steps in order to purify the RNA. All RNA extractions were performed using a single embryo. RNA was extracted from wildtype, heterozygous, and homozygous mutant embryos at 5 dpf. The embryos were genotyped through tail clippings using a razor blade in sets of 96 well-plates. Once tails were clipped, optimization of storage of embryos was crucial in order to ensure that RNA within the embryos was still viable before extraction. The key to this process is to prevent RNA degradation as


much as possible by flash-freezing using dry ice and ethanol. (4) cDNA Creation & Droplet Digital PCR cDNA was created from RNA prepared from the control and mutant zebrafish using Taqman Reverse Transcriptase. Following cDNA creation, droplet digital PCR (ddPCR) was used to measure the expression levels of certain genes within a sample through the use of gene specific-probes. ddPCR involves a water-oil emulsion droplet system, creating 20,000 droplets from one sample, each of which includes DNA template strands. Each DNA template undergoes PCR amplification within its corresponding droplet. The QX200 Droplet Reader then uses a two-color detection system in order to observe each droplet as either being labeled with the FAM fluorophore (the gene of interest) or the VIC fluorophore (the reference gene). Fluorescent observation allows for the ability to determine positive and negative samples. Positive droplets indicate presence of at least one target DNA by emitting greater fluorescence. As a result, four combinations can arise (positive for both VIC and FAM, positive for only one of the two genes, or two negatives). For the experiment, probes of two genes downstream of Jagged-Notch interactions in the Notch signaling pathway were used: HAIRY/ENHANCER OF SPLIT RELATED WITH YRPW MOTIF 1(HEY1), an effector required for cardiovascular development, and HEPATOCYTE NUCLEAR FACTOR 4-GAMMA(HNF4γ), a transcriptional factor. These genes are used in order to examine effects on expression in the various mutant fish strains. Genes downstream of the Notch signaling pathway are needed since the expression of these genes will be impacted if the Notch signaling pathway is not functioning correctly. These genes in particular were selected so changes in regulation would be prevalent (as one is up-regulated, HEY1, and the other is down-regulated, HNF4γ, in wildtype zebrafish). TATA-BOX BINDING PROTEIN (TBP), which serves as a general transcription factor, and is not expected to be affected by changes with Notch signaling, was used as a reference gene.

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There is a decrease in expression of hey1 in homozygote mutants relative to the control wildtype sample. Further, there was an increase in expression of hnf4γ in both the heterozygote and homozygote mutants relative to the control wildtype samples.

Figure 3 Expression Analysis of hey1 and hnf4γ in jag2b Mutants: This figure demonstrates the change in expression levels observed for jag2b heterozygous and homozygous mutations. Homozygous mutation in jag2b results in a decrease in hey1 expression, while both heterozygous and homozygous mutations result in an increase in hnf4γ expression.

(2) jag2b Mutant/THBS2 fish RNA was extracted from 6 samples each of wildtype and heterozygous zebrafish of mutant jag2b overexpressing THBS2 (THBS2/jag2b WT and THBS2/jag2b Het). cDNA from these samples were created, and hey1 and hnf4γ gene expression was analyzed using ddPCR. There is a statistically significant decrease in expression of hey1 in heterozygous mutants relative to the wildtype samples. Conversely, there was an increase in expression of hnf4γ in heterozygous samples relative to the wildtype samples. With the removal of one outlier sample, this difference proves to be statistically significant.

Results: (1) jag2b Mutant Fish RNA was extracted from 6 samples each of wildtype, heterozygous, and homozygous zebrafish of mutant jag2b. cDNA from these samples were created, and hey1 and hnf4γ gene expression was analyzed using ddPCR.

Figure 4 Expression Analysis of hey1 and hnf4γ in jag2b Mutants overexpressing THBS2: This figure demonstrates the change in expression levels observed for jag2b mutant s with overexpression of THBS2. jag2b heterozygous mutation with THBS2 overexpression results in a decrease in hey1 expression and an increase in hnf4γ expression relative to the wildtype control.

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(3) DAPT RNA was extracted from zebrafish raised in four types of media (Control E3 Media, Control E3 Media with DMSO, E3 Media with DMSO and 25µM DAPT, and E3 Media with DMSO and 50µM DAPT). cDNA from these samples was created, and hey1 and hnf4γ gene expression was analyzed using ddPCR. There is a large decrease in expression of hey1 in zebrafish raised in E3 Media with DMSO and 25 µM DAPT relative to both control samples. An increase in expression was observed with an increase in DAPT concentration to 50M. Additionally, there is a large increase in expression of hnf4γ in zebrafish raised in E3 Media with DMSO and 25µM DAPT and 50 µM DAPT relative to the DMSO control sample.

Figure 5 Expression Analysis of hey1 and hnf4γ in DAPT Samples: This figure demonstrates the change in expression levels observed for wildtype fish raised in increasing concentrations of DAPT. E3 and E3 + DMSO serve as control samples. 25µM DAPT results in a decrease in hey1 expression, while both 25µM and 50µM result in an increase in hnf4γ expression.

Discussion: In this study, we sought to understand the role of Thrombospondin 2 in the variable expressivity of the Alagille syndrome associated liver disease, in a zebrafish model of Alagille syndrome. Based on previous work, we hypothesized that THBS2 has a direct effect on NOTCH signaling, and therefore overexpression of NOTCH2 would worsen the liver defects in fish with jagged mutations jag1bla018582 (jag1b) and jag2bsa13408 (jag2b). We investigated the effect of overexpression of THBS2 in zebrafish heterozygous and homozygous for jag2b mutations, and we further tested the role of NOTCH signaling levels in wildtype fish using DAPT, a potent inhibitor of Notch signaling. (1) jag2b Mutant Fish 36 PENNSCIENCE JOURNAL | spring 2019

We hypothesized that heterozygous and homozygous mutations within the jag2b gene of zebrafish would result in limiting Notch signaling. To test this hypothesis, we studied the effect of Notch signaling in fish with WT, heterozygous jag2b mutation, or homozygous jag2b mutation (jag2b WT, jag2b het, and jag2b homo, respectively). We found a decrease in hey1 expression in jag2b homo samples compared to jag2b WT (control) and jag2b het. This makes sense, as hey1 is normally upregulated in wildtype zebrafish. On the other hand, hnf4γ does not observe as clear of a trend. We would expect hnf4γ to increase in zebrafish with a jagged mutation, as hnf4γ is normally down-regulated in wildtype zebrafish. In our results, an increase is only observed from jag2b WT to jag2b het. Further, results proved to not produce any statistically significant differences for both genes. Currently, we believe that we are observing a subtle change in notch signaling in this model. In order to observe a stronger trend, we likely have not hit a threshold for hnf4γ or lack in mutation or the other jag allele is compensating for the effect. (2) jag2b Mutant/THBS2 fish We hypothesized that THBS2 overexpression in a background of jagged gene deficiency, result in a more severe liver phenotype. To begin to test this hypothesis, we looked at the effect on Notch signaling in fish with either WT or heterozygous jag2b mutations and THBS2 overexpression (THBS2/jag2b WT and THBS2/jag2b het, respectively). We found a statistically significant decrease in hey1 expression in THBS2/jag2b het samples relative to the control sample (THBS2/jag2b WT). This suggests that Notch signaling is further inhibited by THBS2 overexpression as hey1 is normally upregulated in wildtype zebrafish. Furthermore, we found a decrease in hnf4γ expression in THBS2/jag2b het samples relative to the control sample (THBS2/ jag2b WT). Again, this suggests that Notch signaling is further inhibited by THBS2 overexpression as hnf4γ is normally down-regulated in wildtype zebrafish. Although not statistically significant, these data contained an outlier, which, when removed, resulted in statistical significance. The presence of this outlier is likely to be explained through the individuality of zebrafish samples and signals to us the importance of increasing our biological replicates. Since each sample is solely comprised of one zebrafish, variability in degree of inhibition of jag2b and expression of downstream genes is expected. (3) DAPT


DAPT is a model of Notch signaling dysfunction, and our ultimate aim is to optimize DAPT dosing conditions so that we can effectively use it as a positive control for our transgenic zebrafish experiments with jagged and THBS2. As a preliminary test, we looked at gene expression of hey1, which is normally upregulated in Notch signaling, and hnf4γ, which is normally downregulated in Notch signaling, to determine the efficacy of our DAPT treatments. Decrease in expression for both hey1 and hnf4γ were observed in the transition from E3 media samples to E3 Media + DMSO; this change was anticipated, as we expected DMSO to introduce some toxicity to the samples. We found a decrease in hey1 expression in jag2b WT fish treated with 25µM DAPT relative to both the E3 Media and E3 Media + DMSO controls. Likewise, we found an increase in hnf4γ expression in jag2b WT fish treated with both 25µM DAPT and 50 µM DAPT relative to the E3 Media + DMSO control. However, we also saw that 50µM DAPT lead to an increase in HEY1 expression. This demonstrates the possibility that adding a concentration of 50µM DAPT may be too potent for the fish. With a concrete foundation of the impact of THBS2 on notch signaling, we anticipate multiple future experiments. For one, we hope to analyze downstream expression with and without THBS2 overexpression in fish with heterozygote mutations in both jag1b and jag2b. This will demonstrate impact on Notch signaling without residual effect from the opposite jag gene. Further, to decrease error bars for jag2b samples, we aim to create RNA and cDNA for samples in the same run in an effort to standardize all methods. Finally, we would like to include analysis of 2 more downstream genes, ccnd1 and hnf4α, to strengthen our conclusions on the impact of jag mutation and THBS2 overexpression on the notch signaling pathway. Author Contributions:

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detailed instruction and aid through the Nucleospin RNA extraction. Dr. B. Wilkins provided the image of the NOL11 zebrafish mutation and a detailed description of generation of zebrafish mutant lines. Dr. B. Wilkins and Dr. C. Seiler raised all zebrafish lines and injected THBS2 to elicit overexpression in the mutant lines. Their research technicians, A. Abdalla and S. Bessho, collected samples for the RNA extractions as needed and genotyped all 5 day old embryos as they came about. Dr. Spinner discussed and edited the paper. References: 1. Gilbert, M. A., & Spinner, N. B. (2017). Alagille syndrome: Genetics and Functional Models. Current Pathobiology Reports, 5(3), 233–241. https://doi.org/10.1007/s40139-017-0144-8 2. Grochowski, C. M., Loomes, K. M., & Spinner, N. B. (2016). Jagged1 (JAG1): Structure, Expression, and Disease Associations. Gene, 576(1 0 3), 381–384. http://doi.org/10.1016/j.gene.2015.10.065 3. Lorent, K., Moore, J. C., Siekmann, A. F., Lawson, N. and Pack, M. (2010). Reiterative use of the notch signal during zebrafish intrahepatic biliary development. Developmental Dynamics, 23, 855-864. http://doi.org/10.1002/dvdy.22220 4. Lorent, K., Yeo SY, Oda T, Chandrasekharappa S, Chitnis A, Matthews RP, et al. (2004). Inhibition of Jagged-mediated Notch signaling disrupts zebrafish biliary development and generates multi-organ defects compatible with an Alagille syndrome phenocopy. Development, 131(22), 5753-5766. http://doi.org/10.1242/dev.01411 5. Penton, A. L., Leonard, L. D., & Spinner, N. B. (2012). Notch signaling in human development and disease. Seminars in Cell & Developmental Biology, 23(4), 450–457. http://doi.org/10.1016/j. semcdb.2012.01.010 6. Tsai, E. A., Gilbert, M. A., Grochowski, C. M., Underkoffler, L. A., Meng, H., Zhang, X., … Loomes, K. M. (2016). THBS2 Is a Candidate Modifier of Liver Disease Severity in Alagille Syndrome. Cellular and Molecular Gastroenterology and Hepatology, 2(5), 663–675.e2. http://doi.org/10.1016/j.jcmgh.2016.05.013 7. Zhang, D., Gates, K. P., Barske, L., Wang, G., Lancman, J. J., Zeng, X.-X. I., … Dong, P. D. S. (2017). Endoderm Jagged induces liver and pancreas duct lineage in zebrafish. Nature Communications, 8, 769. http://doi.org/10.1038/s41467-017-00666-6

The author, James Nassur, completed the majority of the data collection for this project. Dr. M. Gilbert advised me on all methodology used, from RNA extraction to appropriate experimental runs for expression analysis. Dr. M. Gilbert further reviewed all data collected through statistical software to examine significance. Debbie McEldrew completed the ddPCR optimization of probes and contributed to completion of all ddPCR reactions. S. Fiordaliso provided control cDNA samples to be used as comparison in my ddPCR run and provided spring 2019 | PENNSCIENCE JOURNAL 37


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Establishing a Laboratory Infection Model for Dirofilaria Immitis in the Vector Mosquito Aedes Albopictus Fiona O’Neilla, Abigail McCreaa, Sarah Sneeda, Michael Povelonesa, Dr. Michael Povelonesb, Dr. Paul Sniegowskic a Department of Pathobiology, University of Pennsylvania School of Veterinary Medicine b Department of Pathobiology, School of Veterinary Medicine c Department of Biology, University of Pennsylvania

Abstract: Drug resistance is increasingly reported for the canine parasite Dirofilaria immitis, commonly known as heartworm, potentially rendering all currently available preventive heartworm treatments ineffective. Therefore, development of additional methodologies to combat heartworm transmission are needed. In addition to infection of canine hosts, D. immitis also requires a mosquito vector to complete its lifecycle thus providing an additional opportunity to block transmission. This work investigates the interplay between the mosquito immune system and D. immitis. A previous study in the Povelones laboratory showed that overactivation of the Toll immune pathway via RNAi-mediated silencing of the pathway inhibitor Cactus results in increased expression of immune genes and developmental arrest of D. immitis in, Aedes aegypti, a laboratory strain of mosquito used to develop the heartworm infection model. Given that Ae. aegypti is not a natural vector of importance for D. immitis, the aims of this study are to first develop a D. immitis infection model for Aedes albopictus and then to determine their susceptibility at baseline and in the context of Toll pathway overactivation. Although Ae. albopictus is generally regarded as a competent D. immitis vector in the field, the susceptibility of the laboratory Ae. albopictus strains is unknown. We obtained two widely used strains originally colonized in New Jersey and Florida. Our results suggest that while both strains were competent vectors for heartworm, as they both support development of canine infective transmission-stage parasites, there are significant differences in their susceptibility. Other aspects of the strains, such as fitness and culture conditions, were also evaluated for suitability for future gene silencing experiments. Our data suggests that of the two

Introduction: Dirofilaria immitis, the causative agent of of Dirofilariasis, commonly known as feline and canine heartworm, is transmitted by mosquitoes which serve as the intermediate host. While dogs are the site of terminal adult worm growth as well as sexual reproduction, the mosquito is the site of juvenile development. During a blood meal on an infected animal, the mosquito ingests microfilariae– which are small, motile worm eggs – that immediately migrate to the Malpighian tubules (the insect renal organ) of the mosquito (Figure 1). It takes approximately two weeks in the Malpighian tubules of the mosquito for D. immitis to develop into transmission-stage infectious L3 larvae. Upon maturation, 38 PENNSCIENCE JOURNAL | spring 2019

the L3 larvae rupture the cells of the Malpighian tubules and migrate through the hemolymph (mosquito blood) and reside in the proboscis of the mosquito. When the mosquito lands on the skin of a canid to take another blood meal the heat from the skin of the animal signals the transmission-stage larvae to emerge from the proboscis where they are deposited on the skin and enter the host through the bite site. In the subcutaneous tissue of the host, the L3 larva molts into an L4. Months later, the L4 larva migrates to pulmonary arteries and molts to a young adult. In the pulmonary arteries females and males mate leading to the production of microfilariae in the blood around 6 months after the initial infection. Currently, there is no vaccine for heartworm disease although preventative macrocyclic lactones provide effective chemoprophylaxis, there are significant animal


reservoirs that are not possible to treat. More concerning, there is strong evidence for quickly emerging drug resistance to these preventative drugs.1,2 Therefore, new strategies are needed to prevent the spread of heartworm disease. A method to block the development of transmission-stage L3 larvae in the mosquito has been developed through prior work in a laboratory strain of Aedes aegypti “Blackeye” that has been specifically bred for susceptibility to D. immitis infection. Briefly, injection of double stranded RNA (dsRNA) is used to genetically silence Cactus, a negative regulator of the Toll immune signaling pathway. Cactus silencing results in strong constitutive activation of the Toll pathway independent of infection. Toll activation results in increased expression of many of immune genes and significant reduction in the number of L3 emerging from infected female mosquitoes 14 days post-infection. However, natural strains of Ae. aegypti are typically refractory to infection and field studies indicate this species is not likely to play a role in D. immitis transmission. Therefore, it is unknown whether constitutive activation of Toll immune signaling would block D. immitis development in a natural heartworm vector. Previous studies have implicated Ae. albopictus as a competent vector of D. immitis.3,6 However, many mosquito species have also been shown to contribute, e.g. Anopheles crucians, Anopheles punctipennis, Aedes infirmatus, Culex nigripalpus, Psorophora ferox.3,5,7 Ae. albopictus was introduced into the USA before the 1980s and is now widespread throughout North America.9 Greater characterization of this vector species will potentially benefit human health as it is a species of significant concern since it is a vector of numerous arboviruses.

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Materials and Methods: (1) Mosquito Rearing Conditions Ae. albopictus New Jersey strain (ATM-NJ95) and Florida Gainesville strain (Gainesville) were obtained from BEI Resource. Both strains were incubated at 28 °C and approximately 85% humidity. In Povelones lab mosquito colonies are reared on 10% sucrose solution. (2) D. immitis infection Adult, six to ten-day old female mosquitoes were deprived of sugar for twenty-four hours to encourage feeding. 100-300 mosquitoes were collected from each treatment group, placed into quart-size paper cups, and covered with netting. Blood drawn by Dr. Povelones was assayed for microfilariae (mf). Freshly-drawn blood containing microfilariae was diluted to approximately 4000 mf/mL using sheep blood to dilute and fed to each group using an artificial membrane feeder for approximately 20 minutes. Unfed mosquitoes were discarded. Mosquitoes were maintained for 14-17 days after infection. Maintenance of a D. immitis infected dog and blood draw for mosquito infection is covered in an approved and ongoing IACUC protocol (#805059). (3) Mosquito dissection & Transmission Stage Emergence Assays Mosquitoes were submerged in 70% ethanol for 1 minute for both euthanization and killing of surface cuticle bacteria. They are then briefly rinsed with deionized water and placed into individual wells of a 96-well plate with 200 µL of culture medium (DMEM) ensuring their heads are entirely submerged. Plates are incubated at 37 ºC for 45 minutes. The heat signature induces emergence of L3 larvae from the submerged heads of the mosquitoes. These transmission-stage larvae are visible in the bottom of the wells and countable using an inverted light microscope. Results:

Figure 1 Life-cycle of D. immitis in the mosquito vector: After microfilariae are ingested during blood feeding, they migrate to the Malpighian tubules. Here they molt three times to produce transmission-stage infectious L3. Afterwards, transmission-stage larvae migrate to the proboscis of the mosquito where they are poised for transmission. This mosquito diagram is unpublished work of Michael Povelones.

For this study, we obtained two independent laboratory strains of Ae. albopictus to assay their ability to support the D. immitis development to the transmission stage. One strain (NJ) originated spring 2019 | PENNSCIENCE JOURNAL 39


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from Keyport, New Jersey and the other (FL) from Gainesville, Florida. In addition, susceptible Ae. aegypti Blackeye (BE) and refractory Ae. aegypti Liverpool strain (LVP) were included as positive and negative controls, respectively. (1) Aedes albopictus NJ strain is susceptible to Dirofilaria immitis infection We fed Ae. albopictus NJ strain with blood containing D. immitis microfilariae and assayed individual mosquitoes for transmission-stage larvae 14 days post infection. The number of microfilariae in the blood was set to a level that typically leads to 50% of the mosquitoes to develop transmission-stage parasites in Ae. aegypti BE. Excitingly, we found that Ae. albopictus FL supported D. immitis development to the transmission-stage. However, both the number of transmission-stage parasites (Figure 2A) and the prevalence of mosquitoes with at least one transmission-stage parasite (Figure 2B) was significantly lower compared to the positive control Ae. aegypti BE. As expected, the Ae. aegypti LVP strain did not support the development of transmission-stage parasites. We also assayed the number of mosquitoes that survived until day 14 and on average found that significantly fewer Ae. albopictus NJ strain mosquitoes survived compared to either Ae. aegypti strain (Figure 2C).

Figure 2 Transmission-stage parasites emerge from Ae. albopictus NJ strain 14 days post-infection: (A) D. immitis emerging from mosquitoes 14 days after infection. Each dot indicates the number of transmission-stage larvae emerging from individual mosquitoes. The P value is from a Kruskal-Wallis test with Dunn’s correction for multiple comparison. The number (n) of mosquitoes assayed for each group is indicated. (B) Bars show the average prevalence of individuals with at least one emerging parasite. The error bar indicates the standard deviation. The P value is from a Chi-squared test. (C) Average of the percent of mosquitoes that survived to day 14. The error bar indicates the standard deviation and the P value is from a Chi-squared test. The data for this figure are from two independent biological replicates.

(2) Aedes albopictus FL strain is susceptible to Dirofilaria immitis infection 40

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We performed a similar set of analyses on Ae. albopictus FL strain mosquitoes. Across all three experiments, we only observed four mosquitoes with one transmission-stage parasite each emerging from the Ae. albopictus FL, while the positive control had a range of 0-9 transmission-stage parasites per mosquito (Figure 3A). The prevalence of transmission-stage parasites emerging from Ae. albopictus FL was also significantly reduced compared to Ae. aegypti BE (Figure 3B). The number of transmission-stage parasites was so low that Ae. albopictus FL was not statistically different from the refractory Ae. aegypti LVP strain.

Figure 3 Transmission-stage parasites emerge from Ae. albopictus FL strain 14 days post-infection: (A) D. immitis emerging from mosquitoes after infection. Each dot indicates the number of transmission-stage larvae emerging from individual mosquitoes. The P value is from a Kruskal-Wallis test with Dunn’s correction for multiple comparison. The number (n) of mosquitoes assayed for each group is indicated. (B) Bars show the average prevalence of individuals with at least one emerging parasite. The error bar indicates the standard deviation. The P value is from a Chi-squared test. (C) Average of the percent of mosquitoes that survived to the assay date from 3 independent experiments. The error bar indicates the standard deviation. The data for this figure are from three independent biological replicates performed 14, 17, and 20 days post infection.

(3) Developmentally delayed larvae are present in Aedes albopictus FL strain Malpighian tubules It was surprising that the Ae. albopictus FL strain did not support more development of transmission-stage parasites. In refractory mosquitoes, parasites migrating to in Malpighian do not develop past the microfilaria stage. To determine at what stage Ae. albopictus FL are defective, mosquito Malpighian tubules were dissected 5 and 17 days post infection. Compared to aged matched Ae. aegypti BE mosquitoes, Ae. albopictus FL were observed to be delayed in their development (Figure 4). Though they clearly had developed beyond the microfilariae stage, at day 5, the parasites in Ae. albopictus FL were still elongated and retained some of the characteristics of microfilariae (Figure 4A). In contrast, Ae. aegypti BE were uniformly 4C-D). In addition, many developmentally arrested sausage form parasites are present, indicating they are dead or severely developmentally delayed (Figure 4C). shortened and almost all present as “sausage form” developing larvae (Figure 4B). At day 17, a time when Ae. aegypti BE transmission-stage parasites robustly emerge from the BE strain, Ae.


albopictus FL are markedly shorter (Figure 4C-D). In addition, many developmentally arrested sausage form parasites are present, indicating they are dead or severely developmentally delayed (Figure 4C).

Figure 4 Photomicrographs of the dissected Malpighian tubules of FL strain Aedes albopictus and BE strain Aedes aegypti: (A) Day 5 development stage of D. immitis larvae in FL strain. Worms displaying similar characteristics of microfilaria. These worms are long and slender with remnants of the microfilaria tail. (B) Day 5 development stage of D. immitis in BE strain showing shortened, “sausage-like” worms. (C) Day 17 development of worms in FL strain. In the upper Malpighian tubule one elongated worm is observed and two sausage-like worms in the lower tubule. (D) showing two worms in the BE Malpighian tubules of BE strain in the L3 transmission-stage. Scale bar in A and B is 50 µm. Panels C and D were taken on a different microscope at the same magnification (10x) due to technical reasons.

Discussion: This study focused on developing laboratory procedures for investigating Ae. albopictus susceptibility to D. immitis infection. Our results suggest that both the NJ and FL strains of Ae. albopictus are susceptible to D. immitis. However, both the worm emergence per mosquito and prevalence of mosquitoes with worms emerging was higher in the NJ strain than the FL strain, suggesting that the NJ strain better supports the development of D. immitis and therefore has greater vectorial than the FL strain. In order to determine which strain is the best model to use going forward to investigate the immune system of Ae. albopictus, the emergence results from both strains yield important considerations. The low emergence numbers for the FL strain makes it difficult to use going forward for the Cactus RNAi-mediated silencing and Toll activation. Determining an effect of the gene-silencing may be problematic because the baseline emergence number is low. Alternatively, the NJ strain had high emergence numbers but additionally had high mortality rate after the infectious blood meal with only 43% of the mosquitoes surviving to 14 days, compared to the 67% of surviving FL strain mosquitoes. The difference in survival suggests that the NJ strain is

RESEARCH

less fit compared to the FL strain. Furthermore, observational logs noted the general flight activity and sugar feeding of the NJ strain was lower compared to other colonies in the insectary, including the FL strain. A large number of mosquitoes died in the NJ colony cages prior to experiments, demonstrating that the survival effect is likely independent of blood feeding. The standard protocol for D. immitis emergence assays is to collect only engorged mosquitoes. However, the NJ strain did not robustly blood feed to satiation. In many of our experiments with the NJ strain, partially blood fed mosquitoes were also assayed. The amount of blood taken in a blood meal directly correlates to parasite exposure, so it is possible that underfeeding lowered the overall prevalence and parasite emergence in the NJ strain. Under ideal rearing and blood feeding conditions it is possible that the NJ strain of Ae. albopictus could be as competent a vector as Ae. aegypti BE. This was the first attempt to culture Ae. albopictus in the Povelones lab at the University of Pennsylvania. Due to space restrictions in the incubators, the NJ strain was reared in laboratory conditions known to be suboptimal at 28°C and 85% humidity while the known ideal conditions are 24°C and 70% humidity. The microscopy images of Malpighian tubules suggest that the parasites in the FL strain are developmentally delayed. At day 5 of development the worms in the Malpighian tubules of BE develop into the stunted, sausage-like form (Fig. 4B). However, the FL strain parasites were still in the thin and elongated form. By day 17 the parasites in the BE strain undergo another molt back into the elongated, slender phenotype. This is the typical phenotype of transmission-stage L3s. Unlike the parasites in BE, most of the parasites detected in the FL strain were still in the stunted form at day 17. The microscopy images prove susceptibility in the FL strain, but the low number of emerging worms suggests there is an unknown factor that is preventing the development of L3s. While the NJ strain did not robustly blood feed and had lower fitness compared to the FL strain, more emerging L3s were observed on day 14. In future experiments the fitness of the NJ strain will be optimized through rigorous management of larvae and rearing at standard conditions. Our respring 2019 | PENNSCIENCE JOURNAL

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sults thus far suggest that if the culture system can be improved and the overall health of the mosquitoes increased, then the NJ strain is a better strain for future RNAi experiments to investigate the Ae. albopictus immune system.

Acknowledgements: I would like to extend my sincere appreciation to Dr. Povelones and Dr. Sniegowski for this incredible opportunity. I would also like to thank our laboratory technician, Abigail McCrea, who helps rear and maintain the mosquito colonies. Without Abigail’s contribution to the experimental procedures this paper would not have been possible.

References: 1. Bouruiant C., Bhan, A., Peregrine, A., Geary T., Prichard, R. (2011). Macrocyclic lactone resistance in Dirofilaria immitis. Veterinary parasitology, 182, 380-38. doi: 10.1016/j.vetpar.2011.06.008 2. Lespine, A., Martin, S., Dupuy, J., Roulet, A., Pineau, T., Orlowski, S., Alvinerie, M. (2006). Interaction of macrocyclic lactones with P-glycoprotein: Structure-affinity relationship. European journal of pharmaceutical science, 30, 84-94. https://doi.org/10.1016/j.ejps.2006.10.004 3. Lictira, B., Chambers, E. W., Kelly, R. and Burkot T. (2010). Detection of Dirofilaria immitis (Nematoda Filarioidea) by polymerase chain reaction in Aedes albopictus, Anopheles punctipennis, and Anopheles crucians (Diptera:Culicidae) from Georgia, U.S.A. Journal of medical entomology, 47, 634-638. 4. Marcombe, S., Farajollahi, A., Healy SP, Clark, GG, Fonseca, DM. (2014). Insecticide resistance status of United States populations of Aedes albopictus and mechanisms involved. PLoS ONE 9(7): e101992. https://doi.org/10.1371/journal.pone.0101992 5. Montarsi, F., Ciocchetta S., Devine, G., Ravagnan, S, Mutinelli, F., Regalbono, A., Otranto, D., and Capelli, G. “Development of Dirofilaria Immitis within the Mosquito Aedes (Finlaya) koreicus, a New Invasive Species for Europe.” Parasites & Vectors 8 (2015): 177. PMC. Web. 10 Oct. 2018. 6. Nayar, J K, and Knight, J W. (1999). Aedes albopictus (Diptera: Culicidae): An experimental and natural host of Dirofilaria immitis (Filarioidea: Onchocercidae) in Florida, U.S.A. Journal of medical entomology. 36.4, 441–448. https://doi.org/10.1093/jmedent/36.4.441. 7. Paras K., O’Brein V., Reiskind M. (2014). Comparison of the vector potential of different mosquito species for the transmission of heartworm, Dirofilaria immitis, in rural and urban areas in and surrounding Stillwater, Oklahoma, U.S.A. Medical and veterinary entomology, 28, 60-67. 8. Portman, N. & Gull, K. (2010). The paraflagellar rod of kinetoplastid parasites: from structure to components and function. doi: 10.1016/j. ijpara.2009.10.005. 9. Sprenger, D. and T. Wuithiranyagool. (1986). The discovery and distribution of Aedes albopictus in Harris County, Texas. Journal of American Mosquito Control Association, 2, 217-219.

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