Volume 16 • Issue 1 • Fall 2017 Nanomedicine Can nanoparticles make for more efficient drug delivery? CAR-T Therapy How modiied antibodies function in the ght against cancer Neural Engineering Using neuroscience and engineering to answer our questions about the brain Lab on a Chip The answer to the inefficiency of liquid sample testing Nanocomputers From 30 tons to 14 nanometers - how nanocomputers are being engineered Nanocars How nanoparticles took over the eld of motorized racing
The Nanoscale
PennScience Fall 2017 Volume 16 Issue 1
PennScience is a peer-reviewed journal of undergraduate research 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 sciences, and computer sciences. 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 EDITORS-IN-CHIEF Alex Wong Richard Diurba WRITING MANAGERS Ritwik Bhatia Mia Fatuzzo EDITING MANAGERS Aaron Zhang Rachel Levinson DESIGN MANAGERS Chigoziri Konkwo Abi Szabo BUSINESS MANAGERS Jici Wang Donna Yoo TECHNOLOGY MANAGER Rounak Gokhale FACULTY ADVISORS Dr. M. Krimo Bokreta Dr. Jorge Santiago-Aviles
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WRITING
EDITING
DESIGN
BUSINESS
Hiab Teshome Rosie Nagele Eric Teichner Xufei Huang Darsh Shah Roshni Kailar Tamsyn Brann Kenny Hoang Neelu Paleti Amanda Paredes
Sarah Fendrich Sapna Nath Karbi Choudhury Roshan Benefo Nikita Maheshwari Brian Zhong Kathleen Wang Lily Zekavat Valerie Aksianiuk Aditya Rao Sumant Shringari Kelly Liang Billy Hasley
Alison Weiss Grace Wu Olivia Myer Roshan Benefo Abhi Motgi Samuel Xu Lauren Kleidermacher
Rekha Vegesna Christopher Nicholson Justin Lish Catherine Ruan Nicholas Yang
PENNSCIENCE JOURNAL | FALL 2017
Table of Contents
Features Nanomedicine
by Eric Teichner, design by Chigizori Konkwo - Page 6
CAR-T Therapy
by Rosie Nagele, design by Grace Wu - Page 8
Neural Engineering
by Hiab Teshome, design by Lauren Kleidermacher - Page 10
Lab on a Chip
by Neellu Paleti, design by Roshan Benefo - Page 12
Nanocomputers
by Xufei Huang , design by Alison Weiss - Page 14
Nanocars
by Kenny Hoang, design by Abhi Motgi - Page 16
Genotoxicity and Cytotoxicity
by Amanda Paredes, design by Samuel Xu - Page 18
Research Effects of Anthropogenic Acoustic Interference on Female Response to Male Calls in the Strawberry Poison Frog (Oophaga pumilio) by Reena Debray and Nicole Oppenheim Page 26
Characterizing Backscatter Variability Using UAVSAR
by Abigail Lee Page 34
Interview
Professor Charlie Johnson by Darsh Shah Page 24
Features The Practical Applications of Nanotechnology by Tamsyn Brann, design by Olivia Myer - Page 20
Fighting Climate Change
by Roshni Kailar, design by Abi Szabo - Page 22 3
LETTER FROM THE EDITORS Dear Reader, It is hard to believe that another semester has reached its completion and another journal of PennScience has been produced. We would first and foremost like to thank the persistent work and tireless hours put into this journal by our members and co-managers. As Editor-in-Chiefs, it astounds us as to how well our members continue chugging through the publication process. From the editors’ keen attention to detail to the writers’ uncanny ability to breathe life into today’s key scientific issues, we have continued to push ourselves to become better. Our business and design staff has also produced and fashioned our best issue yet, putting in hard work translating our journal into the magazine you are holding in your fingertips. This issue marks the second iteration of a growing theme our previous issues started: an ambitious effort to appreciate and nurture the interdisciplinary nature of scientific inquiry. In this spirit, this semester’s theme of nanotechnology hopes to investigate underlying scientific phenomena involving the very small. From nanomedicine to nanocomputers, our issue’s unprecedented number of feature articles, contrary to its subject matter’s size, actually showcases the complexity of science at its heart. In particular, we think Rosie Nagele’s article on CAR-T cell research and Kenny Hoang’s article on nanocars will be of your interest, as they tie into current events in immunotherapy and nanocar racing, respectively. We also conducted an interview with Penn’s Director of Nano/Bio Interface Center, Professor A.T. Charlie Johnson of Physics and Astronomy. He offers insights on his research on graphene and on how he sees undergraduate researchers in the Penn community. Within the club itself, we also saw our first ever student panel featuring PennScience’s very own members’ budding research. Brian Zhong (Editing), Aaron Zhang (Editing), Susan Zhao, Ethan Fine, and Charles Hussey discussed research topics ranging from robotics to proteins/RNAs to neuroscience. Our upcoming coffee chat by Dr. Mark Goulian, Charles and William L. Day Distinguished Professor in the Natural Sciences, also exemplifies PennScience’s growing interest in scientific issues spanning various fields and arenas. As Richie moves on to graduate school and Alex continues his junior year, we collectively wish the best for PennScience and know that the journal is in good hands with next semester’s Editor-in-Chiefs, Grace Ragi and Mia Fatuzzo. We would like to thank the club for such an exceptional journal and hope that you enjoy reading it as much as we enjoyed managing its creation. Best, Alex Wong (C’19) and Richard Diurba (C’18) Editors-in-Chief
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PENNSCIENCE JOURNAL | FALL 2017
CALL FOR SUBMISSIONS Looking for a chance to publish your research? PennScience is accepting submissions for our upcoming Spring 2018 issue!
Research in any scientific field will be considered, including but not limited to:
Biochemistry Biological Sciences Biotechnology Chemistry Computer Science Engineering Geology Mathematics Medicine Physics Psychology
Submit your independent study projects, senior design projects, reviews, and other original research articles to share your work with fellow undergraduates at Penn and beyond. Email submissions and any questions to pennscience@gmail.com
PREVIOUS ISSUES Visit the PennScience website
www.pennscience.org
to see previous issues and for more information. Volume 15 • Issue 2 • Spring 2017
Radiation & Technology
Volume 15 • Issue 1 • Fall 2016
Volume 14 Issue 2 Spring 2016
SYNTHETIC BIOLOGY
Galactic Cosmic Radiation
A look into the future of space travel and exploration.
Thinking with your stomach Nerve interactions with the gut microbiome
The good bacteria How antibiotics might be harming us
Gravitational Waves Understanding ripples in the space-time continuum.
The Evolution of Medical Imaging The past, present, and future of seeing the human body.
The Evils of Radiotherapy The real risk of exposure to radiation.
Solar Technology
Penn professors explore new materials for more efficient solar power.
Spring 2017
Environment
Will synthetic biology be the solution to pollution?
CRISPR
A look into the future of genomic editing and disease
Metabolism
Reprogramming metabolism in the cell
Fall 2016
Insulin
How it revolutionized what was once a death sentence
Spring 2016 FALL 2017 | PENNSCIENCE JOURNAL
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FEATURES
NANOPARTICLES AND DRUG DELIVERY A SYSTEMATIC REVIEW
Chemotherapy is often a miserable experience, resulting in hair loss, vomiting, and extreme fatigue. Cancer doesn’t discriminate, and neither do the chemotherapy drugs used to treat this disease. Yet, this soon may change – what if we could target the tumor without affecting the healthy cells of the patient? Nanotechnology has already shown highly promising advancements, specifically in the realm of drug delivery.
By Eric Teichner
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PENNSCIENCE JOURNAL | FALL 2017
FEATURES Nanomedicine, as defined by the National Institutes of Health (NIH), refers to specific molecular interventions for the treatment of medical issues, ranging from cancer to heart disease.1 In the field of drug delivery, particles are specifically engineered to optimize the distribution of therapeutic substances to designated cell populations. This allows for increasingly specific delivery of substances and improved bioavailability of poorly soluble drugs. In order to be effective in drug delivery, these materials must be able to either integrate the drug inside the particle or attach the drug to its surface. These nanoparticles used in drug delivery are typically less than 100 nm in diameter and consist of various biodegradable materials, including synthetic polymers, lipids, or metals.2 The nanoparticle’s small size allows it to easily cross in and out of capillaries in the bloodstream in search of “leaky vessels” often found in cancerous tumors. This is significant because unlike healthy tissue, cancerous cells often lack proper drainage systems. In the future, these nanoparticles will be the foundation for treating disease.3 Nanomedicine offers the possibility of utilizing pharmaceuticals in a highly specific mode of action, loading nanoparticles with drugs and successfully delivering them in an efficient manner. However, researchers still have a long way to go. It has
‘‘The nanoparticle’s small size allows it to easily cross in and out of capillaries in the bloodstream in search of “leaky vessels” often found in cancerous tumors.’’ been recently determined that only 0.7% percent of injected nanoparticles actually reach the tumor.4 In order to achieve therapeutic efficacy, it is expected that this number should be close to 10%.5 Furthermore, in 1995, the FDA first approved the nanoparticle-based chemotherapy drug, Doxil, which encloses the drug doxorubicin in a lipid sphere called a liposome. Here, nanoparticle usage allows for direct delivery of this cancer fighting substance to the tumor of interest, helping to reduce, but not eliminate toxicity to the patient. Often, nanoparticles are used in the improvement of targeted drug delivery and specificity of poorly soluble drugs. Dexamethasone (DEX) is a steroid used to relieve inflammation, specifically in patients with tumors of the spine and brain. It is typically given along with other chemotherapy agents. Dexamethasone has been synthesized with nanomaterials, such as polylactic acid (PLA) nanoparticles, in order to enhance its specificity. The PLA nanoparticle complex binds to the cytoplasmic surface of a cancerous cell and is transported to the nucleus of that cell, resulting in the expression of genes that control cell proliferation, or rapid, uncontrolled division, which in turn helps control cancer cell populations.2 In this example, nanoparticles allow for the release of sustained doses of this drug
over a longer period of time. Recently, researchers determined that the in vitro release of DEX from DEX-NPs lasted 5 days in artificial perilymph and 1 day in rat plasma, longer than typical DEX release.6 Other studies have shown that the DEX-NPs did not result in local inflammatory responses or damage to hair and hearing. Although currently emerging, this translational research will soon optimize treatment with DEX. Nanoparticle drug delivery is also particularly useful in the treatment of diseases other than cancer. Although this field is newer than classic nanoparticle delivery for cancer treatment, the research has shown to be promising as well. Cardiovascular disease is a major problem in the United States – it is currently the leading cause of death among both men and women. Yet, this statistic may soon change. Researchers at Clemson University are utilizing nanoparticles that deliver drugs with the ability to repair damaged arteries. Specifically, they have developed nanoparticles that have antibodies on the surface that attach to the diseased sites, a common example being the drug Paclitaxel. Nanoparticles are also being evaluated for the potential of drug delivery across the blood brain barrier. However, the potential toxicities of these particles are not yet fully known.7 More research is needed, specifically in the optimization and safety of drug delivery, in order to progress with these recent advancements. Undoubtedly, nanoparticles are the leading technology for drug delivery, changing what has previously been fantasy into a potential reality. We are now closer than ever to effectively treating a wide variety of human ailments, which will change how scientists attempt to solve society’s most devastating diseases. References 1. Park, K. 2007. Nanotechnology: What it can do for drug delivery. Journal of Controlled Release. 120:1–3. doi:10.1016/j. jconrel.2007.05.003. 2. Zhang, G. 2009. Nanotechnology-Based Biosensors in Drug Delivery. Nanotechnology in Drug Delivery. 163–189. doi:10.1007/978-0-387-77668-2_6. 3. Ngoune, R., A. Peters, D.V. Elverfeldt, K. Winkler, and G. Pütz. 2016. Accumulating nanoparticles by EPR: A route of no return. Journal of Controlled Release. 238:58–70. doi:10.1016/j. jconrel.2016.07.028. 4. Wilhelm, S., A.J. Tavares, Q. Dai, S. Ohta, J. Audet, H.F. Dvorak, and W.C.W. Chan. 2016. Analysis of nanoparticle delivery to tumours. Nature Reviews Materials. 1:16014. doi:10.1038/ natrevmats.2016.14. 5. Torrice, M. 2016. Does nanomedicine have a delivery problem? C&EN Global Enterprise. 94:16–19. doi:10.1021/cen09425-scitech1. 6. Yu, D., H. Wu, C. Sun, F. Shi, X. Wang, Z. Zheng, D. Chen, and X. Wang. 2015. A single dose of dexamethasone encapsulated in polyethylene glycol-coated polylactic acid nanoparticles attenuates cisplatin-induced hearing loss following round window membrane administration. International Journal of Nanomedicine. 3567. doi:10.2147/ijn.s77912. 7. Rice, A., M.L. Michaelis, G. Georg, Y. Liu, B. Turunen, and K.L. Audus. 2003. Overcoming the Blood-Brain Barrier to Taxane Delivery for Neurodegenerative Diseases and Brain Tumors. Journal of Molecular Neuroscience. 20:339–344. doi:10.1385/ jmn:20:3:339.
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CAR-T THERAPY Rosie Nagele Beneath the skin, microscopic battles keep our bodies healthy. Although we are made up of billions of cells all working together, some of the most drastic illnesses are caused by single cells that act independently, such as bacteria and viruses. Among our billions of cells, however, some are specialized to fight off these small but dangerous threats. After millions of years of gradual refinement, the immune system has evolved into an elaborate network of cells that recognize and destroy infectious agents, all while maintaining steady communication and collaboration. Immune activity depends largely on antibodies, a class of Y-shaped proteins.1 The principle is simple; the base of the Y attaches to the host body cells, while the branches attach to invading cells, providing the contact needed to destroy invaders. The nuances of antibody structure, however, are vital for the protein’s ability to recognize invaders. Each branch of the Y can attach to a complementary protein, usually a protein on the surface of an invading cell. The diverse range of possible antibody branches that our bodies can produce equips us to battle many types of microbial invaders.2 The specific structure of the stem of the Y then directs the host’s response to the cells it has grabbed. One class of stems, denoted Fc for fragment crystallizable, directs T-cells, a type of immune cell, to destroy the captured invaders.2 Although immune cells produce certain antibodies from birth, they also have the capacity to produce novel antibodies in response to new invading pathogens. When new antibodies are created, they are stored in the bloodstream for the lifetime of the organism. If the same pathogen strikes again, the body will be able to respond more quickly. The immune system has the potential to adapt to any threat entering the body. The qualities that enable antibodies to recognize foreign cells make the immune system virtually helpless when faced with a threat that arises within our own body - cancer. Like microbial invaders, cancer cells subvert resources for their own gain at the expense of healthy cells. But since cancer cells are derived 8
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from our own cells, they often do not have protein markers that antibodies recognize as harmful. The immune system’s efficiency against pathogens and ineptitude against cancer exemplify the simultaneous ingenuity and fragility of multicellular life. All life forms can be traced back to a single cell that lived about 3.5 billion years ago. That cell divided into two, which went on to live independently of each other and single-celled organisms came to populate the Earth. For some cells, however, cooperating with neighbors became a successful survival strategy. Through incremental increases in cooperation, these cells came to be dependent on each other, unable to survive on their own. After millions of generations, these aggregations of cells became the organized systems of differentiated, specialized cells we identify as singular beings - a tree, dog, or person, for example. Multicellular organisms rely on complex physiological processes and specialized cells, such as those that make up the immune system. The first signs of the immune response appeared in jawed fish, from which we diverged about 500 million years ago.3 Since then, gradual adjustments and improvements shaped the mammalian immune response and ultimately gave rise to today’s complex human immune system. But the very complexity of multicellular systems can bring their own downfall. Multicellular life balances on a precipitous compromise - each cell must act for the good of the whole organism, not just for its own survival. Cells in the body that fail to submit themselves to their assigned role and rather prioritize their own survival and reproduction can lead to the formation of tumors, which are abnormal growth of cancer cells. A cancer cell has, in a sense, reverted back to a more ancient survival strategy, one that predates cellular cooperation. Within the context of a multicellular body, where individual cells are no longer programmed to compete with one another, this strategy can be remarkably efficient. In the immune system, antibodies
FEATURES are designed to latch onto the markers of foreign cells, not the body’s own cells, so that immune cells do not damage the body. Though cancer cells may ravage the body, the immune system remains unaware of their presence. Any antibody it happens to produce that can target cancer cells will most likely also destroy human cells and further weaken the body - a problem shared by many cancer therapies. The rapid division of cancer cells increases the potential of acquiring additional mutations. Though many mutations are lethal to cells, a few actually help them grow and quickly become dominant. Each individual population of cancer cells develops its own innovative ways to ensure survival and growth within the body. Though cancer successfully evades natural immunity, scientists are beginning to explore ways to redirect this time-tested system toward the tenacious disease. The key lies in finding distinguishing markers between cancerous and healthy cells so that immune mechanisms destroys only the harmful cells. Such immunotherapies have progressed slowly over the past few decades, but recent breakthroughs in chimeric antigen receptors (CARs) could accelerate the development of these treatments.4 CARs are essentially modified antibodies. They have two basic parts: one attaches it to the cell like the base of the Y on an antibody and the other recognizes proteins outside the cell like the branch on the Y. Unlike antibodies, CARs have only one of these recognition regions. For cancer therapy, CARs must be able to identify and direct the destruction of tumor cells. This requires matching the recognition portion of the CAR to a protein on the surface of the tumor cell. CAR-T therapy has thus far proven most effective in soluble B-cell cancers such as acute lymphoblastic leukemia (ALL) and chronic lymphoid leukemia (CLL).5 Scientists have engineered CAR-T therapies that recognize a cell surface protein, called CD19, that is unique to B-cells. In ALL and CLL patients that receive this therapy, the CAR-T cells target and destroy all B-cells, healthy and cancerous. Though B-cells play an important role in the immune response to pathogens, they are not crucial for survival or bodily function. So, CAR-T therapy has the potential to destroy all cancerous B-cells, albeit at the expense of a diminished immune response to potential pathogens. CAR-T therapy saw its first major breakthrough in 2011, when researchers at the University of Pennsylvania and the Children’s Hospital of Philadelphia published a report in which CAR-T therapy eliminated cancerous cells in three CLL patients.6,7 However the treatment was not without complications, such as tumor lysis syndrome. This is a side effect of many cancer therapies in which the sudden death of a large number of cancer cells causes physical distress such as fever, nausea, and diarrhea. Even so, CAR-T demonstrated its potential to be a specific, long-lasting, and relatively non-toxic treatment for cancer.8 In August 2017, six years and several clinical trials after this initial publication, the FDA approved the therapy (KymriahTM) for
use in ALL patients up to 25 years in age.9,10 Developing CAR-T therapies for other cancers, particularly solid cancers, faces many barriers beyond the challenge of distinguishing tumor cells from healthy cells. CAR-T easily interacts with fluids within the circulatory system that contain B cells, but delivering them to sites of solid tumors will require extra steps. Moreover, many solid tumors often develop an immunosuppressive environment - actively working to avoid detection from the immune system. But, as researchers continue to zoom in on the world of the cell, they come closer to the molecular discoveries that will enable them to target cancer cells more precisely.11 As hospitals continue to fill with patients, scientists hope to harness the protective capacity of the immune system to eliminate cancer.
References: 1. Cohen, J. 2016. Antibody. AccessScience. doi:10.1036/10978542.040100. 2. Janeway, C. 1999. Immunobiology: the immune system in health and disease. 5th ed. Harcourt Brace & Company, London. 3. Flajnik, M.F., and M. Kasahara. 2009. Origin and evolution of the adaptive immune system: genetic events and selective pressures. Nature Reviews Genetics. 11:47–59. doi:10.1038/nrg2703. 4. Gill, S., M.V. Maus, and D.L. Porter. 2016. Chimeric antigen receptor T cell therapy: 25years in the making. Blood Reviews. 30:157–167. doi:10.1016/j.blre.2015.10.003. 5. Lawrence, D., and F. Jernigan. 2011. Faculty of 1000 evaluation for T cells with chimeric antigen receptors have potent antitumor effects and can establish memory in patients with advanced leukemia. Scientific Translational Medicine. 3. doi:10.3410/f.13096956.14688091. 6. Rosenbaum, L. 2017. Tragedy, Perseverance, and Chance — The Story of CAR-T Therapy. New England Journal of Medicine. 377:1313–1315. doi:10.1056/nejmp1711886. 7. FDA Approves Personalized Cellular Therapy for Advanced Leukemia. 2017. Penn Medicine. 8. Porter, D., B. Levine, M. Kalos, A. Bagg, and C. June. 2016. Chimeric Antigen Receptor–Modified T Cells in Chronic Lymphoid Leukemia. New England Journal of Medicine. 374:998–998. doi:10.1056/ nejmx160005. 9. Lee, D.W., J.N. Kochenderfer, M. Stetler-Stevenson, Y.K. Cui, C. Delbrook, S.A. Feldman, T.J. Fry, R. Orentas, M. Sabatino, N.N. Shah, S.M. Steinberg, D. Stroncek, N. Tschernia, C. Yuan, H. Zhang, L. Zhang, S.A. Rosenberg, A.S. Wayne, and C.L. Mackall. 2015. T cells expressing CD19 chimeric antigen receptors for acute lymphoblastic leukaemia in children and young adults: a phase 1 dose-escalation trial. The Lancet. 385:517–528. doi:10.1016/s0140-6736(14)61403-3. 10. Davila, M., I. Riviere, X. Wang, S. Bartido, and J. Park. 2014. Efficacy and Toxicity Management of 19-28z CAR T Cell Therapy in B Cell Acute Lymphoblastic Leukemia. Scientific Translational Medicine. 6. 11. New CAR T Cell Therapy Using Double Target Aimed at Solid Tumors – PR News. 2017. Penn Medicine.
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Neural
Engineering by Hiab Teshome
The brain is unarguably one of the largest and most convoluted organs in the body. It is the center of all human activity, and contains over 100 billion neurons that work in unison to allow us to live and complete daily tasks. Researchers and doctors have studied the brain for centuries to unmask its importance. Previously, techniques such as brain surgery and brain imaging were used to study the brain. In the past few decades, however, scientists and researchers have been developing a new field known as neural engineering. This field arose with the goal of not only understanding the brain, but also rebuilding damaged neuronal connections and creating detailed maps of the brain. Through the integration of neuroscience and engineering, researchers are using nanotechnology and computer technology to make unprecedented headway toward unearthing the complexity of the brain. Last year, chemical engineer Matteo Pasquali and a team of scientists at Rice University took initiative by using carbon nanotubes (CNTs) to sustain and promote electrical activity in neurons.1 These carbon fibers are only a few nanometers thick, but the metallic and organic coatings on the electrode active site make these fibers extremely conductive, strong, and sustainable.2 The fibers are then carefully implanted into the brain as electrodes to stimulate normal neuronal function and repair broken pathways.The working end of the fiber is about the width of a neuron and is encased in a flexible polymer with insulating properties. This insulating material functions similarly to the myelin sheath that naturally insulates neurons.3 Myelin allows for the faster propagation of action potentials by increasing the electrical resistance of the neuronal membrane. Thus, myelin prevents electrical currents from leaving the neuron, allowing for stronger neuronal connections across large distances.
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In collaboration with Pasquali’s lab, Caleb Kemere, an assistant professor at Rice University, is applying Pasquali’s CNTs to treat Parkinson’s disease. Parkinson’s disease is a neurodegenerative disorder characterized by the death of neurons in a region known as the substantia nigra. The specific neurons affected are crucial for the release of dopamine, the chemical messenger that motivates and initiates movement. Parkinson’s is characterized by bradykinesia (slowed movement) and resting tremors. One way doctors currently treat patients with Parkinson’s is through deep brain stimulation of the midbrain. Patients that undergo deep brain stimulation often do this as a last resort when all other medication fails to treat their symptoms. The electrodes used during deep brain stimulation are not completely accurate at stimulating neuronal bundles and as a result, deep brain stimulation can cause many side effects by stimulating surrounding neurons.4 The flexible carbon fibers in CNTs, however, are much smaller than the metallic electrodes used in deep brain stimulation, and they are more accurate and effective in stimulating damaged neurons.5 Dr. Kemere plans on developing a self-regulating device built with carbon fibers that will be inserted into the brains of patients with Parkinson’s.5 The device will constantly activate and monitor damaged neuronal connections in order for patients to gain control of their motor pathways. This is significantly better than using deep brain stimulation to treat Parkinson’s because the patient only has to undergo one major surgery in order to treat their symptoms. The technology being developed through the engineering of these carbon fibers can treat many other neurodegenerative diseases and provides a catalyst toward regenerating neurons. Another form of neural engineering uses nanotechnology to map the brain and monitor large groups of neurons. The most publicized achievement of brain mapping through nanotechnology was Brain Research through Advancing
FEATURES Innovative Neurotechnologies (BRAIN), launched by the Obama administration in 2013.6 The purpose of this initiative was to fund researchers who are studying the brain at the nano level in order to come up with a complex and accurate map of the brain. Developing the technology needed to map the brain has been a slow process. In the past year, however, a team at Harvard led by Dr. Charles Leiber succeeded in “bugging” the brain by developing a mesh of conductive polymer threads that can be rolled and injected into the brains of unconscious mice.7 The strands were designed to mold around the brain and arrange themselves on the brain once injected. Thus far, the researchers have been able to implant these carbon sheets with 16 electrical monitors in mice brains.7 The carbon sheets, which are able to record neuronal signals, were seen to be structurally and functionally stable in the mice brains without activating a negative immune response. Leiber’s team plans on expanding on their discoveries by implanting larger meshes with more sensors. The team hopes to inject wireless sensors that can track neuronal signals while the animal is moving in order to trace brain signals during activity.8 The researchers hope in the future to be able to inject the electrodes in larger animals and possibly even humans to provide new insights as to how the brain responds when organisms are performing daily actions.
regain sensorimotor function.12 Although the field of neuroengineering has only been around for a few years, researchers have made great headway in better understanding and healing the brain. The integration of neuroscience and engineering provides researchers with unprecedented access to the nervous system and the ability to rebuild the brain. Researchers are moving toward building advanced electrodes and laser lights to manipulate neural signals in order to provide greater access to the brain. Scientists are also striving to move beyond the brain to translate the brain’s abilities into innovative technologies, such as brain-like computers and chips that can learn and form neuronal connections similar to the brain. This represents the array of different ways neuroengineering can impact not only patients suffering from brain injuries or diseases, but society as well. With the rapid generation of this field, in the near future, neurotechnology may eventually become a seamless part of life.
“Developing the technology needed to map the brain has been a slow process.”
Besides using nanotechnology to rebuild neural connections and map the brain, new technology is being developed to provide neuroprotection for the brain. Traumatic brain injury (TBI) occurs when the brain is deprived of oxygen for a long period of time, otherwise known as hypoxia. Reperfusion injury, which is typically seen after TBI, occurs when blood supply returns to the brain after a long period of hypoxia. This sudden return of blood flow results in tissue and neuronal damage and can eventually lead to brain death. Neuroprotection in reference to TBI is used to decrease tissue damage by decreasing reperfusion injury. In the past two years, researchers have developed self-assembling peptide nanofiber scaffolds (SAPNS) to reduce blood flow and prevent reperfusion injury and intracerebral hemorrhages.9 The self-assembling fibers undergo spontaneous selfassembly when exposed to physiologic conditions that indicate brain damage and excess swelling and blood loss in the brain. This rapid self-assembly allows for fast blood control without causing additional brain trauma.10 The fibers are also highly porous and can facilitate the natural expansion and growth of axons and neuronal connections after brain damage.11 In a rat study, researchers inserted SAPNS into damaged rat brains. Researchers observed that the SAPNS replaced the blood that was outside of the blood vessels and reduced brain swelling and injury in the rats. The researchers observed a significant improvement in the recovery rates in the rats, and the rats were able to
References: 1. Long nanotubes make strong fibers. 2017. EurekAlert! 2. Cf2 Complex Flows of Complex Fluids. 2010. Rice University Chemical and Biomolecular Engineering. 3. Basic neurochemistry: molecular, cellular and medical aspects. 6th ed. G.J. Siegel, B.W. Agranoff, R.W. Albers, S.K. Fisher, and M.D. Uhler, editors. 2011. Elsevier Academic Press, Amsterdam. 4. Perlmutter, J.S. and J.W. Mink. 2006. Deep Brain Stimulation. Annual Review Neuroscience. 29:229-57. 5. Vitale, F., Summerson, S. R., and B. Aazhang. 2015. Neural stimulation and recording with bidirectional, soft carbon nanotube fiber microelectrodes. ACS nano. 4:4465-74. 6. The Brain Initiative. 2017. National Institute of Health. 7. Gibney, E. 2015. Injectable brain implant spies on individual neurons. Nature. 522:137–138. doi:10.1038/522137a. 8. Lieber Research Group. 2017. Harvard University. 9. Kumar, A., Tan, A., and J. Wong. 2017. Nanotechnology for Neuroscience: Promising Approaches for Diagnostics, Therapeutics and Brain Activity Mapping. Advanced Functional Materials. 10. Xu, F. F., Wang, Y. C., and S. Sun. 2015. Comparison between self‐assembling peptide nanofiber scaffold (SAPNS) and fibrin sealant in neurosurgical hemostasis. Clinical and translational science. 5:490-4. 11. Cigognini, D., Satta, A., and B. Colleoni. 2011. Evaluation of early and late effects into the acute spinal cord injury of an injectable functionalized self-assembling scaffold. PloS one. 5:e19782. 12. Sang, L. Y. H., Liang, Y. X., and Y. Li. 2015. A self-assembling nanomaterial reduces acute brain injury and enhances functional recovery in a rat model of intracerebral hemorrhage. Nanomedicine: Nanotechnology, Biology and Medicine. 3:611-20.
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lab-on-a-chip:
Transforming Liquid Sample Testing Neelu Paleti
R
esearch. One can imagine the rows of black benches brimming with racks of glass test tubes, half-filled beakers, and scattered pipettes all ready to test a single sample. Yet, what if we could shrink this entire lab to fit between our fingers? What if the hours of work could be condensed into sheer minutes? Recent advances in nanotechnology have enabled us to do just that with a “lab-ona-chip”. Ever since the rise in the field of biotechnology, the focus on improving speed and precision has been paramount. Lab-on-achip technology (LOC) strives to develop these qualities by conducting scientific operations on a microscopic scale to both
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speed up the experiments and increase the accuracy of results. By integrating the different steps of detection and analysis used in sample testing, LOC yields a significantly faster and more efficient system. Ranging from 30 to 100 micrometers in diameter, these chips contain microfluidic channels and pumps that form the basis of their structure.1 The channels and pumps play a crucial role in the control of microscopic fluids by using laminar flow, a mechanism that allows small volumes of liquid to flow in a straight path without turbulence.2 Ultimately, this structure allows for minimal sample consumption, quick reactions, and simultaneous flow of mul-
tiple samples.1 Although the samples used may be extremely small, LOC’s computer-based sensors can yield unimaginably high precision, surpassing the manual ability of scientists. This has enabled LOC to perform many functions from testing for harmful genetic mutations to detecting biochemical markers of disease.3 Alongside many other qualities, LOC’s ability to test samples in a faster manner has rendered it to be an impactful device with broader implications in medicine and global health. LOC is now used to expedite the detection of cancerous tumor cells, simplify stem cell gene transfer therapy, and diagnose diseases more rapidly.4 Without LOC,
FEATURES current methods of blood sampling can take anywhere from 24 hours or longer to receive definitive results.5 Since not every hospital holds the technology and labor needed to test samples in bulk, these tests are often run with the help of third-party private testing companies. Unfortunately, this only increases administrative complexities and further delays the testing process. Not to mention, any following discussions about sample results between the doctor and patient would require yet another scheduled hospital visit. LOC technology, however, enables fast point-of-care diagnostics that eliminates the need for extensive lab equipment or tremendous time commitments. Another defining aspect of LOC is its strikingly low cost. This is primarily because of the inexpensive materials used to produce LOC, which includes glass, plastics, and elastomers such as rubber.2 These materials have made the production of LOC as cheap as a single penny. Using 3D printing, the manufacturing process of LOC can also spare heavy costs by reducing wastage of raw materials with its precise production.6 Furthermore, using LOC would eliminate the need for traditionally used fluorescent microscopy and biochemical assays, potentially saving labs an overall investment upwards of $50,000.5 While LOC can be a great incentive to increase medical health testing in an efficient manner, it also possesses massive implications in the democratization of global health and medicine as a whole. Rural, low-income communities around the world could gain access to basic
health testing and medical care through LOCs. Research labs and expensive technology would not be a requirement for primary medical care in developing societies, bridging the gap between the wealthy and the poor to promote universal access to healthcare. Additionally, this technology could enable epidemiologists to track the spread of deadly viral diseases in communities around the world, while also raising awareness about health and medical conditions needing attention.4 LOC has the potential to revolutionize the field of epidemiological research through the increased availability of essential data and ultimately improve public health standards to new heights.
"Rural, low-income
communities around the world could gain access to basic health testing and medical care through LOCs."
eral public and untrained workers manage this data to prevent public panic and future transmission? How could people make informed decisions without any proper medical counseling? While such ethical claims do not discourage the development of LOCs, they prompt us to consider the ways in which LOC and resulting health care should be managed and distributed in the future. Though these questions may not be pertinent at present, they are essential points to consider as we continue to develop and use labon-a-chip technology in biomedical research.
Referencess: 1. Sedgwick, H., F. Caron, P. Monaghan, W. Kolch, and J. Cooper. 2008. Lab-ona-chip technologies for proteomic analysis from isolated cells. Journal of The Royal Society Interface. 5:S123–S130. doi:10.1098/rsif.2008.0169. 2. Temiz, Y., R.D. Lovchik, G.V. Kaigala, and E. Delamarche. 2015. Lab-on-a-chip devices: How to close and plug the lab? Microelectronic Engineering. 132:156– 175. doi:10.1016/j.mee.2014.10.013. 3. Jha, A. 2011. The incredible shrinking laboratory or ‘lab-on-a-chip’. The Guardian. 4. Bansal, D.G. 2017. Scientists develop ‘lab on a chip’ that costs 1 cent to make. Stanford University Medical School News Center. 5. Perkel, J. 2011. Multiplexed Protein Assays. Biocompare. 6. The printed world. 2011. The Economist.
Yet, despite these advantages, some fear the implications of easy testing and medical detection. LOC brings unprecedented ease and simplicity to biomedical testing, arguably allowing it to fall into the hands of untrained health professionals.3 Such possibilities have prompted new doubts about the ethical use of this data.3 If this technology is easily accessible, could it lead to the misuse and misinterpretation of confidential data? If, for example, a general testing procedure showed the presence of a viral communicable disease, how could the genFALL 2017 | PENNSCIENCE JOURNAL
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10110001 01001101 00101100 10101010 00001111 10101010 10100010 01101001 FEATURES 01010101 00110011 10001100 10010011 10010110 00101010 00110010 01010011 10010100 10010101 01010010 01101001 10010011 10010001 10010001 10100101 10010011 01010110 10001010 10101000 11010110 10100101 10101000 10100001 01010000 11110000 10101010 11001100 10101011 01100010 10000111 01001101 10101010 10010101 10111001 10100010 10101100 10100110 01010110 10101001 10101001 10100010 01010100 10111011 11100111 00011010 11010001 10100110 10100011 11101001 10111001 10100011 10100101 10101010 10101010 10101010 10101110 10111001 10101110 10110101 10111010 10110110 10001110 10100110 10110111 01110011 01101101 10101101 11010101 10101010 10101111 10101010 10101011 11000110 10101010 10100011 10101001 10101011 01010100 01010101 10101111 00000010 10000111 11111110 11111011 00011000 10011010 10010110 1001010 101010100 10101010 10101011 11100010 10100011 11000110 11100101 1101010 100011011 01110111 11001111 00001100 10011110 11100111 00111010 1010101 101110110 11010110 00000000 10110110 10101100 10101011 11010100 By Xufei Huang 1010101 101010100 10100010 01010101 01011011 10001101 01010101 01011101
Nano Computers I
f you had been born 60 years earlier, you would have been lucky enough to witness the creation of the Electronic Numerical Integrator and Computer (ENIAC), the first general-purpose electronic computer, here at the University of Pennsylvania. I am sure you would have been amazed by how gigantic it was. The ENIAC filled a 20 by 40 feet room, weighed 30 tons, and used more than 18,000 vacuum tubes.1 Over the last few decades, however, computers have shrunk in size at an amazing rate, and as engineers continue to devote more effort into making even smaller devices, the future of computers is full of possibilities. We expect to see nanometer-scale replacements of computational and information storage elements, with vast increases in memory density, power, and performance. Just imagine: in 20 years, you might be writing your history paper on a computer that can only be seen through a microscope. These extremely small computers are what we call nanocomputers. Currently, researchers are working on four types of nanocomputers: electronic, chemical and biochemical, quantum, and mechanical nanocomputers. While the first three types have been studied in detail, researchers are still working on the design of mechanical nanocomputers, so a detailed description of how they would work is not available. However, scientists at the University of Wisconsin-Madison have proposed building a computer that would work on a purely mechanical basis; instead of letting electrons flow through circuits, it would do computations as components push and pull on each other.2
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FEATURES ELECTRONIC Electronic nanocomputers would operate in a similar manner to the way current computers work, but on a much smaller scale. This decrease in computer size is primarily due to the continual miniaturization of the computer’s most elementary component, the transistor.3 Basically, a transistor functions as a switch that can either open or block the way for information to come through. According to an observation made in 1965 by Intel co-founder Gordon Moore, the number of transistors in a dense integrated circuit doubles every year and a half.4 Moore’s Law has been an accurate projection of the computer industry ever since. Today, a typical transistor is about 14 nanometers, which is almost 500 times smaller than a red blood cell.5 With the belief that devices will continue to follow the law into the next few decades, engineers are striving to build smaller and faster computers.
CHEMICAL AND BIOCHEMICAL Chemical and biochemical nanocomputers are computers where the structure of chemicals enables them to store and process information.3 Biochemical nanocomputers exist in nature, yet they are hard to control. In order to create a chemical nanocomputer, engineers must figure out how to control individual atoms and molecules to store desired data and perform controllable calculations. In 1994, Leonard Adelman took a significant step forward when he used fragments of DNA to compute the solution to a complex graph theory problem.6 Using the tools of biochemistry, Adelman was able to extract the correct answer from the many random paths represented by the product DNA strands.6
QUANTUM Quantum computers differ from current computers in the way they store information. Computers operate in binary, meaning they store information and execute calculations using a number system consisting of only 0s and 1s. Classical computers encode information in bits, which can be set to the value of 0 or 1. Combinations of several bits are used to represent more complex information. For example, two normal bits can have one of four different configurations (00, 01, 10, 11) at a given time. On the other hand, quantum computers use qubits, which can represent both a 0 and a 1 at the same time. In other words, two qubits can be in all four combinations at once, and twenty qubits can store a million values in parallel. This unique characteristic of qubits offers scientists an enormous gain in the use of computational resources such as time and memory.
Scientists hold a variety of opinions about the best way to design and build a nanocomputer. A strong argument made in favor of chemical and biochemical nanocomputers is that we can always use natural material as a supply. Nonetheless, implementing those biochemical structures requires us to have a more in-depth and comprehensive understanding of them2. For electronic nanocomputers, scientists suggest the conventional transistor technology will eventually reach a minimum size limit at the current rate of miniaturization. At that point, small-scale quantum mechanical effects, such as the quantum tunneling, will start to dominate effects that are critical to the operation of a device.7 Thus, it is evident that a change in the technology of the transistor will be necessary. Skepticism about proposed quantum nanocomputers includes the fact that they would have to be constructed and initialized with extreme precision, because they would be very sensitive to miniscule physical distortions and stray photons.2 Therefore, they would have to be carefully isolated from all external effects and operated at temperatures very close to absolute zero, making their practicality very limited.2 Despite the challenges scientists are facing, the advancement of technology and human ingenuity provide great hope for the future of nanocomputers.
References: 1. ENIAC: Celebrating Penn Engineering History. University of Pennsylvania School of Engineering. 2. Montemerlo, M. S., Love, J. C., and G.J. Opiteck. 1996. Technologies and designs for electronic nanocomputers. McLean: MITRE. 3. Karkare, M. 2010. Nanotechnology: fundamentals and applications. I. K. International Publishing House Pvt., New Delhi. 4. 50 Years of Moore’s Law. Intel. 5. Handy, J. 2011. How Big is a Nanometer. Forbes. 6. Mansuripur, M. 2002. DNA, human memory, and the storage technology of the 21st century. In Optical Data Storage 2001. 4342:1-30. 7. Cavin, R. K., Lugli, P., and V.V. Zhirnov. 2012. Science and engineering beyond Moore’s law. Proceedings of the IEEE. 100:1720-49.
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FEATURES
FORMULATING A CHAMPION FORMULA-ONE NANOCAR BY KENNY HOANG
This past spring, the unlikely matrimony of chemistry and motorized racing gave birth to an exciting new event in the scientific community: the first ever Nanocar Race. Six teams from across the globe gathered in Toulouse, France for the event, a testament to the growing interest in nanocar design and its applications.1 While this is the first year that nanomachines, dubbed “nanocars,” officially raced, they have been around for decades. The most primitive designs of these nanomachines featured simple networks of interlocking rings and chains called catenanes. These archetypes later served as models for creating more complex molecular motors. For instance, one common design for modern nanocars are ring structures that serve as “wheels.” These wheels propel the nanocar forward when they change configuration after being excited by electrons.
Nanomachines are unique in their assembly and usage as they are driven by chemical rules and principles rather than classical Newtonian mechanics. Their activity can also be initiated or extinguished based on changes in environmental acidity and temperature or the introduction of light irradiation.2,3,4
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Nanomachines are unique in their assembly and usage as they are driven by chemical rules and principles rather than classical Newtonian mechanics. At the official Nanocar Race, all the designs were powered with excited electrons from the tip of a scanning tunneling microscope (STM) and were raced on the same vacuumed track, comprised of either 100 nm of gold or 150 nm of silver kept at a cool -268 degrees Celsius.5 Most of the nanocars were composed of approximately 100 atoms or less, making every nuance of each team’s design all the more important. The competing teams employed various strategies to excite their racers across the track. Take the Japanese team for instance; their racer has two wings analogous to those of a butterfly that flap after being excited by the STM tip. The Swiss team, however, took a different approach. Their design, the “Nano Dragster,” has a flat, triangular design that is intended to glide across the track with ease and fluidity. While it has less “mechanical” components, their hope is that this simpler design will result in their nanocar moving the fastest, sort of like a Prius outracing an
18-wheeler, on the basis of its smaller size.6 The unorthodox design failed to pay off for the Japanese team, but the Swiss team ended up sharing the title with an American-Australian team, who utilized components of a traditional car with shapes that are similar to wheels and axles. The American-Australian team leader, Dr. James Tour, suggested
FEATURES critical design features that led to their victory with their nanocar, the Dipolar Racer. Tour first notes how the racer should be adequately stable under the ultrahigh vacuum track conditions and be able to withstand any potential bond breakage that could occur as a result of the STM-tip. Next, a lower molecular weight is ideal as larger nanocars tend to exhibit increased diffusion barriers, restricting mobility. Lastly, Tour stated that the wheels, chassis, and axles should be created to minimize interactions with the surface, analogous to reducing areas of friction on the macro-scale. One strategy includes using aliphatic wheels that are just large enough to keep chassis from touching the surface.7
While it is not confirmed whether the competition will be held next year, it will be interesting to see what strategies and innovations will be employed in the future. Unlike Toyota or Ford, this kind of car typically does not come out with new models boasting updated features after the span of a year. However, Tour says that the next race will probably feature a new generation of motorized nanocars likely with four wheels. Whenever the race happens the be, it is clear Tour and his colleagues will use it as an opportunity to showcase new nanocar developments. With potential applications in areas such as data storage devices, electronics, and drug delivery, nanocars might be the most important and entertaining field in science today.
References:
Anyone designing their own nanocars should take Tour’s suggestions into consideration, as his team’s design won the race in a blazing 90 minutes. In fact, their nanocar was so fast on the competition’s sleek gold surface that they found difficulty in imaging it. The race organizers allowed them to switch to a slower silver surface under the conditions they travel 150 nm instead of 100 nm.8 The Dipolar Racer still clocked an average speed of 100 nm/hr, reaching speeds as high as a blistering 300 nm/hr.9 In comparison, the Swiss team’s Nano Dragster was only the second team to successfully finish, but not until five hours later.
1. Rapenne, G., & C., Joachim. 2017. The first nanocar race. Nature Reviews Materials. 17040. 2. Halford, B. 2016. Molecular machines garner 2016 Nobel Prize in Chemistry. American Chemical Society. 3. Van Noorden, R., and D. Castelvecchi. 2016. World’s tiniest machines win chemistry Nobel. Nature News. 4. Peplow, M. 2015. The tiniest Lego: a tale of nanoscale motors, rotors, switches and pumps. Nature News. 5. Rules of the Nanocar Race. 2017. NanoGraz. 6. Davenport, M. 2017. World’s first nanocar race crowns champion. American Chemical Society. 7. Tour, J. 2017. Email Interview of Dr. Tour on Nanocars. 8. Williams, M. 2017. Rice vehicle tops all in Nanocar Race. Rice News. 9. Simpson, G.J., V. García-López, P. Petermeier, L. Grill, and J.M. Tour. 2017. How to build and race a fast nanocar. Nature Nanotechnology. 12:604–606. doi:10.1038/nnano.2017.137.
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Say you are babysitting your neighbor’s toddler and he decides to waddle over to the kitchen counter and reach over it. He accidentally knocks over a sharp object onto his leg. What do you do? You freak out, call his parents, clean the wound, and rummage around the house for some bandages. You come across a box that says “Aquacel Silver Dressings.” Now, you just put the bandage on his wound and wait for his parents to come home. It can be this easy to introduce silver nanoparticles into someone’s body.
than 30 in 2006 to over 300 at the beginning of 2011. Silver nanoparticles (AgNPs) are used in household products, wound dressings, and antimicrobial coatings.1 They provide a number of advantages in terms of antibacterial uses. Silver ions are highly toxic to microorganisms, showing significant biocidal effects in at least twelve species of bacteria including E. coli.2 Despite their promising properties, AgNPs can have toxic effects on the cells of larger organisms as well.
Silver nanoparticles are, by definition, quite small; they range from 1 nanometer to 100 nanometers in size. However, their minute size should not fool you. The use of silver nanoparticles in our everyday life is becoming increasingly common. In fact, the number of silver nanoparticle-containing products has grown from less
A number of in vitro studies have demonstrated the effects of AgNP toxicity in rat liver cells, human lung epithelial cells, and rat neuronal cells. At the cellular level, Ag+ ions target mitochondria by diffusing through the proteinaceous pores in mitochondrial membranes. In rat liver mitochondria, the increase in permeability causes various detrimental effects including mitochondrial swelling, aberrant metabolism, and cellular apoptosis. In a study led by Mei Jing Piao at Jeju National University, it was confirmed that the presence of silver nanoparticles can induce apoptosis. The group stained cellular nuclei with Hoechst 33342, a fluorescent dye, and assessed the nuclei by microscopy. The microscopic pictures revealed that the control cells had intact nuclei while the AgNPs-treated cells showed significant nuclear fragmentation, indicative of apoptosis. During apoptosis the mitochondrial membrane pores open and the mitochondrial membrane potential is disrupted. Staining data showed that AgNPtreated cells exhibited a decrease in red fluorescence and an increase in green fluorescence, corresponding to a polarized state and a depolarized state, respectively, in the mitochondrial membrane. In a separate part of the study, apoptotic markers Bcl2 and Bax were used. Bcl-2 prevents the opening of the mitochondrial membrane pore while Bax accelerates it. Pore opening results in the loss of mitochondrial membrane
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FEATURES potential, which induces the release of cytochrome c from mitochondria, and subsequent apoptosis. Cytochrome c is a transmembrane protein that acts as a mobile electron carrier in the electron transport chain. It also plays a crucial intermediate role in cellular apoptosis. This release of cytochrome c in turn activates caspase-9, a cysteine protease. Caspase-9 can then activate caspase-3 and caspase-7, which are responsible for destroying the cell from within. The results of the experiment showed a decrease in Bcl-2 expression and an increase in Bax expression in a time dependent manner. The change in the Bax/Bcl-2 ratio led to the release of cytochrome c from the mitochondria into the cytosol. These results suggest that AgNP-induced apoptosis signals through a caspase-dependent pathway with mitochondrial involvement.3
Given the amount of damage silver nanoparticles can cause in mammalian cells, is it truly safe for them to be readily available to the public? The toddler who hurt his leg could potentially have silver nanoparticles floating around in his bloodstream. Not only are AgNPs found in wound dressings, but also in many textiles, keyboards, and biomedical devices. They have a number of unique properties that make them an attractive and promising application in the medical field. However, the field of nanotechnology is all too new to give a definite answer as to whether or not this substance is safe. Before promoting their widespread use, scientists should find ways to avoid different forms of toxicity in human cells. Once the mechanisms of silver nanoparticles in the body are fully understood, perhaps we will have one of the most extraordinary nanomaterials on our hands.
In human lung cells, AgNPs have been shown to cause oxidative stress, which is a result of the production of reactive oxygen species (ROS). ROS are a form of unstable molecules containing oxygen that easily react with other molecules in a cell. A buildup of reactive oxygen species in cells may cause damage to DNA, RNA, and proteins, and in the context of toxicity, may cause cell death.
References: 1.Silver Nanoparticles: Properties and Applications. 2017. Sigma-Aldrich. 2.Lara, H. H., Garza-Treviño, E. N., and Liliana IxtepanTurrent, L. 2011. Silver nanoparticles are broadspectrum bactericidal and virucidal compounds. Journal of nanobiotechnology. 1:30. 3. Piao, M. J., Kang, K. A., and I. K. Lee. 2011. Silver nanoparticles induce oxidative cell damage in human liver cells through inhibition of reduced glutathione and induction of mitochondria-involved apoptosis. Toxicology letters. 1:92-100. 4. Kim, H. R., Kim, M. J., and S. Y. Lee. 2011. Genotoxic effects of silver nanoparticles stimulated by oxidative stress in human normal bronchial epithelial (BEAS2B) cells. Mutation Research/Genetic Toxicology and Environmental Mutagenesis. 2:129-35.
A study conducted by Ha Ryong of Sungkyunkwan University aimed to identify the genetic toxicity related to ROS. In this experiment, BEAS-2B cells, which are human bronchial epithelial cells, were treated with AgNPs in an oxidative stress assay. A fluorescent dye called 2’,7’-dichlorofluorescein-diacetate (DCFH-DA) was used to measure ROS. Fluorescence increased when H2DCF-DA dye was oxidized by ROS to 2’,7’-dichlorofluorescein (DCF). DCF production was measured in a fluorometer, which indicated that DCF fluorescence intensity was significantly increased by the AgNPs. It was shown that the ROS generation in cells treated with AgNPs was 2.24-fold greater than that of the control, which was treated with hydrogen peroxide. This result confirmed that exposure to AgNPs induced the generation of ROS.4 FALL 2017 | PENNSCIENCE JOURNAL
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The Practical Applications of Nanotechnology By Tamsyn Brann
Humankind has always been transfixed by the incomprehensible. Our ancestors looked to the skies and attempted to decipher movements of the heavenly bodies with only their eyes and imagination. Today, we are armed with the technology to look not only outwards and see massive stars and planets but also inwards, at the scale of a billionth of a meter: nanoparticles.
Manipulation of these nanoparticles at the nanoscale with dimensions that measure between 1 and 100 nanometers, is the basis of nanotechnology. The reason nanotechnology is sweeping the scientific world stems from not only the unique size of the realm in which nanoparticles are found, but also their potential to make our lives easier. What if we could harvest the subtlest of movements to capture energy? Your phone could charge as it sits in your pocket; your shirt could measure your respiratory rate. 20 PENNSCIENCE JOURNAL | FALL 2017
Current research shows that we can tap energy sources from our immediate surroundings, especially from changes in temperature, light, and biochemistry. Researchers at Vanderbilt University have harvested and stored electricity in a battery using nanosheets of black phosphorus a few atoms thick that produce small electrical currents when manipulated, which can be done with minimal movement.1 The energy created can then be stored and used to power devices or digitized “smart� clothing.
FEATURES These nanosheets are an eminent 2D material that have been increasing in usage since its recent rediscovery. Essentially, black phosphorus is a rather stable allotrope of the element (compared to the white or red varieties). Phosphorene, which is a single layer of phosphorus atoms, is now a competitor to graphene—a single layer of graphite, or carbon, which is the most popular type of nanosheet used in research—due to its physical properties such as semiconductivity.2
area of wearable technology. Specifically, nanosheets could be built into textiles that wirelessly charge cell phones just by their proximity in the pocket of a specially-made pair of jeans. Fitness-oriented clothing could be sewn with builtin heart monitors or mechanisms to measure respiratory rate. Even the color of clothing could be changed with an application. No longer would you need an external device like a smart watch or phone to perform all of these functions; the device would be the clothing itself.
A key advantage of nanosheets is their ability to glean electricity from the extremely low frequency of human movement. Techniques in traditional piezoelectric generation which produce an electric current by applying stress such as pressure or heat to certain materials--can be used to extract energy from movement frequencies above 100 Hz.3 However, thanks to the quantum mechanics governing the physical nature of events at the nanoscale, these phosphorus nanosheets can produce electricity from movement as low as 10 Hz—slow enough to extract energy from regular human motion.
The integration of nanotechnology into modern life will be slow, as difficulties still exist with scaling nano items to usable sizes. Nanoscale components must be connected using converters that are at the millimeter or even centimeter scale in order to interact with the non-nano world. Although they are smaller than devices we are used to (computers, cell phones or even smart watches), they are monstrous on the nanoscale. In addition, physical and chemical difficulties emerge as well: quantum must meet classical mechanics, the ultra-small must operate in a human-scaled world and function well enough to be a reliable part of everyday reality.5
“No longer would you need an external device like a smart watch or phone to perform all of these functions; the device would be Nanotechnology’s foreseeable apthe clothing itself.” plication to everyday
Investigation of nanosheets is part of an advanced research program in the field of battery systems. For several years, the Vanderbilt team has investigated piezoelectric responses in battery materials which are bent or stretched and how the voltage produced by battery material changes when the nanosheets are placed under tension. Instead of using non-renewable resources to power our devices and fitness monitors, we could use our own motion as a power source.4 Nanotechnology is no longer mere theory; all of the hardware to make these seemingly fictional inventions exists. The energy collected by the nanosheets has almost endless potential in the
A single nanosheet
life indicates that the breach of the chemical and physical barriers of mechanics is imminent. Though we may marvel at the star-studded sky, there will soon exist an equally fascinating universe in our pockets.
References 1. Engineer’s ultrathin device harvests electricity from human motion. 2017. Vanderbilt University. 2. Eswaraiah, V., Zeng, Q., and Yi Long. 2016. Black phosphorus nanosheets: synthesis, characterization and applications. Small, 12:3480-3502. 3. Muralidharan, N., Li, M., and Rachel E. Carter. 2017. Ultralow Frequency Electrochemical–Mechanical Strain Energy Harvester using 2D Black Phosphorus Nanosheets. ACS Energy Letters, 2:1797-1803. 4. Kim, S. H., Haines, C. S., and Na Li. 2017. Harvesting electrical energy from carbon nanotube yarn twist. Science. 357:773-8. 5. What is Nanotechnology?. Georgia Tech University.
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Fighting Climate C
Title.T
One Molecule at a Time Climate change continues to be one of the most pressing environmental concerns of modern society. Since the nineteenth century, the average temperature of the Earth’s surface has increased by approximately 2 degrees Fahrenheit. Evidence from NASA suggests that the increase in temperature results from mankind’s growing production of carbon dioxide, a key cause of global warming. Continued emission of greenhouse gases could have devastating consequences, such as more frequent natural disasters and a loss of biodiversity.1 However, there may be ways to decrease or reverse the effects of climate change. One potential solution involves the use of nanoparticles, which could combat climate change by directly decreasing carbon dioxide levels and energy consumption.2
Nanoparticles can also be used to decrease fuel dependency by changing the design and structure of cars. Nanotechnology could confront climate change by decreasing carbon dioxide levels in the atmosphere. Scientists at the Center for Nanotechnology at the Indian Institute of Technology demonstrate that nanoparticles could be used to efficiently harvest carbon dioxide and convert it into other potentially useful products such as methanol or industrial materials. The unique properties of nanoparticles position them to be the most effective tool to reduce atmospheric carbon dioxide. For one, certain nanoparticles act as light-activated catalysts that allow efficient conversion of carbon dioxide without the use of other power sources. Additionally, their high surface-areato-volume ratio gives nanoparticles high reactive efficiency when interacting with carbon dioxide molecules.3 Researchers in various facilities, such as the CSIR–Indian
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Institute of Petroleum and the Lille University of Science and Technology, have created nanoparticles that utilize water and sunlight to remove carbon dioxide from the atmosphere and convert it into methanol for use in industry or scientific research.3 Originally, the industry believed that nanoparticles may be too expensive to be viable, but lowering costs makes nanoparticles a more feasible option. At Oak Ridge National Laboratory in Tennessee, researchers used nanoparticles to convert carbon dioxide to ethanol. These nanoparticles consisted of a small chip which had several spikes, each made of nitrogen and a carbon sheath along with copper. When the chip is immersed in water, carbon dioxide moves into the chip. Meanwhile, the copper conducts electricity and allows the carbon dioxide to be converted into ethanol4. These nanoparticles can be reused multiple times, making them more cost-efficient.3 Nanoparticles can also be used to decrease fuel dependency by changing the design and structure of cars. Automobiles account for approximately 28% of carbon dioxide emissions. Thus, finding alternative energy sources for automobiles is another compelling method for reducing climate change. While nanoparticles themselves are being investigated as power sources, another way to decrease automobile fuel consumption is to reduce the weight of cars. Cientifica estimates that a 10% decrease in the weight of a car is correlated with a 10% decrease in its consumption of fuel.5 Strong, lightweight materials such as nanotubes and nanoclay can be integrated into the structure of cars, creating lighter cars that consequently use less fuel and emit less carbon dioxide.5 Another potential use of nanoparticles involves increasing engine efficiency. Researchers have begun developing nanocatalysts specifically for this purpose. Nanocatalysts in car engines make the combustion of fuel more efficient
FEATURES
Change
.Title.
e
By Roshni Kailar
so that cars produce fewer emissions over time. Researchers have identified a chemical called cerium oxide, or ceria, which can help decompose fuel and subsequently decrease the amount of fuel used by a car.6 The use of nanoparticles to reduce car weight and increase the efficiency of fuel combustion would lead to a net decrease in the amount of fuel utilized and thus has the potential to ameliorate global warming.
These beneficial aspects of nanoparticles may decrease the catastrophic effects of global warming, including natural disasters and biodiversity loss, and help to mitigate its already widespread effects. While it might be difficult to imagine that nanoparticles have the potential to alleviate such a large-scale issue, nanoparticles can in fact reduce global warming through various applications. Other future applications of nanoparticles include directly decreasing the temperature of the environment or serving as a fuel source themselves. These beneficial aspects of nanoparticles may decrease the catastrophic effects of global warming, including natural disasters and biodiversity loss, and help to mitigate its already widespread effects.
References: 1. Global Climate Change. 2017. NASA. 2. Iyer, L.M., A.M. Burroughs, S. Anand, R.F.D. Souza, and L. Aravind. 2017. Polyvalent Proteins, a Pervasive Theme in the Intergenomic Biological Conflicts of Bacteriophages and Conjugative Elements. Journal of Bacteriology. 199. doi:10.1128/jb.00245-17. 3. Khullar, B. 2017. Nanomaterials Could Combat Climate Change and Reduce Pollution. Scientific American. doi:10.3897/bdj.4.e7720.figure2f. 4. Nanotech Wafer Turns Carbon Dioxide Into Ethanol. 2017. Popular Science. 5. Nanotechnologies to Mitigate Carbon Dioxide. 2010. Nanowerk. 6. Stouter, W. 2012. Nanoparticles as Fuel Additives. AzoNano
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An Interview with
Professor Charlie Johnson CONDUCTED BY Darsh Shah (C’19) Holistically speaking, what is your research about? We are studying so-called two-dimensional materials that are just one or a couple of atoms thick. We’re interested in making materials, we’re interested in understanding them, and then we’re also interested in trying to use them in various applications. Much of our focus lately has been on chemical sensor technologies. Your background is considerably heavy in physics. What applications do you find for nanomaterials in the field of medicine?
Professor A.T. Charlie Johnson is the current Director of the Nano/Bio Interface Center at the University of Pennsylvania and teaches in the Physics and Astronomy Department. Professor Johnson specializes in experimental condensed matter physics, specifically researching properties of graphene. Graphene is a unique one atom thick sheet of carbon that is being investigated for theoretical and practical properties that can be utilized in physics and biomedicine. An interesting research project carried out by Professor Johnson’s lab. Regardless of what specific usage of graphene is being investigated by Professor Johnson and his group, he is best known on campus for his large presence in outreach and his continual support of undergraduate research through programs such as PURM and by continually hiring undergraduates.
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We’re interested in applications in a variety of different areas, of which medical diagnostics is one good example. The fundamental idea is that there are different types of molecules, chemicals that your body makes that are indicative of disease states that could be anything from little snippets of DNA to proteins to metabolites. These molecules could start off in your blood, travel to all your other fluids, and finally reach the air. We want to figure out ways to detect these compounds and connect them to possible disease states. What do you find most exciting about your research? Well, the thing about research is that it’s always evolving, and you get excited about different advances along the way. Over the last four or five years, we have developed a longstanding interest in the diagnosis of ovarian cancer through volatile, airborne compounds that you can smell. Our progress in the area has made that project especially exciting. Just recently, we’ve also developed an interest in water contamination, a project in which we’re getting some very intriguing and promising results, so I am definitely excited about that as well. Our journal’s theme this semester is “Beyond the Nano.” What role have nanomaterials played in your research? Has the difference in scale been impactful for some of the bigger questions we face today? Essentially all the materials we study in my laboratory are just an atom or two thick in size. At the moment, we’re focused on trying to figure out how to take these things and turn them into useful technologies. I think we’re at the transition between understanding nanomaterials to designing and using them. Of course, there are a few fundamental issues getting in our way to applying nanomaterials, but overall, we’re making progress.
For a considerable amount of time, your research group has studied and examined something called “Beyond Graphene.” Could you elaborate on what exactly that is?
Your topics of research seem to require a strong background in fundamental physics and biology. What advice do you have for students who are eager to pursue research with you?
Graphene is unique in that it’s a one-atom-thick carbon sheet that was first discovered and worked on experimentally beginning in 2004. And then, there was the development of a way to make large-area samples of graphene in 2009. Interestingly, in the U.S., a major decision was made that determined that graphene alone wasn’t enough. As a result, researchers have been pushed to look for materials beyond graphene, for many reasons. Graphene is a material with properties in between those of a metal and a semiconductor, whereas other two-dimensional materials, boron nitride for example, are insulators. Beyond that, there are newer classes of nanomaterials, three atoms thick, that possess all the electronic functionality that we know about. Some of these materials are semiconductors that can be used as transistors. Others can emit light very readily, which graphene cannot do. Some have magnetic properties and spintronic qualities and many other attributes that graphene doesn’t have. So, “Beyond Graphene” refers to these different types of nanomaterials that perhaps could be combined with graphene to realize all sorts of electronic and optical technologies.
I have always had a good number of undergraduates working with the group. I find Penn undergraduates to be very talented: they really manage to get things done, and it’s definitely a blast to have them on board. Personally, I look for someone who has taken some physics and biology because, as you know by now, my work involves a considerable amount of chemistry and biochemistry, and the team has begun to interface with people at the medical school. So, someone with a generally strong science background is preferred, and especially someone who is excited about the problems that we work on in the lab. We also like undergraduates who enjoy working in a team and brainstorming ideas together with other team members. The lab is relatively large, so working off by yourself isn’t the preferred approach. We really look for that sort of personality fit, and luckily we have been able to work with a large number of very talented undergraduates over the years.
Photo Credit: ExtremeTech
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Effects of Anthropogenic Acoustic Interference on Female Response to Male Calls in the Strawberry Poison Frog (Oophaga pumilio) Reena Debray, Duke University, Durham, NC, USA Nicole Oppenheim, Washington University in St. Louis, St. Louis, MO, USA Many species rely on acoustic signaling to find and evaluate mates. Extraneous noises can disrupt reception and processing of these signals. In the presence of noise, signal emitters often adjust the acoustic or temporal parameters of their calls, but the impacts of acoustic interference on signal receivers are not well understood. We examined the effects of anthropogenic acoustic interference on female movement towards recordings of calling males in the strawberry poison frog (Oophaga pumilio). We presented 35 females with each of the following treatments: no noise (control), conspecific male call, and conspecific male call with acoustic interference from a weed whacker. Both the male call and the weed whacker noise were played at a volume of approximately 50 dB relative to the center of the test arena. Females spent more time in the half of the arena closer to the speaker when only the male call was playing but exhibited no phonotaxis compared to the control when the call and weed whacker were played simultaneously. The lack of response indicates that females were unable to recognize the male signal or unwilling to approach the source of the weed whacker noise. Our findings suggest that noise pollution may affect signal reception and processing in nearby animal populations, potentially reducing reproductive success.
Introduction Massachusetts is famous for its shellfish industry, which Sexual selection is composed of two components, intrasexual competition and mate choice, both of which are mediated by signaling. For a signal to be effective, it must be received and understood by the receiver. In the process of mate choice, the receiver is usually the female of the species. Reception and processing of acoustic signals can be disrupted by extraneous noises, including conspecific calls (Wasserman 1977), heterospecific calls (Ficken et al. 1974), natural abiotic factors such as wind (Wahlberg and Westerberg 2005), and anthropogenic sounds such as traffic noise (Parris et al. 2009). Calling is energetically expensive, and calling in a noisy environment can be particularly costly. The aerobic metabolism of the grey tree frog (Hyla versicolor) increases linearly with call rate and duration (Taigen and Wells 1984). In these frogs, mean metabolic rates during short periods of vigorous locomotor exercise were only 62% of peak metabolic rates during calling, which reveals that calling is one of the most energetically expensive activities anurans undertake regularly (Taigen and Wells 1984). To avoid expending energy on ineffective calls, males may adjust the acoustic parameters of their calls. Male túngara frogs (Physalaemus pustulosus) increase call volume and complexity in response to chorus noise or white noise in the same frequency range as their call (Halfwerk et al. 2016). Black-capped chickadees (Poecile atricapillus) respond to frequency-masking tones by shifting their song frequencies (Goodwin and Podos 2012). Signal emitters can also adjust the temporal parameters of their calls in response to acoustic interference. The cotton-top tamarin (Saguinus oedipus), when faced with predictable, intermittent, and loud white noise, restricts calls to silent periods (Egnor et al. 2007). Strawberry poison dart frogs (Oophaga pumilio) decrease call rates during audio playbacks of cicadas, crickets, or a sympatric frog call (Wong et al. 2009). Johnstone’s Whistling Frog males (Eleutherodactylus johnstonei) intercalate their calls with 26 PENNSCIENCE JOURNAL | FALL 2017
those of conspecifics (Tárano and Carballo 2016). These behaviors may help animals that rely on acoustic signals compensate for the effects of a noisy environment. Although behavioral plasticity in calling most likely evolved in response to acoustic interference from natural noises, many species use similar techniques to avoid overlap with anthropogenic noise. In response to traffic noise, Grey shrike-thrushes (Colluricincla harmonica) sing at a higher frequency and the Cauca poison frog (Andinobates bombetes) calls less often (Parris and Schneider 2009, Vargas-Salinas and Amézquita 2013). Similarly, painted chorus frogs (Microhyla butleri), sapgreen stream frogs (Rana nigrovittata), and banded bullfrogs (Kaloula pulchra) decrease their calling rates when airplanes fly overhead, thus minimizing acoustic interference (Sun and Narins 2004). Triangle treefrogs (Dendropsophus triangulum) instead increase their calling rates in response to construction and traffic sounds, possibly to overcome the interfering noise (Kaiser and Hammers 2008). Comparatively less is known about the behavioral responses of signal receivers to acoustic interference. In species that rely on acoustic sexual signaling, females often face the “cocktail party problem,” or the difficulty of separating a single acoustic signal from a noisy background (Bee and Micheyl 2008). A decreased ability to understand individual signals may change the response of the female to male calls. Female crickets (Gryllus bimaculatus) normally prefer to spend time in the section nearest to the speaker playing a male call, but this preference disappears when a traffic noise is played at the same time (Schmidt et al. 2014). This reveals that the acoustic interference could decrease their ability to locate mates effectively (Schmidt et al. 2014). In frogs, calls may allow females to identify conspecific males in a chorus of both conspecifics and heterospecifics (Bee 2008, Ryan and Rand 1993, Wollerman 1999), although picking one signal out of a chorus presents a challenge. When given the choice between just a chorus and a chorus with a conspecific male call, female hourglass tree frogs (Hyla ebraccata) prefer the chorus with the conspecific call at signal-to-noise ratios of +6dB and +3dB
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Figure 1. The amplitude and frequency of the call of an Oophaga pumilio male as compared to that of a weed whacker played at the same volume. These images reveal both temporal and frequency overlap of the noises, leading to acoustic interference when they are played at the same time. (Wollerman 1999). They no longer exhibit a preference for either stimuli at +1.5 or 0 dB signal- to-noise ratios. Thus, background noise at the same volume as the signal can impede successful signal reception and processing in this species (Wollerman 1999). Similarly, female grey tree frogs (Hyla chrysoscelis) are less successful at distinguishing between conspecific and heterospecific calls in the presence of a chorus (Bee 2008). Female frogs also rely on calls to discriminate between male conspecifics (Ryan 1980, Wollerman and Wiley 2002). The female hourglass tree frog (Hyla ebraccata) normally discriminates between conspecific males on the basis of dominant frequency, preferentially choosing males with lower frequency calls. Moderate levels of background noise decrease their ability to discriminate between different conspecific males. During periods with high levels of background noise, the frogs no longer discriminate between conspecifics and instead seek out males calling at the average frequency for the species (Wollerman and Wiley 2002). In this study, we examined the effects of anthropogenic noise interference on female phonotaxis in response to male mating calls in the Neotropical poison frog Oophaga pumilio. We presented female frogs with three treatments: no noise (control), a conspecific male call, and a conspecific male call with acoustic interference from a weed whacker. For the purposes of this study we held the male call constant, thus eliminating the variable of male behavioral changes in response to acoustic interference. We ex-
pected that acoustic interference from the weed whacker would reduce movement of females towards the source of the male call. Methods Location and study system We conducted this study in La Selva Biological Reserve from April 24-27, 2017. The reserve is located in the Heredia Province of Costa Rica, near the transition from the foothills of the Central Volcanic Cordillera to the Caribbean coastal plain (Matlock and Hartshorn 1999). La Selva encompasses 1,536 hectares of lowland tropical wet forest (sensu Holdridge 1947), which includes elevations from 35-150 meters (Matlock and Hartshorn 1999). La Selva receives on average 4,210 millimeters of rain per year, with no particular dry season, although the least rain falls from February to April (Matlock and Hartshorn 1999). Yearly, the diurnal temperature varies less than 3 째C, from an average of 27.1 째C in August to 24.7 째C in January (Matlock and Hartshorn 1999). On a daily basis, the temperature can fluctuate 6-12 째C (Matlock and Hartshorn 1999). Sampling was conducted along trails through old-growth forest, old secondary forest, and an abandoned plantation. The strawberry poison frog, Oophaga pumilio (Dendrobatidae) is found commonly in the terrestrial ecosystems in La Selva, with population densities reaching around 827/ hectares in the wet season (Savage 2002). They range from eastern Nicaragua through the lowlands of Costa Rica and into northwestern Panama (Savage 2002), inhabiting undisturbed forest, cacao plantations, and abandoned clearings at elevations from 0-940 m (Savage 2002). These
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Figure 2. Experimental arena setup. The trial started with the frog in the middle “starting zone� and over the course of 5 minutes we recorded the amount of time the individual spent in the half of the arena near the speaker and the quarter of the arena nearest to the speaker. are small frogs, with adults reaching 17.5-24 millimeters in length (Savage 2002). Despite their small size, they are well-studied due to their bright colors, high population density, diurnal schedule, and interesting reproductive system (Savage 2002). Males defend territories 2-3 meters in size (Bunnell 1973) and call to females from fallen logs, stumps, and leaf litter during the daytime (Savage 2002). When a receptive female approaches a calling male, the male leads the female to an oviposition site in the leaf litter and fertilization occurs (Savage 2002). Females tend to favor the closest calling male regardless of call characteristics (Meuche et al. 2013) so we do not expect substantial variation in female response based on their attraction to the call. Further, although this species is most abundant during wetter months, mating can take place throughout the year (Savage 2002). Unlikely many other anuran species, female strawberry poison dart frogs exhibit very high mating rates, with about 4-5 days between matings (Prohl and Hodl 1999). Data collection Oophaga pumilio females were collected between the hours of 8:00 A.M. and 12:00 P.M. on April 24 (11 females), April 25 (10 females), April 26 (10 females), and April 27 (4 females), 2017. Females were identified based on the absence of the darkened gular region characteristic of males (Savage 2002), housed individually in large plastic bags with a damp paper towel, and returned to the site of capture within 48 hours. Each female was observed in three ten-minute behavioral trials: 1) no noise stimulus, 2) only the sound of a calling male, and 3) the same calling male and the sound of a weed whacker (a common source of anthropogenic noise at La Selva Biological Station). The Oophaga pumilio male call was a 10-second clip from a recording made at La Selva Biological Station in 2014 by Michelle Hill. The weed whacker sound was a 15-second clip recorded in 2015 by Sound Effects. When both recordings were played repeatedly from a computer at a volume of 50-60 dBA relative 28 PENNSCIENCE JOURNAL | FALL 2017
to the center of the arena, temporal and spectral overlap occurred (Figure 1). All trials were performed in one of two identical 52.5 cm x 36.0 cm x 20.0 cm open arenas constructed from cardboard. During the first three minutes of each behavioral trial, the female was allowed to explore and acclimate to the arena. After this, a condiment cup was placed over the female to restrict her movement, and one of three treatments (no noise, male call, or male call with weed whacker) was played from a laptop computer at the side of the arena (Figure 2). The treatment was played continuously for the remainder of the trial. After allowing two minutes of acclimation to the treatment, we lifted the cup and began a five-minute observation period. The length of the arena was divided into a 6-cm starting zone, as well as halves and quarters, to quantify the extent to which females approached the side of the arena from which the sound was being played. We systematically varied the order in which a female experienced the three treatments and the side of the arena from which the noise was played. We recorded the total number of seconds spent in the starting zone, the half of the arena closest to the speaker, and the quarter of the arena closest to the speaker over the course of the trial. Statistical analysis To assess the effect of the noise treatments on the amount of time females spent in each section of the arena, we conducted mixed model multiple regressions with individual frog as a random effect and noise treatment, the observer, the location of the trial (room 1 or room 2), the location of the speaker (left or right side of the arena), and the trial number for the female (first, second, or third) as fixed effects. The response variables were each of the following: number of seconds spent in the starting zone of the arena, number of seconds spent in the half that was closest to the speaker, and number of seconds spent in the quarter that was closest to the speaker. All analyses were conducted with JMP statistical software (SAS Institute 2016).
RESEARCH Results The amount of time that females spent in the closest half of the arena to the speaker was predicted by the noise treatment (P = 0.068), but not by trial number (P = 0.348), observer (P =0.246), trial location (P =0.971), or location of the speaker (P = 0.170) in a mixed model multiple regression with individual frog as a random effect (R2 = 0.526). Females spent more time in the half of the arena closest to the speaker during the male call treatment than during the male call with interference treatment or the control treatment, which did not differ from each other (Table 1, Figure 3). The amount of time that females spent in the closest quarter of the arena to the speaker was not predicted by the noise treatment (P = 0.413), trial number (P = 0.728), observer (P = 0.438), trial location (P =0.538), or location of the speaker (P = 0.565) in a mixed model multiple regression with individual frog as a random effect (R2 = 0.511, Table 2, Figure 4). The amount of time that females spent in the starting zone of the arena was predicted by trial number (P = 0.016), but not by the noise treatment (P = 0.367), observer (P =0.926), trial location (P = 0.338), or location of the speaker (P = 0.451) in a mixed model multiple regression with individual frog as a random effect (R2 = 0.636). Females spent less time in the starting zone during their first trials than during second or third trials, which did not differ from each other (Table 3, Figure 5).
Discussion In species with acoustic sexual signaling, noise interference can change the behavior of signal transmitters and signal receivers. Signal transmitters may increase call amplitude or call rate to make themselves heard (Kaiser and Hammers 2009, Halfwerk et al. 2015), increase or decrease call frequency to minimize acoustic overlap with the source of the interference (Parris and Schneider 2009), decrease call rate to reduce energetic investment in signaling (Sun and Narins 2005), or adjust call pattern to call more during gaps in the interfering noise (Brumm 2006, Tรกrano and Carballo 2016). Less is known about the effects of acoustic interference on the behavior of signal receivers, though some evidence indicates that positive phonotaxis (Nityananda and Bee 2011, Schmidt et al. 2014) or discrimination between potential mates (Wollerman and Wiley 2002) may be reduced in the presence of noise. Given the role of acoustic cues in mate recognition and mate choice in a variety of taxa (Searcy and Andersson 1986, Andersson 1994), it is important to understand the potential effects of noise pollution on reproductive success in these species. Reduced female phonotaxis in the presence of noise This study found that acoustic interference reduced female response to male mating calls in Oophaga pumilio. Female positive phonotaxis was greater in the male call treatment than in the control treatment, indicating a response to the acoustic stimulus. During the male call with interference treatment, however, positive phonotaxis was no greater than in the control treatment. This may indicate
Table 1. Results of a mixed model multiple regression testing the relationship of speaker location, observer, noise treatment, trial room, and trial number to the amount of time a female Oophaga pumilio spent in the half of an arena nearest to a speaker during three different treatments: no sound, male call, and male call with weed whacker. The noise treatment of the male call was a significant predictor. Data were collected at La Selva Biological Station from April 2427, 2017. N=35. FALL 2017 | PENNSCIENCE JOURNAL
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Table 2. Results of a mixed model multiple regression testing the relationship of speaker location, observer, noise treatment, trial room, and trial number to the amount of time a female Oophaga pumilio spent in the quarter of an arena nearest to a speaker during three different treatments: no sound, male call, and male call with weed whacker. There are no significant relationships. Data were collected at La Selva Biological Station from April 24-27, 2017. N=35.
Table 3. Results of a mixed model multiple regression testing the relationship of speaker location, observer, noise treatment, trial room, and trial number to the time the female spent in the starting area in the center of an arena during three different treatments: no sound, male call, and male call with weed whacker. Trial number was a significant predictor. Data were collected at La Selva Biological Station from April 24-27, 2017. N=35. 30 PENNSCIENCE JOURNAL | FALL 2017
RESEARCH masking effect occurred. In frogs as well as bush crickets, background noise can decrease the ability of the female to detect males. For Conocephalus brevipennis, random noise within 2 dB of call volume significantly interfered with phonotaxis, implying signal loss (Bailey and Morris 1986). A neotropical treefrog (Hyla ebraccata) could locate male calls when they were played 3 times louder than the chorus noise but not when they were only 1.5 times louder (Wollerman and Wiley 2002). Our signal to noise ratio was approximately 1:1 in amplitude, which may have impaired call detection in Oophaga pumilio. Frequency differences also help females receive and process male calls in a noisy environment. In a variety of taxa, frequency overlap can interfere with perceptual segregation of auditory cues. For example, female gray tree frogs (Hyla chrysoscelis) increasingly respond to a synthetic conspecific call in the presence of a distractor noise as the frequency difference between the conspecific call and the distractor noise increases (Nityananda and Bee 2011). In our experiment, the partial frequency overlap between the male call and the interfering noise may have prevented fe-
signals in a noisy environment. At a signal to noise ratio of 1 to 3, Grey tree frogs (Hyla versicolor) could chose a conspecific call when it was separated from the noise by 90°, but failed to do so when the two sounds were only separated by 15° (Bee 2008). The 0° separation in our experiment could therefore have inhibited the ability of the female to understand the male signal. Another possible explanation for the reduction in phonotaxis is that females were hesitant to approach the weed whacker noise. There is some evidence of animals avoiding noisy habitats. For example, songbird density declines by two-thirds near an array of speakers emitting traffic noises (Ware et al. 2015). Interestingly, we observed a reduction in female response to male calls with an interfering noise of only 50-60 dBA. To someone operating a weed whacker, the volume is approximately 94-96 dBA (Chepesiuk 2005); thus, the interfering noise treatment in our study represents the sound of a weed whacker from much farther away. This indicates that the effects of anthropogenic noise pollution can extend to animal populations at a distance.
Figure 3. Female Oophaga pumilio spent significantly more time in the half of the arena closest to a speaker playing a male call than they did when the speaker was silent or playing a male call at the same time as a weed whacker noise. Error bars show the standard error. Data were collected at La Selva Biological Station from April 24-27, 2017. N=35.
males from recognizing the male call as separate from the noise of the weed whacker. On the other hand, noise pollution has been shown to reduce female response in some species even when the stimulus and the interfering noise do not overlap in frequency (Schmidt et al. 2014). A possible explanation for this behavior is that extraneous noise can act as a distraction (Francis and Barber 2013). Hermit crabs tend to respond to visual threats more quickly when noise is played simultaneously. Their response time increased when the noise had a longer duration and amplitude, revealing that certain characteristics can make sound more distracting (Chan et. al. 2010). The noise we played was relatively high in amplitude and duration and thus may have acted as a distraction, drawing the attention of the females away from the male call. Females also use spatial separation to process acoustic
Acoustic interference does not affect phonotaxis at closest approach Though the noise treatment influenced the amount of time females spent in the closest half of the arena to the speaker, it did not predict the amount of time females spent in the closest quarter of the arena. One likely explanation for the lack of female preference at closest approach was that the female did not see a calling male. In many other frog species, the response of males or females to recorded calls increases when the call is accompanied by a model frog with a pulsating vocal sac (Narins et al. 2002, Taylor et al. 2008). Though this preference has not been explicitly tested in Oophaga pumilio, females identify mates using visual as well as acoustic signals (Summers et al. 1999). This suggests that Oophaga pumilio females use acoustic cues to locate calling males within a general radius, but require a visual cue to approach further.
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Figure 4. Female Oophaga pumilio did not spend any more time in the quarter of the arena closest to the speaker when the speaker was just playing a male call as opposed to silence or a male call and weed whacker noise simultaneously. Error bars show the standard error. Data were collected at La Selva Biological Station from April 2427, 2017. N=35.
Figure 5. Female Oophaga pumilio spent significantly more time in the starting zone of an arena during their first behavioral trial than they did during the second or third trial. Error bars show the standard error. Data were collected at La Selva Biological Station from April 24-27, 2017. N=35.
Effect of trial order on female activity Females remained in the starting zone of the arena for more time during their second or third trials than during their first trial. This effect is likely attributable to fatigue or a lower desire to explore an environment that was no longer novel. This pattern underscores the importance of considering order effects when testing individuals multiple times in behavioral studies. Conclusions In this study, a single, non-varying male call was used in both the call-only and call-with- noise treatments. In reality, males sometimes adjust their calling parameters or calling rates in the presence of noise. Oophaga pumilio males reduce their call rates in response to acoustic interference from cicadas, tree crickets, or ground crickets (Wong et al. 2009), which suggests that a common strategy in this species is to lessen signaling efforts. Given that lower call rates are associated with reduced male reproductive success in this species (Prohl 2003), if males respond similarly to anthropogenic sounds as to natural sources of noise interference, this adjustment would likely reduce reproductive rates during periods of high anthropogenic noise. However, the plasticity of male frog calls may mitigate some of the negative impacts of acoustic interference. For example, 32 PENNSCIENCE JOURNAL | FALL 2017
in a chorus of frogs in Thailand, three species decreased call rates during airplane flyovers, while one species took advantage of this localized lull to increase call rates and stick out from the chorus (Sun and Narins 2003). If Oophaga pumilio males behave similarly and preferentially call during breaks in anthropogenic noise, they may be able to compensate for the effects of acoustic interference. Future studies could take male call plasticity into account by using real males to produce acoustic signals in the presence and absence of anthropogenic noise. The results of this study demonstrate that anthropogenic noise interference can decrease the response of signal receivers to an acoustic cue. Thus, given the importance of acoustic signaling for reproduction in this species and many others in a variety of taxa, anthropogenic noise pollution could lead to population declines in or near areas inhabited by humans. References Andersson, M.B. 1994. Sexual selection. Princeton University Press. Bee, M.A. 2008. Finding a mate at a cocktail party: Spatial release from masking improves acoustic mate recognition in grey treefrogs. Animal Behavior 75(5): 1781-1791. Bee, M.A. and C. Micheyl. 2008. The cocktail party problem: what
RESEARCH is it? How can it be solved? And why should animal behaviorists study it? Journal of comparative psychology, 122(3): 235. Brumm, H. 2006. Signalling through acoustic windows: nightingales avoid interspecific competition by short-term adjustment of song timing. Journal of Comparative Physiology A, 192(12): 12791285. Bunnell, P. 1973. Vocalizations in the territorial behavior of the frog Dendrobates pumilio. Copeia: 277-284. Chan, A.A.Y.H., W.D. Stahlman, D. Garlick, C.D. Fast, D.T. Blumstein, A.P. Blaisdell. 2010. Increased amplitude and duration of acoustic stimuli enhance distraction. Animal Behaviour 80(6): 1075-1079 Chepesiuk, R. 2005. Decibel hell. Environmental health perspectives: A35-A41. Egnor, S.E.R., J.G. Wickelgren, M.D.Hauser. 2007. Tracking silence: adjusting vocal production to avoid acoustic interference. Journal of Comparative Physiology A 193 (4): 477-483 Ficken, R.W., M.S. Ficken, and J.P. Hailman. 1974. Temporal pattern shifts to avoid acoustic interference in singing birds. Science, 183(4126): 762-763. Francis, C.D. and J.R. Barber, 2013. A framework for understanding noise impacts on wildlife: an urgent conservation priority. Frontiers in Ecology and the Environment, 11(6): 305-313. Goodwin, S.E. and J. Podos. 2012. Shift of song frequencies in response to masking tones. Animal Behaviour 85:435-440. Bailey, W.J. and G.K. Morris. 1986. Confusion of phonotaxis by masking sounds in the bushcricket Conocephalus brevipennis. Ethology 73: 19-28 Halfwerk, W., A.M. Lea, M.A. Guerra, R.A. Page, and M.J. Ryan. 2015. Vocal responses to noise reveal the presence of the Lombard effect in a frog. Behavioral Ecology: arv204. Holdridge L.R. 1947. Determination of the world plant formations from simple climatic data. Science 105: 367-368. Kaiser, K. and J.L. Hammers. 2009. The effect of anthropogenic noise on male advertisement call rate in the neotropical treefrog, Dendropsophus triangulum. Behavior, 146(8): 1053-1069. Matlock, R.B. and G.S. Hartshorn. 1999. La Selva Biological Station (OTS). Bulletin of the Ecological Society of America, 80(3): 188-193. Meuche, I., Brusa, O., Linsenmair, K.E., Keller, A. and Pröhl, H., 2013. Only distance matters– non-choosy females in a poison frog population. Frontiers in zoology, 10(1), p.29. Narins, P.M., W. Hödl, and D.S. Grabul. 2003. Bimodal signal requisite for agonistic behavior in a dart-poison frog, Epipedobates femoralis. Proceedings of the National Academy of Sciences, 100(2): 577-580. Nityananda, V. and M.A. Bee. 2011. Finding your mate at a cocktail party: frequency separation promotes auditory stream segregation of concurrent voices in multi-species frog choruses. PLoS One, 6(6): 21191. Parris, K. and A. Schneider. 2009. Impacts of traffic noise and traffic volume on birds of roadside habitats. Ecology and society, 14(1). Parris, K., M. Velik-Lord, and J. North. 2009. Frogs call at a higher pitch in traffic noise. Ecology and Society, 14(1). Pröhl, H. 2003. Variation in male calling behaviour and relation to male mating success in the
strawberry poison frog (Dendrobates pumilio). Ethology, 109(4): 273-290. Prohl, H. and W. Hodl. 1999. Parental investment, potential reproductive rates, and mating system in the strawberry dart-poison frog, Dendrobates pumilio. Behavioral Ecology and Sociobiology 46(4) 215-220. Ryan, M.F. 1980. Female Mate Choice in a Neotropical Frog. Science 209:523-525 Ryan, M.J. and A.S. Rand. 1993. Species Recognition and Sexual Selection as a Unitary Problem in Animal Communication. Evolution 47(2):647-657 SAS Institute. 2016. JMP 13. 0. 0. SAS Institute Inc., Cary, North Carolina, USA. Savage, J.M. 2002. The Amphibians and Reptiles of Costa Rica. University of Chicago Press. 386-388. Schmidt, R., A. Morrison, and H.P. Kunc. 2014. Sexy voices–no choices: male song in noise fails to attract females. Animal Behaviour, 94: 55-59. Searcy, W.A. and M. Andersson. 1986. Sexual selection and the evolution of song. Annual Review of Ecology and Systematics, 17(1): 507-533. Summers, K., R. Symula, M. Clough, and T. Cronin. 1999. Visual mate choice in poison frogs. Proceedings of the Royal Society of London B: Biological Sciences, 266(1434): 2141-2145. Sun, J.W. and P.M. Narins. 2005. Anthropogenic sounds differentially affect amphibian call rate. Biological conservation, 121(3): 419-427. Taigen, T.L. and K.D. Wells. 1984. Energetics of vocalization by an anuran amphibian (Hyla versicolor). Journal of Comparative Physiology B 155(2): 163-170. Tárano, Z. and L. Carballo. 2016. Call intercalation in dyadic interactions in natural choruses of Johnstone’s whistling frog Eleutherodactylus johnstonei (Anura: Eleutherodactylidae). Behavioural processes, 126: 55-63. Taylor, R.C., B. Klein, J. Stein. and M.J. Ryan. 2008. Faux frogs: multimodal signalling and the value of robotics in animal behaviour. Animal Behaviour, 76(3): 1089-1097. Vargas-Salinas, F. and A. Amézquita. 2013. Traffic noise correlates with calling time but not spatial distribution in the threatened poison frog Andinobates bombetes. Behaviour 150(6): 569584 Wahlberg, M. and H. Westerberg. 2005. Hearing in fish and their reactions to sounds from offshore wind farms. Marine Ecology Progress Series, 288: 295-309. Ware, H.E., C.J. McClure, J.D. Carlisle. and J.R. Barber. 2015. A phantom road experiment reveals traffic noise is an invisible source of habitat degradation. Proceedings of the National Academy of Sciences, 112(39): 12105-12109. Wasserman, F.E. 1977. Intraspecific acoustical interference in the white-throated sparrow (Zonotrichia albicollis). Animal Behaviour, 25: 949-952. Wollerman, L. and R.H. Wiley. 2002. Background noise from a natural chorus alters female discrimination of male calls in a Neotropical frog. Animal Behaviour, 63(1): 15-22. Wong, S., H. Parada, and P.M. Narins. 2009. Heterospecific acoustic interference: effects on calling in the frog Oophaga pumilio in Nicaragua. Biotropica, 41(1): 74-80.
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Characterizing Backscatter Variability Using UAVSAR Abigail Lee NASA Jet Propulsion Laboratory University of Pennsylvania, Philadelphia, PA 19104 With the availability of long time-series of UAVSAR data, it is now possible to examine, characterize, and analyze statistics of Earth change over time as viewed by synthetic aperture radar. By developing and using radar processing software, statistical models of backscatter variability were created using UAVSAR data in preparation for the NISAR mission. Results revealed a correlation between low σ [dB] (variability of the backscatter cross section) and high biomass in the Sacramento Delta (σ = 1.50), whereas estimation error was higher in areas of low biomass such as water (σ = 2.10) and grassland (σ = 2.33). Mean backscatter [dB] was also much more variable in uniform-looking areas of forest than previously estimated, changing as much as 5 dB for a change in pixel position of 50 pixels. Finally, when comparing number of looks with the mean backscatter, results showed that a change of 4 looks to 245 looks resulted in a change in backscatter of about 2 dB; while in the change from 245 to 320 looks, the mean backscatter changed only .2 dB. Therefore, in future performance models for high biomass, it would be beneficial to use box sizes of over 250 looks for similar forest environments.
Introduction The NASA Jet Propulsion Lab plans to launch the NASAISRO Synthetic Aperture Radar (SAR), or NISAR mission to study land surface change, especially ecosystem disturbances. Detailed observations will reveal important information about Earth’s surface state and change; measurements will be made to reveal minute forces on the surface, especially variability of biomass, far more comprehensively than from any other previous measurement method. The NISAR mission will deliver unprecedented global maps of L-band HH/HV backscatter every 12 days with resolution ranging from a couple to tens of meters in support of ecosystem, solid Earth, and cryosphere science and applications. Understanding and modeling the temporal variability of L-band backscatter over the scale of years, months and days is critical for developing retrieval algorithms that can robustly extract the biophysical variables of interest (e.g., forest biomass, soil moisture, etc.) from NISAR time series.
Figure 1, which was processed in a previous study, shows that for a randomly chosen pixel in a uniformly arranged area of forest terrain, there was an average temporal standard deviation of 1.25 dB and an average β0 of about -13 dB. It is also important to note that there was no visible trend over the five-year period nor a correlation within hour of day. This study focused on the five-year time series of ~60 JPL/ UAVSAR polarimetric images collected near the Sacramento Delta to characterize the interannual, seasonal, and short-scale variability of the L-band polarimetric backscatter for a broad range of land cover types. Underlying Theory Backscatter Conventions Radar backscatter β is expressed as a ratio of scattered power Ps to incident power Pi at the ground level, where β = Ps/Pi. Aβ is defined as the reference area in the slant range plane, and β0 is defined as β0 (beta-naught) backscatter, where β0 = β/Aβ.
Figure 1: Temporal, multilooked plot showing how backscatter changes over time for a five-year period of the Sacramento Delta.
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Figure 2: Schematic showing examples of different levels of backscatter for different types of terrain.
Figure 3. Google Earth Image of the Sacramento Delta on the left, with the processed radar swath overlaid on the right.
Furthermore, the number of looks is an important parameter in statistical modeling of multilooked SAR images. This describes the degree of averaging applied to SAR measurements during data formation and post-processing.
Figure 4. Plots showing the temporal change of backscatter for low biomass, grassland, on the left, and temporal change of backscatter for an urban area on the right. After initial studies were done (Fig. 1) on forest terrain, comparisons were made in a similar statistical analysis for grassland and urban areas. The grassland sample analyzed had an average β0 of -23.55 dB, and the urban area sample had an average β0 of approximately -9 dB. Both of these observations align with theory ( Fig. 4) As shown in in Figure 1, forest terrain had an average β0 of -13 dB. Therefore, grassland had lower backscatter than forest terrain, which in turn had lower backscatter than urban areas.
Statistical Analysis of the Sacramento Delta Case Study Backscatter for Different Types of Terrain Figure 3 shows a geocoded intensity radar image overlaid on top of Google Earth for the Sacramento Delta. Red areas indicate high backscatter and blue areas indicate low backscatter. This aligns with what theory would suggest, as smoother areas for example, have low backs.
Number of Looks Finding an ideal number of looks when studying a small area is important because too many looks will over-average an area, but not enough looks may be an inadequate sample size. This study was done to calculate an ideal range of looks.
All units are in decibels [dB], so in backscatter increase or decrease, multiplying by 2 would increase the backscatter 10 times. This is significant when comparing power levels.
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Figure 5. Six plots comparing number of looks with β0. The first four show randomly chosen uniform-looking forest terrain, and the last two show short grass and water.
Figure 6. Plots showing change in β0 for different pixel positions. The last visual taken from Google Earth shows how pixel position was chosen, with a range of 100 pixels both up and down. Row was up/down and Col was left/right. 36 PENNSCIENCE JOURNAL | FALL 2017
RESEARCH Change in Pixel Position For row pixel position, a change of 50 pixels resulted in a change in β0 of ~ 5 dB. Similarly, a change in column position resulted in a change of ~ 4 dB. This rejected former ideas about variability of backscatter and pixel position in uniform forest areas; forest terrain was much more variable than previously thought. Future Work: Analyzing Terrain Slope Correction Background Terrain variations, such as mountains in the Sacramento Delta, affect the position of a given point on the Earth’s surface and consequently the brightness of the radar return. Therefore, without slope correction, backscatter created by terrain may overwhelm weaker, but more significant, thematic land cover such as biomass. Subsequently, comparison of backscatter from multiple satellites or tracks loses significance. In order to normalize backscatter return, a new method was introduced that integrates terrain variations with the new concept of γ0 backscatter, converted directly from β0, which had been used previously.
Figure 7. On the top, schematic showing Incidence Angle relative to the flight path, and Projection Angle (Look Angle). On the bottom, schematic explaining range and azimuth In Figure 4, the average β0 began to average out at around 250 looks for each plot. Additionally, the average standard deviation for each plot was 1.28, 1.55, 1.51, and 1.54, respectively. Conversely, for short grass or low biomass, the average β0 began to average out at around 50 looks with an average standard deviation of 2.33. Finally, the β0 for water or zero biomass began to average out at around 200 looks, with an average standard deviation of 2.10. These statistics suggest that high biomass is directly correlated with lower estimation error. In future performance models for high biomass, it would be beneficial to use box sizes of over 250 looks for similar forest environments.
Methods First, an SLC was converted into a power image and then multi-looked. The incidence angle band containing latitude and longitude coordinates was also multi-looked by the same amount, in this case at 7 range and 35 azimuth looks (Fig. 6). Each azimuth line is parallel to the flight path and the range is perpendicular to the azimuth direction. To convert to γ0, the following formula was introduced:
where θi is the local incidence angle and ψ is the projection angle (Fig. 6). Finally, γ0 was converted to dB units and HV gamma-nought statistics was performed. Preliminary Results After correcting for incidence angle, it became apparent that overall backscatter for the Sacramento Delta decreased from -19.85 dB to -18.31 dB. In addition, standard deviation decreased from 6.59 dB to 6.50 dB. Furthermore, in alignment with past models, higher backscatter
Fig. 8. On the left, uncorrected backscatter image of the Sacramento Delta; on the right, corrected for incidence angle.
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Figure 9. Plots comparing average backscatter γ0 for Corrected Backscatter (Green) and Uncorrected Backscatter β0 (Red). Smaller plots show more specific details such as average standard deviation and average level of backscatter. had lower standard deviations over time. Conclusions There were four main conclusions to be drawn from this case study of the Sacramento Delta. First, high biomass is directly correlated with lower estimation error. Secondly, in future performance models for high biomass, it would be beneficial to use box sizes of over 250 looks for similar forest environments. Third, it is important to note that a change of 50 pixels can result in a change of < 3 dB. Finally, correcting for incidence angle decreased the average standard deviation by about .09 dB and the average backscatter by about 1.5 dB. Most importantly, this analysis revealed that backscatter from man-made structures is very stable over time; whereas backscatter from bare soil and herbaceous vegetation fluctuates over time with a standard deviation of 2.3 dB. Land-cover surfaces with larger biomass such as trees and tall vegetation show about 1.5 dB standard deviation in temporal backscatter variability. Closer examination of high spatial resolution UAVSAR imagery also reveals that vegetation structure, speckle noise, and horizontal forest heterogeneity in the Sacramento Delta can significantly affect the pointwise backscatter value. Acknowledgment The author would like to thank Paul Rosen and Marco Lavalle for their constant support, guidance, and mentorship throughout this summer. The author also thanks Gustavo Shiroma for helping with PLAnT navigation and development, as well as Brian Anderson from JPL’s Digital Image Animation Laboratory (DIAL) for helping with temporal animations. JPL’s Education Office and the JPL Summer Internship Program provided financial support.
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REFERENCES Small, David, Flattening Gama: Radiometric Terrain Correction for SAR Imagery, IEEE Transactions on Geoscience and Remote Sensing, Vol. 49, No. 8, August 2011. Anfinsen, Stian Normann and Anthony Doulgeris and Torbjorn Eltoft, Estimation fo the Equivalent Number of Looks in Polarimetric Synthetic Aperture Radar Imagery, IEEE Transactions on Geoscience and Remote Sensing, Vol. 47, No. 11, November 2009. Lavalle, Marco, and Gustavo Shiroma, Piysh Agram, Eric Gurrola, Gian Franco Sacco and Paul Rosen, PLANT: Polarimetric-Interferometric Lab and Analysis Tools for Ecosystem and Land-Cover Science and Applications, NASA Jet Propulsion Lab, IGARSS 2016. Rosen, Paul, Eric Gurrola, Gian Franco Sacco, Howard Zebker, The InSAR Scientific Computing Environment, EUASAR 2012. Rosen, Paul, “Principles and Theory of Radar Interferometry.” 4, August, 2014. https://www.unavco.org/education/ professional-development/short-courses/course-materials/insar/2014-insar-isce-course-materials/InSARPrinciplesTheory_UNAVCO_14.pdf Lavalle, Marco, L-band backscatter change over time, NASA Jet Propulsion Laboratory, 2017. Farr, Tom G, “Chapter 5: Radar Interactions With Geologic Surfaces” from SAR Interpretation. NASA Jet Propulsion Lab. “Geometry Glossary.” ESA: Earthnet Online. Web. http:// envisat.esa.int/handbooks/asar/CNTR5-5.html
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