Longevity is a major focus in biomedical exploration and evolutionary ecology, but little is known about the underlying processes that cause variation in lifespan. Telomere shortening may be one such mechanism; the erosion of this “biological clock” at chromosomal ends can affect organismal aging. Other factors, such as social interaction, may also influence longevity. Here, 36 female Japanese quail from six family groups were studied to explore how cellular aging mechanisms and social factors influence lifespan. Telomeres were analyzed with the Telomere Restriction Fragment assay, and behavioral data, collected through pecking interactions, was evaluated to determine dominance, aggression, and coalition status. Telomere loss in the first and last year of life significantly predicted lifespan, signaling the key roles that early and late life play in survival. Telomere length at 11 and 23 months of age was significantly related to longevity, proposing a biomarker of lifespan. Within the six families, family had a significant effect on telomere length at one month, indicating a heritable component for initial telomere length. Furthermore, dominance significantly predicted increased lifespan, while aggression significantly predicted decreased lifespan, suggesting that being dominant with a light touch maximizes survival. Coalition status was significantly related to telomere loss, perhaps explaining why coalition members exhibited increased lifespan. Finally, family was significantly related to submissive behavior, proposing a heritable component of vulnerability. Ultimately, this groundbreaking longitudinal study provides a window into cellular and social factors that can be targeted to prevent or delay the aging phenotype, and in turn, maximize survival.

Mentor: Dr. Mark Haussmann, Bucknell University, Lewisburg, PA

Mia Dittrich, Class of 2021, Regeneron STS Top Scholar, Junior Science and Humanities Symposium National Finalist, International Science and Engineering Fair National Finalist

Epigenetic editing of Cdk5 leads to sexually dimorphic stress responses

     Women are more prone to disorders such as PTSD and depression. Yet, most preclinical psychopathological research solely uses male subjects, causing a paucity of sex-specific studies. Thus, Mia investigated sex-specific responses to chronic unpredictable mild stress (CUMS) and fear conditioning (FC). Additionally, she examined the role of epigenetic regulation of cyclin-dependent kinase 5 (Cdk5), implicated in stress, fear, and depression. Section one of this study used data pre-collected from mice exposed to CUMS or targeted epigenetic repression of Cdk5 in the nucleus accumbens. Mia scored four tests that modeled behaviors linked to stress disorders and measured Cdk5 protein levels. Results showed Cdk5 repression decreased compulsive and depressive-like behaviors in female, but not male, mice (compulsive:  p = 0.0177; depressive: p = 0.0027). Anesthesia/surgery increased anxiety and depressive-like behavior in male mice only (anxiety: p < 0.0001; depressive: p = 0.0035). These results suggest that targeted Cdk5 repression has potential for female-specific therapeutics. Section two of this study used data pre-collected from mice exposed to FC, either with or without targeted epigenetic activation of Cdk5 in the hippocampus. Results showed, during long-term fear retrieval, females alone exhibited darting behavior—rapid locomotion in response to fear (p = 0.0446). Overall, this study elucidated sex-specific stress responses linked to epigenetic regulation and suggested Cdk5 repression for potential female-specific therapeutics. Beyond the intricacies of Cdk5, this study shows disregarding sex in neuropsychiatric research is detrimental to understanding stress disorders. Thus, researchers must prioritize sex differences, laying the foundation for more effective and equitable treatments.

Mentors: Dr. Elizabeth Heller and Dr. Ajinkya Sase, University of Pennsylvania, Philadelphia, PA

Ali Hafez, Class of 2021, Regeneron STS Top Scholar

Using artificial neural networks to accurately simulate carbon nanotube array field-effect transistors

   Every computer in the world requires billions of transistors to function. For each of these transistors, there has been exponential growth in processing power in the past few decades, alongside the improvements in transistor technology and decreases in transistor size. However, due to the physical limits of silicon, the improvements have recently slowed. Nanomaterials such as carbon nanotubes (CNTs) have emerged as alternatives to silicon that provide advances in speed and efficiency but fall short in manufacturing ease compared to silicon. Nanomaterials are difficult to produce and manipulate, so transistors made of nanomaterials are tested extensively with simulation before manufacturing; however, accurate nanoscale transistor simulation is computationally inefficient. Thus, as a novel approach to simulating CNT array field-effect transistors (FETs), neural networks were used in this study as an alternative to conventional simulation to mitigate these issues. To create a neural network that can accurately predict the properties of new transistors, thousands of existing transistor data were obtained by simulations performed by a device simulator and subsequently passed into the network for training. After training, the neural network-based simulation provided a speed increase of over 650,000x compared to the device simulator, with an average relative error under five percent. These results may enable future research in transistor engineering by cutting the time researchers need to test transistor designs before creation. Computational speed and efficiency improvements made by the neural network model may also enable larger-scale simulations to be done faster than previously while still retaining the physical realism of a device simulator.

Mentor: Dr. Jeffrey Bokor, University of California, Berkeley, CA

Jared Ilan, Class of 2021, Regeneron STS Top 40 National Finalist 

Modulus of elasticity of the ideal decellularized plant material scaffold for the production of cultured meat

     Livestock contributes approximately 14.5% of greenhouse gas emissions, furthering our current climate crisis. Additionally, resources to accommodate the rising demand for meat in the growing global population are insufficient. The production of cultured meat is a means to mitigate this problem. Cultured meat requires cells to be grown on a scaffold; however, current scaffolds lack both scalability and sufficient vasculature to transport nutrients for growth. A scaffold composed of decellularized plant materials, however, would be widely available and extremely cost-effective, allowing for massive scaling potential. The goal of this study was twofold: first, to establish the ideal mechanical properties for a cultured meat scaffold; second, to identify a decellularized plant material that fits these ideal properties. This study analyzed the modulus of elasticity of multiple plants and compared it to that of the native scaffold, decellularized skeletal muscle (DSM). Each decellularized plant demonstrated a significant difference in modulus of elasticity from the native scaffold, however, the modulus of elasticity of celery was closer to the ideal range than the previously recorded modulus for the current standard, spinach. In terms of modulus of elasticity, decellularized celery exhibits more potential as a cultured meat scaffold than decellularized spinach. Additionally, moduli of elasticity recorded for various types of DSM were identified as benchmarks for assessing viability of future scaffolds. These benchmarks can be utilized to identify viable and efficient decellularized plant scaffolds for the large-scale production of cultured meat, eventually helping to sustainably feed the world’s growing population.

Mentor: Dr. Glenn R. Gaudette, Boston College, Boston, MA

Alexa McGrath, Class of 2020, Regeneron STS Top Scholar

An investigation of the medicinal value of the baboon diet in the wild: A comparative study across five species and six study sites

     During the co-evolution of plant-animal relationships, some animals began to utilize plants’ chemical defenses for their own benefit. This behavior is known as animal self-medication, and baboons (Papio) are among some of the understudied species exhibiting self-medicating\behavior. Currently, there is an abundance of information on baboon diet and behavior, but few studies critically evaluate the potential medicinal value of the baboon diet in detail. This study is the first to create a unique database of all plants reported to be consumed by multiple baboon species at various locations across Africa. A meta-analysis was conducted for each plant part consumed, before each plant’s medicinal value was assessed by identifying its phytochemical and pharmacological properties as well as its ethnomedicinal uses. Results show that 30.8% of the baboon diet (N= 406 identified species, 447 plant parts, 246 genera) could be classified as medicinal food, with 13.3% (N= 54/406 items) of that related specifically to the treatment of parasites and/or other related pathogens. These percentages represent some of the highest figures reported for any species’ medicinal diet. The variation between groups in the amount of overall medicinal value and antiparasitic value, specifically, was found, with one study group consuming significantly more medicinal items than the others. Interestingly enough, this group has the closest proximity to humans and is facing the most stress due to human impact. This suggests that habitat and group differences may be at work influencing the selection of plants with various medicinal properties. In the end, due to large genetic similarity and comparable immuno-tactics for battling diseases with humans, this study identifies baboons as a valuable primate model suitable for future research on self-medicative behaviors, perhaps with the benefit of discovering new bioactive compounds beneficial for human use. Equally important, our research points towards the need to preserve natural habitats given the multitude of benefits we may potentially gain from our non-human relatives.

Mentor: Dr. Michael A. Huffman, Kyoto University, Kyoto, Japan

Spencer Karp, Class of 2020, Regeneron STS Top Scholar

A step toward energy efficient infrastructure: A weakly supervised approach to power signal labeling in commercial buildings

     The building sector plays a large role in the progression of climate change, as it is the largest energy-consuming sector in the world. In order to bring buildings to their peak energy efficiency performance, it is imperative to understand their underlying energy load composition. This requires an efficient and effective process of labeling individual end uses—such as heating, lights or plugs—from power signals in a building. This study looked to dramatically expand the breadth of data labeling algorithms to all end uses by employing strategies used for pattern recognition over a time series. It aimed to build a weakly supervised data labeling algorithm using features that reflect cycling and daily trends in the programming language Python. Random Forest (RF) algorithm was used as a standard classification algorithm to demonstrate the effectiveness of the features. With the goal of creating a standardized data labeling algorithm, the model was tested on two separate buildings. Results showed the model could successfully label the various end uses of both buildings, and therefore, supported its standardization over many buildings. Overall, this algorithm could automate the process of measuring and understanding the composition of energy consumption, a major step towards drastically reducing the world’s carbon footprint.

Mentor: Dr. Robert Cox, University of North Carolina, Charlotte, NC

Alan Chang, Class of 2019, Regeneron STS Top Scholar, Published in Cell Systems

Utilizing a novel machine learning pipeline for single-cell transcriptomic characterization of a remodeled tumor microenvironment

     Evading immunosurveillance is a key hallmark of tumor progression. From suppressing immune activity to exploiting intrinsic cell mechanisms, cancer cells utilize diverse genetic perturbations to resist current methods of immunotherapy. Exploring the effects of these tumorigenesis drivers can drastically increase treatment effectiveness. Prior to this study, convergent CRISPR screens identified that mutating the gene Prkar1a facilitates tumor growth within a fully functioning immune system. However, the mechanisms by which Prkar1a-mutant cells escape immune surveillance remain unexplored. In this study, various machine learning approaches are employed via R and Bash shell scripting to analyze single-cell RNA sequencing (scRNA) data from Prkar1a-mutant tumors. This study introduces a novel in silico pipeline that separates, identifies, and characterizes remodeled cell clusters using a scRNA-seq dataset. The results provide convincing evidence of not only the immune cell type identities within the Prkar1a-mutant tumor microenvironment, but also the pathway activity of all cell populations. Alan identified immunosuppressive signatures post-Prkar1a mutation, including an anti-inflammatory M2 macrophage population, a minuscule T-cell population, and several exploited pathways. The novel characterization pipeline described in this study enables future research to define the functional roles of tumorigenesis drivers within the tumor microenvironment and thereby enhance the effectiveness of cancer immunotherapy.

Mentor: Dr. Sidi Chen, Yale University, New Haven, CT

Ethan Jacobs, Class of 2019, Regeneron STS Top Scholar, Google Science Fair Global Finalist 

Optimizing and applying environmental DNA (eDNA) detection methods to analyze the presence of river otters in the Northeast

     Analyzing populations of species has come a long way from simple field research, with recent detection methods being based on DNA detection assays. Collection and analysis of environmental DNA (eDNA), the DNA contained in urine, scales, skin, hair, or other excretes, can now be analyzed to monitor biodiversity and map population distribution with finite precision. This research aimed to optimize eDNA analysis for the detection of undermapped, elusive, non-marine mammal species in the Northeast, specifically North American river otters, beavers, muskrats, and raccoons. Target eDNA was amplified in water samples with the cutting-edge GoFish nested PCR method. The presence of river otter and other target mammal DNA was detected multiple times in the three tested rivers, most importantly providing support for effective protocol and proper primer design. This study is the first of its kind to use eDNA as a method of environmental mapping of non-aquatic and semi-aquatic mammals in the Northeast, and is the first to use GoFish Nested PCR with non-marine mammal DNA and suburban river water samples. Ethan’s results support the use of eDNA-based research, an accessible cost- and time- efficient system of population monitoring, to aid conservation efforts and hoist field research into the imminent future.

Mentor: Dr. Mark Stoeckle, The Rockefeller University, New York, NY

Brent Perlman, Class of 2019, Regeneron STS National Finalist, 7th in nation, International Science and Engineering Fair Finalist, Patent Pending

Human photosynthesis: Functional chloroplast sequestration in human mesenchymal stem cells

     Photosynthesis is vital to the survival of life on Earth, providing organisms with the ability to harness energy from sunlight and evolve oxygen. Although of the utmost importance, photosynthesis is a process that mammals—specifically humans—are unable to naturally conduct. However, recognizing the previous success of an endosymbiotic, chloroplast-based approach to inducing photosynthesis in murine fibroblasts (Nass, 1969), this study documents the novel ability of human mesenchymal stem cells (hMSCs) to endosymbiotically incorporate and sequester isolated spinach chloroplasts in coculture. Chloroplast-hMSC symbionts retained the de novo ability to conduct human photosynthesis over an 11-day culture period. Chloroplast sequestration had no apparent negative effects on hMSC metabolic activity or cellular viability at the end of the culture period. Hitherto unreported in the literature, this patent-pending process, which allows for the sterile culture of chloroplasts with continued viability, provides future chloroplast therapies with great clinical promise. With potential applications in post-ischemia interventions, engineering of full tissues and organs in vitro, targeted cancer treatments, and even in vivo production and delivery of biopharmaceuticals, sterile chloroplast culture and the phenomenon of human photosynthesis may revolutionize the path of future scientific advancement.

Mentors: Dr. Glenn Gaudette and Dr. Joshua Gershlak, Worcester Polytechnic Institute, Worcester, MA

Alexandra Brocato, Class of 2018, Siemens Semi-finalist, Regeneron STS Top Scholar

Illuminating non-neuromuscular phenotypes and their temporal trajectory in Spinal Muscular Atrophy (SMA) using electronic health records

     Spinal muscular atrophy (SMA) is a recessive genetic disease targeting motor neurons (MNs) in the spinal cord that results from decreased survival of motor neuron (SMN) protein. SMA is the leading genetic cause of infant mortality, affecting approximately 1 in 10,000 babies in the U.S. Promising therapeutics increase production of SMN protein, preserving MN levels and delaying neuromuscular phenotypes. However, to be effective, therapies should be administered pre-symptomatically, before significant cellular death. Unfortunately, if given too early, potential side effects could be more harmful to less severe, later onset cases of SMA. Without a clear disease trajectory, developing relevant treatments become nearly impossible. Furthermore, since current treatments focus specifically on motor neurons, effective interventions may need to also address phenotypes outside the nervous system. Our study is the first of its kind to characterize SMA disease progression across both neuromuscular and non-neuromuscular phenotypes and to create a timeline of their trajectories. Focusing on 860 SMA individuals, extracted from a population of 45 million registered Aetna Insurance record holders, we conducted all data analysis in R, a programming language for statistical computing. Using this approach, we provide a framework for pre-symptomatic identification of patients who could benefit from preventative medicine. By understanding phenotype trajectories, therapeutics can be developed and administered before major inflection points in SMA without harming individuals with quality years of life remaining before symptom onset.

Mentors: Dr. Lee Rubin and Dr. Scott Lipnick, Harvard University, Cambridge, MA

Alexis Aberman, Class of 2018, Regeneron STS Top Scholar

A direct comparison of infants’ comprehension of unique versus generic versions of objects

     Infants learn about abstract, generic categories in language through exposure to unique exemplars. In order for humans to use language effectively, they need the ability to make abstractions. There are few studies that examine infants’ ability to make abstractions. This study tested if 15 infants (12-18 months) had the ability to comprehend abstract ideas in language. In a looking-while-listening procedure, infants were directed to look at one of two images. In half of the trials, the two distinct images were of the baby’s own, unique items, while in the other half, the two images were the generic versions of the same objects that the infant had not previously been exposed to. Infants’ success was measured by the corrected proportion of target-looking after receiving instruction to look at the target image. Infants were found to show a greater proportion of target-looking in the unique trials, although there was no significant difference in the infants’ proportion of target-looking between unique and generic trials. Because infants demonstrated a better understanding of their own, unique objects, this study may suggest the existence of a milestone in their ability to make abstractions and must be further confirmed through a larger study. A more precise understanding of the major milestones in language development could aid in both our knowledge and treatment of developmental delays, as well as give us a better understanding of how infants view the world around them.

Mentor: Dr. Elika Bergelson, Duke University, Durham, NC

Jeremy Ma, Class of 2018, Regeneron STS Top Scholar, Neuroscience Research Prize national finalist

Perceptual interactions in visual depth perception: A quantitative EEG study

     Percepts of different sensory modalities have been shown to interact with one another. Previous studies have qualitatively looked into the results of the interactions between stereo depth and specific pictorial depth cues, but failed to address the interaction themselves. My study will quantitatively investigate perceptual interactions between pictorial (two dimensional) and stereo (three dimensional) depth perception, the combination of which I term combined depth perception. Using a steady-state visually evoked potential (SSVEP) paradigm and a high density EEG net, the neural activity of eight subjects was recorded during the alternation and detection of different types of depth. I proposed and implemented the Relative Peak Strength variable, in order to quantitatively compare and plot the response strengths of each electrode. The perception of pictorial depth was observed to induce neural activity in the ventral stream, while stereo depth was observed to induce activity in the dorsal stream, suggesting these percepts have different functions when perceiving depth. The heat map for combined depth perception was significantly different from the mere sum of pictorial and stereo depth, suggesting combined depth behaves like a Gestalt, in which pictorial depth and stereo depth are not processed parallel to each other. Furthermore, heat maps of combined depth resembled the heat maps of stereo depth scenarios, suggesting stereo depth is the predominant type of depth perceived in combined depth. Pictorial depth was also observed to lower neural activity when comparing different amounts of depth; but has no major contributions when detecting depth. These results suggest that pictorial depth can have different roles on combined depth depending on the task; for example, pictorial depth can play a supplementary role when comparing depth, but have no influence when detecting depth. When pictorial depth is not able to supplement stereo depth, the increased amount of neural activity could be a crucial reason of visual fatigue when viewing stereoscopic displays. This connection between depth percepts and streams should be further investigated, as it can lead to a better understanding of the perceptual mechanisms underlying the reconstruction of the visual world.

Mentor: Dr. Pawan Sinha, Massachusetts Institute of Technology, Cambridge, MA

Alexandra Remnitz, Class of 2018, Neuroscience Research National Finalist and Presenter at the American Academy of Neurology

Behavioral lateralization and scototaxis unaltered by near future ocean acidification conditions in Poecilia latipinna
(Sailfin Molly)

     Rising anthropogenic emissions of CO2 have increased ocean acidity by 25% (NOAA, 2017). In more than 40 studies to date on fish, including species of coral reef and pelagic fish, this increase in CO2 has been shown to alter behavior related to specific sensory systems, such as olfactory, auditory, and visual, in addition to behaviors representing broader cognitive function such as learning, activity, and boldness. The underlying cause behind these behavioral disruptions is hypothesized to be the alteration of ion gradients across the GABAA receptor, the major inhibitory neurotransmitter found throughout the vertebrate nervous system. There are few studies that examine CO2-induced behavioral alterations in estuarine species, specifically fish that regularly experience diel and seasonal CO2 fluctuations in their natural environment. This study examined the effects of predicted near-future CO2 concentrations (~1000 µatm) on behavioral lateralization and scototaxis of the Sailfin Molly (Poecilia latipinna). Behavioral lateralization is the tendency of an individual to favor one side of the body and scototaxis refers to light/dark preference and is a proxy for anxiety measurements. Elevated CO2 levels were not found to affect these behaviors in this understudied species. Findings from this study suggest the Sailfin Molly could be more resilient to high CO2 levels in comparison to other tested species; however, more research is needed to fully assess behavioral tolerance. These novel findings may inspire researchers to further explore the mechanisms leading to species-specific differences in behavioral tolerance, potentially allowing for better assessment of adaptive capacity. Understanding resilience in various species of fish may aid in the maintenance of biodiversity throughout the changing oceanic environment.

Mentors: Dr.Rachael Heuer and Martin Grosell, Rosenstiel School of Marine and Atmospheric Sciences at the University of Miami, Miami, FL

Audrey Saltzman, Class of 2017, Regeneron STS National Finalist

Swift XRT and UVOT investigation of low-mass X-ray binary 1RXS J180408.9-342058

     The radii of neutron stars are difficult to determine, and there is little consensus as to the correct models for neutron star spectra. Here, the spectra of observations taken by the Swift Xray Telescope (XRT) of the neutron star in the low-mass X-ray binary (LMXB) 1RXS J180408.9-342058 were analyzed, and the neutron star’s radius values were calculated for each observation using the spectral continuum method. The spectra were best modeled using a blackbody to account for thermal emission and a power law to account for inverse Comptonization. The model’s parameter values and the radius are reported for each of the observations providing a longer term look at the star’s behavior. Physically realistic radius values could not be calculated as the color correction factor is unknown; therefore, the color correction factor’s minimum and maximum values were determined using realistic radius values from the literature. A burst rate of one per 4,168 seconds was calculated. Furthermore, this study is one of the first to trace the UV and X-ray thermal evolution simultaneously for a LMXB with a transient, occasionally outbursting, neutron star. In one of the clearest detections to date, the UV flux was determined to be due to reprocessed emission.

Mentor: Dr. Jon Miller, University of Michigan, Ann Arbor, MI

Michelle Morgenthal, Class of 2017, Junior Science and Humanities Symposium National Finalist

Identifying protective and risk factors associated with behavioral misadventure in high sensation seeking adolescents

     This study examines a cohort of vulnerable adolescents, due to their high sensation seeking tendencies. The goal is to characterize the protective and risk factors associated between youth high in sensation seeking and low behavioral misadventure (HSS/LBM) in contrast with those high in sensation seeking and high in behavioral misadventure (HSS/HBM). These cohorts are important because previous research has mostly focused on high versus low risk takers without taking sensation seeking into account. However, this distinct identification of cohorts can help inform prevention methods more effectively by looking at those who would be willing to take risks, but somehow hold themselves back. A secondary data analysis was conducted, drawing on subsample of data derived from wave one of the Adolescent Health Risk Behavior Study (N = 2017) at the University of Michigan, headed by Dr. Daniel Keating. A modified version of the Brief Sensation Seeking Scale (mBSSS) and the Behavioral Misadventure Scale (BMS) were used in this study to identify both groups for comparison with demographic characteristics as well as protective and risk factors associated with adolescent risk behavior. ANCOVA and MANCOVA were used to contrast the HSS/LBM and HSS/HBM groups across these factors. There were four significant findings. First, race was a significant demographic factor (p < .001, Φ = .35), with Caucasians more likely to be in the HSS/HBM group than African Americans or Asians. Second, BMI (p = .035, Φ = .12) was identified as a protective factor against unsafe risk participation; those who were overweight were more likely to be in the HSS/LBM group. Next, although hypothesized that Physical Activity would be a protective factor, it was found to be a significant risk factor (p = .001, r = .20), as those who reported less exercise were more likely to be in the HSS/LBM group. In contradiction with previous research, Supportive Family Context, Pubertal Timing, School Engagement, Peer Influence, Socioeconomic Status, and Religiosity had null effects on the placement of adolescents in the HSS/LBM or HSS/HBM group. We conclude with plausible rationales for our results.

Mentors: Dr. Edward Huntley, Dr. Daniel P. Keating and Dr. Meghan Martz, University of Michigan, Ann Arbor, MI

Isabelle Chong, Class of 2017, Regeneron STS Top Scholar

Using an Inertial Navigation System (INS) and a Laser Range Finder (LRF) to create a novel Electronic Navigational Aid (ENA) for the blind

     The current navigation aid of choice for the blind is the white cane, which, although lightweight and easy to acquire, has a limited range and requires extensive training to use. While Electronic Navigational Aids (ENAs) have been developed to improve upon the white cane, the need for certain environmental conditions and preconfigured infrastructure in some approaches (e.g., radio frequency identification and structured light) remains an issue. My objectives were to (1) design the conceptual and mathematical methodology of an ENA for device location and obstacle detection without the use of preconfigured infrastructure, (2) build an ENA by combining a Laser Range Finder (LRF) and an Inertial Navigation System (INS), (3) code a real-time algorithm for obstacle detection and Kalman filtering in C++, and (4) test my ENA’s functionality from both an engineering and human subjects standpoint to obtain quantitative and qualitative feedback. The completed ENA can detect obstacles within a six meter range without preconfigured infrastructure, raising an alarm to the user through sound and haptic feedback if an obstacle has been detected. This device has the potential to provide a robust alternative method of blind navigation in the future.

Mentor: Dr. Yao Wang, New York University School of Engineering, New York, NY

Yasamin Bayley, Class of 2017, Regeneron STS Top Scholar

Species-specific responses of coccolithophores’ growth rates and calcification to various light intensities: A comparative study of the species Emiliania huxleyi and Coccolithus pelagicus

     Coccolithophores are a type of single-celled marine phytoplankton vital to the biogeochemical cycles of the ocean, specifically the sinking of inorganic carbon. Due to current projections of increasing surface water temperatures, coccolithophores may begin to shift their position upward in the water column, resulting in exposure to higher light intensities. Coccolithophores have been noted to have somewhat contradictory responses to changes in their environment. It is postulated that this difference in responses is due to the species-specific responses coccolithophores seem to have. We seek to determine how two different species of coccolithophores (Emiliania huxleyi and Coccolithus pelagicus) respond to varying light intensities. Specifically, we looked at how these two species’ growth rates and calcification differed at these varying intensities. We used cell counts to determine growth rates and scanning electron microscopy to determine structural changes that high light intensities have caused on each species. We found that Emiliania huxleyi’s growth rate and photosynthesis are largely unaffected by a high light intensity, whereas we present the novel finding that Coccolithus pelagicus produces more calcite per cell at high light, but fewer cells per ml (less calcite per ml than at a low light). We provide further evidence to address the question of why coccolithophores evolved to calcify. We note a correlation between coccolith production and light intensity, which suggests that the production of coccoliths may be triggered by high levels of light. Additionally, this finding suggests that the current increases in surface water temperature may have wider implications in the ecosystem overall, such as a decrease in the downward flux of calcite to the benthic levels.

Mentor: Dr Glen Wheeler, Marine Biological Association of the United Kingdom, Plymouth, UK

To Brux or not to Brux: The Development of Two Novel, Non-Invasive Devices for the Detection of Bruxism

     Bruxism is a disorder in which a patient excessively grinds or clenches their teeth. Symptoms include tooth wear, headaches, back pain, and neck pain. The most common method of treating bruxism is through the use of a mouthguard. The mouthguard does not cure bruxism but only prevents the symptom of tooth wear. Researchers have attempted to reduce bruxism through biofeedback systems. Current bruxism biofeedback devices such as intra-oral pressure sensors and EMG-based systems are intrusive to wear. This study proposes two separate, novel devices that detect bruxism in a less-intrusive manner. The first device is EEG-based and collects data from the F7 electrode located above the left ear. The device uses a machine-learning discriminant-analysis algorithm to detect bruxism from the EEG data. The second device uses Eulerian Video Magnification to amplify temporal color changes in the masseter muscle as seen in a video recording (or live video feed) of bruxism. Both techniques appear to be novel approaches for the detection of bruxism. Both devices were compared to a commercial bruxism detection device to gauge effectiveness and obtain qualitative feedback. Both of the proposed devices demonstrated statistically significant improved efficacy while being less intrusive when compared to the commercially available device.

Mentor: Dr. Catherine M. Roe, Washington University School of Medicine, St. Louis, MO

Rachel Cawkwell, Class of 2010, Intel STS National Finalist

Effect of Tumor Microvesicles on Macrophages in Cancer

     A normal, though understudied, physiological process is the shedding of microvesicles, membranous sacs, from cells. These microvesicles are representative of the cell type they are derived from and can transfer membrane receptors, proteins, mRNA, and organelles in the derived cell. Microvesicles are found in higher numbers in cancer patients and appear to be a vital method of communication for tumors. This project studies how microvesicles work as tumor messengers with regard to macrophages. Macrophages are a type of white blood cell that the tumor uses to direct processes such as blood vessel recruitment and invasion of other tissues. Tumor microvesicles were isolated to see whether they could transfer mRNA to macrophages and increase macrophage proliferation and migration. The tumor microvesicles did transfer mRNA to macrophages as confocal microscopy and qRT-PCR revealed uptake of fluorescence expressing mRNA from microvesicles. A proliferation assay showed no significant change in macrophage proliferation, but an invasive assay demonstrated that tumor microvesicles can increase macrophage migration. This means that tumor microvesicles could potentially recruit macrophages to the primary tumor site, perhaps by transferring mRNA. Further investigation into the details of tumor microvesicle-macrophage communication should confirm and extend these results.

Mentors: Dr. David Lyden and Dr. Hector Peinado Selgas, Weill Medical College of Cornell, New York, NY