Posters from the annual student research session where DePauw students can demonstrate their collaborative work with faculty or internship experiences.
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Tools for Genotyping of Nicotine-Seeking Zebrafish
Emma Kennedy, Aziza Shemet Pitcher, Sabrina Krause, Autumn McDaniel, Molly Ruggles, and Henning Schneider
Smoking is one of the main causes of preventable diseases such as cancer, cardiovascular diseases, diabetes, and chronic obstructive pulmonary disease. Helping people quit using nicotine products is a main goal of our projects. Developing a zebrafish model for nicotine use behavior could provide a tool for studying the underlying genetic risks and neuronal elements of nicotine use behavior. The availability of large numbers of larval zebrafish, relatively short generation time and genetic tools present a major advantage for studying the genetic causes of nicotine use behavior. Here, we present our approach to test whether identified single nucleotide polymorphisms (SNPs) associated with smoking behavior in humans have SNP homologs in nicotine-seeking zebrafish. Our major focus has been on genes that appear to increase the risk for nicotine-use behavior in humans. A zebrafish behavioral test allows us to separate nicotine-seeking from non-seeking larval zebrafish. Fin or scale tissue can be used to isolate genomic DNA. We have developed tools and protocols to detect SNPs in zebrafish genes for acetylcholine receptors type alpha 3, alpha 5, as well as nol4b2, opiate receptor oprm1 and the zebrafish homolog to human cytochrome P450 2A6 (CYP2A6). The genetic analysis of nicotine-seeking zebrafish could lead to the identification of genes and gene modifications that facilitate nicotine-use behavior.
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Cardiac Neuroanatomy and Chronotropic Modulation of the Adult Giant Danio Heart
Alyssa Koch, Emma Nelson, and Pascal Lafontant
Studies in non-mammalian models species have contributed significantly to our understanding of the biology and the nature of innervation in the heart. The giant danio (D. malabaricus) is a teleost fish species closely related to zebrafish, that is also capable of heart regeneration. We previously described the development and maturation of the giant danio (GD) heart. However, little is known about its innervation. We hypothesized that the pattern of innervation in the GD heart is anatomically and physiologically complex, and that the heart is responsive to physiological modulation similar to that seen in cyprinid fish and mammals. Using various neuronal markers and electron microcopy, we described the presence, distribution, and nature of nerves in the GD heart. Our study shows first that fine intrinsic cardiac nerve fibers are present throughout the heart chambers. Second, nerve soma and ganglia are highly concentrated at nerve plexuses located near the sinoatrial (SA) and atrioventricular (AV) junctions. However, the volume density of axonal processes located over the ventral aorta_ is highest over the corpus of the bulbus arteriosus. Third, using an ex vivo GD heart preparation, we found that the GD heart responded to both adrenergic and cholinergic agonists, in a manner that mirrors mammalian and teleost hearts. Taken together, our studies show that the GD heart displays complex patterns of innervation, and conserved cardiac physiological responses, and strongly suggest that the GD could be used as a viable model for investigating cardiac biology.
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A Highly-Parameterized Ensemble To Play Gin Rummy
Masayuki Nagai, Kavya Shrivastava, Kien Ta, Chad Byers, and Steven Bogaerts
In this work we describe the development and tuning of a computer Gin Rummy player. The system includes three main components to make decisions about drawing cards, discarding, and ending the game, with numerous hyperparameters controlling behavior. After the components are described, three sets of hyperparameter tuning and performance experiments are analyzed.
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Pattern of health behavior and its association with self-rated health: evidence from the 2018 behavioral risk factor surveillance system in the United States
Linh Nguyen, Mamunur Rashid, and M Mazharul Islam
Physical inactivity, tobacco use, and alcohol consumption are linked with increased morbidity and mortality. To improve public health services, we need to keep policymakers updated with health-related issues. Yet, there are limited numbers of recent research on the combination of those lifestyle behaviors as the determinants of self-rated health (SRH) in the US. Therefore, this study (1) examines the pattern of physical activities, smoking, alcohol consumption, and SRH, and (2) investigates the association between the behaviors and SRH status among US citizens. We extracted data from the latest state-based survey of the 2018 Behavioral Risk Factor Surveillance System (BRFSS), which provides a nationally representative sample of 437,436 American adults. We analyzed the data mainly employing chi-square tests and logistic regression models. Results indicate that physical inactivity and smoking are more common among participants with lower education and household income. Normal-weight individuals or those with higher education and income level are associated with drinking and optimal SRH. Younger ages smoke and report optimal SRH more often, whereas older adults tend to be more physically inactive. Women and people with chronic diseases tend to be less physically inactive, drink, and report optimal SRH than those in the same categories. Optimal SRH is less common among people who smoke and are physically inactive. People who have at least one drink monthly report optimal SRH more often than those who do not. We encourage policy formulators to maintain the public space, increase taxes on tobacco products, and make educational campaigns targeting the youth.
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Hsa-miR-4520-2-3p: A Potential Modulator of COVID-related ACE2
Molly Ruggles and Nipun Chopra
ACE2 is a transmembrane receptor located in cells in various tissues around the body. Its normal role is the conversion of Angiotensin II to Angiotensin 1-7 leading to vasodilation and a subsequent reduction in blood pressure via the renin-angiotensin-aldosterone system. ACE2 also plays a pivotal role in the infection of COVID-19 as it determines entry of virus into human cells. SARS-CoV-2 uses one of its four structural proteins, the spike (S) glycoprotein, to bind to the ACE2 receptor. This entry into the cell begins the process of infection and spread of the disease; because of the abundance of ACE2 throughout the body, viruses are able to enter a number of different organs. This multi-cell-entry via ACE2 is why COVID-19 affects multiple organ systems in the human body. Currently, therapies targeting ACE2 expression are limited. MicroRNA (miRNA)s are short non-coding RNA that downregulate the expression of a variety of proteins, and therefore offer a mechanism by which to inhibit the expression of ACE2. MiRNAs can potentially downregulate ACE2 protein synthesis by binding to the mRNA of ACE2 at a seed sequence. This binding results in mRNA degradation or inhibition of translation. Thus, our goal was to identify miRNA that may potentially target and downregulate ACE2. TargetScan, DIANA-MicroT, and PicTar are three algorithms that predict miRNAs that can bind to the mRNA of ACE2 and downregulate its expression. Together, the prediction tools resulted in 57 shared human miRNAs that target ACE2. We then utilized self-defined parameters to narrow down our list and identified hsa-miR-4520-2-3p as our predicted miRNA to target ACE2. This miRNA will be experimentally verified in the future.
Supervisor: Prof Nipun Chopra, PhD
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Mapping Disparities in COVID-19: Determining the Demographic, Economic, Educational, Housing, Quality of Life, and Health Factors that Relate to Disparities in COVID-19 infections and Deaths
Kate Stanley and Naima Shifa
Background: Throughout the pandemic, minority groups, particularly African Americans and Hispanic/Latino Americans have experienced disproportionately high infection and death rates as compared to their white and Asian counterparts. Though this phenomenon could be attributed to high rates of pre-existing conditions in black and Hispanic communities, there are other underlying factors that cause such disparity. We set out to determine whether or not various demographic, economic, educational, health, housing, and quality of life indicators were correlated with higher rates of COVID-19 infection.
Methods: We used USAFacts COVID-19 data to select the 150 United States counties with the highest infection rates. We then collected a series of data, courtesy of the U.S. Census Bureau, for each of those counties. While useful, county-level analysis failed to reveal inequality within counties (i.e. low-income areas nested inside a high-income county). In order to further understand minority health, we used Policy Map to collect a series of data for Chicago and New York City, and performed zip-code level analyses for each city. In order to explore societal indicators of minority health, we used descriptive statistics and statistical t-tests to compare the counties and zip codes with the highest white population to the counties and zip codes with the highest percentages of African Americans and Hispanic Americans. Finally, we created a series of scatterplots, studying the correlation between zip code level variables and COVID-19 infection rates.
Results: Compared to the predominantly white counties and zip codes, areas with higher rates of African Americans and Hispanics demonstrated lower income levels, lower educational attainment, higher rates of certain pre-existing conditions (namely obesity and diabetes), lower rates of flu vaccination, lower self-rated health, lower insurance coverage, and minimal physical activity. Furthermore, larger household size, lower rates of yearly doctor’s visits, homeownership, and computer/internet access, and higher rates of unemployment, multiple jobholders, and public transport use were all related to higher COVID-19 rates among minority communities.
Discussion: Underlying economic, educational, housing, and quality of life factors are associated with higher rates of COVID-19. Mitigating these underlying social determinants of disease could improve the health of minority groups disproportionately affected by COVID-19. Future research can work to further understand how these social indicators cause disease and should seek to uncover potential interventions to address these disparities.
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Visualizing Income Distribution in the United States
Sang T. Truong and Humberto Barreto
Background: Visit https://sites.google.com/depauw.edu/incomedistributionviz/home to see a novel, eye-catching visual display of the income distribution in the United States that conveys fundamental information about the evolution and current level of income inequality to a wide audience. We use IPUMS CPS data to create household income deciles adjusted for price level and household size for each of the 50 states and the District of Columbia from 1976 to 2018. We adjust for state price differences from 2008 to 2018. Plotting these data gives a 3D chart that provides a startling picture of income differences within and across states over time. Those interested in further customization can use our Python visualization toolbox, incomevis, available at pypi.org/project/incomevis.
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Ultra-high vibrational and rotational motion of the HF molecule via Infrared (IR) laser excitation
Toria Tucker, Jingwei (Mike) Ling, and Bridget Gourley
Our goals this summer were to build on previous work in our group modeling ultra-high vibrational and rotational excitation in small molecules via unique pulse sequencing of an infrared (IR) laser. The system was modeled both using Fortran and Mathematica as programming languages. We were able to demonstrate that different numerical techniques for propagating coupled differential equations forward in time led to equivalent levels of vibrational excitation and allowed for identical visualization of molecular state probabilities as a function of time. Work including the rotational motion progressed to the point of being able to see both significant excitation when rotations are included as well as leaking into neighboring rotational states as expected. Much work remains to be done before a full analysis of the rotational excitation can be completed.
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Effects of Mono- and Di- Saccharide Osmolytes on the Stability and Folding Dynamics of src SH3
Mahmoud Abouelkheir and Emily Guinn
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Does Urbanization Drive Evolution in White Clover?
Victor Alfonso, Seika Shiba, Yangjie Tan, and Philips Akinwole
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The Best Studied Crab in Astronomy: Searching for Variability in VHE Emission from the Crab Nebula
Christina Bourantas, Kate Cowger, and Avery Archer
The Crab Nebula is the remnant of a powerful stellar explosion first observed in 1054 AD and has been extremely well studied for decades. previous very high energy (VHE); GeV) studies have observed no variability in the nebula flux making the Crab a standard reference tool for gamma-ray telescopes. As part of the VERITAS (Very Energetic Radiation Imaging Telescope Array System) collaboration, we continue monitoring the nebula’s flux to understand the VERITAS telescopes and physical processes occurring within the nebula. We are analyzing over 80 hours of data from 2017 and 2018 from VERITAS Collaboration, developing and adding to a light curve that includes data since 2007. Our analysis of the 2017-2018 combined dataset determined a spectral index of -2.324 plus or minus 0.005489 and fitting the light curve with a constant function yields a mean integrated flux above 200 GeV of, which is significantly lower than a 2007-2016 dataset.
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Exploring Student Experiences in Science & Math to Address Underrepresentation in STEM
Brittany Davis, Hira Ahmad, Berenice Contreras, Krista Kaleel, and Sydney Majka
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Machine Learning to Support an Interactive Theorem Prover
Salman Haider, Andy Le, Echo Wu, and Brian T. Howard
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Visualizing the Mean and the Standard Deviation Using R/RStudio Shiny Package
Rachel Hufnagel, Ziyi (Amy) Chen, and Mamunur Rashid
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AROutcrop: an augmented reality mobile application for teaching geology in the field
Zachary Wilkerson, M. Scott Wilkerson, and Chad Byers
