Tag: Podium Presentation

Rosalie Chaleunsouck^1,2
Faculty Mentor: Elizabeth Stacy, Ph.D.^3
1College of Sciences, Department of Chemistry and Biochemistry
²College of Sciences, Department of Physics and Astronomy
³College of Sciences, School of Life Sciences

ABSTRACT
Metrosideros polymorpha is a widely dispersed, pioneering tree species endemic to the main islands of Hawaii. The vast variation of the Hawaiian landscape has fostered the phenotypic plasticity of this species to adaptively specialize to thrive within its environmental niches thus producing distinct varieties of form in differing stages of incipient radiation. The geographical isolation of specialized phenotypic forms encourages the use of self-pollination as members of the population no longer need to overcome prezygotic barriers or distance. However, self-pollination has been seen to be detrimental to fitness as it may lead to the expression of deleterious recessive traits resulting in an inbreeding depression within the population. Increased homozygosity has been observed to lead to reduced survival and fertility of the offspring. These concepts are evaluated in a third-generation Metrosideros model through a survey of the effects of inbreeding depression and self pollination within the germinal and embryonic development stages relative to the out-crossed offspring. Each sample cross was plated on water-saturated Whatman filter paper in a petri dish and irradiated under a full-spectrum LED light for 12-hour light cycles during a six-week germination trial period. The number of filled embryonic seeds and germinants grown of each sample was visually assessed using a dissecting microscope. As the underlying driving forces of divergence and speciation amongst tree species are poorly understood, this model seeks to provide insight into the potential postzygotic reproductive isolating barriers and challenges in fitness that offspring may face in development due to increased homozygosity and inbreeding depression.

Jonathan Pasternack¹
Faculty Mentor: Shashi Nambisan, Ph.D.^2
1Howard R. Hughes College of Engineering, Department of Civil and Environmental Engineering and Construction

ABSTRACT
Traffic crashes are of significant concern to society. Understanding key factors related to traffic crashes is critical to develop strategies to enhance road safety. Factors include attributes related to the crashes, persons and vehicles involved, and environmental conditions. These data are based on reports and records maintained by multiple agencies at the local, state, and national levels. Unfortunately, such data are not readily available in an integrated manner. The Nevada Department of Transportation (NDOT) consolidates and captures in a digital format crash reports filed by individual law enforcement officers and their agencies. NDOT’s database has separate subsets for attributes related to crashes, persons, and vehicles with a common field linking two of these three subsets. A consolidated database is required to perform the desired analyses. This presentation will summarize the steps needed to integrate the individual data subsets into one consolidated database using data obtained from NDOT for the years 2015 to 2019. It will demonstrate an automated procedure to develop the consolidated databases. Next, it will highlight the process to georeference data for individual crashes and link them to the crash attributes in a GIS environment. In addition, the presentation will touch upon challenges and issues related to integrating individual data sets and to incorporating them in a geographic information system (GIS) environment. Future work includes developing queries and conducting statistical analyses to answer hypotheses regarding similarities and differences in road safety outcomes based on spatial and temporal characteristics

Citlally Lopez Flores¹
Lilian Huynh²
Jeffrey Ash²
Faculty Mentor: Jun Yong Kang, Ph.D.^1
1College of Sciences, Department of Life Sciences
²College of Sciences, Department of Chemistry and Biochemistry

ABSTRACT
Cancer is the malignant growth and division of abnormal cells. The proliferation of cancerous cells is harmful to the human body since it interferes with many biological processes. Lysine-specific demethylase 1(LSD1) protein levels are expressed at high levels in many types of cancers such as teratocarcinoma, embryonic carcinoma, and embryonic stem cells. Gene expression in cancerous cells can be repressed by lysine-methylation on histones which ensures the maintenance of a tightly organized histone. Targeting LSD1 protein levels can significantly impair the growth of cancer due to the methylated histones being unable to participate in gene expression. Lysine-specific demethylase 1(LSD1) inhibitors prevent the proliferation of cancer by targeting the high concentrations of lysine-specific demethylases vital for cell proliferation. CBB3001 is a LSD1 inhibitor which has been able to inhibit the growth of cancer, warranting further investigation. The aim of this research project is to synthesize CBB3001 by developing efficient synthetic methods and to then create a CBB3001 derivatization library. The researchers involved will synthesize CBB3001, a LSD1 inhibitor, by developing several synthetic pathways with variability along specific steps to produce CBB3001 derivatives. CBB3001, and its derivatives, show great promise in functioning as anti-cancer reagents for many types of human cancers.

Shivangi Sinha¹
Faculty Mentor: Melva Thompson-Robinson, DrPH^2
1College of Sciences, School of Life Sciences
²School of Public Health, Department of Environmental and Occupational Health

ABSTRACT
The COVID-19 pandemic has acted as a catalyst for telemedicine uptake among both healthcare providers and patients. Prior research rarely has examined the lack of patient uptake of telemedicine. Known systemic barriers to accessing telemedicine in the U.S. before the COVID-19 pandemic may play a large role in its uptake. The purpose of this study is to assess the factors associated with the usage and acceptance of telemedicine pre- and since the COVID-19 pandemic. In this cross-sectional study, data was collected from persons residing within the U.S. who are 18 years of age or older using an online survey. Using an integrated model of the Theory of Planned Behavior and Technology Acceptance Model, this study measured barriers to accessing telemedicine before and since the COVID-19 pandemic as well as the six constructs of the model. Descriptive statistics and logistic regression were calculated. In the model examining predictors of telemedicine use before COVID-19 (p<0.001), racial/ethnic identity (p<0.05) was the statistically significant predictor. In the model examining predictors of telemedicine use since COVID-19 (p<0.001), devices used to access telemedicine since COVID-19 (p<0.05) was the statistically significant predictor. Gender identity, employment status, healthcare status and selected constructs of the integrated model were among the variables not statistically significant in either regression model. These findings contribute to the existing literature regarding barriers to telemedicine uptake among patients in the U.S. Future studies should focus on making the survey more accessible to non-English speakers and communities with limited Internet access.

Samantha Giannantonio¹
Faculty Mentor: Laurel Raftery, Ph.D.^1
1College of Sciences, Department of Life Sciences

ABSTRACT
Cells communicate by producing molecular signals that activate a signal-specific pathway to elicit a response in neighboring cells. Signaling pathways share similar elements that include the signal and receptor, and intracellular components to relay the signal and effect a change in gene expression. Two signaling pathways, the Wnt pathway and the Bone Morphogenetic Protein (BMP) pathway, which contribute to the establishment of body plans for all multicellular animals, have been thought to be independent of one another. However, recent evidence suggests that the Wnt and BMP pathways share a signal transducer that has a necessary function in both pathways. This hypothesis has not yet been tested with the definitive genetic method of using a genomic deletion. This is a progress report of such a definitive test. I am testing whether Mad is required in both the BMP and Wnt signaling pathways using the Mad[KO] allele to generate Drosophila embryos that lack Mad. Whether Mad is required for Wnt responses will be determined by examining the denticle belt patterns of exoskeletons from embryos that lack Mad. The denticle belt pattern will be compared to that of embryos that lack the signals necessary for either the BMP or the Wnt pathway. The results obtained will provide critical evidence for whether Mad functions only in the BMP signaling pathway, or both BMP and Wnt signaling pathways.

Sarem Khilji¹
Jae Choi²
Faculty Mentor: Elizabeth Stacy, Ph.D.^1
1College of Science, School of Life Sciences
²New York University

ABSTRACT
Plants rely heavily on innate immunity toward pathogens due to the fact that many of them do not contain specialized adaptive immune system cells. In order to mount proper immune responses, plants must come up with several broad defense mechanisms. One such mechanism in these plants, nucleotide-binding domain & leucine-rich repeat (NLR) proteins, are key players when it comes to intracellular immune-related functions. While the biological functions and protein structure of NLR genes are similar across species, variation in NLR gene numbers and sequences among closely related plant taxa can play a key role in diversification and the evolution of reproductive isolating barriers. In this study, we examine variation in NLR genes within Hawaiian Metrosideros (Myrtaceae), an incipient adaptive radiation of woody taxa that show partial isolating barriers. By using NLR annotating software tools, examining the number of NLR genes through code, mapping these genes to their respective chromosomes, and looking at synteny between taxa, we hope to glean insight into the evolution of NLRs in Metrosideros and how variation of these NLR-mediated mechanisms may potentially confer reproductive isolation within taxa. Preliminary results suggest that pubescent Metrosideros taxa may have a greater number of NLR sequences than glabrous taxa while also varying in their distribution across chromosomes. Future synteny analysis will provide a framework for examining variation of these homologous genes and help to establish if gene order is a significant factor of NLR variation among different species.

Raisa Kabir¹
Sayeda Tazim F. Zaida¹
Faculty Mentor: Manoj Sharma, Ph.D.^1
1School of Public Health, Department of Environmental and Occupational Health

ABSTRACT
People of color (POC) from stigmatized and marginalized communities face implicit bias in healthcare. Implicit biases are unconscious attitudes and internalized discrimination developed through repeated practices based on stereotypes from a foundation of structural discrimination. Implicit bias in clinical settings impacts an individuals’ quality of care and overall health outcomes. The study aimed to characterize and address implicit bias among healthcare professionals toward POC in clinical settings. A literature search in MEDLINE/PubMed, CINAHL, and EBSCO databases was undertaken to include all peer-reviewed studies (2011-2021) about implicit bias toward POC. The original literature search located 121 peer-reviewed articles. Out of those, 20 literature articles met the inclusion criteria. Patients of color disparities are often due to the lack of access to health care/insurance, the quality of care/treatment received, and overall health outcomes. Additional factors include gender, age, mental illness, weight, disability, sexual orientation, AID status, socio-economic status, and social circumstances. Most healthcare providers appear to have an implicit bias in terms of positive attitudes toward Whites and negative attitudes toward POC. Future studies need to employ more rigorous methods to examine the relationship between implicit bias and healthcare outcomes. Interventions targeting implicit attitudes among health care professionals are needed because implicit bias may contribute to health disparities and the overall clinical care of POC. Educational initiatives, reformed policies/practices, and new research are needed. Acknowledging racial/ethnic, cultural, and religious bias in clinical settings minimizes implicit bias and reduces negative health care experiences for POC.

Allyson Deijkers¹
Faculty Mentor: Shashi Nambisan, Ph.D.^1
1Howard R. Hughes College of Engineering, Department of Civil and Environmental

ABSTRACT
This presentation summarizes preliminary analyses of some factors related to fatal bicyclist crashes. It focuses on urbanized counties in California, Nevada, Oregon, and Washington for the years 2008-2018. Key variables analyzed include state and county, crash location (at intersection, on roadway, on shoulder, etc.) and lighting conditions (day/night). The National Highway Traffic and Safety Administration’s (NHTSA) Fatality Analysis Reporting System (FARS)’s data were used for the analyses. Results show commonalities and differences across the counties. In Nevada, Clark and Washoe counties had most of their crashes during daylight conditions, on the roadway. In California, results vary across the state. Yolo County had most of their crashes on the roadway, and not intersection related. San Diego County had half of their crashes under daylight conditions, on the roadway. San Francisco County had most of their crashes under daylight conditions, on the roadway, and at an intersection. Sacramento County had half of their crashes under daylight conditions, on the roadway, and not at an intersection. Los Angeles County had half of their crashes under daylight conditions, on the roadway. Multnomah County, Oregon had most of their crashes under daylight conditions, on the roadway. King County, Washington had most of their crashes under daylight conditions, on the roadway, with a slight majority at an intersection. The results indicate that other factors such as roadway and bicyclist characteristics also need to be integrated in the analyses. These will be explored next to help develop and deploy appropriate countermeasures to enhance bicyclist safety.

Janelle Domantay¹
Faculty Mentor: Brendan Morris, Ph.D.^2
1Howard R. Hughes College of Engineering, Department of Computer Science
²Howard R. Hughes College of Engineering, Department of Electrical and Computer Engineering

ABSTRACT
Awareness detection technologies have been gaining traction in a variety of enterprises; Most often used for driver fatigue detection, recent research has shifted towards using computer vision technologies to analyze user attention in stationary environments such as online classrooms. This study aims to extend previous research on distraction detection by analyzing which visual features contribute most to predicting awareness and fatigue. We utilized the open source facial analysis toolkit OpenFace in order to analyze visual data of subjects at varying levels of attentiveness. Then, using a Support Vector Machine (SVM) we created several prediction models for user attention and identified Histogram of Oriented Gradients (HOGS) to be the greatest predictor of the features we tested. We also compared the performance of this SVM to deep learning approaches that utilize Convolutional and/or Recurrent neural networks (CNN’s and CRNN’s). Interestingly, CRNN’s did not appear to perform significantly better than their CNN counterparts. While deep learning methods definitively performed better, SVMs utilized less resources and, using certain parameters, were able to approach the performance of deep learning methods.