Wetterhahn Science Symposium Posters 2024

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  Patient-healthcare provider interactions on Cannabis for Therapeutic Purposes

  Jivan Achar, Cara Struble, and Alan Budney

  Background and Objectives: There is limited evidence guiding the efficacy and safety of cannabis for therapeutic purposes (CTP). Healthcare providers lack requisite knowledge to support patients. This study aimed to describe and compare aspects of an initial CTP interaction across different provider-types. We anticipated mental health providers would differ from other provider-types based on varied exposure to cannabis consumers.

  Methods: Adult cannabis consumers (N=507) from the U.S. completed an anonymous online survey rating aspects of an initial CTP interaction, including risk mitigation behaviors and recommendations about use. Analyses examined CTP interactions among four provider groups (Mental health [MH], Family Medicine [FM], Medical Clinics [MC], and Other Specialty [OS]).

  Results: Less than half of the sample reported discussion of cannabis risks (44.0%) or subsequent follow-ups (44.0-46.7%). Recommendations (where to obtain, consumption method, dose, and frequency) were uncommon (9.7%-19.5%). While the MH group reported the highest rates of risk mitigation discussion (62.0%-65.0%), models adjusted for sociodemographic and cannabis characteristics were largely non-significant. MC providers were more likely than the MH group to report recommendations (p’s<.05). Younger age and greater cannabis-related problems increased likelihood of risk mitigation and provider recommendations.

  Discussion and Conclusions: Data suggest that CTP interactions focused on risk but generally lacked comprehensive recommendations for safe use. Data from provider perspectives could support the need for CTP dosing guidelines and training for healthcare providers to promote safe CTP practices.

  Scientific Significance: For the first time, this study explored several aspects of CTP interactions and compared experiences across a variety of provider-types.

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  Healthcare utilization associated with mental health symptoms in young adults with type 1 diabetes

  Ayushya Ajmani, Ujvala Jupalli, Enzo Plaitano, and Catherine Stanger

  Today, as mental health illnesses such as depression, anxiety, and eating disorders continue to expand, they are further associated with poor glycemic control, decreased quality of life, increased unemployment, and worse self-care. This study aims to describe the relationship between psychological and diabetes distress and emergency healthcare utilization including 911 calls, ED visits, and hospitalizations among young adults with T1D. The collected and analyzed data indicate that T1D-related ED visits and hospitalizations are significantly associated with higher levels of mental health symptoms and diabetes distress in young adults. In contrast, no significant relationships were found between T1D-related 911 calls and mental health symptoms or diabetes distress.

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  Gastroenterology Environmental Impact Assessment: LCA in Endoscopy

  Fatma Al Arbawi, Joao De Araujo Jr., Cate Pittman, Anya Ramrakhiani, Fatmata Sesay, and Adam Sobel

  With this project we aimed to understand the current state of endoscopy carbon impact and ideate several possible solution sets to help our sponsor, gastroenterologist Dr. Heiko Pohl, know where to focus future engineering design and research. In the first term of research, we reviewed LCA frameworks and observed endoscopy procedures to understand where there were opportunities to improve on the carbon footprint of the procedure. Once identified, these improvement areas were the focus of our second term of work:

  1. Hypothetical packaging, shipping, and material changes

  2. Designing a reusable handle for polyp removal procedures

  3. Designing a mechanism to keep bioloads out of the endoscope during procedures like a bile duct exploration

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  Translating Neurophysiological Recordings Into Dynamic Estimates of Conceptual Knowledge And Learning

  Daniel Carstensen, Jeremy R. Manning, and Peter Mucha

  This study investigates the potential of a computational approach to provide moment-by-moment insights into a student’s comprehension of lecture material through analysis of their neurophysiological responses during the lecture. In doing so, we present a solution to two difficult problems. How do we quantify the conceptual content of a lecture video? And how can we use EEG recordings to compute a knowledge estimate of this conceptual content? First, we used topic modeling to generate moment-by-moment estimates of the conceptual content of a lecture. Then we used EEG recordings collected during the lecture to compute an ISFC-derived knowledge estimate of this conceptual content. We found that particularly gamma band activity may contain a signal indicative of knowledge acquisition.

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  Computational modeling of human sequential decision making in high-dimensional environments

  Seoyoon Choi, Chong Wang, and Alireza Soltani

  Reinforcement learning is the process through which one learns the values of their actions and make adaptive decisions to maximize their reward. In naturalistic environments, this process can be challenging, as (1) choices can have long-term consequences and (2) choice options can have many features.

  Previous studies showed that humans used successor representations to learn cognitive maps for planning. Other studies demonstrated that humans used feature-based learning and selective attention to learn the values of multi-featured stimuli. However, the interaction between these processes is largely unexplored.

  To investigate this interaction, we designed a novel multidimensional two-step task, as well as six computational models representing different learning strategies. Using these models, we made concrete predictions about human behavior in our task paradigm, which can be tested in future experiments.

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  Singular bound states in the 1D pseudoharmonic oscillator

  Elsa Coulam and Rufus Boyack

  This project aims to analyze the bound-state solutions of the one-dimensional pseudoharmonic oscillator potential. Past literature has suggested that bound-state solutions exist only when the coupling constant is greater than or equal to negative one quarter. However, previous research using matrix mechanics and a transcendental Kummer function has discovered bound-state solutions in the region less than negative one quarter. The wave functions of these solutions will be extensively studied by analyzing the limiting form of their probability distribution to understand the origins of these singular energies. Additionally, the expectation values of these wave functions will be analyzed, considering that the singular bound-state wave functions are not peaked at the origin. This analysis will also extend to a modified version of the hydrogen atom to investigate if it exhibits similar behavior. These analyses will offer insights into the essential mathematical properties of singular potentials in one dimension and explore the existence of a universal probability distribution for such states in singular one-dimensional potentials.

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  Characterizing Dopaminergic Signaling in the Nucleus Accumbens Core Across Different Sign-tracking responses using Fiber Photometry

  Daniela Garrod, Erica Townsend, and Kyle S. Smith

  Motivation is a fundamental force driving our everyday actions, yet the intricate neural pathways underlying it and the ways it manifests differently among individuals remain largely unknown. To assess this question, this study characterizes the role of dopamine (DA) signaling in the nucleus accumbens core (NAc) on individual differences in sign-tacking responses. Peak DA signaling during reward-predicted cue (CS+) onset was recorded through in-vivo fiber photometry on the last day of sign-tracking training, while the sign-tracking responses were measured through presses per minute (PPMs) and behavioral video scoring. Rats were then placed in an omission schedule where the persistence and vigor of sign-tracking responses were tested. Results indicate that DA release in the NAc at CS+ onset during sign-tracking training may not only attribute incentive value to a reward-predicting cue but also regulate how much we want to interact with it or want it. There are distinct correlations between DA signaling and sign-tracking behaviors during both sign tracking training and omission trials, suggesting that DA release at CS+ onset may serve a different function in these two paradigms. Overall, these findings attempt to understand the rich differences in motivated behavior, which could potentially be useful in the diagnosis and treatment of disorders like addiction and binge eating.

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  Do common distractions help us attend? Effects of unconscious learning on attention

  Audrey Y. Kim, Kevin Ortego, and Viola Störmer

  This project seeks to investigate the mechanisms underlying our ability to select relevant and ignore irrelevant information. At any moment, we are confronted with an overwhelming amount of sensory information – far more than we can process at once. Selective attention is the cognitive function that allows us to prioritize processing relevant inputs and ignoring irrelevant or distracting inputs, making selective attention a core cognitive capacity that underlies and constraints information processing in the human brain. Traditionally, attention theory distinguishes between two types of selection: consciously deciding what to focus on (top-down, or endogenous attention), and attentional focus drawn to salient stimuli in the environment (bottom-up, or exogenous attention). More recently, another type of attention has been suggested in the literature, namely learned attention, where the attentional system operates based on statistical regularities in the environment, such that attention is incidentally biased toward information that has been relevant frequently in the past (Awh et al., 2012). To date, it is unclear how this learned attention operates and also how it compares to top-down attentional processes.

  A previous study found that explicitly informing participants about an upcoming relevant target or irrelevant distractor feature using attention cues increased performance during a visual search task, but this effect was much stronger for targets than distractors (Addleman & Störmer, 2022). This may suggest that selecting targets and ignoring distractors rely on different cognitive resources. However, unconsciously learned target and distractor features seemed to increase performance at a similar rate, suggesting that they rely on shared selection mechanisms. To measure the neural processes involved in learned attention, I have been conducting research that assesses the changes in visual processing efficiency for learned targets and distractor features using human electroencephalography (EEG). Through this fellowship, I plan to complete the data collection on this project, analyze the behavioral and EEG data, and disseminate the results in the form of a research paper and/or at a conference. With ample time to collect data on the effects of learned feature-based selection and ignoring, I will examine whether previous selection bias for targets and previous suppression bias for distractors utilize the same cognitive resources. This research has the potential to explain visual processing biases that affect attention, changing the way the attentional framework is regarded, integrating not only physical salience and current goals of selection but also selection history.

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  Beyond average: The active processing of information in ensemble perception

  Sarah Parigela, Ria Parikh, Kevin Ortego, and Viola Stoermer

  Ensembles can be found in daily life. Surveying faces in a crowd, generalizing states of objects (ex. clean vs. dirty tables in a restaurant)---they all require computing averages. Previous studies have shown that observers can quickly and automatically extract information about means of groups. Through a task of reporting orientations of sets of triangles, we hypothesized that participants should be more accurate when averaging large groups than remembering individual items.

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  In Pursuit of Understanding the Physiological Mechanism of the Tumor Suppressor LactB

  Julia Patterson, Sukrut Kamerkar, and Henry Higgs

  In this poster, I summarize my work exploring the dynamics and cellular function of the novel protein LactB. LactB is a bacterial penicillin-binding protein homolog and mitochondrial serine protease whose function is not fully understood. LactB localizes to the intermembrane space (IMS) of the mitochondria and forms filaments. However, it is unclear where LactB functions within the IMS, or whether it interacts with the mitochondrial membranes. Furthermore, LactB acts as a tumor suppressor in colorectal cancer, hepatocellular carcinoma, glioma, melanoma, gastric cancer, lung cancer, and ovarian cancer. The mechanism for LactB’s tumor suppressor function is debated, though a number of pathways have been proposed.

  My research focuses on two subjects: 1) the dynamics of LactB within the IMS via fluorescence recovery after photobleaching and 2) the effects of LactB knockout and knockdown on cellular function by examining lipid droplets and apoptosis. Although I found the LactB-GFP construct I used to have an immobile fraction in the mitochondria, my work with FRAP was discontinued after the publication of LactB’s CryoEM structure revealed structural complications with this construct. Instead, I focused on siRNA knockdown and CRISPR-Cas9 knockout exploring the impact on lipid droplets, spherical organelles important in lipid metabolism and tumorigenesis. I found significant changes in lipid droplet size and number in two melanoma cell lines. I also explored the effects of decreased LactB expression on apoptosis, finding a decrease in apoptosis in one cell lines. My studies raise the important question of the mechanism by which LactB contributes to apoptosis.

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  Prompt Engineering for Coding Tutorial

  Adwiteeya Rupantee Paul

  Generative AI tools like ChatGPT, Copilot, and Gemini have become essential to students’ learning in introductory coding classes like CS1. Yet, very little work has been done to create tutorials that utilize the potential of these tools. Traditional coding tutorials are not adaptable to a student’s learning style or understanding of a subject. AI-based tools combined with ma- chine learning algorithms used for adaptive testing can help students by creating a customized environment that adapts to an individual’s performance. The central goal of this project is to create an adaptive coding tutorial that uses generative AI tools to design increasingly challenging problems for a given topic. The tutorial also assists students by creating code samples when they make a mistake while learning.

  Internally, the tutorial has two components. The first component communicates with the stu- dent and determines the learning level using adaptive learning algorithms. The second component uses the output of the adaptive learning algorithm to create coding problems suitable for the student’s learning level.

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  The role of endocytosis in Toll protein function​

  Nina Devi Prakash, Colleen Moore, and Patrick Dolph

  The goal of the project is to determine the role of the Toll protein in retinal degeneration. The Toll protein is a pro-cell death molecule that is also known to be involved in dorsal-ventral patterning during development and innate immunity. This project focuses on the internalization process of Toll, by which it is brought into the cell to mediate cellular functions. Four specific motifs on Toll that are known to be involved in internalization or sorting will be knocked out via CRISPR technology. After screening a population of potential mutant Drosophila flies with a polymerase chain reaction (PCR) to determine lines that have a successful knockout, the effect of these knockouts on cellular processes will be observed. Toll processes are generally conserved across all species which either have the Toll protein or Toll-like receptors (TLRs). Therefore, the results of this project could provide more information on how the TLRs contribute to rhodopsin-related diseases in humans, such as retinitis pigmentosa and give insight into causes of neuronal degeneration.

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  Investigating the neural circuitry of motivation in both food and social rewards

  Angela Shang, Erica Townsend, and Kyle Smith

  Environmental cues that predict rewards can become attractive. Sign-tracking is a conditioned response where animals interact with reward-predicting cues due to incentive salience, or motivational value attribution. However, this behavior can become maladaptive if it remains inflexible to context or cue changes. Previous research indicates that cholinergic (ACh) neurons in the nucleus accumbens (NAc) enable behavioral flexibility in sign-tracking responses. This study aims to investigate the role of ACh transmission in the development and adaptation of sign-tracking in rodents when environmental cues change.

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  Regulation of Lipid Composition of the Golgi during Tissue Formation: Where Does PI 4-Kinase Stand?

  Elise Tong and Bing He

  Four Wheel Drive (Fwd), the Drosophila homologue of PI 4-kinase IIIβ, is a conserved phosphatidylinositol 4-kinase (PI4K) that localizes to the Golgi apparatus and functions in protein trafficking from the Golgi to the plasma membrane. The goal of this project was to determine how the localization of Fwd to the Golgi is regulated during early embryogenesis in Drosophila. Our initial observations suggested that Fwd was only localized to a subset of Golgi apparatus, raising the question of whether distinct types of Golgi apparatus exist in early Drosophila embryos. By optimizing imaging conditions, we found that many Golgi compartments initially identified as Fwd-negative showed weak Fwd-GFP signals, arguing against the existence of a sub-population of Golgi that completely lack Fwd. In addition, we found that phosphatidylinositol 4-phosphate (PI4P), the lipid product of PI4Ks, were both strongly enriched on the plasma membrane and weakly associated with intracellular puncta-like structures. These intracellular signals appear to overlap with Fwd-GFP, suggesting that Fwd colocalizes with its lipid product on the Golgi apparatuses. Together, our findings demonstrate that Golgi apparatuses differ in their capacity to recruit Fwd, which may impact their rate of PI4P production. These observations raise the question of how the activity of individual Golgi apparatuses are regulated in developing tissues.

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  Microscopic Analysis of Ancient Food Residues

  Marit UyHam, Jiajing Wang, and Yiyi Tang

  During the Longshan period of Neolithic China (c. 3000-2000 BCE), settlements took root and flourished in the Yellow River Valley. Kangjia is an example of such a settlement, with its craft specialization and hierarchical social structure. Furthermore, agriculture and animal husbandry contributed to a relatively varied diet, particularly among those of higher social status.

  The primary objective of this experiment was to characterize the diet of Kangjia society. This was accomplished by analyzing plant microfossils sampled from pottery sherds excavated from an archaeological site in Kangjia. Phytoliths, silica plant cell skeletons, have distinct structures which differ between plant species. Similarly, starch granules have characteristic morphological differences between crop species. Because both phytoliths and starch granules are persistent over time, they are ideal diagnostic tools.

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  Interstellar helium voyages: Modeling and comparing theoretical and observed data

  Kendall Yoon and Hans Mueller

  The heliosphere is the volume of space occupied by the solar plasma, surrounded by the local interstellar medium flowing around it. Interstellar neutral atoms, such as helium, can travel from the interstellar medium into the heliosphere unimpeded, affected only by gravity. Therefore, detection of these atoms provides information about the state of the local interstellar medium. This poster details the creation of programs to model the theoretical detection of interstellar neutral helium atoms, 1 AU away from the sun. The final produced plots show the flux of interstellar neutral helium on a mollweide all sky map. These plots were designed to be comparable to data from NASA's IBEX satellite. Analysis of these theoretical plots and IBEX data provides insight into what atoms IBEX is likely missing in its detection.

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  Racial/Ethnic Differences in Psychotic-Like Experiences Among Cannabis Consumers: Exploring Relationships with Cannabis and Mental Health Characteristics

  Jean C. Yuan, Cara Struble, and Alan Budney

  Compare psychotic-like experiences (PLEs) among Non-Hispanic White, Non-Hispanic Racial Minority, and Hispanic cannabis consumers (2) Examine associations between PLEs with cannabis and mental health characteristics

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  Quantifying Synergy and Gender Inequality of Content Creator Collaborations in Video Game Streaming

  Mingyue Zha and Ho-Chun Herbert Chang

  Content creator collaborations have emerged as a significant strategy for enhancing digital viewership and revenue. While existing research has explored the general impact of collaborations, none have looked at potential inequities present in such collaborations. The aim of this study is to examine gender inequality and quantify synergy in content creator interactions. Utilizing Shapley value analysis, a tool from cooperative game theory, we computed the synergy of gendered collaborations. We employed textual and network analysis to further compare collaborations. We offer insight into the streamer collaborations dynamics and their implications for gender equality in the digital space.