Recent political administrations have focused on issues surrounding immigration in the U.S., affecting the ways that immigrant communities are seen and treated. This project recognizes that the rhetoric used by political actors influences and perpetuates views about immigration, and asks the question of how rhetoric around immigration in the 21st Century has affected the identities and experiences of Mexican immigrants in the United States. Drawing upon interviews and secondary research sources, including print and social media, we construct an intertextual and diverse series of podcast episodes, which feature candid discussions with members of the immigrant community. These interviews allow us to gain a more personalized understanding of how public rhetoric, as perpetuated by political administrations and the media, have impacted and shaped the lives and identities of real individuals, families, and communities. Through this podcast, we hope to inspire conversation around the intersection between rhetoric, politics, and immigration, while providing more insight into and compassion for individual, real-world experiences of the immigrant community.

The methods used by actors to learn an accent or a dialect often overlook the cultural and historical significance of a particular way of speaking. More often than not, the majority of the time spent learning a dialect is only spent memorizing the production of distinctive sounds. And what is learned is a “general” version of a dialect that is often stereotyped and not representative of a speaking community. This comes from a long history of reducing the innate complexity of dialects and the creation of foreignness through language prescriptivism and language prestige systems. These impose ideas such as a “proper” way to speak English on stage or the association of negative characteristics with a particular accent. Many productions will not use dialect coaches due to budget constraints or the choice of a director or producer. When productions run on a limited time schedule, dialect coaching is pushed to the side in favor of other elements of character building. This can lead to an actor not doing the proper research, performing a dialect poorly, or at certain cases the production deciding not to use a dialect that is an integral part of a character’s identity. There is also a frame of mind within society that thinks of accents as either authentic or passable, as opposed to accurate. What leads to poor representation on stage is when productions don’t take into consideration the effect a dialect or lack thereof will have on the production as a whole. This project brings a critical lens to the history of dialect coaching and proposes how as theater makers we can shift our thinking regarding accents and through dialect coaching create better representations on stage.

At initial glance, Americans may envy the apparent androgynous nature of Korea’s fashion and dance world. However, what onlookers fail to understand is how the K-pop world’s creation of such genderless dancing and androgenous appearances may be a consequence of the gender binary enforced on Korean individuals by traditional Korean Confucian Values. In this research, I aim to explore how Americans who indulge in Korean pop culture may have interpretations which differ from Koreans who have personally experienced the gendered expectations in contemporary Korean society. I conducted a literature review that focused on the gender presentation of Bangtan Sonyeondan and how cultural values are still strongly weaved into modern Korean society. I also interviewed American and Korean American individuals to conduct a comparative analysis on how their perspectives on Korean gender roles differ. Preliminary results suggest how there may be a glass ceiling to how far an idol’s gender performance can expand beyond societal gender binary constraints. Through my analysis, I hope to bring an alternative perspective to Americans who enjoy Korean culture that highlights some of the unfortunate faults of the seemingly perfect industry.

Metastasis, or the spread of cancer to a secondary site, is responsible for most cancer-related deaths. The tissue-specific environment that disseminated tumor cells experience influences whether they will proliferate and colonize the tissue, remain dormant, or die. Skeletal muscle (SkM) is one of the rarest sites for metastasis, despite making up nearly half of human body mass. What makes SkM so resistant to metastasis? We set out to test the hypothesis that the mechanical nature of SkM is responsible for the lack of metastases at this site. To do so, we used the mdx mouse model of Duchenne muscular dystrophy to probe if the destruction of SkM structure and function would make it a more hospitable host to disseminated tumor cells. Wild type and mdx mice were intramuscularly injected with EO771 murine mammary tumor cells and monitored for tumor outgrowth using bioluminescent imaging. Preliminary results suggest that tumor growth is increased in dystrophic (e.g. dysfunctional muscle) versus wild-type mice. A complementary and more reductionist approach to test whether mechanics influences tumor colonization of muscle is to employ a culture model that allows tumor cells seeded on top of a SkM layer to experience mechanical stretching akin to the contraction/relaxation movements of muscle. To accomplish this, we constructed a device that applies a cyclic stretch to a 3D organotypic SkM culture model on a flexible silicone plate. We predicted that stretching would reduce tumor cell survival, when compared to no stretching. While these experiments are in progress, we believe that these data may elucidate a relationship between mechanical activity and suppression of tumor outgrowth in SkM. This work will contribute to a more complete understanding of how SkM avoids tumor colonization and could inform future approaches that leverage tissue mechanics to treat or prevent metastasis.

Mutations in myosin may lead to severe muscle disorders that greatly reduce the quality of life. For example, the embryonic skeletal myosin (MYH3) mutation R672C leads to Freeman Sheldon Syndrome (FSS), a rare inherited disorder that causes severe contractures at birth. A comprehensive understanding of the relationship between protein structure and function is urgently needed to treat diseases such as FSS. Computational methods, such as molecular dynamics simulations, can be used to examine the effects of mutations on protein structure and function. However, the Protein Data Bank (PDB) is missing most human skeletal myosin heavy chain structures. We employed homology modelling to construct structures of human MYH3. To inform homology modeling, I generated a multiple sequence alignment of 7 human myosin genes. The extent of sequence identity was used to identify the optimum myosin isoforms to use as templates for model generation. For example, MYH3 and MYH7 were the most distinct at 78.93% similarity, which was expected as they are embryonic skeletal and adult cardiac myosin respectively. Specific sequence consensus at each position in the sequence was used to determine the most and least conserved regions of myosin. The cleft region was the most conserved; the N-terminal Domain was the least conserved. I used MYH7, adult cardiac myosin, as a template structure to derive a homology model of the ATP state of MYH3. A structure of MYH3 R672C was generated via in silico mutation of the wild type structure. Molecular dynamics of the resulting structures will be used to explore how R672C, which is located near myosin’s converter domain, alters myosin structure and function. This computational platform will model all phases of the cross-bridge cycle, potentially reveal new drug binding pockets, guide and be validated by in vitro experiments using human induced pluripotent stem cell derived myocytes (hiPSC-Ms).

The purpose of a newly developed foot prosthesis is to improve frontal plane foot adaptability for over 1 million adults living with lower extremity amputation in the US. On uneven ground, side slope, and turning corners, the anatomical foot can adapt but most prosthetic feet cannot. The innovative prosthesis mimics biomechanical aspects of anatomical joints that use ligaments in tension throughout the range of motion while the joint surface acts as a specialized load-bearing structure similar to that of a cross four-bar linkage. In the current prototype cam linkage, we found deviation between the instantaneous center of rotation (ICR) and the point of contact (POC) as it rotated through the frontal plane. The error in this distance could cause unexpected wear on the prosthesis. The goal of this project was to reduce the error caused by the difference in location of the ICR and POC during rotation and translation of the four-bar linkage. In a crossed four-bar linkage, the ICR is found at the intersection of the crossing links. To find the path of the ICR, we plotted a series of points by rotating the linkage about a fixed link in space. The continuous ICR path was estimated by smoothing the ICR points. The curved shape developed becomes the load-bearing surface of the linkage. To create the upper and the lower load-bearing surface, the upper and lower link must be fixed and the opposite rotated, respectively. Using the method described, we built linkage assemblies that showed an error of 0.96 mm per 20 degrees of rotation compared to 2.17 mm of error in the original prototype. The International Organization for Standardization (ISO) requires that foot prostheses undergo wear and fatigue testing. Reducing potential wear on the prosthesis is advantageous because engineers can design for optimal product durability for the foot.

In the United States, 1.5 million individuals suffer a fracture due to bone disease each year. In addition, there are many unknown mechanisms behind how muscular disorders and mechanical load adversely affect bone development, such as in the disease distal arthrogryposis. Disease research in human cell models has greater translational potential compared to animal models but have faced challenges when constructing highly-specialized tissues such as bone. We propose a novel, three-dimensional bone tissue model as a platform for musculoskeletal disease modeling that allows for compressive loading. By seeding induced pluripotent stem cell (iPSC) derived osteoblasts and osteoclasts in a 3D, porous, hydroxyapatite-coated poly-L-lactide scaffold, we propose to generate a bone tissue model that replicates human tissue in a laboratory. By applying compression to the novel 3D bone tissue model, we expect to observe phenotypes of bone disorders and bone development under mechanical loading. We propose to induce osteoblast and osteoclasts lineage from mesenchymal progenitor cells and hematopoietic progenitor cells, respectively, and co-culture to identify optimal conditions for cell growth. Preliminary experiments have found success in culturing active osteoblasts from iPSC-derived mesenchymal progenitor cells. By screening for markers of cell proliferation, calcium deposition, bone resorption and secretion, the cultures can be assessed for their robustness. In parallel, a porous scaffold will be fabricated by dissolving poly-L-lactide in chloroform and molding over sodium chloride particles. Coating said scaffold in fibronectin and hydroxyapatite will improve cell adhesion and uptake bone secretion. Seeding osteoclast and osteoblasts cells in a porous scaffold will allow for improved cell diffusion and 3D growth, mimicking the human microenvironment. We expect that combining robust, osteogenic tissue culture on a bioactive scaffold that allows 3D bone growth with mechanical loading will reveal phenotypes of distal arthrogryposis. Thus, this method has significant applications in accelerating laboratory findings to clinical research.

Transcription factors such as TCF-1, as well as inflammatory cytokines such as IL-12, have been shown to play a role in cytotoxic (CD8) T cell differentiation during an immune response. Here, we build a stochastic computational model of the canonical CD8 T cell immune response encompassing experimentally hypothesized transcription factor and inflammation control mechanisms. We hypothesize that the transcriptional factor control of CD8 T cells can be quantified into concrete model parameters that control various aspects of the immune response such as cell effector cell expansion, proliferation, and memory cell formation in various immune challenge conditions, such as inflammation. With a fully developed model, effects of inflammation levels and gene regulation kinetics on CD8 T cell differentiation can be measured in situ, and new hypotheses surrounding cellular differentiation kinetics can be generated. Understanding the factors that control CD8 T cell differentiation is crucial in the development of vaccines and immunotherapies, such as CAR T cell therapy.

Fluorescent biosensors are a vital tool in the goal to decipher the complexity of neural networks. Genetically encoded fluorescent indicators (GEFIs) are protein-based sensors that increase in fluorescence upon ligand binding and allow for passive monitoring of neuronal signals. However, the development of such sensors is limited by the slow throughput of traditional protein engineering which has long engineering cycles of new plasmid variants. Our project aims to tackle this problem by developing a high-throughput sensor engineering platform that can effectively generate and screen unbiased genetic libraries of GEFIs in mammalian cells. Our platform can identify high performing sensor variants on a custom microarray and effectively isolate and recover their genetic material. Our new platform will be used to develop a sensor for the μ-Opioid receptor (MOR), which is a G-protein coupled receptor that is involved in opioid addiction. Our experiments have already developed a MOR sensor that surpasses the standard in the literature and we will continue to optimize it for maximum spatial and temporal precision. The development of a MOR sensor through this iterative process allows researchers to further investigate the molecular mechanisms underlying the pathology of addiction and provides a novel platform for protein engineers to more efficiently develop a wide variety of biosensors.

The purpose of this study is to examine the feasibility of virtual reality meditation (VRM) for symptom management in outpatients with rheumatoid arthritis (RA). The specific aims of this feasibility study include: 1) examining the feasibility of implementing VR meditation; 2) determining the acceptability of using VR-delivered meditation; and 3) exploring a patient’s experience of using VR-delivered meditation for symptom management. RA is a chronic disease that affects more than 1 million people in the U.S. While recent advances in medicine have shown promising results in managing physical symptoms, a large portion of outpatients with RA still suffer from fatigue. Recent studies have found that fatigue may be managed through meditation, but VR meditation has yet to be tested and deployed in this population. This feasibility study implements a mixed-methods design. Eight adults (18 years and older) with clinically-diagnosed rheumatoid arthritis were enrolled from a local rheumatology clinic. Participants used a VR headset incorporated with meditation software over the course of four consecutive weeks. Patient Reported Outcome Measurement Information System (PROMIS) measures of fatigue, pain, depression, anxiety, physical activity, and mood were collected at baseline and weekly intervals for 4 weeks. Two semi-structured interviews were conducted to capture the patient’s experience of RA, fatigue, as well as experience of the virtual environment. I was personally in charge of analyzing the interview transcriptions and adding coding measurement tags for the quantitative analysis. Results are currently pending. Expected results include that participants will find VRM both feasible and acceptable for fatigue management, and that participants will report reduced fatigue levels after using the VR device. Results of this study will inform future clinical trials using VRM, implementation of VRM into clinical use, and give a better understanding of the patient’s experience of utilizing VRM for fatigue management.

Water is universally critical for life on earth, and snowmelt plays an essential role in the hydrologic cycle, contributing up to 75% of water supply in much of the western United States. As a result, estimating the timing and magnitude of snowmelt is an integral water resources challenge; snow surface temperature observations are key to this issue. It is well established that snow melts at 0°C, so frequent snow temperature measurements supply crucial information for evaluating snowmelt. However, few ground observations of snow surface temperature are available, and those that are only represent a small area. By measuring infrared radiation, satellite thermal imaging can remotely determine surface temperature over large areas and time scales where ground observations are sparse or nonexistent. However, this imagery is limited by its coarse spatial resolution, which results in a blurring of temperatures across study regions. This challenge is especially prevalent for mixed pixels, or pixels with varied land surfaces such as a mix of snow and vegetation or changing topography. Thus, this project investigates how well satellite imaging represents snow surface temperature. Airborne thermal imagery were acquired by the UW Applied Physics Laboratory over Yosemite National Park, California, coincident with ASTER satellite imagery on 21 April 2017. I apply methods including data analysis and zonal statistics over the study area in order to compare finer resolution airborne imaging to coarser resolution satellite imagery. Furthermore, I calculate characteristics of land variation to evaluate where satellite imagery can be scaled for more accurate results. This project works towards the implementation of satellite thermal infrared for use in snow models, creating new datasets for hydrologists to more effectively plan our water resources.

Years before the major events that are tied to the New Left in American collective memory, Bay Area college students’ protests against the House Un-American Activities Committee garnered national media attention for their perceived radicalism in the face of the federal government. Student protesters’ altercation with police at San Francisco City Hall in May of 1960 became a turning point at which the Old Left, New Left, and McCarthyism converged, providing valuable insight into the transition of broad leftist activism from union-based to direct action protest. Through secondary sources including histories of early student protest as well as student newspapers, government publications, supporting organizations’ communications, and oral histories from participants, I construct a timeline of the challenges early student activists faced. This critical angle centers how these protests’ complicate the historical understanding of the university as the postwar institutional mediator for left-wing protest and radicalism, thereby revealing the disparities and power relations between students, professors, and administrators in the pursuit of their respective political agendas. This perspective, therefore, challenges the prevailing notion of universities as a natural partner of progressive social movements by emphasizing the institutional obstacles and inadequacies that restrict student political activism and expression.

The international failure regarding humanitarian relief during the 1994 Rwandan genocide has been the topic of many research endeavors. From the lack of response of the United Nations (UN) to the limited media coverage, international actors continually dismissed the genocide in Rwanda as unimportant primarily due to a lack of interest in the country itself. While much of the existing literature focuses on UN documents and humanitarian aid worker testimony, this paper posits that survivor testimony is a source of largely untapped authority regarding the depth and human cost of the failures of the international community to respond to the genocide in Rwanda. Utilizing survivor testimony, this paper explores the extent of the failure of the international community to respond and the broader dehumanization of Rwandan victims during and since the 1994 genocide. The deeply personal perspectives of survivor accounts highlight three distinct failures: 1) the failure to prevent the genocide and subsequent atrocities; 2) the lack of justice brought to the perpetrators; 3) the lack of care and aid given to survivors in the years following the genocide. Survivors are acutely aware of the lack of intervention during the genocide and the enduring lack of aid and attention due to the lack of international interest. Their testimony speaks to the real human cost of the failure to intervene, as well as to ongoing fundamental institutional weaknesses in the international community today. This study thus ultimately suggests that survivor testimony has healing and perhaps even preventative potential.

 In recent decades, scholars of fascism have increasingly studied how concepts of identity enable and constrain violent political movements. Building on that work, this paper outlines how the Nazi propagandist and ideologue Alfred Rosenberg portrayed a rigid conception of German identity in order to justify his fascist political project. By reading several of Rosenberg’s published books, articles, and his diary to explicate his conception of identity, I suggest that creating a “New German Man” was central to Rosenberg’s calls for Nazism. I argue that Rosenberg built a systematic fascist philosophy out of a series of binaries that were designed to avoid intellectual engagement, thereby preventing criticism and allowing him complete control of the definition of “German.” Thus, this presentation argues that Rosenberg’s conception of Nazi identity as well as the philosophical system he built to justify such a conception of identity are key to understanding how logic and propaganda have been used to enable fascist violence, which allows us to better understand and address harmful ideologies. 

Bacteria can inherit genes through two modes of transmission: vertical inheritance, in which a cell receives genes from its parent cell during division, or horizontal gene transfer, in which genes are passed laterally between two unrelated cells. Extrachromosomal DNA, called plasmids, can be transmitted from a bacterial cell to a neighboring cell of the same or different species through a form of horizontal gene transfer known as conjugation. These conjugative plasmids can encode for antibiotic resistance genes which allows a host cell to produce proteins that degrade antibiotics. In an environment with these drugs, a host cell with this plasmid would be more likely to survive, compared to a plasmid-free cell, due to the benefits of the antibiotic resistance gene. Additionally, these antibiotic resistance genes can often acquire mutations which increases the level of antibiotic resistance for the host cell. However, these acquired mutations may be more beneficial (i.e., higher resistance for the host cell) in one bacterial species than the same mutation in another species. In other words, the effect of mutation on the plasmid-encoded antibiotic resistance gene may be contingent upon the host species. Given that antibiotic resistance genes are often encoded on conjugative plasmids that are shared among species, my project is investigating how protein evolution may be affected due to plasmid genes existing in multiple bacterial hosts. I performed a series of competitions between three bacterial species containing plasmids with versions of an antibiotic resistance gene to determine which versions of the gene outcompete others in an environment containing antibiotics. In doing so, I can determine how this particular gene may evolve when various bacterial hosts exist in a microbial community. The results of this experiment will improve our understanding of plasmid biology and the evolution of antibiotic resistance genes in diverse communities of bacteria.

Many human diseases, including cancer metastasis, and developmental disorders, involve sheets of cells moving together. This concerted process, called collective cell migration (CCM), is critical to maintaining the integrity of the sheet of cells during movement. Maintaining cell sheet integrity is dependent on individual cells retaining their shape while still connected to neighboring cells. To study collective cell migration, we use Drosophila melanogaster (fruit fly) embryogenesis. Dorsal closure (DC), an event in Drosophila embryogenesis, is an example of CCM. During DC, two epithelial layers wrap around the embryo. Because CCM’s core mechanics are conserved, studying DC provides an opportunity to indirectly study human diseases/disorders function in a model that has fewer genetic redundancies and is easy to manipulate. Adherens junctions (AJs), are the site of adhesion between individual cells, and what allows for dynamic rearrangements like CCM by strategically increasing or decreasing adhesion. Despite the importance of this process and its relevance to many diseases, CCM is highly complex and how the scaffolding protein Canoe stabilizes adherens junctions under high stress is not entirely understood. We are interested in how junctions between cells are stabilized during a dynamic movement like in CCM. Using a maternally driven Gal4/UAS system, we created moderate canoe knockdowns. We then performed targeted, immunofluorescence antibody staining of embryos during DC. We expect that the loss of Canoe will lead to increases in cell-sheet tension as well as the compensation by other stabilizing proteins like Polychaetoid. Our research improves our understanding of stabilizing proteins at AJs and CCM and may lead to the more effective treatment of disrupted CCM human diseases/disorders like wound healing, palate formation, and neural tube closure.

Performing computational molecular dynamics (MD) simulations of small-molecule systems has become one of the most prominently used methods in studies of molecular structure and behavior. However, MD is a computationally expensive and time-consuming methodology because of the requirement of computing detailed interactions among atom-atom pairs. There is great interest, therefore, in reducing the time and computational power needed to approximate real-world systems. Most commonly, such efforts have employed machine learning techniques to predict extensive properties of molecular systems. Here, we propose accelerating simulations by predicting conformational changes - a prospect that has not yet been fully explored. Previous work attempted applying a linear dynamical analysis algorithm named Dynamic Mode Decomposition to MD data, which has been shown to be ineffective through a multiresolution analysis. We propose herein the use of Sparse Identification of Nonlinear Dynamical Systems (SINDy), a nonlinear model which has been shown to accurately decipher the governing equations of dynamical systems. We will be testing the effectiveness of SINDy with MD data by performing an iterative error analysis while varying the initial parameters of the dataset, thereby gaining a better understanding of how much data (and in what form) should be inputted to maximize the accuracy of a simulated SINDy model of an MD dataset. If shown to be sufficiently accurate, we then can implement SINDy simultaneously with MD in an active learning loop to save time and computational power while maintaining a high degree of predictive capability for peptide conformations. The current goal is to obtain a deeper understanding of peptide conformational changes that could, in the future, be combined with machine learning techniques to greatly accelerate classical MD simulations.

This project is supported by the UW Computational Neuroscience Center, and the DMREF Program of NSF through the MGI platform under DMR# 1629071, 1848911, and 1922020.

Mexico underwent a dramatic cultural revolution in 1920, and from this revolution sprung a new type of art. ‘Los Tres Grandes,’ as they came to be known, were three men, Rivera, Orozco, and Siqueiros, who painted legendary murals depicting anti-capitalist and Revolutionary themes. This paper discusses the works of David Alfaro Siqueiros, a revolutionary Mexican mural painter, and his involvement in the Modernist movement in the United States. I first explore Siqueiros’ Los Angeles mural America Tropical and argue that he created it to be a strong political statement in a time of national turmoil. I explore the iconology and iconography of the piece that combined ancient Maya symbolism with modern techniques, creating a wholly new form of publicly available art. I also highlighted the importance of the location of this mural in a Los Angeles district that relies on white tourism for survival, and contrasted it with a mural highlighting the suffering of Indigenous people in the United States and America as a whole. Focusing on his time spent in the United States, I also explore his artist-relationship with the modernist painter Jackson Pollock and Siqueiros’ apparent influences on his style. Finally, I will discuss the influences that Los Angeles art culture had on Siqueiros, including a change in his mural style from individualistic to collectivist.

Budget policy in the United States is not uniform across agencies, with some budgets subject to cuts year after year. This research looks to answer why some agencies are more affected by budget cuts. I theorize that differences are explained by the politicization of the agency’s function. Specifically, I emphasize the role of neoliberalism, a political ideology which promotes fiscal and moral conservatism, as well as laissez-faire approaches to government. This presentation hypothesizes that subfunctions that have roles which conflict with neoliberal values, such as those pertaining to education, training, and social services, will experience non-incremental budget decreases more frequently than subfunctions that reflect greater neoliberal values. To test this theory, annual appropriations data for 64 subfunctions was collected, resulting in a database of budget outcomes from 1977 to 2018. Preliminary multivariate regression models suggest that while a subfunction’s “neoliberalness” has some effect on the magnitude of budget cuts, specific subfunctions can experience budget patterns that are not explained by neoliberalism alone. This research adds to existing policy literature by exploring the intricacies of budget-making that have previously been dismissed as chaos.

The effects lobbying has on Congressional voting has been debated for a long time. Despite scholars’ consistent findings that there is no relationship between campaign contributions and a legislator’s vote, special interest groups continue to routinely contribute money to members of Congress. In this project, I consider the connection between contributions from the finance industry and failed legislative efforts aiming at regulating Wall Street or providing greater financial consumer protections. I employ multivariate regression analysis to examine lobbying contributions to individual members of Congress and their subsequent roll call votes in Congressional sessions during 2009-2018. I test for an explicit connection between the finance industry’s lobbying contributions and the inability for Congress to pass financial reforms post-2008. Since campaign finance plays a vital role in the ability for a politician to be elected to office, I expect to find that a congressperson receiving contributions from the finance industry will be inclined to vote in favor of those interests. The findings from this research contribute to the conversation of the influence of big money in American politics and the influence those interests have on specific legislation.

The United States military is a massive proponent for airstrikes and utilizes them in place of ground forces. Although people expect airstrikes to increase precision and reduce civilian casualties, military conflicts continue to last for years. Nevertheless, the United States continues to rely on airstrikes as a principle strategy despite prolonged military conflicts. It is puzzling why the United States would transform military strategy to include a heavy reliance on airstrikes despite few indicators showing its success as a strategy. This research paper examines whether U.S. airstrikes reduce the magnitude- or the total civilian casualties- resulting from military conflicts. I expect to find that airstrikes increase civilian casualties and theorize that the use of these strikes is more for domestic favorability than any military benefit. I explore this expectation by using multiple regression analyses on wartime data from the Iraq War and the Syrian Conflict. I analyze the United States' use of ground forces during the Iraq War and its use of airstrikes during the Syrian Conflict, all while controlling for other actors and forces within these conflicts. This analysis provides insight into the capabilities of drone strikes as a means of ending conflict. 

With political polarization in the United States leading to widespread legislative gridlock, the nation is in dire need of instruments to encourage legislators to cooperate with their colleagues regardless of partisan affiliation. This research will investigate how Congress’ ban on earmarks might have affected the tendency of legislators to vote in favor of bills that are not supported by their parties. Earmarks are commonly understood to act as a form of inducement through which legislators can gain electoral benefits within their constituencies in exchange for their cooperation with Congressional leadership. I expected that the presence of more earmarks in a bill would increase the tendency of legislators to back bills that are not supported by their parties. I employ multivariate regression to compare the relationship between the number of earmarks in appropriations bills and the rate at which legislators defected from their party’s position on roll call votes taken. This information is available for bills introduced between 2008 when the rule mandating the declaration of earmark requests went into effect, and 2010 when the ban was enacted. If the data supports this hypothesis then my work will imply that the ban should be repealed to reduce the negative effects of legislative gridlock. If no relationship is apparent; however, it will represent a significant indicator that earmarks in their most recent form provide no benefit beyond the enrichment of the legislators themselves, which would suggest that the ban on earmarks should be maintained.

 Marguerite Trost is an elite Division I women’s rower, who has competed since the age of fourteen, even attaining unofficial world records in the lightweight class. After a strong freshman year performance at the University of Washington, Marguerite suffered a sacral stress fracture which derailed her sophomore season. Despite a perceived state of full recovery, Marguerite suddenly hit a wall, and it seemed as if she had forgotten how to row. Her body no longer listened to her mind, and she felt as if she was disconnected from the movements that she had found second-nature for so long. After a period of anguish and self-discovery, she began to research the barriers she was now facing, hoping that someone, anyone, may have experienced something similar. And it turns out, they had. This paper discusses the “yips”, an under-researched, yet surprisingly prevalent phenomenon found primarily in sports that require precision to a target, such as baseball or golf. The yips can be defined as a movement disorder, one that has physical and mental etiologies, and entails a seemingly irreversible disconnect between an athlete’s muscle-memory and the motion it produces: a task-specific focal dystonia. There is little to no literature on this phenomenon in rowing specifically. In our paper, we intend to explore and evaluate the convergent factors of rowing “yips” such as injury, the Relative Energy Deficiency in Sports (RED-S), mental health, and societal pressures that all influence an athlete’s experience and ultimate performance. Through interviews with sports medicine professionals, ancillary team staff and impacted athletes in multiple sports, as well as current Division I athletes, we will glean a broader understanding of the contributing factors to develop a framework for further study. Additionally, we expect many directions of neurological, physiological, and sociological research to stem from this beginning.

The University of Washington Bothell (UWB) has a campus emergency response team (CERT) that is not widely known or sustainable. Part of its mission is to train students to participate in emergency response and engage them in other CERT activities. However, UWB CERT struggled in its efforts to recruit students for CERT training and raise awareness of CERT and hazard threats among students. This research project analyzed the successes and best practices of CERT programs in other universities across the Unites States and assessed which practices would be most feasible for implementation at UWB. Research methods included reading case studies about best disaster preparedness practices and conducting interviews of staff at different universities to see what works on each campus. A report centering on recommended best practices will be provided to UWB administrators. This should help UWB develop a plan for the creation of a sustainable CERT program which will greatly increase the number of students trained in emergency preparedness and response skills that they can apply on and off campus, as well as keep the university accountable to student safety.

Diversity training in organizational environments has become commonplace in the 21st century. Most contemporary training seeks to make employees aware of implicit bias and the structural inequities that exist from systematic oppression. However, training is often not grounded in evidence-based practices and past research has shown diversity training may increase stereotyping and bias towards minorities. Additionally, high-status groups (e.g., White people, men) may perceive increased unfairness towards high-status members due to the emphasis on diversity, commonly referred as “reverse racism” or anti-White bias. This study seeks to further investigate how applicants view an organization's approach to diversity. White participants will be asked to apply for a scholarship and subsequently rejected. By investigating anti-White bias after a rejection, this study aims to examine whether Whites rationalize rejection with pro-diversity messages to protect against threat. I am also interested in perceived employability: a principle that has been shown to be linked with emotional regulation, health, and self esteem. I predict the magnitude of perceived qualification for a position moderates the degree of anti-White bias reported. Research on organizational diversity is imperative to decrease turn-over rates and increase satisfaction for minority employees.

As dam removals become more frequent across the United States and globally, understanding kelp forest response to coastal dam removals, in particular, is critical for managing nearshore habitat. Dam removals impact flow and sediment regimes of rivers, both of which can influence coastal kelp forests. The removal of the Elwha River, WA dams released ~19 Mt of sediment into marine ecosystems. This sediment flux dramatically influenced the turbidity of the nearshore water column and permanently increased the amount of sediment released from the river. The objectives of this study were two-fold. First, I developed methods to remotely sense and quantify the abundance of canopy forming kelps from aerial images. Next, I determined how changes in suspended sediment concentration and light attenuation during and following a major dam removal event in the Elwha River impacted the growth of nearshore bull kelp, Nereocystis luetkeana. By incorporating remote sensing to quantify the relative abundance of bull kelp in the area, my study observed that following dam removal, bull kelp abundance declined in the study area. This was an unexpected finding because I calculated that suspended sediment concentration decreased following dam removal, thus improving conditions for kelp growth. Although suspended sediment concentration decreased after the dam removals, other factors, such as an increase in herbivorous predation, could have played a large role in suppressing bull kelp abundance. The supervised classification scheme that I developed for remotely monitoring kelp abundance will make analyzing larger areas feasible in future studies, which may help to better identify regional trends in kelp abundance. Marine aerial monitoring remains an important avenue to better predict and manage future kelp forest response to dramatic changes in the ecosystem.

Progress in addressing the simultaneous demands for increasing speed and miniaturization in electrical and computer engineering is to its greatest extent bounded by material stresses under thermal shock. Higher speeds require higher power dissipation, and smaller unit volumes make adequate power dissipation more difficult to achieve. Although there already exists a large body of research concerning endpoint thermal failure in semiconductors, there is little research available on the topic of pre-failure behavior of circuit designs containing semiconductors. Our goal is to subject a circuit containing a semiconductor-based diode to the failure mechanism of thermal shock and test the conductivity of the circuit under drastically changing ambient thermal conditions. We will then use this data to experimentally determine any observable behaviors that qualify as pre-failure symptoms. The resulting observations will be used to determine the efficacy of simulation softwares like LTspice in predicting thermal behavior of a diode circuit under extreme and rapid temperature fluctuations. Our theory is circuit simulation softwares do not account for extreme ambient thermal changes. After completing statistical analysis we will compare the experimental results to simulated results of a duplicate circuit subjected to equivalent temperature parameters and determine if we can reject our theory.

Vaccine hesitancy reflects concerns about the decision to vaccinate oneself or one's children. There is a broad range of factors contributing to vaccine hesitancy, including the compulsory nature of vaccines, their coincidental temporal relationships to adverse health outcomes, unfamiliarity with vaccine-preventable diseases, and lack of trust in corporations and public health agencies. In addition, the very success of vaccine programs has seemingly fueled increasing vaccine concern as vaccine-preventable diseases are no longer prevalent in the United States. This decrease in prevalence has led the attention of the public to shift from the necessity of vaccines to the safety of the vaccines themselves. In light of the current COVID-19 pandemic and the heavy economic and public health toll it has taken, it became clear that a vaccine may be the “magic bullet”. In the midst of a pandemic that is taking thousands of lives and has been devastating society, many people will find these uncertainties acceptable. While for others, as with many trade-offs, the benefit may have less emotional resonance than the possibility, no matter how small, of a potential risk. My research seeks to understand the risk perceptions of vaccination in an adult population in the Puget Sound region of Washington state. My hypothesis suggests that social proximity to COVID-19 will influence vaccine decision making & vaccine risk perception. I will be using the annual influenza shot as well as assessing smaller recent outbreaks to build a framework for my thesis. Understanding the factors that are influencing adults, when it comes to vaccine decision making, may help inform strategies for state and public health officials in their multifaceted roles of communicating effectively on the benefits and safety of vaccines to policy makers, media, and the public as a means to better support informed decision making.

DNA damage occurs regularly, and although the cell has numerous repair mechanisms to counteract it, some DNA lesions may persist. Many of these lesions can be bypassed by DNA and RNA polymerase, with replicational mutagenesis leading to permanent mutations in the genomic sequence, and transcriptional mutagenesis leading to mutant transcripts that may direct the production of mutant proteins. We hypothesized that transcriptional mutagenesis is a mechanism for initiating adaptive mutagenesis, which occurs in nondividing cells in direct response to a selective pressure, allowing cells to overcome the selection and resume cell division. Our lab has previously demonstrated that DNA damage leading to adaptive mutagenesis in yeast is biased to the template strand relative to transcription, supporting this hypothesis. Unexpectedly, DNA damage leading to replicational mutations in our system is similarly skewed to this strand, although the sequences surrounding these two classes of mutations seems to differ. We hypothesize that sequence context is important for determining whether certain mutation sites are more likely to contribute to replicational or adaptive mutagenesis. To address this hypothesis, our aim was to create Trp5 mutant yeast strains using CRISPR/Cas9 in which the mutation occurred in a sequence context-specific manner, and the reversion of which could be scored for both replicational and adaptive mutagenesis. The CRISPR/Cas9 system required generation of a plasmid containing the target sgRNA (via molecular cloning techniques) as well as a linear repair template with the mutation of interest (via a two-step PCR protocol). Creating both of these components proved challenging, and optimization of the protocols will be required. Once we have all the components for CRISPR/Cas9-mediated mutagenesis, future research involves creating the mutant strains and assessing whether the sequence context affects the mutation frequency with respect to either replicational or adaptive mutagenesis.

Herpes Simplex Virus 1 (HSV1) is a prevalent lifelong virus transmitted through oral-to-oral contact resulting in painful oral sores. HSV1 may also give rise to encephalitis, or inflammation of the brain, and has even been linked to sporadic Alzheimer’s Disease (AD). Typically, HSV1 enters through the oral cavity, replicates, invades nearby clusters of sensory neurons that innervate mucosal membranes called the trigeminal ganglia, and can ultimately lead to infection of the brain. HSV1 can establish latency in these trigeminal ganglia and other neuronal nuclei, and can reactivate in the brain in response to external stresses at any point in time. Previous studies have even shown presence of HSV1 in the brain. However, this process of reactivation is still not understood. Our goal is to comprehend the mechanisms of HSV1 reactivation in the brain by generating two recombinant HSV1 through the CRISPR-Cas9 gene editing system. One strain will contain an insertion into the HSV1 genome of luciferase and mEmerald, a green fluorescent protein, for detection of cells with reactivating HSV1 through in vivo imaging of bioluminescence. The second strain will have an insertion of Cre recombinase and mEmerald. When this strain is injected into a mutant mice line with a Cre-dependent reporter gene, the Cre recombinase can lift genetic repression of a red fluorescence protein. This prompts all cells with an HSV1 infection, including those with past reactivation, to be detected. Through these novel recombinant HSV1 strains, we can monitor viral reactivation in brain cells in response to different external stresses in vivo, examine the time course of the infection, and distinguish areas of the brain with high viral load, especially cell types vulnerable to HSV1 infection. These experiments will be the stepping stone for improved investigation of viral latency and reactivation and understanding the connection between HSV1 and AD.

IMPDH1 catalyzes the rate limiting step of de novo guanine synthesis. cGMP is a critical signaling molecule involved in phototransduction in rod and cone photoreceptors. In humans, nine mutations in IMPDH1 lead to Retinitis Pigmentosa and Leber's Congenital Amaurosis; however, the cause of retinal degeneration is unknown. In zebrafish, IMPDH1a is the major variant in the retina, exclusively expressed in rod and cone photoreceptors. To understand the function of IMPDH1, we utilized an IMPDH1a knock-out (KO) zebrafish line. Loss of IMPDH1a does not lead to retinal degeneration, and cGMP levels remain unchanged. However, retinas lacking IMPDH1a show a 61.6% reduction in guanine. Since photoreceptors do not undergo cell division, mitochondrial DNA (mtDNA) synthesis would be a major use of guanine during mitochondrial biogenesis and turnover. Under normal conditions, the amount of mtDNA between the KO and WT zebrafish was the same. To eliminate the potential that KO fish could supplement guanine from their diet, fish were starved for 24 hours. Starved IMPDH1a KO showed a trend of increased mtDNA compared to WT fish. Interestingly, starved fish had about four times the amount of mtDNA for both WT and KO compared to fed fish. Starvation may increase mitochondrial DNA copy number to increase efficiency of ATP production by increased utilization of oxidative phosphorylation. Reducing guanine levels by knocking out IMPDH1a in zebrafish retina does not affect mtDNA or nDNA levels, and the photoreceptor cells appear healthy. Although more research is needed, silencing the gene encoding for IMPDH1 could be a possible therapy for those suffering from the effects of its mutation.

Cancerous cells have a modified metabolism that supports their demands for increased proliferation. One of the essential molecules in cancer cell metabolism and proliferation is the amino acid aspartate. Aspartate is not only incorporated into proteins, but is also a substrate for nucleotides and other amino acids, including asparagine. Aspartate availability can constrain tumor growth rate, and the consumption of aspartate to generate downstream products can alter aspartate levels. One gene that draws from the aspartate pool is asparagine synthetase (ASNS). ASNS converts aspartate into asparagine, which is used in the production of proteins, but does not increase cell proliferation. Thus we hypothesized that ASNS expression and activity can affect aspartate levels. With this, we aimed to determine if ASNS expression could alter aspartate availability and change sensitivity to aspartate suppressing therapies. Since cancer cells express ASNS to varying degrees, my project sought to determine if ASNS expression could be used to identify those cancers that are most amenable to aspartate suppression therapies. To test this I generated cell lines that express ASNS in different ways and treated them with multiple electron transport chain inhibitors. Preliminary results suggest that cells that express ASNS to a higher degree are more susceptible to mitochondrial inhibitors. More broadly, this research sought to better understand the conditions that determine aspartate levels, and how to exploit those conditions to inhibit tumor growth in association with asparagine synthetase.

Duchenne Muscular Dystrophy (DMD) is a severe muscle wasting disease caused by the deficiency of dystrophin protein affecting ~1 in 3500 boys. Exercise has been investigated as a potential therapy but has shown conflicting effects on dystrophic muscle. Animal models that have been studied but do not fully mimic the disease and cardiac phenotype. Here, we provide the first known evaluation of exercise in a new DMD mdx rat model that mimics skeletal muscle and cardiac pathology. Having an animal model that better reflects the DMD cardiac phenotype is crucial in establishing physical activity guidelines that minimize potential damage to the heart. In Aim I of this pilot study, DMD mdx rats (n=3) and sibling wildtypes (WT; n=3) were assigned to wheel or treadmill exercise training groups (high intensity or low intensity) or unexercised (sedentary) for 6-weeks. Throughout this 6-week period, I was responsible for executing the rat treadmill exercise training protocol at low-to-moderate intensity (5x/week), and monitored the rat wheel running activity. Physiological measurements were conducted pre- and post- training (wheel running, treadmill testing, grip testing, echocardiography, and hindlimb force testing). Compared to wheel running or unexercised rats, treadmill training produced the greatest gain in treadmill exercise endurance testing and in fatigue-resistance in in-vivo hindlimb force testing for DMD rats. However, the treadmill program was associated with severe cardiac effects in DMD mdx, indicated by significant fibrosis and inflammation and echocardiography (Myocardial Performance Index, % fractional shortening and ejection fraction), a finding which will be investigated in subsequent cohorts.

Mycobacterium tuberculosis (Mtb) is a bacterium that kills nearly 2 million people annually and continues to be a large threat to the health of individuals around the world. T-cells play a key role in the immune response to Mtb infection, but there is still much we do not understand about their role in mediating protection. CD4 and CD8 are glycoproteins found on the surface of T cells. CD4 and CD8 T-cells recognize glycolipids associated with the bacterium, such as glucose monomycolate (GMM), that are presented by the cell-surface glycoprotein CD1b on a human antigen presenting cell. I am focused on identifying the T-cell receptor (TCR) of a T-cell line from the Rhesus Macaque species. Using newly validated CD1b tetramers, I sorted for T-cells that can bind to the GMM lipid antigen using flow cytometry. The tetramer is made up of four CD1b molecules which present the antigen and bind to T-cells that have a matching receptor. I used various molecular techniques such as RNA extraction, 5’ RACE PCR (a procedure for amplification of nucleic acid sequences using a messenger RNA template), and in fusion cloning to determine the TCR gene sequence of the alpha and beta chain regions. By identifying the sequence of a T-cell receptor in the Rhesus Macaque species we will be expanding our knowledge of how T cells recognize Mtb lipids in non-human primates. Since we have previously published that CD1d-restricted TCRs are very similar between NHP (non-human primates) and humans, we expect the same is true here. We can use tetramers and the NHP model to understand how lipid-specific T cells are important for controlling Mtb.

Enteric alpha defensins, such as human defensin 5 (HD5), are antimicrobial peptides secreted by Paneth cells in the lumen of the small intestine as part of the innate immune response. Defensin activity effectively inhibits many bacterial and viral pathogens during infection. However, not all pathogenic human viruses are neutralized in the presence of defensins. For example, among the seven human adenovirus (HAdV) species, infections of certain serotypes are enhanced by HD5, while other serotypes are inhibited. Our goal is to identify the molecular determinants that confer HAdV neutralization or enhancement by HD5. We have previously identified regions of the three major capsid proteins that form the outside of the virus, hexon, penton base, and fiber, as key determinants. We identified these determinants through rational design and the creation of chimeric viruses in which we swapped portions of the three major capsid proteins between two serotypes with opposite HD5-dependent phenotypes. From these data, we have created a model of the enhancement and neutralization mechanisms. To further test these models, I am creating a panel of chimeric HAdVs by swapping capsid components from additional HAdV species and serotypes. I will study the concentration-dependent effect of HD5 on each chimera’s infectivity compared to the wild type viruses, which will uncover new mechanistic detail and allow us to create a more generalized model.

Parkinson’s Disease (PD) is a neurodegenerative disease that affects movement and often leads to tremor, rigidity, and balance issues. Speech impairment, or dysarthria, is also common and may influence many aspects of speech production, such as respiration, articulation, phonation, and prosody. There are currently multiple methods for measuring speech impairment severity over time. Often, severity of dysarthria is captured by neurologists during administration of a global measure of PD severity, the Unified Parkinson’s Disease Rating Scale (UPDRS). This scale uses one question to assess speech impairment severity on a perceptual level, but does not formally evaluate specific characteristics, such as intelligibility. Alternatively, speech-language pathologists may use measures of speech intelligibility to assess dysarthria severity. This method systematically quantifies the extent that speech was understood by a listener. The connection between these two approaches is currently unknown. Therefore, the purpose of this project is to examine the relationship between UPDRS scores and speech intelligibility metrics, two commonly-used indicators of dysarthria severity in PD. Connected speech samples for 27 individuals with idiopathic PD were collected. UPDRS ratings were completed independently by a speech expert who was blinded to intelligibility scores. Speech intelligibility ratings were based on 100-word speech samples and averaged across three listeners. Statistical analyses will include Pearson correlation to determine the strength of this relationship. Expected findings include a significant negative correlation, suggesting that increased severity on the UPDRS (higher score) corresponds to increased severity on the speech intelligibility calculation (lower score). Determining the relationship between these two indicators of speech severity will unite clinical understanding of speech impairment across the fields of neurology and speech-language pathology. This will also indicate whether a single speech severity question equates to more time-intensive intelligibility ratings.

This paper aims to explore the gender wage gap in the University of Washington. We use data collected from College of Arts and Sciences to analyze how faculty members' salary might be affected by different factors. The number of women who entered into the labor market grew exponentially after the Second World War and women tended to spend longer hours for work. But this fact did not eliminate the existence of gender wage gap. Researching the gender wage gap in academia is unique because academics employed usually obtain relatively homogeneous education and job trainings such as earning Ph.D. degree. The factors we examine which may have an impact on the salary difference include gender, department, and the years of attainment of Ph.D. degree. This observational document study also intends to show how the number ratio of female faculty members and male faculty members differ in different department and discuss whether implicit discriminations exist. Women may spend longer time to complete Ph.D. degree due to that female's presentations and works somehow seem to face more biased judgments comparing with male by mentor or adviser and thus have less potential job experience. Women professors may experience more years in the process of tenure promotion which can lead to direct salary increase than male peers. 

While technology advances and continues to increase its influence on the world, we need to scrutinize the process in which these technologies and digital platforms are created. Throughout history, there have been repeated offenses of colonization in design that erase or undermine the work of underrepresented communities. With this research, our goal is to destabilize design practices in Human-Computer Interaction (HCI) reinforced through pedagogies that seek to uphold unquestioned and dangerous societal norms. Our research centers around analyzing how colonization is enabled in HCI pedagogy, both inherently from academia and uniquely to HCI, and what the impacts of such colonization are on students in HCI learning spaces. For our methodology, we employed methods of literature review, reflexive writing, and storytelling to design a toolkit facing HCI students. We reviewed literature concerning critical race theory, queer theory, feminist theory, postcolonial and anticolonial design approaches, and design justice in HCI that evoked reflection on our positionality as student designers. Our discussion of past literature and personal stories informed the creation of a design toolkit with the goal of encouraging students to identify and critique current HCI practices in pedagogical materials. The toolkit explored tangible methods and frameworks to deconstruct colonized systems in HCI pedagogy and decentralize whiteness in design, as well as articulated the burden and responsibility of resistance in marginalized communities. Throughout the toolkit, we facilitated daily probe activities and interviews with student communities, in which we asked students to document their thoughts and learning process in a multimedia format. With this study, we hope to enact change within HCI student communities by highlighting colonial concerns in modern HCI pedagogy and providing actionable steps for inclusion, advocacy, and resistance.

 In the United States, there are approximately 2.5 million people with spinal cord injuries (SCIs). Depending on the location and severity of the injury, SCIs can result in long-term motor and sensory impairment. A very promising technology in neurorehabilitation for people with SCIs is transcutaneous spinal cord stimulation (tSCS). tSCS is a novel, non-invasive technique that stimulates the spinal cord through the surface of the skin. Recent clinical studies have already shown that tSCS is effective in helping to rehabilitate people with SCIs. However, while the rehabilitation method is sound, the physiological effects of tSCS on muscle recruitment are not well understood. Therefore, we are investigating the modulation of the spinal networks after the intervention with tSCS. Six patients with cervical SCIs underwent physical training paired with tSCS. Before and after training, SCS was used to induce motor evoked potentials which were measured with electromyogram. Evoked responses were extracted and analyzed by comparing peak to peak amplitude. After training and tSCS, both motor function and motor evoked potential amplitude increased, providing evidence that tSCS improves rehabilitation outcomes by modifying spinal networks. This research could lead to innovations in neural engineering and rehabilitation medicine and could greatly improve the quality of life for many people with SCIs.

Reactive astrogliosis is a condition where astrocytes, a type of brain cell, undergo morphological – shape - changes upon exposure to brain injury. Morphological changes of astrocytes are a key indicator of activation and can be beneficial in stopping initial brain injury effects, but chronic activation can drive glial scarring, which is detrimental for full recovery of normal brain function. Glial scarring has been linked to several diseases, including traumatic brain injury, Alzheimer’s Disease, and dementia. The purpose of this work is to quantitatively analyze the relationship between frequency and extent of reactive astrogliosis with relation to distance from the primary site of brain injury. My approach is to build a Python-based image analysis pipeline to quantify astrocyte cell features. The Nance Lab’s prior work using Python packages was effective in developing a pipeline to identify and quantify microglial - a different type of brain cell - shape properties. We are now building a pipeline to study astrocytes in brain slices from the injured preterm ferret brain, which were stained with an antibody for glial fibrillary acidic protein (GFAP). Images of cells at 20x magnification are provided by Dr. Tommy Wood. Since response to injury can be brain region and animal sex dependent, I analyze astrocyte cell features in each region of the brain from both sexes of ferrets. I used SciKit-Image along with other packages to segment, label, and quantify features of our cells, including perimeter, area, and circularity, among others. Expected results include a significant reduction in area and an increase in perimeter (larger surface-to-volume ratio) of cells that are closer to the injury. This image analysis pipeline will give us quantitative information about the cells morphology which are associated with biological markers that can be targets for future therapeutic treatment. Clear biological markers help researchers develop better treatment.

Mitosis produces two genetically identical daughter cells, each inheriting their own nucleus and a full set of replicated chromosomes from the parent cell. Inaccurate chromosome segregation can result in severe consequences like cancer and developmental defects. Microtubules are dynamic cytoskeletal components that provide the forces necessary to segregate chromosomes into their respective daughter cells during mitosis. The kinetochore is an assembly of proteins and protein complexes located on the centromere that binds to microtubule ends to attach chromosomes to the force-generating microtubules. The accurate segregation of chromosomes relies on the ability of the kinetochore to strongly bind chromosomes to microtubule ends. Ndc80 complex is an outer kinetochore component that binds microtubule ends and is required for proper chromosome segregation. Emerging cellular data suggests that multiple Ndc80 complexes interact with one microtubule end to facilitate chromosome separation. In vivo data suggests multiple Ndc80 complexes are arranged around microtubules. To closely model the native kinetochore-microtubule interface, we have begun to assemble a structured particle of multiple Ndc80 complexes in vitro using designed proteins that form oligomers. The particles have different geometries and stoichiometries. A method to couple Ndc80 complex to the designed protein was developed. We then tested the coupling efficiency under different temperatures and concentrations to optimize the reaction and ensure complete particle assembly. We found that the reaction goes nearly to completion with a 3:1 ratio of Ndc80 complex to designed protein at room temperature with a reaction time of thirty minutes. We will now measure the stoichiometries of the particles, which are designed to have four, five, or six Ndc80 complexes. Successful formation of these organized particles will allow us to measure the effect of geometry and stoichiometry on the ability of the Ndc80 complex to make strong attachments to microtubules.

Photosynthetic bacteria are ideal systems for the sustainable production of chemicals, but their chemical production is limited by the efficiency with which the bacteria can capture and transfer energy. For this project, I have designed light-harvesting proteins that bind chlorophyll molecules that absorb light of the wavelength reflected by the photosynthetic bacteria Rhodobacter sphaeroides. The LH1 and LH2 light-harvesting complexes found in R. sphaeroides bind chlorophyll molecules in a manner that promotes excitonic coupling and minimizes the energy lost during transfer from the complexes to the reaction centers. The proteins I have engineered are modeled after LH2 and are designed to bind a symmetric ring of pi-stacking chlorophyll dimers, promoting high-efficiency energy transfer between light-harvesting complexes. After characterizing these light-harvesting proteins, they will be further engineered to enable their expression in R. sphaeroides, which will allow these bacteria to absorb a broader range of the solar spectrum and improve their energy transfer efficiency. Incorporating this de novo designed protein into metabolically engineered R. sphaeroides will enhance these bacteria’s ability to convert carbon dioxide to useful chemicals. These engineered light-harvesting proteins could also later be adapted for use in hydrogel-based organic solar cells and forming a 2-D sheet of light-harvesting proteins. In my presentation, I will discuss how I have used the Rosetta protein modeling suite to design hexameric chlorophyll-binding proteins. These proteins are designed to bind twelve chlorophyll molecules, and their cyclical symmetry simplifies the design process. I will present data from characterization experiments such as circular dichroism and fluorescence spectroscopy, which are methods that allow for quantification of the proteins’ binding affinities towards the ZnPPaM chlorophyll, and small-angle x-ray scattering (SAXS) and Size Exclusion Chromatography/multiple-angle light scattering (SEC-MALS), which provide information about the predominant oligomeric states of the designed proteins.

During mitosis, chromosomes are organized and separated by the dynamic mitotic spindle. The kinetochore plays a central role in proper chromosome segregation. It is recruited by specialized sites on the chromosome, known as centromeres, and forms attachments to the spindle microtubule. The Dam1 and Ndc80 complexes are essential microtubule-binding elements of the outer kinetochore in budding yeast. The Ndc80 complex bridges the kinetochore to the dynamic microtubule tip, while the Dam1 complex enhances the Ndc80 complex’s residence time on microtubules and load bearing ability. It was previously reported that swapping yeast histone proteins with human histone proteins resulted in poor complementation, in higher frequencies of aneuploidy, and impaired adaption to novel nutrient environments. Several mutations in the Dam1 complex and one mutation In the Ndc80 complex were found to independently rescue these defects. To determine how these mutations rescue human histone swapping in budding yeast, we purified mutant versions of the Dam1 and Ndc80 complexes. We used an optical trap to measure if the mutations alter the amount of force required to break attachments to a dynamic microtubule. A difference in rupture force between wild type and mutant proteins tells us that the mutations rescue histone swapping by changing the load bearing ability of the kinetochore-microtubule interface. Further study is needed to determine the mechanism for rescue. A null result tells us that further research is required, and a novel interaction may be present. This research will uncover differences in human and yeast kinetochore structure and function.

During the Victorian period, a growing middle class and widespread industrial advancements led to the development of serialized fiction and the modern novel. Well-educated writers who had previously referenced classical antiquity in poetry now introduced a new generation of readers to Ancient Greek and Roman authors via the realistic novel. Charlotte Yonge’s best-known novel, The Heir of Redclyffe (1853), has often been interpreted as a promotion of her own religious beliefs in the context of the Oxford Movement and Tractarianism. In addition to Christian themes, Yonge also makes several classical allusions throughout the novel, including a double reference to Vergil’s Aeneid, where she likens the characters Philip Morville and James Thorndale to Aeneas and Achates respectively. The comparison of Philip to Aeneas, one of the most highly esteemed and recognized classical heroes in the Victorian era, centers Philip as the primary protagonist and titular heir of the novel. I also propose an additional parallel between Philip’s cousin Guy Morville and Aeneid’s Pallas to both reinforce Philip as the focus of the novel and to demonstrate Guy’s role as an archetypal hero’s companion. For this project, I compare Philip and Aeneas’ journeys to Redclyffe and Latium, respectively. I also analyze the differences in companionship between James/Achates and Guy/Pallas. The dynamics between each trio lead to a reading of The Heir of Redclyffe as an epic journey and more broadly demonstrate how classical influences shaped story and character in a traditionally Christian morality tale.

Good mental health and well-being are essential to fulfillment in all aspects of life, including the workplace. Although there are many factors that influence mental health and well-being, a new, universal stressor has emerged in the past year: the COVID-19 pandemic. While many are socially distancing and working remotely, those employed in the restaurant industry continue to work in a high-risk environment. Restaurant workers were already mentally and financially vulnerable pre-pandemic, earning low wages and experiencing high rates of substance abuse-- and they now face the additional stressor of potential exposure to COVID-19. Ongoing research suggests that restaurant employees are facing unprecedented pandemic-related challenges to their mental health and well-being. This study explores the experience of restaurant employees in Western Washington who interact with the public regarding their communication about mental health and well-being. The main research questions are: a) Are restaurant employees having conversations about mental health and well-being with their coworkers and with their managers? If not, why not?; b) How do restaurant employees describe communicating about mental health and well-being with their coworkers and with their managers?; c) How do the descriptions about communication with coworkers compare to that with managers? To answer these questions, an exploratory cross-sectional survey was conducted to gather self-report data from a nonrandom sample of restaurant employees in Western Washington. At the time of writing this abstract, all data has been collected and the data analysis phase is beginning. By the time of the symposium, I will be able to report key findings on measures including the prevalence of restaurant workers’ conversations about mental health and well-being, with whom they occur, why they may not occur, the specific topics discussed, when and how these conversations take place, and motives prompting these conversations.

Chinese adoptees have played a significant role in the makeup of transnational adoption in the United States. Due to the intense measures of China's One Child Policy from the 1980's to early 2000's, a large influx of Chinese adoptees were brought to the US and became part of many multiracial families. From this, a unique population of Americans today engage in difficult conversations to clarify and defend their own identity in a multiracial family. These conversations can lead to negative psychological and behavioral outcomes that qualitative investigation can aid in addressing. This study aims to investigate how Chinese American adoptees respond and process these comments and conversations that question their legitimacy as a member of their family.  Methods used for research include qualitative interviews and thematic analysis. Analysis will focus on common patterns in adoptees' responses and types of interactions described during the interviews, grounded in the Communication Theory of Resilience. Communication Theory of Reslieience is the interpretive method that highlights the communicative processes by which people reconstruct a new normal after facing adversity. Results will inform us how Chinese American adoptees choose to respond to these comments, and/or how they would like to respond and construct these conversations in a form of resilience to disruptive narratives around adoption. By understanding how adoptees respond to and handle these conversations, we hope to provide insight for other Chinese American adoptees and their social networks in how to navigate these situations and best support adoptees in communicating their story. 

Hate speech classifiers, which are machine learning models that detect hate speech, are important tools for content moderation online and help keep online communities safe. However, these models show evidence of bias against certain groups of people. For example, current research shows that state-of-the-art hate speech classifiers show significant bias towards African American Vernacular English (AAVE). In response, new research has produced novel datasets with more complex label spaces compared to previous hate speech classification datasets. By having additional labels (i.e. more than a single label determining whether the text is hateful or not), these datasets aim to capture more social context embedded in natural language. In this project, we investigate this aforementioned claim. In particular, we investigate which features of language are the most salient in the decisions they make based on the datasets that they are trained on. We use multiple methods to determine feature saliency to discover biases in hate speech classifiers. Through these methods, we introduce a set of words that hate speech classifiers determine as highly salient which represent these biases. We also investigate whether these sets of words differ across datasets with varying label space complexity to understand whether these biases persist regardless of dataset. Finally, we will discuss the implications of the results and address future directions for the project.

Data-driven predictions of the future often suffer from error propagation and overconfidence. In many scenarios where forecasting is practical, the data follows a quasi-periodic pattern, which means that data from one point in time relays useful information about the data one period later. Through a Koopman theoretic approach, we make use of this feature to make long-term probabilistic forecasts that do not suffer from error propagation. Overwhelmingly, data-driven forecasts attempt to predict the exact value of a quantity into the future; however, such point-forecasts fail to describe the uncertainty in that quantity. Even when models are designed to make probabilistic forecasts, they are often overconfident and rely on the model to supply all sources of uncertainty. By forecasting the parameters of a probability distribution describing a quantity, rather than the quantity itself, we are also able to overcome the problem of overconfidence. Furthermore, our model relays novel and useful information about temporal patterns in the uncertainty of a dataset. We apply our model to electric load data from the 2017 Global Energy Forecasting Competition and show significant improvements compared to competing forecasts. I implemented the approach and ran experiments to explore the ways in which Koopman theory can be leveraged to robustly mitigate error and overconfidence in electric load forecasting. Our contributions to probabilistic forecasting of energy demand have the potential to lessen global warming, and the approach can be used in forecasting problems more broadly.

Amidst the turn of the twentieth century, few women were accounted for witnessing the advancement of archaeology, later known as the "Golden Age'' of Egyptology. In fact, much of the source material by women in this period have been misplaced or yet to be published. Mrs. Emma B. Andrews wrote nineteen volumes of diaries while observing the unearthing of over twenty tombs in the Valley of the Kings. The Emma B. Andrews Diary Project seeks to introduce Mrs. Andrews's works—and other unpublished historical documents composed by women during the time—to modern platforms, such as an online reader and social media. The transcribed texts are encoded into XML, using Text Encoding Initiative Guidelines, and the structural and contextual elements are denoted. The TEI documents are currently being used to create a comprehensive database for scholars and students alike to read the compositions of the lesser-known women of Egyptology. Accompanying the transcribed texts are biographies to equip the readers with additional context. However, we interns stepped further into this project by attempting to answer a fundamental question—how did Mrs. Andrews's accounts of her day-to-day interactions reflect the manner she viewed her life, and therefore herself? Guided by this question, we used research methods involving an analysis of Mrs. Andrews's language and identification via XML-TEI of the various contextual elements referenced—the people, places, hotels, and boats she encountered. These components were also cross-evaluated with further sources, including a sentimental analysis tool, to provide supplemental information to our study. After converging Mrs. Andrews's life history with recognized research in memory retrieval, we have noted observations on how her writing reveals her distinct perspective of the world and how her past may have influenced that point of view.

This research and public history website explores Jewish immigration experiences and Americanization from the perspectives of young Jewish immigrant women around the turn of the 20th century. I used archival material from Cornell University’s School of Industrial and Labor Relations to highlight these women’s voices, and archives from the Tenement Museum and the Jewish Daily Forward to illustrate Jewish life in this period. Additionally, archives from the New York Times were used to examine how Jewish immigrants were viewed. I searched these archives for primary sources to shed light on how Jewish immigrant women worked and lived, including how life in the Lower East Side’s cramped tenements was photographed and written about by outsiders - White society, and how this propagated the notion of Jewish people as Others. My goal for this research was to tell the stories of these women and listen to their voices. They tell of long hours in crowded and often dangerous garment factories, of unionizing and striking for better labor conditions, and the tragedy of the Triangle Shirtwaist factory fire. These women were often the main breadwinners for their families, but many saved a little for themselves to spend on ‘American’ activities such as seeing shows, frequenting dance halls, and developing an interest in ‘American’ fashion and buying clothes. White society dubbed these women’s fashion as tacky, outlandish and vulgar. Their dresses were described by White society, as well as their own community, as cheap knockoffs of the dresses they made, with too many bows, too much jewelry, and too much makeup. These immigrant women were often called ‘Ghetto Girls,’ as the Lower East Side was called the Jewish Ghetto at this point. This research also brings the present into focus and examines how immigrants are viewed and often judged. 

Seattle has a notable history of racial segregation concerning residential discrimination that persists in its neighborhoods and schools. Segregation is often narrated as a result of private discrimination and demographic development. However, this story implies that modern segregation is not a product of government actions and unconstitutional policies, which removes the responsibility of the law to provide legal remedy for the continued existence of segregation. The consequences are evident in how legal actors, such as judges, frequently perpetuate “colorblind” language in their court cases. My study centers on the question, “How does the ‘colorblind’ approach in legal discourse exacerbate the issue of segregation of public schools?” To answer this question, I conduct a legal analysis by reviewing court decisions and review literature on the aftermath of selected court decisions and their outcomes on racial equity and segregation. In particular, I concentrate my textual analysis on pivotal court decisions on segregated public school education in Seattle and the use of colorblind rhetoric practiced by the United States Supreme Court, such as in the case of Parents Involved in Community Schools v. Seattle School District No. 1 (2007); Parents Involved in Community Schools v. Seattle School District No. 1 (2007) defeated a voluntary desegregation program established by the Seattle School District. Predicted findings are that in an effort to assume a non-discriminatory, universal perspective, legal discourse often overlooks the extensive history of racism that has developed the American legal system and results in a legal system that undermines and defeats efforts to establish race-conscious policies. This study sheds light on why Seattle’s public schools remain racially divided, and how the law contributes to this legacy of segregation.

School segregation is viewed as a problem of the past as schools have become more racially integrated since the Jim Crow Era and the Brown v. Board of Education of Topeka court case. However, a new wave of segregation is still present in our school system as a result of systemic inequalities that stem from continued racial segregation such as socioeconomic inequalities and redlining. The goal of this project is to critically examine the public school system in the Seattle area and expose disparities that exist between the more affluent, predominantly white North Seattle area versus lower income and more racially diverse communities within South Seattle. I conducted qualitative interviews with Black, Indigenous, and People of Color (BIPOC) students from each area to compare how their education differed in higher education preparation. Predicted results are that there are significant disparities in educational experience for BIPOC and other disadvantaged groups in the greater Seattle area as they lack equitable access to academic resources and enrichment classes either from school bias or underfunding. Results may also inform us of how the racial population is disproportionately spread across Seattle as a result of redlining and district dividing lines, with BIPOC taking up more lower income areas with less access to education. By studying the experiences of BIPOC in the Seattle area, I hope to help bring awareness to the still present issue of segregation in our school system. As they speak on their own personal experiences, we can learn how to better support these students and work towards structural change to dismantle the inequities they face in our current education system.

 Long-toed salamanders (Ambystoma macrodactylum) are common amphibians throughout the Pacific Northwest, making them an ideal species to use for restoration assessment. A successful wetland restoration project would be expected to have a healthy long-toed salamander population, but it was not previously known whether long-toed salamanders were present in the Union Bay Natural Area (UBNA), a Seattle park with many ongoing restoration efforts. The Amphibian Corridor restoration project in UBNA, installed in 2015, aimed to provide amphibian migration habitat. To assess its efficacy, I examine long-toed salamander movements and woody debris microhabitat preferences within and around the corridor. The study also acts as an inventory of amphibians present in the corridor and throughout UBNA. The corridor and surrounding areas are being monitored throughout the 2021 breeding season (January through May) for adults, larvae, and egg masses. To find larvae and egg masses, dip net aquatic surveys are conducted once per week, alternating between day or night surveys. To find adults, visual encounter terrestrial surveys are conducted once per week, alternating between day or night surveys. Individual salamanders are photographed and identified by their unique spot patterns so that individual movement can be tracked using a mark-recapture method. The location and microhabitat of all amphibians are recorded . My surveys have shown that long-toed salamanders use the corridor. To date, 18 individuals have been recorded in the corridor with up to 10 recaptures per individual, and 11 individuals have been recorded in other parts of UBNA with up to 8 recaptures per individual. Three egg masses have also been found in UBNA. UBNA management and future restoration could be informed by this study’s insights about long-toed salamander microhabitat preference and movement strategies. Given this information, similar restoration projects to the Amphibian Corridor in other urban parks may be effective for amphibian conservation.

Seed dispersal is a crucial phase of plant lifecycles. Effective dispersal is important to the ecosystem as a whole because it affects composition of the community, ecological succession, and response to climate change. Given the importance of seed dispersal, understanding the factors that contribute to the evolution of varied dispersal modes and promote convergence on specific dispersal strategies is particularly important to understanding plant ecology. We think habitat might be one of these important factors. Here, to explore the relationship between habitat and dispersal mode, we are studying the onion grasses (Melica), a small genus of perennial grasses primarily distributed in temperate regions, and their relatives. These grasses are found in a wide variety of habitats and possess a remarkable diversity of seed dispersal strategies. These traits make them a useful case study for better understanding the factors that influence the evolution of dispersal strategy. We are testing the hypothesis that evolution in traits associated with seed dispersal is correlated with changes in habitat. In particular, we hypothesize that the evolution of wind dispersed seeds follows transitions into open habitats. Seed dispersal structures (diaspores) were collected from 28 grass species (14 Melica and 14 outgroup). To assess wind dispersal potential, we quantify falling velocity by filming seed descent at 1000 fps. Lower falling velocities are associated with higher wind dispersal potential. Diaspores were photographed and the images were used to measure surface roughness, which is associated with adhesive dispersal potential. Habitat data were obtained for each species via a literature survey. These data, along with several other traits associated with seed dispersal processes, were mapped onto the evolutionary tree of the onion grasses. Initial results indicate that convergence upon wind dispersal may be in part driven by convergence upon disturbed habitat types.

Currently, in the United States and worldwide, the population is aging, living longer, and the increase in people living with dementia (PLWD) will continue to rise. Many PLWD receive care from their primary care clinicians, who face unique challenges caring for this population given decline in cognitive function, overall health and unpredictable behavior requiring more attention. Gaps in care could be addressed through the development of a cadre of dementia nurse specialists, as much of dementia care is within the scope of nursing practice. However, interest in the aging population is one of the least desirable disciplines to work for new nurses as well as currently practicing nurses. The purpose of this study was to evaluate nursing students’ and practicing nurses’ perceived knowledge and attitudes about providing care for people who are living with dementia and their family caregivers. Based on existing literature, we identified the factors contributing to the attitudes and conducted semi-structured focus group interviews with nursing students and current practicing nurses. Quantitative and qualitative data was analyzed to identify themes and factors that would encourage nursing students and practicing nurses to receive specialty training in dementia. This research will aid in development of a multimodal dementia education training program for nurses in ambulatory care.

The goal of the Kaeberlein lab is to understand the underlying molecular mechanisms of aging and how they can be perturbed in order to beneficially alter the aging process. To do so, we use the unicellular model S. cerevisiae or brewers yeast. In order to expedite the process of studying aging in large numbers of cells, the Kaeberlein lab has been using microfluidic devices that immobilize yeast cells throughout their lives so that visual data can be collected without manual interference of the cells. The question being investigated here is whether a neural network can be trained to automate the scoring tasks required for processing the image data generated by these microfluidic devices. Using python and the Yolov3 neural network architecture, I have created an AI-based screening tool to quickly analyze data generated with these microfluidic devices, such that the pipeline as a whole produces lifespan data for about 120 cells at a time, using stacks of image files as raw data. This work is significant as it provides insights into the issues of training a neural network on similar objects, and more importantly, insights into how these issues can be mitigated. In addition to increasing the speed with which data can be scored, this system will also increase the capacity for scoring experiments with large numbers of experimental groups. The system itself can also be used in order to expedite biology research.

Microglia, the resident immune cells of the brain, become activated and mediate neuroinflammatory responses in response to traumatic brain injury (TBI). This neuroinflammation can be detrimental to the health of the brain; thus, inhibition of this natural response can benefit TBI patients. Designer Receptors Exclusively Activated by Designer Drugs (DREADDs) are a technological advancement that allow manipulation of specific cellular signaling pathways. The hM4D DREADD gene was inserted in a viral construct downstream of the CD68 promoter, which is markedly upregulated in activated microglia following TBI. This construct is activated with clozapine n-oxide (CNO) to downregulate secondary messengers in activated microglia and thus attenuates the inflammatory response by reducing microglial activation and proliferation after injury. After viral transfection to deliver the construct to cells, rats underwent a controlled cortical impact (CCI) - an experimental model of TBI - and were treated with a CNO injection at varied intervals after injury. After the rat brains were dissected and sectioned, we used immunohistochemistry techniques to label microglia with an anti-Iba1 antibody, proliferating cells with an anti-BrdU antibody, and cell nuclei with DAPI. This allowed for the visualization of microglia using fluorescence microscopy and microglia were quantified using stereological principles. The aim of this research project is to use pharmacological DREADD receptor-mediated inhibition of microglia at different intervals post-injury to quantify the proliferation of microglia following CCI. We hypothesize that increased duration between CCI and CNO injection leads to more pronounced microglial activation represented by increased numbers and morphological changes. We also hypothesize that microglial activation can be observed as a gradient with the greatest proliferation closest to the CCI epicenter.

The ability to actively reflect on one's own mental processes, or metacognition, plays a significant role in learning and executing complex tasks by interacting with different learning processes. This study examined the influence of metacognition on declarative and reinforcement learning (RL) mechanisms. I collected data from 221 undergraduates (139 female; age from 18 - 22, mean = 19.0) using a within-subjects metacognitive manipulation half way through the stimulus-response (S-R) learning task created by Collins (2018). The metacognitive manipulation aims to activate monitoring by drawing participants' attention to their own learning strategies and task performance. The task consists of learning blocks of differing lengths; the long blocks rely more on RL, while the short blocks can be completed with declarative or working memory processes. Contributions of declarative and RL mechanisms are also assessed through an incidental post-test given after an intervening task. If metacognition differentially affects declarative and RL, we expect a three-way interaction between the task phase (learning/post-test), block type (long/short) and metacognition (before/during). Results showed significant main effects of task phase (F(1,220) = 153.83, p = 6.32e-34), block length (F(1,220) = 527.29, p = 2.79e-102) and metacognition (F(1,220) = 18.00, p = 2.32e-05), with better performance during the learning phase, short blocks, and metacognitive manipulation. A significant phase by metacognition interaction (F(1,220) = 8.21, p = 0.0042) suggested that metacognitive monitoring improved test performance without interfering with learning performance. Future experiments will examine the possible mechanisms by which metacognitive monitoring facilitated long term memory retrieval.

Statistical learning—predictions based on pattern recognition from varied inputs—is critical in language development. People reference previous grammar encounters in their native language to recognize language patterns, and a strong understanding of statistical learning in language could help create interventions that enhance language development and pattern recognition. However, most research studies on statistical language learning have focused on a select group—monolinguals—ignoring the bilingual community that represent 43% of the world’s population. As such, I review current literature on the unique language learning processes of bilinguals and ask the following research questions: Does bilingualism affect language learning speed, and if so, does it increase or decrease it? When subjects first acquired their second language, what key factors (such as age, proficiency, and whether their second language can be considered another native language) are present? Are there advantages or disadvantages associated with bilingualism in regard to statistical learning and language and how does this compare in relation to monolingualism? To answer these questions, I examined 10 articles that focus on languages across numerous learned languages. A preliminary review of the literature shows that bilinguals have different processes of statistical learning in language development compared to that of their monolingual counterparts. They also indicate that age at which a language is acquired further affects these learning processes. Additionally, results could reveal advantages to bilingualism that strengthen these language learning processes. This literature review can inform future research and studies of the effects of more than one language on statistical learning in language development and point to the need for additional research on not only bilinguals, but also trilinguals, etc.

Chronic pancreatitis (CP) is a significant source of morbidity, mortality, and reduced quality of life. A common symptom of CP is severe abdominal pain, and it is associated with adverse effects on physical, psychological, and social functioning. Despite these concerning impacts, pain self-management programs have not yet been developed or evaluated for individuals with CP. Instead, pancreatitis pain is typically managed with opioids which can have limited efficacy and negative side effects. In other chronic pain conditions, cognitive-behavioral therapy (CBT) programs have improved patient outcomes (e.g., pain-related disability, depression) without pharmacological treatment. Therefore, this study aimed to evaluate the feasibility and acceptability of an internet-delivered CBT program for individuals with CP pain, as well as its impact on pain outcomes (pain interference, pain intensity, and quality of life). The study consisted of 30 adult participants with CP. Participants were randomized to either internet-delivered CBT (Pancreatitis Pain Course) or a wait-list control. The Pancreatitis Pain Course delivered 5 lessons over a span of 8 weeks that gave participants information to understand their pain, a range of CBT skills to manage their symptoms, and homework assignments to practice the skills. Pain outcomes were assessed at pre-treatment, post-treatment and 3-month follow-up, and qualitative interviews were conducted at post-treatment. Eighty percent of participants rated the program as highly acceptable and 64.3% completed all 5 lessons. The qualitative interviews showed that participants found the program relevant and helpful, and patients in the treatment group experienced reduced pain intensity and pain interference. Because this is the first trial of a CBT pain self-management intervention for adults with CP pain, future trials are needed to further assess its ability to reduce pain and disability.

Humans hear through the conversion of pressure waves vibrating in the inner ear into chemical signals released by activated hair cells. Loss of function of hair cells due to damage can result in permanent hearing loss. Zebrafish are one of the model organisms used to study hair cells, since zebrafish have hair cells similar to humans. Unlike humans, zebrafish can regenerate their hair cells after damage. Regeneration occurs when support cells differentiate into hair cells. Determining how zebrafish support cells differentiate into hair cells is important to understand if human support cells can be induced to differentiate in a similar way. This requires comparing the structural differences between support cells and hair cells. One important aspect of neuronal signaling is the release of calcium ions from the cell’s endoplasmic reticulum (ER). This experiment looked to answer whether the ER in zebrafish hair and support cells was quantifiably different. Since structure mediates function and support cells do not signal to neurons, their ER structure should not be equivalent to the hair cells’. To test this, I manually segmented and reconstructed serial block-face scanning electron microscope (SBF-SEM) images of both cell types’ ER into 3D. Using SBF-SEM as a reconstruction method allowed for more detailed visualization of both the cell volume and the ER, in contrast to other methods such as confocal microscopy. Support cells had an ER volume of 50.51 µm3, while hair cells had an ER volume of 29.09 µm3. Support cells had a higher ER to cell volume and ER surface area to volume ratio than hair cells. It can be concluded that ER structures of support and hair cells are quantifiably different. Quantifying ER differences between support and hair cells is an important step toward discovering solutions to deafness caused by damage to human hair cells.

DNA glycation is the DNA damage induced by reactive carbonyls (such as methylglyoxal and glyoxal) in plants and mammals. Glycation damage is quantitatively as important as oxidative damage. It is one of the major in vivo DNA damage sources associated with increased mutation frequency, DNA strand breaks, and cytotoxicity. In humans, glycation damage may contribute to Parkinson’s disease, cancer, and oxidative stress-induced diseases. Glycation damage in plant organelle (Chloroplasts and Mitochondria) DNA remains poorly understood. We recently showed that the demise of plastid DNA (ptDNA) and mitochondrial DNA (mtDNA) during maize seedling development is associated with an increase in DNA damage resulting from oxidative stress caused by reactive oxygen species. As oxidative and glycation stress are closely linked in plants, we hypothesize that glycation might be one of the causes of ptDNA and mtDNA damage during development. Glycation damage can be prevented by the activity of the protein deglycase DJ-1, also known as Parkinson's Disease Protein 7 (PARK7). Our objective is to quantify glycation lesions in the organelles of maize plant tissues in the presence and absence of DJ-1. Our approach involves the quantification of glycation and deglycation in ptDNA and mtDNA using PCR analysis and the enzyme-linked immunosorbent assay (ELISA). This research should better understand glycation damage in plant organelles and might lead to insights concerning human pathologies and neurodegenerative disease caused by glycation.

The primate brain effortlessly segments objects from background stimuli, however, the neuronal underpinnings of this process are largely unknown. Past studies in V1, the primary visual cortex, have demonstrated that neurons encode visual information within the receptive field through edge detection, by which the greatest local contrast evokes the largest response. These studies have typically focused on luminance contrast, but edge detection and object segmentation can rely on a variety of other factors including contrasts in color, texture and blur. The primary goal of my research project is to investigate how variances in contrasts of luminance, color saturation, orientation and blur within a textural image affect neuronal response in primary visual cortex V1 and in subsequent stages V2 and V4. I have created a novel stimulus set that individually incorporates these varying types of contrast. I will record the responses of neurons in the visual cortex of a macaque monkey to these stimuli using Neuropixels, which will allow us to determine whether neurons are selective to object form and whether the strength and latency of form selectivity depends on the stimulus dimensions that define object boundary. We expect that different subgroups of neurons in V1 and V2 may be sensitive to different types of stimulus contrasts, while the same neuron in V4 may be sensitive to object shape regardless of the stimulus modality but the different modalities may be associated with different latencies. Data analysis and discussion of results will be completed and prepared for presentation by May. Our research will build upon and contribute to the greater understanding of visual information processing within the primary visual cortex. 

The locus coeruleus (LC) is a small nucleus of noradrenergic neurons in the pons, which, despite its size, has broad projections throughout the central nervous system (CNS). Functionally, the LC is believed to be involved in various critical functions, including the physiological response to stress, as well as mediating arousal. Previous investigations have demonstrated that optogenetic activation of the LC at a tonic frequency promotes wakefulness in rodents. While this observation causally implicates LC function in wakefulness, it is still not known how the LC is endogenously controlled to mediate arousal. One potential candidate in this control is the peptide nociceptin and its cognate receptor, the nociceptin opioid peptide receptor (NOPR), both of which are highly expressed around the LC. To investigate, we first conducted two pharmacological experiments using the NOPR agonist Ro64-6918 to assess its effects on locomotion and on the activity of LC noradrenergic neurons. To determine where the endogenous nociceptin signal to the LC originates, we performed an intracranial injection of a Cre-dependent retrograde virus (AAV2-DIO-eYFP) into the LC of a mouse expressing Cre recombinase in nociceptin-expressing neurons. We observed that Ro64-6198 (10 mg/kg) strongly reduced open field locomotor activity compared to vehicle treatment. Using in vivo 2-photon calcium imaging (GCaMP6s), we found that Ro64-6198 (5 mg/kg) profoundly reduced LC noradrenergic neuron activity. Wakefulness appeared reduced in both in vivo experiments. Finally, we identified nociceptin-expressing cells projecting to the LC in the peri-LC as well as a long-range projection from the bed nucleus of the stria terminalis (BNST). Together, these studies suggest that nociceptin acting on LC noradrenergic neurons reduces arousal, and that the endogenous sources of nociceptin may originate in the peri-LC and BNST. Future studies will investigate nociceptin-expressing neuron activity during sleep/wake transitions and whether this activity is sufficient to alter wakefulness.

The goal of this project is to develop a dynamically evolving connectionist model that more closely resembles the brain through its information-processing. Over the years, AI has shifted from the first generation of feedforward systems to the use of recurrent or convolutional Neural Networks. The third and newest generation of AI models, the brain-based models, and the Spiking Neural Network (SNN), attempts to bridge the gap between Neuroscience and ML using biologically realistic models like Θ-model, LIF, Izhikevich, HR, HH. These models, however, are still a black box leaving very little control or understanding on the learning process within the system without the access to the inner structure of the network. In addition, these systems are highly inefficient, slow, and very complex due to the limitations imposed by the hardware and explicit simulation of partial differential equations. Real world problems require “flexible learning and dynamically adaptive connectionist systems” that are capable to adapt and accommodate new input in real time. Current solutions have focused on varying the weights within a system rather than focusing on how connections within the system are formed. Based on our understanding from organismal brain structures, our approach, called biomimetic information codec, .bic, is a morphologically-adaptive coding hierarchical network that form in accordance with energy minimization - driven by dissipation of "heat" generated by the training data - constructing cortices and connectome for processing of information. My first objective herein is to quantitatively compare detailed structures between biological (fly brain) and .bic. networks using a random matrix approach.

This paper investigates the impacts that asymmetric information has on private pediatric health insurance coverage. In order to do so, I use the Rothschild and Stiglitz model of equilibria in perfectly competitive insurance markets and apply it to pediatric health insurance. It examines the shifts that occur in the model due to exogenous changes from asymmetric information between insurers and parents. These information problems occur in three forms; moral hazard, when people consume more care because they have health insurance; the principal-agent problem, when a task is delegated to an agent and the principal cannot directly observe the agent's actions; and adverse selection, when the consumer of health insurance has more information than the provider. These information asymmetries affect the behavior of both consumers and suppliers of pediatric health insurance, and so results in changes of supply and demand of insurance contracts. Ideally, in an equilibrium contract, consumers would recieve maximum utility, firms would make non-negative profits, and no other possible contracts would have the potential to make the firms greater non-negative profits. However, due to the changes in supply and demand from asymmetric information, this efficient outcome can become harder to obtain. By examining the changes that happen in the market with the modified Rothschild and Stiglitz model, I examine the the existence of equilibrium points, as well as the anticipated effects on health insurance coverage and health insurance prices. Because there are so many possible events that can occur, such as changes in parental income and risk, and the uncertainty of the magnitude of those events, no concrete conslusions can be made. It can however, be said that pediatric health insurance coverage may change in the presence of asymmetric information. 

Unionization has been proven to give significant benefits for workers, specifically in terms of wages and employee benefits. However, in spite of these benefits, unionization has been on the decline in the United States since the 1960s. One of the main reasons for this decline is right-to-work (RTW) laws, which allow employees to opt out of paying union dues that contribute to the cost of union representation. This poses an interesting puzzle: why are RTW laws enacted in the United States, in spite of the negative economic effects towards workers? My research attempts to examine the relationship between a state’s ‘economy’ and RTW laws. I theorize that RTW laws, while hurting employees, provide a significant incentive to firms who are looking to relocate. Therefore, states with a lower gross state product (GSP) may be incentivized to institute a RTW law. I first look at GSP per capita to identify if there are cases where GSP stagnated, and then a RTW law was enacted. I then analyze the 8 most recent cases of RTW laws, using state data from 1965 to 2019 to look at the impacts of RTW laws on GSP, employment, median household income, and unionization. This is done using a multivariate regression analysis, to test the correlation between the passing of the RTW law and my dependent variables. Ultimately, this study hopes to both build on the existing body of evidence that asserts a negative relationship between both RTW states and unionization, and research additional effects of RTW laws beyond unionization by focusing on state economic development, and incentives around proposing a RTW law. 

The dominant perspective within school governance scholarship is Iacconne and Lutz’s Dissatisfaction Theory, which posits that local school politics are democratic because representatives elected by the public. If a constituency is sufficiently dissatisfied with its elected officials, incumbent board members will be voted out, inducing administrative change in the district. Within this framework, most scholars have focused on the institutional response to incumbent defeat, with topics like superintendent turnover and policy reform. This study places theoretical emphasis upon the community as the foundation of democratic self-government and investigates underlying socioeconomic conditions which induce citizens to vote out their representatives. It is hypothesized that civic engagement affects the causal linkage between dissatisfaction and incumbent defeat as posited by Dissatisfaction Theory. This is tested by a multiple regression model, which incorporates 141 school districts using ACS and newspaper data. If this hypothesis holds, then a positive correlation between civic engagement and democratic outcomes is established. The underlying insight being that civic culture is an essential consideration for local democratic governance.

The Chinese housing market is rising so fast compared to other countries, such as South Korea and the United States. In China, skewed sex ratios caused by the "One-Child" Policy increase the intensity of the marriage market, motivating men to purchase more and better houses in the favor of enhancing their attractiveness in the competitive marriage market. In this paper, we explore the implications of the "Two-Child" Policy on the intensity of the marriage market, represented by the sex ratios (number of boys per 100 girls), and the correlation between the sex ratios and growth rate of house prices. To test the effects of the “Two-Child” Policy, we regress the logarithmic form of house prices on the sex ratios, inflation rates, and other independent variables through building a fixed-effects regression model with two fixed-effects variables, City Fixed Effects for each province in China and Year Fixed Effects for each year from 2002-2019. The result indicates that a 1-unit increase in the sex ratio would increase house prices by 3%. Therefore, we are certain that skewed sex ratios have a negative impact on the growth rate of house prices. High housing costs in China make it harder for future generations to live. Through taking local sex ratios into consideration of implementing the optimal property tax, we could slow down the growth rate of house prices and increase the welfare of the citizens.

Why do some American social movements enjoy Congressional attention while others do not? By contextualizing this question in existing social movement and policy elite preferences theory, this paper proposes a novel theory identifying social movement threat as a key causal mechanism underlying recognition from Congress. To operationalize this, “social movement threat” was measured by analyzing the size, frequency, and violence of protests organized under a corresponding social movement in a given year, while “Congressional attention” was measured by the amount of proposed legislation addressing a corresponding social movement in a given year. The project focuses on the actions of formal social movement organizations as a unit of analysis and hypothesizes that a continuous trend of threatening protest tactics is key to sparking Congressional attention. Preliminary multivariate regression analysis of three distinct social movements and over 300 protests in the 20th century indicates that more threatening social movements may have garnered greater Congressional attention in the form of proposed bills but did not necessarily enjoy a significantly higher amount of passed laws. Further, while Congressional attention did not increase with movement threat, it does appear that it increased over the lifespan of a social movement. The implication of these preliminary findings is that protests do little to influence Congressional decision-making, but that some other characteristic of an ongoing social movement may spark increased Congressional attention.

The Covid-19 pandemic has affected nearly every facet of life, most alarmingly that of food security. Scholars suggests that food security is one of the most important indicators of physical and financial wellbeing. Many governmental policies, both on the federal and state level, have been passed in order to alleviate some of the building pressure. Grassroot organizations, particularly food pantries, have also stepped up in order to meet the increased demand for food security. My study examines the success rate of various food pantries across Washington State in their addressing of local food insecurities. “Success” is measured by how many households each food bank served. In order to collect this data, I individually contacted food banks across Washington State requesting them for the number of households that their pantries served between January and August of 2020. As food pantries are community-based organizations, this study will specifically examine whether food pantry success has been influenced by community population size. A multivariate regression model is employed in order to examine whether locality population size (primarily measured by ZIP code) has a statistically significant relationship with the number of households served, controlling for other variables. It is expected that lower population size will lead to higher rates of food bank success because (1) smaller communities have stronger collective identities and (2) local information is more accessible in smaller communities. If the regression fails to reject the null hypothesis, the implications of this study would be that food bank operators may benefit their communities more by starting multiple smaller local food banks rather than upgrading existing ones. These findings may also be applicable to other grass-roots non-profit organizations wishing to expand their reach.

The Fermilab Muon g-2 experiment seeks to measure the anomalous magnetic moment of the muon to 140 ppb. A highly purified beam of muons is delivered to a magnetic storage ring in bursts of ~15,000 muons called fills. The rate of change of the angle between a muon’s momentum and spin while orbiting in the storage ring is the anomalous precession frequency, which is directly proportional to the anomalous magnetic moment. During each fill, muons orbit in the storage ring until they decay into positrons which spiral into electromagnetic calorimeters stationed around the ring. Positrons which impact the calorimeter deposit their energy in the calorimeters as Cherenkov radiation. The time dependance of the positron energy spectrum is used to extract the anomalous precession frequency of muons in the storage ring. “Early to late effects” are a class of systematic uncertainty in the experiment which result from coherent changes of experimental conditions within each fill. These effects can directly bias the measured anomalous precession frequency. One such effect arose from malfunctioning resistors in the ring’s electrostatic quadrupoles, resulting in non-ideal vertical focusing of the muon beam. This led to coherent downward motion of the beam during each fill. This directly couples into one of the largest systematic effects, as the calorimeter acceptance depends in part on the beam's vertical position. Using data from the calorimeters, I quantified early to late change in the beam’s vertical position and vertical distribution. These results were used to cross-check results from simulation programs. If the Fermilab Muon g-2 experiment retains the same central value as the previous generation measurement but with 140 ppb precision it will be in greater than 5-sigma tension with standard model calculations. Results from Run 1 of the experiment are expected to be published in early 2021.

Nanofibers have broad capabilities in biomedicine, e.g. drug delivery and tissue engineering, because of their diverse tunable properties. For these purposes, nanofibers often must be patterned to be integrated in devices or to optimize their function. Current nanofiber patterning methods lack user-control over design or alter fiber integrity. To optimize and expand the applications of nanofibers, there is a need for a versatile nanofiber patterning strategy that maintains material integrity and function and can be generalized for patterns of different complexity and dimensions. This project aims to address this need with an in situ patterning strategy that allows for complex, three-dimensional patterning at the milli/microscale with different fiber materials. The approach consists of a two-layer composite electrospinning collector with an insulative layer and conductive recessed patterns. An inexpensive collector fabrication method was designed for rapid prototyping. Collector design features predicted to affect fiber deposition were evaluated by quantifying fiber selectivity. Optimal formulations of nanofiber materials were experimentally evaluated based on reproducibility, fiber yield, and selectivity to delineate key polymer solution properties affecting patterning. This project offers a guiding foundation to adapt this patterning strategy to various applications of nanofibers by tuning fiber formulations and specific collector design features.

Implanted biomedical devices are becoming increasingly common for the treatment of tissue defects and organ failures. However, there is an ongoing issue of biocompatibility, where the host body constantly attempts to degrade the foreign object while it can’t most of the time, especially in the case of synthetic polymers. Consequently, virtually all implants will undergo an immune response named foreign body reaction and eventually get encapsulated in collagen, which can be detrimental to the device’s designated function, especially for drug delivery systems. Extensive research attempting to improve biomaterial integration has been conducted in the past decades. Recent studies suggested that the in vivo vascularization within and around a porous polymeric biomaterial is partially driven by the local phenotypic expression of macrophages, where the M1 macrophage was specifically shown to play an angiogenic role. It was also observed that the in vitro pre-vascularization of biologically-derived constructs accelerates and enhances tissue vascularization in vivo. Enlightened by these findings, I proposed to modulate both macrophage phenotypes at the material-tissue interface and scaffold pre-vascularization to restore tissue homeostasis. Two tools previously developed by my mentor’s research groups are vital for my study: the engineered M1-inducible macrophages (i-M1macs) and sphere-templated porous poly(HEMA) biomaterial scaffolds. Three main aims were constructed, where the first two aims are to optimize in vitro the scaffold pre-vascularization from endothelial cells and activation of i-M1macs in scaffolds respectively. The third aim is to determine the effect of macrophage modulation and scaffold pre-vascularization on the foreign body response to biomaterials in vivo. Findings from my research are expected to improve our understanding of the correlation of macrophage plasticity, material porosity, scaffold pre-vasculature, and tissue vascularization, which can be crucial for the development of a novel cell therapy that improves biomaterial integration and ultimately, the quality of life of people with biomedical implants.

Loss of periodontal ligament tissue (PDL) and attachment is a serious complication of periodontal diseases - the most prevalent dental health problems. PDL-degeneration leads to alveolar bone degeneration, infection, gingivitis, and eventual tooth loss. There is currently no product that can cure PDL-degeneration as regeneration requires the combinatorial process of regenerating cementum, signaling the existing relevant cells to proliferate and form PDL, and its integration into a functional system. Current restorative treatments utilize cell-based tissue regeneration, synthetic scaffolds, tissue grafts with limited, temporary success. A market product, e.g., claims to restore periodontium using harvested fetal swine periodontal tissue with highly variable clinical outcomes. Although these traditional procedures are well-established and show some success, their efficacy is limited due to the lack of structural and functional integration of a deposited layer with the underlying tooth, specifically integration into the remineralized cementomimetic layer. GEMSEC labs have developed a proprietary technology dubbed “peptide-guided remineralization” which facilitates new mineral formation using protein-derived peptides and have successfully restored dental hard tissues via several case studies including enamel, cementum, dentin under in-vitro and in-vivo conditions. Translating this technology into a daily-use product, we propose a PDL-regenerating chimeric construct which includes a biomineralizing peptide, ADP5, derived from the key enamel protein, amelogenin, with cell signaling moieties. Herein, we aim to use established bioinformatics, machine-learning tools, and high-throughput experimentation to identify peptides from proteins involved in PDL development cell-signaling towards controlled biomineralization, bioadhesion, and cell-signaling functionalities necessary for PDL regeneration. Addressing current treatment protocol limitations, the interdisciplinary approaches developed in this project are designed for the regeneration and formation of fully functional PDL. 

A survey in the existing literary sources says that there are three main diet-related patterns in Blue Zone communities that contribute to their longevity. After I cross-referenced the micronutrients in Blue Zone diets with the average American diet, I found that the Blue Zone diets are all enriched for some common vitamins and nutrients, specifically: retinol, thiamin, pyridoxine, ascorbic acid, vitamin E, vitamin K, magnesium, and potassium. All of these vitamins and minerals are known to affect cellular metabolism through a wide array of factors, potentially linking them to bettering health and increasing lifespan. I initialially will confirm that these compounds indeed play a vital role in extending the functionality of the biomechanical systems in C elegans. I will then further pursue whether combinations of the nutrients increase effectiveness, and which specific areas in the body they individually impact for promoting longevity. My first step in investigating the biomechanical effects of these micronutrients will be to incorporate each one individually into the C elegans’ diet. My long-term goal, once I test the wild type model, is to focus on how these micronutrients combat age related diseases. To do this I will use my results for optimal micronutrients to test the effectiveness of the specific micronutrients in the Alzheimer’s degenerative pathway. Specifically, I will use the GMC-101 transgenic worm, (genetically modified strain to exhibit the degenerating effects of Alzheimer's disease), which expresses human amyloid- beta - a protein implicated in the progression of human Alzheimer’s Disease - in the body wall muscle and becomes increasingly paralyzed with age. I will use a similar experimental set up, looking for a delayed onset of paralysis. I hope this research will be able to shed light on how micronutrients interact and affect degenerating biochemical pathways in aging C elegans; specifically, in a strain that models Alzheimer’s disease.

Caenorhabditis elegans is frequently used as a model organism for testing the effects of various compounds on longevity. A current limitation of running these experiments is the tremendous amount of work needed to collect large sample sizes of data when testing for several compounds in different genetic populations. Fortunately the Kaeberlein lab has developed the WormBot, an image capture robot used to take high resolution images of hundreds of experimental plates each containing ~30 worms. Researchers still have to rely on humans manually annotating tens of thousands of frames to extract valuable metrics for their analysis. I have developed the implementation of a neural network to automatically analyze these images so that the number of experiments and compounds that can be tested is increased exponentially. I utilize a network architecture known as Yolov3 to allow the computer to identify and track individual worms from the images. The results obtained from our new computational method extract data from the images that is equal to or even better than the human method while also requiring a fraction of the time. Using this novel platform, we are analyzing a broad spectrum of natural and synthetic compounds for their effects on longevity and health span in C. elegans.

 According to the Centers for Disease Control and Prevention, birth defects affect 1 in every 33 babies born in the United States, and severity within each condition varies widely. However, the genetic basis of isolated birth defects (iBD), that is having a single major birth defect, remains largely unknown. The research question for this study is, “What are the underlining genetic causes of different iBDs?” To answer this question, I visually screened patient data obtained from the University of Washington Center for Mendelian Genomics. I looked at the DNA sequences in families to confirm the presence of a genetic variant in the affected child and identify patterns of inheritance for children affected by glaucoma or omphalocele. Glaucoma is a condition affecting vision and omphalocele is a defect of the abdominal wall that causes organs to lay outside of the stomach. I looked at these birth defects because they are common causes of infant mortality in the first year of life. Early findings show that in our cohort, 7 out of 19 individuals with congenital glaucoma have overlapping genotypes with other disorders affecting vision. In the omphalocele cohort, there were no overlaps in their genotype with other similar disorders. These results suggest that within glaucoma, there are other possible candidate genes of interest for targeted sequencing, and that these individuals may be affected by other medical conditions relating to vision. Given these findings, I will continue to analyze data for other defects to expand our understanding of the phenotypes of iBDs. The next major defect I will study is tricuspid atresia which is a defect in the heart. This research will contribute to knowledge of the genetic basis for iBDs by narrowing down the candidate genes which can be used to identify targeted sequences for DNA sequencing.

MicroRNAs (miRNAs) are short 21-23 nucleotide (nt) nucleic acid species that have a seed-sequence complimentary to target RNAs which can then be negatively regulated via the RNA silencing pathway. miR-122 is the most highly expressed miRNA in the liver, accounting for 70% of the miRNA reads and is involved in hepatocyte differentiation and cholesterol/fatty-acid synthesis. Previous studies have indicated that total abrogation of miR-122 or competition of miR-122 by short hairpin RNAs (shRNAs) in mice caused an increased expression of the Dlk-Dio3 locus, which is highly expressed in development but downregulated in adults and ultimately leads to hepatocellular carcinoma (HCC). Furthermore, it is known that activation of the Dlk-Dio3 locus alone has been shown to lead to the development of HCC but the specifics of miR-122’s regulatory role have not been elucidated. To determine the effects of miR-122 on the Dlk-Dio3 locus, I am using human HCC cells that contain a 3-bp deletion down-stream from the miR-122 transcript. We predict that the 3-bp deletion prevents proper miR-122 transcription. By transfecting the cells with a miR-122 mimic transcript to introduce its expression, I can compare the levels of RNA expression in liver cells containing miR-122 to those without by using qPCR and small-RNA sequencing. Preliminary data indicates that cells transfected with the miR-122 mimic have decreased levels of expression of RNAs located in the Dlk-Dio3 locus such as Rtl1 and positive control targets such as Aldoa. To further confirm this relationship, I am planning on using CRISPR-mediated homology-directed repair to replace the 3-bp deletion in my cell line and endogenously re-express miR-122 in order to study its regulatory role at the Dlk-Dio3 locus.

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) causes COVID-19 and can result in preterm birth or severe disease or death in the mother. The research objective was to quantify the SARS-CoV-2 viral load in placental tissue and evaluate whether the placenta mounts an antiviral innate immune response. Furthermore, the study seeks to understand whether the timing of a COVID-19 infection during pregnancy correlates with viral load at the time of delivery and placental pathology. I, along with the two research technicians I am working closely with, hypothesize that a SARS-CoV-2 infection modulates the placental innate immune pathway in pregnant women and result in high viral loads in the context of placental pathology. The virus may amplify or dampen the innate immune response, significantly impacting viral clearance and potentially inducing substantial injury to maternal and fetal tissue. In the study, I helped extract RNA from two tissue types in the placenta, chorionic villous tissue and chorioamniotic membranes, from pregnant women with and without COVID-19 at different trimesters. I have begun to extract RNA, synthesize complementary DNA (cDNA), and perform quantitative polymerase chain reaction (qPCR) to quantify the viral load of SARS-CoV-2 per mg of tissue. In SARS-CoV-2 positive samples, I have also begun to quantify the relative gene expression of ifnb, mxa, ifit1, and il6, which will allow my team and I to evaluate the innate immune response. Our preliminary results indicate a low, but significant frequency of SARS-CoV-2 in placental tissues with rare high viral loads associated with a significant IL-6 response. I will help analyze our data through visual graphs and statistical analysis once the data is uploaded to the lab’s database. This project will not only improve our understanding of pregnancy pathologies, but also make significant strides in what is known about SARS-CoV-2’s impact on pregnancy health.

Poor sleep is a common complaint during pregnancy that is associated with worse maternal and fetal outcomes including increased depression symptoms before and after pregnancy. Mindfulness-based interventions are effective in improving sleep, but little is known about the relationship between mindfulness and sleep during pregnancy. This cross-sectional study explores the associations among mindfulness, objective and subjective sleep parameters, and mood (depression, anxiety, and positive affect) during pregnancy. Participants are between 12 weeks and 28 weeks gestation, enrolled in my mentor’s pilot randomized controlled trial, Online Prenatal Trial in Mindfulness Sleep Management (OPTIMISM). Data include self-report questionnaires, actigraphy, and daily sleep diaries collected at baseline before receiving a sleep intervention. We hypothesize that mindfulness and sleep quality are positively correlated, whereas mindfulness and mood symptoms are negatively correlated. This study's findings would support mindfulness as a potential non-pharmacologic intervention to improve sleep during pregnancy.

The process of development in mammals is always accompanied with high amounts of brain plasticity. Similarly, the maturation of sex organs during puberty in mammals serves as the foundation for important cognitive development. Researching centers of high plasticity could lead to key discoveries for the molecular basis of behavior. The medial preoptic area (MPOA) is an example of a very active site in pubertal gene expression. Estrogen-receptor 1, or Esr1, is a gene that is essential for hormone binding. We aim to gain insights on the neural basis of behavior by analyzing Esr1’s level of control in the MPOA, and on sexual behavior. This was completed by identifying single-cell types, determining the full transcriptome of the MPOA, and then observing any changes in gene expression after selectively knocking out the Esr1 gene. We utilized scRNA sequencing to identify single-cell types. The mating behaviors of mice was also studied to pinpoint any phenotypic differences. We have found that the deletion of Esr1 leads to severe hinderances in maturation, as well as sexual behavior, due to reduced function of Cis-regulatory elements. This provides important clarity regarding the key effectors of brain development in the pubertal stages. We aim to apply this approach to uncover the transcriptional dynamics of other areas in the brain, eventually forming a full, detailed representation of the brain. This would be a massive step forward in understanding the neural foundation governing sexual behavior.

Osteoporosis is an orthopedic disease in which old bone begins to dissolve, but is not replaced by new bone. This reduces overall bone density and increases a patient’s risk for fractures. Our lab studies genes that contribute risk to osteoporosis. One human gene associated with osteoporosis is WNT16, which is also expressed in zebrafish. Previously, we mutated the wnt16 gene at four different sites to produce a range of skeletal phenotypes. These studies show that wnt16 mutant fish have skeletal defects. The aim of my project was to find how wnt16 influenced spine segmentation in mutant zebrafish. Through GNOMAD, a Genome Aggregation Database, I collected data on the types of mutations that naturally occur in human Wnt genes. Across all human Wnts, there was no strong bias for stop-gained mutations in the terminal coding exon; however, in WNT16, stop-gained mutations were underrepresented in the terminal coding exon, which was of interest. Using CRISPR-based gene editing, we used a guide RNA to mutate the terminal coding exon in zebrafish wnt16 and found a range of severe skeletal abnormalities along the spine. Segmentation of the wnt16 mutant zebrafish was disrupted compared to the controls. I determined how wnt16 influenced segmentation of the spine by quantifying centrum fusions and other morphological abnormalities in these mutant zebrafish. Our results implicate the wnt16 gene as essential for spine morphology and contributes to understanding human phenotypes of osteoporosis.

Humans are incapable of regenerating a majority of their major tissues following traumatic injury. Xenopus tadpoles have the ability to regenerate a variety of complex tissues quickly following tail amputation, but lose this regenerative competency during metamorphosis. Though tadpoles have been extensively used to study regeneration, we do not yet understand the roles that stress signals from injury play in directing regenerative gene expression. We have found that inhibition of the stress responsive transcription factor Hypoxia Inducible Factor 1α (Hif1α) with the Hif1α inhibitors 2-methoxyestradiol (2ME) and Echinomycin (Ech) prevents regeneration. In particular, inhibition of Hif1α decreases Wnt mediated gene expression. Wnt is known to be one of the primary signaling processes necessary for proper Xenopus regeneration, specifically tail regeneration. While we have shown that Hif1α and Wnt regulate expression of similar gene programs in regeneration, we predicted that there are unique processes that Hif1α regulates to facilitate growth. To investigate how Hif1α and Wnt regulate regeneration, we utilized the two Hif1α antagonists, as well as the Wnt antagonist, IWR-1 (IWR) which I have previously shown inhibits regeneration. To determine Hif1α and Wnt regulated genes, we performed RNA-sequencing 24 hours post amputation. I then identified genes downregulated in Hif1α inhibited tadpoles, which are likely Hif1α dependent. I then removed genes downregulated by Wnt in order to isolate genes uniquely regulated by Hif1α. With the 250 genes uniquely regulated by Hif1α, I used PANTHER to perform gene set enrichment based on Gene Ontology terms. The main biological process of interest found to be regulated by Hif1α during regeneration was DNA replication. By determining how Hif1α uniquely regulates DNA replication during regeneration, we will continue to enhance our understanding of the roles that stress signals play in directing how regenerating cells meet increased proliferative demands post traumatic injury.

Some environments hinder microbes from gaining the nutrients they need for a chemical reaction. Species in this circumstance collaborate to produce energy by clearing toxic substrates or providing nutrients. This is mutualism, where two species benefit from each other’s fitness. Previously, Desulfovibrio vulgaris and Methanococcus maripaludis were forced to rely on mutualism for survival over time. D. vulgaris catabolizes lactate, producing hydrogen as a byproduct. Hydrogen is inhibiting at high concentrations. M. maripuladis consumes this hydrogen and uses it for energy, producing methane as a byproduct. To learn how these microbes adapted to mutualism over time, 22 communities were propagated for 5000 generations. Each species was also propagated alone in environments that were as similar as possible to the mutualistic evolution environment. The whole genomes of the entire population of D. vulgaris or M. maripaludis were sequenced for the first 1000 generations using Illumina sequencing. This was done from 8 mutualism-evolved and 8 solitary-evolved cultures. Our research goal is to identify alleles that were substituted because they had a beneficial effect on mutualism fitness instead of other generic features of the environment. We can rule out generic adaptations in the population data by comparing mutations in community versus solitary-evolved clones. Clones were collected from each population that had been stored at –80 °C by streaking them on plates. Plates were also used to test if the clones could grow on sulfate. The DNA of these clones will be sequenced to confirm the presence and determine linkage of alleles that are beneficial to mutualism. It is anticipated that the mutation frequency of catabolic proteins will increase within D. vulgaris solitary clones in comparison with community D. vulgaris clones. This experiment has greater implications for mutualistic interactions between microbes, specifically in terms of the methane greenhouse gas that microbes produce.

Loss of neurons in the retina underlie many blinding diseases, such as macular degeneration, glaucoma, and diabetic retinopathy. These retinal neurons are not replaceable. The Reh Lab has developed a strategy to achieve functional regeneration of neurons in the adult mammalian retina, but not enough regeneration to restore vision loss. One of the potential limitations to restoring vision is the inflammation that occurs during retinal injury or disease. All mammalian retinas contain microglia, which are the primary immune cells of the nervous system that respond to pathogens, injury, and disease. My goal is to determine how microglia respond to damage-induced regeneration in the retina. After damaging mice retinas with an excitotoxin (NMDA), we induced neuronal regeneration with a proneural transcription factor called Ascl1. Using immunohistochemistry and confocal fluorescence microscopy, I stained various markers that represent different inflammation states of microglia. I quantified microglia and analyzed their response to neural regeneration. Data from confocal fluorescence microscopy revealed that microglia surround newly regenerated neurons and display a variety of subtypes during regeneration. Follow up single-cell sequencing experiments confirmed that these immune cells show a molecular heterogeneity of states. This study provides a better understanding about how microglia function during retinal regeneration. Results from this study can help reveal targets for manipulation to improve regeneration of the retina. Further work can be done to analyze how these microglia behaviors impact regeneration of lost retinal neurons.

Tauopathies are a set of neurodegenerative diseases identifiable by the aggregation of insoluble intracellular deposits of the microtubule associated protein tau. Among others, this class of diseases includes frontotemporal dementia (FTD), Pick’s disease, and supranuclear palsy. Though the precise pathology of tauopathies is poorly understood, most forms are associated with hyperphosphorylated tau and impaired clearance of tau through the ubiquitin-proteasome and autophagosome pathways. We attempt to explore the degradative properties of one specific tau variant, a serine to threonine missense mutation (S356T), which is strongly associated with an early onset behavioral variant frontotemporal dementia (bvFTD). Posttranslational modification at the S356 residue in tau controls its proteasomal degradation. Therefore, we hypothesize that the S356T variant exhibits impaired tau clearance compared to wildtype tau. To test this hypothesis, we use the pharmacological inhibitor Cycloheximide that prevents protein synthesis in both human embryonic epithelial cells (HEK293) and neurons transfected with wildtype and S356T tau protein. Cycloheximide has been shown to inhibit translation by binding to the E-site of the 60S ribosomal subunit and preventing protein elongation. This drug allows us to measure protein degradation without being confounded with new protein synthesis. We expect the amount of tau, relative to total protein, to be elevated in the S356T transfected cells after application of cycloheximide. If our hypothesis is correct, we plan to explore possible mechanisms behind the aberrant degradative properties of the S356T tau variant. By exploring the mechanisms through which tau mutants contribute to neuropathology, we hope to provide molecular insight into tau proteostasis that if successful could offer a promising therapeutic target.

Leptin and ghrelin are two hormones essential to maintaining and regulating energy levels and food intake. These hormones have opposite effects on feeding behavior where leptin suppresses feeding and ghrelin potentiates it. While the roles of these two hormones have been widely researched, their relative effects on distinct neural populations are still largely undetermined. Previous electrophysiological and in vivo imaging experiments have shown that the activity of individual populations of glutamatergic hypothalamic projection neurons are differentially affected by feeding hormones. This data leads to the question of whether or not the projection populations have a bias for leptin and ghrelin receptors that could account for the difference in sensitivity. We hypothesize that Lepr and Ghsr will be expressed at different levels within the different projection populations. To study this, we injected two retrogradely trafficked viruses into the target locations, lateral habenula (Lhb) and ventral tegmental area (VTA), in Mus musculus and performed fluorescent in situ hybridization experiments in the lateral hypothalamus (LHA), dorsomedial hypothalamic nucleus (DMH), ventromedial hypothalamus (VMH), paraventricular nucleus (PVH), and arcuate nucleus (ARC) for viral based fluorophores as well as leptin and ghrelin receptors. The viral expression was imaged using fluorescence microscopy and quantified for within individual hypothalamic neurons. Analysis is currently underway to reveal any differences in fluorescence between the two projection populations and therefore, determine any disparities in hormone receptor expression. The objective of this research is to understand whether differences in expression of Lepr and Ghsr exist within LHb- and VTA-projecting glutamatergic hypothalamic neurons. This study could be indicative of how hormones regulate feeding behavior and their particular effects on the hypothalamus projection neurons. Further research concerning the downstream impacts of these opposing hormonal pathways could shed light on the neural networks that govern food and energy balance.

Anxiety, a heightened state of arousal without the presence of an immediate threat, can be incapacitating once it reaches a disease state. Located in the extended amygdala, the Bed Nucleus of the Stria Terminalis (BNST) has been implicated in sustained fear states and other anxiety-related conditions. BNST neurons have been shown to be diverse, co-releasing neuropeptides and other neurotransmitters, but the quantification and localization of these neuromodulators is not clear. In order to identify the co-expression of neuropeptides I employed in-situ hybridization in the mouse BNST, where RNA sequences specific to relevant peptides are recognized with a fluorescent probe. Then, I created pipelines that identify and group amplified peptide signals to cells, quantifying intensity and presence, and collect them by co-expression and subregions within the BNST. I hypothesize that co-expression of these peptides is regionally biased. Finally, identifying differences in cell-type distribution has implications for anxiety-behavior and may provide insight towards treatment of anxiety conditions.

In synthetic chemistry, the direct functionalization of C-H bonds with oxygen-containing groups is a powerful strategy to efficiently synthesize molecules used in materials and therapeutics. However, current methods to accomplish such reactions suffer from limited substrate scope, selectivity, and tolerance towards other functional groups. Iron-dependent enzymes represent a promising solution to this problem, as they are known to mediate a plethora of complex oxygenation reactions in a highly selective fashion while using inexpensive and earth-abundant reagents. In prior work, we found that Fe(II) 2-oxoglutarate dependent hydroxylases (Fe(II)/2OGs) exhibit non-native oxyfunctionalization activity on olefinic amino acids. Here, we explore the ability of Fe(II)/2OGs to catalyze non-native asymmetric oxyfunctionalizations. We plan to evaluate the ability of our library of Fe(II)/2OGs to catalyze oxyfunctionalization of non-native substrates with various functional groups. Subsequently, we will optimize activity using directed evolution to arrive at a highly active and enantioselective enzyme capable of this chemistry.

There are an estimated 300 million people worldwide who are affected by asthma, a respiratory condition characterized by inflammation and swelling of the airways. One key process during an asthmatic event is vasodilation (i.e., the widening of blood vessels) in the lungs which causes increased blood flow and inflammation, making it difficult to breathe. Processes like vasodilation are mediated by the exchange of chemical signals between cells. Crucial to advancing our knowledge and understanding of inflammatory disease progression is gaining more insight into the underlying cellular communication during complex signaling events. Current methods used to study cell signaling include 2D cell culture studies which often lack spatial biological relevance or animal models, which are not adequate for understanding inflammation in humans. We developed a user-friendly method that can be used to measure cytokine response during inflammatory processes, including vasodilation. Our device enables the creation of a model blood vessel structure, offering a simple approach to test potential drug treatments. A 3D printed device is used to form hydrogel rings in a range of sizes. The rings are comprised of cell-laden collagen I to mimic blood vessels; vasodilators and constrictors can then be introduced to the solution housing the free-standing vessels. We then collect and analyze the solution to identify the chemical signals released by the cells during treatment with the drug. By identifying key chemical signals mediating disease pathways, we can begin to target those chemical signals and develop new therapeutic treatments.

Engineered solid binding peptides can be used as molecular tools for a variety of bio/nanotechnology applications, especially in interfacing biology with solid-state devices at bio/nano soft interfaces. The control of surface organization, and therefore peptide-solid interactions, is critical and involves surface phenomena such as binding, surface diffusion, and self-organization on atomically flat solids. Each of these phenomena requires the knowledge of peptide’s folding patterns which are, however, difficult to study both experimentally and computationally. Molecular dynamics, MD, has been used to computationally model peptide/solid interactions, but without information regarding the energy landscape of peptide conformations the challenge of predictive design remains. While several methods exist for finding the energy landscapes of single peptide systems, currently no approach handles multi-peptide/surface systems. Here we use Time-Varying Autoregression with Low Rank Tensors, TVART, to efficiently explore the energy landscapes of such systems, aiming to find accurate linear approximations for predictive design of peptides at bio/nano interfaces. Using TVART, with each slice representing a discrete time window, allows for temporal smoothness and high predictive accuracy. It is anticipated that some descriptions of conformation will be better suited to describe peptide conformation energy landscapes than others; based on this premise, we examined interatomic distances/adjacencies and peptide backbone torsion angles as descriptions of peptide conformation. Through such analyses, it is becoming possible to describe how peptide conformations in multi-peptide/surface systems evolve through the energy landscape and settle into energy minima (stable conformations). These conformations can then be corroborated with experimental validation of peptide self-organization on the surface using scanning probe microscopy techniques with sub-A resolutions. The combination of computational modeling and high-resolution experiments is expected to aid predictive design platforms for future applications in biosensors, bioelectronics, and logic devices.

Everyday environmental exposure can lead to the cell’s DNA to undergo double-strand breaks (DSB). If left unrepaired, these DSB are toxic to the cell’s survivability, since it can lead to the breakdown of the genetic code that is essential for the production of proteins vital to cellular life. As such, organisms have developed mechanisms to account for these common DSB situations. These mending processes are evolved to strongly combat these breaks, as failures or mistakes in the process can result in error-stricken genetic information, resulting in faulty proteins. Not only that, DSB and its repair are observed to be important to the contribution of genetic diversity, as it allows for chromosomal crossovers. This proves that the DNA repairing mechanisms to be a complex yet significantly important process for organismal life. In Escherichia coli, DSB repair processes are carried out by a trimeric protein complex, RecBCD. The mechanism behind RecBCD is not completely understood. Previous studies in the Smith lab have proposed a working model of the protein. Here, we combine both computational prediction and genetic assay to further understand the specifics of its structure-function relationship. Past experiments have identified a structural change that affects the protein’s function. Then, using a protein-protein docking algorithm, we have identified the possible conformation and interacting amino acid docking pair accounting for it. We then follow up with site-directed mutation of these pairs to test the validity of our prediction to elucidate the exact model. These experiments will allow us to further understand the conformational effects on the complex’s function. Proper understanding of RecBCD will enable us to generate new drugs to target bacterial infections whilst also reinforcing our understanding of DSB repair.

Interactive add-ons to computers offer the potential to enhance user experience and productivity, but these peripherals are often expensive and uncustomizable for normal users, designers, and differently abled individuals. AcousTickBoard uses cardboard, a ubiquitous household material due to widespread online shopping deliveries, to address accessibility in human-computer interaction (HCI) through tangible widgets that are both cheap and easily reconfigurable. First, we created the design of a pressable button made of cardboard that emits a “tick” sound when released. Then, we explored different ways of modifying the cardboard buttons in order to produce unique enough acoustic signatures to be independently recognized such that multiple buttons could be used at the same time. The modifications made to the buttons generally involved adding or subtracting material in order to manipulate the “tick”’s frequency and amplitude. Next, we developed a machine learning (ML) pipeline to recognize these different buttons through the computer’s microphone, with several modifications on the buttons producing detectably different audio signatures with an average of 90% accuracy per button. Finally, we conducted a user study in which participants replicated a subset of our button designs and provided both quantitative feedback in terms of how well their button worked as well as qualitative feedback in the form of survey questions. By understanding which modifications to the cardboard buttons yield the most accurate detection results, we can create and use the fabricated buttons as peripheral computer widgets. These low-cost widgets are easy to create and customize for educational purposes, temporary computer setups, and people with different abilities who need regular adjustments to their digital setups.

 Motor neuroprosthetics are brain-computer interfaces (BCIs) that record neural signals from an individual, use a decoding algorithm to predict the individual's intended movement, and perform that movement using a prosthetic device. As the neural code for movements is still being uncovered, current devices are still limited in their ability to create naturalistic movements. Development of motor decoding algorithms that can predict more naturalistic movement may enhance these prosthetics. In this project, we aim to implement and elaborate on newly published motor decoding algorithms and then compare alternative approaches to predicting the direction of movement in upper body joints (initially just the wrist) based on electrocorticography (ECoG) recordings from the surface of the human brain. Our dataset uses neural data collected during one week of continuous ECoG recordings from four subjects undergoing chronic, in-patient seizure monitoring, and includes hours of naturalistic movement, previously mapped from concurrent video to provide joint tracking of the head, shoulder, elbow and wrist. Carrying out this study on existing ECoG recordings provides a basis for extending our decoding work to future, real-time neural recordings. We have identified electrodes that correspond to hand-related areas in motor and sensory cortices for our initial focus on motor decoding of wrist movement. The goal of our project is to explore motor decoding of dimensionally-reduced spectral features using various neural network architectures. This will allow for more accurate responses in motor neuroprosthetics since they rely on motor decoding of naturalistic movements.

Wave energy converters (WECs) are devices that convert the motion of waves into useful energy. An interdisciplinary team of University of Washington students have designed and prototyped a WEC to power ocean sensors. One of the primary advantages of a sensing system powered by a WEC rather than relying on external charging of batteries is the potential for an increase in power output, which means that the system can support higher sensing loads at finer temporal resolutions. The characteristics of the environment in which such a device would be deployed place constraints on the device’s design because they impact durability and performance. To determine these characteristics and inform design decisions, analysis of wave model data was performed at potential locations of device deployment for parameters including significant wave height, mean period, and dominant period. Analysis revealed typical wave conditions as well as statistically extreme conditions that are associated with storms and lulls in wave energy. Then, in situ measurements from ocean sensing buoys were used to determine model bias and provide potential error/offset values for the model-based analysis of wave parameters. This evaluation of model-based analysis was done by comparing model data at locations of National Data Buoy Center buoys to the in situ measurements from those buoys using regression and distribution based statistical methods. The computed error/offset values were then extrapolated to the potential device deployment locations and used as a confidence metric for the accuracy of the model-based analysis. These results ensure that the WEC design team has an accurate understanding of the constraints of the environment that they are designing for. This analysis is also essential for market research because it can establish if an area, and thus potential users, provides a viable opportunity for the deployment of the WEC-powered sensing system.

Recent legalization of cannabis in various states has sparked research on the impact of cannabis use on postnatal outcomes. While previous research has yielded contradictory findings, some studies suggest increased cannabis use is directly associated with increased depression and psychological distress.We assert that prenatal mental health should be an essential consideration in the discourse surrounding prenatal cannabis use, as issues such as untreated maternal depression are risk factors for adverse postnatal outcomes like low birth weight and preterm delivery.However, few studies have considered the relationship between prenatal maternal mental health and cannabis use. Here we question: what is the association between cannabis use and psychological distress in pregnant individuals? For our sample population, we recruited pregnant individuals in the greater Seattle area. 12 individuals reported using cannabis (CB) at least 3 to 5 times a week throughout their first trimester of pregnancy, and 22 were non-cannabis users (n-CB). In early pregnancy, we administered the Brief Symptom Inventory (BSI), a self-reported measure, to evaluate psychological distress levels. We tracked cannabis use with weekly surveys from time of enrollment to birth, evaluating reasons for use and amount consumed, among other variables. We hypothesize that prenatal cannabis use will be associated with elevated BSI T-scores compared to the control group; within the prenatal cannabis use population, we expect cannabis use for mental health reasons to be associated with elevated BSI T-scores. More research is needed on possible causal versus correlational associations between cannabis use and psychological distress, and the role of psychosocial distress as a possible confounder in previous prenatal cannabis use and infant development studies.

We have established a head and neck squamous cell carcinoma (HNSCC) cell line resource to facilitate translational research on HNSCC in individuals with Fanconi Anemia (FA). FA is a rare genetic disorder characterized by bone marrow failure and predisposition to leukemia and solid tumors. FA individuals have an extraordinarily high lifetime risk of HNSCC compared to the general population and the pathogenesis of these cancers is not understood. Apart from surgery, effective treatment of these cancers is limited by patient hypersensitivity to standard-of-care therapies that include ionizing radiation and DNA cross-linking drugs. Insight into the mechanistic origins of these cancers and the identification of less toxic, more effective therapies are necessary to improve survival and quality of life. The FA Cancer Cell Line Resource was developed to provide well-characterized, experimentally tractable pre-clinical models to investigate the origins, pathogenesis, treatment and prevention of FA HNSCC. Isogenic cell line pairs or trios included in this Resource were generated from FA patient-derived or sporadic HNSCC cells using CRISPR/Cas9 technology. The biochemical and molecular characteristics of these models were confirmed to verify the presence or absence of FA-associated phenotypes following gene edits. This Resource addresses the critical need for well-characterized and tractable disease models that are FA patient-derived, and versatile enough to permit both in vitro and in vivo analyses. These cell lines are now available at no cost to foster research through the Fanconi Anemia Research Fund-sponsored “Fanconi Anemia Research Materials” repository at Oregon Health and Sciences University (https://apps.ohsu.edu/research/fanconi-anemia/celllines.cfm).

Charcot-Marie-Tooth (CMT) is a group of inherited nerve disorders resulting in muscle weakness in which the motor and/or sensory peripheral nerves are affected; hereditary neuralgic amyotrophy (HNA) is a rare genetic disorder characterized by severe pain and muscle wasting in the arms. Using whole exome sequencing (WES), we aimed to find the causative mutation in a five-generation family with CMT and single-generation family with HNA. WES is an efficient method to identify possible disease-causing mutations by searching for variations in the protein-coding region of any gene. After excluding variants from a known list of genes to be causative of CMT, we used stepwise criteria to filter and prioritize the candidate variants in the exome data from two patients in this family: heterozygosity, alternative splicing, gnomAD frequency, CADD score, function of the gene, and its expression. In CMT, out of the 26 candidate variants, 10 were INDEL mutations and 16 were single nucleotide polymorphisms (SNPs). Each variant was Sanger sequenced to verify the exome variant; the verified variants were further evaluated for co-segregation with the disease by Sanger sequencing affected and unaffected individuals of the family. The results from these analyses did not identify any candidate variant as a possible candidate, concluding the CMT WES study without yielding a causative gene. Our next steps for this project will be to use whole genomic sequencing (WGS) to reveal DNA variation outside the exome or copy number variant or repeat expansion that may alter protein production to identify potential causative mutations. Currently, we are using the same methodology to screen for candidate variants in three exomes from the family with HNA. Out of 22 candidate variants, we have screened 2 INDEL mutations and 2 SNPs. We are actively screening the remaining variants in search of a causative mutation for HNA in this family.

Among the estimated 1.5 million adults and children living with HIV in Kenya, only 68% had suppressed viral loads in 2019. Improving adherence to antiretroviral therapy (ART) and minimizing ART failure is crucial in ensuring viral suppression. New types of viral load (VL) and drug resistance mutation (DRM) testing through point-of-care (POC) assays are potential solutions to optimize viral suppression rates. POC assays have faster turnaround times, can facilitate rapid clinical decision making, and are cost-effective, all of which can facilitate better patient outcomes. In the Opt4Kids and Opt4Mamas studies, children and pregnant/postpartum women either received the intervention, consisting of POC VL testing every three months with targeted DRM testing, or standard-of-care (SOC) testing according to national Kenyan guidelines. As undergraduate researchers, we are responsible for coding and analyzing 68 in-depth interviews collected from key informants and participants, including adolescents, children’s caregivers, and pregnant/postpartum women, to better understand how POC VL and targeted DRM testing influences viral suppression and may be utilized for use nation-wide. We used the socioecological model to identify the individual, interpersonal, organizational, societal/cultural, and structural/policy factors that influence viral suppression in children and pregnant/postpartum women. Through inductive coding and thematic analysis, we discovered six major domains of themes of interest amongst these populations: 1) HIV health literacy, 2) HIV testing and treatment experience, 3) differences between SOC VL testing and POC VL testing, and 4) DRM testing experience, 5) future improvements, and 6) impact of the COVID-19 pandemic on treatment and testing. Our findings will provide insight into ways of optimizing existing protocols and will determine whether our intervention is an improved alternative to current national standards. Ultimately, our research will shape national policies regarding HIV treatment and directly address ways to optimize HIV viral suppression.

Merkel cell carcinoma (MCC) is a rare, aggressive skin cancer with a recurrence risk of ~40%; however, prognosis for low-risk, stage I disease is excellent with primary surgical management. The role of post-operative radiation therapy (PORT) is controversial as it can cause significant and acute long-term side effects. Here, we assess the efficacy of PORT on local recurrence (LR) rates in patients with pathological stage I MCC with primary tumors on the head/neck (HN) vs. non-head and neck (Non-HN) sites. One hundred forty-seven MCC patients treated from 2006-2020 were identified from an IRB-approved prospective registry who had ‘low-risk’ disease: pathological T1 primary tumor resected with negative margins, negative pathologic node status, and no immunosuppression. LR was defined as tumor recurrence within 2 cm of the primary surgical bed. I led compilation of the cohort, and contributed to discussion of results, and development of the figures and manuscript. Seventy-nine patients received PORT (30 HN, 49 Non-HN), and 68 patients were treated with surgery alone (30 HN, 38 Non-HN). Addition of PORT was associated with a decreased risk of LR across the entire cohort (5-year rate: 9.5% vs. 0%, p=0.004), with 6 LRs in the surgery alone group. The addition of PORT significantly reduced LR rates among HN patients (21% vs. 0%, p=0.034). Conversely, no LRs were observed in Non-HN patients. No significant MCC-specific survival differences were observed. For low-risk MCC of the extremities and trunk, excellent outcomes were achieved with surgery alone. However, HN MCC was a risk factor for LR that was significantly reduced with PORT. Overall, this study demonstrates the importance of primary tumor site location for prognosis and treatment of MCC to determine patients that would benefit from PORT and those that can be spared the toxic side effects of radiotherapy.

Copy number variants (CNVs) are typically a result of chromosomal duplications and deletions, making them a well-known form of genetic diversity and associated with several human disorders. Little is known about CNVs within humans and insight into CNV mechanisms would help scientists better understand, and potentially treat, many genome-based diseases. A particular form of CNV within humans is the inverted triplication of a gene without any chromosomal deletions. A similar phenomenon is observed at the SUL1 gene in Saccharomyces cerevisiae yeast cells, providing a model for studying such CNVs. The Brewer lab proposed a replication error mechanism responsible for this specific amplification described as Origin Dependent Inverted Replication Amplification (ODIRA). What impacts the initiation of this mechanism is unknown, but the proximity of SUL1 to the telomere raises the possibility that properties of the telomere may stimulate replication errors responsible for the triplication. I conducted a literature review analyzing 11 articles discussing various CNV mechanisms and telomeric influence on replication to establish their relationship. Through my review, I found a likely method to test whether the telomere does affect ODIRA. I propose utilizing a CRISPR-Cas9 based method to first circularize and eliminate the telomeres of the chromosome. Subsequently, the chromosome would be linearized at a location distant from the original telomere sites, effectively moving the entire SUL1 site away from potential telomeric influence. This research design allows for a comparison of SUL1 amplification events within the original and the restructured chromosomes and would reveal whether the telomeric region influences inverted SUL1 amplification formation. An observed reduction in rates of SUL1 amplification events with the reconstructed chromosomes would indicate telomeric influence on the amplification mechanism prompting further examinations within that genomic region. Attaining a greater understanding of this CNV mechanism yields information for future implications in genetic disease research.

A plethora of research documents the negative impacts of incarceration and poor nutrition on individual, family, and population health, but little research explores how these seemingly disparate issues may intertwine. Based on the knowledge that children learn to eat and develop lifelong nutritional patterns as part of their families, and that incarceration of a parent breaks family units apart, I investigate the question: How does a parent’s incarceration shape the trajectory of a child’s developmental food environment, including meal structure, staple foods, and changes in routine? Based upon current research on parental incarceration and childhood eating patterns and health outcomes, I predict that parental incarceration will be associated with negative changes in a child’s food environment by disrupting previously held family eating routines and by creating additional barriers to healthfully feeding a family. I conduct semi-structured interviews with formerly incarcerated parents or co-parents whose partners are currently imprisoned. Interviews were coded in NVivo using two rounds. First, I open coded to identify preliminary themes. Then I coded a second-round to refine the themes found and identify patterns between themes. Preliminary coding of the interviews reveals evidence of family eating pattern disruption and constrained choice that limits food options as a result of incarceration. This implies that parental incarceration may be associated with challenges and barriers to feeding a family and disruption of healthy meal patterns for children. It illuminates how large-scale social phenomena such as mass incarceration can patten eating behaviors and habits, therefore directly impacting health outcomes. The conclusion situates this study in the context of Socially Engaged Nutritional Sciences and explores the implications of these findings for children of incarcerated parents and for racial and socioeconomic inequalities in nutrition and beyond.

In the process of uniting Europe, European integration has inadvertently strengthened secessionist movements that seek to fracture the very states it has brought together. Through the creation of the European Single Market, the common travel area, the single currency, and the establishment of the four freedoms of movement for goods, capital, services, and people, many of the benefits a region with a potential desire for independence gains from remaining a part of its host state are transferred to the European level. Currently, nearly all academic analysis of European integration and its impact on secessionist movements has been published around the time of the 2014 Scottish independence referendum and before the UK’s 2016 European Union membership referendum. The current academic consensus argues that European integration has harmed secessionist movements more than it has helped, but in the years since the UKs decision to leave the EU, this argument has become outdated and no longer holds the strength it once did. I conducted a review and analysis of current academic literature on the topic along with statements from current and former European politicians and separatist political parties to explore and compare the cases of secessionist movements in Scotland, Catalonia, and Flanders. My analysis incorporates the events since the UK’s Brexit referendum currently left out of academic literature published to date. I hypothesize that an updated review of European integration’s effect on secessionist movements will show that integration has helped secessionist movements and their arguments. While these cases were chosen for their strength and their diversity in circumstances, these independence movements are united in being transformed from pipedreams to real possibilities thanks to European integration.

Network goodness of fit (GOF), which deals with determining if an observed network could have been drawn from a particular graph model, is a common method to identify network structures and a prerequisite of further network analysis. In this talk, we will present a method that constructs a test statistics using advances in Random Matrix Theory, which traces the limiting behavior of the leading eigenvalue of the observed graph's adjacency matrix to perform network GOF. We show that under many network models - such as the Degree Corrected Stochastic Block model (DCSBM), the Beta model, and the Aggregated Relational Data (ARD) - our method performs well in identifying the correct model with high precision and low computation time. We further extend our method to the popular Latent Space model, and develop an algorithm that fast-and-accurately predicts the underlying dimension of the true model. With precision grows with network sizes, our algorithm enables better estimations for large-scale networks with minimal computational cost.

Systems of non-linear differential equations are often difficult to analytically solve, control, and analyze, whereas systems of linear differential equations are relatively straightforward to solve, control, and analyze because we possess tools to study systems of linear differential equations. Koopman analysis allows us to transform a system of non-linear differential equations into a linear system. The caveat is that sometimes, the resulting linear system is infinite-dimensional, meaning that the mapping between the original space and the Koopman space is infinite-dimensional. This poses a computational challenge because infinite dimensional vector spaces are difficult to computationally work with. Koopman analysis has traditionally been done on one fixed point (equilibrium). Previously, work has been done to study specific examples of systems that have closure i.e. systems with a finite-dimensional Koopman operator. In this project, we looked at how to apply Koopman operators to systems with multiple fixed points. We found effective eigenfunctions that linearize low-dimensional non-linear dynamical systems analytically if possible, computationally otherwise. Under the assumption that the right-hand side of the differential equations are polynomials, we identified appropriate eigenfunctions that linearize the Koopman space with a possible invertible mapping. Previously, we have been able to find a closed-form solution that generates eigenfunctions for one-dimensional systems that have a polynomial form. However, in practice, the resulting integral equation can be difficult to computationally solve with current methods, and edge cases such as singularities and asymptotes are not well understood. Using implicit SINDy (an algorithm that approximates dynamical systems given data), we attempted to find polynomial decompositions that allowed us to describe the eigenfunctions with rational polynomial functions. This work is significant because better understanding dynamical systems allows us to better understand dynamic fields such as natural disaster detection, the firing of neurons, and the spread of pandemics.

Hormones heavily influence feeding behavior and body weight. Estrogen depletion in post-menopause women leads to high risk of obesity, while estrogen replacement therapy suppresses body weight. While previous studies have started to reveal the neural substrate of feeding behavior control, how they are modulated by estrogen action is not well understood. The paraventricular hypothalamus (PVH) is known to control satiety in animals. Thus, in this study, we hypothesized that neurons responding to estrogen in the PVH is related to hormone-dependent modulation of feeding. To evaluate the causal relationship between the activity of PVH estrogen responsive cells and feeding behavior, we virally targeted channel rhodopsin (ChR2) to PVH expressing estrogen receptor beta (Esr2) using Esr2-Cre transgenic mice and Cre-dependent virus. The virus delivers ChR2 mRNA nonspecifically to cells in the PVH. In Esr2-Cre mice, only cells expressing Esr2 will also express the Cre recombinase enzyme to allow successful expression of the virally delivered ChR2. ChR2 is activated by light delivered into the PVH via fiber optics and the feeding behavior of the animal is observed and quantified under on or off lighting conditions. Preliminary results show that the light stimulation of ChR2 expressing neurons decreased feeding behavior, suggesting that the activation of PVHEsr2+ cells are sufficient to suppress feeding. Further studies to reveal the neural basis of hormone-dependent regulation of satiety can shed light on eating disorders in humans, potentially leading to the discovery of new drug targets to treat these disorders.

Ischemic preconditioning (IPC) is an experimental phenomenon in which a brief ischemic event confers neuronal and axonal protection against subsequent ischemic exposure. The cell types responsible for IPC in the brain are unknown. In a novel model of white matter (WM) IPC and ischemic injury, we identified specific innate immune signaling pathways in microglia as required for IPC-mediated axonal protection, leading us to suspect that microglia are required for IPC. The model of WM IPC involves exposing the mouse optic nerve (MON) to a brief ischemic event 72 hours before the MONs are isolated and exposed to oxygen-glucose deprivation. Animals were treated with PLX5622 - a colony stimulating factor-1 receptor (CSF1R) pharmacologic antagonist – to deplete microglia in the central nervous system, including the MON, to test our hypothesis. By recording axonal function, we determined that microglial depletion eliminated IPC-mediated axonal protection in the WM. This study examines the impacts of IPC and ischemia on the nodes of Ranvier, which we hypothesize are protected by preconditioned microglia. The length of the nodes of Ranvier affects conductance and action potential propagation through an axon, with recent publications suggesting elongation of the notes in disease or injury states. We hypothesize the nodes of Ranvier will be shorter in preconditioned MONs than non-preconditioned MONs, which would support IPC-mediated protection. Additionally, we expect the nodes of Ranvier in PLX5622-treated MONS will be of similar length as non-preconditioned control MONs, indicating loss of IPC-mediated protection in animals without microglia. We will use immunofluorescence and confocal microscopy to measure the nodes of Ranvier and correlate these anatomical findings to prior electrophysiology experiments. The results of this research would contextualize a novel understanding of how microglia and ischemia affect the WM in specific regions of the axon, which is vital for advancing the development of neurotherapeutics for stroke.

The rhombic lip is a dorsal germinal zone that produces nearly 80% of all neurons in the human brain and assists in the production of all glutamatergic neurons in the cerebellum. In the mouse which has traditionally been used as a model organism, the rhombic lip is a transient structure and a dorsal stem cell zone that appears between embryonic days 12.5 and 17.5. While the mouse rhombic lip is molecularly compartmentalized, it lacks structural compartmentalization. The human rhombic lip on the other hand is long-lived and seen throughout gestation. It also exhibits substructure and is compartmentalized into a ventricular and subventricular zone. The extended duration of rhombic lip is a unique feature of human development and not seen in other model organisms including non-human primates like the macaque. This indicates that model organisms have limitations as they cannot fully recapitulate human development. Histological and immunohistochemical analyses of over 27 Dandy Walker Malformation (DWM) and Cerebellar Vermis Hypoplasia (CVH) samples suggest that rhombic lip disruption leads to cerebellar hypoplasia that disproportionately affects the posterior vermis. DWM and CVH are birth defects of the cerebellum that are diagnosed using ultrasound and MRI. Our histopathological analysis suggests that reduced proliferation and self-renewal of the rhombic lip progenitor pool leads to underdevelopment of the posterior cerebellum. These findings add to the understanding of the developmental pathogenesis of DWM, and underlines the need for further research of the human rhombic lip which can further improve our understanding of cerebellar brain defects.

People who spend early life at high altitude have an increased capacity for aerobic work due to developmental adaptations to hypoxic environments. Since the effects of altitude on aerobic performance became evident after the 1968 Mexico City Olympics, altitude training has been implemented to increase red blood cell carrying capacity and improve performance. However, it is unclear how early development at altitude and current training at altitude may differently advantage endurance athletes. In order to test for possible mechanisms by which altitude enhances endurance performance, this research compares personal records and biomarkers of oxygen carrying capacity among endurance athletes who experienced early development at altitude or sea-level and are currently training at altitude or sea-level. The study aims to determine if the altitude in which athletes developed and are currently training at will be associated with faster gender-adjusted personal records and greater lung capacity. I conducted a cross-sectional observational study with 23 endurance athletes in Seattle, WA and Boulder, Colorado. Participants self-collected chest circumference (CC) at maximum inhalation and completed online questionnaires about running performance, family history, and personal motivations for competing. I devised a gender-adjusted personal record percentile score for each subject’s 5k times based on the top 500 US men’s and women’s 5k times recorded during the 2019 season. This presentation discusses the results on differences in personal records and CC in relation to early development and current training altitude. I examined athlete’s motivation for competing through the qualitative analysis of open-ended interview responses to explore how motivation works synergistically with physiological biomarkers. These findings will be discussed in terms of existing research and consideration for endurance training at altitude and sea-level.

Neurons in the brain are dynamical in nature, maintaining constantly changing states. Neurons modulate voltage based on input currents and produce spikes when the voltage exceeds a certain threshold. Additional dynamics after spiking, called evoked after-spike currents, are important for computation and memory over time scales. The diversity of neuronal dynamics and the variability in parameters underlying them give rise to rich and varied dynamics across networks. We hypothesize that the complexity and diversity of biological dynamics in the brain play a critical role in predictive coding of temporally complex systems, and that diverse forms of after-spike currents enable computation over variable timescales. Current artificial neural networks (ANNs), that emulate the structure of biological neural networks, successfully learn relationships between static patterns but have difficulty learning dynamic patterns that change over time. We aim to incorporate complex biological dynamics and diversity in ANNs and thereby systematically explore the function of such dynamics in network computation and learning. To this end, we construct ANNs that express biologically realistic dynamics, developing methods to learn dynamics-generating parameters, such as membrane capacitance and threshold, in individual neurons. Theoretically, diverse dynamics of individual neurons will enable even more complex dynamics when combined in networks and may improve performance on tasks requiring computation over complex timescales, such as determining actions based on temporal patterns of cues. Hence, we hypothesize that when trained on temporally challenging tasks, our networks will learn diverse dynamics across neurons. We present the diversity of parameters learned and the resulting distribution of firing patterns and compare performance between our neural networks and traditional networks that only learn connection weights. This research will inform learning methods for training novel biologically inspired neural networks and will also shed light on the physiological role of diversity in the brain.

New technologies capable of controlling the position-and-spacing of nanostructures have advanced applications such as electronics, sensing, and catalysis. In contrast to conventional top-down approaches such as lithography, biological-macromolecule-templates offer an attractive way to direct the assembly of nanoparticles because their high-information content can be used to direct complex structures over multiple length-scales, just as they encode living structures. Here, we study the use of de novo designed protein-nanofibers to control the assembly of gold nanoparticle chains as a model system. We employ Derjaguin-Landau-Verwey-Overbeek (DLVO) theory, which combines the energy contributions of van-der-Waals-attraction (vdW) and electrostatic-double-layer-repulsion (EDL) to understand the factors governing electrostatic assembly of gold nanoparticles along a protein-nanofiber anchored to a charged substrate, explain observed experimental results, and predict the assembly outcome under varying solution conditions. During the assembly process, as the distance between nanoparticle and protein-functionalized substrate decreases, we expect an increase in the magnitude of vdW and EDL forces. Varying nanoparticle size reveals particle-substrate EDL repulsion limits larger nanoparticles from reaching the protein despite an increase in vdW attraction, while tuning the pH varies EDL particle-protein-attraction and particle-substrate-repulsion, resulting in predictable particle density and binding specificity. We use Python 3.7.2 programming to calculate total system energies at different stages of the assembly process using equations based on the surface-element-integration method. By constructing a virtual representation of the protein-nanofiber as a chain of spheres on a flat plane and a spherical nanoparticle above the fiber at varying distances, we can use DLVO theory to map out the interaction energies for all solution conditions. With the ability to define the energy of a system, we will be able to design new biotemplates, indefinitely predict the solution conditions, and identify potential intervention points that would allow the self-assembly of plasmonic particles for new and/or difficult-to-achieve photonic applications.

The circumgalactic medium (CGM) is a massive reservoir of gas surrounding a galaxy in which density and temperature range several orders of magnitude and contains more mass than the galaxy itself–similar to a cloud engulfing the galaxy. The CGM also plays a substantial role in the life of its galaxy as it will govern the accretion of matter for the galaxy to continue star formation. To better learn about the CGM, many astronomers utilize simulations to test theories by comparing their simulation data with observational data. Yet, current simulations struggle to replicate the CGM and its breadth of properties accurately. This project uses the TEMPEST and Patient0 simulations of Milky Way-type galaxies and a novel analysis method–known as synthetic spectroscopy–to better understand the effects of cosmic rays on altering how the CGM gas is ionized and how cooler CGM gas moves within the cloud. Many simulations tend to omit cosmic ray physics, however, cosmic rays are believed to provide non-thermal pressure support which will change the ionization structure of the CGM. Through our use of synthetic spectroscopy, we extracted column density and velocity information of various ions, such as HI and OVI, from our simulation to generate velocity histograms and plots of column density versus distance from the galaxy. Ultimately, this provided us further insight into the impacts of cosmic rays on setting the ionization and kinematic properties of the CGM which will better inform us on galactic evolution.

NGC 6822 is a barred irregular galaxy located about 1.6 million light years away in the Sagittarius constellation. We are observationally identifying red supergiants (RSGs) in this galaxy to compare with stellar evolutionary models. Stellar evolutionary theory provides us with the expected quantity of RSG populations. The research conducted will allow for a comparison between observational data to theoretical expectations. Here, we propose a new sample of RSG candidates in NGC 6822 that can be utilized as an observational test of such theory. RSG stars are the coolest of the evolved massive stars and have K and M spectral types and temperatures below 4100 K. Typically, they can be up to a thousand times the radius of the Sun and are therefore highly luminous. To find them in NGC 6822, we first used parallax and proper motion values from the GAIA satellite to filter out foreground stars, before using the NIR color-magnitude diagram to eliminate lower-mass asymptotic giant branch star contaminants. Next we transformed the J and K magnitudes to effective temperatures and luminosities to create an HR diagram (HRD), and selected RSGs based on their position on the HRD. Currently, we are comparing our results to previous spectroscopically confirmed RSGs. In combination with population studies done by ourselves and others in the Local Group galaxies IC 10, M31, M33, and the Magellanic Clouds, we can test model predictions across a wide range of metallicities. Additionally, by locating a population of RSGs in NGC 6822, future possibilities for studying these massive stars with direct spectroscopic follow-up are created.

Lightning is an intensely energetic atmospheric phenomenon that causes significant loss of life and property, ignites wildfires, and sustains the natural cleansing power of the atmosphere. Lightning is also an indicator of storm intensity and of the microphysical properties of cloud precipitate. Thornton et al. (2017) showed that lightning frequency over two of the world’s busiest oceanic shipping lanes is on average double that over neighboring ocean areas. Fuel combustion by ships emits sub-micrometer particles which alter cloud microphysics and possibly storm intensity, providing a potential explanation for the increased lightning density over the shipping lanes. Starting January 2020, the International Maritime Organization imposed a seven-fold reduction in the amount of sulfur in shipping fuel. Fuel sulfur is a significant contributor to particulate matter in ship exhaust. In addition, there was a significant temporary reduction in maritime ship traffic related to economic impacts of COVID-19. We use lightning frequency observations from the World-Wide Lightning Location Network (WWLLN) to analyze how these changes in shipping activity and emissions affect lightning enhancements over major shipping lanes in 2020 compared to the past decade. We find that the lightning enhancements over shipping lanes in 2020 were significantly lower compared to the past decade, with more than 100% reduction in the lightning enhancement, temporarily, as well as sustained, but smaller reductions in over half of the seasonally active months. Together, these changes suggest both the temporary COVID-19 reductions in ship traffic and prolonged reduction in ship exhaust emissions may have significantly altered lightning activity in major oceanic shipping lanes.

Plants have evolved to represent a diversity of species, characterized by functional traits that dictate their performance in response to changing environments. One such leaf functional trait that relates to plant ecological strategy and is strongly correlated with photosynthetic rates, is minor leaf vein density (LVD). Our study will assess how ecological strategies within plant communities shifted in response to Earth’s most recent major global warming event, the Middle Miocene Climatic Optimum (MMCO) from 17-14 Ma, where rises in both global temperature and atmospheric CO₂ levels occurred. We hypothesize that global warming led to longer growing seasons and ecological strategies that prioritized persistence over productivity became dominant, and more favorable climates increased the diversity of ecological strategies present within the community. We will be traveling to various museums to photograph fossils that have all their minor veins preserved, collected from sites representing before, during, and after the MMCO in the Pacific Northwest region. Our goal will be to include several species per site, and photograph their fossil leaves under a stereo microscope. From there we will measure LVD using the program ImageJ using standard protocols. Once we have that data, we will calculate measures of the community-level distribution of this trait (mean, variance, kurtosis), and then compare those values between sites, and thus across the MMCO. In support of our hypothesis, we predict to see a lower mean and kurtosis, and higher variance of LVD values in MMCO plant communities, relative to those existing before or after the warming event. Overall this research is important to not only understanding how plant communities responded in ancient times to rising temperature but how plant communities could potentially respond to the rising temperatures in the future.

Plants face an enormous number of environmental stressors, including agriculturally important pests and pathogens. To defend against these biotic stressors, plants rely on pattern recognition receptors (PRRs), which are cell surface proteins that recognize conserved, non-self molecules indicative of attack or infection and initiate pattern triggered immunity (PTI) signaling pathways to mount defense responses. Recently, the first PRR involved in immunity against herbivorous pests was discovered in legumes. INR, a leucine-rich repeat receptor-like protein, mediates defense responses to inceptin, a peptide found in the oral secretions of caterpillars. To better understand the structural aspects of INR that are necessary for its ability to bind to inceptin and associate with downstream signaling components, I am developing a reporter system to screen INR variants to identify mutations that affect its function as a PRR. I have generated several different reporter constructs driving luciferase expression with promoter regions of genes found to be upregulated by inceptin when INR is transgenically expressed in the model organism Nicotiana benthamiana. These constructs vary in strength of expression but only one promoter region shows inducibility by inceptin. However, several constructs also show responses to a different immune elicitor, a peptide fragment of bacterial flagellin, which suggests that these constructs could be used as markers of PTI in plants more broadly. Robust reporters of PTI would not only be useful in understanding the structure and function of INR but may also enable further studies that will inform engineering practices to improve crop resistance to pests and pathogens.

Induced pluripotent stem cell-derived cardiomyocytes (iPSC-CMs) that have been engineered into three-dimensional heart tissues (EHTs) are valuable research tools for investigating debilitating genetic diseases that afflict the heart, such as Duchenne muscular dystrophy (DMD). Ensuring iPSC-CMs can be sufficiently matured to model such diseases remains a hurdle in current research, and maturational analysis techniques for iPSC-CMs are either qualitative, manual, or primarily based in two dimensions, leaving much to be desired. In this project, we created a suite of MATLAB image-processing scripts that can quantify the effect of three-dimensional culture and disease-causing DMD mutations on cardiomyocyte structure and maturation state. The iPSC-CMs were differentiated from stem cells, cast into EHTs, stained using immunofluorescence, and imaged using a confocal microscope. Using the scripts to analyze these 3D images of iPSC-CM stains, key maturational features of the cells can be quantified such as nuclei count; cardiomyocyte area; and sarcomere length, orientation, and z-disk width. Analyzing cardiomyocyte area can give key information on cardiomyocyte hypertrophy while examining sarcomere length, orientation, and Z-disk width can provide information on myofibril structure and organization. The suite allows analysis of these maturational features in both 2D and 3D cultures and offers a method for quantitatively assessing maturation in an automated manner. Measuring iPSC-CM maturation will also allow better comparison of existing maturational methods, such as mechanical loading, electrical stimulation, and small molecule treatment. The suite can also create graphical outputs to elegantly display data. Overall, the suite will help improve maturational analysis of EHTs, and hopefully contribute to the discovery of new treatments for diseases that affect the heart.

The spatial distribution and degree of colocalization for two or more proteins, based on their fluorescence intensities, are useful metrics for phenotyping cells and informing on biological function. Yet, most commercial and open-source image analysis tools report global colocalization statistics at the image-level, and offer limited analysis at the individual cell level. To address this, we are developing a python-based image analysis pipeline to quantify robust per-cell metrics of colocalization. Our pipeline stacks image tiff files acquired on high-throughput automated fluorescence microscopes into multichannel 3D image stacks. The images are then restored via deconvolution algorithms, and cropped to remove out-of-focus image planes using Laplacian variance algorithms. For image thresholding and cell segmentation, the pipeline incorporates scripts from the Allen Institute for Cell Sciences to threshold and segment individual cells. Finally, the pipeline calculates per cell colocalization metrics based on the fluorescent intensity of each voxel in each cell. CLARITY was used to quantify the spatial relationships of the peroxisomal biogenesis protein Pex3 with the endoplasmic reticulum protein Sec61 and peroxisomal membrane protein Pmp70. Pex3 colocalized with both Sec61 and Pmp70 and this colocalization could be manipulated by treatment with different kinase inhibitors. In several instances, these differences in localization contributed to a large variance in the measured Pearson’s Correlation Coefficient of cells within the same image. Morphometric analysis showed the volume of peroxisomes per cell negatively correlated with the number of peroxisomes per cell. The automation of per-cell image analysis leveraged in this pipeline will allow for systems-level phenotyping and data mining from fluorescent microscopy images.

Blood clotting plays a heavy contribution to the mortality and morbidity in patients with diabetes mellitus. In blood clotting, the interaction between platelet glycoprotein Ib (GPIb) and blood protein von Willebrand Factor (VWF) is a catch bond, a bond whose lifetime increases under tensile force. Current, identification of this single-molecule behavior of a catch bond is useful but insufficient to understand behavior with multiple molecules known as clusters. It is recognized that patients with diabetes mellitus have higher levels of VWF and GPIb but there is no existing flow assay that accurately demonstrates the difference in thrombosis flow in diabetics. In addition, there is no definitive conclusion on the influences of the amount and geometry of the catch bond between GP1b and VWF in clusters. A recent innovation in the Thomas Lab has developed a DNA origami nanostructure that allows control over the number and spacing of ligands in a cluster, facilitating the study of clusters of catch bonds. I designed a method to quantify the nanostructure-presented ligands on a surface using 96-wellplate reader. This method was used to characterize the effect of cluster size on platelet rolling behavior. The result of the method suggests using quenching low concentration of biotin-4-fluorescein had the highest accuracy and was able to be picked up by the 96 well plate reader. The method allows observation seen in platelet rolling behavior over these surfaces that are cluster-size dependent rather than concentration-dependent. This will introduce a new assay for diabetic studies and further our understand difference in platelets rolling behavior over clusters between diabetic patients and non-diabetic patients.

Gene gun technology uses DNA-coated gold microparticle bombardment to achieve DNA vaccine immunogenicity by effective intradermal transfer. This delivery system results in increased uptake of plasmids by cells, potent cellular and humoral immunity compared to other delivery methods like direct needle injection or electroporation. DNA vaccines are expected to exhibit long term stability, ease of manufacturing, low cost, reduce cold chain requirements, and reduce concern for vector immunity from repeated immunizations. Additionally, gene gun DNA vaccine technology allows for multiple antigens to be added in the same immunization. Beyond the advantages above, genetic adjuvants have the potential to further improve the immunogenicity of DNA vaccines. One strategy to improve the immunogenicity of DNA vaccination would be using chemokines like Xcl1 to recruit dendritic cells for induction of CD8+ and CD4+ T-cells. Xcl1 is a ligand that binds to and specifically activates dermal dendritic cells, which presents Xcr1 and efficiently activates T-cell responses. Two ways to introduce Xcl1 as an adjuvant are fusion and cotransfection, the latter of which is the method used in this project. In cotransfection, Xcl1 cytokines induce localized inflammatory responses which recruit dendritic cells. This allows the antigen of interest to target the dendritic cells, leading to the induction of CD8+ T-cells specific to the antigen of interest. I believe that Xcl1 has the potential to induce antigen-specific effector and memory CD8+ T-cells and enhance proliferation of CD4+ and CD8+ T-cells. I gene gun vaccinated mice with and without Xcl1 DNA and assessed the induction of appropriate T-cell responses to determine whether the addition of Xcl1 as an adjuvant enhances the T-cell and antibody response needed to protect against P. yoelii infection challenge. The results of this ongoing work will be presented. This data will inform whether genetic adjuvants have the ability to increase immunogenicity in DNA malaria vaccines.

In the Reh Lab, our research team focuses on neurodegenerative diseases that affect the retina by causing the death of neurons which result in irreversible blindness. In working towards treatments for retinal diseases we have engineered Muller glia to serve as a source for functional regeneration in the mammalian retina, but not enough to restore lost vision. While this is remarkable progress, limitations to this regeneration strategy still exist in regards to the amount of neurons generated. Recently, we have found that the endogenous immune cell of the retina, the microglia, responds to dead neurons by causing inflammation, which restricts the regenerative capacity of Muller glia. However, microglia are not the only immune cell present during regeneration and we currently do not have an understanding of the diversity of cell types that contribute to this regeneration restricting inflammation. My research project aimed to fill this gap by revealing which immune cells infiltrate the retina after injury and thereby revealing immunomodulation targets to improve retinal regeneration. In order to begin to understand the interaction of the peripheral immune system and the nervous system and how it impacts neurogenesis, I will present on my examination of monocyte and neutrophil invasion after retinal injury. For this study I have processed retinas using cryosectioning, immunohistochemistry, fluorescent antibody labeling, and confocal microscopy. Using this data I visualized and quantified the infiltration dynamics of monocytes and neutrophils in the damaged and regenerating retina. Data from this proposal will determine the types of immune cells and their window of infiltration for cell-type specific immunomodulation strategies to improve the regenerative capacity of the mammalian retina.This understanding of the immune component of regeneration is critical in moving forward to develop therapies for not only retinal diseases such as glaucoma but all neurodegenerative diseases such as Alzheimer’s and Parkinson’s.

Teaching techniques that involve high structure active learning have grown in popularity due to their usefulness in establishing an efficient and equitable learning environment. During this transition, a lot of work has been done to understand the equity impacts of high-stakes testing, particularly moderated through test anxiety and similar forces. Less work has focused on low-stakes points -- course points offered for good faith effort, completion, or participation. Are students as concerned with earning low-stakes points as they are with high-stakes points? The COVID-19 pandemic and the rapid shift to digital learning have provided a natural experiment with regard to course point allocation. Many professors have been forced to make unexpected changes to course organization, including the decision about what assignments to grade for thoughtfulness (low-stakes) and which assignments to grade for accuracy (high-stakes). This project attempts to address demographic and general trends in low-stake performance in a large introductory STEM course before and after the transition to online learning. Through qualitative and quantitative data analysis, we identified characteristics of students who are likely to forgo low-stakes course points in a large, high structure, introductory STEM course. Ultimately, the goal of the project is to recenter the discussion in education research regarding highly structured courses and serve as a reminder that critical low-stakes course points are as critical for student success as are high-stakes course points.

The 1972 Marine Mammal Protection Act (MMPA) helps govern human-environment interactions in the United States with public and agency processes. As a result, the 1972 MMPA has accumulated praise and critiques concerning its provisions and implementation. Previous research explored the impacts of the 1972 MMPA, but these publications do not provide a comprehensive assessment based on human-environment interactions and government structures in the Pacific Northwest to determine possible “best practices” for environmental law. The study observes the 1972 MMPA concerning its goals and cultural, environmental, and international implications to determine the 1972 MMPA’s effectiveness and opportunities for improvement in the National Oceanic and Atmospheric Administration’s “West Coast Region.” Through this research, I analyzed literary information and interviews with people from the National Oceanic and Atmospheric Administration, non-governmental organizations, and Indigenous communities to gather a holistic review of the 1972 MMPA as well as reveal pathways for enhancing environmental law in the United States. Available scholarly and media-based literature surrounding the 1972 MMPA suggest accomplishments encompassing the increased abundance of marine species over time, while mitigations for secondary impacts may be lacking. To appropriately address current concerns and perspectives of the 1972 MMPA, the United States public, agencies, and government bodies may collaborate to refine marine mammal securities. Revised implementation of the 1972 MMPA could inform future environmental policies and actions in the United States. Incorporating suggestions and relevant modifications in the 1972 MMPA may provide further effective partnerships in the “West Coast Region” with diverse stakeholder representations and marine conservation between governments and collectives. Consequently, the 1972 MMPA can serve as a case study for current and future environmental law in the United States and the international community.

From the Dakota Access Pipeline demonstrations to increasing popularity around climate-activist-turned-household-names like Greta Thunberg, a resurgence of environmental advocacy has taken the 21st century by storm. The environmental justice movement, a term first coined in the 1980s, was born from the idea that mainstream environmentalism does not examine environmental policy in the intersection of socioeconomic status and race. This literature review explores the history and impacts of environmental racism and the evolution of the environmental movement. It finds that not only have the burdens of environmental degradation been disproportionately distributed across different communities, but that analyses of the ecological impacts of imperialism have created a singular discourse that is paradigmatic of colonial ideologies. It parallels the colonial vision of conservation in North America with the treatment of its Indigenous populations and explores nature as something portrayed as the antithesis of culture. Finally, further examination of the changes from the Trump to Biden administrations is warranted by the construction of a new framework for examining environmental policies, with an emphasis on social equity. The intended outcome of this paper is to create a set of criteria for existing and future environmental legislation.

Understanding the microbial process in the conversion of food waste into methane is necessary to realize the societal need to convert waste into a sustainable energy source. A critical step in the process is the synergistic breakdown of butyrate to methane. My project Food Waste to Energy allows us to mimic the degradation of food waste to isolate the microbial partners responsible for the production of methane. This process is carried out by a syntroph and a methanogen. Although we do not know the specifications of either organism, identification can allow us to improve the way we utilize bio-reactors dependent on food waste to produce clean energy. Each organism has been grown using media designed to allow for their specific development, doubling methane production within four months on average. We are in the process of conducting a dilution to extinction to reduce the contaminating microbes while selecting for the target majority by close observation of the purity of each sample microscopically. We will sequence the genome of each organism to characterize their respective genetic capabilities and identity which we suspect is novel. Activity and growth characteristics will then be studied to understand the growth kinetics when the organisms grow separately and together. Once the organisms are isolated, we look forward to accelerating methane production by selecting mutants that can catalyze the conversion of butyrate into methane. By identifying the organisms responsible for the conversion of butyrate to methane, we can begin to introduce highly productive bioreactors in urban, rural, and manufacturing settings to combat the use of non renewable energy and create energy from the 40 million tons of food waste produced annually in America.

Bergmann’s rule describes the correlation between increased body size and living at higher latitudes, seen in many endothermic animals. However, there is debate over if Bergmann’s rule is applicable to ectotherms. Using an exhaustive review of the literature, we investigated whether the relationship between body size and latitude is consistent with Bergmann’s rule in >100 species of Alpheus snapping shrimps. We found a significant correlation between body size and latitude (i.e., latitudinal midpoint of the range), using both raw species correlations and correlations corrected for phylogeny (phylogenetic independent contrasts). We discuss multiple hypotheses that may explain adherence to Bergmann’s rule in this group of shrimp, and the broader ecological implications of variation in body size during a time of global change.

Benthic foraminifera are shelled single-celled marine microorganisms which are particularly sensitive to changes in their environment. A census of species found in an area can function as an indicator of the health of a marine ecosystem. My project focused on the distribution in 2018 of foraminiferal assemblages in Budd Inlet, near the city of Olympia, to assess the recent health of the area and the presence of pollutants. I examined nine sediment samples for foraminifera and identified the species. I then compared the abundance and diversity of species found to previous pollution data to pinpoint problems in Budd Inlet. My analysis found a low species diversity overall, as well as a correlation between the distribution of heavy metals and the presence of key species of foraminifera. The strong presence of the species Buccella frigida and Cribroelphidium excavatum and the low species diversity are consistent with a concentration of heavy metal pollutants, and mark Budd Inlet as an area of heavy anthropogenic impact.

Prehistorically, people of Alaska carved household tools from rocks, mostly slate. ‘Ulu’ is an Inuit word that translates as ‘woman’s tool’. It was used for household needs such as meat cutting. The Unangan civilization (Aleuts) in the late Aleutian phase (1000-200 BP) adopted the use of ulus sourced from slate, due to the rock’s durability and ease to sharpen. The paradox is, there is no slate widely present on the Aleutian Islands, yet fine grained volcanic rocks are abundant. In this study, I analyse 5 ulu fragment samples that were excavated on the Tanaxtaxak Spit (UNL_55), Amaknak Island of Unalaska where volcanic rocks and argillite were common. Kodiak Island, the nearest source of sufficient slate, is ~880 km away. The UNL_55 samples in this study were collected from different chrono-stratigraphic layers of the same site.The UNL_55 samples have previously been classified as slate, based solely on visual analysis. This implies possible inaccuracy in identification, since aphyric volcanic rocks and silicified argillite visually resemble slate. Using the Scanning Electron Microscope, I investigate the microtextures and minerals in the ulu fragments to identify whether they are slate, volcanic rock or argillite. Determining the rock type will guide inferences related to inter-island trade and migration of people in the prehistory of the Aleutian Islands. I expect the results to indicate rock composition that is similar to rocks that abundantly exist at the excavation site; volcanic. 

The pupillary light reflex (PLR) curve is an important point-of-care biomarker for the diagnosis of traumatic brain injury (TBI). Using PLR, first responders can determine the severity of TBI in the field and direct patients to a trauma center where staff can continually assess PLR to monitor TBI severity. Manual pupillometry, the most commonly available method for first responders and most clinicians wishing to assess PLR, is qualitative and often inaccurate. The current gold-standard device for PLR measurement is digital infrared pupillometry, but such devices are fragile and expensive. Our research team has developed a smartphone-based pupillometer (PupilScreen) with the ability to assess PLR using a standard iPhone, assisted by a cloud-based neural network. To demonstrate the feasibility of using PupilScreen in a realistic clinical setting and compare the accuracy of the device to the current clinical gold-standard, we have built an annotated dataset of the PLR in n=120 patients with TBI who are hospitalized in a neurological intensive care unit. Pupillometry is performed using the mobile device and the gold-standard digital infrared pupillometer. Pupil videos are manually annotated and used in the further training of our machine learning algorithm that generates a PLR curve for each patient. We anticipate that our technology will demonstrate accuracy in assessing the PLR that exceeds that of manual pupillometry and is at least equivalent to the gold-standard digital pupillometer. This technology has the potential to alleviate the current undertreatment of many TBI patients in the United States and abroad that results from a lack of accurate and cost-effective pupillometry equipment.

Disruptive mutations to DYRK1A, located in the Down Syndrome critical region of chromosome 21, are associated with autism spectrum disorder and medical comorbidities. Previous literature suggests facial anomalies in children with DYRK1A mutations, and studies of DYRK1A’s regulatory functions confirm its role in the expression of several morphology-affecting genes, particularly DCAF7. This study attempted to determine if quantitative differences in facial features exist between children with DYRK1A mutations and the general population, including unaffected parents. From a sample of 28 children with de novo DYRK1A mutations, analyses focused on nine white non-Hispanic children (M age = 11.33 years, 77.78% male) whose data were collected using a 3dMDhead System through an ongoing genetics-first study. Measurements between facial landmarks were later calculated using 3dMDvultus. FaceBase’s 3D Facial Norms for European Caucasians were used as a control group, and Z-scores were calculated for all complete measures. Six measures—intercanthal width, outercanthal width, palpebral fissure lengths, cranial base width, and philtrum width–were selected for analysis based on previous clinical findings. Wilcoxon sign-rank tests compared Z-scores between probands and each biological parent, assessing familial genetic influence on observed dysmorphologies. Outercanthal width in probands significantly differed from both biological parents and was significantly below population average. Additionally, palpebral fissure lengths significantly differed between probands and fathers and fell below population averages for probands. These findings bolster the link between DYRK1A and genes that code for craniofacial development and suggest the facial phenotype associated with DYRK1A mutations may be more variable and nuanced than expected, presenting challenges for clinical assessment. Additional research should examine how DYRK1A interacts with genes that code for eye regions, facial phenotypes in non-white participants, and possible differences in dysmorphology between sexes.

Induced pluripotent stem cells (iPSCs) can be directed to create 3D mini retinas in vitro known as retinal organoids. Retinal organoids recapitulate the developmental timeline of the human fetal retina and have the potential to serve as disease models for a multitude of retinopathies. However, we have observed that retinal organoids contain a disorganized inner nuclear layer and discontinuous lamination hindering their ability to be considered as a comprehensive disease model. The protein β-catenin is produced from the canonical WNT signaling pathway and has been shown to be essential for retinal lamination in mice due to its role in cellular adhesion. I investigated the effects of a canonical WNT signaling pathway agonist, CHIR,  in order to improve the disorganization and lamination of retinal organoids so that we can develop a comprehensive disease model for different retinopathies. We have used three different stem cell lines to construct retinal organoids that I cultured with the addition of the WNT pathway agonist, CHIR. I performed immunohistochemistry staining followed by microscopy analysis and have obtained data that shows an increase in lamination and cellular organization with the addition of the WNT signaling pathway agonist. Our data suggests that the WNT signaling pathway plays a role in maintaining organization and lamination in the developing human fetal retina. 

Tuberculosis is a major burden of disease worldwide. Although drug regimens for the treatment of tuberculosis are available, they are complex and lengthy. Efforts are being made to understand and develop novel drugs. The Parish Lab has identified a common mechanism of drug resistance in the type VII secretion system (T7SS) of Mycobacterium tuberculosis. Mutations in several components of the Esx3 T7SS system confer resistance to aminothiazole (AmT), 8-hydroxyquinoline (8HQ) and nitrothiazole salicylamide (NTS) compounds. The Esx3 T7SS is unlikely the cellular target for these compounds as four other genes had mutations, one of the four genes not being a part of the ESX-3 complex. Therefore, resistance is believed to arise from a distinct mechanism. Rv0474 is a transcriptional regulator identified to mediate resistance to AmT and 8HQ. It is a copper-responsive regulator with a copper binding motif. I am studying the Rv0474 homolog (MSMEG_0918) in Mycobacterium smegmatis, a fast-growing species used as a model organism. MSMEG_0918 lacks the copper binding motif, permitting determination of whether copper binding activity is required to confer resistance. I am using CRISPRi knock down technique to generate strains with reduced expression of MSMEG_0918, along with constructing overexpression strains. Knock down and overexpression strains allow us to determine growth, AmT/8HQ sensitivity and copper sensitivity. We propose that if copper binding activity is involved in AmT/8HQ resistance, overexpression or downregulation of MSMEG_0918 would have no effect on compound activity, because it lacks this activity. This work will determine whether MSMEG_0918 plays an equivalent role to Rv0474 in conferring resistance to AmT and 8HQ compounds. This research will provide knowledge to further global efforts in developing an adequate and effective treatment necessary for tuberculosis. 

Human adenoviruses (AdVs) infect and cause disease in multiple organ systems, and certain human AdV serotypes are associated with particular diseases; however, the basis for AdV tissue tropism is unknown. To better understand this problem, I am using mouse adenoviruses (MAdV). Like human AdVs, MAdV serotypes are associated with distinct tissue tropisms: MAdV-1 infects macrophages whereas MAdV-2 infects intestinal epithelial cells. By swapping genes between MAdV-1 and MAdV-2, I hope to uncover the genetic basis of tissue tropism in MAdVs. Importantly, these studies will be aided by the availability of a cell culture system that recapitulates the cellularity of the intestinal epithelium and supports MAdV-2 replication, but not MAdV-1 replication. Due to genetic conservation, principles of MAdV tissue tropism are likely to apply to HAdVs. A major determinant of viral cell tropism is receptor usage, which may also play a primary role in tissue tropism. For both MAdV species, the trimeric fiber protein that extends from the icosahedral capsid is thought to be the viral attachment protein that binds to a host receptor. Although the MAdV receptors are not completely known, they are distinct for MAdV-1 and MAdV-2. To gain insight into tissue tropism, I have created a chimeric MAdV-1-M2f virus, where the fiber gene of MAdV-2 has been inserted in place of the native fiber gene in the MAdV-1 genome. A prior student in the Smith lab created the inverse chimera. If replication is fiber dependent, the chimeric MAdV-1-M2f virus should be capable of infection. By studying these chimeric viruses, I will uncover whether the fiber/receptor interaction plays a central role in determining tissue tropism.

Skin can detect a wide range of stimuli through the touch system, which is mediated by specific cells and structures. Merkel cells, one of these specialized types of skin cells, sense gentle touch and texture. In mammals, Merkel cells are identified by the expression of the transcription factors Sox2 and Atoh1. Recently, the Rasmussen lab identified Merkel cells in the zebrafish skin that share many characteristics of mammalian Merkel cells, including expression of Sox2 and Atoh1a. Interestingly, a paper by Konig in 2018 also described a novel cell type that expresses serotonin (5-HT), calretinin, and synaptic vesicle glycoprotein 2 (SV2), termed “HCS” cells, within the zebrafish skin. These researchers proposed that HCS cells are a different sensory population than Merkel cells, because of differing visual characteristics between these cells. However, the paper did not present any conclusive evidence, making the relationship between HCS cells and Merkel cells still uncertain. I hypothesized that Merkel cells and HCS cells are actually the same population of cells. I tested my hypothesis using antibody staining and confocal imaging of zebrafish skin. I found that Atoh1a-positive Merkel cells express serotonin and SV2, demonstrating that Merkel cells in zebrafish are the same cells as HCS cells. Overall, my results resolve the identity of recently described sensory cell types in the zebrafish skin. In future research, I hope to use zebrafish Merkel cells as a promising model to better understand touch system development and regeneration.

Δ⁹-tetrahydrocannabinol (THC) is the primary psychoactive compound found in Cannabis sativa. The psychoactive and cannabimimetic behaviors associated with THC have been well described as being dependent on the partial agonist activity of THC at the endogenous cannabinoid 1 receptor (CB₁R). We are investigating the direct action of THC on the medial prefrontal cortex (mPFC, a brain region primarily responsible for executive function), and the effects of adolescent THC exposure on µ-opioid receptor (MOR) expression in adult periaqueductal grey (PAG, a brain region involved in opioid-mediated pain inhibition). To increase our understanding of the cannabimimetic behavioral effects of THC, and its direct pharmacological action in the brain, it is important to map the neuro-anatomical expression of target proteins. We examined expression patterns of CB₁R and MOR in the mPFC and the PAG, respectively. To do this, we utilized a form of in situ hybridization, RNAscope. We leveraged RNAscope by preparing tissue samples from brain regions of interest for treatment with mRNA-specific probes, allowing us to target CB₁R and MOR mRNA. After a series of washes and incubations, these fluorescent probes hybridize to our target mRNAs and allow us to visualize their expression under a confocal microscope. Analysis of mRNA expression informs us on the localization of the CB1R/MOR and known neuron types within our brain regions of interest. After imaging, we are able to utilize HALO software to analyze the levels of expression and co-localization of CB₁R/MORs with neuronal markers for glutamatergic and GABAergic neuron types. By creating and optimizing a workflow for extraction, preparation, hybridization, and analysis, we determined CB₁R mRNA is primarily co-localized with glutamatergic neurons in the mPFC. Moving forward, we are utilizing this RNAscope technique to investigate differential CB₁R expression GABA interneuron subpopulations in the mPFC. (Funded by DA051558)

 Mu-opioid receptors (MOR) are expressed on populations of neurons within the brain. Exogenous activation of these receptors by drugs of abuse, such as heroin and fentanyl, causes feelings of euphoria and can be highly addictive. During natural behavior, MORs in the brain are activated by the endogenous ligand enkephalin. Spiny projection neurons (SPN) in the nucleus accumbens (NAc) are known to express enkephalin and likely release it during neural activity. It is known that these enkephalin SPNs can be either excited or inhibited while animals consume natural rewards. However, it remains unclear whether these functionally distinct enkephalin SPN populations are anatomically intermixed or are anatomically separated within NAc. In this study, we used 2-photon calcium imaging through endoscopic lenses to examine the neural activity of enkephalin SPNs in NAc while mice consumed sucrose rewards. We characterized the reward-excitations or reward-inhibitions of individual enkephalin SPNs over multiple imaging sessions. Through precise post-mortem histological examination, we then verified the anatomical placements of our endoscopic lenses and associated the relative anatomical location of neuronal populations to their reward-related neural activity. We found that enkephalin SPNs in anterior NAc were consistently reward-inhibited while enkephalin SPNs in posterior NAc were reward-excited. This is the first demonstration of anterior-posterior axis differences in the reward-related modulation of enkephalin SPNs and is a key step to understanding how opioidergic neurons function in natural reward behavior.

While pregnancies with multiple offspring are known among cetaceans, sources of differences in rates of monozygotic (identical) twins versus dizygotic (fraternal) twins across cetacean species are not highly studied. The present study determined the most likely proportions of monozygotic and dizygotic twins using Weinberg’s Differential Rule and a large historical data set supplied by years of whaling data across six cetacean species: blue whale (Balaenoptera musculus), fin whale (Balaenoptera physalus), sperm whale (Physeter macrocephalus) humpback whale (Megaptera novaeangliae), sei whale (Balaenoptera borealis), and Antarctic minke whale (Balaenoptera bonaerensis). Additionally, we use this data to test the hypothesis that twins are less likely to survive to birth compared to a single offspring, by testing whether the proportions of twins decrease with increasing fetus length in each species. All six cetaceans were more likely to have dizygotic twins than monozygotic twins, with the exception of the humpback whale. Probability of monozygotic twins were found to be 0%-29% in blue whale, 23%-44% in fin whale, 8%-54% in sperm whale, 14%-85% in humpback whale, 2%-25% in sei whale, and 9%-34% in Antarctic minke whale. This study has the potential to determine what factors govern successful twin pregnancies within cetaceans and provide a better understanding of the reproductive capabilities of the order.

 Phytoliths are microscopic silica structures produced in plant tissue, and palms (family Arecaceae) are prolific producers of them. The stability of these structures contributes to the abundance of palms within the fossil record, as these structures can fossilize in sediments where leaves cannot, providing a wider range of evidence of the past palm geographic distribution. Palms generally grow in warmer and wetter environments, but certain species can live in more extreme climates (i.e., cold, dry). However, because 90% of palms are currently distributed around the equator and tropical rainforests, they are often used as an indicator of warmer environments in the fossil record. The current understanding of the taxonomic groups below the family level is limited, and it is unclear whether palm phytolith shape can be used to identify different palm groups in the fossil record. The Palm Project hopes to address this gap by testing phytolith classification using a morphometric approach. Over 100 species of known modern Arecaceae (~30 images/species) phytoliths have been imaged with a confocal microscope, and a semi-automated script in ImageJ quantifies the overall shape (globular or hat), density, and size of the phytolith ornamentations. Next, multivariate analysis on the morphometric data attempts to distinguish the phytoliths of various modern subfamilies based on distinct morphological traits, forming a quantitative baseline to describe and classify phytoliths. When combined with the collected ecological data, this could potentially identify signals between the environment of modern palm species and the phytoliths they form. Once the morphological differences between groups of modern palms are quantified, the same analysis can be applied to fossil phytoliths of unknown origins. This could reveal which taxonomic and ecological groups they belong to based on the most similar modern phytolith, giving insight into the phylogeny of Arecaceae and the paleoenvironment the fossils came from.

Reactive oxygen species (ROS) such as superoxide (O2–) and hydrogen peroxide (H2O2) are partially reduced oxygen molecules produced during cellular metabolism in all organisms. Plant chloroplasts and mitochondria are major ROS sources because of photosynthesis and aerobic respiration in these organelles. We previously found that the levels of oxidants were higher and antioxidants lower in maize (Zea mays) seedlings grown in the light than in the dark; these changes were accompanied by greater oxidative damage to the DNA in both chloroplasts and mitochondria in light-grown than dark-grown plants. In my research project, we will measure both H2O2 and antioxidants (catalase and peroxidase) after exposing dark-grown plants to light for increasing periods of time. Maize seedlings were grown in continuous darkness followed by 2, 4, 6, 12, and 24 hours of light. We then measured the levels of H2O2 and antioxidants in the chloroplasts and mitochondria isolated from leaf and stalk tissues during seedling development. Our data show the time course of ROS accumulation after the transfer from dark to light growth conditions and should provide a better understanding of the role of light in plant oxidative stress. Specifically, oxidative stress by ROS can be linked to DNA (mitochondria, plastid and organismal genomes) damage and by looking at the gradient of light exposure, it can open doors to discover how plants physiologically limit genetic impairment. This research can be used to assess more cancer-related topics in regards to ROS levels and how scientists can possibly find a solution in plant evolutionary-engineered genetics.

 Stroke is the leading cause of long-term disability in the United States. Disabilities can range from a loss of sensory function like touch to motor functions like controlling arm movements due to the damage to the brain’s network. Despite the prevalence of stroke, the underlying network dynamics that lead to functional deficits are not well understood. Due to the physiological similarities between non-human primate (NHP) and human brains, an NHP model is essential for studying the effects of stroke and developing therapies. Here we used the photothrombotic (PT) stroke technique to study network dynamics in the NHP sensorimotor cortex following an ischemic lesion. Using the PT stroke technique, we induced a focal ischemic lesion on the NHP sensorimotor cortex. We collected local field potentials from both hemispheres using an electrocorticographic  array on the cortical surface. As a measure of neural activity, we calculated ipsilesional power in the low gamma band. Channels were then organized into three clusters based on their net change in power (increase, decrease, no change). As expected, the cluster with an overall decrease in power corresponded to the lesion's physical location. We also studied the network connectivity by calculating pair-wise coherence across different frequency bands: theta, beta, low gamma, and high gamma. Overall, we saw that low frequencies were associated with decreases in coherence, while higher frequencies were associated with increases following stroke. Preliminary results from the contralesional hemisphere show similar changes. In this study, we observed local neurophysiological changes up to three hours following an ischemic lesion. The observed increases in power in the perilesional region and coherence at high frequencies suggest compensatory mechanisms immediately following an injury. We can use this study's results to guide future developments in stimulation-based therapy to alleviate the functional deficits from a stroke.

Despite recent advancements in cancer treatment, the 5-year survival rate for glioblastoma is only 22%. The greatest challenge in brain cancer treatment is the blood-brain barrier (BBB), a physical barrier that protects the central nervous system (CNS) from circulating solutes in the blood, but in cancer, prevents therapeutics from entering the brain space. While surgery is the gold-standard treatment, this procedure is high-risk. Thus, we are investigating injectable therapies to treat brain tumors by crossing the BBB. To do this, we are developing nanoparticles (NPs) to cross the BBB via receptor-mediated transcytosis (RMT). In RMT, ligands (keys) bind to receptors (locks) expressed by the BBB to gain entrance into the CNS. By attaching the ligand transferrin, we can trick the BBB into granting our NPs access to the brain. Prior to testing particles in vivo, I am developing a cellular model of the BBB to assess the ability of different NP formulations to cross the BBB in vitro. The transwell model comprises two main compartments: the donor and acceptor compartments, separated by a cellular monolayer that only allows transport between compartments via RMT. Here, I developed a co-culture consisting of brain endothelial cells and astrocytes. This co-culture model is more representative of the BBB and provides higher monolayer integrity than single-cell models. In parallel, I am investigating the use of acidification inhibitors to enhance the ability of NPs to cross the BBB. If successful, these inhibitors will be incorporated into a new NP design. Through this project, I am (i) developing a more representative in vitro model of the BBB and (ii) exploring alternative mechanisms to enhance NP transport through the BBB. Ultimately, these two aims will enable us to better direct NP behavior in vivo and cross the BBB.

Though renewed efforts in tuberculosis (TB) research have facilitated massive strides towards treating Mycobacterium tuberculosis (M.tb), TB remains a global health problem with an estimated 10 million infections and 1.4 million deaths in 2019. The ability of the pathogen to hide itself inside a granuloma, a mass of immune cells whose precise mechanism of regulation is unknown, prevents both the study of M.tb pathogenesis and the development of drugs or treatments. Current in vivo models have been established to study TB infection using animal models or tissues, limiting its biological relevance as it relates to human disease while current in vitro models lack components of the complex lung microenvironment during infection. We present the creation of a novel microscale infection model, which uses open and suspended microfluidic principles to enable spatial and temporal manipulation of cultures in suspended hydrogel plugs. By stacking together two devices, we demonstrate the ability of a suspended model granuloma consisting of M.bovis BCG (Mycobacterium bovis bacille Calmette-Guérin) and monocyte-derived macrophages to interact with a model vasculature layer consisting of endothelial cells. Analysis of soluble factors for proinflammatory cytokines and characterization of infection-dependent angiogenesis in the vasculature layer are used to verify communication between cultures. In the future, we envision this model expanding to contain multiple immune cell types and to incorporate additional aspects of the lung anatomy to approach a more accurate pathophysiological model as a tool for other researchers.

Glioblastoma (GBM) is a cancer originating in glial cells in the brain that accounts for more than 60% of all brain tumors in adults. The low survival rate can be attributed to high resistance to radiotherapy due to the hypoxic tumor environment which induces signaling networks in cancer cells that lead to the epithelial to mesenchymal transition (EMT). EMT gives rise to mesenchymal cancer stem cells (MSC) with a highly invasive phenotype which resists traditional means of therapy. Phospholipid glutathione peroxidase (GPX4), a selenocysteine-containing enzyme that dissipates lipid peroxides, has been shown to regulate pathways that prevent ferroptosis, a unique iron dependent form of cell death initiated by an increase in reactive oxygen species. Disrupting the GPX4 pathway by siRNA-induced gene knockdown induces ferroptosis. Therefore, NPs as a vector for gene therapy may be able to eliminate mesenchymal state stem cells for a more effective treatment. Using hypoxia to induce EMT to develop a cell model for this work, preliminary results from quantitative real time PCR showed a correlation between GPX4 and EMT markers of human glioblastoma cells in hypoxia. GPX4 siRNA were evaluated using commercially available transfection agents on hypoxic and normoxic cells as proof of concept in vitro over a period of ten days. NP mediated delivery of validated siRNA were optimized using different ratios of NP and siRNA. Incubation time was also optimized. Finally, dual therapy of siRNA knockdown and radiotherapy were performed to evaluate sensitization of cells. The capabilities of NPs, along with concurrent radiation therapy, may provide a means to overcome radioresistance in GBM therapy.

Periodontal disease stands to be the leading cause of tooth loss in older adults and is characterized by inflammation of tissues supporting the teeth and periodontal bone loss. This oral disease also occurs during normative aging in mice models. Thus, targeting the biological aging process may provide an innovative approach to reduce the impact of this disease in the elderly population. Rapamycin is a specific mTOR inhibitor shown to delay age-related decline and significantly extend the lifespan of mice models. Our lab has demonstrated that an 8 week treatment with rapamycin in aged animals reversed age-related periodontal disease. However, whether this improvement persists even after the treatment ends is still unknown. To determine whether reversal of periodontal disease persists even after stopping rapamycin treatment, cohorts of aged mice were either started with 8 week treatment with control (eudragit) food or rapamycin (42ppm) food, and then switched to either rapamycin (42ppm) food or control (eudragit) food for another 8 weeks, respectively. High resolution microCT imaging was completed to measure the amount of periodontal bone, and western blot was performed on total alveolar bone extracts and probed for the osteoclast marker RANKL. Our microCT analysis showed there was less periodontal bone loss in aged mice treated with rapamycin, and this result persisted even after 8 weeks on the control diet. Additionally, the age-related increase in RANKL expression was decreased in both treatment groups. In conclusion, the regain of lost periodontal bone in aged mice persisted even after cessation of rapamycin treatment, and the age-related increase in the osteoclast marker RANKL was decreased after rapamycin treatment and such decrease persisted. Overall, our studies indicate that short term treatment with rapamycin is sufficient to rejuvenate oral health and the benefits are maintained even after stopping the treatment.

The focus of this project is to study two newly discovered gene fusions that involve the Anaplastic Tyrosine Kinase (ALK) gene and define their role in Acute Myeloid Leukemia (AML) and potential for utility as therapeutic targets. ALK is a Receptor Tyrosine Kinase that contributes to brain development, regulation of cellular functions, and is linked to cell growth. Mutations and other genetic alterations are identified in various cancers. We recently discovered novel ALK fusions within a small set of AML patients in individuals with Monosomy7 AML (Loss of chromosome 7) and one of the most refractory subtypes of AML, making this particular group of patients high-risk. Additionally, ALK is otherwise not expressed in normal bone marrow making this a potential target. The current focus has been to verify if the ALK fusions are viable gene targets for chemotherapies that are already approved for clinical use, specifically Crizotinib, a chemotherapy drug and Tyrosine Kinase Inhibitor; by focusing on an FDA-approved targeted chemotherapy drug, this eliminates much of the process and time it would take to be able to treat AML in these high-risk patients. Crizotinib is successful in treating abnormal ALK expression seen in Anaplastic Lymphoma, Neuroblastoma, and Non-Small Cell Lung Cancer (NSCLC), and functions by preventing critical cell signals. We have engineered AML cell lines to express these fusions of interest in order to test Crizotinib in the context of AML.

The female reproductive tract must maintain normal reproductive functions while also being able to elicit immune responses to sexually transmitted microbes and viral pathogens. In response to virus exposure, the balance of these two functions can determine the outcome of infection and disease through alteration of vaginal mucosa integrity. Recent in vivo research in our laboratory revealed that vaginal infection by Zika virus (ZIKV), an emerging mosquito-transmitted flavivirus that is also sexually transmitted among humans, induces epithelial cell-specific innate immune response that accelerates a homeostatic form of cell death known as cornification. We hypothesize that specific processes in vaginal epithelial cells mediate cornification in response to ZIKV infection, and that this cornification may alter barrier properties, innate-adaptive immune crosstalk, and ultimately, the degree to which ZIKV disseminates from the female reproductive tract. We therefore analyzed and compared vaginal epithelial cell infection by both African and Asian lineage ZIKV strains using traditional 2-dimensional cell culture and organotypic 3-dimensional culture infection models. Differences in viral infection and replication kinetics, and innate immune response were characterized through RT-qPCR, immunoblot analysis, cell imaging, and viral plaque assay. Ongoing analyses are expected to reveal the application of organotypic 3-dimensional cultures in capturing in vivo qualities of vaginal epithelial cell/ZIKV infection and response compared to 2-dimension cultures. These studies will provide insights for application of vaginal epithelial cell culture models of ZIKV infection that encapsulates the complex functional and structural aspects present in vivo.

Cystic fibrosis (CF) is a genetic disorder characterized by chronic lung infections involving various organisms, including the gram-positive pathogen Staphylococcus aureus. Antibiotics, such as trimethoprim-sulfamethoxazole (SMX), play key roles in treating CF infections; these drugs inhibit bacterial growth by disrupting important bacterial metabolic processes. SMX specifically inhibits folate metabolism, causing DNA damage that results in bacterial cell death. However, S. aureus is able to persist in CF pulmonary infections despite treatment with antibiotics, and evidence suggests that S. aureus does so through adaptive mutations. Our goal is to identify the adaptive mutations of S. aureus during SMX exposure in vitro, to understand how this pathogen persists and to prevent the emergence of resistance. We grew S. aureus in the presence of super-inhibitory SMX concentrations for 24 hours in Luria Bertani broth. We sampled the culture at specific timepoints and measured viable bacterial counts on chocolate agar; we evaluated all resulting colonies for SMX susceptibility and associated genetic changes. Surprisingly, we identified mutants that survived SMX treatment carrying diverse adaptive changes not associated with folate metabolism or DNA repair, suggesting previously-unknown lethal effects of SMX against S. aureus. These mutants carried mutations predicted to decrease production of reactive oxygen species (ROS) - toxic compounds produced by all cells during aerobic respiration and in response to stress. Our results indicate ROS may play a role in SMX-mediated S. aureus cell death, suggesting that treatments that augment the effects of ROS could improve antibiotic efficacy. We are now exploring the involvement of ROS in S. aureus killing by SMX using engineered S. aureus strains with knockout and overproducing mutations in ROS detoxification genes. This study will help us better understand SMX’s mechanism of action and S. aureus’ response to this drug, in order to improve the treatment of diverse infections caused by this pathogen.

Tuft cells are a lineage of chemosensing epithelial cells that contribute to intestinal “type 2” immune responses during parasitic worm (helminth) infection. Tuft cells are thought to monitor the intestinal lumen, looking for type 2 agonists. While rare at steady state, during a helminth infection the number of tuft cells in the gut increases greatly (a phenomenon called hyperplasia), directly proportionate to the underlying immune response. Nippostrongylus brasiliensis is a common model of hookworm infection. This parasite is injected under the skin, migrates to the intestine, and can be cleared within 10 days, with a tuft cell response mediated by the cytokine interleukin (IL) 25 and largely independent of the IL33 receptor, ST2. In contrast, the roundworm Heligmosomoides polygyrus is ingested orally and has a lifecycle in which it matures inside the intestinal tissue rather than in the lumen, then re-enters the lumen and establishes chronic infection. Given their distinct lifecycles, we hypothesized that N. brasiliensis and H. polygyrus are sensed differently by tuft cells. Since the kinetics of tuft cell hyperplasia during N. brasiliensis are well defined, we created a comprehensive timeline of tuft cell hyperplasia in wild type mice infected with H. polygyrus for comparison. Intestinal tissue was collected from three mice on every other day of infection, until 20 days post infection. We used immunofluorescent staining to quantify the tuft cells on each harvest day and discovered distinct waves of tuft cell hyperplasia that align with the two separate times that H. polygyrus worms enter the lumen. This timecourse highlighted two peak timepoints of hyperplasia, which we studied further to test the hypothesis that IL33 is critical in the H. polygyrus immune response. Through this work, we strive to better understand how and why our bodies respond to the various type 2 agonists, and how this response can be most effective.

 In 2019, the severe acute respiratory syndrome coronavirus (SARS CoV-2) emerged across the world with devastating effects. In severe cases of infection, SARS CoV-2 elicits an overactive immune response leading to extensive damage to lung tissue potentially through overproduction of proinflammatory cytokines. To further our understanding of this novel coronavirus, our project studies the effects of SARS CoV-2 on the innate immune response in lung epithelial cells. Innate immunity mediates antiviral defense in response to virus infection and other pathogens, wherein innate immune activation is triggered by virus infection and induces type I and III interferons that play an important role in antiviral defense though expression and actions of interferon stimulated genes (ISGs). Our project investigates which SARS CoV-2 protein is responsible for antagonizing virus-induced innate immune activation of the infected host cell. We screened the individual SARS-CoV-2 proteins in a lung epithelial cell transfection/innate immune activation model using Sendai virus as an innate immune activator to examine interferon induction in cells expressing each SARS-CoV-2 protein. We hypothesize that one or more viral proteins will antagonize innate immune activation. Our preliminary results show that increasing amounts of the viral membrane protein (M) decreases the innate immune activation as marked by reduced ISG induction. Our findings have implications for future treatments of SARS CoV-2 by providing insight on new potential viral targets to mitigate virus-mediate innate immune blockades.

Brain extracellular matrix (ECM) structure mediates many aspects of neuronal function. When ECM structure becomes dysregulated in neurological disease, one resulting impact is impaired neuronal function. Therefore, probing changes in the ECM structure could provide insights into disease mechanisms and expose potential therapeutic pathways. Previous work in our group determined that degrading neural ECM structures leads to a significant increase in the diffusive ability of nanoparticles navigating the brain extracellular space. However, this diffusion-based analysis provides little insight into changes in ECM-specific morphology or structure; analysis only predicts if they are present and the degree of alteration from normal. With this project, we aimed to characterize changes in perineuronal net (PNN) structure with high spatial resolution using a fluorescence-based imaging approach. PNNs, a structure that impact neuronal function were stained using a fluorescently labeled lectin (Wisteria floribunda agglutinin) and images acquired via confocal microscopy. Images were collected from the cortex of brains spanning an age range of post-natal day 14 to adulthood. We first manually quantified morphological features associated with PNNs, including the total number of branches, average branch length, and total branch length using the image processing program ImageJ. To reduce image processing time and minimize user-bias, I am building a Python-based, automated quantification workflow for future use. Regarding the manually quantified PNN features, we observed an increase in both the total branch length/PNN and average branch length/PNN as brains increased in age. The total number of branches/PNN remained relatively consistent across age groups. Future work will focus on applying the same approach to a model of neonatal hypoxia ischemia to study injury effect on PNN structure. Collectively, this project established a methodology that can be applied for enhanced characterization of ECM-related structural changes induced by neurological disease, and has the potential to unveil new avenues of therapeutic intervention.

Antiseizure medications (ASM) may contribute to adverse fetal outcomes in pregnant women with epilepsy (WWE). Folate processing (methylenetetrahydrofolate reductase, MTHFR) gene abnormalities are common in women with epilepsy and depression. The enzyme product of this gene is a component of the metabolic pathway that makes folate bioavailable through methylation, critical for maintaining adequate serum folate levels. Folate is known to be crucial for fetal development, namely in the prevention of spina bifida and other neural tube defects (NTDs). The teratogenesis of some ASM in combination with genetic polymorphisms put WWE at higher risk for infertility, miscarriage, and/or major fetal malformations. L-methylfolate supplements may bypass deficiencies in the MTHFR-mediated folate metabolism pathway, yet their use in WWE during gestation or on fetal development is not well studied. We hypothesized that supplementation with L-methylfolate and methylcobalamin (methylated B12) may support better perinatal and fetal outcomes in pregnant WWE. We examined pregnancy histories of three WWE who supplemented with either folate or L-methylfolate and methylcobalamin (methylated B12) during pregnancies. Their pregnancy outcomes (both in conception and gestation) as well as mood stability improved with supplementation. L-methylfolate and methylcobalamin supplementation merits further study in WWE who have MTHFR mutations, fertility, recurrent miscarriage and/or depression histories.

Seattle, Washington was one of the first major U.S. cities to be impacted by the COVID-19 pandemic. In March 2020, the city implemented a stay-at-home order, shutting down businesses and restricting gatherings. In response, the COVID-19 Seattle Streetview Campaign project was launched in May 2020 to collect longitudinal photographic data to track the impacts of the pandemic on the city, as well as its recovery. Using technology similar to Google Streetview, the campaign collects data every 2-3 weeks along a consistent route in the city of Seattle. Our research objective is to utilize images collected from the Streetview Campaign project to understand COVID-19’s impact on Seattle’s hospitals and parks following non-pharmaceutical interventions (NPIs) such as stay-at-home orders. We described and compared changes in the content of images collected in the Streetview Campaign at hospitals and parks in Seattle from May to December 2020. Our data analysis first identified parks and hospitals that were fully visible along the route. Then, we selected a purposive sample of five fully visible hospitals and five fully visible parks, with a goal of diverse socioeconomic representation. In pairs, we each independently reviewed the images at a mutually-agreed upon location and wrote open-ended descriptions about the content of the images (e.g., number of people and cars; presence of other objects like construction equipment and bikes). We met weekly to compare results, identify discrepancies, and formulate a mutually-agreed upon description of the images. We then explored changes in the content of the images over time. Our findings include information about changes observed in images at hospitals and parks throughout the COVID-19 pandemic. They also provide insights about unique contributions of Streetview data can make in understanding the impacts of the pandemic and associated NPIs, as well as inform future analyses using machine learning and corresponding qualitative inquiry.

In this study, I aimed to determine whether the genetic signature of Nitrate Reductase (NR) from phytoplankton in the environment is correlated with the in-situ nitrate concentration. To accomplish this, I first generated a phylogeny of phytoplankton NR amino acids sequences to determine if the sequences separate into monophyletic groups that match their taxonomic identification. Secondly, I placed RNA transcripts for NR derived from samples collected off the coast of Hawaii onto the tree to determine which clades expressed NR. Finally, I constructed heat maps to show the abundance of RNA transcripts for each phytoplankton clade by latitude and nitrate concentration to establish trends in phytoplankton phyla distribution. Results indicated that all phytoplankton, no matter phyla or cell size, were more abundant in higher nitrate concentrations. If instead RNA transcript abundance was normalized by chlorophyll concentrations, there was little separation in distribution based on plankton size, and different trends based on phyla emerged. Alveolata, Archaeplastida, and Stramenopiles were found in similar low to moderate nitrate concentrations (0.0023µM-0.8052µM). In contrast, Cryptista did not display a consistent trend across the phylum, as all clades displayed different abundance patterns. Haptophyta, both large and small, made up a significantly higher proportion of phytoplankton found in low nitrate environments (0.0009µM). These results indicate that there is separation of phytoplankton phyla by nitrate concentration, supporting the hypothesis that these phyla have evolved to utilize different ecological niches, however further research is needed with higher taxonomic resolution to fully quantify the factors controlling the distribution of different phytoplankton clades.

This study, hosted by the Washington State Department of Natural Resources, uses passive acoustic monitoring (PAM) and forest habitat surveys to measure ecological diversity and responses of biota to habitat change caused by forest management. The management experiment takes place in the Olympic Experimental State Forest (OESF) on the western Olympic Peninsula in Washington State, and includes upland forest manipulations with assessment of stand and upland biotic responses. The specific objective of this study is to evaluate bird species as indicators of habitat quality and function in forest stands at different seral stages and subject to different regeneration practices. To establish occupancy models for each indicator species, PAM instruments are set in forest stands of various seral stage and management practices across OESF, and from their recordings, audio surveys are developed for processing into occupancy data. Automated detection using R programming is utilized for the processing of this data. I personally contribute to this project through manual verification of species detection data to assess accuracy of automated detection systems. Habitat characteristics are sampled in the field and derived from remote sensing data using ArcGIS. Results will inform future management decisions by offering analyzed data on the ecological effects of different forest management strategies. Results will additionally provide a more robust evaluation of certain songbirds as indicator species of habitat quality and function. My concurrent independent research objective, examined via literature review and occupancy data subsampling, is to assess indicator species efficacy and identify species alternatives, considering criteria relative to suitability for passive acoustic monitoring and suitability in anticipation of climate change. All of these results can be consulted in future research and management in the region by providing a more detailed understanding of the effects of management strategies and how best to evaluate them.

Climate Change is an undeniably major issue in the 21st century. While the effects of climate change and global warming cannot be reversed in one day, with cumulative efforts from individual communities, it is possible to slow down its effects. With the rapid development of major companies in cities, more foot and vehicle traffic are bound to follow, releasing higher levels of carbon dioxide in the air. Taking place in Bellevue, Washington, The research study explored the effect of the density of trees in varying areas, on its carbon dioxide and temperature levels. A series of data was taken at the well-forested Robinswood Park, and the minimally forested Bellevue Downtown Shopping center, over a two-week span, twice a day; once in the afternoon, and once in the evening. The goal was to see if a higher density of trees would lead to lower temperatures and lower carbon dioxide levels. My role in the research project was to format the data in order to put it into data correlation graphs between carbon dioxide levels, a varying density of trees, and temperature. After the study, an analysis of the data correlation graphs, revealed that a higher density of trees did lower carbon dioxide and temperature levels. In fact, even the mere presence of trees lowered these levels. Therefore, with the addition of low impact, low maintenance trees to urban areas, carbon dioxide, and temperature levels can be reduced. This study provides insight into a smaller scale of a very large issue, which can eventually be improved with collaborative efforts.

This project determines how a legacy of disturbances affects resident wildlife. By using small mammals as an indicator of ecosystem health, this research observes species richness in decommissioned military bases that are now parks by using camera traps. The 20m circular survey sites consist of two disturbed plots and one control plot in both Discovery Park and Fort Worden State Park. The disturbed plots in Fort Worden State Park consist of a dump site and gas station site, whereas those in Discovery Park are highly developed areas that are now undergoing restoration. There is evidence of military bases serving as biodiversity hotspots, and this project lends insight into how previously disturbed areas within the military bases support species. Through the collection of small mammal and vegetation species richness data, as well as recording the characteristics needed for small mammals to persist in each plot, I conducted linear regression analyses and observed concentric circles overlaid on land use data. Landscapes are often surveyed regarding a single species, but rarely studied in the context of land ownership alterations and their effects on the wildlife community depending on the resources the land provides. Likewise, studying residual disturbances after restoration takes place is important in concluding that management strategies maintain or improve the well-being of wildlife, as well as benefit the public. So far, I have concluded that vegetation does not play a significant role in small mammal species richness, though I suspect that contiguous forest cover will play a significant role upon further analysis. My expectations for this project are that the results will inform restoration managers what species are utilizing park resources and how disturbed areas can be managed to better support wildlife.

Microbiomes are now known to provide numerous benefits to hosts, from immunity to reproductive success. Vertical transmission of microbes has been linked to improved offspring success, for example by protecting eggs from pathogens post-oviposition. Infection with pathogenic soil fungi is associated with mortality in soil-incubated eggs, but may be ameliorated by the transmission of beneficial microbes.To determine whether 1) maternal microbes are deposited on eggs during oviposition, and 2) whether they have an antifungal effect that increases hatching success, we conducted challenges between dissected or oviposited eggs from the striped plateau lizard (Sceloporus virgatus) and fungi from failed S. virgatus eggs. Unique fungal and bacterial morphs were isolated from eggs to identify potential pathogenic fungi and antifungal bacteria. Direct challenges were carried out between individual bacteria and fungi to assess antifungal capabilities of bacteria isolated from the S. virgatus eggshell microbiome. Dissected eggs (no contact with the cloaca) had significantly lower hatch success, and hatchlings from dissected eggs were significantly smaller and lighter than those from oviposited eggs, indicating that some element of oviposition is key for hatchling success. One bacterial genus (Enterobacter) was found in the cloacae of females and on eggshells, suggesting that vertical transmission may be occurring. Three fungi were found to dominate the eggshell community of both dissected and oviposited eggs exposed to multiple fungi, suggesting that they may be responsible for egg mortality. At least two of these species of fungi have known pathogenic effects in other reptiles, and may produce antibacterial and antifungal metabolites.These results suggest an antagonistic relationship between fungi and bacteria on S. virgatus eggshells, indicating that bacteria transmitted during oviposition may improve hatch success in this species. Additionally, vertical transmission of beneficial microbes may serve as a form of parental care and occur via a novel pathway, the cloaca.

Ice cores provide unique records of past climate, including chemical deposits from volcanic events, for up to 800,000 years before present. In this project we examine sulfate concentrations in five different ice cores in Antarctica. Sulfate measurements from deeper in an ice core are at risk of diffusion altering the chemical concentration. We define any sulfate concentration exceeding a prominence threshold of two standard deviations above the mean as a volcanic event. We track how the volcanic signals differ from one another, and evolve with depth (age), by finding the amplitude, width, and total area under each peak. By taking a variety of measurements of each volcanic signal, we can then compare similar signals across ice cores. Using the change in duration of volcanic events, we were able to infer a considerably lower diffusivity than the only previously published estimate, suggesting less alteration of the sulfate signal than originally expected. Understanding how mechanisms in the ice change the sulfate record allows for a more accurate interpretation and clearer understanding of Earth's past climate.

Extreme precipitation events have the potential to threaten physical infrastructure, property, and human lives, and are predicted to become heavier due to climate change. Understanding past, present, and future precipitation is important in analyzing how precipitation risks change spatially and temporally. The observational record, from which point precipitation frequency estimates such as NOAA Atlas-14 are derived, is limited by its lack of spatial coverage and it represents just one realization of past climate. When using a high-resolution large ensemble global climate model, we have multiple realizations of climate, consistent spatial coverage, and the added benefit of being able to incorporate climate change scenarios into precipitation risk analysis. Here, we use the GFDL (Geophysical Fluid Dynamics Laboratory) 50-km horizontal atmospheric resolution global SPEAR (Seamless System for Prediction and EArth System Research) 30-member ensemble to analyze how U.S. 24-hour precipitation extremes at various return periods change over the 1921-2100 time period. We quantify extreme precipitation risks across the U.S. and locally under different climate change scenarios (SSP2-4.5, SSP5-8.5, and natural forcings alone). With the large ensemble, we are also able to explore methodology and uncertainties in characterizing extreme precipitation risks.

Star formation at the outer extremities of the Milky Way takes place under conditions much different from those in the rest of the Galaxy, giving us a window into how the process differs in a low-density, low-metallicity region. The Outer Scutum-Centaurus (OSC) spiral arm is the most distant molecular spiral arm in the Galaxy, lying about 15 kpc from the center of the Galaxy. In this study, we use the VLA radio array to observe 12 HII regions in the OSC, all of which had no previously existing continuum data. HII regions are areas of ionized hydrogen around massive stars and are the brightest objects in the radio spectrum across the Milky Way, making them perfect laboratories to study star formation in the outer Galaxy. These OSC HII regions represent the most distant known high-mass star formation regions in the Milky Way and give us an excellent laboratory for studying those processes in a low-density, low-metallicity environment. Our data let us identify radio continuum data for 7 HII regions in the OSC, as well as establish upper limits for the RMS associated with the other 5 observed nondetections. By assuming a single ionizing star for each region, we assign spectral types from O9 to O5.5 to these sources. Combined with existing data, we identify a total of 12 HII regions in the OSC Arm with continuum and spectral data. Further research would involve re-observing our nondetections to identify data for what are likely B-type ionizing sources. Obtaining meaningful data for those nondetections would allow us to classify more stars powering HII regions in the region, increasing the amount of information known about star formation in the extreme conditions of the OSC and potentially revealing new information about how O-type and B-type stars form differently in the same unique environment.

Standard diagnostic tests for common bacterial and viral infections are invasive and uncomfortable, especially for children. Difficulty performing these tests leads to diseases such as strep throat or pneumonia going undiagnosed in children with significant health risks. There is a need for more accessible diagnostics. Our research uses saliva analysis as a diagnostic medium for Streptococcus pyogenes. This presentation depicts a novel saliva collection platform that is designed and engineered to be child-friendly, effective at pathogen collection, and is suitable for home use. We produced prototype devices using 3D printing, computer numerical control (CNC milling), and molding. Human studies were performed to examine usability and inform further design. In addition to engineering the device, we tested coatings and capture of bacteria. Preliminary data finds success in capturing S. pyogenes. Collection of commensal oral bacteria capture is the next step of our human studies. Our expectation is to find success with our device in a human mouth. Once our device and system are established, we plan to expand to include additional diseases. We will be presenting our innovations in the device as well as our preliminary data on the efficient capture of bacteria. We hope this technology will provide diagnostics with a way to provide care to underserved populations as well as help us to better collect data regarding the bacteria and viruses present in previously inaccessible populations. 

Dental implantation is a common clinical procedure used to replace missing teeth and maintain bone structure and facial aesthetics. However, it leads to unexpected side effects, including bone loss or peri-implantitis in 1 out of 10 cases due to failure of osseointegration, defined as improper integration of the implant into the mineralized bone. To enhance osseointegration, the present study aimed to form a layer of hydroxyapatite that could facilitate the integration of the implant (Titanium or Zirconia) with the alveolar bone that lead, while also having antimicrobial property to prevent local infection. Our previous study demonstrated that titanium-binding peptides (TiBPs) are able to bind specifically to the surface of Ti and that amelogenin-derived peptide (ADPs) can be used for direct remineralization on the bone surface. We also identified antimicrobial peptides (AMPs) that can inhibit common oral bacterial growth. These results imply that there is an opportunity to design two of heterofunctional peptides, both binding to Ti with one has the function of directing biomimetic remineralization process, while the other providing antimicrobial activity. The Ti-surface is modified by chimerizing the TiBPs and the ADPs, and TiBPs and AMPs, with short amino acid sequences. The overall process is separated into two main steps: 1. Designing and synthesizing the chimeric peptide; 2. Characterizing (a) binding, (b) mineralization and (c) antimicrobial efficacy of chimeric peptides on the implant surface. We predict that the chimeric peptides will have high binding affinity to the titanium surface while simultaneously enabling mineralization on the implant surface and inhibiting the growth of bacteria. The present aims to contribute to the foundation of finding a long-term novel dental implant treatment via the molecular biomimetic approach towards a clinical strategy to enhance the long-term durability of dental implants. The research is supported by Mary Gates Scholarship (YL), Spencer Funds from School of Dentistry, and CoMotion.

Cannabis is one of the most commonly used recreational drugs in the United States. Its effects are mediated by cell surface receptors binding to cannabinoids found in cannabis, and expression varies with location and cell type. Endocannabinoid receptor 1 (CB1) expression occurs primarily in the nervous system while endocannabinoid receptor 2 (CB2) expression is commonly associated with immune cells. Cannabinoids can affect the immune response, however their specific effects on the immune response to pulmonary viral infection is unknown. In these experiments we use a mouse model to study the effects of cannabis smoke inhalation on subsequent influenza virus infection. C57BL/6 wild type mice or CB2 knock-out mice were exposed to a sub-acute level of smoke for 2 to 4 weeks using a TE Manual Smoking Machine. Cages of mice were exposed every other day to two rounds of smoke from six cannabis cigarettes. Each smoking round lasted 30-60 minutes with a 10-15 minute recovery period. Tetrahydrocannabinol (THC) levels, an active component in cannabis, were assayed by mass spectrometry in urine and blood. THC levels (0.74 +/- 0.17 ng/mL in urine, 14.3 +/- 0.94 ng/mL in blood) indicate an effective smoking regimen. Mice were subsequently infected with 10-20 plaque forming units of mouse adapted Influenza A virus and harvested 9 days post infection. Data includes bronchoalveolar lavage (BAL) cell count, daily weight change, and flow cytometry analysis of lung cells. No statistical significance in BAL cell count of mice air or cannabis smoke exposed was seen. Air exposed female mice exhibited significantly more weight loss than cannabis exposed female mice, indicating a more severe response to the virus. Cannabis exposed mice exhibited less weight loss on days 5 to 9. Continuing studies include a more detailed flow analysis of cannabis smoke exposed immune cells and its impact on viral infection.

Toll-interacting protein (TOLLIP) is a ubiquitin-binding protein that is involved in the signaling pathways of Interleukin-1 receptor (IL-1R) and Toll-like receptors (TLR). Previous studies have shown that single nucleotide polymorphisms in the TOLLIP gene are associated with mortality and outcomes in idiopathic pulmonary fibrosis, however, the biology of TOLLIP in lung injury and repair is unknown. While animal studies have shown that TOLLIP modulates acute inflammation, the effect of TOLLIP deficiency in the mouse model of lung injury and fibrosis is unknown. In this study, our group investigated the effect of TOLLIP deficiency in the bleomycin model of lung injury. Previously, we observed that TOLLIP deficiency attenuated acute lung injury in the lipopolysaccharide (LPS) model of lung injury. We hypothesize that TOLLIP deficiency leads to increased lung injury in bleomycin-induced lung injury. To study this, we treated wild-type (WT) and TOLLIP knockout (KO) mice with bleomycin through intratracheal instillation (IT). At 14 days post-treatment, we collected bronchial alveolar lavage fluid (BALF) and lung tissues to evaluate the degrees of lung injury and fibrosis. Throughout this study, I helped maintain the mouse colonies, genotype the mice, process the samples during the harvests, collect BALF cell differentials, and analyze the data. Preliminary analyses of weight loss, BALF total protein, and cell differentials suggest TOLLIP deficiency results in worse lung injury at 14 days post-bleomycin. This work provides insight into the role of TOLLIP deficiency as an attenuator in long-term lung injuries and how it may be used as a potential treatment for inflammatory disorders and infections.

Cell quiescence is defined as the reversible state of a cell in which it does not divide but retains the ability to re-enter cell proliferation. Quiescence can either be programmed or injury-induced. The phenomenon is influenced by mTORC1 signaling, a target for cancer therapeutics. Improved understanding of the mechanisms behind stem cell quiescence holds potential for future therapeutics against tumorigenesis. Cancer biology research in the past have suggested a correlation between mTORC1 activity and mitochondrial fusion and biogenesis. To pinpoint how mitochondrial dynamics influence stem cell quiescence, I radiated, dissected, and imaged UAS-Gal4 Drosophila models with specific mitochondrial gene knockdowns. As hypothesized, Drosophila ovaries with mitochondrial biogenesis and inner-membrane fusion knockdowns failed to exit quiescence after radiation. To further confirm our hypothesis, I am now directly quantifying the mTORC1 activity of mitochondrial knockdown Drosophila lines. Once collected, our data will contribute to ongoing research in cancer therapeutics.

Spinal cord injuries can result in devastating health consequences and impair voluntary muscle control. Animal models are invaluable for the development of new treatments to restore hand and arm function. In rats, we are developing a novel targeted, activity-dependent spinal stimulation (TADSS) therapy that promotes plasticity in spared pathways with a neuroprosthetic device after a C4-C5 spinal cord injury (SCI). Recovery is measured through training the rats in reaching tasks and comparing performance during therapy to the pre-injury scores. We have found that females show robust functional recovery with TADSS treatment, but males do not. One potential explanation for the difference in recovery is that females are more motivated to perform the behavioral tasks. Thus, we examined reaching performance of males and females prior to injury to see if there is any evidence of preexisting sex differences in reaching performance. Within groups of uninjured animals learning the reaching task, females on average had more trials than males, though both males and females had similar success rates. This may be evidence of greater motivation to perform the reaching task in females. Little research has been done on the role of sex and motivation in reaching tasks; however, other groups have shown that sex differences in performance of behavioral assays may be due to differences in motivation. We hypothesize differences in motivation may influence the level of functional recovery from SCI’s with TADSS therapy, as the intraspinal stimulation is dependent on muscle activity in impaired forelimbs. The aim of our future experiments is to determine the effect of sex on rodents’ motivation to perform reaching tasks before and after injury. By continuing to investigate the effect of sex-related motivation differences on motor tasks associated with SCI recovery, we hope to optimize TADSS therapy for clinical use in humans.

Human Immunodeficiency Virus type 1 (HIV-1) is currently a major cause of morbidity and mortality worldwide. HIV-1 isolates are classified into genetic groups M, N, O, and P. Group M is the most widespread and is further divided into at least nine genetic subtypes and over 100 circulating recombinant forms, the prevalence of which vary by geographic locations. Subtype B is the most common form in Europe and North America and as a result, receives the majority of funding and research. Because of this, most of what we know about antiretroviral drug resistance in HIV-1 is based on studies of subtype B. However, the majority of HIV-1 infections worldwide involve other “non-B” subtypes, and much less is known about drug resistance in these subtypes. Knowledge of resistance to integrase inhibitors (INIs) is particularly important, since INI-based regimens are now recommended as first-line treatment for HIV-1–infected individuals globally. My objective is to genetically alter a full-length HIV-1-encoding plasmid (HIV-1 pNL4-3) that can used as a “cassette” for cloning non-B, patient-derived integrase sequences. To do this, I have identified restriction sites flanking the integrase region that can be used to remove and replace the integrase region with a patient-derived sequence, but site-directed mutagenesis must be used to knock out additional restriction sites for the same enzymes within the plasmid to avoid undesired enzymatic activity. This will result in only the desired sites, without changing the amino acid sequence. This vector will enable us to generate recombinant viruses from patients who are failing INI-based treatment, which can be tested for resistance to INIs in cell culture. The resulting data will be used to improve prediction of drug resistance in non-B HIV-1 based on sequence information alone. These studies will help guide treatment recommendations for both individuals and populations infected with non-B-HIV-1.

Epilepsy is one of the most significant neurological diseases in the world. Although there have been numerous advances in the study of epilepsy, there is still much we can learn about it. This is supported by the fact that one third of the patients with epilepsy are resistant to their anti-seizure drugs. With the mechanisms of pharmacoresistant seizures still unresolved, this project utilizes the mouse 6 Hz model of pharmacoresistant focal seizures to help answer some of its questions. Specifically, we hypothesize that the extent of brain region activation is directly correlated with increasing stimulation intensity used to invoke a seizure. Using cFOS, a marker for neuronal activity, we characterized the effect of varying stimulation intensities on cFOS immunoreactivity and its recruitment of nearby brain regions at various stimulus intensities. Using the established 6 Hz model we determined the convulsive current that caused a seizure in 97% of the population (CC97) in adult male mice. Ninety minutes after stimulation, brains were extracted, and processed for immunohistochemical labeling of the early activation gene, cFOS. Pending results will determine whether increasing stimulation intensity will result in greater cFOS labelling as well as greater recruitment of surrounding brain regions. These data will inform our future studies investigating the effects of several antiseizure drugs on blocking the recruitment and activity of different brain regions at varying stimulus intensities in the 6 Hz model.

Neurogenic cough is a type of chronic cough related to hypersensitivity of the nerves in the larynx. There are several treatments for neurogenic cough, including neuromodulating medications, procedures, and cough retraining therapy. Superior laryngeal nerve (SLN) block is an emerging treatment that has yet to be well studied. This procedure involves injection of a steroid, along with a local anesthetic, into the neck trans-cervically, anatomically targeting the main nerve responsible for transmitting laryngeal sensation. It is thought to interrupt or dampen the neural pathways that simulate coughing. We aimed to assess factors that are predicative for a positive response to an SLN block via a retrospective chart review cohort study. We examined a variety of factors, such as history of cough, including triggers and type of cough, history of reflux and allergies, and prior neuromodulator use. We reviewed physical exam and testing findings, such as unilateral vocal cord paresis, which has been associated with neurogenic cough. We have identified 33 patients who are eligible for this study, have nearly completed chart review, and we will perform statistical analysis to associate factors with positive responses. Our series will report on the infrequently studied (2 existing publications) SLN block as a treatment for neurogenic cough patients. Our results will help us understand whether SLN block is a feasible treatment for neurogenic cough.

  Constructed response short answer assessments provide greater insight into student understanding than multiple choice evaluation, but involve time-intensive grading. To increase scoring efficiency, we worked with the Automated Analysis of Constructive Responses (AACR) Research Group to use supervised machine learning to generate a computer scoring program for a biology constructed response formative assessment question. However, ensuring accurate and unbiased scoring is necessary before this technology enters classrooms. Due to underrepresentation of first-generation and minority students in STEM classrooms, and the assessment rubric’s potential specificity to University of Washington curriculum, I hypothesized a decreased scoring accuracy for first-generation and minority student responses and for students not attending the University of Washington. Responses for the constructed response formative assessment question were collected from five institutions, including public universities and community colleges, and were scored by myself, another trained human scorer, and the scoring program. Previous research found that this question, human-scored, shows no bias by student demographic (i.e., there is no differential item functioning). Responses were de-identified prior to human scoring, and human scores were reviewed by the supervising researcher before analysis. I analyzed the scoring program’s accuracy for dependence on students’ reasoning level, GPA, university, timing of assessment, first generation status, race or ethnicity, and gender, using logistic regression and model selection. My analysis found no significant demographic or institutional bias in the scoring program. However, results did indicate a decreased computer scoring accuracy for higher-level reasoning scores (when students had more accurate responses to the question). For this assessment question and scoring program, my results indicate that further training of the program on higher-level responses is needed before scoring bias is eliminated. This bias-analysis research ensures the increased scoring efficiency offered by computer scoring programs does not come with an increase in assessment bias.

The flexibility of general models, such as flux, provides physiology instructors with a great tool to enhance students’ ability to apply physiology concepts to many different scenarios. The general model of flux is that the magnitude of the gradient divided by the magnitude of the resistance is proportional to the rate of flow. Flux can be used to understand the bulk flow of a wide variety of fluids (e.g., air, blood, sap) as well as diffusion and osmosis across physiological systems. In order to design effective curricula to support students’ mastery of flux, it is necessary to understand the types of reasoning about flux that students bring to class. Our study focuses on students’ use of flux in the specific case of air movement from the atmosphere to lungs while taking a breath. We collected more than 1000 student responses from five institution to a question about how people take a bigger breath. We used a constant comparative analytical approach to uncover recurring patterns in the way students approached this problem and to what extent they utilized flux in their reasoning. We summarized these patterns into a framework describing four levels of student reasoning: Level 4, highest level, explains how air pressure gradient is manipulated to create air flow into lungs by increasing volume and therefore decreasing pressure; Level 3, explains the inverse relationship between volume and pressure OR the concept of pressure gradient between lungs and atmosphere; Level 2, explains that lung volume increases to cause more air flow; Level 1, describes air moving into lungs causes a big breath or describes the anatomical steps in a big breath. Our framework can be used by physiology instructors to improve their teaching. Moving forward we will validate our levels of reasoning through oral interviews conducted for the same question.

 Multiple-choice assessments do not adequately gauge students’ understanding of principle-based reasoning in physiology. Open-ended formative assessments provide a more accurate method to assess students’ reasoning, however, large classrooms and short-staffing can limit their implementation. Utilizing machine learning to develop computer scoring models trained to score according to principle-based reasoning rubrics can make categorization of student responses efficient and feasible. However, potential biases in computer scoring models is yet uninvestigated. The aim of this study is to investigate biases, specifically towards age and accessibility to English in high school, by comparing demographic data with trends in computer and human code differences. We collected demographic data and responses to two physiology questions which were then coded by experts and the computer model. Utilizing generalized linear models including fixed effects to control for potential discrepancies, we investigated relationships between demographic data and computer scoring accuracy. There were no significant differences in computer model accuracy for our demographics of interest. However, the probability of the computer being accurate depended on the reasoning level of the response as categorized by human coders. The computer had a higher probability of being accurate for lower-level responses. When examining how the computer scored if it was incorrect, we found the computer was more likely to score higher levels of reasoning lower than the human categorization and vice versa for lower reasoning levels. While we did not identify any biases due to our demographics of interest, we observed a pattern in the accuracy of the computer depending on the reasoning level of the response. Our investigation provides essential feedback for computer model developers. Improving the computer model will more accurately measure students’ reasoning level and guide physiology education. Instructors from other disciplines will benefit from this research as it proposes a framework for better assessing student understanding.

The COVID-19 pandemic has caused many college courses to shift to an online format. Many instructors have altered their teaching methods to maximize student learning. For example, some active-learning instructors have embedded autopause questions, which appear when the video stops at certain points, in recorded lectures. We wanted to understand how autopause questions could change student behavior in approaching class questions. We hypothesize that if a professor has the video “autopause” before the video provides the answers to these questions, then students will be more likely to generate their own answer prior to hearing the correct answer. We investigated this hypothesis over two quarters of introductory biology III. Students complete “lecture follow alongs (LFAs)” assignments as they watch the video. In one quarter, students were asked to pause the video and answer the questions. In the second quarter, the video autopaused, and the students had to positively affirm they answered the question before the video continued. Only the LFA responses, not the autopause questions, are graded. We are investigating differences in student responses to the LFAs between quarters. In our initial scoring of two LFA sets in summer and autumn quarters, about 50 percent of students copied the instructor’s own answers for about a third of the LFAs, while less than 30 percent copied in an earlier set. Looking at such responses will inform us about how students are approaching the questions and whether they are initially thinking about and forming their own answers. Our results will give insight into the effectiveness of autopause questions in changing student behavior, so that students approach the questions themselves before hearing the correct answer. If autopause questions are able to significantly change student behavior in this manner, then this method can be successfully implemented in other online courses to maximize student learning.

In 2020, the COVID-19 pandemic caused students living in rural areas to experience exacerbated educational disparities. This included familial financial stresses, which also pushed many migrant students living in rural communities to prioritize work over school. The pandemic shed light on educational disparities featured in rural public-school education systems. The purpose of the study was to examine how the education trajectory of students in rural communities had been affected by the social and economic impacts of COVID-19. To accomplish this purpose, we examined the extent to which familial needs impacted students’ post-high school educational plans, how financial strain influenced their post-graduation choices, and how students practiced resourcefulness and resilience despite experiences of economic hardship. In this community-based qualitative research project, we conducted semi-structured interviews with Eastern Washington high school seniors who are 18 years of age or older and used a phenomenological thematic analysis to gather themes related to our research questions. As part of the research, we collaborated with a community advisory committee composed of teachers and recent high school graduates from Eastern Washington communities to develop the project’s research methods and to ensure the analyses and interpretation of interviews are reflective of the students’ experiences. We predicted that students will plan to alter their post-high school paths to accommodate their families’ needs. Anti-racist - strength-based - frameworks were used to make academic support recommendations for students in rural communities. Ultimately, our study can help inform collaboration with community members to find solutions so we can best support students and encourage them as they navigate pathways after high school graduations.

The engineered wood product Cross-Laminated Timber (CLT) is a promising alternative to steel and concrete construction in multi-story buildings, and it is beginning to be implemented far from its birthplace in Austria. Advantages of CLT like quick installation, resistance to earthquakes, and strong insulating properties have led Japan to import it, as well as open their own CLT production lines. Our research explores the properties of CLT, trends in the trade flows of CLT and the major component of it (softwood lumber), and the positive and negative environmental impacts of manufacturing and using CLT. We reviewed studies on CLT manufacturers, life cycle assessments from various sources, and our own analysis of trade data from 2010 to 2019. Information on how and why Japan might use EU-produced CLT is limited, but we did find that the EU exports to Japan because they have the largest manufacturers and until Japanese production increases, trade is economically advantageous--for both softwood lumber and CLT. The environmental impact of EU-manufactured CLT is greater than domestically-produced CLT; though it has a higher price per panel with shipping cost included, Japanese CLT has 40% less global warming potential than CLT manufactured in Austria and shipped to Japan. This all points to the conclusion that to gain the advantages of CLT construction efficiency and carbon storage, domestic manufacture must expand in Japan.

Seed dispersal is an important component in the lifecycle of plants and aids in establishment of successive generations. Flowering plants have developed multiple ways of dispersing their progeny, including via wind, a strategy known as anemochory. In this presentation, I evaluate and compare wind dispersal potential of ecologically dominant grasses of the tropical savannas of Venezuela, Cerrado region in Brazil, and Serengeti region in Tanzania. Due to increased canopy cover in regions of the Cerrado and Venezuelan savannah relative to the Serengeti, I predict that conditions in the Serengeti would favor wind dispersal. Dispersal structures, known as diaspores, were sampled from specimens obtained from various herbaria. I measured falling velocity as a proxy for wind dispersal ability. I dropped diaspores from a chute and recorded them on high-speed video, which I analyzed to determine the speed of the falling specimen. My data analysis so far has consisted of obtaining and comparing average falling velocity for communities. Contrary to my original prediction, preliminary data suggest that wind dispersal is favored in the Cerrado. This may be due in part to the relative abundance of megafauna in the Serengeti, which would allow for seed dispersal via animal adhesion (epizoochory) or consumption (endozoochory). Diaspores using these dispersal mechanisms may not be as likely to have low falling velocities associated with anemochory. To further evaluate epizoochorous and endozoochorous potential, I am currently analyzing surface roughness using photographs of dispersal units.

The Serrasalmidae are a family of Neotropical freshwater fishes that includes carnivorous piranhas as well as their herbivorous relatives, the pacus. Pacu diets consist of leaves, stems, fruits, seeds, and algae, as well as insects, benthic invertebrates, plankton. Likewise, some piranha species are actually more omnivorous than carnivorous, feeding on fruits and seeds in particular and only to a lesser degree the fins and scales of other fishes. These diverse prey materials appear concomitant with diverse jaws and dentitions in both pacus and piranhas, suggesting that some species are ecomorphologically specialized for feeding on certain prey. We investigated how the pattern and tempo of feeding morphological specialization in herbivorous serrasalmids reflects the ecological diversity of their food resources. Pacu and piranha species were first categorized as either algivores, frugivores, folivores, phytophages, planktivores, or omnivores based on a meta-analysis of published gut content data. We used computed tomography (CT) scanning and morphometrics to describe the primary morphological axes of jaw and dental variation and any correlates these phenotypes may have with each species’ primary prey. We found significant differences in the occlusional offset, mechanical advantage, size and shape of the lower jaw among different diet guilds. Phytophages tended to have scissor-like dental occlusion, resembling piranhas more than other pacus. We also found significant differences in the rate of morphological evolution among different diet guilds, notably folivores had morphological rates over 40 times faster than that of planktivores, suggesting different selective regimes acting on each dietary guild.

Many widespread species show morphological variation across the unique habitats and climates they inhabit. For reptiles these morphological adaptations such as limb length or body depth are often correlated with habitat use and substrate types. Additionally, body size trends and the degree of pigmentation of reptiles, driven by thermoregulatory requirements, can correspond with the elevation and climate of populations. The blue ventral coloration of Western Fence Lizards (Sceloporus occidentalis) is a social signaling device and can also be a byproduct of increased melanism in response to thermally challenging environments. I used handheld and photo analysis methods to obtain head, body, and limb measurements in addition to quantifying belly and throat coloration from S. occidentalis in Washington State at a high elevation creek canyon population, a low elevation forest population, and a coastal beach population. I found that high elevation creek canyon lizards used rock perches 69% of the time, low elevation forest lizards used trees 67% of the time, and beach lizards perched on driftwood 97% of the time. Given this distinct substrate use, my morphological data suggests adaptations between populations. Rock lizards had the longest front fore-limbs which could result in increased running speed to optimally navigate their open rocky habitat. Forest lizards had the shortest front fore-limbs possibly due to reduced running reliance, as they specialized in arboreal perches. Driftwood lizards had the skinniest body condition that could optimize them for cracks in driftwood logs they relied on. Beach lizards had bluer and darker bellies than high elevation lizards, and bluer throat patches than the other two sites. My study suggests morphological and signalling adaptations among populations of S. occidentalis at the species’ geographic extreme, and demonstrates how habitat and climate selection pressures create intraspecific variation between populations of widespread species.

Trait-based plant ecology can serve as a means to better understand shifts in ecological strategies within plant communities, and how that affects greater ecosystem processes, such as productivity, before, during, and after a period of major climate change. Apart from modern anthropogenic activity regarding greenhouse gases, the most recent major global warming event was the Middle Miocene Climatic Optimum (MMCO). 17 14 million years ago, this event was a short aberration to a long-term cooling trend that lasted over the last 53 million years, with global temperature averages during the MMCO estimated to be about 8°C warmer than preindustrial averages. Through statistical analysis of leaf functional trait measurements such as leaf area, leaf perimeter, tooth count, and petiole width, we seek to help document an example of how global warming affected vegetation in Earth’s past by comparing changes in leaf traits across the MMCO to modern leaves. While studying Miocene fossil leaves, we are creating a modern leaf database to better interpret trait trends analyzed from samples. This is building off of a previous study’s global dataset to create a model that can be used as an analog for categorizing fossil plant assemblages into different vegetation types using functional trait distributions, as well as assist in trait trend interpretation. At this point in time, we have analyzed enough modern samples to be prepared to interpret trait trends preserved in MMCO leaf fossils. Our objective during the 2021-2022 school year will be to collect enough MMCO trait trend data to make stronger predictions about how modern plant communities will be affected by climate change.

Friedreich's ataxia (FRDA) is an extremely destructive neurodegenerative mitochondrial disease with no cure to date. The disease is characterized by mutations in the FXN gene, resulting in a deficiency of functional frataxin protein. These reduced levels of frataxin protein cause multitudes of metabolic problems, including oxidative stress, disruption in iron-sulfur cluster synthesis, and iron overload in mitochondria. Recently, it has been discovered that hypoxia can rescue frataxin deficiency in various types of model organisms, including yeast, cultured human cells, nematodes, and mice. However, despite frataxin and oxygen’s integral relationship in mitochondrial function, the exact genetic pathways by which they interact remain elusive. I aim to bridge this gap by using yeast homolog and studying its oxygen dependence. YFH1 is the yeast frataxin homolog that can mimic FRDA pathology. I first created a yeast model of ∆yfh1. I am currently in the process of creating synthetic lethals and rescues of ∆yfh1 by mating it with previously identified yeast knockout strains that are known to show hypoxic resistance. After I obtain these double mutants, I plan to screen them for oxygen dependence by subjecting them under hypoxia, normoxia, and hyperoxia. Finally, I will replica plate my experiments in order to confirm the double mutants. Because ∆yfh1 is known to grow better in hypoxia, genes that create synthetic lethals in hypoxia with ∆yfh1 will most likely be the genes involved in genetic pathways of hypoxic rescue of frataxin deficiency. This will not only streamline the process of searching for the genetic basis of the disease but also serve as a platform for novel therapy to treat FRDA at its biochemical basis.

Acute respiratory distress syndrome (ARDS) is a significant cause of morbidity and mortality in older people. ARDS is initially mediated by an acute lung injury (ALI) response. Studies are needed to investigate why aging increases the risk for more severe ALI and complications assoicated with ALI. Animal models are useful for these types of investigations but most studies use young animals and therefore do not replicate an aging environment and fail to provide valid translational information. The purpose of this pilot study was to determine the pulmonary response and serum cytokine levels in old mice exposed to lipopolysaccharide (LPS), designed to induce ALI. Twenty C57BL/6 mice, 22 months of age, were exposed to 800 ng LPS in 50 ul of saline or saline alone by endotracheal instillation. Two days later, mice were euthanized and serum, lung and other tissues were collected. Serum was tested by ELISA for inflammatory cytokines TNFalpha and IL-6. Lungs were formalin fixed for H and E staining, and slides were read by a veterinary pathologist. Serum TNFalpha and IL-6 were both significantly increased in LPS treated mice compared to baseline and saline controls. Lung pathology consisted of an acute response of proteinaceous exudate flooding alveolar spaces, inflammatory cells within interstitial and alveolar spaces, and inflammatory cells surrounding and within small blood vessels. Additional studies are needed to confirm the utility of the model but this preliminary observation suggests that LPS-induced ALI in old mice might enable more valid investigations into pathogenesis and interventions associated with ARDS and respiratory afflictions caused by SARS-Co-V2 and related virus infections in older people.

Various fatal and debilitating genetic diseases are caused by mitochondrial dysfunction. To study mitochondrial diseases in humans, the Kaeberlein Lab uses NDUFS4-KO mice as a model of the human mitochondrial disease Leigh Syndrome. These mice have a non-functioning protein in their energy-producing oxidative phosphorylation process. We previously observed an increase in total iron in livers of NDUFS4-KO mice, which can damage cells by producing reactive oxygen species. Thus, we hypothesized a low-iron diet may alleviate the effects of the mitochondrial disease. My project aimed to study the molecular consequences of a low-iron diet in NDUFS4-KO mice by quantifying mRNA transcript levels and protein expression of genes involved in iron uptake, storage, or efflux, and comparing these levels between wild-type (WT) and NDUFS4-KO mice fed a normal or low-iron diet. First, I purified mRNA through cell lysis from 35-day old mice liver samples and used the mRNA to perform a one-step Quantitative Reverse-Transcriptase Polymerase Chain Reaction (qRT-PCR). Next, to quantify protein levels, I performed western blot analysis in collected protein extracts. I observed an increase protein expression and mRNA transcript levels of iron-uptake proteins such as TfR1 in both WT and NDUFS4-KO low-iron diet mice compared both control groups. This suggests iron levels were reduced to safer levels, supporting my hypothesis. Furthermore, when analyzing the expression of genes which respond to iron overload, such as ferritin, I observed a decrease in the low-iron diet NDUFS4-KO mice compared to control diet NDUFS4-KO mice. This observation shows that low iron diet contributes to a reduction in excess iron. My data may illuminate the involvement of iron in mitochondrial diseases as well as support further research into the consumption of low-iron containing foods, and eventually lead to the development of therapeutic drugs to treat humans who suffer from such ailments.

Immigrant and refugee communities are disproportionately impacted by COVID-19 due to pre-existing social and health disparities. In King County, COVID-19 incidence among Black individuals is 2.8-times higher than White individuals. In addition, communities with limited English proficiency have elevated rates of hospitalization particularly in Washington state. King County testing data has not been disaggregated by racial groups, limiting our knowledge on community testing needs. To better understand these issues, our team has collaborated with the Somali Health Board (SHB) to explore the barriers to COVID-19 testing within the King County Somali Community, where approximately 30,000 Somali immigrants reside. We administered anonymous surveys to Somali and non-Somali participants aged ≥18 (n=540) at testing fairs in South King County and recruited through community outreach. Survey data were used to quantitatively determine prevalence and correlates of timely COVID-19 testing within the King County Somali Community (defined as testing within 2 days of symptom onset). We conducted in-depth interviews with healthcare workers (n=5) and policymakers (n=5) to qualitatively explore the barriers and facilitators of testing in the community. We hosted two virtual focus group discussions -- one female-identifying group (n=10) and one male identifying group (n=10) -- with members from the King County Somali community to gather personal experiences of COVID-19 testing barriers and concerns. Our preliminary results suggest that there is a trend towards longer time from symptom onset to test for Somali respondents and that Somali respondents face various barriers to testing such as distrust, misinformation, stigma, language barriers, and transportation. This work is critical to help identify Somali community barriers to COVID-19 testing and how they can be adequately mitigated to improve access and promote equity in King County’s pandemic response.

According to the 1991-2015 Combined National Youth Behavioral Risk Surveys, Native Hawaiian/Pacific Islander adolescents had rates of attempted suicide two times higher than non-Hispanic Whites. However, there is a great lack of research and resources dedicated to Pacific Islander mental health. This literature review seeks to understand the unique experiences of Pacific Islanders in regards to their mental health. I reviewed 10 research articles concerning mental health in the Pacific Islander community, with a focus on adolescence and emerging adulthood since this is a critical developmental period that impacts the lifetime health outcomes of a population. These studies range in focus from documenting personal experiences to general disparities that impact this population. In the literature, I found that Pacific Islander youth experienced higher rates of mental health issues such as depression, anxiety and psychological distress in comparison to non-Hispanic whites and other minority groups like Hispanics in the United State. These findings signal that future research should focus on identifying and better understanding the risk and protective factors that impact mental health outcomes in Pacific Islander communities. This literature review helps summarize the small existing literature, identify gaps in research about Pacific Islander mental health, and inform future research questions.

The COVID-19 pandemic has highlighted the importance of understanding indirect routes of transmission for infectious microorganisms and how we can implement barriers to prevent it. As we have observed with SARS-CoV-2, a virus’s ability to survive on surfaces plays a significant role in its ability to spread via fomites and surfaces. Surrogate viruses such as pseudomonas bacteriophages phi-6 and MS2 coliphages are common surrogate viruses for enveloped and non-enveloped viral pathogens such as coronaviruses and norovirus, respectively. Our objective was to determine 1) how long phi-6 and MS 2 are viable on surfaces as a result of different temperatures and relative humidity and 2) the efficacy of HOBr and HOCl disinfection to inactive these viruses on surfaces. Phage dried on stainless steel were incubated at various temperature and relative humidity conditions and sampled over time to determine the viral die-off rate. Separately, dried phages were treated with various concentrations of HOCl or HOBr to evaluate the disinfection capabilities of these solutions. Viral viability and quantification were determined using plaque assays. We found that phi-6 and MS2 die-off at much higher rates with increasing humidity and temperature. HOBr and HOCl treated phages are reduced over 6-logs at 50ppm and 5 minutes contact time with HOCl and HOBr. These results indicate that these surrogate phages and their respective pathogens are viable long enough to be a public health concern and that hypohalous agents are promising compounds for future surface disinfection.

 Millions abroad and at home have been devastated by the COVID-19 pandemic. The worldwide case total surpasses 110 million with a brutal death toll of 0.5 million in the US alone (nearly 2.5 million worldwide). Comprehensive characterization of SARS-CoV-2 and its impact on patient immune systems remains under-analyzed but is critically needed for the development of COVID-19 therapies. Our study presents an integrated analysis of patient clinical measurements, immune cells and plasma multi-omics of 139 COVID-19 patients. This cohort represents the entire spectrum of disease severity (as quantified via WHO) with longitudinal blood draws collected during the first week of infection following clinical diagnosis. We identify a major immunological shift between patients of mild and moderate disease, at which point elevated inflammatory signaling is accompanied by the loss of specific metabolite classes and processes. These metabolites include amino acids and lipids that may be indicative of nutrient depletion. This stressed plasma environment found in patients with moderate or severe disease is accompanied by the onset of multiple uncanonical immune cell phenotypes. These phenotypes include proliferative-exhaustive T cells, cytotoxic CD4+ T cells and dysfunctional monocytes; the presence of these unusual subtypes are amplified by increasing disease severity. Further, we condensed over 120,000 immunological features into a single axis to capture the ways in which different immune cell classes coordinate with each other in response to SARS-CoV-2 infection. This immune-response axis independently aligns with the major plasma composition changes, clinical metrics (including blood clotting), and with the sharp transition between mild and moderate COVID-19 patients. Our study offers deep immunophenotyping of COVID-19 patients that, through integration of multi-omic analyses, suggests that moderate disease may provide the most effective setting for therapeutic intervention.

Polymers are commonly seen in our daily lives. Proteins and plastics are both familiar classes of polymeric materials whose utility is heavily relied upon. There are different architectures of polymers, for instance, linear and cyclic, each of which has unique properties. For example, cyclic polymers have a lower viscosity, smaller hydrodynamic volume, and a unique topology as an endless circle. In this project, we are investigating and improving a privileged method to approach cyclic polymers, Ring Expansion-Metathesis Polymerization (REMP), which grows the polymer chain while cyclizing it, using a Ruthenium-based (Ru) system. The goal of the research is to solve the recent major challenge of synthesizing cyclic polymers in a controlled fashion, through systematically modifying the structure of Ru-based initiators. My goal in the research project is to synthesize a precursor ligand, the subsequent initiator, and the monomers(commonly strained alkenes, norbornene). Eventually using the monomers to conduct polymerization reactions and analyze their properties and characteristics with spectroscopic instruments. Preliminary results of this research suggest we can make cyclic polymers that are more evenly distributed in size and weight. Since polymers have played an important role in people’s everyday life, improving the methodology through having better control on making cyclic polymers can make a big contribution to applications in the aspects of biomedicine and energy for our society. For example, cyclic polymers could generate biotherapeutics for the field of medicine; they could also serve as well-behaved and new types of conducting materials for the field of semiconductor.

Current research and development of robotic arms aims to increase both functionality and versatility. In the agriculture industry autonomous harvesting machines have the potential to be cost effective tools that efficiently pick crops, and robotic arms are a key component of that process. The agricultural robotics market was valued at $7.4 billion in 2020. Robotic arms available are typically designed to pick up one specific object. The market lacks solutions that can harvest a wide variety of crops quickly and carefully. The goal of this research is to develop an adaptable and robust grasping mechanism to attach to robotic arms for harvesting crops from a prototype developed for prostheses. This design adapts in position in response to the object geometry to reduce pressure on the object and requires less time to position the arm. Reducing pressure is a key metric in this study because of the fragile nature of many crops. Utilization of this mechanism reduces articulation time because it can adapt to the shape of the object being grasped at any orientation. My work in the lab has been to develop testing methods to prove these theories, both in simulation and through printing my own prototypes and performing physical tests. Preliminary virtual models and prototype tests consist of repeated grasp tests on a standard set of different grasp test objects including plastic fruits, cleaning supplies, and children’s toys. The objects are grasped repeatedly with and without the linkage mechanism attached. Results show that the mechanisms are adaptable and provide more contact area with the grasped object, reducing point pressure and requiring less articulation of the robotic arm. Further testing will apply the mechanisms in an agriculture setting and include prototyping with different materials and improved design.

Biological organisms are capable of generating inorganic materials to fulfil their needs in a process called biomineralization, and have been shown to exhibit control over the properties, such as size or shape, of the materials. Biomineralization occurs at mild conditions, which has generated a growing interest in replicating this process in a lab environment and developing methods that would allow researchers to apply this technique of biomimicry to the synthesis of inorganic materials that are not directly created through biomineralization. Biomimetic synthesis involves the use of biomolecules, such as proteins, DNA, or peptides, as templates or to induce mineralization. The mechanisms involved in synthesizing titanium dioxide, TiO2, using this technique of biomimicry are the specific interest of this project. Titanium dioxide is an oxide commonly found in titanium-containing ores, and has wide-spread application such as in pigments, pharmaceuticals, cosmetics, and photocatalysis. My work within this project specifically aims to understand the thermodynamics of the equilibrium equation between titanium(IV) bis(ammonium lactate)dihydroxide (TiBALDH), the preferred reagent for biomimetic titanium dioxide, and titanium dioxide. I created optimized structures of each reactant and product, and then I ran density functional theory (DFT) calculations using the computational chemistry software Gaussian to understand the energetics of each molecule. My use of these calculations to understand the energetics and mechanisms of this titanium dioxide reaction, as well as similar reactions, will help inform methods of improving the synthesis of titanium dioxide and other inorganic materials.

All-electronic approaches, such as the Single Molecule Break Junction method (SMBJ), are emerging as promising alternatives to the traditional polymerase chain reaction based DNA sequencing. However, existing work on DNA sequence identification based on conductance histograms requires hundreds or thousands of measurements to obtain accurate identification results. Previously, our team demonstrated a machine learning (ML) based sequence identification system that requires only 20-30 current spectra to achieve accurate and real-time results. Broadly speaking, my work involves: (i) designing a classifier that is relatively robust to experimental noise, (ii) development of a classification methodology that is insensitive to the choice of bias voltage during SMBJ experiments and (iii) performance validation on a wide range of DNA samples. SMBJ experiments are inherently noisy, and molecular binding is not guaranteed on every experiment. Current spectra recorded from experiments without any molecular binding can be viewed as noise. Too many “noisy spectra” can significantly distort the conductance histograms when constructed from a relatively small number of experiments, ultimately impairing the performance of the identification system. I am currently developing an iterative clustering algorithm, which can automatically filter out the noisy spectra. The performance of this algorithm will be compared to traditional statistical tests currently used by the team. On another front, I have tested our current experimental framework on a more extensive database of DNA samples. My experiments revealed that the classifier does not work too well on certain types of DNA sequences, the reasons for which are not yet fully understood. We are currently performing simulations and molecular modeling to better understand the characteristics of DNA sequences which appear to be hard to classify within our ML framework. Insights derived from these physical models should allow us to better understand the DNA conductance mechanism and utilize DNA molecules to develop next-generation nano-devices.

Gastrointestinal helminth infections are among the most common infections worldwide affecting about 1.5 billion people. Previous work shows that during infection with Trichuris muris, a mouse model of human whipworm in the large intestine, basophils, rare innate immune cells, accumulate at the site of infection and upregulate the expression of Notch receptors, part of a signaling pathway that regulates gene expression. Due to this discovery, we are investigating the importance of Notch receptor expression in basophils for the anti-helminth immune response and parasite clearance during infection. With single-cell RNA sequencing (scRNAseq) we are able to analyze the expression of individual cells to better understand immune cell response to infection. To investigate how Notch signaling in basophils impacts CD4 T cell function during infection, we performed scRNAseq on CD4 T cells from the intestine of naive and T. muris infected wild-type mice and mice without Notch signaling specifically in basophils. Using this approach, for the first time, we have characterized the gene expression profile of CD4 T cells at the site of infection, allowing us to identify different CD4 T cell subpopulations and their differential gene expression. This will provide insight into how T. muris infection impacts CD4 T cell gene expression and function, and the importance of Notch signaling in basophils for promoting T cell function during infection. Ongoing work is addressing how CD4 T cells and basophils interact in the large intestine, how the highly regulated environment impacts the development of the CD4 T cell response and the T cell receptor repertoire in T. muris infection, and the importance of basophil Notch signaling for this process. A better understanding of the response to helminth infection and manipulation of Notch signaling-dependent cellular responses can lead to the discovery of novel treatments for helminth infection and allergic diseases.

Postsurgical acute pain hinders children’s recovery from major surgery. Due to enhanced recovery after surgery (ERAS) approaches, patients are now discharged from the hospital sooner, and are managing more of their postsurgical recovery and pain at home. It is estimated that 80% of children undergoing major surgery experience moderate to severe pain two weeks post-surgery. Around 20% go on to develop chronic pain, which affects their long-term health related quality of life. There is currently no method for identifying patients prior to discharge who are at risk for poor acute recovery. This study aimed to determine if a patient’s functional ability as measured by the validated Youth Acute Pain Functional Ability Questionnaire (YAPFAQ) during hospitalization can predict pain and recovery at two-weeks post-surgery. We also aimed to compare the predictive ability of YAPFAQ to hospital pain intensity numerical rating score (PI-NRS) self-report. Adolescents undergoing major musculoskeletal surgery (N=119) completed YAPFAQ daily for up to three days following surgery, and questionnaires assessing health-related quality of life and pain intensity at two-week follow-up. Regression analyses showed that mean YAPFAQ score were significantly associated with both pain intensity and health-related quality of life at two-weeks post-surgery. In comparison, PI-NRS was significantly associated with pain intensity at two weeks, but not with health-related quality of life. The rate of improvement of both YAPFAQ and pain intensity score were not associated with two-week outcomes. YAPFAQ should be considered as a possible tool to alert providers of pediatric patients at risk for poor recovery at home following musculoskeletal surgery.

Knee osteoarthritis (OA) is a chronic condition that causes pain and disability in older adults. Currently, there are no curative treatments that reverse knee OA. However, exercise has been demonstrated to slow the progression of knee OA, reduce pain, and improve physical functioning. The mechanisms through which exercise improves pain in this population are unclear. Prior research in healthy adults suggests that physical activity, including acute bouts of exercise, is associated with improvements in central pain processing. We wanted to explore the relationships of free-living physical activity with somatosensory function and the acute effects of walking exercise in older adults with knee OA. Physical activity was measured with a thigh-mounted accelerometer worn for 1 week. Participants underwent pain pressure threshold (PPT) testing (algometer placed 2cm proximal to the superior edge of the patella) before and immediately after walking for 6-minutes at a fast pace. Participants (N=46) had a mean age of 73.5 (SD=6.3) years, 80.4% were women, and 17.4% self-identified as racial/ethnic minority. Mean pre-exercise PPT was significantly higher in men (6.6±1.9kg) than in women (4.7±2.0kg, P=0.01). There were no relationships between accelerometer measured physical activity and PPT in men or women (p>0.05 for all comparisons). For example, the correlation between average daily step count and pre-exercise PPT was -0.08 in women. When comparing PPT before versus after walking 6 minutes, women exhibited exercise-induced hypoalgesia (pre-post within person mean difference=-0.35kg, P=0.01), but this effect was not observed in men (mean difference=0.23kg, P=0.65). Preliminary results suggest that moderate-to-vigorous walking exercise can induce hypoalgesia in older women with knee OA, but free-living walking and other measures of physical activity were not associated with PPT. In the future, we plan to enroll additional participants and examine changes in PPT and other measures of somatosensory function after a multicomponent exercise intervention.

Approximately 90% of women in the United States report physical or emotional changes prior to and during their period. These changes can include symptoms such as fatigue, cramps, reduced concentration and memory, sensitivity to noise and light, sadness, anxiety, irritability, mood swings, and sleeping too much or not enough. In the Fall Quarter of 2020, we collected sleep, mood, and menstruation data from 19 female university students over the course of 2 months. Participants wore Actiwatches to track sleep, light exposure, and activity. In addition, participants answered daily and one-time surveys about sleep, mood, and menstruation. We hypothesized that mood scores on menstruating days would be lower than scores on non-menstruating days. We analyzed differences in mean mood scores on menstruating days versus non-menstruating days. This mood score was on a scale from one to seven, with one indicating poor mood and seven indicating excellent mood. Since subjects reported significantly lower mood scores on menstruating days than on non-menstruating days, we aim to expand on research to uncover which variables impacted mood specifically. The t-test compared average scores for menstruating and non-menstruating per participant to allow us to compare results within and across all subjects. To test for other variables that may have contributed to lower mood, we will also examine how mood scores varied with participant birth control usage, activity, and natural light exposure. We hypothesize that additional variables such as natural light exposure and activity may have contributed to the statistically significant difference between mood reported on menstruating vs. non-menstruating days. Our work is important because while menstruation is extremely common, research on variables that impact mood during menstruation is often inconclusive or minimized by stigma.

Cancer is the second leading cause of death in the United States. Research shows that vulnerable populations, including low-income, uninsured, and racial and ethnic minority groups, disproportionately experience negative cancer outcomes. In Washington State, the Breast, Cervical, and Colon Health Program (BCCHP) aims to reduce cancer health disparities by providing free cancer screening to residents with low incomes or who either lack insurance or have a high deductible plan. However, clinics face challenges to enrolling eligible participants into BCCHP. The purpose of this ongoing study is to identify barriers and facilitators in the BCCHP enrollment workflow in order to optimize the BCCHP enrollment process, with the goal of increasing access to cancer screening among marginalized communities. In this qualitative study, we identified clinics within an urban health system and conducted interviews with key clinic staff involved in the BCCHP enrollment process. Key informants include the clinic’s BCCHP enrollment coordinator as well as other staff such as providers and medical assistants who participate in enrollment. We then analyzed interview transcripts using content analysis to determine characteristics of clinics associated with high and low performance in BCCHP enrollment. These results will inform preliminary recommendations to Public Health—Seattle & King County for overcoming workflow barriers and optimizing enrollment of eligible participants.

In this study, we investigate the relationship between alcohol consumption and sleep efficiency among a sample of University of Washington students. Alcohol consumption has been found to activate the hypothalamic-pituitary-adrenal axis, leading to an increase in cortisol levels. Elevated levels of cortisol are known to have adverse effects on sleep patterns. If the consumption of alcohol leads to elevated levels of cortisol which thus negatively affects sleep, we can predict that individuals who consume alcohol regularly will exhibit poorer sleep quality than individuals who do not consume alcohol at all. We hypothesize that individuals who consume alcohol regularly will exhibit poorer sleep quality than individuals who do not consume alcohol at all. To test this hypothesis we analyzed daily sleep data from 20 students collected from Actiwatches worn over two months. As a measure of sleep quality, we analyzed variation in sleep efficiency, defined as the percentage of time spent asleep while in bed. Participants reported alcohol usage in anonymous one-time surveys. We compared participants who drank on a weekly basis (between one to four or more times a week) versus participants who did not drink at all. Average sleep efficiency was calculated by the percentage of time spent asleep which gives an overall sense of how well an individual slept. The higher the percentage the higher the quality of sleep. Average sleep efficiency was significantly greater in participants who indicated they did not drink alcohol in comparison to those who did (85.16% vs. 73.02%, p = 0.01). It must be noted that the correlation between participants who do not drink and have higher average sleep efficiency cannot be stated as a causative relationship. Further research is suggested to determine whether weekly alcohol consumption directly affects sleep efficiency and if so, by what mechanisms.

Autism spectrum disorder (ASD) is a neurodevelopmental disorder characterized by deficits in social communication, restricted interests, and repetitive behaviors. Symptoms can vary widely in type and severity between individuals, but approximately 23% of children show clinical levels of aggression. Considering evidence for other racial disparities in healthcare, race/ethnicity is also a factor of interest in ASD research on disparities in diagnosis rates and severity. Previous studies have found ASD symptom severity, but not race, to be a significant predictor of physical aggression, though they investigated race alone and not as a moderator. This project aims to look at the relationship between measures of aggression and symptom severity, and the moderating effect of race/ethnicity on that relationship. 145 participants between the ages of 8-17 years with an autism diagnosis from an NIH-funded study were included in the analysis. Symptom severity was determined based on clinician observation of and interaction with the participant using the Autism Diagnostic Observation Schedule Calibrated Severity Score (ADOS CSS). Parents of the participants completed the Child Behavior Checklist (CBCL), rating their child’s level of emotional/behavioral problems. Questions were grouped together to yield scores in different “syndrome scale” categories, including aggressive behaviors. We will use multiple linear regressions to do predictive analysis on the relationships between symptom severity, aggression, and race. We expect that children with greater ASD symptom severity will display more aggressive behaviors. We also predict that there will be a moderating effect of race/ethnicity, with this relationship being stronger in white, non-Hispanic children than others. This study will provide insight into the diversity of ASD presentation, and it may help illuminate (biological or socially constructed) differences in ASD presentation between races/ethnicities and further efforts for equitable treatment.

 Cannabis sativa is one of the most widely used drugs in the world. In humans, Cannabis sativa is commonly used to alleviate anxiety and pain, among other things, in medical and recreational contexts. In mice, intraperitoneal (i.p.) injections of its primary psychoactive compound, Δ9-tetrahydrocannabinol (THC) produce a characteristic triad of behavioral responses consisting of hypolocomotion, hypothermia, and analgesia. However, injections of THC do not accurately represent how humans typically administer THC, which primarily consists of inhalation and oral consumption. To better model a typical route of administration used by humans, we developed a voluntary oral consumption paradigm in mice whereby THC is formulated in gelatin. Following habituation, mice were given ad libitum access to THC gelatin for 2 hours. We measured the triad behaviors immediately following consumption to determine whether voluntary oral consumption of THC-gelatin using this paradigm induces acute cannabimimetic behaviors. Due to the slow pharmacokinetic activity of orally consumed THC, we measured triad responses immediately, 1 hour, and 2 hours after consumption. To compare our relative THC-gelatin-induced cannabimimetic behaviors to published data, we replicated the triad experiment and demonstrated our ability to obtain dose-dependent triad responses by using i.p. injections. At high concentrations (4mg/15mL) of THC-gelatin, cannabimimetic behavioral responses matched those of mice treated with low-dose (3 mg/kg) of THC i.p. injections. From these initial studies we conclude that development of THC-gelatin formulation triggers characteristic cannabimimetic behavioral effects in mice. These results suggests that classical THC and cannabinoid-dependent behaviors in mice can feasibly be studied with a more translational model (Funded by DA051558). Optimizing an oral administration model of cannabinoids in mice will enable future research on the pharmacology of oral cannabinoid therapeutics. 

The utilization of crowdfunding websites has grown in popularity, particularly in the arena of medical crowdfunding to cover costs due to inadequate health insurance coverage and lack of social safety-net systems in place. Research on medical crowdfunding in global health contexts is not robust, and knowledge about its impacts on health outcomes is limited. What is known is that unmet health disparities are driving the need for medical crowdfunding, and crowdfunders face numerous disparities that impact campaign outcomes, such as racial or gendered biases among campaign donors. Using descriptive statistics and content analysis of viral medical campaign data from the GoFundMe site, this research helps create an archetype for the most successful campaigns and examine social ideas of deservingness related to race, gender, and severity of the disease. The results show stark disparities in medical crowdfunding outcomes based on race and gender and a lack of diverse representation among highly successful crowdfunding campaigns, particularly in the case of Black women. This mixed methods research analysis looks to create further discussion on how technology may aid in creating health inequities for already marginalized and traditionally disenfranchised populations.

Kenya has the fourth-largest HIV epidemic globally, with adolescent girls and young women (AGYW), ages 15-24, holding the highest number of HIV infections. Antiretroviral-based daily oral pre-exposure prophylaxis (PrEP) for HIV prevention reduces HIV acquisition risk by over 95%. Kenya is a leader for PrEP delivery in Africa and efforts are ongoing to increase PrEP accessibility; however, most approaches include expanding access within health facility-based settings. Many AGYW at-risk for HIV in Kenya access contraception at commercial pharmacies without interfacing with public sector health facilities. Commercial pharmacies could increase options for reaching AGYW at-risk of HIV with PrEP services. We piloted nurse-facilitated PrEP provision at 3 commercial pharmacies in Kisumu, Kenya. PrEP-prescribing nurses counseled on and offered PrEP to all AGYW purchasing contraception per national guidelines. AGYW who accepted PrEP were provided with a free one-month supply of PrEP pills. We evaluated acceptance among all AGYW offered PrEP; at 30 days after acceptance, we evaluated PrEP use initiation, and plans for continuation among those who accepted PrEP. We enrolled AGYW until 200 AGYW had accepted PrEP . We will use a concurrent triangulation mixed methods study design. Among a subset of 40 AGYW who initially accepted PrEP pills, we will conduct qualitative in-depth interviews (IDIs) to examine user experience of pharmacy-delivered PrEP. We anticipate that AGYW will report positive user experiences with pharmacy-based PrEP and that offering PrEP in this setting will increase accessibility to HIV prevention treatment options for AGYW. Quantitative data analysis will compare socio-demographic and behavioral characteristics between AGYW who do and do not accept PrEP. Data from this study will help determine if pharmacy-based PrEP convenience is feasible as it could increase PrEP availability and work as a model for future implementation.

There is growing use of technology-enabled contact tracing, the process of identifying potentially infected COVID-19 patients by notifying all recent contacts of an infected person. Governments, technology companies, and research groups alike have been working towards releasing smartphone apps, using wifi-connected devices, and distributing wearable technology to automatically track "close contacts" and identify prior contacts in the event an individual tests positive. However, there has been significant public discussion about the tensions between effective technology-based contact tracing and the privacy of individuals. To inform this discussion, we present the results of seven months of online surveys focused on contact tracing and privacy, each with 100 participants. Our first surveys were on April 1 and 3, before the first peak of the virus in the US, and we continued to conduct the surveys weekly for 10 weeks (through June), and then fortnightly through November, adding topical questions to reflect current discussions about contact tracing and COVID-19. Our results present the diversity of public opinion and can inform policy makers, technologists, researchers, and public health experts on whether and how to leverage technology to reduce the spread of COVID-19, while considering potential privacy concerns. 

Biotechnology and DNA sequencing have become commonplace in their integration into a multitude of fields. Forensics has employed DNA sequencing in order to identify crime scene victims. Direct to consumer (DTC) DNA testing has allowed consumers to determine nuances regarding their ancestry and health. Medicine has employed sequencing and wet lab systems in order to further drug development and create targeted treatments. Previous literature has shown the potential for DNA sequencing and biotechnology systems to host unique cybersecurity vulnerabilities rooting in their functionalities. For example, researchers have shown the potential for misuse in the genetic genealogy database GedMatch. Often used by law enforcement, databases such as GedMatch allow individuals to perform relationship and family tracking, using DNA sequencing results to match potential relatives. Researchers have shown that this database and its underlying algorithms could be capitalized on by an adversary to spoof their own identity or create false relationships. In coming years, we expect genetic inference models such as ancestry analysis and DNA Phenotyping, the extrapolation of an individual’s physical features based on their genetic information, to become commonplace in the aforementioned fields amongst others. Given the potency for issues that researchers have found in other models, we look to advance the body of knowledge surrounding the validity and robustness of these genetic inference models being used. We perform an overview of a series of models that determine traits such as ancestry and physical features of individuals from DNA and explore how these models could be exploited or tricked into returning incorrect results. Finally, we discuss the implications of these vulnerabilities, both for the biotechnology space and cyber-physical systems as a whole.

Wearable medical devices are now increasingly connected to the Internet, enabling improved patient outcomes and quality of care. However, this increased connectivity has also increased the attack surfaces, making the device and their data vulnerable to cyberattacks. Because wearable medical devices transmit private and sensitive medical information, it is critical to secure access to these devices. As evidenced by recent ransomware attacks on hospitals, the ability to remotely access and manipulate a medical device poses a direct threat to patient health whether in a hospital or at home. In this research, our goal is to enhance the security of wearable medical devices by using patients’ electrocardiogram (ECG) signals to authenticate devices. Specifically, we propose a deep learning approach for classifying a patient’s electrocardiogram (ECG) as a biometric for authentication. The deep learning approach allows a device to learn its user’s ECG in order to authenticate them against untrusted entities. Our research also extends the use of electrocardiogram signals for authentication by accounting for patient’s stress levels and varying emotional states, as the accuracy of ECG authentication may be affected by these variables. Our experimentation involves testing different parts of electrocardiogram signals using deep learning models and determining the most accurate method of classifying the end user’s device. The proposed research is useful for studying and evaluating the benefits of deep learning algorithms used in conjunction with authentication techniques in healthcare domains.

Despite widespread implementation of solar energy, there are still issues with efficiency in varying conditions. For example, photovoltaic (PV) arrays function optimally at a specific temperature and have decreasing efficiencies at higher temperatures. Other factors that also impact the power production of a PV array include the amount of direct sunlight, the distribution of incident light, and the intensity of incident light. As solar energy installations continue to increase worldwide, proper modeling of PV arrays is critical for potential asset owners and power system operators. Effective simulations of a PV array’s power production require models that effectively consider the uncertain external factors that vary by geographical region and climate. In this research project, a realistic PV cell model is developed in the programming language Python. This model explores the sensitivity of a PV cell’s power production to different external variables, including ambient temperature, solar irradiance, and other weather conditions. Additionally, this PV cell model is extensible, allowing power production from PV modules and arrays to easily be considered. This model can be seamlessly integrated with other energy asset models, including those for energy storage and flexible demand resources, allowing for complex scenarios to be simulated. To display this functionality, a cost-minimizing consumer with a behind-the-meter PV array and battery is simulated.

The study of cell morphology is important and prevalent in understanding normal and pathological conditions in the brain. Brain cells are common targets for treatment for brain diseases. Specifically, microglia – the brain’s resident immune cells – undergo a range of morphological changes in response to injury and are targets of many mitigating treatments. Image processing has been a valuable tool to assess microglial cell morphology via the analysis of microglial shape features and there continue to be additional opportunities for further investigation. Prior research has indicated a connection between features such as solidity and extent, two shape features that measure the ratio of cell areas. In this study, we examine three shape features of fluorescently labeled microglia: Euler number, extent, and solidity, in the context of ischemic injury. Ischemic injury was modeled using oxygen-glucose deprivation (OGD) in cultured whole hemisphere brain slices. Using python, images were thresholded with the Otsu threshold. Shape features were extracted from the binarized images. These shape features were analyzed based on brain region (cortex, hippocampus, thalamus), generalized treatment type (non-treated, injured, injured with treatment), and specific treatment type (OGD 0.5 hour, 1.5 hours, 3 hours, 1.5 hours with azithromycin treatment, 3 hours with superoxide dismutase treatment) and visualized using seaborn. The results verified trends in effects of injury and recovery after treatment on extent and solidity. Both findings support the expected shift from a circular shape of microglia in the injured state to more branched in the healthier state. The Otsu thresholding is limited in its accuracy, and, hence, these results provide an opportunity to optimize cell segmentation protocol for higher quality thresholded images. The results of this work have the potential to be applied to various forms of injury and cell types.

Wireless power through magnetic resonance between coils of wire has enabled a new charging paradigm in a variety of domains, from robotics to biomedical implants. As wireless power systems move from simplistic to more perfomant architectures comprising of many coils, the design complexity scales very quickly. This is due to the difficulty in simulating and modeling the magnetic fields that form the backbone of the wireless power transfer, as in the multi-coil case the computational complexity quickly exceeds the capacity of even high end servers. To enable the development of next generation wireless power devices, we developed the Mostly Printed Field Characterization System (MPFCS), a robotic scanner that collects high-fidelity, high-resolution magnetic field data. However, while the system creates useful visualizations for wireless power, it does not provide a mathematical model that would allow for the precise optimization and rigorous understanding of the fields that engineers often need. Addressing that, we present physics-driven machine learning methods that combine electromagnetic theory with data collected from the MPFCS to build simplified mathematical models for these magnetic fields. We provide, for the first time, a characterization of fields for systems that were previously too complex to analyze effectively by hand or through computation. Preliminary evaluation of the data shows that there is very little error compared to simulated values. Based on the algorithm's performance on similar problems, this suggests promising final results. This work provides a deeper understanding and design tool to build and iterate on next generation devices, leading to both accelerated prototyping and novel research directions.