Learner experiences are under-examined in environmental learning research. Our research consists of studies of experiential aspects of environmental learning by undergraduate researchers, conducted over three years, culminating in a focus on how community-engaged learning (CEL) fosters connections between social justice, ecological consciousness, and student well-being. Research questions we came to consider were: What connections are students drawing between social justice and ecological consciousness? How does engaging in community-based environmental learning affect students’ well-being? Methods such as coding, memoing, reflecting through learning diaries, whole-part-whole analysis, and group collaboration all contributed to establishing an adaptable infrastructure of undergraduate research (UGR) in experiential aspects of the course. Our findings on students’ connections between social justice and ecological consciousness revealed their thoughts about becoming advocates, or “leaning toward justice”, though they had diverse prior knowledge and experiences. Findings on the CEL experience within the large course with regard to well-being showed how students integrate environmental education with community engagement, particularly in addressing issues such as food insecurity, environmental justice, and language barriers for immigrant communities. Some key themes found were that CEL promoted personal growth through unexpected learning, connection to nature & emotional relief, and a sense of belonging in research participants’ experiences. The significance of this research has been to establish a way for undergraduate researchers to drive experiential learning research, and to find research outcomes about how learning experiences foster awareness of social and ecological justice, encouraging students to see themselves as advocates for change. 

Adolescents and young adults often experience barriers to accessing inclusive, high-quality, and youth-friendly healthcare. Despite growing attention to these disparities, few standardized tools exist to assess or encourage youth-friendly practices across healthcare settings. This project, conducted under the Adolescent Health Team at the Washington State Department of Health, asks: What criteria define a youth-friendly healthcare environment, and how can these be translated into a sustainable certification model? To answer this, we employed a mixed-methods approach. We conducted a landscape review of existing youth-focused health frameworks, analyzed qualitative feedback from community partners and youth advisory groups, and iteratively developed criteria through stakeholder engagement. Branding materials and an informational flyer were designed to enhance accessibility and understanding of the certification. A draft patient satisfaction survey was also created to capture ongoing youth experiences in certified settings. Preliminary findings highlight key themes in youth feedback, such as the importance of inclusive language, provider relatability, and confidentiality and privacy in care settings. These themes directly shaped the final set of certification criteria and informed outreach materials. This work contributes to the field by piloting a novel framework for Youth-Friendly Certification in Washington State. Findings underscore the value of youth-informed design in public health initiatives and provide a replicable model for other regions seeking to improve healthcare access and equity for young people.

Nepali migrants play a significant role in India’s workforce, facilitated by the open-border policy established under the 1950 Indo-Nepali Treaty of Peace and Friendship. However, they face numerous challenges in accessing healthcare, particularly those employed in informal sectors. This research paper examines the healthcare barriers experienced by Nepali migrants in both North and South India, including overcrowded public hospitals, legal restrictions, language barriers, and work-related health concerns. Using a literature review and qualitative exploratory research based on interviews with Nepali migrant adults aged 20-45, the study highlights how, in North India, the high concentration of Nepali migrants places additional strain on healthcare infrastructure, while seasonal migration disrupts continuity of care. In South India, key challenges include social isolation, language difficulties, and dependence on costly private healthcare. Findings reveal significant policy gaps, such as the absence of a bilateral healthcare agreement between India and Nepal and the exclusion of Nepali migrants from India’s national health insurance programs. To address these issues, this paper proposes solutions, including employer-provided health insurance, mobile clinics, language-inclusive healthcare services, and cross-border cooperation modelled on successful approaches from Thailand and Germany.

Global plastic production has already surpassed 300 million tons annually, which poses serious environmental challenges due to the limited recycling and effective management of plastic waste. Current mechanical recycling methods are not efficient, since only a small fraction of plastic waste goes through recycling processes, resulting in severe environmental degradation and pollution. In view of this, the use of bimetallic nanoparticles as catalysts is critically evaluated in the case of plastic recycling. In this Literature Review, I look into different metal combinations, such as ruthenium-platinum, ruthenium-nickel, and ruthenium-cobalt bimetallic catalysts. These catalysts are known to have great potential for enhancing the selectivity and efficiency of the hydrogenolysis process, hence increasing the conversion of plastic into more valuable hydrocarbons like fuels and chemicals. It intends to draw attention to various advances in chemical recycling methods that may offer sustainable solutions to the global plastic waste crisis through a critical review of the synthesis methods, catalytic mechanisms, and practical applications of these bimetallic catalysts. Further work on the unique properties of the bimetallic nanoparticles provides insight into their catalytic role in enhancing efficient C-C bond cleavage in plastic, ultimately providing higher yields of desirable products and reduced formation of unwanted byproducts.

Understanding and predicting changes in primary productivity depend on both upper ocean warming and nutrient supply from the ocean interior. Fronts, where distinct water masses converge, are hotspots for these vertical exchanges, transporting nutrients upward and supporting diverse ecosystems. These fronts create sharp gradients in temperature and salinity, generating strong vertical velocities that upwell nutrients and biomass. However, the exact dynamics of frontogenesis (the formation of fronts) remain poorly understood. Additionally, these processes occur at scales too fine to be resolved in global climate models and are only marginally captured by high-resolution ocean simulations. This underscores the need for observational studies to characterize frontogenesis and test existing theoretical frameworks. In this study, we diagnose frontal dynamics using Petterson’s frontogenesis function, which quantifies the roles of divergence and strain. Using NcCut, a GUI developed by our group, we compiled a unique dataset capturing the full life cycle of numerous ocean fronts in front-following coordinates from a state-of-the-art ocean simulation. Our results indicate that for mesoscale (~100 km) fronts, strain dominates over divergence, aligning with classical theories. In contrast, submesoscale (~10 km) fronts exhibit shorter life cycles and no clear dominant driver of frontogenesis within the Petterson framework. We also identified key limitations in conventional diagnostics and improved our analysis by masking the front from its surrounding environment before diagnosing its drivers. This enhancement provides a more accurate representation of frontogenesis dynamics. In the future, we plan to apply our method to satellite observations to study real-world ocean fronts, validate ocean models, and improve predictions of primary productivity changes. Our findings highlight the importance of refining frontogenesis diagnostics to better capture the small-scale dynamics critical to ocean biogeochemistry and climate predictions.

Pacific Oysters (Magallana gigas, previously named Crassostrea gigas) are marine bivalves that are widely cultivated in the US Pacific Northwest. A widespread range combined with high commercial interest makes the Pacific Oyster a very crucial species to study for both environmental and human health. Shellfish farms often experience major summer mortality due to multiple interacting factors that heavily impacts production and profitability. Two current key concerns are 1) the increasing severity and frequency of marine heat waves and 2) impacts of diseases (e.g., OsHV-1) that cause oyster mortality. Under current environmental stress scenarios, shellfish require capacity to withstand interacting stressors through their sophisticated innate immunity and cellular stress responses. In the face of multiple environmental stressors, it is of great interest in the aquaculture community to increase oyster stock resilience. However, it remains unclear how temperature influences survival of early life stages of oysters and whether strengthened immune system responses offer protection to thermal stress. To address this need, we conducted an immune challenge using PolyI:C (i.e., an RNA analog that mimics viral DNA to activate the oyster’s immune system) in oyster broodstock and reared their offspring until the spat stage. Oyster spat were then exposed to thermal challenges and we characterized metabolism, survival, and growth. Offspring from immune-challenged parents had higher survival under thermal stress and differences in their metabolic response to elevated temperature. This work raises additional questions about how the biological responses between thermal stress and immune response are connected and the potential to apply immune priming in oyster aquaculture. Further, it is important to understand if there are growth trade-offs associated with improved stress tolerance. Improving the general understanding of temperature affects in oysters and their interacting stressors as climate change amplifies is important and applicable to other farmed invertebrates.

Grand strategy in the U.S. has historically meant setting its eyes overseas. Defying tradition, this task report examines how major shifts in domestic policy can continue to influence international spheres while simultaneously improving the situation at home. There is growing consensus that there is instability-economic, environmental, political, security-brewing in every theater of the world; the time to exercise strength at home and collective global strength abroad is now. Through reform in economic strategy, addressing the U.S.'s role in the climate crisis, strengthening U.S. institutions to enhance political discourse and human rights, and reassessing the infrastructure of the U.S. military, the United States can reinforce its position as a global leader and acknowledge the necessity for shared power in the 21st century. Americans are finding themselves in an increasingly multipolar world state, where competitors become more capable and influential by the day. This report aims to examine the reflection of U.S. domestic policies on an international scale, while accounting for past and current actions that undermine the core values of what it promotes. When addressing the way in which a world power such as the U.S. can maintain its status as an international leader, it must first begin by addressing pivotal concerns at home and abroad, and enhancement in military infrastructure to meet the dynamic demands of the 21st century and thrive abroad. 

The Svoboda Diaries Project (SDP) is an interdisciplinary digital humanities effort dedicated to preserving and analyzing a collection of historical diaries. Written by Joseph Svoboda, a British steamship purser, these diaries span 40 years and offer firsthand insights into the daily life, healthcare practices, social networks, economic conditions, and cultural landscape of 19th century Iraq. Due to the unstructured and handwritten nature of these texts, analysis of them could benefit from computational techniques. Our research specifically addresses this challenge by extracting and analyzing references to food, medicine, symptoms, and healthcare providers, making these diaries a valuable resource for studying historical medical practices. To extract key terms from the diaries, we apply Natural Language Processing (NLP) methods,  which allow computers to interpret human language. Specifically, we use Named Entity Recognition (NER), a technique that identifies and categorizes entities or terms such as foods, medicines, illnesses, and doctors within the diaries. This type of extraction allows us to transform narrative into a format that is more amenable to analysis using automated methods. Once extracted, we visualize these relationships through network visualizations—graphical representations that illustrate connections between different entities in the text. These visualizations help us trace the circulation of medical knowledge, showing who prescribed what, which remedies were most common in the diaries, and how treatment preferences may have varied depending on provider perspectives. We aim to directly link healthcare providers with the remedies they recommended, allowing us to understand patterns of medical practice at the time. Structuring historical information into data-driven models allows us to examine cultural and economic influences on healthcare. Beyond this specific case, our research demonstrates how data science can be applied to historical texts, enabling researchers to discover patterns in historical healthcare practices across different time periods and regions.

Polymer networks, materials comprised of interconnected polymer chains, have been the subject of research interest for decades and have, particularly in recent years, found use cases in a variety of applications. Despite their broad use cases these materials are limited by their inherent tendency toward brittleness. One strategy for increasing the toughness of polymer networks is to introduce mechanochemically reactive groups in the crosslinks of a network instead of in the load-bearing primary polymer chains. Previously reported scissile crosslinkers have typically relied on strained ring structures or unusually weak covalent bonds for selective bond scission, introducing challenges such as difficult synthetic procedures and high design complexity. My collaborators at Johns Hopkins University have developed a novel, synthetically accessible crosslinker design that allows for selective mechanochemical bond scission via the replacement of a single carbon atom with silicon. They demonstrated that this scissile crosslinker doubles the toughness of a polymer network prepared by controlled polymerization. In my project I incorporated this crosslinker into a liquid resin compatible with free radical vat photopolymerization, 3D printed this new material, and mechanically characterized it through tensile testing. My work demonstrated that the same toughening effect occurs on polymer networks that are much less controlled and that this strategy for network toughening is compatible with 3D printing, which allows for the fabrication of more complex constructs. In conjunction with the expedient synthesis of this new crosslinker my project demonstrates that this approach to network toughening has the potential for large-scale applications.

The Tait graph, an undirected graph with signed edges derived from a knot diagram, is fundamental to knot theory and algebraic topology, enabling the study of knot invariants and topological properties. Despite its importance, widely-used software packages like SageMath and SnapPy lack native functionality for Tait graph construction and manipulation. Our research addresses this gap by presenting an efficient algorithm to construct the signed Tait graph and its associated dual graph from a knot's Planar Diagram Code (PD-Code). We validated our algorithm by comparing the reduced weighted Laplacian matrices of our constructed graphs with those of nearly 3,000 classified knots up to 12 crossings. Future work will extend our implementation to support additional functionalities such as Reidemeister moves, Jones polynomial calculations, and directed edge representations. By deploying our code on SageMath, we aim to provide a valuable tool for researchers in knot theory and related fields.

In modern software ecosystems, computations and operations are commonly supported using independent scalable lightweight services called microservices. Cloud computing platforms offer computational services to host small code snippets that behave like microservices in a serverless paradigm. Referred to as Function-as-a-Service (FaaS), these platforms promise reduced hosting costs, high availability, fault tolerance, and dynamic elasticity. FaaS platforms contrast with traditional cloud computing platforms where customers may overprovision resources to meet peak demand. FaaS platforms abstract infrastructure management from end users including the creation and configuration of virtual machines (VMs) and load balancing. The abstraction of compute infrastructure obfuscates the factors that influence the performance and cost of software deployments. In cloud computing, real world workload traces are rare, as the data can include sensitive customer information. Publicly available workload traces remove sensitive data effectively reducing the detail and granularity necessary for reproducing workloads to enable robust system testing. This poster presents the Serverless Event Trace (SET) Generator to support distributed reproducible multi-node testing. The SET Generator can create synthetic workload traces, replay existing public industry traces, or generate real workload traces by ingesting FaaS log files for execution using Distributed FaaSRunner, a companion tool.  Serverless function log files are ingested without requiring the use of provider-specific monitoring tools to produce event trace files to support reproducing distributed real-world workload patterns. In reproducing log file derived workload traces, we seek to minimize the time drift between expected vs. actual event invocation times using a variety of test clusters. Our work aims to precisely reproduce workloads by addressing issues such as test cluster network latency and queueing delay. With the SET Generator’s ability to generate spatially and temporally detailed event traces that reproduce real workload characteristics, our work can help developers and researchers optimize serverless deployments and platform designs for real world conditions.

Corepressors are an essential element of gene repression – complexes of proteins that keep genes off, yet poised to turn on when needed. Clarifying the mechanism of this repression is key to understanding gene regulation in all eukaryotes in diseased and non-diseased states. My project is implementing a forward genetic screen in Arabidopsis thaliana to identify and characterize proteins that bind to and regulate the conserved plant corepressor TPL. TPL is fully essential to plant development, so to visualize TPL inhibition in living plants, we created an Arabidopsis line containing a synthetic repressor, TPL fused to dCas9(dCas9-TPL), that represses RUBY, a genetic reporter that turns Arabidopsis plants dark pink. Plants with both constructs appear light pink as dCas9-TPL represses RUBY expression. Mutations in proteins needed to maintain TPL-based repression lead to dark pink plants, allowing us to identify mutants to study. Using ethyl methanesulfonate (EMS), we created a pool of seeds with random point mutations and the repressed RUBY construct. My team and I visually screened the mutated pool for pink plants showing inhibited RUBY repression and successfully identified promising homozygous mutants with unique phenotypes including infertility, shade avoidance, and irregular growth patterns. Using whole genome sequencing and computational analysis, I selected specific loci to further investigate. We are currently testing our candidate mutants' sensitivity to the plant hormone auxin, one of the best-understood TPL-regulated pathways. My next steps will be to identify the causal mutation through the following: (1) characterizing additional mutations in the same gene to compare phenotypes using available mutant libraries, (2) testing whether the candidate gene interacts with TPL using assays like yeast two-hybrid, and (3) complementing my mutants with wild-type versions of candidate genes. By uncovering new proteins, I aim to piece together more of TPL's conserved mechanism of repression. 

Cutaneous squamous cell carcinoma (cSCC) is the second most common cancer in the United States. Distant metastasis serves as the primary cause of mortality. It is therefore important to identify molecular signatures as potential therapeutic targets that contribute to metastatic phenotypes of cSCC. To profile gene expression in cSCCs, we performed RNA-seq analyses of normal skin (n = 6), primary cSCCs (n = 12), and metastatic cSCCs (n = 3). To identify differentially expressed genes, we created a hierarchical clustering heatmap of top 5,000 most variable genes across these 21 samples. This analysis identified multiple clusters of coordinately expressed genes, and we selected three clusters that showed robust upregulation or downregulation in metastatic cSCCs, compared to normal skin and primary cSCCs. Gene set enrichment analysis for each of these three clusters revealed what pathways were associated with upregulation or downregulation of the genes in each cluster. Cluster 1 includes 786 genes that were upregulated in metastatic cSCCs, and Cluster 1 was associated with mitotic cell cycle, indicating hyperproliferation of cancer cells. Cluster 2 includes 932 genes that were downregulated in metastatic cSCCs, and Cluster 2 was associated with lipid biosynthetic pathway. The downregulation of this pathway may reflect the loss of differentiated skin cells during cancer progression. Cluster 3 includes 440 genes that were also downregulated in metastatic cSCCs, and Cluster 3 was associated with extracellular matrix organization pathway. The extracellular matrix is a structural scaffold for tissues, and its dysregulation is related to tumor growth and metastasis. The sets of identified genes and pathways provide novel insights into potential biomarkers and therapeutic targets for patients with cSCC.

Premature neonates are particularly vulnerable to electrolyte and fluid imbalances due to their increased insensible fluid losses and immature kidney function. Clinicians carefully monitor and document electrolyte and fluid intake. However, research suggests that saline flushes, small volumes of sodium chloride solution administered to clear intravenous lines after medication delivery, are a source of electrolytes and fluid in the NICU that are often unaccounted for. In the first week after birth, frequent medication administration leads to multiple flushes, and the relative contribution of flushes to total sodium and chloride intake may be substantial for the smallest newborns. Particularly, sodium imbalances contribute to pathologies and have been associated with adverse health outcomes, including intraventricular hemorrhage (IVH) and all-cause mortality. Understanding the impact of saline flush administration on fluid and electrolyte balance is essential for developing evidence-based neonatal care guidelines. We hypothesize that saline flushes in the first have greater relative contributions of sodium, chloride, and total fluid intake for smaller and more premature newborns. To investigate, we are conducting a retrospective study of very preterm newborns admitted to a level III NICU in Washington state. We will statistically compare sodium, chloride, and total fluid intake before and after accounting for saline flushes, and we will descriptively analyze the amount of each in relation to gestational age and birthweight. We will additionally evaluate via univariate models how sodium intake with and without inclusion in total fluid intake correlates with serum sodium daily values. This ongoing study aims to expand the sample size to increase our ability to perform multivariate regression models to account for confounders which may bias our findings. Ultimately, results from this research can improve neonatal care guidelines, helping clinicians optimize sodium, chloride, and fluid intake. 

Sexual dimorphism, the difference in structural features between males and females, is observed in many species across vertebrates. However, even between closely related species, the differences in sexual dimorphism can be extreme. In this study, I examine the functional implications of sexual dimorphism in two mustelids, the American marten (Martes americana) and the fisher (Pekania pennanti). Martens and fishers are prime targets for comparison because despite inhabiting similar geographic ranges and consuming similar diets, fishers exhibit significant sexual dimorphism in cranial size and shape while martens do not. Thus, my goal is to assess if these characteristics exhibited by male fishers result in enhanced biting performance compared to female fishers and American martens of both sexes. My first hypothesis is that size-corrected male fisher skulls, with their more robust morphology, exhibit lower stress than female fisher skulls. In martens, I test the second hypothesis that there is no difference in stress between size-corrected male and female martens due to the lack of size and shape sexual dimorphism observed. I quantified the stress on the mandible and cranium as a proxy for biting performance. Higher stress indicates areas likely to fracture with increasing forces or continuous use, signifying lower biting performance. To model the stress caused by jaw adductor muscles, I employ finite element analysis (FEA). FEA allows me to input scans of the skulls sourced from the Burke Museum and simulate forces on the models. I then conduct t-tests on the stress of shared regions between the species and sexes. My preliminary results in fishers show males having lower cranial stress but similar mandibular stress compared to females, suggesting males and females exhibit stress in different areas of the skull when biting. This research adds to existing literature by proposing a mechanical explanation for the evolution of sexual dimorphism.

Spinal cord injury (SCI) affects millions of people around the world, often leading to severe physical, psychological, and social consequences. Understanding how the brain and spinal cord react to injury is important for finding ways to help people recover lost movement. Previous research has investigated c-Fos expression, a protein that shows when nerve cells in the spinal cord are active, as a marker of neuronal activity in response to SCI; however, further investigation is needed to identify new pathways and technologies that could aid in the recovery of SCI patients. I am investigating how c-Fos behaves in the spinal cord of rats through Steve Perlmutter’s lab, part of the Department of Neurobiology and Biophysics at the University of Washington, which focuses on developing neuroprosthetic therapies - therapeutic interventions that restore lost neural function by electrical stimulation of sensory or motor pathways. These prosthetics enhance the nervous system’s ability to promote reorganization of brain and spinal cord connections, which can support improved motor recovery in conditions like stroke, traumatic brain injury, and SCI. In this study, I am investigating how c-Fos behaves in the spinal cord of rats before and after they are injured, and how different types of stimulation affect it. I use a technique called immunofluorescence to look closely at c-Fos activity in the lumbar and cervical areas of the spine, which are critical for motor control. The goal of this project is to further investigate which pathways in the spinal cord help recovery and how stimulation can affect c-Fos expression. Since the research is still ongoing, the study aims to contribute to the broader goal of improving SCI rehabilitation by providing insights into neuronal plasticity and supporting the development of new neuroprosthetic therapies to enhance motor function in SCI patients.

Schizophrenia is a complex mental illness influenced by genetic, environmental, and neurodevelopmental factors. Cognitive impairments are a prominent symptom of schizophrenia and are associated with long-term outcomes. Current literature suggests that damaging genetic risk factors, such as copy number variations (CNVs) and loss of function (LOF) mutations, are important contributors to schizophrenia etiology and may influence cognitive functioning among patients. However, isolating the effects of these variants can be complicated by the contributions of other factors, such as environmental factors, to schizophrenia etiology and functioning among patients. Using a within-family study design offers one way to control for background factors and isolate the effects of rare, damaging risk variants. This study used data from 446 subjects enrolled in the University of California, Los Angeles Family Study, involving 83 schizophrenia and 59 control families with genetic and behavioral data. An initial analysis of variance (ANOVA) revealed that schizophrenia probands showed a significantly greater decrease in IQ compared to their own relatives than control probands compared to their own relatives. Building on these findings, this study aims to explore whether extreme within-family IQ differences are associated with the presence of known risk CNVs for schizophrenia and broader neurodevelopmental disorders or LOF mutations in genes previously associated with these disorders. By elucidating the heterogeneity of schizophrenia through the examination of genetic risk variants and their connection to cognitive impairments, this research may help inform optimal intervention strategies for different patients and thereby improve clinical outcomes for individuals with schizophrenia and related disorders.

Elevated levels of metals such as copper (Cu) and manganese (Mn) are often observed in liver failure patients, individuals with Wilson’s Disease, and those with hypermanganesemia with dystonia or workplace exposure. The binding of Cu and Mn to proteins such as albumin and ceruloplasmin poses difficulties for their removal through dialysis. The primary objective of this research is to evaluate the effectiveness of adding albumin in dialysis in removing these toxic metals. We explored different blood and dialysis flow rates and dialysate albumin concentrations to find optimal conditions for Cu/Mn removal. We also explored cheaper Food and Drug Administration (FDA) approved alternatives to albumin that may be effective at removing Cu/Mn. Additionally, due to Human Serum Albumin’s (HSA) limited supply and blood bank pricing, albumin from other mammal species were used to make treatments feasible. In this study we used albumin from several species and three low-cost albumin alternatives to remove Cu/Mn in a closed-loop dialysis process. We digested the biological samples with Nitric Acid and Hydrogen Peroxide on a hotplate and analyzed the atomic compositions of the biological samples using Inductively Coupled Plasma Mass Spectrometry (ICP-MS). We measured the percent reduction of each toxic metal normalized by albumin concentration and found that 20 mL/min and 150 mL/min of Bovine Serum Albumin (BSA) dialysate resulted in a significant percent reduction compared to the negative control. For albumin alternatives, Dextran Sulphate showed promise by notably increasing Cu percent reduction compared to the negative control. Despite the encouraging data, a larger sample size is needed to make a conclusive statement. Although Mn had little variance with different dialysate flow rates or albumin, charcoal columns demonstrated an effective near 100% reduction at both 20 mL/min and 120 mL/min of dialysate flow rate. Further replication studies are needed.

Syphilis, caused by Treponema pallidum (T. pallidum), remains a significant global health concern, with increasing cases worldwide. Doxycycline post-exposure prophylaxis (Doxy-PEP) has emerged as a potential strategy to prevent infection. However, widespread use raises concerns about the possibility that doxycycline-resistant T. pallidum strains might emerge and spread. This issue is alarming since doxycycline is a second-line therapeutic for syphilis and is often used in patients with allergies to beta-lactams or when beta-lactams are unavailable due to shortages. If genetic resistance to doxycycline were to develop in T. pallidum, it could undermine the effectiveness of Doxy-PEP and further narrow the range of treatment options for syphilis. To address this concern, I developed a restriction fragment length polymorphism (RFLP) assay to detect potential doxycycline resistance mutations in T. pallidum. This assay analyzes the 16S rRNA gene region of T. pallidum where most likely mutations could develop based on the analysis of other resistant pathogens. The assay was optimized using three synthetic 16S rRNA gene constructs containing the resistance-associated mutations and DNA from a wild-type T. pallidum strain (Nichols) as controls. The presence of mutations in the amplified control DNA was assessed by restriction digestion with the AluI, RsaI, and SfaNI enzymes, which can selectively cut wild type and mutant sequences and reveal specific mutations. The analysis of 60 archived samples from syphilis patients collected in the US, Madagascar, Argentina, and Sri Lanka is ongoing. Results will provide data on the frequency of doxycycline resistance mutations in T. pallidum, if any are found in this selected group of specimens. Developing a rapid, cost-effective surveillance tool is essential for monitoring potential resistance and preventing treatment failures when doxycycline is used.

Malaria, caused by the Plasmodium parasite, remains a relentless and destructive infectious disease, disproportionately affecting children in Sub-Saharan Africa, due in part to the absence of a highly effective, widely deployable malaria vaccine. Lipid nanoparticle (LNP) vaccines are a promising approach for vaccine development, especially against pathogens such as Plasmodium, which have proven historically difficult to vaccinate against. When coupled with the glycolipid adjuvant 7DW8-5 at a 5ug LNP to 0.5ug adjuvant ratio, malaria-targeting LNP formulations confer protection in mouse models. However, the optimal vaccine-to-adjuvant ratio and the mechanisms underlying 7DW8-5-mediated protection remain unclear. Here, we present a study that aims to refine dosing strategies and elucidate the role of CD8+ T and NKT cells in adjuvant-induced protection in a human-translatable mouse model. Different groups of mice will be vaccinated with varying LNP-to-adjuvant ratios, and immune response will be assessed via ELISPOT 28 and 56 days post-vaccination. Furthermore, we will use ELISA to reveal variations in innate immune response between groups 3 hours after vaccine administration. In parallel, we will investigate the necessity of CD8+ T cells and/or NKT cells in protecting from malaria challenge. Mice will be vaccinated using the standardized LNP-to-adjuvant ratio and treated with depletion antibodies targeting CD8+T or NKT cells 24 hours before challenge with Plasmodium sporozoites. Protection will be assessed via blood smear analysis. Our findings will reveal optimal dosing strategies for malaria-specific LNP vaccines and provide insight into the immunological mechanisms behind 7DW8-5-driven protection. This research will contribute to the development of effective nanoparticle-based malaria vaccines — a necessary innovation to help relieve the global malaria burden.

The future of clinical research is expanding towards sampling that can be completed from the comfort of a participant's home. Blood samples allow for the collection of ribonucleic acid (RNA), which is relevant for gene sequencing that can track the progression of a disease. However, venous blood draws require trained phlebotomists at a healthcare facility, which may not be readily accessible in some areas. Dried blood spots are an existing remote sampling method, but rapid degradation of RNA and low blood volume can limit the scope of analyses that are possible. Previously, our lab developed homeRNA, which interfaces with the Tasso-SST (Tasso Inc.), a lancet-based device that draws blood from the upper arm. The addition of the engineered, spill-resistant container creates a channel through which participants can draw their own blood, stabilize the blood with RNAlater (Thermo Fisher Scientific), and ship the sample to a laboratory for analysis. The homeRNA+ project improves upon the original homeRNA by integrating a commercially available blood collection tube for better compatibility and doubling the maximum blood collection volume. Feedback from study participants over the United States across all age and race demographics generally find the blood collection process painless and the stabilization easy to perform. We expect samples to also have sufficient RNA integrity and yield for downstream analysis. The project serves a number of nationwide and global collaborators, including academic institutions like New York University and Boston University. I assist in receiving and processing biological samples from remote collection, ensuring proper handling by safely unpackaging, logging, and preserving returned samples in cold storage for future analysis. Additionally, I serve as a study coordinator by meeting with collaborators, manufacturing high volumes of kits in a timely manner, and managing inventories.

The increasing rise in allergy prevalence has led to a growing demand for portable allergen testing devices. Food allergens, which can lead to fatal immune reactions, are especially complicated to avoid due to cross contamination and food mislabeling, as seen with many types of seafood. Instances of seafood mislabeling and inauthenticity also impacts consumers financially when cheaper options are passed off as more rare and expensive fish. Atlantic salmon is one of the most commonly used fish for this type of fraud. Devices to detect allergens and/or authenticity must be easy-to-use, quick, and require little to no dangerous reagents for the regular consumer. While there are some commercial devices on the market for peanut and gluten detection, they are costly and do not appear to be very accurate or sensitive. Our prior work showed a proof of concept for a one-pot amplification-detection method with recombinase polymerase amplification that allowed for a reaction to occur at a fixed temperature and with no expensive laboratory equipment. Currently, I am developing fluorescence-based polymerase chain reaction and recombinase polymerase amplification assays that can differentiate Atlantic salmon from other types of salmon. To further develop this technology into a consumer-friendly allergen detection and seafood authentication device, I plan on adapting the assay into an electrochemical format, allowing for simplified readouts of the results. The results from this assay would be able to be displayed on easily accessible electronic devices, such as a smartphone or laptop. In its final form, this project will demonstrate a portable heating device with a classification assay that would be able to detect the presence of Atlantic salmon without laboratory equipment.

The necessity of criminal justice reform has grown increasingly significant as governments address the challenges of mass incarceration and its far-reaching social and economic consequences. Over the last decade, California has been spearheading reform in the United States. In compliance with a Supreme Court ruling, California passed Proposition 47 (Prop 47)—a landmark policy that reclassified certain nonviolent felony offenses as misdemeanors—to reduce the population of nonviolent offenders in the prison system. While Prop 47 successfully reduced incarceration rates and state expenditures on corrections, critics argue that it has also contributed to increased property crime, particularly retail theft, due to theft-felony threshold being increased from $400 to $950. Utilizing a difference-in-differences methodology, this study compares retail business activity in California with a synthetic control group composed of demographically and economically similar states with felony thresholds similar to California’s, pre-Prop 47. The analysis draws on data from the U.S. Census Bureau, incorporating crime rates, business permit activity, and economic trends. This study aims to assess whether Prop 47 led to a tangible increase in property crime and, in turn, a decline in retail business sustainability. The findings will provide empirical insights for policymakers seeking to balance criminal justice objectives with economic stability, informing on the broader implications of sentencing reforms on local economies.

Estradiol, a steroid hormone, plays a crucial role in bone density, cardiovascular function, and neuroprotection. It signals through Estrogen Receptor α (ERα), a nuclear receptor that, upon estradiol binding, undergoes a conformational change, translocates to the nucleus, and regulates gene transcription. While ERα's role in gene regulation is well established, the real-time kinetics of estradiol signaling remain poorly understood. To address this, I have been developing and optimizing a fluorescent biosensor, ER_mNG, to enable real-time monitoring of estradiol levels in living cells. ER_mNG consists of ERα’s ligand-binding domain (LBD) inserted within the mNeonGreen fluorescent protein. Estradiol-induced conformational changes in ERα alter mNeonGreen’s fluorescence, providing a readout of estradiol dynamics. To improve the sensor’s dynamic range, I have employed linker optimization, a structure-guided protein engineering approach. I designed and cloned ER_mNG variants with modified linker lengths and amino acid compositions using site-directed mutagenesis and in vivo assembly (IVA) cloning. These variants were transiently expressed in HEK293 cells via lipofection, and their fluorescence response to estradiol stimulation was quantified using live-cell fluorescence microscopy. By systematically modifying the sensor’s structure, I aim to develop an improved ER_mNG variant with a significantly enhanced dynamic range, enabling more precise measurements of estradiol signaling. This tool has the potential to advance our understanding of estradiol’s role in health and disease.

Upon nerve injury and neurodegeneration, neuron regeneration is crucial to maintain proper function. However, this natural process happens infrequently and slowly. Neuron regeneration is known to be mediated by the activity of nerve growth factor (NGF) in neurons, which binds to two receptors: tropomyosin receptor kinase A (TrkA) and p75 neurotrophin receptor (p75NTR). Previous studies have shown that engaging the receptor p75NTR activates a signaling pathway that also triggers a pain response, thus it would be ideal to have a ligand that only activates TrkA for neuron regeneration without initiating the pain response. In collaboration with the Institute for Protein Design (IPD), this study investigated an AI-designed TrkA agonist that specifically binds to and activates only the TrkA receptor. We used fibroblasts transdifferentiated into neurons as a model to study the efficiency of this TrkA agonist. Western blotting was used to study the phosphorylation of the proteins downstream of TrkA in the signaling pathway, such as pPLCγ, pAkt, and pErk, and the activity of transient receptor potential vanilloid 1 (TRPV1), a calcium channel that indicates the sensitivity of a neuron. Immunofluorescence staining was used to examine the expression of calcitonin gene-related peptide (CGRP), a neuropeptide involved in pain perception. We found that the designed TrkA agonist generates a similar level of activation of downstream proteins as NGF while successfully preventing the expression of pain response markers. Directly injecting NGF as a treatment for neurodegenerative diseases is generally not considered viable as it often induces significant pain, therefore this TrkA agonist has the potential for therapeutic use.

This research examines the statistical interactions of genetic risk scores and behavior data from wearable devices, including physical activity and sleep measures, to predict Major Depressive Disorder (MDD) symptom onset. MDD is a widespread mental health issue, with nearly all indicators of mental health worsening from 2013 to 2023 and 30% or more current children experiencing mental health symptoms. Research shows that lifestyle changes, such as improving physical activity and sleep behavior, can alleviate early-stage MDD symptoms. But, many people are unaware of their genetic vulnerability to MDD, leaving them unprepared for potential challenges. This study uses the Adolescent Brain Cognitive Development (ABCD) dataset, the largest U.S. longitudinal study of brain development and child health. ABCD provides extensive psychometric, demographic, genetic, and wearable data for research. This study uses genetic and wearable tracking data to predict MDD severity and support early interventions. It also investigates how genetic risk levels inform how physical activity and sleep patterns must change to mitigate MDD symptom severity.  This study will calculate polygenic risk scores (PRS) for ABCD subjects and improve prediction accuracy for non-European populations using state-of-the-art bioinformatics tools. Then, this study will utilize mixed effects modeling to analyze additive and interactive effects of PRS, wearable data, and depression severity scores. Lastly, this study will program machine learning (ML) models to provide variable importance and accuracy results. The goal is to create a personalized, data-driven approach to MDD prevention and empower individuals to take proactive steps toward mental well-being based on a comprehensive view of their genetic and behavioral factors.

Aberrant protein levels can lead to pathological states and subsequent disease, traditionally requiring treatment by therapeutics that work by occupying a pocket on a target protein and result in inhibition of the protein's enzymatic function. However, many high-value therapeutic targets do not have enzymatic activity and thus are not amenable to small molecule inhibition. To address this shortcoming and expand the number of druggable proteins, an intense focus on directly altering protein levels within cells has recently emerged. Targeted protein degradation (TPD) or stabilization (TPS) aims to develop therapeutics for previously undruggable targets by leveraging the endogenous protein degradation system within cells, recruiting an effector protein, either an E3 ubiquitin ligase (for TPD) or a deubiquitinase (for TPS), in proximity to a target protein. My research in the Shendure Lab  combines computational de novo protein design and high-throughput screening with the goal of identifying designed proteins capable of mediating TPD and TPS in cells. Specifically, we are collaborating with the UW Institute for Protein Design to design degrader/stabilizer binding proteins to be screened in HEK293 cells. By labeling each designed protein with a unique RNA barcode, we can leverage massively parallel DNA sequencing to characterize 6,000 de novo designed degraders/stabilizers in a single experiment. If successful, this will be the first demonstration of designed proteins that can modulate cellular protein levels, paving the way for a new therapeutic modality.

Mountain snow is an important source of freshwater for forest and meadow ecosystems. However, extreme events such as heat waves and low snowpack pose a significant threat to the availability of these essential resources. Current technology for detecting snow coverage from satellite imagery is limited due to insufficient image quality, especially in forests and meadows. To address this, we developed a Python package that improves access to a machine learning-based snow coverage detector at meter-scale resolution. Built upon research by Yang et al., 2023, this package integrates machine learning models to generate snow coverage masks from Planet satellite imagery. The package includes five core components to assist researchers in leveraging this technology: data searching and downloading from Planet's satellite imagery, custom training and fine-tuning of random forest models for snow coverage detection, prediction of snow-covered areas using the model, and geometry simplification for defining areas of interest. Other features include pre-trained models and sample datasets for quick and efficient implementation. By consolidating their research into a Python package, we aim to improve accessibility to software and research for those seeking to track mountain snow coverage and its environmental impact. Ultimately, our goal is to empower researchers to accelerate progress in understanding spatial patterns of snow in forests and mountain meadows. Additionally, we aim to support resource managers in more effectively tracking snow distribution across complex terrain.

The resistance of castration-resistant prostate cancer (CRPC) to androgen receptor signaling inhibitors (ARSIs) continues to be a significant clinical problem. Translation inhibitors are being researched as a potential treatment for AR-independent CRPC after our laboratory discovered that elevated mRNA translation as one of the major contributing factors. We screened pharmaceutical firms' known mRNA translation inhibitors in three human LuCaP models of advanced prostate cancer: AR-low prostate cancer (LuCaP 176), castration-resistant prostate cancer (LuCaP 35CR), and AR-intact castration-sensitive prostate cancer (LuCaP 35CS). We discovered that only a unique eukaryotic translation initiation factor 4E (eIF4E) 5' cap-binding domain inhibitor was able to efficiently target LuCaP 176, whereas the majority of inhibitors were able to stop the growth of LuCaP 35CS/CR. 5' cap binding inhibition increased the efficacy of enzalutamide in AR-low cells by inducing basal to luminal lineage plasticity and post-transcriptionally downregulating basal keratins. Furthermore, in the AR-low basal LuCaP 176 PDX (patient derived xenograft) model, enzalutamide effectiveness was enhanced by eIF4E cap binding domain suppression. These results are consistent with patient data indicating that people with elevated eIF4E levels have faster resistance to ARSI. Overall, our preliminary data demonstrates that translation inhibitors targeting the eIF4E cap binding domain can reverse lineage plasticity through a translation-based mechanism and sensitize AR-low prostate cancers to ARSIs. To further investigate these mechanisms and assess their implications in patient specimens, we are determining how eIF4E cap binding domain inhibition regulates translation of basal keratins and cellular plasticity along with impacting CRPC growth. Our study shows a promising method for reducing ARSI resistance in deadly metastatic CRPC which is to target eIF4E cap-binding. In order to optimize patient outcomes, this study lays the groundwork for eIF4E cap binding domain inhibition as a possible therapeutic and incorporates a cap-binding assay as a biomarker for individualized treatment.

Individuals vary in their bias toward visual or verbal information when perceiving and making decisions. These differences in information processing style are not all-or-nothing; people vary not only in the direction of attentional bias, but also in its strength. If forced to choose between competing visual and verbal stimuli, people exhibit differing degrees of bias when selecting information. The Card Sorting Task measures this bias by asking people to select either the visual (shape) or verbal (word) representation of a card suit. On 75% of trials, the word and shape match, however, 25% of trials contain inconsistent information, which is used to show visual/verbal bias. My prior research found that people more biased toward visual or verbal information had faster response times than more neutral people and showed more bias during consistent and inconsistent information trials, suggesting biased attenders are less sensitive to conflicting information than more neutral attenders. This study seeks to follow up on my previous work; exploring whether a preference for picture/word stimuli (Relative Skill) or sensitivity to evidence needed to make a decision (Decision Sensitivity) drives the individual differences in conflicting stimulus responses. 100 participants will complete the Card Sorting Task, followed by subsequent trials modified to instruct participants to select the visual or verbal information. This creates “correct” and “incorrect” ways to sort the stimuli, allowing the use of Drift Diffusion Modeling to measure evidence accumulated before decision making. If the Relative Skill hypothesis is true, we expect a higher drift rate when participants sort according to their preferred modality, meaning that they have faster response times. If the Decision Sensitivity hypothesis reigns true, biased attenders will have higher drift rates, not needing as much evidence to make a decision, while neutral attenders will have a lower drift rate, taking their time responding.

Neuropsychiatric disorders lead to devastating impacts on a patient’s life, affecting physical movement, cognition, and behavior. A pattern observed in patients with neurodegenerative disease includes neurofibrillary tangles in the brain, which may be caused by the abnormal accumulation of the microtubule-associated protein tau (MAPT). Tau is encoded for in the MAPT gene locus on chromosome 17, where the locus commonly interacts with an enhancer to boost transcription. However, some patients have one copy of chromosome 17 with an inversion that breaks this interaction, which is associated with lower risk of disease. This raises the question of whether the MAPT locus interacts with other enhancers that increases tau production. Thus, the goal of this project is to identify genetic variants that influence the 3D interactions between the MAPT locus and potential enhancers in patients heterozygous for the MAPT inversion associated with a lower risk of neuropsychiatric disorders. To accomplish this objective, neuronal nuclei extracted from patients are analyzed using fluorescent in-situ hybridization (FISH) to identify interactions in the MAPT gene locus. We will map a 2 Mb region of chromosome 17 centered on the inversion using FISH probes. This region is broken up into ten 200 kb spots to be individually visualized using fluorescent oligonucleotides through a fluidics system, to create a composite image of all spots. Interactions involving the MAPT locus may be identified by comparing distances between spots, in which gene segments that interact would have a shorter distance compared to segments that do not interact. This would allow us to find genetic variants associated with the chromosome 17 inversion that potentially influence MAPT gene regulation.

The cerebellum (Cb) is typically associated with the regulation of motor behavior. However, recent studies have shown that the Cb has connections to other brain regions associated with higher-order cognitive functions, such as the Hippocampus (HPC), suggesting that the Cb is involved in modulating cognitive behavior. The literature also implies that dynamic changes in the levels of the neurotransmitters Dopamine (DA) and Norepinephrine (NE) may underlie the functionality of involved circuits. This project aims to characterize specific cerebellar circuits involved in the modulation of learning and memory. To test this question, I ran a Fear Conditioning (FC) paradigm in which a conditioned stimulus (CS+), a tone, was presented with an aversive unconditioned stimulus (US), a shock. An additional tone, CS-, was presented without shock. A cohort of 7 mice (4 control, 3 experimental) were run through the paradigm and injected with the optogenetic construct ChR2 to stimulate Purkinje Cell (PC) terminals that synapse on the Lateral Cerebellar Nuclei (LCN). Additionally, Fiber Photometry (FP) was used to record changes in DA and NE in the LCN. I used ezTrack’s python packages to analyze freezing % as the measure of learning, and coded python notebooks to process and visualize DA and NE signals. Mice that received ChR2 stimulation on PC terminals displayed better associative learning between CS+ and US compared to mice that did not receive ChR2 stimulation. These mice also extinguished the association of CS+ and US sooner than unstimulated controls. We also expect these mice to display elevated levels of DA and NE that is statistically significant compared to unstimulated controls. These experiments elucidating cerebellar circuitry in cognitive behaviors may serve to expand our understanding of neural substrate alterations in cognitive function. The LCN may also be a novel locus for targeted therapeutics in human affective disorders.

Cerebellar development relies on the coordinated proliferation and differentiation of progenitors from the ventricular zone (VZ) and rhombic lip (RL). To systematically map their spatiotemporal dynamics, we performed EdU pulse labeling by injecting pregnant mice with EdU and collecting embryonic cerebella at daily intervals over five consecutive days as well as an acute half-an-hour post EdU injection. EdU labeling identifies actively dividing progenitor cells at the time of injection. As development progresses, EdU+ cells can be tracked to study their differentiation and migration, revealing the temporal dynamics of VZ and RL progenitor-derived neurons in the cerebellum. Using multiplex immunohistochemistry with VZ- and RL-derived cell-type specific markers, we tracked the spatial distribution and differentiation of EdU-labeled cells, distinguishing VZ- and RL-derived progenitor lineages. Additionally, we outline a strategy to isolate EdU+ cells for single-cell RNA sequencing (scRNA-seq) and ATAC sequencing (ATAC-seq), enabling a comprehensive molecular characterization of progenitor fate transitions. This approach provides a high-resolution developmental trajectory of cerebellar progenitors, offering new insights into the regulatory mechanisms driving cerebellar neurogenesis and their disruptions in neurodevelopmental disorders.

Developments in data-driven technology have been targeted at large-scale produce farms in Washington state, leaving out small farms from what is being called “Agriculture 4.0”. This agri-tech revolution seeks to leverage data technologies such as artificial intelligence (AI) for efficiency and profitability, but small farmers are largely excluded. This pattern echoes the Green Revolution of the 1960s and 1970s, where technological advancements primarily benefited large farms, increasing output while forcing small farmers out of business and into consolidation. Consequently, advancements in data-driven technology may create similar agricultural monopolies and decrease food resilience through longer supply chains. Alternatively supporting small farmers, with annual sales of less than $250,000, can be integral to regulating agricultural monopolies and increasing food resilience. To promote the inclusion of these farms, this study investigates how small produce farmers perceive data-driven technologies in the context of “good” farming practices. I will conduct semi-structured interviews with small produce farmers in Western Washington, a region with a diverse farming population, employing an inductive analytical approach to understand how farmers’ values and morality shape their openness to technological adoption. This research is critical because findings will contribute to more inclusive AI development accounting for the needs and perspectives of small-scale farmers in Washington, mitigating agricultural monopolies and increasing food resilience.

This study investigates the Namonuito region of Micronesia to determine whether the many guyots and atolls in this region contain specific slope conditions suitable for cobalt crust growth. This project also investigates whether there is a relationship between suitable zones and general bathymetry. The primary research focused on NAM-2 Atoll and Enterprise, Essex, and Namonuito Guyots. After collecting multibeam and sub-bottom data, the slopes were analyzed for slope angle, optimal slope distribution and composition. Then the results were compared with each other to determine if there are any similarities or correlations. Among all the guyots it was found that almost all the optimal zones were found in gullies, ridge slopes, and at the bottom of areas that experience slope failures. However, there isn’t a clear correlation between mean slope angle, optimal slope distribution and slope face orientation. In addition, sub-bottom data showed that almost all the guyots northern slopes were covered by a single thick pelagic layer, while the southern slopes of Namonuito and Enterprise contained thin pelagic layers with zones of exposed hard substrate. NAM-2 Atoll also was entirely covered in a single thick pelagic layer. Overall, by conducting a geomorphology and sub-bottom comparison test it is possible to narrow down locations of interest that can be further surveyed. The implications of cobalt crust research are that cobalt crusts are another natural source of cobalt which is becoming increasingly difficult to obtain on land. If the Namonuito region contains a large cobalt crust and the cobalt crusts can be extracted, it could have a huge impact of global technology and manufacturing industries.

Anaerobic digestion is a biological method of treating wastewater. Waste, such as food scraps, oils, and manure, is converted to acetate among other biodegradable organic matter in the absence of oxygen. Acetate is converted to biogas later in the digestion process, which may be captured as a renewable energy source. This study aims to determine how different dosages of substrate affect biomethane generation of anaerobic archaic culture. To explore this hypothesis, six serum bottles are filled with 30 milliliters of material from anaerobic. They are then injected with different acetate dosages. To determine the methane generation rates, gas from the headspace of each bottle was injected into a Gas Chromatography Flame Ionization Detector (GC-FID) instrument that detected the concentration of methane. Three measurements for each bottle were taken at one-hour intervals for five runs and are averaged in the results. The GC-FID rendered a graph between time and methane concentration from these measurements. The results of this study will help improve the understanding of anaerobic digester activity in response to different acetate concentrations, which is critical in establishing stable, large-scale digestion operations. 

In mathematics, a symmetry of an object is an invertible mapping from the object to itself. In classical geometry, symmetries are described by group actions. However, group actions are not enough to capture all of the symmetries of some objects. In particular, algebras have symmetries given by Hopf actions of quantum groups called quantum symmetries. In this project, we aim to classify the quantum symmetries of gentle algebras given by Hopf actions of generalized Taft algebras. Path algebras are algebras associated to a directed graph. All finite dimensional algebras can be understood as quotients of path algebras including gentle algebras. The directed graphs associated with gentle algebras can be obtained by gluing copies of particular directed graphs with 1-4 edges. Our approach is to start by classifying Taft actions on these smaller directed graphs. Then, we will determine how these actions glue together to give us Taft actions on any gentle algebra. There is a known parametrization of Taft actions on path algebras, and this project is a step in generalizing this to Taft actions on any finite dimensional algebra.

The Lidstrom Lab aims to better understand methane-consuming microbes (also called methanotrophs) so that we can develop technologies to remove anthropogenic methane emissions, which will reduce the severity of global warming. Our research explores how the methanotroph Methylotuvimicrobium buryatense 5GB1C can be bioengineered to grow well at the low methane concentrations found in human-made emission sites, while providing value-added products like biomass from dead bacteria that can be used as animal feed. Understanding bacterial methane utilization will allow us to create effective biocatalysts at a far lower monetary and environmental cost. My research project involves deleting cytochrome genes that may be important for the 5GB1C strain to grow in low methane conditions. Manipulating these genes may allow for further improvement of growth at low methane. My targets are three genes that encode cytochromes, which are electron carriers that take electrons from particular reactions and supply them to other reactions that are otherwise energetically unfavorable. My hypothesis is that these cytochromes are involved directly in supplying 5GB1C with electrons needed for the oxidation of methane into methanol. If these cytochromes supply electrons required for methane consumption at low methane, then deleting them would generate a mutant that would grow poorly on methane because it lacks the electron carrier(s). I have generated two possible cytochrome deletion mutants and continue to work on a third cytochrome. Once the mutants that can be generated are sequenced to verify the deletions, cultures will be grown under low methane and methanol conditions to determine how their ability to grow has been affected by the knockout mutations. In this manner, our lab is building a valuable knowledgebase of genes that are suitable for manipulation to improve growth in low methane for the technologies that one day will help curtail the worsening of global warming.

Acomys Cahirinus (spiny mice) are remarkable creatures that exhibit key differences in inflammatory response, regeneration, and aging compared to mice. Adult neurogenesis - the production of new neurons- in the hippocampal niche declines with age in most mammals, yet Acomys exhibits sustained neurogenic potential, presenting a unique model for regenerative neuroscience. This study leverages advanced image analysis software (Imaris) to develop robust pipelines for quantifying neural stem cell (NSC) and intermediate progenitor (IP) proliferation and fate determination in Acomys versus standard laboratory mice (Mus musculus). Using EdU incorporation to track S-phase entry and a 4D pulse-labeling approach, we assess neurogenic niche activity across species. Additionally, we extend this analysis to aging Acomys, utilizing consistent sectioning, staining, and imaging parameters to confirm continuous progenitor proliferation in young and old cohorts. Our findings provide critical insights into the cellular and molecular mechanisms underlying sustained neurogenesis in Acomys, offering prospective therapeutic targets for age-related neurodegenerative conditions.

Introduction: Evidence-based treatments (EBT), such as cognitive behavioral therapy (CBT) remain underused in community mental health (CMH) settings in part due to financial, time, and geographical barriers associated with training clinicians in-person. Virtual EBT training offers a potentially cost-effective and feasible alternative; however, limited research has examined its effectiveness in improving clinicians' perceived knowledge and skills for treating youth with various mental health conditions. The current study uses benchmarking analyses to compare change in perceived knowledge and skill levels for treating youth with depression, anxiety, trauma and behavior problems among clinicians trained in-person versus those trained online. Method: Participants included 1,250 Washington State CMH clinicians (Mage=35.58 years, SD=12.12, 92% Master’s level) involved in the CBT+ initiative, a Washington statewide EBT training program. Of these clinicians, 658 attended training in-person (years 2016–2019), while 592 participated virtually (years 2020–2023). Clinicians self-reported their perceived knowledge and skill levels for treating youth with depression, anxiety, trauma, and behavior problems before training and after completing a six-month consultation period. Results: Preliminary analyses using paired samples t-tests revealed that across all disorders, perceived knowledge and skill scores significantly increased from pre-training to post consultation for in-person training clinicians (all p’s < .001, Cohen's d ranged from .93 to 1.61), as well as virtual training clinicians (all p’s < .001, Cohen's d ranged from 0.75 to 1.73). Benchmarking analyses will be conducted to compare effect sizes for changes in perceived knowledge and skill levels between clinicians trained in-person and those trained virtually. Discussion: As the need for youth mental health services continues to grow, it is vital to evaluate alternative training methods to expand access to high-quality mental healthcare.

Spoken, written, and body language are the media through which we interact with our social world. Formalized in the 20th century and owing to the work of anthropologists like Franz Boas, Edward Sapir, and Benjamin Whorf, the theory of linguistic relativity posits that the language we use influences our thoughts and our perception of the world. Linguistic practices like code-switching point toward an intricate relationship between language use and social setting. As new technologies proliferate alongside evolving patterns of migration around the globe, it is likely that multilingual ability will increase. However, a knowledge gap exists regarding the role of bi- or multilingualism (hereafter encompassing bilingualism) within linguistic anthropology. Given the cultural origin of identity and the interlinked nature of culture and language, my research question asks if multilingualism can grant individuals greater latitude in the expression of their discrete identities. This literature review examined multilingualism in diverse contexts, including psychotherapy, postcolonialism, and stand-up comedy, to better understand how linguistic flexibility affects our interpersonal lives and intrapersonal conceptions. Despite the aforementioned knowledge gap, a broad scope of answers from the literature suggests that multilingual ability uniquely shapes how people interact with the world around them. Multilingualism provides benefits to both multilingual individuals and the communities and social networks in which they live. The ability to communicate in one more than one language or dialect can afford a more complete sense of identity, maintain connections to cultural roots, and open new avenues for self-perception. As political rhetoric veers towards xenophobic and jingoist tendencies, the question of how people who live and communicate at the intersection of two or more cultures becomes more relevant, both for the self-conception of those at the margins and for the perception of this population by the dominant culture.

Molecular computing, which harnesses biomolecules such as DNA for computation, has rapidly advanced in the past two decades. DNA Strand Displacement (DSD) is a key molecular primitive used to implement molecular circuits. DNA’s predictable A/T C/G base-pairing enables precise control over molecule interactions. However, visualizing DSD processes remains a challenge. Current tools generate only static representations, making it difficult to illustrate reaction pathways and communicate complex molecular interactions effectively. This lack of clear visualization hinders collaboration among researchers and makes it difficult to communicate to those outside the field about the principles and potential of molecular computing. To address this, we have developed a Python package that automates the visualization of DSD reactions, generating both static and animated representations of DNA/RNA secondary structures. Using the Manim library from creator 3Blue1Brown, our tool takes as input DNA/RNA structures written in the widely-used dot-parenthesis notation and produces layouts and animations of the displacement events. Users can toggle between different layout and color modes that highlight features such as sequence and bonding probabilities, providing flexible options for different needs.

Sleep disruption is a key factor that contributes to cycles of relapse in opioid addiction, a pressing public health concern. However, the underlying mechanisms of this sleep disruption are yet to be well-understood. Gaining a better understanding of the neural circuits involved in opioid-mediated sleep disruption may help to develop new treatment to mitigate the risk of opioid dependence. We previously found in a mouse model of escalating morphine administration and withdrawal that the locus coeruleus (LC), the brain’s primary source of cortical noradrenergic projections, is hyperactive during opioid withdrawal and is accompanied by a shift in sleep pattern during the first withdrawal day. However, its precise role in affecting opioid-mediated sleep disruption remains unclear. We are now investigating the role of LC noradrenergic projection to the paraventricular thalamus (PVT) in opioid-induced sleep disturbances, as the PVT is known to promote wakefulness. As PVT manipulation has previously been shown to reduce opioid-induced sleep disruption, I am examining the contribution of the LC-PVT circuit in this disruption in sleep pattern. To address this question, I am quantifying LC projections to the PVT by clearing brain tissue in mice expressing a fluorescently tagged synaptic marker in LC neurons, and counting the number of LC synapses in the PVT. Additionally, we  quantified norepinephrine release in the PVT using a genetically encoded fluorescent sensor and fiber photometry, and measured cortical activity using electroencephalogram (EEG). Our preliminary data show a potential decrease in NE activity during the first withdrawal day, but more mice are needed for this experiment. Additionally, given the elevated LC activity on the first withdrawal day, we plan to inhibit LC-PVT circuit on that day to determine if sleep disruption can be prevented. Together, these studies will help better define how changes in the noradrenergic circuits contribute to sleep disruption from opioid use.

Dehydration is a silent but pervasive health risk, particularly for older adults in assisted living home settings, where prevalence rates can reach up to 60%. Medications that increase fluid loss place seniors at a heightened risk, leading to severe complications including urinary tract infections, falls, cognitive decline and hospitalisations. Caregivers continue to struggle to monitor fluid intake effectively, with less than 10% maintaining consistent hydration logs. Existing hydration monitoring solutions are often invasive, expensive and poorly suited for non-medical care settings. To address this critical issue, we developed a novel, non-invasive hydration monitoring system designed for elderly care environments. Unlike existing methods that rely on highly variable sweat salt concentrations, our approach leverages ultrasound-based elasticity measurements to assess hydration status. Changes in hydration levels alter the biomechanical properties of skin and muscle, affecting the speed at which ultrasound waves travel through tissue. By using a dual-transducer system to induce and measure shear wave propagation, we can quantify hydration status in real-time. The device provides both quantitative readouts for longitudinal tracking and intuitive qualitative feedback, similar to a blood pressure monitor's high-normal-low classification, ensuring ease of use without specialised training. Initial testing demonstrates promising accuracy and usability, positioning our solution as a practical solution to improve hydration management, prevent dehydration-related complications, and enhance quality of life for elderly residents. By empowering caregivers with a reliable, accessible hydration monitoring tool, our solution has the potential to significantly reduce healthcare costs, improve patient outcomes, and transform hydration care in aging populations. 

In the Berndt lab, we develop genetically encoded fluorescent indicators (biosensors) by attaching a naturally occurring sensing domain to a fluorescent protein. When the ligand of interest, such as dopamine or calcium, interacts with the sensing domain, the protein will undergo a conformational change that induces a fluorescent response. The change in fluorescence can be measured and used to quantify biochemical activity. Applications of these biosensors span a wide range of research topics in neuroscience and behavior, providing insights into the neuronal network activity correlated with addiction, pain perception, emotion, and reward signaling. The current project that I am working on is optimizing the red dopamine sensor, GRABrDA2m. I developed a genetic library, mutating the linkers that connect the sensing domain and fluorescent protein. The behavior of proteins is highly dependent on structure and orientation, which is why I have chosen the linkers as a target region to explore. I have cloned in degenerate codons that randomize the nucleotides at specific positions on these linkers, with the linker locations having been recently identified in published literature. After sequencing the DNA to validate that the sites of interest were mutated appropriately and that the remainder of the sensor is intact, I will transfect these plasmids into human embryonic kidney 293 (HEK293) cells and screen for promising variants by employing OptoMASS, an cell array technique developed in the Berndt Lab that allows for the testing of hundreds of mutations simultaneously. I will pick out the cells whose sensors performed better than the parental variant, looking for improvements in baseline fluorescence and sensitivity to dopamine, then conduct reverse-transcriptase polymerase chain reactions to extract the sequences of the high-performing sensors.

Public discourse on prison labor often centers on its ethical implications, yet little research has been conducted on its impact on local labor markets. The Prison Industry Enhancement Certification Program (PIECP), a federal initiative that allows private companies to employ incarcerated individuals at prevailing industry wages, offers a unique opportunity to assess these impacts. Currently, there are 45 correctional facilities which use the program, and they partner with 222 businesses. This empirical study examines how participation in PIECP influences local labor markets by analyzing changes in wages across sectors and metropolitan statistical areas (MSAs) to inform public policy discussions on the role of prison labor in the U.S. economy. Using a difference-in-differences research design, I compare regions where prisons implement PIECP employment with those where certified facilities do not engage in the program. Data from the National Correctional Industries Association and the Bureau of Labor Statistics will be used to quantify these effects. This research aims to provide insights into how prison labor through this program affects local labor markets.

Previous research indicates that males typically outperform females in spatial perspective-taking tasks where an individual is prompted to assess a scene by adopting a perspective other than their own. However, a recent study, with only female participants, found an increase in female perspective-taking performance when the task asked subjects to take the perspective of a social agent. Many have theorized that this performance increase is exclusive to females, who are believed to hold superior social skills. This implies a distinction between purely spatial perspective-taking and social perspective-taking, the latter of which females are theorized to perform better at. More recent studies have countered this notion, suggesting that directional information provided by a social agent could explain the increased performance in females. Assessing the relationship between spatial and social perspective and sex-based differences in performance can provide insight into social perspective-taking in human cognition. To clarify the influence of social agents on perspective-taking performance in both males and females, we administered two spatial perspective-taking tasks, with either a social or non-social agent. We aim to clarify theorized sex-based differences in performance by comparing accuracies and reaction times in social and non-social conditions. We hypothesize that male and female performance in perspective-taking tasks will be equally affected by the presence of a social agent.

Methane is an extremely potent greenhouse gas, with a warming potential 86 times greater than that of CO2 on a 20-year timescale, and is therefore a top priority for mitigation efforts to combat climate change. Methanotrophic bacteria, such as M. buryatense 5GB1C, metabolize methane as their main source of carbon and chemical energy, a trait that could help slow climate change by reducing emissions. A major obstacle is the rate at which methane consumption occurs at low methane concentrations, which tends to be too low to be appreciable. This project seeks to answer whether currently unknown genes involved in the growth of M. buryatense 5GB1C on low methane could be discovered by comparing its genome with that of a closely related methanotroph, M. alcaliphilum 20Z. While the two have very similar genomes and metabolisms, M. alcaliphilum is not able to grow at low methane concentrations (500 parts per million), while M. buryatense is. I analyzed the two genomes and isolated all genes present in M. buryatense without homologs in M. alcaliphilum. Because they are unique to M. buryatense, they may be involved in the observed growth difference. I systematically performed targeted deletion mutations on many of these candidate genes, and then tested them for growth on low methane compared to the wild type strain, looking for any defect that would suggest a gene directly essential to growth at 500ppm. I confirmed several genes to have no impact on growth at low methane, as well as one that appears to be essential to growth in any conditions, and anticipate reaching conclusions on several more mutants. These findings will help to develop microbial methane mitigation technologies that can be utilized in a great range situations and at a larger scale, essential characteristics for a global impact.

In this work, I propose an improved remeshing approach for particle method approximations. Particle approximation methods are a flexible tool for approximating solutions to nonlinear continuity equations, and are especially useful for aggregation-diffusion equations, which have important applications in fields ranging from modeling physical processes to neural networks. They work by decomposing functions into constituent parts, called particles. By tracking the motion and mass associated with each of these particles over time, we then use these to construct a high-resolution approximation to a desired solution. However, particle methods suffer from accuracy decay over time, necessitating remeshing (resetting particle positions) to maintain a useful approximation. It's important that the techniques used for this remeshing preserve existing structures, so that our approximation exhibits the same qualities as the true solution of the underlying equation. For instance, existing remeshing techniques often preserve conservation of mass, but not entropy decay. By combining remeshing techniques to periodically merge clustered particles and introduce new particles, I'm developing a method that maintains approximation accuracy and preserves structural properties. I present the results of the numerical analysis done using Python, as well as an implementation of the method using a finite-difference approach, which examines the approximation at various steps through time. This approach is expected to preserve the structure of the true solution within the particle method approximation, contributing to the development of robust particle methods for a broad class of partial differential equations.

Umbilical vein catheterization (UVC) is a life-saving procedure performed in neonatal intensive care units (NICUs) to provide emergency vascular access for critically ill newborns. The procedure requires accuracy in catheter placement and detailed knowledge of the relevant anatomy. Improper catheter placement can lead to severe complications such as hepatic necrosis, thrombosis, and cardiac tamponade. Current UVC training models lack the anatomical accuracy and tactile realism needed for effective hands-on training. My research aims to develop a realistic UVC training model that improves procedural accuracy and reduces neonatal complications. To address these limitations, I conducted a cognitive task analysis (CTA) with NICU clinicians to evaluate existing training gaps. The CTA revealed difficulties in distinguishing the umbilical vein from the smaller, thicker-walled umbilical arteries, a key factor in accurate catheter placement. The umbilical vein’s thin walls and similar coloration to arteries often lead to misidentification, resulting in incorrect catheterization. Additionally, practitioners reported difficulties in gauging the appropriate insertion depth, which vary based on neonatal size and condition, leading to potential complications if the catheter is advanced too far. Current models lack realistic tactile feedback, making it difficult to differentiate the collapsible umbilical vein from the rigid arterial walls. Without accurate resistance simulation, trainees struggle to develop the necessary sensitivity to detect vein entry and confirm catheter placement effectively. Based on the CTA findings, I am developing a model with depth markers, a simulated blood flashback system, and a suturable outer layer to improve training realism. This research contributes to neonatal care by improving hands-on UVC training, ultimately enhancing practitioner confidence, reducing neonatal morbidity, and raising the standard for UVC procedures. Usability testing with NICU practitioners will evaluate the model's effectiveness and guide refinements for optimal training outcomes. With refinement, this tool could become a vital NICU resource, ensuring high-quality neonatal care everywhere.

This literature review explores the effects of inclusion in general education classrooms on the academic outcomes of special education students, comparing the effects of inclusive settings to segregated, self-contained classrooms. Inclusion, as an educational philosophy, seeks to provide equitable opportunities for special education students by integrating them into mainstream classrooms. This review consolidates evidence from recent studies evaluating both the benefits and challenges associated with this approach. I conducted a comprehensive literature review to identify relevant studies examining the effects of inclusion on the academic outcomes of special education students in general education classrooms. I performed a search across multiple academic databases, including Google Scholar and PsycINFO. I reviewed studies that specifically addressed the academic outcomes of special education students in inclusive versus segregated settings, including only peer-reviewed articles and dissertations to ensure credibility. While findings demonstrated significant improvements in academic performance in math and English Language Arts (ELA), there were reports of modest, non-significant effects on language literacy, with high variability across studies. Additionally, positive academic growth for students during and after special education services were observed, emphasizing lasting improvements in math and reading achievement post-exit from special education programs. Limited academic improvement for special education students transitioning from pull-out services to inclusion raised questions about the consistency of inclusion's benefits across different educational contexts. Overall, this review highlights that the success of inclusion depends on context, teacher attitudes, and individual student needs. While academic gains in inclusive settings are evident in some cases, particularly in standardized tests, other domains are less consistently observed. The findings underscore the need for continued research to refine inclusion strategies and tailor them to maximize academic outcomes for special education students.

Non-fatal firearm injuries significantly outnumber fatal ones, yet research of acute rehabilitation for these injuries remains sparse leading to disproportionate effects on marginalized populations. The goal of this study was to characterize the use of inpatient rehabilitation (IPR) after firearm-related injury in local and nationwide samples. I hypothesized that patients who suffered from gunshot wounds (GSWs) and are transferred from acute hospitalization to IPR (referred to as the GSW IPR population) have greater injury severity compared to other traumatic injuries. Injury severity was assessed using three metrics: Injury Severity Score (ISS) total length of stay (LOS) at the hospital and Intensive Care Unit (ICU LOS). Additionally, we sought to evaluate associations between patient demographics—age, primary insurance type, race—and the frequency of discharge to IPR due to GSWs. Patients were identified locally from the Harborview Medical Center (HMC) Trauma Registry, and nationally, using the Trauma Quality Improvement Program (TQIP) database with deidentified patient records from over 700 participating Level I-V and undesignated trauma centers. R statistical analysis displayed both HMC and TQIP samples having a much higher ISS, LOS, and ICU LOS for GSW IPR patients compared to other traumatic injuries, supporting my primary hypothesis. Demographic data also revealed GSW IPR patients were more likely to be younger, and insured by Medicaid for both sampled. Interestingly, national data showed that patients with a GSW were less likely to discharge to IPR, and more likely to be Black or Hispanic, while local data concluded opposite findings, with GSW patients being more likely to discharge to IPR, and no significant racial association to IPR frequency. This study raised questions regarding the variability between regional and national health outcomes, and allowed us to assess demographic disparities and potential gaps in accessibility to rehabilitation services after fire-arm related injuries.

The city of Seattle is implementing a 1-year pilot of new surveillance technology including closed-circuit television (CCTV) cameras, new real-time crime center (RTCC) “software technologies”, and automated license plate readers (ALPR), in three target neighborhoods to reduce crime. Our research seeks to understand the details of the pilot’s implementation, reasoning behind chosen neighborhoods, and resulting impact on crime and the communities. Preliminary results show that the neighborhoods chosen for the pilot may not have the highest crime rates in Seattle. I am conducting sentiment analysis on various online communities’ discussion of different Seattle neighborhoods to understand how neighborhood perceptions compare to crime rates. Additionally we are conducting user studies to directly inquire about residents' comfort with and desire for different surveillance technologies. We also are building a device to detect ALPR sensors to understand the extent of their coverage across the city and density within targeted neighborhoods. We anticipate that the reduction in privacy experienced by these communities will lead to feelings of diminished safety rather than additional safety afforded by the technology. The results of our research can be used to modify the implementation of the technologies to address concerns by residents.

A microclimate is a relatively small area wherein temperature, humidity, and sunlight differ significantly from the surrounding macroclimate. Though there is a broad assumption of microclimate variation in greenhouse environments, there is little formal data quantifying this variation. Additionally, in the service of scientific rigor and productive efficiency, plants are often placed together at high density, but there is a lack of research on the impact of plant spatial density within the greenhouse environment. To assess greenhouse microclimate variation, I am investigating how climatic variables such as temperature, humidity, and light vary over the length of one table. In quantifying these variables, I am measuring photosynthetic photon flux density (PPFD), relative humidity, and temperature data from 11 sampling points. To quantify the effect of density on plant physiology, I am measuring stomatal conductance of Populus trichocarpa over four different density treatments. I am also measuring relative humidity and temperature within and above each experimental setup. Treatments include high, medium, low, and zero density. I expect to see considerable variation in light and humidity within the greenhouse, as fading lights and an evaporative cooling system create very heterogeneous conditions. I expect plant density to have a small effect on stomatal conductance as climate control likely has a larger effect on variables like CO2 and light availability than plant density alone. The findings of this research have the potential to uncover useful insights into microclimatic variation with applications in the horticultural, agricultural, and forest product industries.

Northern Australian landscapes are dominated by termite mounds, raising questions about how these insects might have bioturbated local archaeological sites. In this research we aimed to investigate termite bioturbation at Madjedbebe, Australia’s oldest archaeological site, located in the Northern Territory. We analyzed stone artefact data from Madjedbebe to investigate possible clustering of artifacts, which could have been influenced by termite activity. Specifically, we explored the following questions: Do mass distributions of lithic materials within each of the phases at Madjebebe reflect a non-uniform redistribution associated with termite bioturbation? How does this affect the reliability of the earliest occupation date of Australia? To address these questions, we visualized trends in artifact location and mass in the strata to evaluate artifact size-sorting in each phase as well as within excavation squares B2, C2, and C6. We contextualized our findings using previous experimental and observational research on termite bioturbation to robustly assess the extent of disturbance caused by termites at Madjedbebe. On both site-wide and excavation square levels, we did not find any significant trends that reflected clustering patterns. Thus, we found that mass distributions do not corroborate size sorting at Madjedbebe. This research will contribute to our broader understanding of termite effects on sites in Northern Australia and help with assessments of the validity of dated artifacts at Madjedbebe, enriching our knowledge of the earliest known human activity in Australia.

Parkinson’s disease (PD) is a neurological disorder that affects patients’ movement, balance, and coordination, primarily due to the death of dopaminergic neurons. Traditionally, researchers use MPTP, a neurotoxin that destroys dopaminergic neurons, to replicate the motor symptoms of PD. However, this approach captures the later stages of the disease, making it difficult to develop early stage interventional treatment with this model. There is a long prodromal, or early, phase of PD, in which neuronal cells and circuits are changing before the neurons die and cause overt motor symptoms. A critical gap exists in our understanding of the early progression of PD due to the lack of robust primate models of this phase of the disease process. In an effort to create a prodromal phase model of PD, we made intrasnasal and intracranial injections of a pathological form of the protein alpha-synuclein (aSynPFFs) extracted from human PD patients, and used it in macaques. We quantified the motor changes in macaques using a modified version of Unified Parkinson’s Disease Rating Scale (UPDRS), which has 14 categories that each define a movement function of interest scaled from 0 to 3 (no symptom to highly impaired). To improve the detection of the changes, we used a deep learning software called DEEPLABCUT (DLC) to track the subtle motor changes seen in the macaques after exposure to aSynPFFs. By using quantitative approaches to assess motor function before and after aSynPFFs exposure, we hope to establish a timeline of neurodegeneration associated with PD in primates. Such a model would provide an important platform to assess therapies to halt neurodegeneration associated with PD.

Microbial bioproduction supports the manufacturing of sustainable chemicals but requires accurate and easy-to-use tools for monitoring cell growth. A simple and effective tool for estimating cell concentration in aqueous systems is optical density (OD). However, commercially available OD measurement systems are expensive and require manual sampling, which is time-consuming and disrupts culture growth, particularly in anaerobic microbes. To address this, I developed a low-cost OD sensor for continuously monitoring anaerobic bacteria in culture tubes. The sensor design, based on Deutzmann et al. (2022), consists of a 3D-printed sample holder with an LED and a photosensor positioned on opposite sides. The photosensor generates a voltage, which a Python script processes to calculate optical density values for each bacterial species. Plotting these OD values provides researchers with insights into bacterial growth behavior and enables optimization of culture conditions. This device's advantage over commercial spectrophotometers is that it can measure optical density directly from sealed culture tubes, eliminating the need for manual sampling into cuvettes and saving researchers valuable time. It can be configured to run autonomously, further minimizing measurement time and disruptions to bacterial growth. Additionally, the design is fully open-source and customizable while costing less than $100 to reproduce, making it accessible for a wide variety of lab setups. Overall, this low-cost, open-source OD sensor offers a practical, efficient, and customizable solution for continuous monitoring of anaerobic bacterial growth, making it a valuable tool for research laboratories.

Impervious surfaces associated with urban development cause increased runoff intensity during precipitation events. Green stormwater infrastructure such as rain gardens and bioswales can increase retention capacity, slow down runoff, and reduce flooding. Understanding the hydrologic impacts of onsite factors can elucidate whether or not the green infrastructure mitigates flooding. This study aimed to quantify the hydrologic effects of these rain gardens and bioswales at a community garden in Kent to understand if the gardens helped mitigate flooding issues in this area using a combination of onsite data collection and high resolution stormwater modeling. To achieve this, we compared the current condition to the previous higher impervious surface coverage condition. Probes monitoring water depth, conductivity, and temperature inside three storm system sumps were deployed on site, as well as rain gauges to cross reference with rainfall data obtained through NOAA radars. The previous condition was modeled using publicly sourced LiDAR data produced before the construction of the rain garden to create predictive simulation models of the hydrologic characteristics of the site when it was covered with a larger proportion of impervious area. This comparison elucidates the impact of this community garden on the local urban hydrology and flooding issues of the area, which can inform future management and stormwater mitigation decisions. 

Self-initiated mobility has multi-faceted implications for early development, influencing cognitive, social, and physical growth. Children with Down syndrome experience delayed motor milestones—learning to walk much later than their neurotypical peers—potentially resulting in a delay of their overall development. Currently, limited research describes the impact of mobility aids on the muscular development of young children, particularly those with Down syndrome. Our study aims to address this gap by comparing and analyzing muscle activation patterns in children with Down syndrome aged 12-36 months,  both with and without mobility aids. I hypothesize that mobility aid use will result in an increase of muscle activation during play. Participants engaged in 30-minute exploratory play sessions in an enriched environment with and without mobility aids. During these sessions, data was recorded using surface electromyography sensors on the legs. The data was then analyzed to identify the nuances in muscle activation across different methods of movement—both aided and unaided. Preliminary results show that muscle activity may be similar regardless of the use of mobility aids. By identifying key muscle movement patterns, this analysis could inform future designs and protocols for motor skill development in all children, including those without Down syndrome. These findings could have implications for physical therapy and the recommendation of mobility aids for pre-ambulatory young children.

Liposomes are synthetic vesicles composed of phospholipids that are used as both a model biological membrane and drug-delivery system. Doxil® is a widely used liposome-based chemotherapy drug used to treat ovarian cancer, multiple myeloma, and Kaposi’s sarcoma. Liposome stability affects drug-delivery efficacy. Cholesterol is a key component of membranes that has been shown to regulate membrane fluidity, permeability, and overall structure. Electrostatic interactions between phospholipid headgroups also can impact liposome stability and are impacted by buffer conditions. While it is known that inclusion of cholesterol and electrostatic interactions can impact liposome stability, how these changes influence membrane structure and stability is poorly understood. Cryo-electron tomography (CryoET) is an electron microscopy technique that produces high resolution 3-dimensional images of macromolecular structures, allowing detailed visualization of lipid bilayers and membranes. Cryo-ET can be used to preserve native hydration of membranes in order to maintain lipid organization. Using Cryo-ET, we plan to study how inclusion of different cholesterol concentrations and phospholipid compositions can influence membrane architecture and stability. We hypothesize that we will be able to directly visualize and analyze structural changes in membrane leaflets and membrane fine structure, which will enhance our understanding of lipid membrane architecture. An in-depth understanding of how cholesterol concentrations in liposomes under various buffer conditions influences membrane architecture will provide insight into how these factors directly impact membrane architecture and thus liposome stability. This knowledge is crucial for optimizing liposomes as drug delivery systems, improving their stability and efficiency, and enhancing their use as model membranes for studying biological processes.

We present a novel evaluation framework designed to reveal whether Large Audio Language Models (LALMs) truly understand speech or merely exploit acoustic patterns across languages. Our goal is to understand the robustness of current state-of-the-art LALMs across different categories of audio tasks that could either be dependent on either acoustic and semantic features or both. Some of these tasks would include common speech tasks (keyword, intent, emotion detection) and non-verbal tasks (sound interpretation, acoustic scene reasoning). To expose current LALM failures, we will synthesize adversarial speech and non-verbal sounds that potentially achieve high performance through pattern matching rather than holistic audio comprehension. Through systematic testing of LALMs like Qwen2Audio, Salmonn, WavLLM, and Gemini we demonstrate that current evaluation frameworks inadequately assess genuine audio understanding - models can be reliably manipulated into achieving high performing on audio tasks through simple acoustic modifications, despite the absence of semantic content.

Since 2020, the median sale price of homes in Seattle has risen by approximately 30 percent (Redfin, 2025). Additionally, median rental prices in Seattle averaged around $2000, 37 percent higher than the national average (Zillow, 2025), placing financial burden on some renters and homeowners, and leaving some unable to continue to afford their homes. The rising cost of housing is largely the result of a deficit in housing supply, which does not meet Seatttle’s demand. As of March 2023, King County constituted a third of Washington State’s total deficit (Washington State Department of Commerce, 2025). A major consequence of the housing shortage is displacement. As prices continue to rise, many people find themselves in financial positions where the only option is to move. Seattle housing policy is in a state of flux. Washington State’s Middle Housing Bill (HB 1110), Seattle’s newly proposed Comprehensive Plan, and other ongoing legislative efforts create avenues towards previously unexplored housing preservation, development, and anti-displacement strategies. As displacement is difficult to directly measure, our literature review seeks to evaluate the effects of housing policy on displacement proxies, variables correlated with displacement, and compares those findings with Seattle’s current housing policies. Our research focuses on three categories of housing policy: Housing Production, Housing Stabilization, and Affordable Housing Preservation. Our review shows that stabilization strategies have immediate effects on displacement proxies, and may be the best short-term solution to displacement in Seattle. We highlight policies that both mitigate key correlates of displacement.

The project aims to engineer a new µMASS sensor with increased baseline fluorescence and improved dynamic range by applying linker optimization and subsequent high-throughput screening. µMASS is a genetically encoded fluorescent indicator that, when bound to an opioid, changes conformation, causing an increase in fluorescence intensity. µMASS is a tool that enable real-time imaging of opioids in the brain, allowing researchers to study neural pathways involved in addiction. While the sensor can detect opioid ligands in vitro, it requires optimization for use in vivo to study real-time opioid release. Linker optimization is a technique that involves introducing mutations into the linker region of the sensor. I hypothesize that mutating the linker residues will enhance the conformational change observed in µMASS-5-HT upon opioid binding while retaining enhanced baseline fluorescence.

The 20th century in America was one marked and shaped by the United States’ relationship with the Soviet Union. As communist ideology grew globally after the Bolshevik Revolution, U.S. leaders like Woodrow Wilson responded in turn with hardline, restricting government action domestically that sought to uproot the same growth from within. The “Red Scare” would be a small preview of the much larger and greatly more draconic response to the growing global influence of the Soviet Union post-World War 2, which is now known as the Second Red Scare, spearheaded by former FBI Director J. Edgar Hoover and often attributed to Republican Senator Joseph McCarthy. However, it has been commonly acknowledged that this action often took the form of drastic government overreach, to the extent of damaging the rights of anyone involved with radical ideologies. The groups affected most by anti-communism were organizations of the working class. This research seeks to examine the way that workers were oppressed by anti-communism through a literature review of historical and legal analyses, and re-contextualize this history from a modern perspective to draw attention to its long-lasting effects. Research has discovered that labor movements were dramatically weakened due to the removal of critical support from radical groups, legislation restricting union actions under the guise of punishing unfair labor practices, and the assimilation of effective unions into larger state-sponsored unions that posed less of a threat to government and corporate interests. Despite the aforementioned wide acknowledgment of these issues and the way they have shaped labor history, the issue is largely not considered currently, and sufficient efforts have not been made to restore the power taken from workers in America. Further research will critically analyze modern labor events and establish connections to prior damage to labor movements.

Current at-home, minimal cost viral test kits are often limited to human-visible (colorimetric) readout methods which lack the same sensitivity achievable in laboratory settings that use complex equipment. We aim to develop a more accessible alternative by leveraging smartphone touchscreens to detect viral presence. Touchscreens emit an electrical field that changes when conductive materials interact with them. DNA has been shown in prior work to exhibit conductive properties based on its negative charge. Our approach utilizes a DNA replication reaction involving a thermostable polymerase, primers, dNTPs, and viral RNA as a template. If the template is present, amplification occurs, altering the capacitive response compared to a negative control. To validate this, we are testing the reaction on a vector network analyzer (VNA), measuring capacitive output changes directly on the sensor. We are also building and testing low-cost temperature controls to enable isothermal amplification. With the use of a Peltier heater, a temperature control sensor, we aim to speed up the reaction times and the use of a Pulse Width Modulation (PWM) power control system to ensure consistent reaction temperature. We are currently comparing active polymerase reactions to controls and plan to eventually transition these tests onto phone screens, creating a cost-effective, widely available diagnostic tool.

Obstructive sleep apnea (OSA) in children is linked to early life viral infections and increased severity of viral respiratory illnesses. As respiratory viral infections occur in airway epithelial cells, we investigated differences in viral responses using an organotypic epithelial cell model in children with OSA as compared to children without. We hypothesized that gene expression in response to rhinovirus (RV16) infection would differ between healthy children and children with OSA. Primary airway epithelial cells (AECS), from both healthy pediatric donors and children diagnosed with OSA by polysomnography, cultured at an air-liquid interface, were infected with RV16 on the apical surface at a multiplicity of infection of 0.5. RNA-sequencing quantified gene expression at baseline and after RV16 infection. Limma was used to identify genes with differential expression post-infection in healthy AECs as compared to AECs from donors with OSA. Weighted gene co-expression network analysis (WGCNA) was able to organize the identified genes into groups of interest. Using Enrichr, the primary biological functions of the gene groupings were analyzed. Following infection, 122 genes were found to have differing gene expression responses to RV16 in OSA when compared to healthy cell lines. WGCNA identified two modules of gene expression with opposite expression patterns following infection in OSA compared to healthy. One module consists of 43 genes enriched for glycogen metabolism which are downregulated in healthy but upregulated in OSA following infection. A second module consists of 23 genes enriched for DNA repair and replication which are upregulated in healthy but downregulated in OSA after infection. Epithelial cell gene expression differs in response to RV16 in healthy AECs as compared to AECs from children with OSA. Given the small sample size, further studies are needed to investigate the relationship of OSA severity and clinical phenotypes of OSA with epithelial responses to viral infection. 

Tattooing is an ancient practice with many different significances and cultural meanings across time and space. However, there has been a lack of research on the relatively common themes of transformation and healing that emerge from the ritual of tattooing. This presentation is part of an ongoing research project investigating how tattoos are part of transformative healing processes. By conducting literature review and qualitative analysis of semi-structured interviews with participants who had tattoos they identified as healing, I identified three (3) frameworks of tattoos that commonly hold healing significance: 1) biomedical tattoos, (such as those used for radiology treatment), 2) paramedical tattoos, including scar camouflage and decoration (for example those after mastectomies), and 3) those that promote abstract healing, focusing on mental health and grief. This research thus shows how tattoos contribute to a transformative healing journey, and how these frameworks of tattoos differ in their symbolism and healing significance. I argue that tattoos of all types are inherently transformative, though the subjective dimensions of such transformation varied immensely. I also found that each recipient’s healing journey is personal, specific, and complex. Furthermore, the process of receiving, healing, and wearing a tattoo indexes healing cosmologies and practices, demanding self-reflection, agency over one’s body and life, undergoing physical pain, self-care, and ultimately, transformation. 

Tame knots, which are equivalent to a polygonal knot with a finite number of sides, have well-studied invariants; conversely, wild knots that exhibit infinite and pathological behavior are difficult to study and classify. Knot mosaics, introduced by Lomanoco and Kauffman, are an example of a complete invariant for tame knots. Our project aims to expand the existing formal system of knot mosaics to develop an invariant for wild knots. We define n-singular mosaic tangles, the mosaic analog of tangle insertions in pseudoknots and singular knots, and we formalize a system of infinite insertion that generates a wild mosaic to represent certain wild knots. We also intend to define wild mosaic equivalence moves to capture the notion of wild knot equivalence in the mosaic setting. This gives insight to many wild knots explored in existing literature and provides methods to generate and classify new examples.

Syphilis remains a serious global health concern, underscoring the need for better control strategies. In the absence of treatment, the syphilis agent, Treponema pallidum subsp. pallidum (T. pallidum), can persist for the lifetime of the host and syphilis can progress to its later stages. To combat the increase in syphilis incidence, doxycycline post-exposure prophylaxis (doxy-PEP) can be used to reduce the likelihood of infection with T. pallidum. However, the widespread use of doxy-PEP raises concerns about the possibility that this pathogen might become resistant, as seen in the past when azithromycin was used to treat syphilis. We wanted to explore whether continuous in vitro exposure to doxycycline could induce resistance in T. pallidum. To test our hypothesis, cultures of T. pallidum Nichols or SS14 strain were exposed to either increasing concentrations of doxycycline, azithromycin, or grown without antibiotics. Darkfield microscopy (DFM) was used to quantify the treponemal yield in cultures weekly. DNA was also extracted from T. pallidum cultures to evaluate bacterial presence by PCR, targeting the tp0574 gene. We found no sign of doxycycline resistance in T. pallidum SS14 cultures. Darkfield microscopy counts were detectable for up to three weeks in Nichols, whereas they lasted for five weeks in SS14. DNA extractions and PCR analysis showed no significant differences between strains, suggesting that albeit no strain developed resistance, one might be intrinsically more tolerant to the antibiotic. The results from this research provide encouraging evidence that T. pallidum may not easily develop resistance to doxycycline.

The Jewish people span international and political borders in a widespread diaspora. Today, many Jewish people worldwide oppose Zionism and the existence of the nation of Israel due to religious, cultural, moral, and philosophical reasons. How was this opposition founded, and what can be learned from it? In essence, what is the early history of the anti-Zionist movement in the Jewish community? This literature review examines the shared histories of Eastern European and American Jews to explore this organized Anti-Zionist Judaism, through analyzing and comparing accounts and articles detailing the major groups, ideologies, and figures of the movement. I use this historical information to create an organized synthesis of events and locations that are especially significant to the development of the current anti-Zionist Jewish movement, revealing its roots in organized struggle. I focus on the years 1897-1948 and organizations at the forefront of this movement like the General Jewish Labor Bund in Lithuania, Poland and Russia and the American Council for Judaism. I further explore how this history has led to the current modern reality of anti-Zionism in Judaism. This literature review uncovers a rich history of the early Jewish anti-Zionist movement, supporting the conclusion that the current Jewish-led anti-Zionist movement is neither unfounded nor a sudden development. This finding suggests a precedent for further Jewish-led organized labor parties and anti-Zionist organizations to draw upon the history set by the earlier anti-Zionist groups to organize more effectively and affirm the legitimacy of their movement. Looking to the future, research conducted by any person, whether that be Zionists, anti-Zionists, or unaffiliated groups and individuals, can use these findings to better inform their understanding of accurate anti-Zionist history and improve the understanding of anti-Zionism today.

Environmental mechanical stress within a biological system is integral to proper cell fate, function and disease. These complex processes are affected by mechanotransduction, or the transfer of mechanical stimuli into biochemical signals. This occurs through the activation of mechanosensor proteins which transduce physical signals to the nucleus, leading to the activation of certain genes and cellular remodeling. Commonly used 2D cell culture techniques fail to replicate these forces, and are thus unable to activate mechanotransductive pathways seen in vivo. We have developed a method to apply physical stresses to 3D tissue models for investigating how these pathways impact functionality of the human physiological microenvironment. Our method was inspired by methodology created previously by our lab known as STOMP (suspended tissue open microfluidic patterning), which uses surface forces to pattern 3D hydrogel-based culture models. We use our method to create a cell-laden hydrogel suspended between two rows of disconnected rungs, referred to as tissue hooks. The hydrogel can then be transferred to a secondary device, where it is stretched to varying degrees, generating mechanical stress on the tissue. We use confocal fluorescent microscopy to observe cellular remodeling and use image analysis techniques and qPCR to quantify the activation of mechanotransduction pathways. While it is important to investigate how static mechanical stress on tissue impacts functionality, the human body is a dynamic environment. We created a system to dynamically stretch tissue cultures to further investigate cellular contractility within 3D tissue models. Instead of a static stretch, the cell-laden hydrogel is patterned to hooks with serpentine-style springs on the side. As the cell embedded hydrogel compacts, it pulls on the springs, allowing us to quantify the contractile forces. We plan to apply these models to study highly contractile tissue, such as skeletal muscle, and subsequent disease pathways shown in mechanotransduction.

The King County Brightwater Treatment Plant includes two twin outfall pipes that were installed in 2012, and discharge approximately 36 million gallons of highly treated effluent into Puget Sound daily. After observing colonization of the pipes by marine organisms, King County biologists launched a ten-year study examining the impact of effluent discharge on motile and sessile species on and near the outfall over time. They placed plates of the pipe material, high-density polyethylene (HDPE), on the seafloor, with replicates near the effluent discharge diffusers and approximately 300 ft away. King County retrieved the replicate plates after 2, 5, and 10 years and, photographed each plate for subsequent image analysis. In this study, we analyzed the photos to investigate whether there was a measurable effect of effluent discharge on the abundance, identity, and size of organisms colonizing the plates. We concluded that effluent discharge likely does not affect percent live cover, number of taxa, or the identities of taxa present. However, some motile species may be more abundant in the absence of effluent discharge, and there may be some effect of effluent on the size of some species. These abundance and size differences are worth further investigation as they may indicate that, although highly treated, effluent discharge from the Brightwater Treatment Plant impacts some species' demographic rates, like survival and growth rates, and the water quality of the Puget Sound. Our results indicate that even highly treated effluent impacts the surrounding water and the species that depend on it and that further research is needed to fully investigate the impacts of wastewater discharge in the Puget Sound ecosystem.

Functional assays on intact tumor biopsies play a key role in drug testing, personalized oncology, and cancer research by allowing scientists to better characterize tumor biology. However, these assays usually rely on antibody-based fluorescent labeling. Fluorescent labeling, while well-researched and reliable, is labor-intensive, semi-quantitative, and cannot provide real-time data. In this project, we designed and created a sensor that addresses these issues by using electrochemical aptamers. Our sensor features a 24-well, multiplexed electrochemical setup that detects concentrations of Cytochrome C (CytC), a cell death indicator, with high affinity and specificity. We found that we were able to quantitatively track increasing CytC concentrations in real time as microdissected tumor samples were being treated with various cancer drugs. In the future, this sensor could be expanded to work with more biomarkers, paving the way for clinical use, real-time tumor response monitoring, and high-throughput oncology drug screening.

G proteins play a vital role in regulating neuronal activity by acting as key intermediaries that relay extracellular signals inside the cell, triggering a cascade of further signaling events that impact cellular function. This signaling can modulate the activity of ion channels in the neuronal membrane, which control membrane excitability by opening or closing in response to signals, thereby affecting the cell's electrical potential. We are studying the signal transduction pathway that acts downstream of the heterotrimeric G protein Gq to regulate the NCA cation channel in Caenorhabditis elegans. My project focuses on characterizing an unidentified mutant yak133, which has a distinct phenotype defined by deep body bends, also referred to as "loopy." This phenotype suggests that yak133 could be connected to Gq signaling, as activating the Gq pathway leads to a loopy phenotype. The goal of my project is to identify the gene affected by yak133 and understand how it functions to modulate the NCA channel. I narrowed down a list of candidate genes from whole genome sequencing of yak133 by performing a genetic cross to deficiency strains that lack a specific segment of DNA. I then carried out a forward genetic screen and identified a new recessive mutant, yak193, which appears to affect the same gene. I am currently preparing this strain for genome sequencing, and by analyzing both mutants, I expect to identify the gene affected by yak133 and yak193, as they should share mutations in one gene in common. This work will provide relevant insights into the molecular mechanisms regulating neuronal activity and how disruptions in this pathway affect motor and behavioral function. Since many of the genes in C. elegans are conserved in humans, these findings could have broader implications, potentially advancing our understanding of human neuronal function and related disorders. 

There is a crucial need for a vaccine that produces a robust immune response against Human Immunodeficiency Virus (HIV), particularly for those without access to effective treatments. We investigated the immunogenicity of a novel self-amplifying RNA (RepRNA) vaccine for HIV in non-human primates (NHPs). RepRNA vaccines encode subgenomic sequences that enable the self-amplification of additional copies of RNA, inducing strong immune responses with lower doses of RNA. The repRNA was formulated with a lipid nanocarrier called LION (HDT Bio), which protects the RNA from degradation and enables its delivery into the cell. This platform has shown success in a licensed SARS-CoV-2 vaccine, suggesting it may be similarly promising as an HIV vaccine. I aim to evaluate whether the RepRNA/LION vaccine can elicit robust systemic and mucosal responses in NHPs. I hypothesized that the vaccine would increase HIV-specific T-cell responses in PBMCs and induce HIV Env-specific antibody production in nasal and rectal secretions. To investigate the immunogenicity of this vaccine, we vaccinated twelve cynomolgus macaques, divided into three groups, with HIV Env and/or HIV Gag-Env. To determine vaccine efficacy, I measured the frequency of antigen-specific T-cells in blood using interferon-gamma (IFN-γ) Enzyme-Linked ImmunoSpot (ELISpot) assays because activated T-cells secreting IFN-γ help eliminate infected cells. I also assessed HIV Env-specific Immunoglobulin A (IgA) levels in nasal and rectal secretions using Enzyme-Linked Immunosorbent Assays (ELISAs) because IgA is key in neutralizing pathogens at mucosal surfaces. My preliminary results show an increase in IFN-γ production after the first vaccination, which indicates a systemic antigen-specific T-cell response. We will continue to run assays to see if further vaccination doses can induce more robust immune responses. Results from this study indicate that the RepRNA/LION HIV vaccine may be a promising approach to induce mucosal and systemic immune responses against HIV.

Key drivers for primary productivity vary on latitudinal scales, such as nutrient and light. Nutrient variation can be seen at differing latitudes, such as lower nitrate to phosphate concentrations in the tropics (23°26’N to 23°26’S) compared to higher nitrate to phosphate concentrations in temperate regions (35° to 50° N and S) (Lønborg et al., 2021). With consistent differences by latitude of nutrient concentrations and abundance, it prompts the question of whether a nutrient-dependent entity such as phytoplankton biomass can be attributed to latitude change. To determine a correlation between nutrient availability and phytoplankton biomass, limiting nutrients and nutrient variations by latitude were investigated within the mixed layer determined by thermoclines from 4°N to 16°N along 149°E in Guam. The limiting nutrient of phytoplankton biomass was determined using on-deck incubators consisting of three conditions: + 1uM nitrate, +0.2uM phosphate, and a control with no added nutrients. Total chlorophyll served as a proxy for phytoplankton biomass, and was measured for three incubation sets from three different sampling stations. Nutrient concentrations were collected at every degree from 4°N to 16°N and compared by latitude to determine a relation between nutrient variability to latitude. Chlorophyll rate of change and mean total chlorophyll from nitrate incubations were significantly greater than phosphate and control incubations, pointing to nitrate as the limiting nutrient of primary productivity. No statistical correlation was established between nutrient variability and latitude, but there was a statistical correlation between size-fractionated chlorophyll and N:P ratios at the same latitude, signaling a latitudinal correlation. I hypothesized that the intensity of bottom-up control on primary productivity will increase with increasing latitude across a ten degree transect due to concentration variation of the limiting nutrient of chlorophyll.

This project examines community-driven strategies for preserving shoujo and josei manga, genres created for young and adult women by female manga creators. Despite their significance in representing gender and identity, these works face archival neglect due to institutional bias, lack of preservation funding, and limited institutional recognition of female manga creators’ contributions. This research investigates how non-professionals can contribute to preserving and ensuring access to these materials through community-driven and hybrid archival models. Through a comparative analysis, I assess how community-driven archives preserve marginalized media with greater flexibility and inclusivity than traditional methods. I also conduct case studies of successful archival models and interview archivists and contributors to evaluate strategies for collection management, accessibility, and sustainability. My findings will outline a scalable, community-integrated archival framework that balances professional preservation standards with participatory engagement, ensuring the long-term accessibility of shoujosei manga. This project is the foundation for my forthcoming Fulbright Scholarship in Japan, where I will apply these strategies to develop a shoujosei manga archive. My findings will contribute to preserving female manga creators' artistic and historical legacies.

The Hedgehog signaling pathway is essential for embryonic development. Errors in the Hedgehog pathway can cause limb, heart, and left-right patterning defects. However, Hedgehog signaling also plays a crucial role in the regeneration and maintenance of adult tissues and cells. Mutations in key components can lead to the constitutive activation of the pathway, leading to uncontrolled cell proliferation and cancer. Dysregulated Hedgehog signaling is associated with two major cancer types: basal cell carcinoma (skin cancer) and medulloblastoma (a pediatric brain tumor). To counteract this, small molecule inhibitors like Vismodegib have been developed to directly bind to and suppress the activity of the Hedgehog transducer, Smoothened (SMO). While Vismodegib is a potent inhibitor of Hedgehog signaling, mutations in SMO eventually lead to drug resistance and tumor relapse.The mechanisms underlying Vismodegib drug resistance and how the Hedgehog signaling pathway is reactivated in its presence remains unknown. To investigate these mechanisms, a constitutively active fluorescent Hedgehog reporter was knocked into the mouse skin cells, and a genome-wide CRISPR knockout (KO) library approach was used to generate a pool of gene-edited cells. Following treatment with the Hedgehog ligand Sonic Hedgehog (SHH) to activate the pathway and Vismodegib to inhibit it, fluorescence-activated cell sorting (FACS) was performed to sort the cells with high fluorescence to identify the KO cells that retained Hedgehog pathway activity after treatment with the Hedgehog inhibitor. This screen identified 10 novel genes associated with Vismodegib resistance. For further studies, I used a dual guide approach to generate knockouts of each gene respectively and clone them into CRISPR/Cas9 gene-editing vectors. My goal is to evaluate the expression of different Hedgehog genes using biochemical approaches. This would allow us to understand how each gene affects downstream pathway activity and identify the mechanism through which these genes could potentially impart drug resistance.

Tooth whitening is a rapidly growing sector in oral health, yet the interactions between chemical whitening products and the tooth microstructure remain complex and not fully understood. This study investigates how natural changes in the enamel microstructure and composition with age affect tooth whitening efficacy. Specifically, we are looking at the enamel of teeth from different age groups that are treated with the whitening agents potassium hydroxide (KOH) and bleach (NaOCl). Using Fourier Transform Infrared Spectroscopy (FTIR) and Raman Spectroscopy, we assess key compositional parameters, including organic-mineral ratios and carbonate-phosphate ratios, as both techniques reveal characteristic spectral “fingerprints” of enamel. Preliminary results indicate observable changes in the molecular structure of enamel post-treatment, emphasizing the need for balancing product efficacy with enamel preservation. This research not only advances tooth whitening technologies but also contributes to broader dental care practices for a range of ages, ensuring safer and more effective dental products for consumers.

Self-exploration and mobility are crucial parts of a child’s development. Young children with Down syndrome experience movement delays compared to typically developing peers. The use of mobility aids, such as gait trainers and orthotics, has been shown to support these children with increasing their mobility. However, there remains a distinct lack of research on children with Down syndrome’s use of mobility aids. Therefore, this study examines children’s exploration in the Permobil Explorer Mini, a powered mobility device meant to facilitate self-exploration. In particular, this study compared changes in exploration as measured by distance traveled when using an Explorer Mini with a standardized rigid seat and a dynamic soft seat. During play sessions their movement was tracked using synchronized video cameras and a region-of-interest movement-tracking algorithm. This data, combined with annotations from the sessions, was used to determine if there is a significant difference in exploration between the rigid and dynamic seats. I expect there to be a significant increase in distance traveled with the dynamic seat than with the rigid seat due to its increased flexibility, comfort, and adjustment for children. The results of this study will help to expand research on mobility aids in promoting self-autonomy for young children with disabilities. These results can also aid in improving future mobility aid designs to ensure greater comfort for the children using them.

Diabetes is characterized by hyperglycemia, which is exacerbated by the inappropriate storage and mobilization of hepatic glycogen. Incretin drugs, specifically GIP and GLP1 agonists, have been clinically successful. In the islet, GIP stimulates insulin and glucagon, while GLP1 stimulates insulin and inhibits glucagon production. Incretin receptors are not in the liver, suggesting that any effect of incretins on liver metabolism is through indirect islet hormone effects. Preclinical studies show the benefits of increasing hepatic glycogen storage in diabetes models, yet no drugs currently target this important source of carbohydrate metabolism. Therefore, my study aims to investigate how incretin drugs interact with hepatic glycogen stores to modulate islet hormone action. I hypothesized that increased hepatic glycogen will amplify islet hormone action and GIPR agonism will increase glycogen metabolism, while GLP1R agonism will have little effect on hepatic glycogen. I used hepatocyte-specific AAVs to overexpress the PPP1r3b protein in mice (PPP1r3bOE), resulting in a significant increase in hepatic glycogen compared to the control. Post-incretin injection (GIPR agonist, D-Ala2-GIP or GLP1R agonist, Ex4), I measured blood glucose and collected plasma to quantify circulating insulin and glucagon by ELISA. I collected liver to measure glycogen by glucose oxidase reaction and glycogen signaling intermediates by western blot. My results have indicated that GIP is less effective at glucose lowering in PPP1r3bOE compared to controls, while there is no effect on GLP1R-mediated glucose-lowering. This supports that elevated hepatic glycogen is likely altering glucagon action in response to GIP, with no effect on GLP1 action. I am currently analyzing plasma insulin and glucagon and will be assessing post-receptor insulin and glucagon signaling in the liver in response to GIP. This study will provide a better understanding of hepatic glycogen regulation, and offer an opportunity to investigate how incretin action can be optimized as a diabetes treatment.

CdCr₂X₄ and ZnCr₂X₄ (X = S, Se) spinels are ferromagnetic semiconductors, with reported bandgaps between 1.3-2.5 eV. With the advent of spintronic devices, a renewed technological interest in materials with coupled magnetic and optical properties has caused a resurgence in the study of these magneto-optically active spinels. Despite prevailing interest in their magnetic structure, the semiconductor luminescence of these materials is not well studied. We have prepared these materials in-house to study the magneto-optical coupling of this bandgap transition. We are also beginning to prepare these materials as nanocrystals for the first time as a way of accessing alloyed and shelled varieties. We started by synthesizing the non-magnetic In³⁺-based analogous sulfide and selenide spinels as nanocrystals, establishing a starting point to prepare the Cr³⁺-based spinels. We then introduced Cr³⁺ ions, which occupy the In³⁺ sites, into the lattice during the solution-phase synthesis. We aim to make the pure chromium-based nanocrystal spinels, along with a concentration range of Cr³⁺ ions in the In³⁺-based lattice. Our goal is to explore the relationship between the Cr³⁺ concentration gradient and the magneto-optical properties of these materials. We have characterized the composition and optical bandgap energies of these spinels with X-ray diffraction, photoluminescence, and UV-Vis absorption spectroscopy. We have begun tuning the bandgap energy of the nanocrystals by preparing mixed anion alloys with different ratios of Se and S ions (i.e. CdCr₂(Se_1-xS_x)₄; ZnCr₂(Se_1-xS_x)₄) and examining the bandgap shift with photoluminescence excitation spectroscopy. Future work includes utilizing magnetic circularly polarized luminescence (MCPL) to probe the magnetization of the lattice emission, letting us conclude how the optical properties of the semiconductor are coupled to its magnetism.

Visual perspective-taking (PT) is a fundamental spatial cognition task, requiring an individual to adopt another’s viewpoint. Previous experiments have shown that response times increase as the angular difference between viewer and reference perspectives grows. Preliminary fMRI results suggest that neural activity in specific brain regions follows a similar pattern, their activity increases as a factor of angular difference, reflecting the cognitive demands of mental perspective transformation. However, little is known about how eye-gaze behavior varies in this task. In this study, we analyze eye-tracking data collected during fMRI scans with an Eyelink 1000 to examine the relationship between gaze patterns and perspective alignment. Specifically, we investigate whether eye-gaze behavior differs between aligned and unaligned trials and whether angular difference influences gaze dynamics. Gaze coordinates (xpos, ypos) will be analyzed trial-by-trial to determine how visual attention is modulated during perspective-taking. Understanding these gaze patterns may provide insights into the strategies used in spatial perspective shifts and their neural underpinnings.

People experiencing homelessness are disproportionately affected by alcohol-related morbidity and mortality, with a 7 times higher prevalence of alcohol use disorder (AUD) than the general population. Past research shows that in-person harm reduction treatment for alcohol (HaRT-A) within Housing First facilities is preferred because it focuses on client-centered goals and improving quality of life. This study is a pilot study which is part of an ongoing project adapting HaRT-A into a digital platform (eHaRT-A), to assess the feasibility, usability & acceptability of the electronic harm reduction treatment for alcohol (eHaRT-A). Participants were recruited from low-barrier, permanent supportive housing.  Residents (N = 34) were interested in participating in the study. Participants (n=19), who were interested and eligible, first completed a 45-minute assessment questionnaire asking them about their substance use, quality of life, and pain. Then, they completed one eHaRT-A session, followed by a feedback interview. Recruitment and completion rates were used to assess eHaRT-A feasibility (i.e., percentage screened who expressed interest, qualified, and completed eHaRT-A). My teammates and I utilized self-report measures, including the Acceptability of Intervention Measure (AIM) and the System Usability Scale (SUS) to evaluate participants’ perceptions of eHaRT-A. A priori thresholds for high acceptability (AIM≥3/5) and usability (SUS≥ 70/100) were established. Among those eligible, 86.4% completed the full study, demonstrating high feasibility. The data we analyzed showed a mean AIM score of 4.45 and a mean SUS score of 81.2, indicating strong acceptability and usability.  eHaRT-A’s feasibility, acceptability, and usability, demonstrate its potential as a scalable, harm reduction intervention. These findings support the integration of telehealth interventions into supportive house programs, offering a promising approach to addressing health disparities and improving access to care for this vulnerable population.

The Traveling Salesman Problem (TSP) is a classic NP-hard combinatorial optimization task with numerous practical applications. Classic heuristic solvers can attain near-optimal performance for small problem instances, but become computationally intractable for larger problems. Real-world logistics problems such as dynamically re-routing last-mile deliveries demand a solver with fast inference time, which has led to specialized neural network solvers being favored in practice. However, neural networks struggle to generalize beyond the synthetic data they were trained on. In particular, we show that there exist TSP distributions that are realistic in practice, which also consistently lead to poor worst-case performance for existing neural approaches. To address this issue of distributional robustness, we present Combinatorial Optimization with Generative Sampling (COGS), where training data is sampled from a generative TSP model. We show that COGS provides better data coverage and interpolation in the space of TSP training distributions. We also present TSPLib50, a dataset of realistically distributed TSP samples, which tests real-world generalization ability without conflating this issue with instance size. We evaluate our method on various synthetic datasets as well as TSPLib50, and compare to state-of-the-art neural baselines. We demonstrate that COGS improves distributional robustness, with most performance gains coming from worst-case scenarios.

Neuroscientists have conventionally used enriched preparations of synaptosomes, or isolated nerve terminals containing particles such as synaptic vesicles and synaptic mRNAs, to study biochemistry in the brain and the physiological features of the synapses. However, the molecular diversity of the brain limits the ability to study specific types of synapses with conventional preparations. Here we present a synthetic protein “TAG”, comprised of PSD95Δ1.2, part of the postsynaptic scaffolding protein, guides the TAG construct to be recruited at the targeted synapse; an extracellular binding site that binds to a CD4 antibody to allow us to sort synaptosomes that express TAG, and intracellular mVenus green fluorescent protein for easy visualization. TAGed synapses provide a tool for scientists to more robustly investigate the biochemical properties of synapses by increasing signal over noise. My work was done to optimize a novel preparation method by isolating rare TAGed synaptosomes in the TAGxCAGGCre-ER mouse model. I induced conditional TAG gene expression by injecting tamoxifen into a TAG-crossed transgenic double-floxed inverted open-reading frame Cre mouse. I also optimized a new preparation method using a high-salt buffer, filtration system, bead conjugation, and magnetic separation to isolate TAGed synaptosomes. The product was the input of a series of Western Blots to assess the enrichment of TAG in sorted and pre-sorted samples. From my latest results, the CD4-sorted lysate showed significant enrichment in the GFP band, meaning the TAGed synaptosome has been purified. By replacing the CAG promoter in the TAGxCAGGCre-ER model, scientists can also use this method to target region-specific neuron subtypes and isolate rare synaptosomes. The precision and flexibility of the TAG construct allow scientists to observe subcellular connections with more specificity and allow for the discovery of biological mechanisms underlying neuronal diseases.

This paper investigates the impact of the benefits of the INDYC Program on the social determinants of health of immigrant children. Using the data extracted from the IPUMS CPS, I applied an event study - a dynamic difference-in-differences model with the combination of propensity score matching and inverse probability weighting to study the effects of IDNYC on immigrant children's access to public insurance coverages and affordable housing options. The analysis suggests that the benefits offered by the program could support immigrant children in gaining short-term coverage on the Medicaid and extended Medicaid Program, yet only positively associated with gaining long-term access to Medicare. The analysis also suggests a short-term increase in immigrant families' access to public housing and no cause-and-effect relationship with their access to government subsidies on rent. Lastly, similar to findings from previous papers, the effect of the program on health status remains ambiguous. Overall, the findings of this paper are consistent with previous research in the related field, contributing to the big picture of how municipal ID programs improve the social inclusion of immigrants in the North American region.

Auditory input, such as infant directed speech and music, is integral to childhood language development. However, existing research focuses primarily on examining monolingual English-speaking families, overlooking families of other cultures and languages. Hence in this study, I investigate the naturalistic auditory home environments of Latino and Hispanic infants in comparison with Pacific Northwest monolingual English speaking infants to better understand the differences in auditory exposure. This study uses audio data obtained from daylong recordings of Latino and Hispanic infants' home environments utilizing the Language Environment Analysis (LENA) technology. Infants wear the LENA recorder in a vest for up to 16 hours per day. The selection requirement for Latino/Hispanic infants is that at least one parent identifies as being of Latino or Hispanic origin. I randomly sample short snippets of recordings and upload them to Zooniverse, an online citizen science research platform, which allows volunteers to annotate for types of sounds (music or speech), its source (in-person or electronic), and target audience (infant-directed or not). I quantify the types of auditory input to compare it with an existing study of Pacific Northwest monolingual English infants to uncover differences and understand the impact that culture has on infants' language input and ultimately development.

Daniel Kevles’ The Physicists: The History of a Scientific Community in Modern America details how physics in academia, industry, and government became increasingly intertwined within the national security state. He focuses on members of the physics elite who gained political power within the federal government and orchestrated the militarization of the field. However, his emphasis on these elite physicists, who were predominantly white males, overlooks the labor of non-white physicists. Drawing on Cedric Robinson’s Black Marxism: The Making of the Black Radical Tradition, which outlines a racial capitalist framework recognizing the inherent racialization of American labor hierarchies and national imperial interests, this paper theorizes the function of Cold War-era physics within a racial capitalist political economy. Specifically, it examines how the military-industrial complex exploited domestic racial capitalist structures to wield Black scientific labor. Using archival documents and the American Institute of Physics (AIP) oral history interviews with Black physicists, this paper will argue that the national security state co-opted the goals of the Civil Rights Movement to bolster national scientific manpower, advancing Cold War-era imperial expansion while reinforcing racialized labor hierarchies within physics.

Intrinsic hand muscles and tendons are crucial for joint stabilization, fine motor control, and coordinating flexion—functions essential for performing dexterous tasks such as typing, grasping, and tool manipulation. However, monitoring strength and real-time activities remains challenging. Surface electromyography (EMG) struggles to isolate signals from interior tissue due to low signal-to-noise ratios. Devices like the Rotterdam Intrinsic Hand Myometer measure strength but are cumbersome for continuous monitoring. Electrical Impedance sensing offers a promising alternative. This technique passes a low-frequency electrical current through electrode pairs (injectors and receivers) on the skin and measures the resulting voltage changes to model tissue impedance. Through this approach, we can track and classify the activity of hand muscles and tendons in real-time, targeting the challenge of capturing signals within the hand. Our approach integrates a custom conductive fabric electrode array into a wearable form, such as a glove or a flexible bandage, to detect impedance variation with muscle contractions. These signals are processed through a regression-based machine-learning algorithm that predicts hand poses. A dynamic simulation further visualizes the motion and corresponding muscle activity, providing feedback on intrinsic muscle coordination. By offering real-time monitoring of deeper musculoskeletal dynamics, our system opens new avenues for analyzing muscle function and optimizing performance. Beyond research, this system can inform a range of applications—from enhancing human-computer interaction and prosthetic control to supporting personalized rehabilitation protocols. Looking ahead, we plan to optimize electrode designs for improved comfort and precision and to incorporate advanced machine-learning techniques for enhanced pose prediction. Through refinements, we aim to make EIS-based hand muscle monitoring a versatile tool for researchers, clinicians, and innovators across diverse fields.

Developing and validating new methods of enumerating species of concern is important for many conservation and management goals. Environmental DNA (eDNA) has shown potential to be a viable tool for obtaining non-invasive and cost-effective estimates of many organisms, including fishes in streams such as salmon. However, before eDNA can be used beyond an experimental basis, we need to understand how eDNA flows through small streams where salmon may spawn. This study aims to examine how sockeye salmon (Oncorhynchus nerka) eDNA is transported in small streams by collecting samples while ascending two morphologically unique streams. eDNA within each reach was analyzed against two measures: the abundance of salmon within each reach and cumulative abundance salmon above of the reach. Preliminary analysis suggests that eDNA is effectively transported to stream mouths when salmon are in high abundance. Moreover, eDNA does not accurately predict the abundance of salmon within individual reaches but corresponds more closely with the cumulative abundance of salmon above each reach, particularly when salmon are highly abundant. This closer alignment with cumulative salmon abundance is likely due to the cumulative nature of eDNA within streams.

Hearing loss is a prevalent disability that is commonly caused by damaged hair cells, which are mechanosensory cells critical for hearing and balance. Among the ways in which hair cells can die—including aging, genetic predisposition, and noise exposure—is damage due to ototoxicity, which is when medications damage hair cells. Aminoglycosides, a commonly-used family of antibiotics, is known to cause hearing loss in patients that undergo multi-day treatments. Our lab and others have shown that certain aminoglycosides (e.g. neomycin) can cause acute hair cell death, whereas other aminoglycosides (e.g. gentamtcin) kill in a more delayed manner. In the case of delayed hair cell death, it has been shown that these aminoglycosides accumulate exclusively in the lysosome, which is the organelle that contains digestive enzymes. It is thought that a lysosomal stress response contributes to hair cell protection through calcium release and then the recruitment of lysosome-membrane-repairing proteins known as ESCRTIII. In my project, I use zebrafish live imaging to elucidate if ESCRTIII proteins are recruited onto lysosome membranes in aminoglycoside-treated hair cells. First, I create a transgenic zebrafish line containing IST1-GFP in its genome. IST1 is a part of the ESCRTIII complex and serves as a biomarker to track where ESCRTIII proteins are active in a cell. If the aforementioned hypothesis is true, then in aminoglycoside-exposed hair cells, we expect to see ESCRTIII proteins localized around lysosomal membranes following lysosomal stress response and calcium release. Elucidating the lysosomal repair mechanism in the context of aminoglycoside exposure is valuable for understanding how hair cells could survive ototoxic conditions. In the future, it may be possible to harness ESCRTIII proteins to prevent hearing loss induced by ototoxicity.

Perfectionism is defined as “striving for flawlessness and setting exceedingly high standards for performance, accompanied by tendencies for overly critical evaluations” (Stoeber, 2011). It has become a growing topic in mental health research, particularly in understanding its impact on well-being for people of color. Among Asian Americans, cultural expectations, the “model minority” stereotype, and discrimination have been linked to increased depressive symptoms and perfectionistic tendencies (Suh et al., 2023). Given these high stakes, our research aims to understand how racial, ethnic, and cultural identities influence the views and experiences of perfectionism and self-compassion among Asian Americans. Using a grounded theory approach (Charmaz, 2006), we analyzed qualitative data from Asian American students at the University of Washington Bothell. We have conducted semi-structured interviews with five participants so far and anticipate collecting data from at least five more participants by the time of the presentation. Our findings reveal that Asian American participants often struggled with perfectionism in the past, largely driven by pressure from their immigrant families and the academic expectations of the model minority stereotype. Shaped by these experiences, perfectionism influenced their daily lives. Whether it was pressure to game efficiently, maintain high grades, or follow strict, regulated gym and eating routines, participants described perfectionism as wanting to optimize every aspect of their lives. However, many found healing through forgiving themselves, which we connected to a form of self-compassion. We aim to use this knowledge to help students develop stronger self-compassion techniques, ultimately improving their well-being and quality of life. Our study findings point to the need for future scholarship and practice on culturally sensitive counseling approaches that acknowledge how perfectionism can be shaped by cultural identity and other intersecting factors, allowing for more effective support and intervention.

The Pools Lab is investigating whether reducing tau expression can decrease seizure frequency in temporal lobe epilepsy (TLE). Tau is a microtubule-associated protein that stabilizes neuronal cytoskeletons, but its dysregulation has been implicated in neurodegenerative diseases and epilepsy. Tau dysregulation has been observed in epileptic brain tissue, and previous studies in genetic seizure models in mice suggest that reducing tau expression may decrease seizure susceptibility. However, this hypothesis has not been evaluated in the context of chronic TLE, which our study aims to explore using the pilocarpine rat model of TLE, which mimics chronic seizures in humans. To test this, we administered a CRISPR/Cas9 construct (AAV5-saCas9-sgTau) targeted at tau, injected unilaterally into the left hippocampus for tau knockdown. To assess knockdown efficiency, I performed western blot analysis on hippocampal tissue, comparing tau expression between the CRISPR/Cas9-tau knockdown and contralateral (control) hippocampus. This method allows for quantitative assessment of protein expression using tau-specific antibodies to detect site-specific changes. I then conducted densitometric analysis to quantify band intensities as a measure of tau levels and performed statistical comparisons, including a two-tailed t-test, to determine significant differences. Tissue collection of the CRISPR/Cas9 treated hippocampus versus the contralateral (control) hippocampus at 4 weeks post-injection showed a modest decrease in tau levels. Given tau’s estimated half-life of 23 days, we extended the timeline to 8 weeks to allow for further degradation of pre-existing tau. We predict that reducing tau expression will correlate with decreased seizure frequency, providing insight into tau’s role in epileptogenesis and seizure propagation. Given the heightened risk of neurological and cognitive impairments in epilepsy patients, this research has important implications for understanding tau’s contribution to disease progression and identifying potential therapeutic targets for chronic epilepsy.

This study explores the content and effectiveness of responses in suicide ideation subreddits, comparing human responses to those generated by Large Language Models (LLMs). Mental health discussions on online platforms such as Reddit provide crucial support for individuals in distress, and as AI tools like LLMs become more common, their role in these sensitive discussions needs to be evaluated. Using data from the r/SuicideWatch and r/depression subreddits from 2020, 2023, and 2024, I analyzed 150 human responses and 150 LLM-generated responses for emotional resonance, support styles, and contextual relevance. The findings revealed that human responses were more empathy-driven, often emphasizing emotional validation and shared experiences, while LLM-generated responses were more focused on providing practical advice. A semantic analysis showed that while LLMs aligned well with the contextual content of posts, they fell short in conveying the emotional depth and personal connection inherent in human interactions. This study highlights the strengths and limitations of AI-generated responses in mental health discussions, suggesting that while LLMs can assist in offering guidance, they are not yet capable of fully replicating the emotional complexity and personal understanding found in human responses. These findings will guide future research aimed at improving AI models to better simulate empathy in sensitive contexts such as mental health.

In HIV-1 vaccine research, “sieve analysis” evaluates the genetic differences in breakthrough viruses between vaccine and placebo recipients during efficacy trials. The HIV-1 envelope (Env) protein, comprising over 850 amino acids, poses a challenge due to its high dimensionality, increasing the likelihood of false positives when using standard statistical methods. Multiplicity adjustments lower the p-value threshold, making it difficult to identify sieve effects unless they exhibit strong signals. Our approach is a data-driven method to address this challenge, comparing the amino acid (AAs) distributions at Env sites from clinical trial breakthrough cases (“study sequences”) with publicly available Env sequences (“reference sequences”) from the Los Alamos HIV Sequence Database. I parsed the sequences using Biopython, a suite of tools for biological sequence analysis written in Python. Building on this, I developed software with Pandas, an open-source data analysis and manipulation package, to subset the viral sequences by subtype, geographic location, and time. With these subsetting functions, it allows me to generate a set of reference sequences which are of prior clinical trials (USMHRP RV144). From these prior clinical trials, I compared the Shannon entropy and Hellinger distance of the AAs at each site between the reference sequences and the study sequences from those trials. This method aims to refine establishing threshold for feature selection to identify sieve effect sites that may have been overlooked due to multiplicity adjustments. These thresholds could enhance the sensitivity of sieve analyses in ongoing and future trials (e.g., HVTN 702 and 706). Improving the identification of minor amino acid variations linked to immune evasion contributes to understanding the mechanisms viruses use to escape immune responses. These insights could inform the design of new vaccines by identifying immunogens or epitopes that elicit more effective immune responses, ultimately advancing HIV vaccine development.

Copy number variations (CNVs) of the 16p11.2 (BP4-BP5) genomic locus are closely associated with neurodevelopmental disorders such as autism spectrum disorder (ASD) and schizophrenia. Interestingly, 16p11.2 CNV deletion and duplication carriers exhibit some opposing phenotypes, with deletion associated with macrocephaly and obesity, and duplication with microcephaly and decreased body mass index. To identify the molecular mechanism underlying 16p11.2 CNVs, we differentiated patient-derived stem cells into neural progenitor cells (NPCs) as a model system for early neurodevelopment. Quantitative tandem mass tag (TMT) proteomics identified proteins that are phosphorylated differently between NPCs from carriers of a 16p11.2 CNV and NPCs from unaffected individuals. Notably, the differentially phosphorylated proteins found were enriched in primary cilia and centrosomal function, which is relevant for neurodevelopment. Through immunocytochemistry on the NPCs using a primary cilium specific antibody, the lab found that deletion and duplication had opposing effect on the cilia length. Deletion carriers had increased cilial length and duplication carriers had decreased cilial length. To identify which of the 30 known genes involved in 16p11.2 are drivers of these changes, knockdown and overexpression screens determined thousand and one kinase 2 (TAOK2) to be the most significant in cilia length. Using immunofluorescence assays, I found that intraflagellar transport protein 88 (IFT88), accumulates at the cilia tip in TAOK2 knockout NPCs, indicating disrupted transport within the cilia. IFT88 is a key regulator of Sonic hedgehog (Shh) within primary cilia and Shh is also a key regulator of neurodevelopment. Therefore, to understand the functional relevance of these findings on ciliary length, I performed quantitative PCR to measure changes in Shh activity. Since our findings so far demonstrate disrupted ciliary transport, I expect differences in Shh activity between wild-type and knockout TAOK2 NPCs. These investigations build our understanding of 16p11.2 CNVs and the mechanisms that implicate them in neurodevelopmental disorders.

Understanding the dynamic behaviors of cells in the developing human brain is essential for elucidating the mechanisms that drive both normal and abnormal neurodevelopment. Using lentiviruses encoding fluorescent proteins, we infected cells in slices from different regions of the developing human cerebellum to track their movements over several hours. We then captured timelapse images of these fluorescent slices under a microscope, allowing us to visualize their dynamic behavior. Using live imaging analysis software, hundreds of individual cells were then tracked and characterized. Our analysis found several key processes, including novel modes of cell division and differentiation, neuronal migration, and intercellular communication. This approach allowed us to map a timeline of critical events that shape cerebellar architecture. This research aims to help us gain insight into neurodevelopmental disorders, where disturbances in fundamental biological processes underlie disease progression.

Disruptions in the mechanisms underlying threat detection and maladaptive aggressive behaviors are core features of several psychiatric disorders, including anxiety disorders and post-traumatic stress disorder (PTSD). In these conditions, heightened vigilance and attentional biases toward perceived threats can contribute to inappropriate aggression or avoidance behaviors, underscoring the need to understand the neural mechanisms mediating threat assessment and aggressive responses. We aim to better understand threat assessment and responding by interrogating brain region and cell-type specific activity patterns during unfamiliar social encounters using mice as our model system. Recent studies have identified the posterior paraventricular thalamus (pPVT) as a hub for processing sensory and emotional information in response to stress, predators, and other aversive contexts to facilitate a choice action. Despite its relevance, the role of pPVT in social-emotional brain circuit function remains unexplored. Recent transcriptomic datasets have revealed genetically identifiable clusters within PVT, specifically highlighting estrogen receptor-1 (Esr1) as a genetic marker for more posterior areas of PVT. In our behavior paradigm, mice with intact pPVT^Esr1 neural activity selectively attack novel conspecifics with unfamiliar traits (out-group) but not those with familiar traits (in-group) when introduced into their home cage. Given this, we designed an experiment using chemogenetics, a technique that utilizes genetically engineered receptors (DREADDs) to modulate neural activity, to test the involvement of pPVT^Esr1 neurons during unfamiliar social encounters. We have found that selectively inhibiting pPVT^Esr1 neurons using Gi-DREADDs reverses attack behavior, suggesting a putative role for these neurons during threat assessment and response processes. To follow up on these results, we are selectively exciting these neurons using Gq-DREADDs to determine how increased excitatory activity within pPVT^Esr1 neurons affects aggressive behaviors towards in-group and out-group intruders. We hypothesize that chemogenetic excitation of pPVT^Esr1 neurons will increase aggressive behaviors toward intruder mice for the entirety of the trial.

In our biochemistry teaching labs, students conduct 10-week projects using recombinant protein expression and purification protocols, adapted from Fred Hutch, distributed and tracked via GENI-ACT.org, to identify immunoproteins of research or biomedical interest. We hypothesize they can produce antigen fragments for antibody studies and siderocalin proteins, which bind bacterial siderophores, yielding different amounts and results. In Winter 2023, students modeled antibody fragments with I-TASSER, expressed top constructs with His-tags, and purified them using Ni-NTA resin. In Winter and Fall 2024, siderocalins were expressed as GST-tagged constructs in BL21 and DH5alpha cells using longer expression. The human siderocalin in DH5alpha formed an orange solution, consistent with known siderocalin-enterobactin-Fe complexes. Unexpectedly, other species’ siderocalins appeared yellow, pink, or blue, suggesting functional diversity. Students produced enough immunoproteins for viability tests and are now expressing homologs of the blue siderocalin. They participated in all stages, developing spectroscopy and protein crystallization skills for research careers.

Malaria, caused by Plasmodium parasites, infects millions of people across the globe and leads to over half a million deaths annually. Infection begins when a mosquito takes an infectious blood meal, resulting in the deposition of infectious parasites known as sporozoites into the skin. Sporozoites traffic from the skin into the liver and undergo clinically silent development in hepatocytes.  This liver stage development is required for the transition into blood stage development where all the clinical symptoms of malaria and transmission back into mosquito vectors occur. No highly efficacious malaria vaccines exist, but one promising vaccination strategy is immunization with sporozoites that are impaired in their ability to complete liver stage development.  These attenuated whole parasite vaccines provide robust immune protection in malaria-naive individuals, but further refinement of this approach is required before this strategy can be deployed globally in endemic regions.  We have shown that the type 1 interferon (IFN-1) signaling regulates the immune response induced by whole parasite vaccines. My project aims to spatially characterize how IFN-1 influences parasite development within the liver using immunofluorescence. Interferon-alpha/beta receptor knockout (Ifnar-) mice (which are impaired for IFN-1 signaling) and wildtype C57Bl/6 mice were infected with Plasmodium yoelli. We then harvested livers from infected mice at various time points during liver stage development. I observed that IFN-1 restricts parasite development beginning at 24 hours post-infection but does not impact parasite size in hepatocytes. Future studies will selectively eliminate IFNAR on hepatocytes or on distinct immune cells to identify if IFN-1 mediated parasite restriction is hepatocyte intrinsic or is immune cell mediated.

Aging is a significant risk factor for many chronic diseases. Understanding longevity interventions can help prevent these illnesses. When mitochondria fail to function correctly, energy production decreases, leading to diseases and shorter lifespans. This study investigates a potential longevity intervention and utilizes Ndufs4-/- mice, a model for mitochondrial disease resembling a human condition called Leigh Syndrome. Mice carrying this mutation have shortened lifespans and neurological impairments. This study aims to determine whether the Sirt3 gene is required for an extended lifespan when using Adefovir Dipivoxil (ADV) injections in a Ndufs4-/- mouse model. In prior experiments, ADV has been shown to increase the expression of genes involving fatty acid oxidation, allowing cells to break down fats for energy. This increase in energy production has been shown to extend the lifespan of Ndufs4-/- mice. ADV is hypothesized to work through a similar pathway as Rapamycin to influence fatty acid oxidation. Rapamycin inhibits the mTOR complex, which influences the CEBP-Beta complex to produce a high LAP/LIP ratio. This shift in the LAP/LIP ratio enhances fatty acid oxidation, extending lifespan. However, in Ndufs4-/- mice lacking Sirt3, a mitochondrial protein, Rapamycin fails to extend their lifespan. This study determines whether ADV works through the same pathway as Rapamycin, specifically if it requires Sirt3 to exert longevity effects. To investigate this, Ndufs4-/- mice are crossed with Sirt3-/- or Sirt3 +/+ and given ADV injections starting at 10 days of age, continuing until the end of their lifespan. I am responsible for genotyping experimental animals and ensuring the correct genetic profile before enrolling them in the study. My role includes administering ADV injections, tracking weight changes, and monitoring the onset and progression of disease.

Leigh Syndrome (LS) is a neurodegenerative disease due to the dysfunction of mitochondria. This disease usually begins in infancy and affects approximately 1 in 40,000 individuals, with children experiencing a progressive decline in their cognitive and motor functions often accompanied by severe treatment-resistant epileptic seizures. Mutations in Ndufs4, the gene that encodes a subunit of mitochondrial complex I have been linked to LS. Using mouse models, our lab has previously demonstrated that GABAergic interneurons play an important role in the pathophysiology of LS. Specifically, mice with Ndufs4 knockout (KO) in GABAergic neurons located across all brain regions exhibit seizures. However, seizures in epilepsy patients and animal models typically originate from forebrain structures. In this project, we examined whether inactivation of Ndufs4 in GABAergic neurons of the forebrain alone is sufficient to cause seizures in mice. To inactivate the Ndufs4 gene in the interneurons of the forebrain, homozygotes floxed Ndfus4 (Ndufs4flx/flx) mice were crossed with Dlx56Cre+ mice. Ndufs4flx/flx; Dlx56Cre+ mice obtained from this cross were used as experimental mice. We hypothesized that mice carrying the gene KO in this region will exhibit seizures and related mortality. Thermal seizure testing was conducted on 9 experimental mice and 10 control mice. Our results show that mice with Dlx56Cre KO exhibit a high seizure susceptibility to both spontaneous and thermally induced seizures. In addition, these mice exhibit a very reduced life span with nearly all mice dying by age P60. These findings indicate that inactivation of Ndufs4 in GABAergic neurons of the forebrain is sufficient to induce seizures and mortality in mice.

Clear auditory communication is essential for effective learning in university classrooms, and poor acoustics can hinder comprehension and engagement. This study explores the relationship between subjective listening experiences and objective acoustic parameters in classrooms at Seattle Pacific University. Previous studies have established that poor acoustic conditions – such as long reverberation times, high levels of background noise, and poor room isolation – are associated with negative learning outcomes like lower comprehension and increased stress, anxiety and fatigue. A small, liberal arts school like SPU is likely to face unique acoustic challenges, i.e. classrooms are more often multi-use, and class and classroom sizes are significantly smaller than large universities, where much of the existing research has been conducted. In this study, I examine student and faculty responses to a survey designed to assess auditory experiences in classrooms. I compare responses with acoustical measurements of background noise level and reverberation time in the same classrooms. By analyzing the correlation between perceived and measured acoustic conditions, this research identifies acoustical factors that impact learning and teaching experiences. My findings contribute to the understanding of university classroom acoustics and may inform future architectural and instructional strategies to improve learning environments.

The collection of underwater sounds for anomaly detection can contain white noise, making it challenging to analyze data. This project’s goal was to improve the process of analyzing data and detection in the presence of white noise. The project focused on the detection of the fin whale’s twenty hertz down sweep call. The call is visually recognizable on the spectrogram, a tool that visualizes audio using shape and color over time as a static image. The project used detection output from the publicly available WhaleTracks software as a comparison to the method presented herein. I focused on tuning a part of the detection process to better detect fin whale calls in a noisy environment. We focused on studying changes in the Python script find_peaks function’s prominence parameter in a normalized signal. The prominence parameter is a variable responsible for characterizing the sensitivity of the detector. Lower values of the prominence parameter increase the sensitivity of the detector and higher numbers lower the sensitivity. My research analyzed how changes in the prominence parameter would affect the detection of fin whale calls. Using a Google Colab notebook, I modified a set of code that took in data, processed the data into a readable form for the machine, detected peaks in the twenty hertz range, and then printed the data in the form of several graphs readable for the human eye. Based on the time frames used for evaluation, we concluded that the best value for the prominence parameter for all environmental conditions was three. In the future, this prominence parameter should instead be made dynamic, changing depending on the amount of sound energy present in the audio data.

Salivary glands are organs in the mouth which produce and secrete saliva, a multifunctional fluid crucial for processes including oral cavity lubrication, digestion, and antimicrobial functions. Diabetes mellitus has been associated with salivary gland dysfunction and harmful oral consequences including severe tooth decay and disrupted wound healing, yet it is not currently known what cell populations are affected in salivary glands and how this disease affects cell organization, function, and metabolic response. One model for diseases in human tissues are organoids, three-dimensional multicellular systems derived from stem cells which self-organize to mimic the structure and function of tissues in vivo when given the right cues. Dr. Devon Ehnes in the Ruohola-Baker Lab recently created a protocol to develop salivary gland organoids from induced pluripotent stem cells (iPSCs), and through additional culture in a high-glucose media along with inflammatory cytokines, this organoid has been used to study how diabetes affects salivary glands. Preliminary analysis has suggested acinar and ductal cell dysfunction and mitochondrial stress as causes of salivary gland dysfunction, but further work is necessary to understand how this diabetic environment leads to changes in cell function and mitochondrial activity. Here, I use a human iPSC-derived organoid model to assess how diabetic conditions affect the expression and localization of the acinar marker AMY1A, the ductal marker KRT19, the cell stress marker FOXO1, and the mitochondrial marker ATPB to determine the mechanisms for salivary gland dysfunction in diabetes.

In the intertidal community, various factors can influence the species richness and the percent cover of dominant species such as rockweed (Fucus distichus). Around San Juan Island, Washington State, there are different current speeds during September. There are high currents (0.7-1.5km/hr) and low currents (0.1-0.6km/hr), which can influence the community structure at different intertidal areas. This project focused on examining how species richness and the percent cover of rockweed varied at low and high current sites. Two vertical transect lines were laid (3m apart) during low tide (<1ft) from 0m (waterline) to 10m (shoreline) at both the low current site, Lab 11 and the high current site, Eagle Cove. Using the 60cm² quadrat placed at every meter (0-10m), the averaged species richness and percent cover of rockweed was recorded. Percent coverage was calculated per each square in the 60cm²  quadrat and species were identified and recorded. The high current site had a significant higher species richness of 7 and lower percent cover of rockweed of 18.9% in the intertidal. Conversely, the low current site had a significantly higher rockweed percent cover of 56.2%, with a lower species richness count of 5. The percent cover of rockweed seems to have an inverse relationship with species richness, in which when percent cover of rockweed is higher, species richness declines. This data is important because knowing the species richness and the percent cover of dominating species can contribute to understanding intertidal community structure and how current speeds may influence it. 

Anaerobic digestion is a biological process that converts waste into biomethane, a renewable energy source. Acetate conversion is the last step of anaerobic digestion and is the most likely to fail in methane production. Understanding the microorganisms responsible for this process, and the conditions they thrive in, can help to increase success of that final step. Previous studies have concluded that changing the acetate feeding conditions of a digester will select for different microbial species. Starting with established lab-scale acetate-fed digesters, this study aimed to identify the present species through DNA extraction and sequencing. Samples were extracted over the course of a week from digesters that varied in feeding schedule. Statistical analysis of the DNA sequences was then completed to determine the diversity in archaeal and bacterial species, and the richness of those species. The variance between digesters was visualized using Principal Coordinate Analysis (PCoA). This data confirmed that digesters operated under different feeding conditions establish different microbial communities. Next steps will include comparing the community composition to acetate consumption kinetics. These results will help advance the understanding of conditions required to ensure stabilized biomethane energy production from anaerobic digestion.

There is evidence that screen habits (i.e., screen time and parental involvement) may be associated with a series of academic achievement precursors among children. Mental rotation is an early emerging spatial skill that serves as a foundational academic precursor, predicting future spatial reasoning abilities and later success in STEM fields. While prior research has found associations between unmediated screen time and outcomes such as language development, little is known regarding how screen time context influences spatial skill development. In this study, we are examining the impacts of children's media use (specifically total screen time and parental mediation) on mental rotation performance. To assess mental rotation abilities, 50 24- to 36-month-old toddlers complete an eye-tracking task requiring them to mentally transform a giraffe to predict the direction it will move. Children respond to the task via anticipatory eye-movements and the giraffe increases in rotation with each successful trial, progressively increasing task difficulty. Mental rotation is assessed based on the highest angle of rotation achieved within the task. Parents report their child’s screen time across different media types and parental mediation through a subsection of the Comprehensive Assessment of Family Media Exposure questionnaire. Parental mediation is defined as parents’ active regulation of the type, duration, and context of screen time exposure. In our analyses, we will investigate the relationship between total screen time and parent-mediated screen use on spatial skill abilities. We hypothesize that children with high parent-mediated screen time and low total screen time, assessed separately, will have stronger mental rotation abilities. Advancements in technology in recent decades have led to an increase in digital media use among children in the United States and we hope our anticipated results will promote a more nuanced understanding of the interplay between media use and spatial skills in early childhood development.

2D van der Waals materials are composed of atomic layers held together by weak van der Waals forces, which allows them to be separated into individual 2D sheets that are only a few atoms thick and exist in a single plane. When 2D layers are stacked together the resulting heterostructure often exhibits interesting electrical, optical, thermal, and mechanical properties. The most well-known van der Waals material is graphene, which is often layered with hexagonal boron nitrate (hBN). Peptides are short chains of amino acids, which form the building blocks of proteins. They are crucial in various biological processes, such as cell growth and development. Peptide-based materials hold great promise in fields such as drug delivery and nanotechnology due to their ability to self-assemble and interact with other molecular structures. In this research, we aim to incorporate peptides into graphene-hBN heterostructures to study the interaction between these two material systems. We focused on using dry transfer techniques to pick up peptide sheets with graphene and hBN. Through careful documentation of pick-up attempts, we can refine our approach and optimize the conditions for effective peptide incorporation. These results provide insight into the challenges in integrating biological components into van der Waals heterostructures and will inform future applications of these hybrid structures. Understanding how peptides can be effectively integrated into layered systems is crucial for advancing functional biomaterials. By refining peptide pickup and incorporation techniques, this work contributes to the broader goal of designing tunable, bio-inspired materials with potential applications in medicine and advanced manufacturing.

The last decade has seen unprecedented legislative attacks on Sexual and Reproductive Health(care) and Rights (SRHR). In the US, barriers to women’s reproductive healthcare access, particularly for termination of pregnancy, are increasing at the local, regional, and national level through numerous institutional and legislative sanctions; the construction of such changes reverberating on a global scale via policies such as the Global Gag Rule (GGR). Reinstated by the Trump administration, the rule (also known as the Mexico City Policy), is a regressive, inimical policy, restricting American foreign assistance to organizations providing legal abortion services—regardless of the organization's adherence to local laws. This represents a significant setback for global health and human rights efforts, particularly for vulnerable communities who already face social stigmatization and systemic barriers to accessing critical healthcare. In the case of Kenya, a substantial recipient of American aid, US regulations stand in direct contradiction to the country’s own constitution, thus forcing local organizations to choose between complying with the policy or providing care at the expense of funding. Through exploring Kenya’s structural and organizational reconfiguration in the face of interventionist policies such as GGR, this project aims to explore the manner in which foreign aid influences— and often, stifles— the progression of developing nation’s SRHR and impedes local organizations from facilitating care; thereby exacerbating existing gender inequities that trickle beyond the healthcare sector. The methodology employed involves examining the formation of foreign funding from International Development agencies, placing such data in cross-examination with US Congressional changes while tracking foreign funding influence on domestic developmental institutions in Kenya. In considering Kenya as a case study, this research seeks to illuminate the gendered inequities prevalent in SRHR interventionist policies and how they take shape, simultaneously attesting to the implications of the paradox of "development" and its disparities globally.

We explore the Earth in order to discover and understand the ecosystems present on it. Representing 70% of the surface of the globe, the oceans are arguably the place we struggle the most to explore due to their size and depth (we know more about space than we do about our oceans). Dissolved organic compounds, produced by diverse marine organisms for a wide variety of reasons, are present in very low concentration in the oceans. This research was done in order to develop, design, and ameliorate existing techniques to detect and analyze dissolved organic compounds (amino acid in this case) present in seawater. Cation exchange chromatography, derivatization and gas chromatography mass spectrometry were used. The results were not as expected but the methodology is very promising. With some ameliorations, that methodology will be able to help us detect and analyze known and unknown particles at very low concentration in our vast oceans.

Treatment-related cardiomyopathy is a significant cardiotoxic complication for cancer patients treated with chemotherapy or radiotherapy and a leading cause of premature morbidity in childhood cancer survivors. Predicting a patient’s cardiomyopathy risk could help clinicians intervene early but is not possible with standard echocardiogram analysis methods. Preliminary research at the CardSS lab demonstrated that a deep convolutional neural network has modest success at predicting a pediatric patient’s risk for developing CM but is significantly limited by insufficient pre-diagnosis data for training, impairing its ability to learn generalizable disease progression patterns. This research aims to develop a generative AI model that generates synthetic echocardiogram data for training to improve the prediction model’s ability to learn distinctive patterns representing cardiomyopathy risk. By training on a longitudinal dataset containing echocardiograms from several cardiomyopathy stages before diagnosis, we aim to produce synthetic echocardiograms conditioned on specific classes: 0-1 years before diagnosis, 1-3 years before diagnosis, cardiomyopathy present, and control. Thus far, I have preprocessed echocardiogram data and implemented three experimental diffusion model architectures to investigate how the addition of a cross-attention layer to the encoder, bottleneck, and decoder regions of the model affects its ability to produce echocardiograms of different classes. I also implemented an analysis pipeline that calculates the Fréchet Video Distance (FVD), Structural Similarity Index Measure (SSIM), and Peak Signal-to-Noise Ratio (PSNR) between two sets of echocardiograms, which provide measures of image/video similarity. Using this pipeline, I am evaluating two key standards for synthetic data—intraclass fidelity and interclass separability—to quantify each model’s ability to generate data that is (1) representative of its class and (2) distinct from data produced for another class, and how these metrics change as training progresses. Preliminary data has shown that these models are producing synthetic echocardiograms that closely resemble real echocardiograms, but inconsistently.

Ocean eddies contribute significantly to the transfer of heat and energy throughout the world’s oceans, playing a key role in regulating climate. Eddies are observed predominantly through Earth-orbiting satellites that collect data on sea surface height (SSH), a metric that can be used to estimate eddies on a global scale. Historically, satellites could only capture point-wise measurements, resulting in low-resolution SSH maps, which led to underestimations of small-scale eddy strength. Launched in 2022, NASA’s Surface Water and Ocean Topography (SWOT) satellite now provides groundbreaking 2D SSH imagery with higher resolution relative to existing SSH products. However, there are only two years of SWOT data available, unlike other satellites with decades-long records. Here, we considered how the recent SWOT data could be deployed to improve the spatial resolution of SSH products from the preceding 30 years. To achieve this, we trained an image-to-image U-Net neural network to predict the high-resolution SSH from an existing low-resolution product (NeurOST). We used SWOT high-resolution data as a ground truth to train this neural network and minimize the mean squared error of the SSH output with respect to the SWOT data. By evaluating the accuracy of the SSH output maps against an independent withheld satellite, we demonstrated that our method improves the spatial resolution of the SSH product compared to the NeurOST dataset. We next plan to test the accuracy of our method when applied to years before SWOT was launched. Overall, our research highlighted how leveraging deep learning and SWOT can enhance the spatial resolution of a decades-long eddy observation time series, enabling more accurate studies of eddies and their climate impact.

Chronic pain is a public health crisis that has been clinically demonstrated to disrupt reward learning and motivation in affected individuals. Previous literature has indicated that Calca neurons in the parabrachial nucleus (PBN) play a key role in the sensory and emotional processing of pain and become hyperactive in chronic pain models. Despite this, how PBN Calca signalling impacts adaptive decision-making in a positive-reinforcement context remains unclear. This study aims to explore how chronic PBN Calca hyperactivity impacts learning and motivation. Using chemogenetics, a technique that selectively modulates neuronal activity, we chronically activated PBN Calca neurons in transgenic mice. These mice were then tested in a two-phase positive-reinforcement operant conditioning paradigm to assess how chronic PBN Calca activation altered learning rates and motivation compared to controlled animals. In phase one, mice underwent a fixed ratio schedule in which they learned to press a lever during a distinct cue to obtain a food reward. In phase two, mice underwent a progressive ratio schedule in which they had to press a lever an increasing number of times to obtain a food reward. We hypothesized that chronic activation of PBN Calca neurons would impair both learning rate and motivation. With this work, we hope to clarify the impact of centrally-mediated chronic pain on motivational and cognitive processes, which could inform the development of future therapeutic strategies.

Attention-deficit/hyperactivity disorder (ADHD) is a neurodevelopmental condition characterized by differences in attention, focus, and emotional regulation. ADHD has high heritability rates, meaning children commonly inherit ADHD from their parents. Despite this, there is little research on parental ADHD symptoms and how they affect parenting. We hope to bridge this knowledge gap by investigating the relationship between temperament and emotional socialization in ADHD parent-child dyads (parents and their children with ADHD). Temperament refers to innate behavioral traits shaping one's personality. Individuals with ADHD are known to experience higher rates of negative affect, a temperamental factor including significant aversion from feelings like sadness. Emotional socialization is the process through which individuals recognize, understand, and manage their emotions in a social context. This process is especially complex with ADHD parenting, as parents with ADHD symptoms may have differences in emotional regulation and temperament that could influence parenting behaviors and emotional socialization in their children. We hypothesize that negative affect in parents is positively correlated with (1) negative talk towards children and (2) perceived anxiety and lack of anger control in their children. To test these hypotheses, parents complete the self-report Adult Temperament Questionnaire (ATQ), which assesses negative affect, and the Behavior Assessment System for Children (BASC), which assesses their child's perceived anxiety and anger control. We evaluate negative talk via behavioral coding of video-recorded standardized parent-child interactions. Using these laboratory-based interactions, we use the Dyadic Parent-Child Interaction Coding System (DPICS) to analyze the frequency of parents' verbal disapproval of child behavior and/or attributes. I then use bivariate correlation analysis to determine the relationship between the proposed variables of interest. Through our anticipated findings, we hope to better inform care for children with ADHD by identifying individualized support strategies to use in parental interventions to better facilitate emotional socialization in ADHD families. 

This study investigates the mechanical behavior and fracture mechanisms of 3D-printed continuous carbon fiber/polymer matrix unidirectional composite materials as potential alternatives to conventionally processed laminate samples of similar geometry and constituents. A Markforged Mark Two 3D-printer is used for printing test samples using a proprietary nylon based, Onyx matrix-reinforced with C particulate and pure C fiber filament. 3D-printed samples and laminate samples will be evaluated through tensile and flexural tests to quantify mechanical properties to include strength, modulus of elasticity, and percent elongation. Hardness and sample densities will also be compared. Printing limitations of the Markforged printer will also be investigated. Fracture surfaces of both 3D printed samples and laminates will be examined with both stereomicroscopy and scanning electron microscopy to investigate differences in fracture morphologies involving fiber and matrix.

Online proctoring uses intrusive features many students aren't aware of such as lockdown browsers, video monitoring, and video or audio recording during the exam process. These intrusive features oftentimes have especially negative impacts on students with disabilities. Our goal is to determine how students with disabilities view data privacy and online proctoring. We conduct semi-structured interviews with students with DRS accommodations to understand how their circumstances affect them during test taking and how they view tracking and surveillance during the testing process. We use grounded theory qualitative analysis to find common themes and patterns in how students see their mental models of privacy, potential misrepresentation of academic integrity, justification for proctoring, definitions of intellectual and educational privacy, and the future of online proctoring. We will provide design solutions that will help students understand and feel more comfortable with their online test-taking process. Students with disabilities make up a large number of the student population; focusing and accommodating their needs in regards to online test taking is a foundation for test-taking improvements for everyone. 

The lung microbiome plays an important role in immunity where any shifts within the microbial community can affect the immune response. Tropheryma whipplei, a bacterium that causes Whipple’s disease primarily in the human gastrointestinal tract, can also reside in the human lung microbiome of both healthy and immunocompromised individuals. Tropheryma is more commonly found in lungs of individuals with pneumonia, those who smoke, or in people living with HIV. Tropheryma is also found in the lung microbiome of certain non-human primate species, where the dominance of Tropheryma is associated with shifts in pulmonary immune cells. Similarly, we found that Tropheryma is highly prevalent and dominant in the pigtail macaque (PTM) lung. However, little is known regarding the factors contributing to the establishment and dominance of Tropheryma in the non-human primate lung. Here, we test the hypothesis that Tropheryma dominance and microbial diversity (beta diversity indexes) in the PTM lung are similar in co-housed animals. Bronchoalveolar lavage (BAL) and housing metadata were collected from PTM (n = 50). Genomic DNA was extracted using the QIAgen PowerFecal Pro DNA kit and the V3-V4 region of the 16S rRNA subunit was amplified and sequenced. The QIIME2 bioinformatics platform was used to evaluate the composition of the lung microbiome and to determine the dominance index and the beta diversity of the sample set. Expected findings will show similar lung microbial compositions across co-housed animals. Results from this study will help us determine the specific environmental factors contributing to the emergence and colonization of Tropheryma in the lung microbiome of PTM. This will lay the groundwork for further research into the role of Tropheryma in the immune response against respiratory diseases, ultimately guiding the development of targeted therapies for lung infection.

Alzheimer’s Disease (AD) is characterized by Amyloid β (Aβ) plaques, clumps of misfolded proteins which interfere with neural function, leading to cognitive decline. Despite being the most common form of dementia, exact causes and accessible early markers for AD remain elusive. Recent literature has suggested that deficits in risky decision-making appear before memory loss, making them a potential early marker. My project investigated how risky decision-making and corticolimbic circuit activity is impacted by Aβ pathology in 5XFAD mice, an established model of AD. Mice were lowered to 85% weight for motivation to forage, and then habituated to a rectangular nest area separated with a sliding door from the foraging arena. This was followed by baseline trials over four days where mice foraged for a short, medium, and long-distance pellet each day. On the fifth day, mice procuring the long-distance pellet encountered a weasel on wheels which surged forwards, simulating a predatory threat. Mice were given three minutes to procure the pellet. Ninety minutes after the encounter, mice were euthanized and brains extracted. Brain tissue was immunostained for c-fos, a molecular indicator of neural activity, to compare neural "snapshots" of control and 5XFAD mice who encountered/did not encounter the weasel. Brain regions to compare included the amygdala, prefrontal cortex, and hippocampus, responsible for processing fear, decision-making, and spatial information, respectively. The study ended when mice were eleven months old. In line with previous studies, it is expected that 5XFAD mice will have more weasel trial pellet retrieval attempts and exhibit differences in c-fos activity in brain regions of interest. These findings could help confirm deficits in risky decision-making as an early marker of AD, significant due to the scarcity of early markers.

Halofun is an object-oriented program using Chebfun software in MATLAB that employs low rank spectral approximation methods to efficiently compute and store functions on annuli. The computational cost of numerical techniques are often a major constraint in computing and working with large and complex mathematical problems. Low rank representations of functions can reduce computational costs; low rank function approximation has relations and advantages similar to that of the singular value decomposition in terms of isolating the most important features of the problem. Similar to writing a matrix representation as a sum of rank 1 matrices, we can write a function as a sum of k rank 1 functions. By using a representation based on Chebyshev/Fourier basis functions, we can make use of fast, FFT-based transforms and other fast algorithms to compute with functions on annuli. Halofun expands on previously developed low rank spectral methods in rectangular, circular, disk and spherical domains, so that a user-friendly software for fast and spectrally accurate computations now exists for ring-shaped domains.

Decision-making is important for quality of life. Adaptive decision-making can improve one’s quality of life, while maladaptive decision-making may be detrimental. Here, we investigate the effect of Cannabidiol (CBD) on neuroeconomic decision-making in rats, specifically cognitive flexibility, and inflexibility. Rats were trained in a concurrent choice task, where a set number of lever presses resulted in a high reward (HR, 4 food pellets) and a low reward (LR, 1 food pellet). The first treatment level consisted of two behavioral treatment groups, where one group had the HR lever alternating between the left and right side of the operant chamber (flexible group), and the other group (inflexible group) had the HR lever stay on the same side for 20 sessions, where each session had forced trials (one lever accessible) and choice trials (both levers accessible). The metric used for assessing flexible and inflexible choice behavior was the number of choice trials needed to reach the criterion, criterion defined as 10 choice trials within a 12-choice trial sliding window being assigned to the HR lever, which is considered significant bias according to the binomial statistics. The next treatment level is the vehicle vs CBD, where the flexible or inflexible groups receive 20 vapes of vehicle or CBD. As a control experiment, we tested for any effect of vehicle (vegetable-glycerin/propylene-glycol, 20/80) between or within flexible and inflexible groups by administering vehicle vape or no vape in the vape chambers. Preliminarily, we found no statistical effect of vehicle exposure to either behavioral group no main effect in a three-way ANOVA (F1, 20 = 1.753, p=0.2005), however more subjects need to be added as there is a small trend towards vehicle affecting the development of inflexibility. After the control experiment, we will compare the effects of CBD in this behavioral paradigm.

Exoplanetary studies suggest that massive outer planets, such as Jupiter in our Solar System, play a crucial role in shielding inner planets from excessive asteroid bombardment, thereby contributing to long-term orbital stability. The Kepler-11 system is a tightly packed configuration of six planets that lacks a known massive outer planet protector. In this project I investigated the stability of Kepler-11 planets under varying levels of asteroid impact modeled using a combination of n-body simulations in 10,000-year segments, Monte Carlo methods, and statistical extrapolation. These results were then further extrapolated using Poisson statistics to estimate the system’s long-term evolution over millions of years. I ran simulations as the system is currently known and with a Jupiter-like planet to assess its role in deflecting or capturing incoming objects. Preliminary findings suggest that in the absence of a massive outer planet, asteroid impacts on the inner planets increase significantly, leading to cumulative orbital drift and potential long-term destabilization. These results highlight the importance of massive planets in preserving planetary system stability and suggest the possible existence of an undetected distant massive planet or a densely packed outer system that has maintained Kepler-11’s current planetary configuration.

How the brain transforms sensory information to guide action and choices remains largely unknown. Although the brain regions and systems involved in decision-making are studied extensively in primates, understanding the details of the neuronal cell types and circuits that perform the computations related to decision-making requires the use of an animal model that is amenable to neuronal cell type-specific and circuit-specific manipulation. The mouse (Mus musculus) has become a model of choice for such experiments due to the explosion of new genetic and molecular tools allowing for such experiments. However, the behavioral sophistication of the mouse model is very different from that of the primate, so the ability to train mice on tasks also used in monkeys becomes critical. We trained mice on a modified random-dot motion (RDM) task, adapted from non-human primate studies (Britten et al., 1992), in which they discriminate between two directions of motion across varied levels of difficulty. This design exposes mice to varying levels of directional coherence, allowing us to measure behavioral effects following future experimental manipulations such as chemogenetic inhibition. Toward that goal, we developed an optimized training protocol for mice to perform RDM discrimination designed to maximize learning efficiency while minimizing stress. The protocol consists of sequential stages of training: habituation/acclimation, free reward, directional, dynamic, and maintenance, only advancing once a pre-defined accuracy threshold is reached. We trained 34 mice using this approach, and 80% of them learned to perform the task with the easiest condition in 40 training days. 16 mice completed the full protocol in 130 days. Our findings establish an efficient framework for training mice in complex perceptual tasks, which can be combined with neuroscientific tools to assess circuit function, allowing us to explore the evolutionarily conserved or divergent neural circuits underlying decision-making between mice and monkeys.

Planktonic protists (unicellular eukaryotes) play essential roles in open-ocean biogeochemical cycles and food webs, functioning as phototrophs, heterotrophs, or mixotrophs depending on the species. However, cultured representatives of protists from the Pacific Ocean are scarce, limiting our understanding of protists within the largest ocean on Earth. In this study, we analyze seven cultured protist strains isolated from the tropical Pacific Ocean from the upper ocean from 30 °N to 4 °S and from 120 to 140 °W, including seven haptophytes, five pelagophytes, and four dinoflagellates. We examine transcriptomes from laboratory cultures of these isolates. We construct a phylogenetic tree of the isolates based on single-copy marker genes to infer evolutionary relationships. We examine correlations between phylogenetic relatedness and the latitude and depth of isolation. An additional objective of this work is to resolve the species-/strain-level taxonomy of these isolates, enabling their integration into the Marine Functional Eukaryotic Reference Taxa database. This will improve our ability to characterize marine protist diversity and function in metagenomes and -transcriptomes.

Spurred by hegemonic competition, the Department of Defense (DoD) has poured investments into military AI and courted the commercial tech sector. This raises critical questions on the tech industry’s approach to ethics and its role in military AI development. Silicon Valley’s past collaboration with the DoD has led to significant ethical controversies, prompting the industry to invest in AI ethics initiatives such as regulatory boards, ethics officers, and ethical guidelines. Existing scholarship conveys that while ethics is often in tension with innovation in the tech industry, key stakeholders drive its prioritization. Still, the tech-military complex and military AI development have dramatically accelerated despite ethics frameworks that should slow their progress; this forms the study’s basis of investigation. Scholarship observes military cultural attitudes influencing the organizational behavior of DoD partners, but not its connection to the Silicon Valley-DoD nexus, military AI, and ethics. This study addresses these gaps, hypothesizing that the tech-military complex enables a transference of military cultural attitudes towards ethics in the tech industry, resulting in a weaponization of ethics to justify accelerated AI development. I utilize a dataset of outward-facing documents from Big Tech companies that have received DoD contracts and semi-structured interviews with developers. I employ qualitative discourse analysis to assess the prevalence of these cultural dimensions, and I expect to find a notable presence based on preliminary analysis. Discerning if and how sociocultural influences shape corporate objectives provides insight into the underlying determinants of imminent AI governance frameworks, which becomes essential to understand as technological development outpaces regulation.

Chimeric Antigen Receptor (CAR) T-cell therapy has revolutionized immunotherapy for blood cancers, achieving unprecedented outcomes for many patients. However, variability in treatment responses—ranging from complete remission to relapse or severe side effects—remains a critical challenge. Mathematical and computational models that have been calibrated to experimental data can help to predict treatment efficacy and inform personalized therapeutic strategies. Working with Dr. Konstantinos Mamis (UW Applied Mathematics) and Dr. Katherine Owens (Fred Hutchinson Cancer Center), Rohan Pandey and Ray Chen (UW ACMS Department) employ models consisting of systems of ordinary differential equations (ODEs)- to simulate tumor and CAR T-cell dynamics. Though several prior mathematical models analyzing the interactions between CAR T-cells, tumor cells, and effector cells under varying treatment conditions exist, there has not been a systematic comparison of models representing competing mechanistic hypotheses against data from patients undergoing CAR T-cell treatment and/or chemotherapy. For two existing mathematical models, we explore the practical identifiability of model parameters using synthetic data and a population approach with nonlinear mixed effects implemented in Monolix. Furthermore, we calibrate the model parameters to real data from 10 patients with B-cell acute Lymphoblastic Leukemia (B-ALL) and identify the most accurate and parsimonious of the existing models. Finally, we determine and study the effect of key variables that largely influence patient responses to therapy, including those associated with sustained remission or relapse. This computational oncology work has the potential to inform strategies for optimal CAR T-cell therapy, improve patient outcomes, and further innovation in cancer treatment.

The opioid epidemic remains a critical public health crisis, with opioid use disorder (OUD) affecting millions worldwide. Research indicates significant sex differences in addiction patterns, with women exhibiting faster addiction progression, heightened cravings, and increased relapse rates compared to men. However, the biological mechanisms underlying these differences remain poorly understood. This study aims to investigate how chronic heroin use and withdrawal impact gonadal hormone levels in male and female rats, shedding light onto the role of opioid addiction on hormonal regulation. Using a 20-day heroin treatment followed by a 20-day withdrawal period, we examined changes in locomotor response, fluctuations in key gonadal hormones (testosterone, estradiol, and progesterone), and differences in brain activity patterns. Our preliminary data  suggest that females more consistently develop sensitization to heroin and also do so at an earlier time point compared to males. Our ongoing research is working to quantify serum hormone levels across heroin treatment, as well as developing a way to measure neural estradiol activity in real-time during sensitization. Future work will focus on the long-term effects of hormonal disruptions on brain signaling pathways and opioid receptor regulation, with the ultimate goal of informing sex-specific therapeutic interventions for individuals struggling with opioid addiction. Understanding these hormonal changes is crucial for developing more effective, personalized treatment strategies for OUD. By furthering the research on opioid addiction and endocrine function, this research highlights the need to consider sex as a biological variable in addiction studies.

As modern electronics shrink rapidly, DNA stands out as a promising material for future technology due to its atomic scale and durability. Scientists worldwide are studying DNA’s electronic behavior in various conditions. This work simulates the quantum charge transport within a uniform DNA strand consisting of the cytosine-guanine (C-G) base pairs to understand its non-symmetric current-voltage characteristic curve. I used known quantum calculation methods such as the Density Functional Theory (DFT) along with Green’s function to calculate the transmission of the system at different energy levels. I also used Schrodinger’s equation to determine the energy profile of the system. In the strand for this study, the electron wavefunction at the Lowest Unoccupied Molecular Orbital (LUMO) energy level is concentrated in the second half of the DNA strand, pointing to an asymmetry of the system. This asymmetry spans for various lengths of the C-G strand. My work brings light to new technologies that are available for us to use and facilitates our knowledge of bioelectronic systems. With more understanding of DNA and its electronic properties, we can engineer faster and smaller devices.

This project critically examines online narratives about human and more-than-human cloning, with a focus on the spread of misinformation, radicalization, conspiracies, and their dangerous impact. At first glance, discussions about human vs. more-than-human cloning differ significantly. Human cloning is commonly considered morally objectionable, with supporters often forming part of controversial communities. In contrast, more-than-human cloning frequently sparks curiosity and, in some contexts, is encouraged. It is viewed not as an "act against God" but as a testament to human intelligence and dominance. This difference in responses raises many questions: Why are responses so dissimilar? How does online discourse drive these reactions? And can these distinctions--these different understandings of personhood and "life"--reinforce or perpetuate ideologies that cause harm? To answer these questions, I examine academic explorations of cloning and compare them with ones found all across the digital sphere-from social sites such as Reddit, X (formerly known as Twitter), and 4chan, to YouTube comment sections. Using a digital, “websplorer” approach, I analyze different perspectives on cloning, ranging from the "manosphere"-- interconnected misogynist online communities, scientism, and how they relate to the more-than-human. After a critical interrogation of these perspectives, I invite the user to consider an alternative, perhaps more ethical, approach to discussing cloning, one that does not reinforce heteronormativity, human exceptionalism, or pro-eugenic views. This alternative approach includes an exploration and critique of the Western concept of “personhood” and its limitations regarding cloned life, human and more-than-human.

California’s Universal Meal Program (UMP) provides free meals to all public school students, reducing household food expenses and potentially freeing up time previously allocated to meal preparation. This study investigates the program’s impact on household resource allocation, analyzing shifts in income use and time management through a difference-in-differences approach. Using data from the American Time Use Survey (ATUS) and the Consumer Expenditure Survey (CES), the research examines variations across socioeconomic groups to determine whether the UMP influences financial decisions, work-life balance, and food-related behaviors. By exploring these downstream effects, the study aims to provide insights into the broader implications of universal meal programs beyond food security, offering evidence to inform future policy decisions on their expansion and effectiveness. 

Neural epidermal growth factor-like 1 (NELL1) is a protein that plays a significant role in bone and tissue development. Recent research has shown that NELL1 may also be involved in cancer progression, making it an important target for cancer research. In neuroendocrine prostate cancer (NEPC), the role of NELL1 remains largely unexplored, particularly in relation to the neuroendocrine features that make the cancer very aggressive. I investigated how NELL1 affects the transcription of principal genes associated with neuroendocrine differentiation, a process in which prostate cancer cells become similar to nerve and hormone-releasing cells, making the cancer more aggressive. Through quantitative Real-Time Polymerase Chain Reaction (qRT-PCR), I measured how the transcription of various genes changed when NELL1 levels were altered in prostate cancer cells. This technique quantifies mRNA levels, revealing genes' transcriptional activity. I found that changing NELL1 levels leads to changes in the transcription of certain genes that control neuroendocrine features of the cells. This suggests that NELL1 may crucially control prostate cancer aggressiveness. By understanding its relationship with key NEPC genes, this could lead to new treatment approaches and improved therapeutic drugs for patients.

Technologies like CRISPR-Cas9 have emerged as promising tools for gene regulation and single nucleotide editing. The field has recently developed mRNA responsive base editors that can edit a genomic scratch pad and record mRNA expression and abundance in bacterial cells over time. RNA responsive base editors can let us retroactively study gene expression that can result in phenotypic differences. However, in complex heterogeneous communities, such as biofilms, monitoring the phenotype and expression of individual cells in real time is challenging. Pairing fluorescence signals to levels of mRNA can convey spatial information about how individual cells behave differently in complex communities. Our goal is to achieve mRNA-responsive base editing to generate fluorescent reporter output. To accomplish this, we will utilize the two existing systems, Rptr, which performs mRNA-responsive base editing, and CRISPR activation (CRISPRa), which can activate a fluorescent signal. These two systems will simultaneously perform base editing and CRISPR activation within the same cell. For this purpose, we will prototype orthogonal CRISPR systems that can independently recruit either activators or base editors through RNA hairpins attached to the guide RNA. My work focuses on designing synthetic fluorescence reporters with installed stop codons that can be modified with base editing and then activated with CRISPRa. My reporters will allow for rapid prototyping of mRNA responsive base editing with RNA hairpin recruitment. We can then find our best performing RNA-recruited base editing system to use in a multiplexed effector system. Ultimately, this integrated approach will couple mRNA expression with a fluorescent reporter read out, allowing us to monitor individual bacterial cells within complex populations.

Self-organized criticality is the concept that certain systems naturally evolve to a critical point where one more incremental addition will cause the whole system to shift or reorganize. It is thought that many natural phenomena such as earthquakes, avalanches, and wildfires exhibit and can be explained according to this. The probability of a certain size event (“avalanche”) occurring can be described using the power-law distribution. Our work focused on finding the parameterizing exponent of this distribution. To accomplish this, we created computer simulations of Activated Random Walk (ARW) a probabilistic model that exhibits self-organized criticality and has good potential for universality. By finding the critical exponent in the power-law distribution describing ARW stabilization, we advance the understanding of self-organized criticality and add to a body of research which may improve our ability to predict disastrous events and their effects.

Directly converting fibroblasts (that make up scar tissue) into skeletal or heart muscle without a pluripotent intermediate (direct skeletal muscle or cardiac reprogramming) is one of the most promising methods for regenerating lost muscle tissue, but its low efficiency in human cells remains a significant obstacle toward clinical application. In collaboration with the Institute of Protein Design, UW, we have designed several synthetic minibinders against receptor kinases which are highly specific to their cognate receptor. Utilizing these minibinders we have created a new class of designed protein, called heterofusions, that fuse two unrelated minibinders together to force the two cognate receptor kinases together in an unnatural pairing, which could elicit novel signaling responses not achievable using natural ligands. However, which heterofusions elicit novel signaling is unknown. We aim to use direct skeletal muscle and cardiac reprogramming systems, which would benefit from this novel signaling, to screen which heterofusions elicit novel signaling to increase efficiency. To do this I developed an inducible direct cardiac reprogramming system and we also used a previously established inducible direct skeletal muscle reprogramming system to be backgrounds for screening heterofusions, with efficiency determined by imaging cardiac and skeletal muscle development makers. We found a few heterofusions, including that which brings together TrkA and BMPRII (TAB2), increased the efficiency of skeletal muscle reprogramming. I found in signaling experiments using Chinese hamster ovary cells modified to express human TrkA and BMPRII that TAB2 upregulates pERK and pCREB. Interestingly, pCREB is not part of native TrkA or BMPRII signaling, meaning novel signaling is occuring. Additionally, I have shown pCREB inhibition with a small molecule impairs direct skeletal reprogramming and TAB2’s ability to increase efficiency, showing pCREB is TAB2’s mechanism of increasing efficiency. These results show heterofusions novel signaling abilities and its applications in revolutionizing regenerative therapies.

Given the pressing challenges of climate change caused by human interference in natural systems, the civil engineering industry must adopt more sustainable solutions. One approach is the use of supplementary cementitious materials (SCMs), as cement production is a major source of CO₂ emissions. This ongoing study investigates the use of zeolite as an SCM in pervious concrete. During the summer of 2024, over a dozen pervious concrete specimens were cast with 0%, 25%, and 50% zeolite powder replacing traditional Portland cement. Zeolite, a naturally occurring mineral formed from volcanic eruptions millions of years ago, has been shown to adsorb pollutants and, when used as an SCM, can reduce CO₂ emissions from cement production and potentially increase the material's levels of strength. To assess the impact of zeolite on the mechanical and hydraulic properties of pervious concrete, tests on compressive strength, porosity, and permeability shall be conducted during the Winter 2025 and early Spring 2025 quarters. Results will be shared as laboratory tests are conducted and data is analyzed. The filtration capacity of pervious concrete for different types of pollutants, both with and without zeolite, is a key focus for future phases of this research project.

Machine learning models are increasingly applied across scientific disciplines, with deep-learning based pose estimators revolutionizing the fields of neuroscience and marine biology, allowing researchers to automate and enhance accuracy of behavioral analysis. While markerless pose estimators have transformed behavioral neuroscience, their effectiveness is limited by a lack of species- and domain-specific data, especially for marine invertebrates such as cephalopods and starfish. Due to their highly flexible body structures, starfish cannot be effectively represented by the rigid skeletal models commonly used for terrestrial vertebrates, making existing pose estimation techniques unreliable for tracking their movements. This project addresses this by developing a deep learning-based pose estimation model and archive database specific to cephalopods and starfish. Using DeepLabCut, we train a supervised machine learning model to track movement patterns in both naturalistic and laboratory settings. Our dataset, sourced from the Hodin lab in Friday Harbor, undergoes preprocessing with embedding and clustering algorithms to identify representative frames for model training. By establishing a reliable, quantitative framework for cephalopod behavior analysis, this product can enhance reproducibility and contribute to the development of standardized methodologies and definitions of behaviors in marine and neuroscience research. This tool would ease cross-lab collaboration and eliminate ambiguities when investigating cephalopod and starfish behavior.

The Type 4 pilus (T4P) in Neisseria gonorrhoeae, and other bacterial species, is a protein system responsible for host-cell adhesion of the pathogen. Insight into the structure of this system necessary for N. gonorrhoeae pathogenesis can aid the development of novel therapeutic avenues. PilC, the adhesin located at the tip of the T4P, is essential for the initiation of pilus assembly, DNA transformation, and host-cell adhesion. It is believed to interact with a complex of minor pilin proteins to initiate pilus assembly, but the mechanisms of this process are unclear. My project aims to develop an amber-codon suppression system to investigate the function of PilC and its interactions with minor pilins and host cells. Based on computational modeling, the last 12 amino acids of PilC form a beta-strand that binds to the minor pilin PilK to initiate piliation. I designed a mutated version of the PilC gene by inserting an amber stop codon (sequence “TAG”) before the genetic code for this beta-strand. When expressed in gonorrhoeae, the mutated gene leads to a loss of T4P. Next, I aim to genetically modify an existing tRNA to read an amber stop codon. I hypothesize that such a tRNA, known as an “amber suppressor,” when expressed in the non-piliated cell, should rescue the defect in PilC by reading the amber stop codon, thus enabling translation of the complete, functional protein. The resulting cell should change from non-piliated to piliated, confirming that the final beta-strand of PilC is essential for T4P formation. Once I develop a functional amber-suppressor system in N. gonorrhoeae, I intend to study other domains of PilC and the minor pilins essential to T4P biogenesis, by extending the system to enable site-specific incorporation of non-canonical amino acids with useful properties.

Medical debt is a significant burden with fourteen million Americans owing at least $1,000, and the U.S accumulating at least $220 billion (Rae & Rakshit, 2024). Researchers have developed the concept of financial literacy to help patients understand health insurance and apply this newly-acquired knowledge to actively manage their medical bills. Our research challenges the portrayal of medical debt as the patients’ fault for lack of financial literacy and reframes it as a structural problem that purposefully blocks people’s access to financial aid resources. We conducted seven semi-structured interviews with healthcare workers, representatives from non-profit organizations, and financial counselors who help with medical debt. In the interviews we asked about their work, challenges they may face, and recommendations for improving access to financial aid. We recorded these interviews on Zoom, transcribed, and coded them with qualitative analysis software, Dedoose. Our interviews showed that hospitals mandated to have financial aid policies do not help patients access these policies. The documents contain excessive jargon and lack uniformity across hospital systems. Because of this obscurity, many patients are unaware of financial aid opportunities, unable to understand their eligibility and end up with exorbitantly high medical bills. Furthermore, we discovered that healthcare providers are unable to navigate these policies, leaving patients without adequate support. Our results show that policies solely focusing on improving financial illiteracy among individual patients fail to address that hospitals and insurance companies block patients from resources that mitigate medical debt. We advocate for widespread user-friendly financial aid guides, health financial literacy curricula for healthcare staff, and the public dissemination of financial aid resources across clinical settings. Addressing financial illiteracy as a systemic instead of an individual problem helps create a more equitable and accessible health system that enables patients to prioritize their well-being over managing their medical debt.

A factor influencing the ability to tune into a single speaker in the presence of competing speech is speech rhythm. The Selective Entrainment Hypothesis suggests that attention fluctuates periodically and synchronizes with speech, a quasi-periodic stimulus. This synchronization allows the brain to predict when the most salient parts of speech will occur and direct attention towards those moments. According to the hypothesis, more rhythmic speech should be easier to synchronize with, as it is more predictable. This hypothesis has been supported by previous behavioral research, which found that altering the rhythm in the target speech stream decreased comprehension of the target speech, while rhythm distortion in the background improved comprehension, likely because it became a weaker competitor. The present study replicated and extended these findings by recording electroencephalographic (EEG) data from listeners (N = 20) to measure phase locking, or synchronization, between the target speech envelope and neural activities. I ran EEG sessions, which began by exposing participants to the target speaker’s voice on its own. Participants then listened to 300 sentence pairs, which I created by playing a sentence spoken by the background speaker and sentence from the target speaker simultaneously. The sentence pairs were divided into three rhythm alteration conditions: target-altered, background-altered, and neither-altered. After each trial the participants answered a multiple choice comprehension question to collect behavioral data. Using EEG allowed for a more direct measurement of synchronization compared to behavioral results alone. We test the hypothesis that in the conditions there will be the strongest phase locking in the background-altered condition, followed by the neither-altered, and worst in the target-altered condition, a pattern that mirrors the behavioral results. This will provide more insight into the role of rhythm in speech processing and has potential future implications for hearing aid development. 

Alcohol and cannabis are associated with increased rates of sexual risk behaviors, especially unprotected sex, and decreased perception of the risk involved in unprotected sex. However, little research has explored the relationship between the context of substance use (e.g., partner presence, simultaneous alcohol and cannabis use) and sexual risk behaviors. Multilevel models tested if simultaneous alcohol and cannabis use with a romantic partner present was associated with a greater likelihood of sex, sex while intoxicated, or unprotected sex compared to using only alcohol with a romantic partner present. Young adults (n=409, ages 18-25) who reported using alcohol alone at least three times and alcohol and cannabis simultaneously at least once in the last month were recruited from the Seattle area. Participants completed six two-week periods of twice-daily surveys over two years. Items measured alcohol and cannabis use, presence of others during use, whether sexual intercourse occurred, condom use, and intoxication during intercourse. Analyses were conducted on 308 participants who reported the presence of a romantic partner during use at least once. Simultaneous alcohol and cannabis use with a partner present was associated with significantly higher rates of sex while intoxicated compared to days when only alcohol was used with a partner present. No other associations were found. Although there was no increase in the likelihood of sex or unprotected sex on simultaneous use days with a partner present (versus alcohol-only days with a partner present), there was an increased likelihood of sex while intoxicated. The increased likelihood of sex while intoxicated on simultaneous use days with a partner present could lead to issues with consent and harmful emotional/psychological outcomes (e.g., guilt, regret, lowered self-esteem, worse self-image). Future work could expand the definition of sexual risk behaviors to include these outcomes of sexual encounters rather than focusing exclusively on protection.

This research explores the effects of water deficit treatments on the leaf structure and efficiency of photosynthesis of Miscanthus sinensis 'Bandwidth,' a grass popular in landscaping and known for its variegated leaves, an alternating green and yellow banding pattern found along each leaf blade. Previous research on Miscanthus suggests that leaf variegation can influence the efficiency of photosynthesis, however, the impacts of variegation in Miscanthus under water stress remains underexplored. By measuring chlorophyll concentrations, leaf areas, and photosynthetic efficiency in both the green and yellow regions of the leaves, this research evaluates how water stress affects the plant’s overall performance. Measurements are compared between the green and yellow portions of the leaves across high and low water treatment groups to better understand the impact of water deficit on the plant's overall performance. The preliminary results indicate that water availability affects total leaf area, the ratio of green to yellow area, chlorophyll content in both yellow and green sections, and photosynthetic performance, as measured by stomatal conductance of gas exchange and the performance of photosynthetic components in the leaves under both high and low water treatments. This research is part of the University of Washington’s Climate Ready Landscape Plants project, which aims to promote sustainable landscaping practices and urban resilience strategies in response to climate change. The results from Miscanthus can continue to encourage sustainable landscaping, urban resilience, and maintaining biodiversity by examining plant adaptability under drought-like conditions.

The ability to learn from others by observing and imitating useful behaviors has been proven as a key component of human and animal evolution. However, enabling AI agents to effectively learn from others remains a fundamental challenge. Indiscriminately copying the behavior of other agents, Behavior Cloning (BC), leads to generalization challenges. Specifically, BC Agents trivially fail in cases where other agents have different goals or exhibit different levels of competence. However, pure Reinforcement Learning (RL) agents often learn inefficiently from scratch and struggle to learn in environments with a heavy exploration penalty. A key criteria of effective social learning is learning when to copy, and when it is better to rely on individual learning. In this work we propose a new algorithm, called Selective Behavior Cloning (SBC) which uses RL to enable an agent to learn when and who it pays to copy.

Lys-R type transcriptional regulators (LTTRs) are one of the largest families of bacterial transcriptional regulator proteins with over 850,000 known members.  Many of these LTTRs are enriched in our gut microbiota, whose metabolic processes affect human health outcomes. LTTRs regulate gene expression through the binding of specific ligands to their ligand binding domain. Currently, less than 500 of them have been studied which represents a severe knowledge gap that conventional methods of characterization are unable to keep up with.  We aim to create a high throughput methodology to characterize LTTRs by their corresponding ligands that regulate gene expression. We are currently developing an assay to use chimeric LTTRs, or engineered LTTRs that share the same DNA binding domain yet a variable ligand binding domain. The use of chimeric LTTRs, which will all bind to the same DNA promoter, will potentially allow dozens of LTTRs to be tested in one assay. Our work thus far has demonstrated that chimeric LTTRs can be expressed in E.coli cells and purified using affinity chromatography and magnetic bead purification. We have also demonstrated that their ligand binding domains are functional and specific via differential scanning fluorimetry, and that their DNA binding domains are functional using an electromobility shift assay using SYBR green and SYPRO ruby dyes. Future work will explore their ability to regulate gene expression when their proper ligands are introduced with a substrate-induced gene expression reporter assay. Then uncharacterized LTTR candidates to be made into chimeras will be selected via a bioinformatic sequence similarity network analysis for assay piloting. If successful, this assay has potential to elucidate new metabolic pathways of our gut microbiota allowing for better understanding of their complex relationship with the human body.

I aim to uncover the impact of mass graves on indigenous populations, particularly focusing on how such atrocities contributes to the dehumanization and cultural erasure of these communities. Throughout history, colonization, genocide, and systemic violence have led to the forced removal and killing of indigenous people. When examining these sites, I hope to illuminate how the existence of mass graves strips indigenous populations of their humanity, undermines their grief and cultural practices, and perpetuates cycles of trauma. This research also integrates the concepts of necropower and necropolitics to further understand the dynamics surrounding mass graves and their implications. Necropower refers to the ways in which political power determines who is allowed to live and who must die, thereby shaping life through the control of death. Within this framework, mass graves are not merely sites of death; they symbolize a historical and ongoing exertion of power over indigenous bodies, reflecting systemic oppressions that dictate the value of life within these communities. Similarly, the concept of necropolitics will be explored to analyze the ramifications of governmental and societal decisions regarding the recognition, treatment, and memorialization of mass graves. Necropolitics involves the regulation of populations and life through the lens of death, revealing how political authorities often manipulate narratives around mortality to control and marginalize indigenous peoples. By investigating the political implications of mass grave sites, this research will illuminate the struggles for justice and recognition faced by indigenous communities. Questions that will be explored: How is the relationship between state policies and indigenous rights reflected in the treatment and acknowledgment of mass graves, and what are the potential paths toward justice? How do indigenous communities respond to the existence of mass graves? What strategies do they employ to resist the narratives of dehumanization and cultural loss? 

Spinal cord injuries (SCI) affect over 1.2 million people in the United States, resulting in severe motor impairments due to disrupted communication between the brain and muscles. While physical therapy is the standard treatment of rehabilitation, its effect on recovery is limited. The pairing of spinal cord stimulation (SCS) and physical therapy is a promising new improvement for rehabilitation. SCS is thought to work by increasing spinal excitability, allowing more neural input to generate voluntary movement. However, preliminary data have shown that training on one task may interfere with progress in another, raising questions about the mechanisms underlying motor recovery after SCI and how to optimize rehabilitation strategies. In this project, we explore how multichannel, targeted, activity-based spinal stimulation (mTADSS) can enhance functional recovery in a rodent model of SCI. Using intraspinal stimulation, we examine whether training multiple tasks during a therapy period will interfere with the effect of recovery. Our experimental design consists of five groups of rats that first undergo baseline motor assessments, including training to evaluate grabbing ability and measure both grip force and range. Following these assessments, the rats receive a moderate cervical contusion injury, after which they undergo retraining with or without TADSS to assess its effects on motor recovery. I am responsible for operating the stimulation system and ensuring precise stimulation timing during physical training. I also collect and analyze behavioral and stimulation data to assess the impact of different rehabilitation approaches. Based on our preliminary data, we expect to find interference between tasks highlighting the need to develop better task training protocols to induce greater motor generalization. This research aims to contribute to the development of more effective rehabilitation strategies for individuals with SCI, potentially improving their mobility and quality of life.

Microfluidics has enabled researchers to engineer environments with precisely controlled fluids in submillimeter scale, making it an essential tool in biomedical research. Moreover, the study of fluidic dynamics in both closed and open channels has been a major focus in the field of microfluidics. This study specifically examines capillary flow dynamics in open microfluidic systems where capillary flow refers to the spontaneous flow of liquids in narrow spaces without the assistance of external forces. The Lucas-Washburn-Rideal (LWR) law is commonly used to describe capillary flow dynamics in closed and open channels, microporous media, and threads that assumes a viscous regime in which capillary forces are counterbalanced by friction with the solid channel walls. However, in conditions beyond the viscous domain, inertial forces become significant, leading to an imbalance between wall friction and capillary force (e.g. the inertial regime at the onset of capillary motion). This study proposes a straightforward criterion for identifying inertial effects using the Lucas-Washburn-Rideal (LWR) law. This criterion is derived by analyzing the plot of a characteristic function, F, that is defined as the product of the cross-sectional area at the meniscus location, the travel distance, and the meniscus velocity. To validate this criterion, we present four different examples: open-channel devices with converging and diverging channel configurations, an open channel separated into two daughter channels in a symmetrical or asymmetrical configuration, and a two-phase capillary flow experiment in which pentanol pushes a plug of water in an open channel. These experiments successfully validate the proposed criterion for identifying inertial effects in capillary-driven flow within open channels. Furthermore, we also demonstrate that the Bosanquet equation can serve as an accurate model for open capillary flows in rectangular channels with progressively decreasing cross-sections. This study could impact the design of microfluidic systems that traditionally assume negligible inertial effects.

Cardiopulmonary bypass (CPB) is a conventional way to treat the majority of cardiac surgeries. CPB is used during heart surgeries to circulate blood out of the patient's body in order for surgeons to operate on the heart. However, CPB has led to inflammation and multiorgan dysfunction especially leading to post CPB complications in neonates. Lack of questioning and understanding behind the complications of the technique have posed issues for improvements to clinical outcomes. Specifically, lack of understanding of molecular mechanisms and CPB-associated post surgery inflammation have posed obstacles to improvement of methods in recent years. To better understand these mechanisms, we performed mRNA and ATAC sequencing on circulating leukocytes from neonatal CPB patients. Notably, IL-8 and TNF-α were strongly upregulated in leukocytes. To explore these findings, I performed in-vitro experiments of running THP-1 human monocytic cells to CPB-like conditions, including high shear stress and cooling/rewarming. These experiments were collected and studied at times pre and post shear, and recovery post shear. Experiments regarding blood plasma changes were proposed and this plasma was similarly collected during varying conditions pre and post bypass. ELISA kits were run on antigens AREG and EREG to determine how antigen binding changes with shearing. Sheared then rested samples were found to show a significant increase in antigen binding in both kits AREG and EREG. Sheared and processed samples also showed an increase in binding when compared to the static samples. I have shifted my focus from plasma experiments to investigating the effects of commonly used plasticizers on blood composition. Specifically, I am analyzing how these plasticizers influence changes in blood and plasma using a PIPSeq kit.

The retina is composed of many neurons that pre-process light stimuli before synapsing to the brain. To understand the function of different neurons, tracing neurons on a scanned image of a retina by hand is necessary to identify the neuron’s locations and synapses. Thresholding is an image processing technique that separates an image into two or more classes of pixels, simplifying an image and targeting specific structures. My goal is to create a tool to make annotation easier. I am coding a threshold program to generate binary images that will separate neurons from other surrounding neurons and the background. After generating these regions, I find their centers and approximate the region as a circle to match the style of annotations done by humans. To compare accuracies between machine and human, I compare overlapping areas between the circles created by machine and circles annotated by humans. I aim to have 80 percent accuracy in areas between the neurons annotated by a machine and neurons annotated by human annotators. Thresholding is a computationally simple process that can be applied with ease. A highly accurate threshold would make annotating quick and efficient, allowing for related studies to be conducted. Future work includes applying a threshold to a larger image and tracing a single neuron throughout a z-stack instead of identifying individual sections of neurons in a single image. 

Ayurvedic home remedies have been utilized for centuries as effective and accessible solutions for a wide range of health conditions. However, their use remains unknown in Western medicine due to limited understanding and scientific awareness. This review aims to bridge this gap by providing scientific reasoning and research behind three commonly used Ayurvedic remedies: Tulsi (Ocimum sanctum) for managing fevers, Turmeric (Curcuma longa) for alleviating arthritis, and Ashwagandha (Withania Somnifera) for stress management. These remedies not only offer an alternative to conventional medicine but also address critical barriers such as cost, accessibility, and empowering the body’s natural ability to heal. By highlighting the mechanisms of action, clinical efficacy, and safety of these remedies, this paper seeks to justify their use to a western audience, while alleviating misconceptions about allopathic medicine. The findings underscore the potential of Ayurvedic remedies as cost-effective and viable options for individuals facing challenges such as limited mobility or financial constraints. Ultimately, this work advocates for the integration of scientifically validated Ayurvedic practices into modern healthcare to provide a holistic and affordable approach to wellness.

Interfacility transport (IFT) is essential when a patient's care needs exceed the capabilities of their current hospital. However, pediatric patients face a disproportionately high demand for IFT due to the specialized nature of pediatric care. Pediatric IFT is a complicated and risky process with adverse events occurring in up to 70% of critical care ambulance transports even with a highly trained team. This project aims to explore pediatric transport stakeholder workflows, decision making, technology, and communication to identify potential areas for improvement. In this phase of the project, we conducted semi-structured interviews with key stakeholders, including Medical Control Physicians (MCPs), Referring Providers (RPs), and Pediatric Critical Care Transport Teams (PCCT). Participants were asked to describe their roles, tasks, decision-making processes, and communication strategies throughout the transport process. The goal of the study is to qualitatively analyze these interviews to uncover key themes and insights. For methods, we employed NVivo qualitative analysis software to analyze data from 16 interviews. Participants were contacted and voluntarily agreed to take part in the study. Through this research, we aim to gain a deeper understanding of stakeholder experiences in the IFT process, which will inform future efforts to improve pediatric transport practices.

Obesity in youth populations is an increasingly prevalent issue in the U.S., affecting 14.7 million children between ages 2-19. Evidence shows that poor diet quality directly contributes to inflammation in body-weight regulating areas of the brain, which predates the occurrence of obesity. Controlled-feeding studies can improve diet quality and assess health outcomes in children with overweight or obesity but require thoughtful execution and strict participant adherence to the study-prescribed diet. This project will assess the feasibility of a short-term controlled feeding study using two measures: acceptability from children of a high-quality diet menu and caregiver opinion on their child’s participation in a controlled feeding study. In collaboration with the Fred Hutch Nutrition Kitchen, I created a high-quality diet menu to meet study goals including: standard nutritional principles of USDA guidelines, whole foods, and low-fat, as well as age-appropriate and easy to prepare. Furthermore, I developed a child-appropriate taste-test questionnaire using a 5-point Likert scale and contributed to an interview guide in order to capture the qualitative and quantitative data from parents. These tools will be applied in a study of 7-10 families with healthy children aged 9-11. Families will attend a focus group where child caregivers will undergo the structured interview and children will taste-test the menu items. Quantitative survey data from the taste-test will assess menu acceptability to help ensure participant adherence to a study-provided diet. Qualitative data themes from adult caregivers will assess feasibility of child participation in a controlled feeding study by illuminating social and logistical concerns of parents. Understanding child acceptability of a high-quality diet menu and the perceived feasibility of study participation from families will inform the most optimal design of our planned controlled-feeding study in children to test if high-quality diet can acutely reduce inflammation in body-weight regulating areas of the brain.

Engineered heart tissues (EHTs) have emerged as a promising tool for cardiac disease modeling and drug screening, allowing for better study of heart diseases (HDs). However, most current EHTs are composed of only a mixture of an extracellular matrix, heart muscle cells, called cardiomyocytes (CMs) and cardiac fibroblasts, without a vascular element. This prevents the study of the impacts of flow and the endothelium on cardiac function, despite their important role in both development and disease progression. Endothelial cell (EC) function is essential for maintaining cardiac homeostasis through protective signaling interactions between ECs and CMs. Disruption of endothelial function through vascular stressors such as hemodynamic changes and acute inflammation can trigger EC dysfunction, dysregulating cardioprotective signaling. It is important to incorporate the endothelial and perfusion components in EHT in vitro for better disease modeling and drug testing. The Zheng lab has developed a tube-like perfusable collagen-based EHT model, where CMs are embedded in the bulk collagen matrix, and the inner lumen of the tube can be endothelialized, serving as an effective, in vitro, model of cardiac vasculature. This project controls the size of the inner tube diameter of this model utilizing structural and contractile properties of muscle cells. Through the integration of these cells, we can maintain the inner diameter under a range of flow conditions, and subsequently use the model to identify healthy and unhealthy flow conditions within the EHTs. This project establishes a perfusable EHT model that allows us to examine EC function under several flow-related changes and, in the future, assess the effect of endothelial dysfunction on cardiac function.

Downregulation of the mTOR complex has been shown to increase lifespan and delay development of multiple organisms, including Drosophila melanogaster. Rapamycin, an inhibitor of this complex, is undergoing FDA-approved clinical trials as a promising anti-aging drug. However the impact of genetic variation on rapamycin's response is unknown. Our study of 140+ genetically diverse Drosophila strains revealed significant variation in pupation time after rapamycin exposure, however, the underlying mechanisms of this variation remain poorly understood. Surprisingly, this sensitivity does not correlate with genetic variation in or around the mTOR gene. We therefore hypothesize that differences in phosphorylation of downstream mTOR targets may explain this variation. Currently, we are using multiple approaches to investigate how activation of downstream targets differs between highly resistant and sensitive strains. We aim to characterize the phosphoproteome of first instar Drosophila larvae from highly sensitive and resistant strains. First instar larvae were treated with rapamycin for 12 hours, followed by mass spectrometry analysis to identify phosphorylation changes in mTOR pathway targets. To validate that 12 hours of treatment induces a rapamycin response, we monitored the growth of a parallel group of larvae until 72 hours and measured their size. Sensitive DGRP strains, 348 and 517, showed a twofold reduction in length when treated with 20uM rapamycin compared to control (p-value <0.0001), while the resistant strain, 441, showed no significant decrease. Comparing the phosphoproteome of multiple resistant and sensitive lines will uncover molecular factors associated with resistance or sensitivity. Additionally, whole-larvae RNA-seq will assess the expression profile of these factors, revealing whether gene expression of tor pathway-related genes contributes to sensitivity. Understanding the mechanisms behind rapamycin resistance or sensitivity is critical for its clinical application. This project highlights the value of accounting for genetic variation in drug development, guiding future approaches for developing new drugs.

Research indicates that how parents respond to their child's pain can impact the child's experience of abdominal pain during childhood. To better understand how the parental responses influence abdominal pain, a systematic literature review was conducted to examine recent research into parent responses to illness behavior and the influence on child functional abdominal pain. A search of the electronic databases PsychINFO, PubMed, and Web of Science was administered of articles published from 2015 to 2025 using the search terms unexplained abdominal pain, child*, psychosocial, assessment, disorders of gut brain interaction, and somatic. Searches were also administered of articles by authors Rona Levy, Tonya Polarmo, and Miranda Tilburg published from 2015 to 2025. The criteria for the studies were that the participants must include participation from parents/caregivers of children with abdominal pain, the pain must not be linked to an organic cause and children must be from the U.S.. Ten studies met criteria and were included in the review. One of the studies had participants of U.S. military families which meant some of the participants were living outside of the U.S., but the exact location is not included in the study. The literature found that parental perception of pain, parental catastrophizing, and parental protectiveness all had an impact on the pain of the child. However, the number of children in a family did not influence the parental perception of pain, parental catastrophizing, and parental protectiveness in the parent. Additionally, positive effects were found for CBT(cognitive behavioral therapy) treatment involving parents and children.

Tetralogy of Fallot (TOF) is the most common cyanotic congenital heart defect and consists of four structural defects that prevent babies’ hearts from delivering oxygenated blood to their body. When life saving surgeries correct these defects, the resulting scar changes the way the heart conducts electrical impulses, causing abnormal heart beats later in life. These abnormal heart beats, arrhythmias, often present as sudden cardiac arrest. Due to the high risk of arrhythmias in patients with repaired TOF, it is clinically important to understand the exact mechanisms causing them. These mechanisms provide insight that is essential to developing personalized methods for preventing arrhythmias. In our lab, we use late gadolinium enhanced MRI scans from TOF patients to create personalized computational models of their heart and particular scar distribution. We then attempt to induce arrhythmias in our models, which are individualized and represent subcellular and cell-scale electrophysiological phenomena. These models are useful because they allow us to study arrhythmia mechanisms noninvasively. We expect that patients whose computational models are susceptible to arrhythmias will also be more likely to experience arrhythmias in real life. We also aim to use the mechanistic insights from these simulations to determine new ways of predicting arrhythmia risk in this vulnerable patient population. Our results should predict what subset of patients would benefit from invasive preventative procedures, and help give patients with TOF a better understanding of their personal risk with or without those procedures. We hope to use our methods and results to create a simple and accessible arrhythmia risk stratification tool.

Natural growth factors like fibroblast growth factor (FGF) are essential for maintaining pluripotency in induced pluripotent stem cells (iPSCs). However, current limitations of native growth factors include signal instability, off-target pathway activation, and dependence of xenogenic components for production. To address these issues, we developed a synthetic protein, C6-79C, which consists of six scaffolded subunits of a de novo designed FGFR1/2c binder, mb7. While mb7 functions as an FGF pathway inhibitor, the hexameric C6-79C acts as a receptor tyrosine kinase (RTK) agonist, providing more isoform-specific and prolonged signaling compared to native FGF. We formulated SynGrow, replacing FGF with C6-79C in minimal E8 media, and compared its performance against commercial media. Our study focused on three objectives: (1) comparing the expression of pluripotency markers (Oct4, NANOG, SOX2, and TRA1-60) in cells grown in SynGrow versus commercial media, and (2) evaluating morphology and viability under different media change regimens (daily, every other day, or no change). iPSCs grown in SynGrow exhibited superior morphology compared to those in mTeSR (commercial media). Pluripotency markers (Oct4, NANOG, and SOX2) were expressed at similar levels in both media, with SynGrow also showing higher expression of TRA1-60 across passages, confirmed by flow cytometry. Future evaluations will assess germ layer marker expression following directed differentiation. Our findings demonstrate that synthetic protein-based media formulations, like SynGrow, can effectively replace native growth factor-based media. This approach offers stable, prolonged, and xeno-free alternatives for stem cell culture, with broad implications for improving reproducibility and safety in regenerative medicine and cell-based therapies. 

Human tooth development is a complex and tightly regulated process that involves multiple signaling pathways and specialized proteins coordinating enamel formation. Enamel, the hardest tissue in the human body, is secreted by ameloblasts, which follow a distinct developmental process. Disruptions in these processes can lead to enamel-related disorders, such as amelogenesis imperfecta, a genetic condition characterized by defective enamel formation. A key factor in this disorder is WDR72, a gene that encodes the tryptophan-aspartate repeat domain 72 (WDR72) protein, which is critical for intracellular trafficking during enamel maturation. Although WDR72 has been studied in animal models, its precise localization and function in human fetal tooth buds remain incompletely understood. To address this question, I cryosectioned human fetal tooth samples at 19 and 22 gestational weeks and performed immunochemistry staining to visualize WDR72 alongside key enamel proteins. I performed cryosectioning to prepare thin tissue sections of each tooth bud sample, followed by immunohistochemical staining with antibodies specific to WDR72. I then imaged selected sections under a fluorescence microscope. Preliminary results suggest distinct WDR72 distribution in regions corresponding to secretory ameloblasts. These findings offer insights into the localization of WDR72 during tooth formation and lay the groundwork for future studies on the mechanisms of tooth regeneration. 

The marine cyanobacterium, Prochlorococcus, is the most abundant photosynthetic organism in the world. Prochlorococcus is composed of two main clades, High Light (HL) and Low Light (LL). Within the clades, further subdivisions exist as differentiated populations adapted to their environment (ecotypes). Although these organisms can be found in most global surface oceans, the ecotypes are not equally distributed latitudinally nor vertically. Furthermore, the inter-specific relationship between the ecotypes and how the proportion of each one corresponds with different environmental conditions are not well understood. Therefore, in this study I investigate the intra- and interseasonal environmental conditions (e.g. temperature, light, and nutrients) that affect the distribution of Prochlorococcus ecotypes in the North Pacific Ocean. Using python coding, I analyzed the correlation of environmental data to datasets from a series of cruises that contain optical and molecular properties of Prochlorococcus. I utilized sequenced and mapped community samples of RNA from a published dataset, also known as metatranscriptomes, to identify present Prochlorococcus ecotypes and their associated relative abundances. Additionally, I used flow cytometry data to analyze forward scatter (cell size) and red fluorescence (chlorophyll) of each Prochlorococcus cell that is captured in a sample. Expected results of this study are that 1) light and temperature will be the most important factors determining the distribution shifts between the HL and LL clades, 2) temperature will be the most important factor differentiating the HL ecotypes, and 3) nutrient levels will be the most important factor differentiating the LL ecotypes. This study will enhance our understanding of how environmental conditions influence Prochlorococcus ecotypes in the North Pacific, though the findings may not represent global patterns. Furthermore, the results suggest that Prochlorococcus strains more susceptible to environmental changes may experience ecological shifts, an issue likely to intensify as climate change impacts the ocean.

Disruption of the Wnt signaling pathway is critical in the emergence of some of the most difficult cancers to treat. Transducin β-like protein 1 (TBL1) forms a complex with β-catenin, a transcription factor that switches ON Wnt target genes (Li & Wang, 2008). The Nemhauser Lab engineered a synthetic repressor circuit, dCas9-TBL1, that targets a constructed constitutive promoter driving GFP expression in human cells. I hypothesize that levels of TBL1 activity will correlate strongly with expression of Wnt target genes. My research uses time course qPCR to test Wnt-induced gene expression in both HEK293 and HCT15 cell lines. HEK293 have normal levels of Wnt signaling, whereas the HCT15 colon cancer cell line is known to have high Wnt activity which contributes to uncontrolled cell growth. Specifically, I will extract RNA from both cell types at 6, 24, and 48 hours after treatment with a control chemical and test for expression levels of  Wnt-target genes such as AXIN2. These experiments will test whether the elevation of downstream Wnt-target gene expression is correlated negatively or positively with TBL1 activity, and will enable further understanding of this route to oncogenesis and future optimization of chemotherapy targets.

Substance use disorders are a devastating global issue and using multiple substances simultaneously has become common among drug users. Polysubstance use has been linked with higher rates of mortality, overdose, and relapse when compared to single substance use. There is currently little research on how using multiple substances simultaneously affects behavior and motivation to take drugs. Our goal is to better understand the motivations of drug seeking and consumption in rats with a history of polysubstance use compared to rats with a history of single substance use. Rats (n=18 male,18 female) were implanted with jugular catheters and trained to press a lever for an infusion of either 0.0015 mg/kg/infusion of fentanyl (fentanyl-only: FENT) or 0.1mg/kg/infusion of methamphetamine (methamphetamine-only: METH), or both (polysubstance: POLY). The rats then underwent a behavioral economics threshold test, in which the concentrations of fentanyl and methamphetamine were decreased over ten days in an attempt to determine the level of effort and motivation for the drug at each dose. The FENT and METH rats only underwent the behavior economics test for one drug and POLY rats were randomly assigned to either fentanyl or methamphetamine. Our preliminary results suggest that polysubstance use increases the motivation for consuming fentanyl but not methamphetamine; however, sample sizes are small right now and further analysis is needed. In future experiments, we will image the brains of these rats using light sheet microscopy to map the neurocircuit activation that may point to differences between polysubstance and single substance use. Understanding the differences between polysubstance and single-substance use is imperative for designing effective treatment plans that address the motivations behind drug use.

Nitrogen is often a limiting resource in marine ecosystems, and its availability is heavily influenced by human activities, sometimes causing eutrophication. The study of phytoplankton metabolism under nitrogen-limited and replete conditions is of interest due to eutrophication's ecological and economic implications and the prevalence of nitrogen limitation on marine primary productivity. To investigate the metabolic effects of rapid nitrogen addition on phytoplankton metabolism, 15N-nitrate was traced into polymerized and free amino acids in two treatments of the microalgae Tisochrysis lutea with either initially limiting or replete nitrate concentrations. Using acid digestion, derivatization, and GCMS analysis we found that the culture with a lower initial nitrate concentration incorporated more 15N into alanine, valine, serine, and threonine. This suggests that phytoplankton under nitrogen-limited conditions exhibit greater increases in metabolism than those under replete conditions following rapid nitrogen influxes. Heavy nitrogen incorporation into other metabolites was also detected. This work provides a foundational method for future studies into phytoplankton metabolism under varying environmental conditions.

Alzheimer's disease (AD) affected approximately 6.9 million Americans aged 65 and older in 2024, and it is projected to rise to 13 million by 2050 (Alzheimer’s Association, 2024). AD is characterized by progressive cognitive decline, but sleep disruption is an often overlooked symptom that emerges early in the disease's progression. Evidence suggests that AD-related sleep disturbance may originate from dysfunction in the circadian system, particularly in the suprachiasmatic nucleus (SCN) of the hypothalamus. The SCN regulates sleep-wake cycles, and recent findings from de la Iglesia lab have shown that specific SCN neurons exhibit a daily rhythm of fiber expansion and retraction. This study aims to investigate how aging and AD affect SCN structural plasticity; this could help explain circadian disturbances in AD patients. I aim to identify the age at which abnormal circadian phenotypes emerge in a mouse model of AD which shows circadian disruptions. We are currently comparing activity patterns of AD mice ages 6 to 16-months old with their wild-type littermate controls using behavioral running wheel data. We hypothesize that the AD mice will exhibit a decreased mean total sleep and shorter circadian period in constant darkness. While these symptoms are common with aging in healthy mice, we expect that they will appear earlier in AD mice than in their wild-type littermates, as disrupted sleep is an early-onset symptom of AD. Future studies will assess whether these symptoms are associated with deficits in daily structural plasticity of the SCN. By elucidating the relationship between AD, SCN neuronal structure, and circadian rhythm disruptions, this research aims to provide insights into the mechanisms underlying sleep disturbances in AD patients. Understanding these processes could potentially lead to the development of targeted interventions to mitigate sleep disruptions and slow disease progression in AD patients.

Less than 10% of drugs successfully transition from preclinical to clinical trials, principally due to the inability of currently used 2-dimensional models to simulate the 3-dimensional structure and function of human tissues. To develop 3D in vitro models of human vasculature for more efficacious screening of anti-atherosclerosis drugs, I created a device for constructing a perfusable tissue containing a lumen by leveraging open microfluidic patterning methods developed by our group: suspended tissue open microfluidic patterning (STOMP). The device can be used to pattern tissue with a hollow luminal structure lined with endothelial cells, which can be perfused via hollow posts the tissue is suspended between. Using surface tension-driven flow, a liquid hydrogel precursor solution flows through the open microfluidic channel and around the two hollow posts. After gelling, the tissue anchors to the post, contracts away from the sides of the microfluidic channel, and the STOMP device is removed. By adding a second STOMP device that can surround the first tissue another cell-laden hydrogel can be patterned around the first tissue, encapsulating it. To form a lumen in cardiac tissue, I will pattern the inner region with human umbilical vein endothelial cells (HUVECs) in an enzymatically degradable polyethylene glycol hydrogel, surrounded by human induced pluripotent stem cell-derived cardiomyocytes in fibrin hydrogel. Enzymatic degradation of the core region will form a cavity through which HUVECs will remodel the cavity walls, forming an endothelial lining. I will assess lining formation by adding fluorescent dextran to cell media being perfused through the device and measuring fluorescence through confocal microscopy in the surrounding region over time, allowing me to evaluate the permeability of the membrane to compare with physiological values. This model can then be used to screen treatments for atherosclerosis to study how drugs interact with cells in a 3D microenvironment. 

Kaposi’s sarcoma (KS) is a cancer caused by Kaposi’s sarcoma-associated herpesvirus (KSHV). While most KS tumor cells are latently infected, where KSHV is inactive, all current treatments for herpesviruses target lytic infection. The Lagunoff lab has shown that latent KSHV infection, similarly to cancer cells, induces the Warburg effect, in which glycolysis is used as an energy source rather than oxidative phosphorylation. Inhibition of lactate dehydrogenase (LDH), an enzyme that catalyzes the last step of glycolysis, increases cell death specifically in latently infected cells. This indicated that the KSHV-induced upregulation of glycolysis was necessary for the survival of these cells; however, it is unknown how KSHV induces this requirement. The goal of my proposal is to determine the viral mechanism for the induction of the Warburg effect in latently infected cells. During latent infection, only the KSHV-latency-associated-region (KLAR) of the viral genome is expressed. KLAR encodes 4 genes: vFLIP, vCyc, LANA, the kaposins, and a cluster of 12 microRNAs. I hypothesized that one of the genes or miRNAs is necessary and/or sufficient to induce the requirement for glycolysis in latently infected cells. To test for necessity, I am using KSHV recombinant viruses that have a deletion in vFLIP, vCyc, the kaposins, or the entire miRNA locus to infect endothelial cells. To test sufficiency, our lab has created lentiviral vectors that contain one of the KLAR genes or the miRNA locus to overexpress these genes in endothelial cells. I anticipate that vCyc and/or the miRNA locus might exhibit necessity/sufficiency, since prior studies have identified these as important for the regulation of other metabolic pathways. Understanding KSHV’s alteration of specific metabolic pathways in latently infected endothelial cells provides novel therapeutic targets for the inhibition of latent KSHV infection and ultimately KS tumors.

Mycoplasma genitalium (MG) is a sexually transmitted bacterial pathogen commonly associated with urethritis in men and cervicitis, endometritis, pelvic inflammatory disease, infertility, and preterm birth among women as it invades the upper reproductive tract. Due to antimicrobial resistance, infections can persist for months to years, and first-line drug choices fail in over half of all patients. Whole-genome sequencing reveals that natural nitroimidazole (NDZ)-resistant mutants have mutations in or near MG_342, which encodes a flavin mononucleotide-dependent oxidoreductase required for activation of NDZs to the toxic form. We hypothesize that these mutations reduce oxidoreductase expression or activity, impairing drug efficacy. To determine if these mutations reduce MG342 protein expression, I used molecular techniques to engineer MG strains expressing FLAG-tagged alleles of MG342 including wild type and four spontaneous resistance mutations in or near the MG_342 start codon. FLAG-tags are peptide tags that bind to commercially available, high-affinity antibodies for protein quantification. My study aims to examine how these MG342 mutations affect (1) protein levels using quantitative immunoblots and (2) NDZ susceptibility using qPCR-based minimum inhibitory concentration (MIC) assays. As MG_342 is an essential gene, we hypothesize that an alternate downstream start codon allows sufficient expression for viability of MG while reducing activation of NDZs, leading to resistance. Future RNA sequencing will examine how mutations, particularly a 92 base pair deletion upstream of MG_342, impact transcription. Developing this RNA sequencing method will help define mechanisms of resistance as new mutations are identified. Since physicians are already beginning to treat MG patients with NDZ drugs, insight into the resistance mechanisms could help determine which mutations to screen for to prevent drug-bug mismatch and treatment failure.

Lithic artifacts are global phenomena that prevail throughout the archaeological record. Unretouched lithic flakes, though highly abundant, are often ignored as diagnostic parts of an assemblage. However, a recently developed method, FLEXDIST by Will and Rathmann (2025), handles mixed, correlated, incomplete, and high-dimensional data and so is ideal for revealing detailed information from unretouched flakes. We apply this FLEXDIST method to an assemblage of lithic artifacts from Nguom Rock Shelter in Vietnam to understand how people adapted their technology to climatic changes of the Last Glacial Maximum. During the transition from Marine Isotope Stage 3, to Marine Isotope Stage 2 (Last Glacial Maximum), the climate became cooler and drier. Our results suggest that this shift in climate resulted in people adjusting their lithic technology to make longer, heavier, and thicker flakes. We interpret this as a strategic reduction of mobility, perhaps using the Nguom Rock Shelter as a refuge during the peak glacial conditions of the Last Glacial Maximum. Our application of the FLEXDIST method to a novel dataset validates its use as an analytical tool on unretouched flakes and encourages more investigation into what can be learned from this abundant and under-studied component of the archaeological record. In addition, we hope that the application of this method to the Nguom dataset will further our understanding of not only how ancient humans adapted to climate change, but how modern humans might adapt to our changing climate both in the present and in the future. 

Vibrio parahaemolyticus is a gram-negative marine bacterium that causes acute gastroenteritis in humans generally following the consumption of raw or undercooked shellfish. Mice are highly resistant to many human gut pathogens, including Vibrio, Salmonella, and Shigella spp., which has hindered our understanding of bacterial pathogenesis, immunity, and the development of therapeutics. Inflammasomes are cytosolic innate immune complexes that assemble in response to pathogen infection or harmful stimuli. Once the inflammasome is assembled, inflammatory caspases like caspase 1 are activated, driving a lytic cell death termed pyroptosis and the maturation and release of pro-inflammatory cytokines (i.e., IL-1β, IL-18). Inflammasomes have recently emerged as a necessary mediator of mouse resistance to Shigella and Salmonella, suggesting that inflammasomes may also be the cause of mouse resistance to V. parahaemolyticus. Consistent with that possibility, our preliminary data suggest that inflammasomes prevent intestinal inflammation in mice infected with V. parahaemolyticus, although the mechanism of protection is unknown. To identify the inflammasome(s) responsible for mouse resistance, I reconstitute specific murine inflammasomes in HEK293T cells, which lack most components of the inflammasome pathway. Then, I assess their activation in response to V. parahaemolyticus infection. Our previous findings demonstrated that V. parahaemolyticus robustly activates the mouse NAIP-NLRC4 inflammasome. However, we unexpectedly observed that V. parahaemolyticus infection also induces inflammasome activation in HEK293T cells even in the absence of NAIP-NLRC4 inflammasome reconstitution. This suggests the presence of an inflammasome-sensor in 293T cells that is responsive to V. parahaemolyticus infection. I am currently using inflammasome inhibitors and gene knockouts to identify this unknown inflammasome, which will ultimately aid in our understanding of host factors that mediate host defense against V. parahaemolyticus.

Initiated in Spring 2024, I wanted to answer the question of why oral histories and community engagement are imperative to the cataloging process in museums. My findings assert that these factors lead to a richer understanding of the value of belongings in the collection. My interest in this work began with a personal connection to Punjabi artifacts, as my family hails from Amritsar. A visit to the archives with my mother showed me the vital role oral history plays in understanding the value of artifacts often disregarded as insignificant. Given my family’s displacement during the Partition of 1947, this visit also developed my own goal of connecting the South Asian community with material heritage. As the only South Asian student to conduct comprehensive research on this collection, I have developed a methodology that combines archival studies with community-based knowledge gathering. I have conducted my research through museum visits and interviews with community members, using the collections as my field site. I record or note the knowledge shared during these visits, and this data has informed my findings. Indrani Chatterjee’s methods of knowledge gathering in the book, Unfamiliar Relations: Family and History in South Asia, have been my main inspiration. My  research emphasizes ethics such as cultivating respect for cultural artifacts and looking to communities as the chief source of knowledge. Through this work I have learned that the material culture can only be properly cared for if communities have access to history that is rightfully theirs. This research is important in helping decolonize collections and create spaces where marginalized voices are respected in academic and museum contexts.

Nonlinear dynamics and its related stochastic phenomena described by linear partial differential equations are exceptionally useful for modeling climate processes. In particular, climate often exhibits bistability: the system under one forcing can exist in two stable states. With changing parameters and fluctuations, the state may transition through a bifurcation (tipping point) or spontaneous pre-tipping transition. One example is Snowball Earth. Earth is thought to have a bistable ice-covered and ice-free climate and once transitioned away from ice-covered. With a time dependent parameter, we expect a bistable system will eventually undergo bifurcation. Methods have been used to predict the time until tipping. However, these predictions do not include the possibility of transition prior to the bifurcation. I calculate this probability by modeling the Snowball Earth state as an Ornstein–Uhlenbeck process through a saddle-node bifurcation. As the system approaches the bifurcation, we expect the variance of the OU process about the stable state to increase. While my model shows it increasing for most time towards the tipping point, there is an unexpected decrease near the end. I found this corresponds to a change in symmetry of the OU process distribution. To check the significance of this, I will compare with a numerical simulation of the Fokker-Planck equation for the OU process. I will also show a probability distribution for transition over time, by modeling the state as a continuous-time Markov chain that depends on the varying shape of the “barrier” in the potential function. Ultimately, Snowball Earth is a paradigm for the exchange between stochastic and partial differential equations that describes many systems. We can compare it with other systems to characterize similarities among them, as well as features making the climate system unique. This is also important as critical transition in Earth systems is a growing concern under climate change.

3D Gaussian Splatting (3DGS) is a real-time rendering method that models 3D scenes as thousands of anisotropic Gaussians, which are projected and rasterized ("splatted") onto 2D screens to synthesize images. A core challenge is ensuring these splats render in correct depth order to resolve occlusions, traditionally requiring computationally expensive sorting. We propose eliminating sorting entirely to accelerate 3DGS while preserving visual quality. To achieve this, we explored clustering algorithms to group spatially coherent splats, avoiding explicit sorting. Among these, sequential k-means clustering emerged as a promising solution, achieving near-identical image reconstruction to ground truth while reducing computational overhead. By grouping splats into depth-ordered clusters, we bypass per-frame sorting without sacrificing accuracy. We are currently reimplementing the CUDA-based forward and backward rendering passes to integrate this cluster-first approach. This work demonstrates the potential of algorithmic redesign to unlock efficiency gains in modern graphics pipelines, with implications for scaling 3DGS to dynamic scenes in VR, simulations, and gaming.

Comprehensive brain atlases are an instrumental prerequisite for neuroscientists, akin to geologic and topographic maps for geographers. In providing a spatial reference system, brain atlases allow for navigation to identified brain regions based on anatomical location. However, many standardized mammalian brain atlases have not been quantitatively validated for in vivo accuracy. Observations of various mouse brain atlases in use  reveal numerous inconsistencies and lead to unquantified errors in brain area targeting. My  hypothesis is that existing mouse brain atlases misrepresent real-world coordinates of the in vivo brain within the mouse skull. To test this, I am establishing reliable methods for the systematic measurement of true stereotaxic brain locations and quantification of coordinate discrepancies between the in vivo brain and atlases. Across a cohort of mouse subjects, I optimized the localization of fluorescent dye injections to quantify specific points in the in vivo space. I evaluated fluorescent dye injections using iontophoresis to control dye flow in mouse brain tissue through applied current. This achieved high-contrast fluorescence histochemical detection without diffusion into untargeted brain areas. In addition, I developed an algorithm that maps injection coordinates from histochemical imaging datasets and targeted stereotaxic brain locations to various brain atlas spaces. In our comparison of the average Euclidean distance between mapped real-world injection and targeted location coordinates across three standardized mouse brain atlases, we identified the MRI-based atlas to be the most accurate. Further, I computed and implemented non-negligible 3-dimensional affine transformations to correct discrepancies between the in vivo space and each mouse brain atlas. We expect this work to produce a validated and accurate coordinate system for targeting electrode insertions. This innovation will substantially improve the quality of large-scale data collection in labs around the world. 

Core needle biopsy tissue samples were prepared manually with 10% Formalin fixation followed by Hematoxylin & Eosin (H&E) staining in clinical laboratories worldwide, a gold standard for biopsy tissue preparation. The prepared samples were then sent to pathologists for analysis. The goal of this research project is to develop an automated H&E stain dispensing system capable of preparing diagnosable biopsy tissue samples in minutes, and to be integrated onto an automated core needle biopsy diagnosis medical equipment using Fluorescence Imitating Bright field Imaging (FIBI) method. This automated process reduces the time needed for the diagnosis process from days to hours. For many African countries that lack trained personnel and infrastructure, the time reduction is from a month to within a day. The reduction of cost and time makes early stage cancer diagnosis much more affordable and accessible to patients, especially in low-and-middle income countries (LMICs). This early diagnosis of cancer allows patients to start treatment earlier with projected improvement of cancer survival. The research mainly focuses on methods of H&E stain distribution and controlling stain uptake time on 1mm diameter x 16mm long biopsy tissue samples without damaging the sample using various protocols. This project also investigates whether the system should dispense hydrogen peroxide to remove excess blood on tissue specimens and Triton X-100 as a surfactant to permeabilize cell membranes for a fast stain uptake. Large volume of imaging results from automated system prepared tissue samples will be compared with results from manually prepared samples to determine the quality and reliability of the automated staining system.

The obsolescence of U.S. Navy parts pose significant challenges in managing diminishing manufacturing sources and material shortages (DMSMS). This research focuses on predicting and mitigating part shortages by analyzing case resolution times, leveraging machine learning and natural language processing (NLP) techniques, and developing data-driven methodologies. In collaboration with the Naval Undersea Warfare Center (NUWC) Keyport division, data is sourced from Navy systems that track part availability and supplier management, providing critical insights into supply chain vulnerabilities. To address these challenges, multiple predictive models were developed, incorporating classification, regression, and clustering techniques. Initial model development utilized publicly available datasets to refine methodologies and test various approaches. Extensive exploratory data analysis (EDA) was conducted to identify patterns in supply chain issues, with a focus on text-based insights and categorical variables with a company response factor. Sentiment analysis and machine learning techniques, including logistic regression, support vector machines (SVM), gradient boosting, and word embedding models, were explored to enhance predictive capabilities. Our work focused on refining these models using real-world Navy data, optimizing classification strategies, and expanding NLP applications for more proactive supply chain management. These advancements aim to improve operations and minimize delays by reducing the time required to resolve cases associated with obsolescent parts.

Genetic mutations in Caenorhabditis elegans (C. elegans) worms can be studied to understand disruptions in pathways relevant to those in humans, due to ortholog between worm genes and human counterparts. These mutations can manifest as an unmotivated phenotype where the worm displays decreased motivation to move. To explore this phenotype, we performed a series of crosses on a strain of mutated worms to map and identify which gene the mutation is on and to gain a better understanding of the underlying reasons behind the unmotivated phenotype. Our work thus far has led to the potential uncovering of a new gene correlating with this phenotype that has never been associated together before. The worm mutation named yak187 was first generated through random mutagenesis. I performed crosses between yak187 worms and various other strains that each contained a fluorescent marker on a different chromosome. Results yielded little correlations between yak187 and any of the chromosomes we tried. We continued crossing with more strains that contained markers near the ends of chromosomes of suspect and eventually narrowed our highest probable linkage to the right arm of the X chromosome. There are no mutants with this phenotype known in this region yet so our next steps are to sequence the whole genome to pinpoint the location. Furthermore, we have reason to believe that this mutation impacts the dense core vesicle (DCV) pathway impacting neuropeptide release. This pathway is important for regulating body functions, development, and emotions. Disruptions to DCV processes can result in diminished abilities for organisms to operate correctly, resulting in similar consequences as those seen in the mutated worms. The overall pathway involving the production and maturation of DCVs and the secretion of neuropeptides is similar to that in humans, making the study of this system in C. elegans further more exciting.

Glycogen Synthase Kinase 3 (GSK3) is a well-studied enzyme that is implicated in many diseases due to its regulatory role in numerous signaling pathways, both known and unknown. The scaffold protein Axin binds to GSK3 and the substrate β-catenin (Bcat), specifying GSK3 so that it primarily acts within the cancer-implicated Wnt signaling pathway. My project seeks to determine if GSK3 is recruited to other potentially unknown signaling pathways by other scaffold proteins that compete with Axin and each other to bind GSK3 at its Axin-binding site. A previous proteomics and computational experiment identified five proteins that potentially interact at this interface of GSK3. Five peptides were designed from the theorized binding sites of the proteins to evaluate whether these proteins compete with Axin. I am using an engineered mammalian cell line to indirectly measure cellular levels of GSK3's substrate, Bcat, and test whether the peptides are capable of displacing Axin from GSK3. When GSK3 is both active and bound to Axin, it causes degradation of Bcat; when GSK3 is inactivated or unbound from Axin, Bcat builds up in the cell. Lithium chloride is a known pathway-independent GSK3 inhibitor that will be used to compare the effect of the peptides on the amount of Bcat, and thus the effect on the amount of Axin-bound GSK3. Displacement of Axin by these peptides indicates that the proteins specify GSK3 for signaling pathways in a similar mechanism to Axin, and that in normal cell states, some equilibrium exists between pools of pathway-recruited GSK3. Understanding the equilibrium between these binders and their associated signal pathways would give insight into how overexpression of one can cause the development of disease states such as cancer.

Ocean microbial communities are sensitive to temperature fluctuations. This study examines the direct and indirect effects of temperature on bacterial abundance off the coast of Guam (4°N-16°N, 149°E). Water samples were collected at 10m depth and the Deep Chlorophyll Maximum (DCM) to assess bacterial abundance and its relationship with temperature and chlorophyll concentration. Results show a strong positive correlation between bacterial abundance and temperature at 10m, suggesting warmer conditions enhance microbial growth. However, no significant correlation was found at the DCM, indicating other factors, such as mixing and nutrient availability, influence deeper bacterial communities. A notable anomaly at 8°N was linked to strong currents that redistributed bacteria, concentrating them at about 200m. These findings highlight the interplay between temperature, primary production, and ocean currents in regulating microbial abundance, offering insight into how microbial ecosystems may respond to climate-driven ocean changes.