Liver disease is a global health burden accounting for two million deaths a year worldwide. The demand for transplant has quickly risen all over the world in the last decade due to an increase in the prevalence of organ failure, rising surgical success and better posttranslational outcomes. In the U.S., seventeen people die each day waiting for an organ transplant. Bioengineering tissue could address these demands and help minimize death, surgical complications, and improve patient well-being overall. To bioengineer a transplantable liver in the lab, it must successfully model the structures and functions found in native tissue. The liver is a complex organ that carries out thousands of tasks, such as energy homeostasis, nutrient metabolism, and protein recycling. To perform these functions simultaneously, the liver separates its jobs into zones of high or low oxygen, also known as "zonation." For bioengineered tissue to reach the clinic in the future, it is essential that it demonstrates zonation and resembles what is observed in vivo. The present study aimed to test a bioengineered liver model that was designed by the Stevens lab group. Immunofluorescent staining was used to examine the expression of zonated proteins in engineered tissue and compare to the expression in native liver. We tested markers that are restricted to regions of low oxygen (glutamine synthetase), intermediate levels of oxygen (CYP2E1), or found at highly oxygenated areas (HAL). It was also hypothesized that fluctuations in oxygen availability would result in differing levels of mitochondria and generate reactive oxygen species (ROS), so these were assessed by immunohistochemistry. Results confirm zonation in bioengineered liver tissue, assuring it is a more-physiologically accurate model for tissue engineering. Future studies will explore the mechanism of liver zonation in vitro, using organoids to test known murine drivers of zonation such as Wnt proteins and oxygen gradients.

T cell activation is an essential element of the adaptive immune response. When the T-cell antigen receptor (TCR) interacts with a peptide antigen bound to a major histocompatibility complex (MHC), lymphocyte-specific protein tyrosine kinase (Lck) phosphorylates the CD3ζ chains of the receptor complex, initiating an intracellular signaling cascade. Therefore, Lck plays a crucial role in TCR signal transduction and thus Lck’s kinase activity and scaffolding function are tightly regulated by intramolecular protein-protein interactions (PPIs). Regulation is conferred by phosphorylation of two tyrosine residues on Lck, leading to conformational changes. When the C-terminal tail tyrosine is phosphorylated, the alignment of catalytically necessary residues is perturbed, rendering an inactive closed conformation. However, when the C-terminal tail is dephosphorylated, and the activation loop tyrosine is phosphorylated, Lck adopts a catalytically active open conformation. Using its regulatory domains, Lck also functions as a scaffold. First, Lck uses its tyrosine kinase domain to phosphorylate the kinase ZAP-70. Then, Lck bridges ZAP-70 to LAT by binding both proteins using its regulatory SH2 and SH3 domains. To study the intramolecular regulation of Lck’s kinase activity, we performed a Deep Mutational Scan (DMS) in yeast to measure the activity of ~5,000 single amino acid variants of Lck. Because Lck’s kinase activity is toxic to yeast, we can infer information about Lck’s kinase activity from changes in abundance of yeast expressing individual Lck variants, relative to wild type, over time. Specifically, we analyze the mutations along the SH2-SH3/kinase domain PPI which we hypothesize perturb the accessibility of Lck’s SH2/SH3 domains. In Lck variant expressing T cells, we expect to see differences in Lck’s binding partners due to differences in Lck’s SH2 and SH3 domain accessibility. This research will help us better understand Lck’s role in T-cell activation, with the long-term vision of leveraging Lck variants in next-generation T-cell therapies.

The older population (≥65 years old), projected to double by 2030, is the fastest growing age group and represents 20% of the US population. Normal aging of the brain results in a nearly 30% reduction of microvasculature in the cerebral cortex with significant drops in capillary density, vascular responses to metabolic demand, and reduced angiogenic capabilities signifying the “sensitive” nature of the aging brain to ischemic injuries. The aged spinal cord is also vulnerable to injuries; in recent years, spinal cord injuries (SCI) from ground falls are among the most common trauma suffered by older patients. Unfortunately, we know almost nothing about how spinal cord microvasculature, hemodynamics, and inflammation changes with age. The present study aims to address this knowledge gap. Our group has recently developed a novel intravital ultrafast contrast enhanced ultrasound (CEUS) imaging to visualize blood flow within the microvasculature with unparalleled temporal (30,000 frames per second) and spatial (down to 50 micron) resolution. Unlike other imaging modalities limited to only a few hundred microns deep from the surface of the tissue (e.g., laser speckle and two photon imaging), ultrafast CEUS imaging allows us to examine intraparenchymal microvascular structure and blood flow hemodynamics within the entire depth of the spinal cord tissue in real-time. We applied this innovative technique to study intraspinal microvasculature anatomy and function during normal aging, and age-related microvascular vulnerabilities after traumatic SCI (tSCI). We also examined differences in inflammatory markers from aging using basic histological and microscopy techniques. Because previous studies have detected microvascular density differences between male and female rodent and human models, we have also measured microvascular changes during normal aging in both sexes. Results from this study will ultimately be foundational to understanding sex and age-related alterations in both the static and dynamic microvascular function of the spinal cord.

The genetic makeup of beer-brewing yeast plays an essential role in determining the flavor profile during production of beer. With functional copies of genes on the MAL locus, beer yeasts, namely Saccharomyces cerevisiae, can utilize maltose and maltotriose as their carbon source. The three genes in this locus are responsible for the regulation (MALx3), transport across membrane (MALx1), and breakdown of sugars (MALx2) in brewers’ wort. If a strain lacks a functional copy of any of these three genes, it cannot digest these alternative sugars. Alternatively, some strains have more than one MAL locus, but which loci are functional, remains unknown. Apart from previous studies that have investigated a handful of MAL alleles, the function of the genes in these duplicated loci (or paralogs) cannot be determined based on sequences alone. To address this problem, I experimentally tested the function of alleles from 1,011 natural isolates. I focused on MALx3 because the reference strain lacks a functional MALx3 allele, preventing its growth in maltose. Therefore, introduction of any functional MALx3 alleles should permit growth in maltose. To test this, I cloned ~250 MALx3 alleles from three different loci (MAL1, MAL3, MAL7) and transformed the reference strain to generate three yeast libraries. The library with the MALx3 gene of the MAL3 locus, or MAL33, successfully grew to saturation after ~2.5 days of incubation in 2% maltose, showing this approach can be used to determine the function of MAL33 alleles. Looking forward, I will use DNA barcodes to track the growth of alleles in maltose to pinpoint which are functional. With the MAL loci serving as a great candidate for understanding paralog differences, by identifying the functional paralogs, we can better understand the evolutionary history of MAL genes and what role these loci play in the brewery and across all natural isolates.

Post-acute sequelae of COVID-19 (PASC) represent an emerging global crisis. However, quantifiable risk-factors for PASC and their biological associations are poorly resolved. We executed a deep multi-omic, longitudinal investigation of 309 COVID-19 patients from initial diagnosis to convalescence (2-3 months later), integrated with clinical data, and patient-reported symptoms. We resolved four PASC-anticipating risk factors at the time of initial COVID-19 diagnosis: type 2 diabetes, SARS-CoV-2 RNAemia, Epstein-Barr virus viremia, and specific autoantibodies. In patients with gastrointestinal PASC, SARS-CoV-2-specific and CMV-specific CD8+ T cells exhibited unique dynamics during recovery from COVID-19. Analysis of symptom-associated immunological signatures revealed coordinated immunity polarization into four endotypes exhibiting divergent acute severity and PASC. We found that immunological associations between PASC factors diminish over time leading to distinct convalescent immune states. Detectability of most PASC factors at COVID-19 diagnosis emphasizes the importance of early disease measurements for understanding emergent chronic conditions and suggests PASC treatment strategies.

The glymphatic system is the waste clearance system in the central nervous system, and it is most active during sleep. This system clears toxic solutes from the brain and include amyloid beta peptides, tau aggregates amongst others. Accumulation of these proteins is the hallmark of many degenerative diseases, including Alzheimer's disease (AD). Therefore, there is high interest in studying the glymphatic system and its role in the pathogenesis of AD. Typically, intrathecal contrast injections are used to study glymphatic flow. However, it is impractical to use this method for studies since they are invasive and need multiple MRIs over almost 24 hours. In this study, the effectiveness of intra-voxel incoherent motion (IVIM) is explored, which is a non-invasive diffusion MRI method that only takes minutes to complete. This procedure measures the velocity and distance of molecules at slow motion over long distances (D*) and fast motion over short distances (D). We hypothesize that glymphatic flow is associated with D*. The glymphatic clearance mechanism is sleep active and even acute sleep restriction or deprivation is known to cause transient impairments in its flow. To determine whether D* is sensitive to glymphatic flow, we compare measurements in subjects with a full night of sleep and in those with sleep deprivation. We expect that D* will be reduced after a night of sleep deprivation compared to that after a full night’s sleep.

This research project involves analyzing planetesimal accretion through the use of an N-body simulation. A terrestrial planet passes through many stages of growth including: dust grains, pebbles, planetesimals, embryos, to planets. This study focuses on the formation process between planetesimals and embryos. Current simulations demonstrating terrestrial formation use parameters similar to those of our own solar system. This investigation attempts to envision this process at a more “bunched” up scale, such as in the case of the Trappist-1 system. Our inner solar system, a radial distance from the Sun to Mars, is about 25 times larger than the entire Trappist-1 system, meaning that its planets were formed much closer to its star. Through the use of N-body simulations, we can begin to understand the unknown formation of this system as well as others with similar characteristics. These N-body simulations are processed through the University of Washington’s supercomputer Hyak, approximating the motion of the particles that represent the planetesimals and detect if any are in a collision course. Two short period simulations were run using a number of sophisticated collision models that differ in how the particles interact and formation efficiency. The previous collision model used parameters calculated in 2005. The second newer model uses parameters from 2021, which I have programmed into the model's initial condition files. The study’s purpose is to compare the outputs of the collision models through a variety of quantitative and qualitative factors, concentrating on particle growth and runaway growth. More specifically, the data is measured through plots that depict the semi major axis vs. eccentricity, max mass over mean mass as a function of time, and the ratio of collisions that result in a merger. This will later lead to the investigation of which models can accurately replicate terrestrial formations such as the Trappist-1 system.

Implications of social media on social relationships, especially those of younger people, has been widely studied in recent years as adoption of various apps grew rapidly during the late 2010s. Within this research has been a focus on the use of social media to maintain relationships. Snapchat is one of the most popular social media platforms used among Gen-Z individuals. This study investigates how college students used Snapchat during early 2021 in the COVID-19 pandemic to keep up with their friends when more typical forms of engagement were suspended. The study targeted concepts such as relational maintenance, relational closeness, relational well-being, and comparison to face-to-face communication. The study started with four virtual focus groups where I gained firsthand accounts of Snapchat use by UW students. My advisor and I then created a survey based on responses from these focus groups and administered it online to people recruited from 17 college-centric subreddits from across the United States. Results indicated a dichotomy between members of Gen-Z in their Snapchat use, where a certain portion found Snapchat to be related to positive developments within their friend group while the other portion saw the app providing an inadequate amount of closeness and maintenance. These findings suggest that Gen-Z should not be generalized as one homogenous group, but, rather, recognized as two subsets of a generation who have differing views and preferences when it comes to the influence of their virtual communication habits on their friendships. When looking at the present state of the COVID-19 pandemic, this study would be worth conducting again to identify differences now that in-person meetings have become more common.

Aerial surveys are a tool commonly used to estimate population abundance for many species, yet little is known about how aircraft presence impacts animal behavior. The National Oceanic and Atmospheric Administration (NOAA) periodically conducts surveys in the U. S. waters of Alaska to monitor Arctic seal populations. These surveys are important as trends show reductions in the sea ice that these pinniped species depend on. Quantification of ringed seal (Pusa hispida) and bearded seal (Erignathus barbatus) rates of flushing from the sea ice into the water in response to aircraft overflights is necessary to strengthen population estimates and implement sound policy measures for activities in Alaska that may impact these pinnipeds. In the spring of 2021, NOAA conducted aerial surveys over the sea-ice of the Beaufort Sea. As an intern I separated the video into trials that captured seals before, during, and after the plane passed overhead. For each individual seal I then recorded species, weather, group size, distance from the plane, and seal behavior changes and geographic locations and analyzed which factors influence seal flushing behavior. In 161 trials, we recorded 266 ringed seals and 21 bearded seals. Only one bearded seal flushed (4.8%) while 47.8% of all ringed seals flushed. Most ringed seals flushed before the plane passed overhead. Generalized linear models indicated that distance from flight path and group size exerted the greatest influence on flushing behavior while weather and plane altitude were less important. Less distance from the flight path and larger group sizes led to higher ringed seal flushing rates. Understanding ice seal behavior will improve population estimates in future surveys. Overall flushing rates are important indicators of the disturbance ringed and bearded seals experience as a result of commercial and scientific activity in the Arctic and may be useful for permitting processes.

Research in recent decades has highlighted the influence of descriptive and injunctive norms on young adult behavior in relation to alcohol and cannabis use. Simultaneous alcohol and cannabis use is when these two substances are used a way that their effects overlap. Rates of simultaneous alcohol and cannabis use are higher among young adults and use is associated with more negative outcomes compared to alcohol or cannabis alone. The relationship between norms and simultaneous use has been less examined, especially among higher-risk young adults (e.g., driving under the influence). Additionally, it is not fully understood why norms influence substance use behaviors for some individuals and not others. Past research has linked factors of impulsivity with higher rates of substance use, but how impulsivity may impact the relationship between norms and simultaneous use is not known. For this research I used data from a larger parent study that sampled high-risk young adults who reported both simultaneous alcohol and cannabis use and riding or driving under the influence in the past (6) months. I used moderated regression analyses to assess impulsivity as a moderator of descriptive and injunctive norms on substance use. I hypothesized that for young adults high in impulsivity the association between norms and substance use would be dampened. These findings may suggest interventions that utilize norms (e.g., normative feedback interventions) may be less effective for individuals who are higher on impulsivity factors and that other intervention approaches should be applied for these young adults.

Joubert syndrome (JS) is a neurodevelopmental disorder diagnosed by the appearance of a “molar tooth sign” on an axial brain magnetic resonance imaging (MRI). JS patients present with hypotonia (low muscle tone), abnormal eye movements, and ataxia (uncoordinated movements). Subsets of patients develop progressive medical complications. Autosomal recessive, X-linked and rare dominant causes of JS in >40 different genes can be identified by DNA sequencing in ~75% of families. Cryptic DNA variants and alternative inheritance mechanisms are thought to account for the other 25% of families. The goal of this project is to evaluate the role of non-canonical splice variants in the pathogenesis of JS. We identified candidate splice variants in MKS1 from whole genome and targeted sequencing data and prioritized using SpliceAI annotation. A synonymous variant in patient 1 and a 30 base pair intronic deletion in patient 2 were identified. For each variant, we designed two sets of primers to flank the affected splice junction. Next, we extracted RNA from patient fibroblasts. We converted RNA into complementary DNA (cDNA) and amplified using polymerase chain reaction (PCR). Using gel electrophoresis and Sanger sequencing, we compared PCR products from patients versus controls.  We identified differences in DNA band sizes between unaffected control and patient samples. Based on Sanger sequencing, we determined that exon 4 is skipped in patient 1, but we were unable to determine the specific aberrant splicing event in patient 2. We confirmed the pathogenicity of candidate splice variants, identifying the precise genetic cause. An accurate genetic diagnosis informs prognosis, avoids unnecessary work-up, and guides monitoring for associated complications. Defining all genetic causes of JS expands our knowledge of the genetic mechanisms underlying recessive Mendelian conditions, confirming a substantial role for non-canonical splice variants.

When trying to develop the combinatorics of the p-parts of a multiple Dirichlet series given a group of functional equations isomorphic to the Weyl group of a type A root system, one runs into two natural combinatorial defintions of these p-parts in terms of Gelfand-Tsetlin patterns. The fact that these two natural definitions are equivalent is proved in Brubaker, Bump, and Friedberg's Weyl Group Multiple Dirichlet Series: Type A Combinatorial Theory. Their proof is not bijective. Further developing the combinatorics of these generalizations of the Riemann zeta function and other Dirichlet series, and finding a bijective proof of the result of Brubaker-Bump-Friedberg, remains an active area of research. I worked with a large group of undergraduate mathematicians, mentored by Ben Brubaker himself as part of the online collaborative Polymath Jr. Program, and we introduced new combinatorial objects, namely a new kind of colored lattice model, with which we can explicitly conjecture the existence of such a weight-preserving bijection for result of Brubaker-Bump-Friedberg in the most general setting, with p-parts corresponding to certain metaplectic Whittaker functions.

Since late 2020, vaccination rates against SARS-CoV-2 have increased with 64% of the U.S. population fully vaccinated as of February 2022 [CDC, 2021]. Although vaccines are an effective method of protection, breakthrough cases have been occurring especially with variants of concern (VOC). Vaccination has remained protective against severe disease for multiple VOCs, including Delta and more recently Omicron. It is important to understand how different levels of vaccination, such as the number of doses received, impact symptom severity as additional VOCs continue to emerge. I utilized data collected from the Husky Coronavirus Testing research program, which provides testing to students, faculty, and staff at the University of Washington, to evaluate the relationship between severity of COVID-19 symptoms and number of doses received and type of vaccine received. Self-reported symptom severity data was collected from individuals who completed a follow-up questionnaire 7 days after testing positive for COVID-19. This analysis can help us to learn more about vaccination status and its impact on illness severity in those infected with the omicron variant. From this research I anticipate vaccinated individuals to report mild COVID-19 symptoms and those who are unvaccinated, or only slightly vaccinated to report more moderate or severe symptoms. 

Adolescents with type 1 diabetes (T1D) are at risk for poor physical and psychosocial outcomes. Diabetes-related family conflict has previously been associated with youths' glycemic control (HbA1c). However, less is known about how family conflict associates with other health outcomes. This project aimed to explore correlations between adolescent and parent reported family conflict with diabetes-distress, depressive symptoms, resilience, and health-related quality of life (HRQOL) for both adolescent and parent. Eligible patients were enrolled in a two-site randomized controlled psychosocial intervention study. Participants were ages 13-18 with T1D for over a year and elevated levels of diabetes distress. At baseline, patients and their parent completed measures of: diabetes-specific family conflict (DFCS), HRQOL (T1DAL), diabetes distress (PAID-T), depressive symptoms (PHQ-8), and resilience (CD-RISC). HbA1c was pulled from participants medical charts. Descriptive statistics were used to summarize demographic variables, and bivariate correlation analyses were used to investigate the association between DFCS and the other psychosocial variables. Adolescents (N= 131; 53.4% female, 6.1% identified as another gender, 78.6% White, 9.9% Black, 2.3% Asian, 3.1% American Indian/Alaskan Native, and 80.9% Non-Hispanic, average age 15.38  1.5) DFCS scores correlated with more diabetes-distress (r=0.386, p<0.001), depressive symptoms (r=0.334, p<0.001), and less HQOL (r= -0.303, p<0.001). Parents’ (N=131; 79.4% White, 9.2% Latino/Mexican 6.1% Black, 2.3% Asian, 0.8% other, 79.4% private insurance) DFCS scores correlated with higher youth A1C (r=0.280, p<0.001), higher parent diabetes distress (r= 0.479, p <0.001), and lower parent resilience (r= - 0.200, p = 0.022) and HQOL (r = -0.369, p < 0.001). Both parent and patient reports appear to be an important area of further investigation for determining correlates of poor physical and psychosocial wellbeing in this high-risk group. While further investigation is needed, screening for family conflict may be important in clinical procedure, as it may become a future target for intervention.

Astrocytes, in addition to neurons, are vital cells in the brain that contribute to maintaining function. Like neurons, astrocytes can also accrue abnormal deposits of proteins with aging and neurodegenerative disease. However, how these abnormal proteins in astrocytes contribute to cognitive decline has not been well-studied as opposed to neurons. Phosphorylated tau is one protein that can accumulate in astrocytes and is often referred to as tau astrogliopathy. Tau astrogliopathy frequently accompanies the pathology of chronic traumatic encephalopathy- a neurodegenerative pathology associated with repetitive head injury. Given this information, we hypothesized that tau astrogliopathy would also occur at a higher incidence and with increased levels of pathology in those with a history of a single traumatic brain injury (TBI), especially those associated with loss of consciousness (LOC). We evaluated and quantified tau astrogliopathy in brain sections from donors with TBI and LOC compared to age-, sex-, and cognitive-status matched controls, from the University of Washington neuropathology research core. Specifically, the density of thorny shaped astrocytes (TSA) and granular fuzzy astrocytes (GFA) in different tissue locations (white matter, grey matter, etc.) throughout different cortical and subcortical regions was quantified. Preliminary data showed a higher density of tau astrogliopathy in cortical sections but not subcortical regions in the TBI with LOC cohort compared to the control group. This supports our hypothesis that there is an association between TBI and tau astrogliopathy; further research is needed to understand the clinical implications of this finding.

Photosynthesis and organic matter production by photoautotrophs in the upper ocean are fueled by sunlight. In previous research, environmental metabolite concentrations in the sunlit ocean have been found to display significant 24-hour periodicity. Prochlorococcus is a marine cyanobacteria that is the smallest and most abundant photosynthetic organism on Earth and is a key primary producer in the ocean’s vast oligotrophic gyres. Past studies employing transcriptomics and flow cytometry-based approaches revealed that cell division, metabolism, and gene expression of Prochlorococcus are synchronized with the daily light-dark cycle, but the impacts of these diel changes on the Prochlorococcus metabolome remain poorly understood. Here we investigate how levels of particulate metabolites in Prochlorococcus vary over simulated light-dark cycles in a non-axenic culture. We grew Prochlorococcus MED4 and its associated consortium of heterotrophic bacteria over daily light-dark cycles in culture and sampled for particulate and dissolved metabolites every 6 hours for a total of 48 hours. We extracted metabolites using a modified Bligh and Dyer extraction and quantified metabolites using liquid chromatography paired with mass spectrometry. To detect diel patterns in metabolite concentrations, we used Rhythmicity Analysis Incorporating Nonparametric methods to identify significant changes in Prochlorococcus’ metabolome over the light-dark cycle. Sucrose, a disaccharide sugar, varied over the diel cycle and peaked at the end of the light cycle, highlighting the use of this compound for energy storage in Prochlorococcus. Glutamine, a metabolite associated with nitrogen assimilation, displayed diel variation and peaked at midnight, lagging the peak in sucrose by 6 hours. These results indicate diel partitioning of Prochlorococcus’ metabolic functions related to energy storage and nitrogen assimilation. This diel partitioning mirrors prior results observed in environmental metabolomes and transcriptomes.

Individuals experiencing homelessness and housing instability in King County have inadequate access to water, sanitation, and hygiene (WASH) services. This urgent matter of community health has only been exacerbated by the coronavirus disease (COVID-19) pandemic in recent years and can necessitate open defecation or unsafe disposal of wastewater. Particularly among those residing in recreational vehicles (RVs) and use their bathroom facilities, unsafe sanitation practices increase the risks of intestinal pathogen transmission and infection in densely populated communities. In a continuation of efforts to address this, I have developed a study that aims to identify an optimal method of RV wastewater concentration for downstream detection of pathogens. With informed consent from RV residents and sampling assistance from Seattle Public Utilities, I have began collecting a representative collection of samples of RV wastewater from multiple neighborhoods across Seattle. I have utilized a split-and-seed approach in which half the samples were seeded with known amounts of target bacterial, viral, and spore-forming organisms, and the other half left unseeded as a control. These samples will be used to compare two methods of sample concentration, skimmed milk flocculation and membrane filtration, using a weighted rubric that evaluates biosafety, seeded organism recovery efficiency, personnel time, and cost. Upon observation in the lab, I have found that skimmed milk flocculation led to inhibition during detection via molecular assays. Additionally, high turbidity of the samples yielded significant logistical challenges with processing skimmed milk samples, leading my team and I to instead favor the membrane filtration technique. As we move forward, I anticipate detecting elevated levels of pathogens in wastewater from RVs when compared to samples from control locations chosen to represent populations living in sewered and unsewered environments representing populations. Upon development of the optimized protocol, my work will be prepared for publication in a peer-reviewed journal and shared with the City of Seattle.

Hands-on experience in any field is crucial in establishing an understanding of a concept within that field. For undergraduates learning quantum mechanics, this form of experience may be difficult to come by. This study is meant to bridge that difficulty, as I have designed an accessible lab that can be performed by students at an undergraduate level. For this I used the quED, a device created by quTools with the capability to run many quantum experiments, to build these procedures. The particular lab that I focused on was single-photon quantum state tomography, a process that uses repeated measurements to compute the quantum state of a photon. This experiment functions as a solid base for understanding the fundamentals of quantum-enabled technologies, and effects of optical elements on light. By performing the experiment iteratively, I was able to figure out what method would best suit students learning about these concepts. From this, I constructed a procedure that can be easily followed to complete the lab, while allowing the student to still put in the work necessary to learn essential concepts. The outcome of this project will determine how I put together future procedures for other experiments the quED is capable of. Wherefore, sets of instructions for successive labs can be seamlessly integrated into the quantum curriculum further down the line.

Fewer than 20% of adolescents and young adults (AYA) with diabetes achieve optimal glycemic control. The use of diabetes technology, including insulin pumps and continuous glucose monitors (CGM), are associated with improved outcomes; however, there are inequities in technology use. The University of Washington (UW) AYA Diabetes Program aims to address disparities in AYA with diabetes by providing tailored education and access to multidisciplinary specialists, including a social worker and psychologist. We examined the impact of the UW AYA Diabetes Program on change in diabetes technology use among AYA and assess whether this varied by sex, race/ethnicity, and health insurance. The study included participants seen in the UW AYA Diabetes Program between 2017-2021. For each binary outcome of insulin pump use and CGM use, we calculated proportions and 95% CIs (confidence intervals) using generalized linear models. We assessed for possible effect modification by sex, race/ethnicity, and health insurance. In this cohort of 453 patients (51% male, 87% non-Hispanic White, 27% public insurance, 55% CGM and pump use) there was evidence of effect modification by health insurance type for both pump and CGM use (p=0.01 and 0.03 respectively) but not by sex or race/ethnicity. Baseline CGM use was significantly lower among public vs private insurance participants (38%, 95% CI: 29-46%; vs 61%, 95% CI: 56-66%) but not after 6-months of program participation (58%, 95% CI: 45-72% vs. 74%, 95% CI: 68-80%). Pump use was also lower at baseline among publicly-insured AYA (29%, 95% CI: 20-37%; vs. 67%, 95% CI: 62-72% for privately-insured). However, by 12-months, pump use for publicly-insured AYA had increased and was no longer statistically significant (44%, 95% CI: 30-59% vs. 64%, 95% CI: 56-72% for privately-insured). We found that the UW AYA Diabetes Program proved to be successful in mitigating baseline disparities and increasing diabetes technology use in AYA with diabetes.

Melusin, a chaperone protein expressed in cardiac tissue, is known to induce a protective hypertrophic response in response to chronic mechanical stress. This protective hypertrophic response prevents the progression of cardiomyopathy into heart failure. In previous work done in wild-type (WT) and melusin knockout (melKO) mice, the absence of melusin was correlated with a hypertrophic response indicative of heart failure. I plan to further investigate the biomechanical role of melusin in humans using human engineered heart tissues (EHTs) created from human induced pluripotent stem cell-derived cardiomyocytes (hiPSC-CMs) that lack melusin and their isogenic controls. EHTs are more representative of the human heart, making them an ideal model for studying the role of melusin in humans. I hypothesize that WT EHTs subjected to different mechanical stress conditions, i.e., high afterload, will outperform the melKO EHTs. In order to measure this, I increased the stiffness of the EHT posts and measured contractile force. I have been successful in differentiating high purity WT cardiomyocytes from iPSCs, essential for creating healthy EHTs. I also differentiated the melKO iPSCs and cast both WT and melKO tissues. The EHTs were planted on a bed of silicone EHT posts that can then be stiffened to induce mechanical stress on the cells. I compared the contractile force between the WT and melKO tissues. Improving our understanding of the role of melusin in humans can lead to further research into therapies and treatments for heart failure.

Following a heart attack, clinically known as a myocardial infarction (MI), the heart undergoes changes that replace healthy heart muscle with rigid scar. Fibrotic scarring can lead to long term heart dysfunction, arrhythmias, and potentially heart failure. Currently, there are no anti-fibrotic therapies available to patients that can help to stop, slow, or reverse the heart's fibrotic response to injury. It is thought that the transition of fibroblasts to activated matrix secreting myofibroblasts underlie the hearts fibrotic response, and harnessing these transitions holds therapeutic promise. Although the mechanisms behind these transitions remain poorly understood, recent genetic mouse models removing the mitogen-activated protein kinase p38α in resident cardiac fibroblasts have shown that fibroblasts void of p38α fail to form activated myofibroblasts in response to MI. This resulted in over a 50% scar area reduction after MI, but these mice were prone to cardiac rupture since they failed to form an early protective scar crucial to maintaining the heart’s structural stability. Thus, when considering the therapeutic window for anti-fibrotic therapies, timing is essential. This led us to investigate the ideal therapeutic window for small molecule p38 inhibition to reduce scarring and preserve cardiac function in a mouse model of MI. A p38 inhibitor was administered to mice either immediately following MI, to reduce the formation of myofibroblasts, or 3 days following MI to try to initiate myofibroblast deactivation to reduce overall scarring but also give time for initial protective scar to form. Following 10 days post MI, mice receiving a p38 inhibitor showed preserved cardiac function and reduced pathological remodeling. Yet, fibrosis was only significantly reduced in mice receiving the inhibitor 3 days following MI. This data suggests that targeting myofibroblast deactivation holds therapeutic promise in reducing pathological fibrotic remodeling, although further studies are needed to fully validate these findings.

Towards Universal Newborn and Early Childhood Hearing Screening in Kenya (TUNE) is a project designed to introduce low-cost phone applications, akin to a standard tool, to screen for middle ear fluid in children. The device, which can be used by non-specialists, has the potential to provide low- and middle-income countries the opportunity to address problems in ear and hearing health that could otherwise impair childhood development. Kenya does not have a universal newborn and early childhood audiology screening program due to a lack of trained screeners and the high cost of assessment tools. The TUNE team met twice weekly via Zoom since colleagues lived in both Seattle and Nairobi, Kenya. My early responsibilities included documentation of stakeholder input. In September 2021, we sponsored a healthcare worker training program in Nairobi. In support of this work, I generated the training videos, created a website, and developed slide decks. These tools were used to provided healthcare workers with a background on hearing health and the importance of early identification of hearing loss, general information about the phone application, and trained them to use the device with a detailed instructional video. Healthcare workers were then given time to practice using the application. Finally, they were asked to complete a survey about the application. Most respondents reacted positively to the tool, with 100% of participants reporting they “would be comfortable using the device ‘as is’ in their work.” Most indicated that they would recommend using the application but noted that there were updates that could make the application more user friendly. We used the resulting qualitative data to inform future iterations of the application, a stakeholder workshop and policy recommendations. Ultimately this technology may help ensure that children’s growth, development, and educational needs are met in low- and middle-income countries.

Carbapenem-resistant Enterobacteriaceae (CRE), usually belonging to the bacterial species E. coli or Klebsiella pneumoniae, are resistant to carbapenem antibiotics, which are often used as a last resort in treating infections. CRE is a growing public health concern as it spreads rapidly within certain settings like hospitals. Currently, limited research assessing the presence of CRE within environmental samples is available. Without this research, the abundance of CRE and therefore its threat to public health remains unclear, making mitigation strategies challenging. This study seeks to identify if CRE resides in the protected wetlands at the University of Washington Bothell campus. Because crows, specifically Corvus brachyrhynchos, provide an impeccable habitat for Enterobacter species, and because of the large crow population in this area, we want to find out if crows are bringing in any CRE strains to the wetland. To answer this question, samples of both wetland water and crow feces have been collected from strategic locations, and using selective plating potential CRE strains have been isolated. The isolated Enterobacter species have undergone a modified Hodge test with both meropenem and ertapenem. Isolates suspected to have resistance to either antibiotic are undergoing PCR with primers specific to the genes bla_KPC, bla_NDM, and bla_OXA, genes which are common culprits of carbapenem resistance. We plan to perform multidrug resistance testing to determine if our isolated strains are resistant to other antibiotics. After conclusion of this project, we will be able to say if crows could be responsible for bringing these antibiotic-resistant bacteria of clinical importance to the Bothell Wetlands, and what health risks they pose to the community.

Among the promising candidates for physical realizations of quantum registers, the negatively-charged nitrogen-vacancy (NV) center in diamond – consisting of a substitutional nitrogen atom and an adjacent vacancy defect – stands out due to its optical stability and its long (even at room temperature) coherence time. However, since the quantum states of the system are read by measuring the photons emitted from the NV centers, one problem introduced by the high refractive index of diamond is that these emitted photons may experience total internal reflection back into the diamond or refraction out of the detection area, thus leading to extremely low efficiency of collecting them. To solve this problem, hemispherical-like structures called solid-immersion-lenses (SILs) are sculptured, by focused-ion-beam (FIB), on the surface of diamond around the NV centers. SIL allows the emitted photons to form desirable incident angles with the diamond surface, so that the collection efficiency is optimized. During the FIB-fabrication of SILs, because NV centers are not visible when using FIB-imaging, markers that are both visible under FIB-imaging and confocal photoluminescence microscopy are needed. This project aims to identify a promising diamond sample, etch suitable markers on the sample surface with electron-beam lithography, and register the coordinates of the targeted NV center(s) with respect to the markers under confocal microscopy. The preliminary result will enable the sample to be fabricated with SIL(s) around the registered NV center(s), after which the sample will be further engineered to run quantum protocols.

As the fields of quantum cryptography and quantum computing grow there is a greater need for training electrical engineers who are interested in these subjects. At the University of Washington, there has been a push in the Electrical & Computer Engineering department to increase the accessibility of these fields. The goal of my work is to generate procedures that can be followed by undergraduate-level engineering students to teach them foundational quantum mechanical processes. As a part of this effort, a new hardware lab has been created, the Quantum Technologies Teaching and Testbed (QT3) Lab. The QT3 lab includes a quED kit that produces polarization-entangled photon pairs and requires minimal laboratory experience to operate. By using the motor and hand controls included in the kit students will be able to follow straightforward step-by-step processes to see the violation of Bell’s inequality. Bell’s Theorem is the idea that parts of quantum theory require non-local effects meaning the correlation between two measurements cannot be accounted for with a signal traveling at the speed of light. One way this has been demonstrated is through the CHSH inequality where two entangled photons are sent through polarizers set to several different angles and then through two detectors. The counts of the number of “coincidences” or simultaneous detections are recorded and then they can be used to calculate a statistic that describes the correlation between the photons. If they are entangled they will show a value that violates the correlation possible within local realism. In my research, I created a setup to replicate the CHSH experiment and verify the result. I then designed an educational lab around this process to allow students to learn from it. This will give students an introduction to many of the fundamental concepts required to understand how quantum computing functions.

Given the upper-trophic nature of marine mammals, their population numbers can be indicators of marine ecosystem health. For pinnipeds - including seals, sea lions, and fur seals in Washington State - one method of population assessment is documentation of stranded individuals, or dead animals that wash up on beaches. Due to the lack of a comprehensive stranding program along the Washington coastline, with some carcasses being reported to official stranding networks while others are noted on citizen science websites, I explored whether the citizen science photo-platform iNaturalist could be used to augment the Marine Mammal Stranding Network (MMSN) stranding database managed by the National Oceanic and Atmospheric Administration (NOAA). I searched for pinniped photographs on iNaturalist between the years 2015 through 2020, limited to Washington waters. After removing duplicates, I cross-referenced iNaturalist data with MMSN strandings. After compilation of the high-quality data, I calculated the ratio of unreported to reported strandings over the entire dataset, as well as annually, by species, and as a function of carcass freshness. I found there were unreported strandings throughout Washington waters, with a ~1:3 ratio of unreported-to-reported strandings overall (27% of the total). My findings suggest that some species were much more common than others, with an order of magnitude difference between the most common species (harbor seals) and rarest (fur seals). However, species-specific unreported-to-reported ratios were not dissimilar (22-30%). Unreported carcasses also crossed all freshness categories ("fresh" through "skeletal"). These analyses prove that stranding cases often go unreported to stranding networks, and suggest no biases in space, species, or carcass condition in citizen science data. Based on these conclusions, I recommend that citizen science stranding data be incorporated into national stranding databases to allow for the largest dataset possible from which to analyze and manage marine mammals and marine ecosystem health.

Neuroligins (NLGNs) are a family of postsynaptic cell adhesion proteins that are essential to the formation and proper functioning of synapses and play a critical role in maintaining neural excitation/ inhibition balance. Neuroligin mutations are linked to several neuropsychiatric disorders like autism, although their role in maladaptive social behavior remains unclear. Inappropriate aggression and agitation are often comorbid with neuropsychiatric disease and understanding the neural pathways underlying aggressive behavior may help to identify potential therapeutic targets. Neuroligin-2 (NLGN-2) specifically supports inhibitory synapse function and plays a key role in regulating social stress behaviors. Here, we examine the role of NLGN-2 in mediating adaptive and maladaptive aggressive behavior in adult male outbred CD-1 mice. In Experiment 1, we use immunohistochemistry to localize and quantify NLGN-2 in Fos-positive cells in nucleus accumbens of mice following resident-intruder reactive aggression. In Experiment 2, we train mice in an operant aggression self-administration procedure and examine changes in NLGN-2 in nucleus accumbens Fos-positive neurons following appetitive, or rewarding, aggression. In Experiment 3, we selectively knockdown NLGN-2 in nucleus accumbens in a neural circuit-specific manner to determine the functional effects of NLGN-2 manipulation on adaptive and maladaptive aggressive behavior. Together, these data demonstrate an important role for nucleus accumbens NLGN-2 in mediating the spectrum of aggressive behavior.

Lipid peroxidation has been found to be associated tightly with ferroptosis, a type of programmed cell death. Our lab recently reported that lipids with unconjugated and conjugated double bonds undergo lipid peroxidation via different mechanisms. Importantly, conjugated polyunsaturated fatty acids (PUFAs) were found to be more reactive to lipid peroxidation than their non-conjugated isomers. Since ferroptosis is caused by lipid peroxidation, we hypothesize that the addition of different exogenous lipids will affect the induction of ferroptosis in cancer cells differently. We treated multiple cancer cell lines with a variety of saturated, monounsaturated, polyunsaturated FAs, and other biologically important lipids at varying concentrations to obtain the EC50 values, the concentrations of various lipids where 50% of cells are viable. We then treated the cell lines with ferroptosis inducers in the presence and absence of various lipids at their EC50 concentrations to observe changes in cell viability. We found that while some biologically important lipids protect the cells from ferroptosis, PUFAs enhance ferroptosis induction. Among PUFAs, the conjugated ones show higher potency compared to their nonconjugated counterparts. We then performed flow cytometry to compare lipid peroxidation accumulation between lipid treatments and found that conjugated PUFAs lead to higher lipid peroxidation levels. Additionally, according to the proposed lipid peroxidation mechanism of conjugated PUFAs, conjugated aldehydes could potentially form as secondary oxidation products. Aldehydes are highly electrophilic and react readily with nucleophiles in cells, including DNA and proteins. We performed cell viability assays with unsaturated, nonconjugated, and conjugated aldehydes and found that the conjugated ones are the most toxic to the cancer cells, suggesting that they contribute to the high potency of conjugated PUFAs in inducing ferroptosis. Identifying the effects of biologically important lipids and their oxidation products on the induction of ferroptosis in cancer cells can lead to the development of therapeutic candidates.

Breast cancer became the most common cancer globally as of 2021, accounting for 12% of all new annual cancer cases worldwide. An estimated 43,250 women in the U.S. are expected to die in 2022 from breast cancer. In vitro models for breast cancer exist such as using existing cancer cell lines or extracting tissue from patients. Recently, induced pluripotent stem cells (iPSC) have emerged as a new powerful tool to model cancer progression and provide information on the cancer cell-of-origin. They are amenable to genome editing and can be differentiated into various cell types. iPSC-derived cells and organoids have the potential to produce more relevant cancer models that could be used for drug screening and personalized medicine. One group has previously reported the generation of mammary gland organoids from human iPSC. However, this protocol seems to produce highly variable organoids, in terms of morphology and cell composition, and the molecular mechanisms of the individual hormones and growth factors driving the differentiation are unclear. We have characterized organoids differentiated from the protocol through western blots and immunofluorescence staining and found lumenized structures expressing relevant markers. We are assessing the presence of basal and luminal epithelium and aim to improve the generation of hiPSCs derived mammary gland-like organoids. Using published single cell RNA sequencing data in combination with previously published literature on mammary gland development, we are in the process of identifying regulatory mechanisms relevant to the differentiation process and recapitulating findings in vitro. This study has potential for disease modeling and drug screening for a greater ethnic and racial background.

Opiate overdose deaths in the US continue to increase at an alarming rate, yet we still only have a partial understanding of the neural mechanisms that regulate opiate addiction. The paraventricular thalamus (PVT) and nucleus accumbens (NAc) are regions of the brain that have both been implicated in addiction to drugs of abuse. Prior studies show that the somatic effects of opioid withdrawal are mediated by excitatory input from the PVT to the NAc. Recently, cannabinoid compounds such as tetrahydrocannabinol (THC), the principle psychoactive constituent of marijuana, has been shown to alleviate effects of opioid withdrawal. Our goal for this project was to determine how cannabinoids regulate the PVT-NAc circuit to modulate these opiate withdrawal symptoms. This study had two principal aims: 1. Understanding the physiological mechanisms by which cannabinoids can modulate PVT-NAc circuits, and 2. Using in-vivo photometry and optogenetics to determine whether we can treat the behavioral effects of opiate withdrawal by using cannabinoid compounds to inhibit the PVT-NAc circuit pathway (n=10 animals, age 12-24 weeks). We first demonstrated that a genetically defined population of anterior PVT (aPVT) neurons expressing the neuropeptide Neurotensin (NTS) sends excitatory projections to the NAc, which are regulated by cannabinoid signaling. Using in-vivo fiber photometry to record activity of aPVT to NAc projections, I showed that rewarding stimuli inhibits the circuit, whereas painful stimuli (such as heat from a hotplate) activate the circuit. Administration of morphine was sufficient to block the pain-induced activation of the aPVT-NAc circuit, and caused robust analgesia. Furthermore, following chronic morphine administration, I used naloxone to precipitate opiate withdrawal, and demonstrated that enhancing cannabinoid signaling was capable of reducing some of the symptoms of opiate withdrawal. Future studies will aim to understand the causal relationship between cannabinoid modulation of the aPVT-NAc circuit and the development of opiate withdrawal.

Chimeric antigen receptor (CAR) T-cell therapies have been shown to effectively control various types of cancer in patients. Recent studies have demonstrated that these therapies may be enhanced by the delivery of gain-of-function genetic payloads. In order to evaluate the significance of numerous genes at scale, researchers have turned to CRISPR activation (CRISPRa), a programmable gene over-expression system adaptable to forward genetics screens. However, cell products that include constitutively-expressed genes may present a risk for oncogenic transformation and cannot be modulated by clinicians in real-time. With the end goal of deploying controllable genetic payloads, screening pipelines using drug-sensitive CRISPRa may better steer and therefore approximate the behavior of genes as candidates in the final cell product. In this study, we adopted two highly sensitive, drug inducible CRISPRa switches and deployed them to T cells to exquisitely control targeted gene overexpression. In an immortalized cell line, various CRISPRa variants featuring the Estrogen Receptor Ligand Binding Domain (ER-LBD / ERT2) and Small Molecule-Assisted Shutoff (SMASh) systems were tested, and two designs were selected with high sensitivity and stringency upon the addition of tamoxifen (4-OH) or asunaprevir (ASV), respectively. These designs are currently being evaluated in CAR-CRISPRa CD8 T cells. This pair of newly-tested CRISPRa ON/OFF tools may complement and enhance genome-wide forward genetics screens where the expression of numerous genes can be tuned by one shared drug-inducible system. Such tools may help improve the design and performance of future CAR T-cell therapies, as the improved regulatability of transgenes has the potential to lead to improved patient safety or treatment outcomes.

While vaccines help prevent infection from SARS-CoV-2, therapeutic drugs remain necessary to treat people who are already infected. In my research, I am developing peptide-based therapeutics. These therapeutics are safe and readily bioavailable due to their low immunogenic response and low production cost. I design peptide inhibitors against the Mpro enzyme, the main protease present in SARS-CoV-2. Mpro normally cleaves the virus’ pp1a and pp1ab viral polyproteins, which are then activated and assist with viral replication and transcription. By creating a competitive inhibitor that binds to Mpro, I can prevent it from activating the pp1a and pp1ab proteins and thereby prevent viral proliferation. The project began with computational design of peptide inhibitors on the Rosetta Macromolecular Modeling suite, a computational platform that provides accurate structure prediction and design of peptides. An effective drug not only finds the active site of Mpro, but is able to bind more strongly to it than the natural substrate. Mpro’s active site is hydrophobic, so my mentor designed the stub, the part of the peptide that fits within the active site, to include three hydrophobic amino acids: alanine, valine, and leucine. From there, she followed Rosetta's Generalized Kinematic Closure Algorithm to develop various cyclic peptides. After filtering these peptides on Rosetta based on shape and chemical complementarity, she proceeded with 50 peptides. Afterwards, I chemically synthesized and purified some of these peptides with High-Performance Liquid Chromatography. I tested their effectiveness in mass spectrometry-based inhibition assays and determined that the gzm_1,2 peptide has an IC50 value (the concentration of peptide required to inhibit 50 percent of Mpro) of 12.68 µM. Through refining the structure of gzm_1,2, I can improve its inhibitory effectiveness and membrane permeability, enabling it to serve as the basis of an effective and affordable medication for people infected with SARS-CoV-2.

As part of the shared Quantum Technology Teaching and Testbed (QT3) Laboratory, a confocal microscope is being developed to study individual quantum emitters in various solid-state systems, such as nitrogen-vacancy centers in diamond and silicon-vacancy centers in silicon carbide. Laser power is a key control parameter in confocal measurements as the signal to noise ratio of photons collected from the quantum emitters depends on the intensity of the excitation laser. I am developing a laser power control system using a variable power attenuator and a power meter. The power attenuator is composed of a neutral density (ND) filter wheel attached to a stepper motor, which rotates the filter wheel until the desired power output is reached. The power meter uses a photodiode and a reverse-bias circuit to measure the incident light power as a voltage which is read by a computer through an Arduino. The power meter and power attenuator are combined in a feedback configuration where the stepper motor continuously turns the ND filter wheel until the power meter measures the desired power. With incident power 50 mW, I expect to vary the laser power between 5 μW and 45.5 mW by reducing the power by 5.9% every step of the stepper motor. This low-cost laser power control system will allow us to image single quantum emitters in a variety of materials and eventually perform quantum entanglement protocols with these emitters.

The construction contracting method, Design-Build (DB), has provided owner, architect, and contractor groups with a process of early design and rapid construction for the past three decades. Although there are many benefits to using DB, dissatisfaction has arisen due to limitations to innovation, limited owner involvement in the design, and long Request For Proposal (RFP) durations. Progressive Design-Build (PDB) has become an appealing alternative contracting method, providing owner benefits not seen with DB. This project investigates how PDB impacts a project and how those impacts compare to DB by assessing our proposed “Four Pillars of Project Success.” The four pillars are defined with respect to an owner’s responsibility and assessment of a project, including project predictability, project risk, project schedule, and project cost. We conducted literature review across several public projects, analyzed PDB project information collected by the Design-Build Institute of America (DBIA), and conducted stakeholder interviews with owners, contractors, and architects who have used both PDB and DB. In outcome, this project identified that PDB offers higher project predictability by giving owners control over the scope to be procured. PDB does not decrease project risks, but it identifies broader project risks so that each party can prepare a mitigation plan. The project schedule was positively impacted by finishing a project 1.4% faster than contracted. The project cost did not show much difference compared to DB, with a cost escalation of +3.28% as compared to +3.63% of DB cost escalation. This project offers insight into PDB’s structure and outcomes so an owner group can make an informed decision when considering PDB as their next construction contracting method.

Biological aging is the greatest risk factor for most major causes of mortality. Our lab operates under the hypothesis that slowing the rate of aging will also lower the risk of associated diseases. Unfortunately, biological aging research is often limited by the need for labor-intensive manual scoring of lifespan experiments. To solve this problem, we have created a pipeline using machine learning and robotics for the automated processing of lifespan experiments in Caenorhabditis elegans, a type of roundworm often used in biomedical research. Plates of C. elegans are first placed into a “WormBot” image capture robot, which takes images of the plates throughout the day. These photos are processed using YOLO, an object detection system that creates bounding boxes used to track general worm motion. I have implemented a semantic segmentation network that uses these bounding boxes to determine the general shape of the worm. This lets us gather morphological and behavioral data such as length, width, and position. This information is used to infer when the worm stops moving and can be called dead. The time of death this provides shows whether a treatment was successful in extending life. The morphological data can also be used to estimate whether or not the worm was healthier as it aged. This analysis lets us understand how effective various drugs, such as metformin, are at modulating the biological aging process and lessens the time required to run large numbers of trials. Our framework increases the rate at which experiments can be performed and also creates predictive models that provide suggestive data on the effectiveness of an intervention before the end of life. . By automating lifespan scoring, we accelerate the discovery rate of potential interventions that may eventually work in humans.

Asian Americans are underrepresented in public health research in the U.S. My research aims to explore the historical, social, and institutional factors that contribute to this, both in Seattle and the broader U.S. I will identify these factors through an extended literature review and demonstrate their role in constraining the scope of Asian public health research using a case-study on industrial pollution in Seattle’s Duwamish Waterway. The case-study will focus on Seattle’s Industrial District, Beacon Hill, and surrounding neighborhoods because of their proximity to the Duwamish Waterway and high exposure to industrial pollutants, such as benzene. This region also has a large Asian population. Genome-wide studies have shown that Asians are genetically predisposed to pancreatic dysfunction when chronically exposed to benzene and other volatile-organic-compounds. Pancreatic dysfunction can lead to diabetes mellitus, a health condition in which the body is unable to process glucose naturally. The spatial overlap of Asian residents and industrial pollution around the Duwamish Waterway is concerning and merits investigation. My methodology includes an extended literature review and a quantitative geospatial analysis of a Seattle case-study. The literature review explores systemic limitations of public health research on Asian Americans, examining factors like systemic racism and data collection issues through a critical Science and Technology Studies (STS) lens. The geospatial analysis will be used during the Duwamish Waterway case-study. I will use publicly available data to map and compare Asian population sizes, diabetes incidence, and industrial pollution in Seattle. The gaps in existing data for these factors will make it difficult to draw conclusive generalizations from the case-study, but paired with STS analysis, highlighting these gaps can contribute to improving public health research by demonstrating the limitations that currently hinder Asian public health research in Seattle and pointing the way to future research to fill in what is missing.

Quantum sensing platforms based on ensembles of nitrogen-vacancy (NV) centers in diamond enable high-sensitivity magnetic field detection at room temperature, making them uniquely suited for studying biological systems. Our work leverages the advantages of this diamond-NV sensing platform to directly measure the bend stiffness of individual DNA molecules using quantum-enabled magnetic imaging. In our experiment, a single DNA molecule is tethered to the surface of a diamond-NV sensor at one end and adhered to a ferromagnetic nanoparticle at the other end. A magnetic tweezer is used to apply a torque on the magnetic particle which bends the DNA strand in an effort to align the nanoparticle’s magnetic moment with the applied magnetic field. Quantum control and microscopy of the NV centers subsequently allows us to image the particle’s magnetic dipole field and the total applied field. Any deviation of the particle’s magnetic moment vector from the applied field vector can then be attributed to an opposing torque exerted by the DNA on the magnetic particle. Thus, measuring the difference between these vectors allows for the measurement of DNA bend stiffness. With this project, I detail the use of optically detected magnetic resonance and magnetic field image analysis to accurately measure the components of the aforementioned vectors. Additionally, I explore the limits of the diamond-NV platform in sensing the applied magnetic field in a highly symmetric configuration. Prior measurements have inferred the bend stiffness of DNA from statistical measurements such as cyclization. The novel direct measurement of DNA bend stiffness enabled by this project will help the scientific community understand sequence-dependent DNA flexibility, which plays a key role in biological processes such as eukaryotic nucleosomal compaction, viral genome packaging, and transcription regulation.
 

Kaposi’s sarcoma-associated herpesvirus (KSHV) is a γ-herpesvirus that is the etiological agent of Kaposi’s sarcoma (KS), a cancer of endothelial cell origin. Like other herpesviruses, KSHV has distinct latent and lytic replication cycles – during latency there is limited viral gene expression and no KSHV virions are produced, while in the lytic life cycle all viral genes are expressed and new virions are assembled. Both lytic and latent genes are implicated in KSHV’s oncogenic properties. During infection, endothelial cells from both blood and lymphatic vessels undergo changes in signaling pathways and morphology. However, differences in the expression of lytic and latent genes have been described for the different sources of endothelium. We have previously observed that blood endothelial cells (BECs) grown in culture are less susceptible to infection as compared to lymphatic endothelial cells (LECs). Other labs have reported higher levels of lytic gene expression in LECs. I aim to determine if there are differential levels of KSHV lytic gene expression in the BEC and LEC lines in our lab. To determine the levels of lytic replication in BECs and LECs, I isolated RNA at different time points post infection and use RT-qPCR to determine the relative levels of viral lytic genes. I tested different infection rates to determine the role of infection rates on levels of lytic replication. I am also testing different cellular growth conditions, including cell medias to determine if the levels of lytic replication depend on cell proliferation levels. The goal is to determine differences seen in the level of lytic replication in different endothelial cell types in different labs. Understanding the conditions for higher lytic replication of KSHV in endothelial cells could help understand KSHV tumorigenesis as lytic replication is a key factor in the way KSHV causes cancer.

As part of the shared Quantum Technology Teaching and Testbed (QT3) Laboratory, several microscopes are being developed to characterize quantum emitters in various material systems. We want to be able to control the amount of laser power used to excite these quantum emitters. One such microscope being developed is a wide-field microscope that combines optical and microwave excitation to coherently control the spin states of quantum emitters and read them out optically. It is important to be able to control the laser power because the amount of power used will affect the spin initialization and readout in these measurements. To implement laser power control, we use a feedback loop between a variable laser power attenuator and a power meter. The power meter uses a photodiode setup in a reverse-bias configuration. Upon absorbing incident light, the photodiode outputs a current that is proportional to the incident laser power. A load resistor converts that current to a voltage, which is read into a computer by an Arduino. This readout will provide feedback to the variable power attenuator to reach the desired power. The power meter is expected to measure laser power to within 9 μW and is designed to have the dynamic range needed to allow us to coherently control ensembles of quantum bits.

Ever since the COVID-19 outbreak, hate crimes and violence towards minoritized groups such as Black and Asian people have surged. Consequently, Black, Indigenous, and People of Color (BIPOC) continue to face several mental health challenges as well as inaccessibility to mental health care. The literature suggests that culturally responsive psychotherapy can improve BIPOC clients’ clinical outcomes. Thus, this study examines the actions community mental health (CMH) clinicians have taken to better serve BIPOC clients. Data came from a Washington State-funded cognitive-behavioral therapy training initiative (CBT+) in 2020 - 2021. CMH clinicians and supervisors attended a virtual CBT training followed by six months of expert consultation and completed pre-training and post-consultation surveys. In the surveys, CMH clinicians reported on the frequency of performing certain actions to better serve their BIPOC clients (e.g., discuss issues of race or racism with BIPOC clients) using a 5-point Likert Scale ranging from 0 (Never) to 5 (Always). We conducted descriptive statistics to summarize clinicians’ responses. Our analyses showed that clinicians most frequently incorporated the following actions when working with BIPOC clients: “consider the client's ethnicity” and “the use of bilingual staff or interpreters for those whose English is not their first language.” On the other hand, clinicians appeared to rarely collaborate with natural community healers, spiritual healers, clergy, etc., as part of their service delivery. Our findings suggest that CMH clinicians have taken several actions to thoughtfully consider and incorporate BIPOC clients’ backgrounds and context into treatment delivery. However, certain CMH clinicians' actions to better serve BIPOC clients occur more frequently than others. Future research should better understand which culturally responsive actions are most helpful in helping BIPOC clients’ experiences in CMH.

 Twelve million US citizens are currently suffering from visual impairment, many of them with late-stage blindness, which is accompanied by a drop in visual acuity, and the inability to recognize faces (CDC, 2022). Currently, few electronic sight restoration devices (SRDs) exist as treatment options for late-stage impairment that are precise in targeting retinal cells. Current SRDs cannot selectively stimulate on and off-center retinal cells – instead, all cells are stimulated regardless of their biologically natural firing pattern. Our research aims to examine whether neural plasticity can aid in overcoming this distortion in sighted individuals, using dichoptic presentation of stimuli that roughly mimics this simultaneous stimulation of on- and off- cells. Specifically, we convolved Fourier filters (F, and it’s contrast reverse complement F′) with images that are contrasted reversed complements of one another (I and I′) to induce a similar coding distortion caused by SRDs. We hypothesized that, through perceptual learning, sighted participants who received training with these distorted stimuli would be able to adapt to these distorted on-and-off cell responses. To test our hypotheses, participants were assigned to one of two groups. While both groups performed an object discrimination task with the distorted visual input, the experimental group did 25 hours of video game (VG) training, while the control group (CG) completed 5 hours of the object discrimination task. Participants in the VG group played a game that is an adaptation of Fruit Ninja, and tested in the discrimination task every 5 hours of video game play. Preliminary results indicate that individuals assigned to the VG group displayed superior performance in the object discrimination task, compared to the control group. Our results indicate that individuals with SRDs may have the potential to learn to decode unnatural visual cell population responses, which could improve their visual perceptions and enhance quality of life.

The SARS-CoV-2 Delta variant, first detected in India, has contributed significantly to the 78 million global COVID-19 cases throughout the course of the pandemic. As such, effective diagnostic tools remain crucial for controlling widespread infection. DNA aptamers are single-stranded, self-folding oligonucleotides that can bind to specific targets with high specificity and affinity. DNA aptamers are especially useful for diagnostic applications because they are stable, inexpensive, consistent between batches, and allow for additional chemical modifications for diagnostic applications. On the other hand, commonly-used alternatives such as antibodies are difficult to store and are produced through a labor-intensive cellular process that makes them susceptible to batch-to-batch variation. This project selected for DNA aptamers that bound to the S1 domain of the SARS-CoV-2 Delta variant spike protein using the iterative method SELEX (Systematic Evolution of Ligands by Exponential Enrichment). In each round of SELEX, a starting aptamer pool was first exposed to undesirable proteins in a process known as negative selection. Aptamers that bound strongly to these unwanted proteins were removed from the aptamer pool using magnetic Dynabeads. In an analogous process of positive selection, aptamers with high affinity for the Delta S1 spike protein were retained in the aptamer pool, while nonspecific aptamers were discarded. With each passing round of SELEX, the stringency of aptamer binding was increased such that only the highest affinity aptamers remained in the final SELEX rounds. These final rounds were then sequenced through Next-Generation Sequencing (NGS) and the aptamers that displayed the highest enrichment were characterized using a combination of ELISA (enzyme-linked immunosorbent assay) and biolayer interferometry. In the near future, effective aptamers discovered through this process will be applied in antigen testing applications through the use of tools like lateral flow assays.

Computing solutions to partial differential equations using the fast Fourier transform can lead to unwanted oscillatory behavior. Because of the periodic nature of the Fourier transform, waves that leave the interval on one side reappear on the other. However, the fast Fourier transform is a very efficient numerical tool, so it is important to find a way to damp these oscillations so that this transform can still be used. Our goal is to accurately model nonlinear partial differential equations on an infinite domain by considering a finite interval and implementing various damping techniques outside of the interval. We consider the Korteweg-de Vries equation with an initial condition that produces leftward traveling oscillations and a rightward traveling soliton. To damp the wrap-around oscillations, we have used the Strang-splitting method to solve the heat equation with a non-zero diffusion coefficient on the left side of the interval. To stop the soliton from wrapping around, we judiciously multiply the solution values by a decaying exponential on the right side of the interval. We have found that this damping process produces much more accurate solutions at larger times than the undamped solution when modeling solutions on an infinite interval. This method also applies to the nonlinear Schrodinger equation with some additional modifications.

The mesolimbic dopamine system mediates various behavioral functions, including motivation and reward association. Midbrain dopamine neurons of the ventral tegmental area (VTA) send projections to the nucleus accumbens (NAc), forming the mesolimbic pathway. It has been hypothesized that two subregions of the NAc, core and shell, are differentially involved in motivation and reward association. Previous studies identified distinct groups of dopamine neurons with synaptic projections to either the core or shell. The goal of this project is to establish the functional roles of core- and shell-projecting VTA neurons in motivated behavior. More specifically, we investigate whether either subpopulation is necessary or sufficient to reinstate an extinguished goal-directed behavior. The optogenetic approach allows for millisecond-precise gain or loss of function in distinct neural circuits. We use transgenic mice engineered to express Cre-recombinase in either core- or shell-projecting dopamine neurons. Cre-dependent targeting confers cell-type specificity while local intracranial injection of light-sensitive opsins via viral vector provides anatomical specificity. After surgical manipulations, mice undergo a conditioning task with separate acquisition, extinction, and reinstatement phases to measure the rate of food reward retrieval. Operant conditioning paradigms provide the ability to dissect how cues, contexts, and instrumental responses influence goal-directed behavior. During acquisition, mice are trained for six days of lever pressing for food reward paired with an audiovisual cue. In the extinction phase, no reward or cue is delivered. During reinstatement, lever pressing is followed by laser stimulation and cue presentation. We hypothesize that VTA-core-projecting and VTA-shell-projecting neurons differentially regulate cued reinstatement behavior. Our project will provide insight into the functional organization of the mesolimbic pathway and its role in motivated behavior. Collectively, these studies will establish the anatomical basis of dissociable aspects of motivation, extinction, and reinstatement of reward-seeking behaviors, which are implicated in substance abuse and obsessive-compulsive disorders.

Cement is a large contributor to carbon dioxide (CO₂) emissions, and there is ongoing research to reduce this impact. The negative impact of carbon dioxide emissions on our atmosphere is a growing concern, so finding avenues to reduce such pollution is constantly sought after. Namely, studies have been conducted to explore the inclusion of natural fibers into the cement matrix, both cellulose-based and pure cellulose. For this reason, sustainable cement composites with mechanical performance comparable to ordinary cement are of interest. Cellulose has been proven to enhance mechanical compressive properties under certain processing conditions. Additionally, concrete is limited in applications due to its inherently weak tensile/flexural properties; to combat this, fiber reinforcements (often steel) are incorporated. Here, we compare the effects of different types of cellulose fibers as fillers in cement, specifically the effects in density, viscosity, and compressive strength. We used cellulose microfibers as well as nanofibers, with substantially different degrees of crystallinity and aspect ratios. Overall, the mechanical performance of mixtures produced with varying amounts of cellulose micro- and nan-fibers as well as varying water content were studied. We correlated the changes in viscosity, micromorphology, and compressive strength to rationalize the effects. Utilizing readily available natural fibers in the cement matrix will enhance the tensile properties of concrete structures while also reducing the harmful carbon dioxide emissions due to cement production.

Following allogenic hematopoietic cell transplantation (allo-HCT), patients are at risk of developing graft-versus-host disease (GvHD) in which donor T-cells attack the recipient’s healthy tissues, including in the gut leading to inflammation, diarrhea, and sometimes death. Low gut bacterial diversity in the host has been associated with GvHD severity. Anaerobic bacteria in the Lachnospiraceae family, specifically Blautia species, have been associated with reduced GvHD related mortality. Using family and genus specific qPCR assays, we quantified the bacterial concentrations of Lachnospiraceae and Blautia species pre- and post-transplant in patients. We extracted DNA from stool samples of 306 HCT patients. Samples were collected pre-transplant and post-transplant at day 30 and day 60. GvHD gut stage was graded 0-1 (none-mild), 2-4 (moderate-severe). Quantitative PCR assays were designed using primers targeting specific regions of the bacterial 16S rRNA gene. Amplicon specificity was confirmed using post-run melt curve analysis. There was a significantly higher (p=0.016) concentration of Lachnospiraceae in patients presenting none-mild GvHD (6.78x10⁷ copies per swab) versus moderate-severe gut GvHD (1.84x10⁷) at day 60. A similar association for Lachnospiraceae was trending (p=0.088) at day 30. In addition, there was significantly higher concentrations of Blautia species in patients with none-mild (3.33x10⁶ at d30, 1.05x10⁷ at d60) versus moderate-severe gut GvHD (1.35x10⁵ at d30, 1.41x10⁶ at d60) at both day 30 (p=0.026) and day 60 (p=0.014) post allo-HCT. There were lower concentrations of both Lachnospiraceae (1.89x10⁷) and Blautia (2.30x10⁶), regardless of GvHD stage, at day 30 versus pre-transplant (p<0.0001) or day 60 (p<0.0001), likely reflecting the impact of antibiotic treatment during neutropenia immediately following allo-HCT. Higher concentrations of Lachnospiraceae and Blautia in the gut following transplant were associated with less severe gut GvHD; these bacteria could be markers or drivers of less severe GvHD.

Airline flight schedules face various kinds of stochastic disruptions, such as inclement weather, that cause flight delays. These delays then propagate and disrupt the regular operations of subsequent downstream flights. These propagated delays can be extremely costly to airlines, so it is beneficial to reduce disruptions to subsequent flights. To minimize these disruptions, we consider the stochastic nature of these disturbances when creating aircraft routes that reduce delay propagation and are manageable once disrupted. In this study, we develop and compare three stochastic optimization models to optimize aircraft routing: (i) robust optimization, (ii) chance-constrained programming, and (iii) stochastic programming. To solve these models, we modify an efficient approach for solving vehicle routing problems with time windows and capacity constraints known as the Vehicle Routing and Scheduling Algorithm (VeRSA) for these three models. VeRSA is the integration of a heuristic with an exact method to quickly find a feasible solution while also providing an optimality gap and a guaranteed optimal solution. A benefit of VeRSA is the ability to devise a flexible index that can accommodate different objectives for various forms of uncertainty. VeRSA can also modify the feasibility routine that accommodates the complex aircraft maintenance constraints, which is a challenge in the mathematical programming approach. Using various delay scenarios, we compare the performance of the solutions from our three stochastic optimization models and discuss insights regarding their performance differences. Preliminary results using the base model and a small example have been solved in Gurobi while future results using real data from airlines in VeRSA are pending.

The concept of mild cognitive impairment (MCI) has evolved over the past several decades to represent a state of cognitive function between that seen in normal aging and dementia. Clinically, it is challenging to fully characterize and propose strategies for treatment partly becuase little is known about the extent of underlying pathology and why some individuals are resistant, and some are susceptible. This study describes a model of naturally occurring MCI in middle-aged mice that will help address neuropathology and resistance questions. C57BL/6 mice, 20 months of age, were tested for cognition using a spatial navigation learning task, a box maze, that identified a fast-learning group (MCI resistant) and a slow-learning group (MCI susceptible). Regarding strength and activity performance, both groups performed equally well. Brains were collected and either flash frozen and stored at -80°C, or placed in formalin for sectioning and immunohistochemistry (IHC). Preliminary data suggest a number of messaging pathway differences in the brains of MCI resistant and MCI susceptible mice. One such pathway appears to involve inflammatory cytokines providing the rationale to test for expression of inflammatory regulators MCP1 and TNF-𝜶, using IHC and digital imaging. I am currently staining the brains using these IHC assays and then running the images through a digital imaging program known as Qupath. The expectation is that MCI resistant mice will display low levels of MCP-1 and TNF-𝜶 expression while MCI susceptible mice will show high levels of MCP-1 and TNF-𝜶 expression in the brain. Additional data will help establish naturally occurring cognitive impairment in middle aged mice as a useful model for studying neuropathology and therapeutic approaches related to MCI in people with increasing age.

The Southern Ocean is the largest oceanic carbon and heat sink on the planet with complex dynamics at a variety of scales. Reliable, accurate, and high resolution estimates of nitrate and carbonate system parameters (hereafter biogeochemical estimates) of the Southern Ocean would enable the analysis of mesoscale and submesoscale biogeochemical processes throughout the water column. This work explores the use of multiple methods, including several from the machine learning literature, for biogeochemical parameter estimation in the Southern Ocean. Training data for this work includes temperature, salinity, oxygen, and nitrate data from the 2019 R/V Thomas G. Thompson reoccupation of the I06S line and from Southern Ocean Carbon and Climate Observations and Modeling project (SOCCOM) floats deployed during this cruise. Four models for the estimation of nitrate were trained and validated for accuracy, these models included a random forest regression, a general additive model, a multiple linear regression, and a gradient boosted regression tree model. The random forest regression performed the best out of the four machine and statistical models on our nitrate test data with a median value for the absolute error of 0.096 µmol kg-1 and an interquartile range of 0.194 µmol kg-1 in the absolute error. Using this random forest model, we generate high resolution predictions of nitrate along the tracks of two Seagliders deployed on this cruise. We plan to repeat this estimation process for pH along the Seaglider tracks as well. The nitrate and pH data estimated from the random forest can then be used to calculate the carbon flux at each point, which can be used to improve our understanding of mesoscale and submesoscale processes related to carbon flux in this region of the Southern Ocean.

Creating novel anti-cancer drugs aimed at targeted glioblastoma multiform (GBM), a type of brain cancer, is slow, extremely expensive, and remains a persistent challenge within the medical field. To address this challenge, our team’s research project is aimed at creating scaffolds from chitosan-hyaluronic acid (CHA) to mimic the brain microenvironment and serve as a platform for high throughput screening (HTS) of cancer drugs. 3D culture systems can promote more cell-cell and cell-matrix interactions, which can closely mimic the in vivo extracellular matrix environment. Studies have shown that the drug resistance of 3D-cultured cancer cells can better reflect the in vivo situation, and thus can potentially improve the success rate in drug screening processes. CHA scaffolds are especially beneficial for culturing GBM cells, as hyaluronic acid (HA) is a major component in brain tissues. To generate the scaffolds, we used different freezing rates and temperatures to create freeze-dried 8 wt% CHA scaffolds with pore sizes of 60, 120 and 180 μm. We characterized the compressive modulus of the scaffolds using the Instron test machine, and the porosity using liquid replacement methods. Cell studies with 3 different cell lines are currently being conducted on these scaffolds, after which an AlamarBlue assay will be used to determine the optimal pore size for each cell line in terms of their growth and drug resistance. The results of this can prove that our CHA scaffolds have good flexibility in response to different cancer cell line 3D cultures and have good potential to be an HTS platform.

Chronic non-bacterial osteomyelitis (CNO), also known in its severist form as Chronic Recurrent Multifocal Osteomyelitis (CRMO), is a rare, auto-inflammatory disease with no present cure. The disease involves the chronic inflammation of normal, healthy bone without the presence of infection. Currently, no medications have been approved by the US Food and Drug Administration specifically for CNO. Consequently, many different types of medications, including disease modifying anti-rheumatic drugs (DMARDs) and tumor necrosis factor (TNF) inhibitors, and Bisphosphonates are being prescribed off label. However, patients can have significant side effects after taking these medications and consistent reports on the prevalence of these serious adverse events (SAE) among CNO patients are lacking. We will be examining instances of COVID-19 infection, hospitalizations, and psoriasis while taking CNO medication. We aim to investigate the association between taking various medications with the prevalence of SAEs among patients under 21 years old. For our research, we are drawing information from one of the largest CNO clinical research databases, Seattle Children’s Hospital’s database from January 2014 - present day. We hypothesize that all medications will be well tolerated by CNO patients under 21 years old. Through self-reported patient data and physician examination, information on SAE prevalence was collected. The patient population includes 351 patients treated with DMARDs, 294 treated with TNFs, and 89 treated with Bisphosphonates. General statistical methods were used to summarize the data and determine correlation; descriptive statistics was used to report the incidence rate per 100 patient years.As there is minimal knowledge about effective treatments for CNO, we expect that the results of this study will shed light on the reliability of various medications, improving patient disease management and possibly lead to a cure.

Breast cancer is one of the most common cancers in women. The effectiveness of a person’s immune response in combating the spread of cancer varies from patient to patient. By creating an immune cell profile, our research hopes to visualize whether immune cells are prohibiting or promoting cancer growth. To comprehensively analyze the tumor profile, our current research is focused on developing a deep learning program that can accurately identify immune cell profiles on H&E tissue samples. With advancements in AI technology and computational power, deep learning models can now offer more accurate cancer prognosis due to its ability to handle vast amounts of data. We will first utilize H&E stained tissue samples from existing public datasets, such as TCGA-BRCA and CAMELYON17, to develop a program that accurately maps the immune network associated with the disease. Public datasets are more advantageous in developing deep learning models as it provides large quantities of readily available data to test and train the program. We will train the algorithm to digitally segment different types of immune cells directly on H&E stained images. A spatial immune profile of the cancer will allow clinicians to provide more accurate breast cancer prognosis and a new method in monitoring the effectiveness of immunotherapy for different patient groups. Our goal is to deploy our technology across different clinics. Additionally, we will also acquire high-resolution immune maps by targeting multiple cells on the same slide using multispectral imaging technology to enhance the previously generated digital spatial library.

Cyclic population tendencies, found in small mammals like voles, lemmings, and snowshoe hares, have fascinated ecologists for over a century. More recently, it has been suggested that large mammals like ungulates may have cyclic patterns as well. For example, Indigenous history and palaeoecological records show that caribou or reindeer (Rangifer tarandus) can have population cycles that last from 50-100 years. Though caribou are well-studied globally, few studies have examined the underlying conditions prompting these dynamics, and so little is known about what causes them. It is hypothesized that factors such as climate, vegetation growth, predation, density-dependence, and subsistence harvest are all influential. I aimed to identify which of these factors contribute to population cycling, and better understand how to manage caribou for subsistence and recreational harvest. To do so, I built a tri-trophic mathematical model based on ordinary differential equations representing wolf-caribou-vegetation dynamics under various parameter scenarios. Based on available data, I chose to focus on North American barren-ground caribou herds located in Alaska and Canada. I extracted parameter values from existing literature on caribou and moose to parameterize my tri-trophic model. I ran my model in R, manipulating parameter values to see which factors influenced cycle period and amplitude most significantly. The results from these model simulations can better inform future management strategies and policy implementation surrounding sustainable harvest. Caribou are immensely important to Indigenous communities for cultural and subsistence purposes. With a shift in global climate, sensitive biomes such as the tundra are increasingly at risk of experiencing lasting negative impacts which will severely impact wildlife and other biotic systems. Adaptive caribou management is crucial to ensure survival for this globally declining species.

Biological tubes are the foundation of most animal organs, and thus, tube formation is an important developmental process. We study tube formation in Drosophila melanogaster egg chambers by analyzing the formation and elongation of dorsal appendages (DAs), eggshell structures that facilitate gas exchange in the fully developed egg. To form these tubes, a subset of follicle cells (the DA-patch) must rearrange, change shape, and migrate towards the anterior of the egg chamber. Polarity proteins, which establish cell directionality, are important for mediating these behaviors, but the mechanisms through which they do so are not fully understood. My research aims to enhance our understanding of these mechanisms by establishing how the polarity protein Crumbs (Crb) is involved in the formation of the DAs. To address this question, I used the mosaic analysis with a repressible cell marker method to generate mosaic clones in egg chambers that are null for crb and marked with green fluorescent protein. To determine how the loss of Crb affects DA formation, I used immunostaining to assess cell shape and position by visualizing the membrane protein E-cadherin, which participates in a regulatory network with Crb. I found that Crb is important for proper DA-patch cell shape changes during early tube formation, and that losing Crb causes delayed DA-patch cell migration, leading to shortened DAs. I also discovered that E-cadherin is mislocalized when Crb is lost, indicating that the interaction pathway involving E-cadherin and Crb may be responsible for the defects observed during tube formation. To test this hypothesis, I will stain for other proteins in this interaction pathway. By understanding this pathway, we can gain insight into how Crb functions in DA formation. Since tube-forming mechanisms are highly conserved, this work will suggest how polarity proteins regulate tube formation in all animals, including humans.

Age is the biggest risk factor for Alzheimer’s Disease (AD). However, it is insufficiently studied in regards to AD treatment and therapies. Cellular senescence is a hallmark of aging that is characterized by irreversible cell cycle arrest, and the senescence-associated secretory phenotype (SASP). Senescence can be beneficial in some contexts, but the accumulation of senescent cells with aging contributes to a chronic inflammatory state and age-associated functional decline. Cellular senescence in the brain has been implicated in AD, highlighting the need for appropriate models to study this process in more detail. Senescence-accelerated mouse prone 8 (SAMP8) mice are a model of AD that arises from a natural mutation that causes accelerated cognitive decline due to brain accumulation of amyloid-beta, a protein that is thought to contribute to AD. The goal of this project was to characterize cellular senescence-related changes in the brains of SAMP8 mice and track senescence markers with amyloid-beta and cognitive dysfunction. The cerebral cortex and hippocampus were isolated from 2, 6, and 12-month-old SAMP8 mice brains. Quantitative Polymerase Chain Reaction (PCR) assays were utilized to measure mRNA levels of senescence (p16, p21) and SASP (PAI-1 and IL-6) markers in each brain region. Amyloid-beta was measured using ELISA. We saw a significant increase at 12 months for all markers of senescence and SASP in the cortex, however, we only saw an increase in p16 and IL-6 in the hippocampus. Our results show that cellular senescence in the brain is temporally associated with the onset of cognitive decline in SAMP8 mice, but appears to happen after the amyloid-beta has maximally accumulated. As a future direction, we will determine whether senolytic drugs, which selectively kill senescent cells, can improve cognition in SAMP8 mice.

Workplace diversity and inclusion (D&I) efforts are well-intentioned but often too focused on meeting metrics instead of making structural changes that are directly aligned with the commitment to D&I. To examine people’s perception of company training towards D&I efforts, the current study investigates whether knowing a company is dedicated to implementing D&I initiatives influences their perception on the necessity of other systemic interventions. We expose each participant to a company that implements D&I training (diversity training company) and a company that does not (no diversity training company). Then, we measure their perception of each company's need for structural changes. We hypothesize that participants presented with the diverse training company will rate the company’s future diversity efforts as less necessary. The finding of this research provides evidence that the presence of D&I training may have unintended consequences of preventing organizations from making other important systemic changes.

The misfolding and consequent aggregation of amyloid peptides to form insoluble fibril plaques has long been known to be implicated in amyloid diseases such as Alzheimer's Disease (AD), Type 2 Diabetes (T2D), and Transthyretin Amyloidosis (ATTR Amyloidosis). More recently, these peptides have been shown to form intermediates of unique secondary structure called alpha-sheet. Furthermore, it has been shown that these alpha-sheet intermediates, rather than the insoluble fibrils, are the toxic conformation of amyloid peptides, causing effects such as the death of neural cells and beta-cells, in AD and T2D respectively. Using this knowledge, in this project we have characterized the aggregation and structure of the amyloid peptides such as amyloid-beta and islet amyloid polypeptide under reproduceable conditions and through a variety of techniques such as thioflavin T fluorescence assays and circular dichroism. Additionally, we have shown the ability of synthetic alpha-sheet peptides to inhibit amyloid aggregation and reduce overall fibril content. Using this idea of selective alpha-sheet binding, we have developed a soluble oligomer binding assay (SOBA) that is able to detect toxic amyloid species. These SOBA experiments have shown promising results and have been used to confirm amyloid aggregation pathways as well as detect toxic amyloid at physiologically relevant concentrations, with applications in the early diagnosis of amyloid diseases.

Alzheimer’s Disease (AD) is a neurodegenerative disease that is the most common cause of dementia. One hallmark of AD pathology is hyperphosphorylation of Tau protein. Tau is a neuronal-specific protein that stabilizes microtubules. Hyperphosphorylation of Tau leads to loss of its normal function and promotes aggregation into neurotoxic fibrillary tangles. While Tau aggregation is well-documented, the exact role of Tau loss-of-function in AD pathogenesis remains uncharacterized. The goal of our project is to determine the mechanism by which Tau loss-of-function contributes to AD pathogenesis. We hypothesize that Tau loss-of-function contributes to AD pathogenesis by activating the cellular stress response in neurons, characterized by DNA damage, stress granule formation, and immune activation. To test this hypothesis, we produced mixed cultures of neurons and astrocytes derived from human induced pluripotent stem cells. We generated three cell lines: one in which Tau expression was knocked out (Tau KO), another in which Tau expression was knocked down (shTau), and control lines. To determine whether genes implicated in the cellular stress response are upregulated in Tau KO neurons, we used RNAseq and real-time polymerase chain reactions (RT-PCR). Then, we used immunocytochemistry to detect protein markers of cellular stress in neural progenitor cells and neurons from all three lines. Preliminary results indicate upregulation of genes and proteins associated with neuroinflammation and stress granule formation. Regarding neuroinflammation, Tau-depleted neurons exhibit increased secretion of chemoattractant cytokines, and tau-depleted astrocytes demonstrate increased glial fibrillary acidic protein expression suggestive of pro-inflammatory cytokine induction. In terms of cellular stress, Tau-depleted neurons show increased levels of proteins involved in stress granule formation and cytoplasmic double-stranded RNA known to induce stress granules. By elucidating the role of Tau loss-of-function in AD pathogenesis, this research could inform therapeutic targets for AD.

Substance use disorders contribute to mortality nationwide and are associated with aversive and appetitive behaviors the ventral hippocampus (vCA1) is known to process. The neuromodulators dopamine (DA) and norepinephrine (NE) are also involved, but their release dynamics have not been thoroughly studied in this region. The dorsal hippocampus (dCA1) has similarly weak innervation from the ventral tegmental area (VTA), the major DA source, and the locus coeruleus (LC), the major NE source, and preliminary data in this region suggest an inhibitory effect on DA during salient aversive stimuli and minimal DA release during anxiogenic behaviors. To quantify monoamine release in the vCA1 and determine whether LC-sourced DA can be released there, we intracranially injected Dbh-cre positive mice with one of two biosensors, dlight for DA or GRABNE for NE, in the vCA1, and chrimson, a cre-dependent red-shifted channelrhodopsin, in the LC. A fiber optic lens for optogenetic stimulation and recording was implanted in the vCA1. We recorded dynamics during aversive and appetitive behaviors and found that DA and NE are released in the vCA1 during salient aversive stimuli, and that DA is released and NE release is inhibited during appetitive behaviors. We stimulated chrimson-transfected LC noradrenergic axon terminals while recording neuromodulator dynamics in the vCA1, and found that when stimulated for three seconds at 20 Hz, GRABNE fluorescence increases before slowly returning to baseline, while dlight fluorescence spikes quickly over 10 seconds, then exhibits a secondary, less steep, wave over the next 20 seconds. This secondary wave of DA is not observed in preliminary dCA1 data, indicating that it is unique to this region. In future studies we will investigate the role of the VTA in this secondary release with pharmacological inhibition experiments. These findings reveal distinct monoamine release in the vCA1 during aversive and appetitive behaviors. (Funded by NIMH-R01MH112355)

Chronic Nonbacterial Osteomyelitis (CNO) is a rare chronic auto-inflammatory bone disease that causes persistent bone pain and complications including bone deformities and poor growth. The goal of this study is to determine the impact of CNO on growth at the diagnosis and the longitudinal outcome of the height and weight of affected children from a prospective observational cohort registry, Chronic Nonbacterial Osteomyelitis International Registry (CHOIR) (NCT04725422).This report includes children between the ages of two and eighteen who were newly diagnosed between August 2018 and August 2021 and had weight, height, and BMI measurements documented at enrollment within 6 months of diagnosis. Age- and sex-standardized scores were calculated for all and measured against the growth impairment criteria defined by the WHO’s Child Growth Assessments. The impact on the height, weight, and BMI Z-scores by CNO using physician assessed disease activity as surrogate marker, primary ethnicity, and sex will be assessed. Incidence of obesity and short stature will be reported using descriptive statistics. Due to variations in treatments and CHOIR being a relatively new database, we will only be reporting generalized trends with limited data. We expect that more than 2.5% of CNO patients will be in each of the growth impairment categories, including short stature (<2.5 percentile of height by age and sex), obesity (>97.5 percentile of weight by age and sex), and thinness (<2.5 percentile of weight by age and sex), all within 95% confidence interval (CI). In addition, those with improved physician disease scores will have either an improved or unchanged impairment category. Understanding the possible implications of CNO disease activity and treatment options on growth and development will provide insights into another treatment goal beyond pain control and resolution of physical symptoms for these children.

Chronic kidney disease affects over 15% of the U.S. population and 9% of people worldwide. For many of these individuals, chronic kidney disease leads to kidney failure, or end-stage renal disease, where their kidneys are no longer capable of filtering wastes and toxins out of the bloodstream. Current treatments for kidney failure are limited to kidney transplantation and dialysis. Kidney transplantation is a lengthy and taxing process, limited by the availability of donor organs, and typically requires lifetime immunosuppressant usage post-transplantation. Hemodialysis, the most prevalent form of dialysis, is more accessible but tethers patients to dialysis clinics 3-5 hours per session, three times a week. Thus, the development of portable dialysis devices is integral for greater patient freedom and wellbeing. However, since hemodialysis requires ~120L of dialysate per session, development of such devices is restricted by the inability to efficiently and effectively recycle dialysate. To address this problem, we investigated polymeric membranes as candidates for dialysate toxin filtration, given previous industrial applications in water purification. We developed a cellulose acetate-based membrane that is selectively permeable to urea, a primary toxin targeted by dialysis, over larger molecules such as glucose. Using artificial dialysate solutions, I have assessed the diffusion and flux properties of various iterations of the membrane to determine the effect of chemical composition and synthesis procedure on molecular exclusion properties and performance parameters. I am currently performing static membrane characterizations to quantify morphology and structure. By integrating our toxin filtration membrane with a previously developed urea photodecomposition system, we will be able to efficiently regenerate dialysate and develop a portable dialysis device, providing patients with significantly more freedom in day-to-day life. Furthermore, our results can be applied towards other areas requiring nanofiltration for molecular separation, extraction, and purification.

Globally, about 10% of people living with HIV (PLHIV) also have concurrent Hepatitis B virus (HBV) infection. Without routine screening for HBV, the choice of antiretroviral therapy can be more difficult to manage, as not all medications treat both infections. The objective of this research was to identify risk factors that put PLHIV at higher risk of HBV infection. We conducted a prospective clinic-based study from 2013 – 2017 in Durban, South Africa. Participants were enrolled into the study if they tested positive for HIV, and all PLHIV were tested for HBV after enrollment. Follow up assessments were conducted at 3, 6, and 12 months after enrollment. Patients completed questionaries pertaining to sociodemographic status, medical history, clinical symptoms and mental health at each visit. I compared prevalence of HBV between age groups using a T-test. Univariate and multivariate logistic regression models were conducted on co-variates of the data set using the ‘dplyr’ and ‘stats’ packages in R. I measured adjusted odds ratios (aORs) for each covariate to compare risk factors for those with HBV and HIV compared to PLHIV. A total of 3105 PLHIV were enrolled, with a mean age of 33 years and 43% (n=1331) male. Of those, 196 (6%) individuals tested positive for HBV, with a mean age of 33 years and 62% (n=121) male. Participants aged >25, who were born before South Africa implemented routine infant vaccination for HBV in 1995, were more likely to have HBV (p=0.043). HBV diagnosis was associated with drinking alcohol over the past year (aOR = 1.17), lack of condom use (aOR = 1.10), and income >10,000 ZAR/month (aOR = 1.63). Implementing routine HBV testing for adults born before 1995 can help prevent the further increase of HBV infection rates. These study findings also provide additional support for enhanced HBV screening among PLHIV.

The discovery of fluorescent proteins led to the development of various protein-based biosensors that are vital in the goal to decipher the complexity of neural networks. Genetically encoded fluorescent indicators (GEFIs) are protein-based sensors with cell type specificity that increase in fluorescence upon ligand binding and allow for passive monitoring of neuronal signals. However, the development of such sensors is limited by the slow throughput of traditional protein engineering which has long engineering cycles of new plasmid variants. My project tackles this problem through the development of an optogenetic microwell array screening system (Opto-MASS) that effectively generates and screens unbiased genetic libraries of GEFIs in mammalian cells. The platform identifies high performing sensor variants on a custom microarray and effectively isolates and recovers their genetic material. This new platform was used to develop a sensor for the μ-opioid receptor (MOR), which is a G-protein coupled receptor and is responsible for the pain relieving effects of opioids and addiction. The platform has developed a MOR sensor that surpasses the standard in the literature in response to the synthetic opioid peptide agonist [d-Ala2, N-Me-Phe4, Gly-ol5]enkephalin (DAMGO). I used this platform to engineer a new class of MOR sensors that are ligand-specific to endogenous opioids versus exogenous opioids and optimized the sensors for maximum spatial and temporal precision. The development of a MOR sensor through this iterative process allows researchers to further investigate the molecular mechanisms underlying the pathology of addiction and provides a novel platform for protein engineers to more efficiently develop a wide variety of biosensors.

The rapid rise of bioanalytical testing has renewed discussions in improving the collection of bacteria through oral sampling. Current diagnostic tests for common respiratory illnesses such as strep throat are invasive and uncomfortable, especially for children. Undiagnosed, these treatable diseases can cause serious damage. The Theberge lab has created the CandyCollect, a saliva sampling device intended to be a child-friendly alternative to current sampling techniques for home and clinical settings. The CandyCollect utilizes candy in the design to appeal to children, a unique component that requires additional testing and standardization to be appropriately implemented. This study explores the intersectionality of safety, design, effectiveness, and ease of application by using candy to increase children's compliance and act as a built-in timer. Our goal is to modify the existing device with these objectives in mind. Several types of candy were made using different ingredients, flavors, and textures, and the interaction of these candies with oral bacteria and saliva was investigated. We engineered the device using rapid prototyping, computer-numerical-control (CNC) milling, and silicone mold development. These methods allow for the flexibility to modify the design of the candy and sampling device. We then designed a survey for a human subjects study for adults (>18 years) to receive useability feedback and adapt the device components. Our analysis of these results determines the variety of candy that is most suitable for large scale use. The findings of this study will offer an improved method for child diagnostics and encourage other industries to redesign traditional sampling procedures. 

Cultural stigmatization, financial burden, and low mental health literacy are reasons why Chinese people with mental health issues tend not to seek help from psychotherapists or psychological counselors. I hypothesized that Measurement-based Care (MBC) might provide a possible solution to some of the problems mentioned above by introducing a data-driven approach to mental health treatment. By representing mental health suffering in a quantitative and objective way, I thought this might legitimize mental health treatment, especially by showing the effectiveness of psychological counseling on symptoms. Additionally, I hypothesized that the combination of MBC and psychotherapy might impact Chinese people’s attitudes toward psychological counseling services in China. I recruited two hundred participants, ages 18-65, through an online Chinese survey platform called Wenjuanxing (wjx.cn) from all regions in mainland China. I collected survey responses to questions measuring attitude changes toward psychological counseling before and after learning about MBC. After conducting preliminary analyses, the results indicate that participants were significantly more likely to receive help from mental health counselors providing psychosocial interventions after learning about MBC compared to their attitudes before learning about MBC. This result means that MBC has the potential to facilitate positive attitudes toward psychological counseling in China, helping more Chinese people to accept mental health counseling when they need mental health support. This survey study also built a foundation for future researchers to explore this area further.

The detection of bioaerosols is critical to the control of public health hazards. Improvements in detection technology enable better tracking of infectious diseases, allergens, biogenic pollutants, and biowarfare agents. Bioaerosols are typically detected through laboratory analysis on collected aerosol samples. Porous filters exist for collecting aerosols, but are bulky, which makes them unsuitable for many testing environments and results in a dilute sample due to the large collection region. We present an automated microfluidic device for the collection of bioaerosols. Our design aerodynamically focuses aerosol particles into a microwell collection region, then elutes (washes off) the contents of the well into a 10 μl volume for analysis. This method automates the elution process and results in a tenfold increase in sample concentration compared to conventional filtering, making it highly compatible with analysis methods such as spectroscopy, plaque assay, and qPCR. In preliminary experiments, we evaluated device performance by collecting non-biological test particles. We then compared the device’s collection efficiency to that of reference filters and found the efficiency to be approximately 80%. Additionally, we applied a water-soluble sacrificial layer on the microwell to reduce the elution time. To optimize the sacrificial layer, sucrose solutions of varying concentration were tested on 3D-printed microwells. The next focus is on optimizing the elution protocol to achieve peak elution efficiency in the minimum timeframe. We, the undergraduate research assistants on the team, are responsible for running experiments, analyzing data, and presenting to stakeholders. This project will ultimately provide a fast and efficient method for users to examine a room for bioaerosols, with little to no training and minimal user exposure to hazardous air. We hope that this device can be provided to a variety of beneficiaries, including healthcare providers for immunocompromised individuals, severe allergy sufferers, and virulent disease researchers.

Juvenile idiopathic arthritis (JIA) is the most common rheumatic disease in children and frequently presents in knees, followed by ankles, wrists and elbows. JIA is typically evaluated by pediatric rheumatologists using joint exams. However, musculoskeletal ultrasound or MRI with contrast can be used for greater sensitivity but are more expensive and require extensive operator training. In contrast, infrared thermal imaging is a noninvasive tool that is quick, economical, and precise in detecting temperatures of different body parts. Thermal cameras are becoming increasingly accessible and can be used with smartphones, like the FLIR ONE Pro camera by Teledyne FLIR. Recent efforts with temperature after within limb calibration (TAWiC) algorithms have made use of thermal imaging and demonstrated promising results in detecting arthritis in knees and ankles. However, the current TAWiC algorithm implementation has limited scalability due to its dependency on trained technicians to identify key anatomical points. We leveraged existing computer vision libraries like OpenCV and human pose estimation models like OpenPose to automate the TAWiC algorithm. We designed a pipeline that first entails extracting thermal and visible images from a radiometric JPEG generated by a FLIR ONE Pro. The extracted images are subsequently co-registered. Key anatomical points are then labeled in the visible image using OpenPose and contours drawn around the regions of interest. The contours coupled with the labeled key points are used to segment and retrieve the temperatures of specific anatomical regions. We collected preliminary data that demonstrated the feasibility of this workflow. We anticipate that similar TAWiC measurements will be generated when using the automated approach to re-analyze participant thermal images. Automating this algorithm will increase the scalability of this approach and allows for extending this algorithm to other joints.

China’s rapid economic growth and urbanization in the recent two decades marked one of the most incredible speeds since human civilization, but the deeper social and environmental issues keep being exposed as relentless urban sprawl sweeps across the country. In 2012, under the nationwide “land-creation” movement, Yan’an, a major city in central China with a population of 2 million situated on the Loess Plateau, started implementing its 10-year plan to bulldoze mountains and build a “New District” on the hilltops to accommodate the exploding population. Despite mainstream narratives that feature it as a pioneer work of urbanization, I argue that the scarred land and the exploitative system in the “New District” cannot support the Plateau residents culturally and psychologically. This research draws on various theories and studies on anthropology, sociology, and urban planning to analyze the social, cultural, symbolic, and psychological impacts of the Yan’an “New District” project. The novel perspective proposed by this paper reconsiders urbanization as an exploitive and deceptive process and reexamines the future of rural-to-urban migration and urban growth.

Although the prevalence of cannabis use among pregnant individuals in the US has increased dramatically over the past decade, limited research is available on the impacts of prenatal cannabis exposure (PCE) on infant development. The main psychoactive compound in cannabis, tetrahydrocannabinol (THC), has been shown to cross the placenta during pregnancy, suggesting potential impact on fetal development. Previous studies yield contradictory findings, yet many link prenatal cannabis use to postnatal outcomes such as impaired motor development. However, many of these studies were conducted before recreational cannabis use was legalized in many states, and often failed to control for known teratogens such as tobacco and alcohol. To address this gap, pregnant individuals from the greater Seattle area who used cannabis frequently (3-5 days/week) during the first trimester (PCE; n=37) or did not use any (control; n=35) were enrolled into this observational study. Use of cannabis, medications, and other drugs were tracked in real-time via weekly surveys throughout pregnancy. After birth, we assessed infants between 6-9 months of age using the Early Motor Questionnaire (EMQ). Birth information including weight, length, head circumference, and Apgar scores (1/5min) were also obtained for each infant after birth. I will investigate group differences on the EMQ and sample characteristics using independent samples T-tests. I hypothesize that infants with PCE will have poorer motor development compared to control infants. I also hypothesize that infants with PCE will have reduced birth weight, head circumference, and length. Due to increasingly widespread cannabis use, research on the impacts of PCE while controlling for demographic factors and known teratogens remains essential to support pregnant individuals in making informed decisions. Additional research on the relationship between PCE dosage and frequency on infant brain development will further aid in providing this necessary and comprehensive guidance.

Epithelial cells form barriers at mucosal surfaces that protect against pathogen invasion. Recently, epithelial inflammasomes were demonstrated to be a key component of epithelial immunity. Inflammasomes are multiprotein complexes that function as intracellular sensors of pathogens. Upon pathogen detection, the inflammasome-sensor assembles with the adaptor protein Apoptosis-associated speck-like protein containing a CARD (ASC) to activate the pro-inflammatory protease Caspase-1 (CASP1), which then goes on to activate the inflammatory cytokines IL-1β and IL-18 and the pore-forming protein Gasdermin D, which results in a lytic form of cell death called pyroptosis. In epithelia such as the lung and gut, Nucleotide-binding domain, leucine-rich repeat, pyrin domain-containing 1 (NLRP1) is the predominant inflammasome-forming sensor. However, the role of NLRP1 in corneal epithelia is unknown. To characterize the role of inflammasomes in corneal epithelia, we used the human corneal epithelial cell line hTCEpi as a model. We used CRISPR-Cas9 to knock out genes required for NLRP1 inflammasome signaling (NLRP1, CASP1, and ASC) in hTCEpi cells. To induce NLRP1 inflammasome activation, we treated the hTCEpi cells with Val-boroPro (VbP), an inhibitor of the NLRP1 inhibitor dipeptidyl peptidase 9 (DPP9). We then measured IL-1β levels as a readout of inflammasome activation. We found that VbP-induced inflammasome activation was dependent on NLRP1, CASP1, and ASC. Our findings demonstrate that hTCEpi cells have a functional NLRP1 pathway, and suggest that the NLRP1 inflammasome mediates host defense and/or inflammatory pathogenesis in the corneal epithelium. We plan to test if viruses that cause conjunctivitis elicit an NLRP1 response in corneal epithelial cells, which would implicate NLRP1-mediated responses contributing to inflammation during viral conjunctivitis (i.e., pink eye).

The consumption of Cannabis has increased with legalization, rising 46% from 2019 to 2020 in the US. The primary psychoactive compound in Cannabis, ᐃ9-tetrahydrocannabinol (THC), modifies motivation and induces hypolocomotive effects that cause patients to stop using medical marijuana. Given the increasing frequency of Cannabis use and the unwanted side effects of THC, I sought to decipher the motivational and locomotive effects of THC on prefrontal cortex (PFC) activity during appetitive Pavlovian conditioning. I utilized biological sensors to measure neural activity (CamKIIa-GCaMP6f for calcium in projection neurons (N=3) and eCB2.0 for total endocannabinoid activity (N=6)) in WT mice aged 8-12 weeks. Neural activity (utilizing fiber photometry) and general behavior was recorded during appetitive Pavlovian conditioning. Here, a house light in the behavioral chamber (conditioned stimulus (CS)), initiated 6s before a sipper (sucrose) extended for 20 seconds (unconditioned stimulus (US)). After a random inter-trial interval of 60, 90, 120, or 150s, another event triggered a reward to consolidate an association between the house light (CS) and the reward (US). Mice experienced this conditioning for 25 minutes every day for 5 days. On day 6, I treated mice with either a moderate dose of THC (5 mg/kg) or vehicle to measure changes in neural and endocannabinoid activity during conditioning. I found that both endocannabinoid and calcium signaling were tightly locked to the CS and the US. Interestingly, trials where THC-treated mice did not interact with the sipper (THC-dependent demotivation), neural activity matched the pattern during training days. These data suggest time-locked neural activity linked to stimuli, separate from the locomotor output, to receive the reward. This study contributes to the understanding of THC’s effects on signaling during motivated versus locomotive behaviors to inform future THC-derived treatment paradigms.

DNA replication is vital to most every organism, yet key processes in replication are not yet understood. As the replisome moves through a strand of DNA, it naturally induces a state where the DNA strand wraps around itself, termed ‘positive supercoiling.’ Positive supercoiling knots DNA, preventing DNA from being pulled apart further during replication, with ~100 supercoils formed every second during DNA replication in bacteria. These positive supercoils must be resolved for DNA replication to continue, a task performed by topoisomerase enzymes. However, the mechanism for topoisomerase recruitment to positive supercoils is not known. Growth-Associated Protein in Regulation (GapR) is a structuring protein that stimulates topoisomerases in α-proteobacteria: without GapR, α-proteobacteria die off, unable to replicate their DNA, suggesting GapR is likely a missing regulator to topoisomerase recruitment. The focus of my research is the mechanism for how GapR interacts with topoisomerases, and I hypothesize that GapR interacts directly with topoisomerases. I am studying this interaction by analyzing interacting proteins from interaction assays between GapR and proteins from Caulobacter crescentus. In initial assays, I utilized histidine-tagged GapR to interrogate potential interacting proteins and found multiple bands of proteins in the size range of topoisomerases, supplemented with similar findings for 3xFLAG tagged topoisomerase subunits GyrA and ParC identifying GapR-sized proteins, suggesting a possible direct interaction between GapR and topoisomerase enzymes. Because topoisomerase inhibitors are anticancer and antimicrobial therapeutics, understanding the mechanism of how GapR and topoisomerases interact will reveal crucial information regarding the topoisomerase regulation of DNA replication and could have far-reaching implications for both antibacterial drugs and cancer treatment.

Proteins serve a pivotal role as building blocks for all living species in the biochemical world. An understanding of the function of a protein often requires first obtaining knowledge on the protein’s structure. Our research utilizes an innovative spectroscopic approach, double electron-electron resonance (DEER), to analyze protein structure. In the DEER experiment, we tag the analyte protein with magnetically active labels, the magnitude of magnetic interaction reflects the distance between the labeled sites. This technique has been utilized in determining the structure of many proteins that play important roles in society and public such as cell-membrane ion channels. A key component of using this method is rigorous data analysis and uncertainty quantification to achieve higher resolution and confidence in the structural conclusions made from the data. To conquer the constraints of traditional data fitting schemes that can usually succumb to bias and overconfidence, we apply the principles of Bayesian statistics through a Python based program, Dive, that utilizes Markov Chain Monte Carlo simulation to sample the data and analytical model. The program generates a fitted distribution of parameters to best characterize the data such that a good balance between uncertainty and bias can be achieved, which will help DEER practitioners in processing the data and making conclusions with respect to the critical functions of proteins.

Measurement based care (MBC) is an evidence-based approach to psychological care that has been gaining momentum in the field. MBC emphasizes the use of frequent, repeated administration of measures and the consequently collected data in order to inform the course of treatment. This contrasts with traditional care, which relies more heavily upon clinical judgment and only sparse use of measurements. MBC has been shown to provide significant improvements for patients, largely due to increased patient feedback which results in quicker responses in changing treatment plans accordingly. Ecological momentary assessment (EMA) is a data collection strategy where researchers repeatedly remotely administer surveys that ask about participants’ current real-time states, and can provide additional clinical utility to MBC treatment through more contemporaneous data which is less subject to the errors of retrospective recall. Despite EMA’s ability to gather more ecologically valid data, there is a lack of research on how to optimize EMA to reduce concerns of response burden and adherence. This research aims to help clarify this knowledge area by examining how timing and frequency of measures affects participants’ adherence to an EMA procedure. We recruited 215 participants from the University of Washington’s Psychology Subject Pool, and randomly assigned each participant to one of two groups—each group was tasked with answering the same short survey, a modified 5-item version of the Subjective Happiness Scale (SHS), either three or seven times a day, both over a period of three weeks. We predicted that there would not be a significant difference in adherence rates between the two different sampling frequencies, and that surveys taken earlier in the day would be completed less frequently than those in the evening. Understanding participants’ responses to EMA is critical not only for optimizing future psychological research, but also for improving the use of measures in clinical care.

Electric propulsion is the use of electrical energy to accelerate a propellant such as plasma, a superheated gas with its electrons stripped. Electric propulsion, as opposed to chemical propulsion, provides a low-propellant-mass solution for deep space exploration. My research evaluates the University of Washington’s ZaP-HD Shear-Flow-Stabilized (SFS) Z-pinch for its application to electric propulsion. The ZaP-HD SFS Z-Pinch, usually studied for fusion energy applications, compresses and confines a plasma into a column. This is done by using the self-generated axial plasma current to create a radial magnetic field that confines the plasma without the use of external magnets. In this experiment, I investigate the specific impulse, a measure of the efficiency of thrust generation, and ion temperature of the plasma plume. I take data using the spectrometer, which measures the intensity of light per wavelength. Using these measurements, I can calculate ion temperatures, ion velocities, and specific impulse. By varying the electrode voltages and collecting data, I find the optimal settings to generate a high-velocity plume with uniform flow and low plume divergence. These measurements enable me to evaluate the performance of the ZaP-HD SFS Z-pinch for an in-space propulsion application and aim to serve as a baseline for future experimenters in the optimization of the thruster configuration. Previous research predicts that the Z-pinch will produce high specific impulses. This would allow for a more efficient propulsion system, ultimately helping space exploration to reach new parts of our universe.