The recent decline in the body size of sockeye salmon (Oncorhynchus nerka) returning to Bristol Bay, Alaska has been associated with increased competition within the marine environment as these populations have increased in abundance. As an anadromous species, different populations of sockeye salmon return to freshwater environments, occupying streams of varying sizes to which they have evolved habitat-specific adaptations to local habitat conditions. In particular, fish spawning in small streams are substantially smaller than ecotypes that spawn in the deep water of rivers and lakes where sexual selection promotes large body sizes. We hypothesized that density-dependent marine growth in sockeye salmon would be most intense for large-bodied spawning ecotypes, compared to small-bodied populations where there is less evolutionary pressure to achieve large body size. Using general linear mixed-effects models, I compared the effect of run size on growth rates in sockeye salmon from a range of streams of different sizes. My preliminary results suggest that ecotypes spawning in large water bodies (stream mouth >5m wide, rivers, and beach spawners) show stronger density-dependent marine growth than ecotypes spawning in small streams (stream mouth <5m wide). These results demonstrate that evolutionary selection for spawning success as adults affects the development programs of juvenile salmon while in the ocean.

One outcome of strong intraspecific interactions is the top-down regulation of juveniles by older individuals in a population, resulting in cohort dominance. Due to their distinct spawning patterns and high variability in juvenile recruitment, many species of fish experience these interactions. Arctic char (Salvelinus alpinus) is a commercially and ecologically important species native to Alaska whose intraspecific interactions are only vaguely understood. The goal of this study was to assess the evidence for suppression of recruitment by older individuals that both compete with and cannibalize younger individuals in a population. I used Arctic char fork length data from Little Togiak River, Alaska, between 1972-2023 to construct annual size distributions. I conducted a wavelet analysis for periodicity to determine whether there was distinct cyclicity in the size distribution of individuals in the population, as would be expected by a population regulated by a dominant cohort. The analysis suggests periods of 10-15 years, the natural life span of Arctic char, where a new cohort arises from a successful recruitment event and suppresses subsequent generations through competition and cannibalism. Improving the understanding of top-down intraspecific regulation in Arctic char can help inform fisheries policy and provide additional insight into Alaskan ecosystem functions.

China’s rise and growing presence in the Indo-Pacific region is a major source of concern for the United States. To meet this challenge, President Biden’s administration has envisioned an Indo-Pacific Strategy aimed at keeping that vast region “free, open, prosperous, secure, and resilient” in conjunction with its allies and partners. This Task Force assesses the effectiveness of this strategy from the perspective of China as well as that of Australia, India, Japan and South Korea. It also examines the workings of this strategy from the standpoint of ASEAN and EU/NATO and that of such important world regions as the Middle East, Africa and the Pacific Islands. What can and must the U.S. do to maintain and enhance its ties to existing allies and partners and line up additional prospects to advance its Indo-Pacific strategy.

Dilated cardiomyopathy (DCM), a heart muscle disease characterized by ventricular enlargement and disorganized sarcomeres, stands as a leading cause of heart failure in young adults. Human induced pluripotent stem cell derived cardiomyocytes (hiPSC-CMs) can be used to study diseases with genetic components such as DCM which can be caused by mutations in structural components of the sarcomere. Missense mutations in the myosin heavy chain 7 gene (MYH7), encoding for the myosin heavy chain beta isoform (β-MHC), are the third most common genetic cause of DCM. However, the mechanism by which MYH7 variants lead to sarcomere disarray is poorly understood. In this study, I developed a novel assay to interrogate sarcomere incorporation and turnover dynamics in hiPSC-CMs. CRISPR/Cas9 genome editing was used to knock-in mEos, a green-to-red photoconvertible fluorescent protein, into the endogenous MYH7 locus of hiPSCs to visualize sarcomeric β-MHC incorporation and turnover. Upon differentiation of transduced hiPSCs, MYH7-mEos fusion protein is expressed and integrated in the sarcomeres of hiPSC-CMs. Pre-photoconversion, these cells exhibit green fluorescent sarcomere striations, transitioning to red fluorescence upon UV irradiation. Tracking green signal recovery (incorporation) and red signal depletion (turnover) over time post-photoconversion allows for quantification of sarcomere kinetics in these hiPSC-CMs. Through preliminary experimentation, I revealed a steady state fluorescence recovery and depletion of 40% in wildtype MYH7-mEos hiPSC-CMs. Future work is aimed towards using this novel strategy to analyze sarcomere dynamics of pathogenic hiPSC-CMs, thus allowing for the discovery of how and which of these rates differ across various MYH7 variants. I hypothesize that in hiPSC-CMs derived from a DCM patient expressing the MYH7 E848G variant, decreased incorporation or increased turnover rates may contribute to sarcomere disarray leading to a disturbance in sarcomere homeostasis among patients with this disease.

Seattle's Black community faces significant challenges in banking and finance, including a lack of trust, limited access, and systemic barriers. While FinTech presents potential solutions, concerns persist regarding data privacy and cultural sensitivity. In response to these issues, I took on a central role in facilitating a research project that aimed to co-design an inclusive FinTech solution directly with Black communities in Seattle. To create a participatory design approach and host collaborative sessions with a Black community advisory board, my research group worked closely with community leaders and stakeholders. This involved organizing focus group sessions, where we explored three key questions: 1) What challenges do Black Americans face in banking and FinTech? 2) How can FinTech revolutionize their economic outlook? 3) How can community members co-design a culturally sensitive virtual AI assistant for mobile FinTech? Throughout these sessions, I played an active role in observing and leading discussions to ensure that community members had a meaningful voice in shaping the solution. I also analyzed the data collected from these sessions using inductive and deductive coding techniques to identify key insights and inform the process and steps for the next focus group. We anticipate developing a prototype solution designed by and for Black communities, prioritizing trust, accessibility, and empowerment. Preliminary findings suggest that community engagement and co-design processes are crucial for creating effective and culturally sensitive FinTech solutions. Additionally, fostering understanding and collaboration between Black communities, financial institutions, and FinTech developers is essential for paving the way towards a more equitable financial future for all stakeholders involved.

Achieving consistent targeting of multiple simultaneous probes during electrophysiology experiments is a challenging and time-consuming process. Even with a planned insertion trajectory, experimenters still have to go through a lengthy process of positioning and inserting each probe. Electrophysiology experiments are increasingly focused on brain-wide coverage, requiring three or more simultaneous probes motivating researchers to accelerate their processes to reduce the duration of the experiment and the corresponding stress levels of their subjects. To improve the efficiency and reproducibility of multi-probe electrophysiology experiments, we developed two frameworks: a communication platform to allow software control of hardware micro-manipulators and an automation platform to perform multiple synchronous probe insertions. Each existing manipulator platform has proprietary software for programmatic control, which is rarely cross-platform and often exposes inconsistent interfaces. To standardize manipulator communication, we developed a Python server that acts as a generic cross-platform application programming interface (API). This platform ensures that client applications only need to interface with one API to be compatible with many different manipulator platforms connected across various computer operating systems. Building on top of this communication platform and an existing trajectory planning tool, Pinpoint, we next developed a system that automates the insertion process for multiple probes, saving time. The automation system provides three guarantees for researchers: first, that probes will reach their intended targets without manually introduced errors in targeting; second, that experiments can be repeated exactly to improve reproducibility; and third, that movement speeds are limited to low levels for reduced tissue damage. Because our software drives multiple probes simultaneously, complex multi-probe insertions are more manageable. Taken together, these open-source tools for communicating with hardware manipulators and automating multi-probe insertions enable the next generation of reproducible, high-efficiency, brain-wide electrophysiology data collection.

Communities in the Pacific Northwest region of the United States face a risk of harm from earthquakes and tsunamis, which cause significant health impacts. There is currently limited research on the specific vulnerability of women and gender minorities to natural disasters in the Pacific Northwest. This study examines how gender identity affects risk perception and disaster preparedness for residents of this region. This study asks: what individual or communal resources can Pacific Northwest residents access during a disaster, what are their experiences with disasters and disaster planning, and how do these differ across gender identity? I developed an online survey instrument alongside other undergraduate fellows with the Cascadia Coastline and Peoples Hazards Research Hub (CoPes Hub). The survey was completed by hundreds of residents of Washington, Oregon, and California in February 2023 and remains open. The study utilizes crosstabulations of current data from this survey, as well as interview data currently being collected by CoPes Hub fellows from 18-30 year old transgender residents of the Pacific Northwest (n = 10). I expect to find that women and gender minorities have less access to resources and have unique perceptions of disaster risk and preparedness compared to cisgender men. Identifying existing gender differences in disaster preparedness can inform further research into the root causes of these disparities, as well as targeted disaster policy that eliminates barriers to resilience for people of all genders.

While recent advances in sequencing technology have increased the detection of missense variants in human genes, the functional impact of ~99% of these variants is unknown. Improving our understanding of variant effects will make precision medicine more effective, allowing us to define, test, diagnose, and treat genetic diseases better. One way to understand what variants do is to measure and read out each variant’s effect in cell-based assays. However, there are nearly 9 billion possible single nucleotide variants in the human genome. To measure variant effects in a comprehensive manner, scalable experiments are necessary. Previously, the Fowler lab developed landing pad (LP) vectors to conduct scalable cell-based assays over entire gene variant libraries. However, the current LP design suffers from rapid silencing in cell culture, a phenomenon in which cells deactivate the expression of transgenes, greatly limiting the scope of variant assays. Stem cells are known to rapidly silence most exogenous sequences during differentiation, but they are a target model as LPs embedded in stem cells would allow us to study the effect of gene variation in cells specific to the related disease. Through previous work at the Fowler lab and others, we have characterized a set of promoters, enhancers, insulator sequences and other elements that will provide stable and robust expression of transgenes over time. We hypothesize that combining the LP with this set of elements will allow us to stably express variant libraries regardless of cell context. To test this hypothesis, we have designed a nested LP delivery system that allows us to compare different LPs side-by-side in the same genomic context. By comparing expression levels of transgenes over time, we expect to find that LPs enhanced with a set of stabilizing elements will express stronger signals over longer periods of time compared to LPs that are not enhanced.

Upconversion (UC) is a non-linear optical process where a material absorbs two lower energy photons and subsequently emits one of higher energy. Currently, inorganic UC materials used in lasers and photovoltaics are primarily lanthanide-based. However, a few transition metals also exhibit UC, such as Re4+ , Os4+, Ti2+, Ni2+, and Mo3+, and due to their high oscillator strengths, d-d transitions, and a strong ligand field dependency, offer the potential for greater tunability and efficiency in upconverting optoelectronics than their than their lanthanide counterparts. The goal of this work is to increase Re4+’s PLQY by isovalently doping low-phonon vacancy-ordered double perovskites (A2BX6 : A = Cs+, NH4+; B = Ti4+, Zr4+; X = Cl-, Br-) with rhenium to minimize non-radiative decay that can occur through defects and lattice vibrations. This has been attempted via schlenck line synthesis of the host lattice and coprecipation and ion-exchange doping procedures. While [ReX6]2- has previously demonstrated near-IR to visible upconversion in the bulk, this work aims to characterize its upconversion mechanism on the nanoscale with variable temperature and time-resolved photoluminescence. If made successfully, the colloidal stability of Re4+:Cs2TiBr6 nanocrystals would allow for new post-synthetic processing avenues including electrohydrodynamic inkjet printing and core-shelling, and new applications in flexible electronics.

Typical data visualizations in neuroscience flatten 3D space into just two dimensions, limiting researchers ability to observe spatial relationships. To overcome this limitation, we have previously developed rendering tools to support exploratory 3D visualizations, specifically for neuroscience data. In this project, I am expanding the renderer to allow users to display and explore additional non-spatial dimensions of their data. These new tools will allow users to explore additional dimensions of their dataset such as time, stimulus properties, or the spatial position of an animal. For example, to explore time, I have developed an interactive slider bar that dynamically updates the 3D display and a corresponding linked 2D plot, providing a clear depiction of neural activity with relation to specific events. Scrolling along the 2D plot enables users to pinpoint their position in time relative to stimulus onset, with the 3D display concurrently adjusting to reflect the data from that specific snapshot in time. These functions are packaged into the API of the renderer, streamlining the process for users to transform raw data into intuitive and interactive visualizations. Reducing the complexity of the code expands the accessibility of these new features, making them more approachable for new users who may be less familiar with coding. By supporting additional dimensions, users will be able to develop visualizations that are tailored to their individual research projects. My objective is to create research tools that are versatile, applicable to a range of projects, and accessible to individuals with diverse levels of experience, including students and researchers of varying programming backgrounds.

Viscous Thread Printing (VTP) is a novel manufacturing technique that allows foam production using traditional Fused Deposition Modeling (FDM) printers. This printing technique takes advantage of an everyday phenomenon called Viscous Thread Instability (VTI), which can be observed when honey is drizzled onto pancakes. Similarly, molten filament buckles onto itself and creates a coiling pattern when extruded from enough height. These coils create cellular structures that have shown potential improved durability and expanded applications such as in medical scaffoldings. However, as a relatively new technique, VTP has been limited to producing single-stiffness (uniform density) foams in previous works, and it remained unproven whether we can produce VTP foams containing multiple densities. Drawing inspiration from biological structures with variable porosity such as bones and balsa woods, we hypothesized that we could create multi-density VTP foams by manipulating predominant VTP parameters that affected the size of the coils. This way, we can vary the pore sizes, and thus the density and stiffness, of a single cellular structure while preserving high structural integrity. Such structures would have many applications such as in robotics and prosthetics, such as customizable orthotics and limbs for soft robots. Beyond enabling this technique, we further investigate a novel methodology to simulate the printing process of variable density VTP foams and measure the foam's material properties. This allows for an easier and more sustainable exploration of the design of VTP foams without wasting any filament, which would make VTP foams more accessible in industry and research settings.

In an ideal world, the electrical grid could fully decarbonize with just solar and wind as forms of energy generation. However, more traditional and firm forms of generation, such as natural gas or nuclear power, support the stability of the electric grid and lower the cost of transition to a net-zero carbon grid. To properly integrate emerging technologies, such as carbon capture and sequestration (CCS), as sources of firm generation, there needs to be an understanding of their economic behavior, and larger impact on other forms of electrical generation. CCS is of interest because the natural gas industry supplies the cheapest electricity and plays a major role in planning the energy transition. This project seeks to understand the economic viability of CCS to inform policy encouraging the deployment of emerging electricity resources. How do the investment costs associated with CCS need to change to result in significant buildout of natural gas plants with CCS? How does the increase of CCS buildout impact other forms of generation within a given system, and contribute to the overarching goal of creating a sustainable energy future? Using the MIT Energy Initiative's capacity-expansion model GenX, the investment costs associated with adding new natural gas plants with CCS and with retrofitting existing plants with CCS are varied in a sweep and the impact on the amount of added capacity of CCS and other forms of generation is analyzed. It has been found that an 80% reduction of the investment costs associated with CCS begins to promote the buildout of new CCS plants. Further investigation on the impact to other power sources, particularly battery storage, will provide insight into the impact of expanding CCS capacity on the rest of the system, with the anticipated result that increasing CCS buildout discourages the buildout of already established power sources.
 

Polycystic Ovary Syndrome (PCOS) is the most prevalent reproductive condition in pre-menopausal women, impacting around 5-10% of women in the U.S., despite being underdiagnosed. Previous research has linked a higher free androgen index with cardiovascular risk factors in women with various forms of ovarian dysfunction. Given that elevated androgen levels are a criterion for PCOS diagnosis, understanding the potential association between total testosterone and cardiometabolic risk factors in women with PCOS, specifically, is crucial. This cross-sectional study investigates the relationship between total testosterone levels and cardiometabolic risk factors among women diagnosed with PCOS. Limited research exists on endocrine and cardiometabolic health in PCOS patients, prompting our inquiry. Data for this study was extracted from women with PCOS who attended the University of Washington Endocrinology Clinical and Diabetes Institute. Blood samples underwent analysis for biomarkers including total testosterone, glucose metabolism, and lipid levels. Linear models, both adjusted and unadjusted, were applied to assess correlations between total testosterone levels and the aforementioned biomarkers. Insights into the impact of total testosterone on insulin resistance and lipid levels could offer better insights into how women with PCOS can better manage their health. Preliminary findings indicate a limited correlation between total testosterone and cardiometabolic risk factors, contradicting previous studies. Further analysis, including controlling for factors such as oral contraceptive use, will be done to bring greater clarity to these results. This study aims to bridge gaps in our understanding of the mechanisms by which PCOS can affect the health of women. It also seeks to address the underfunding and underrecognition of research in diseases that primarily affect women. Future research in this domain must be done to investigate biomolecular pathways on how testosterone could potentially affect cardiometabolic health.

The backsplash galaxies of the Milky Way are galaxies that have once entered the virial radius of the Milky Way but reside outside of which today. As a backsplash galaxy enters the Milky Way, its gravitational interaction with the Milky Way causes its star forming material to be stripped away and causes it to appear to be more diffused and older. The evolution and properties of a backsplash galaxy depend significantly on the properties of its dark matter halo as it makes up the majority of its mass. In my research, I use cosmological simulations of Cold Dark Matter (CDM) and Self-Interacting Dark Matter (SIDM) of Near-Milky Way halos done by my mentors and their colleagues to identify and analyze the properties of backsplash halos during their evolution and compare the results across the two dark matter models. Significant differences between the results from the CDM and the SIDM models are anticipated, with the major difference caused by the interactions between the SIDM particles allowing the exchange of energy and momentum between particles, causing the energy to transfer between regions of the halo, resulting in altered density profiles which influences the tidal evolution history. After the analysis of both models are completed, the results can be compared and matched to observational data of the candidates of backsplash galaxies of the Milky Way, and conclude in each model’s ability to make accurate predictions. This research contributes to the ongoing investigation of the properties of dark matter particles and the analysis of the evolution of backsplash galaxies.