This research is being conducted through the Svoboda Diaries Project (SDP), a digital humanities effort within the University of Washington based on the diaries of a British steamship worker during 19th-century Ottoman Iraq. This study aims to assess how students from varying academic backgrounds think and learn on a conceptual level and analyze how this influences their interactions with a digital humanities resource. We are conducting this research in hopes of improving the SDP website and contributing to generalizable knowledge regarding facilitated learning with digital tools. We are performing an interview study that employs two main methods used in usability testing: concept mapping and the think-aloud protocol. Concept maps are defined as graphical representations of one’s conceptual understanding of a topic, and the information falling within that topic. The think-aloud protocol is a research method involving participant’s verbalizing their thought process concurrently with the tasks being performed. During the interview, participants will create their own concept maps of their area of study, followed by a usability test on the image gallery feature of the SDP website, and lastly a second concept map activity where participants will map out the image gallery itself. The interviews will be analyzed using qualitative data analysis methods, and concept maps will be scored both qualitatively and quantitatively. By examining students from diverse academic backgrounds, we can analyze how they interact differently with our digital humanities resource, apply it to their field, and characterize how they think conceptually about topics. This research will contribute to the Svoboda Diaries Project by enabling us to make quality improvements to our website and gain insights to enhance our efforts within the digital humanities domain. Findings from the study may also be valuable when thinking critically about how students think about and interact with digital humanities resources as a whole.

Chronic pain affects 30% of children and adolescents, putting them at risk for physical and psychological impairments. Given poor access to pediatric pain care, psychological treatments such as cognitive behavioral therapy are more accessible through digital health interventions. One intervention our lab created is Web-based Management of Adolescent Pain (WebMAP). In this mobile app, youth with chronic pain develop pain management strategies by progressing through interactive modules. Although digital health interventions like WebMAP are transforming accessibility to chronic pain care, limited information is available to understand how best to enhance youth engagement in a mobile app or whether there are differences in engagement among youth with different background characteristics. Our project aimed to 1) identify barriers to engagement with WebMAP among subgroups defined by user demographics and 2) develop recommendations for enhancing engagement with WebMAP and extending its reach to target underserved populations. In a previous cluster randomized controlled trial, participants assigned to the WebMAP intervention were 73 youth aged 10 to 17 (84.3% female) with various chronic pain conditions. We analyzed the app metadata to assess module completion rates across various subgroups, including groups defined by age, race, sex, and annual household income. We also coded interview and questionnaire responses from users to identify app preferences and areas of improvement. Results indicated that although users liked WebMAP’s design and content, they suggested changes to its display and features. By viewing our findings on usage and perception through a health equity lens, we summarized the accessibility of WebMAP and outlined recommendations to enhance its cultural relevance to different groups. Ultimately, our research identified factors that impacted engagement with WebMAP and offered valuable insight into optimizing digital health psychological interventions for chronic pain management. Moving forward, we hope to apply these findings as we develop the next release of WebMAP.

Skin is a densely innervated sensory organ, populated with various somatosensory receptors that help us perceive touch stimuli. Frequent injuries to the skin cause axon damage and lead to axon degeneration. Degenerating axons leave behind debris that must be cleared before reinnervation can occur and sensation is restored. We use adult zebrafish as a model to study injury and innervation because they have homologous cells and structures to humans and have transparent skin, allowing for high-resolution microscopy. Previous experiments in our lab revealed that skin-resident immune cells known as Langerhans cells (LCs) use highly motile protrusions to engulf axonal debris in the zebrafish epidermis. How are these dynamic protrusions regulated at a molecular level? Calcium signaling regulates phagocytosis and cell motility in other cell types, but the role of calcium signaling in LCs is unstudied. Through scale pluck assays and fluorescent microscopy, I have established a model for monitoring calcium signaling in LCs. I observed transient calcium flashes in LCs that varied in frequency, intensity, and subcellular location. I perturbed calcium flux using a calcium chelator and observed decreased flash intensity and protrusion length in LCs, suggesting that calcium signaling is required for protrusion dynamics. To investigate how calcium signaling affects engulfment, I imaged calcium flux in LCs during phagocytosis of apoptotic cells after laser injury. In contrast to the transient flux normally observed, LCs exhibited sustained high concentrations of cellular calcium during corpse engulfment. Because of the effects of perturbed calcium flux on intracellular calcium and protrusion motility, I hypothesize that perturbing calcium concentrations will inhibit LC phagocytosis. Identifying the molecular mechanisms underlying debris removal, such as calcium signaling in LCs, is relevant to understanding skin repair and disease states in which axon homeostasis is altered, including diabetic and chemotherapy-induced peripheral neuropathies.

The leading causes of hearing and balance disorders are damage and loss of inner ear hair cells. Noise overexposure and aging can damage the fragile synaptic transmission between presynaptic hair cells (HC) and postsynaptic afferent neurons (AN), leading to “hidden” hearing loss. Hidden hearing loss is a condition where one can show normal auditory sensitivity when tested but still have difficulty in situations such as hearing one person in loud environments. Mitochondria might play an essential role in this connection by regulating transmission and energy supply. Mitochondria are known to adapt their morphologies to meet cellular demands. Studying mitochondrial morphology may reveal solutions to hearing preservation and contribute to our overall knowledge of the auditory system and general biology. Our lab has previously found that presynaptic hair cells harbor unique mitochondrial networks localized at the presynaptic HC release sites (ribbons) regulated by activity. However, the synapse requires postsynaptic neurons to function correctly to maintain healthy auditory transmission, so we examined the postsynaptic ANs. Preliminary data of two postsynaptic ANs revealed mitochondrial networks that extend between different HCs, but substantial evidence was lacking. Using the zebrafish lateral line as a model system, I microinjected fluorescent probes that tag AN mitochondria, Ca2+ uptake, and track depolarization via Channelrhodopsin. I used serial block-face scanning electron microscopy (SBFSEM) to reconstruct zebrafish AN and their mitochondria. SBFSEM cuts thin layers of the fluorescently tagged structures and images each layer to generate high-resolution 3D images. Probes successfully tracked the different functional characteristics. We observed distinctive architecture in postsynaptic mitochondria, confirming our preliminary findings. Further research will assess changes in postsynaptic mitochondria and regulation by synaptic activity. Understanding the connection between mitochondrial architecture at the synapse and its functional mechanisms will contribute to our knowledge of proper synaptic transmission and the pursuit of healthy hearing preservation.

 Autism Spectrum Disorder (ASD) is a neurodevelopmental disorder that often results in deficits in communication, social skills, and emotion regulation. Additional concerns include disruptions to the sleep wake cycle that results from circadian rhythm dysfunction. 40% of individuals with ASD also have clinically significant anxiety, which tends to exacerbate pre-existing behavioral issues and social deficits. Previous studies suggest an association between increased sleep dysfunction and increased issues with anxiety in typically developing (TD) adults, and have insinuated a possible bidirectional relationship between the two. This study aims to look at the relationship between sleep quality and anxiety in adults with and without ASD. 89 adults (ASD=39) from a longitudinal five-site NIH-funded study on sex differences in autism were included. Participants completed the Munich Chronotype Questionnaire (MCTQ), a measure of the amount of sleep, based on sleep-wake times, and the Screen for Adult/Child Anxiety Related Disorders for a measure of generalized anxiety. Analysis will include (1) independent sample t-tests to examine group differences in anxiety and sleep duration and (2) correlations between sleep duration (MCTQ) and generalized anxiety subscore from the SCAARED measure for the group with ASD and the typically developing group. I hypothesize that individuals with ASD compared to TD will demonstrate higher anxiety scores and worse sleep quality. I also hypothesize that there will be a correlation between higher anxiety scores and shorter sleep duration. Additionally we will explore sex differences in anxiety and sleep. If sleep quality is related to anxiety, this might support the increased use of sleep behavioral interventions to improve mental health in individuals with autism spectrum disorders.

The lateral hypothalamus (LHA) is an important brain region for motivated behaviors including feeding. The LHA contains GABAergic (inhibitory), Glutamatergic (excitatory), and other neuropeptide neuron populations. Previous research demonstrated that optogenetic stimulation of LHA GABA neurons increases food consumption while stimulation of glutamate neurons decreases food consumption, but both populations increase in activity during consumption. The caveats to these previous research experiments are that they do not isolate consummatory behaviors from appetitive behaviors, and they only focus on the role of neuronal stimulation on caloric consumption, not on non-caloric rewards or aversive tastants. In our experiments, we use a multi-spout head-fixed mouse behavioral system to isolate consumption from other behavioral variables, and measure consumption over a range of different concentrations of either rewarding or aversive taste solutions. Using fiber photometry, I recorded calcium dynamics from both neuronal cell types of interest simultaneously, and we found that GABA neuron activity scales with increased lick rate regardless of the solution, while glutamate neuron activity scales with aversive but not rewarding solutions. When I stimulate LHA GABA neurons during consumption using the red-shifted excitatory opsin, Chrimson, we see an increase in licking regardless of solution. Stimulation of LHA vglut2 neurons reduced licking regardless of solution. We also ran inhibition experiments using the red-shifted inhibitory opsin, JAWS, of the two populations and saw that GABA inhibition reduces consumption, while glutamate inhibition increases consumption. Our research has shown how both populations work to drive consummatory behaviors and how their activity level influences consumption. This research is important because it uncovered the function of LHA GABA and Glut neurons in bidirectionally mediating consummatory behaviors for both rewarding and aversive solutions and will contribute to understanding of health issues related to consumption such as obesity.

To test questions on the evolutionary history of a species, it is important to consider the drivers of genetic diversification that lead to speciation. Species diversification is often driven by the formation of geographical boundaries, ecological diversity, sexual preference, or a combination of these factors. However, for the Western Banded Gecko (Coleonyx variegatus), a species native to the southwestern region of the United States, few of these factors exist. Despite the lack of clear barriers to gene flow, prior research identified several distinct populations of C. variegatus in this region, though there is some uncertainty with these distinctions as they relied solely on the signal from one mitochondrial DNA (mtDNA) locus. The aim of this project is to instead use genomic data to assess the validity of the C. variegatus populations defined by mtDNA, and to investigate how these populations are distributed across the geographic region they inhabit. Using genomic data allows us to more confidently define population boundaries and assess how they have evolved through time. To explore the aim of this project, we sequenced reduced representation genomic data for 224 individuals across the range of the species to determine how populations of C. variegatus are structured. We then built species trees to assess the relatedness of these populations with respect to each other and the overall evolutionary history of the species. Our findings show that there are consistencies between both the genomic and mitochondrial data population definitions, but distinct differences are also present, with mtDNA overestimating the number of populations. Thus, relying on mtDNA data alone may be insufficient for confidently ascribing population boundaries for C. variegatus. Accurately defining populations can have great implications for the conservation of native biodiversity, but as shown by our study, relying on a single mtDNA locus may mislead this crucial process.

Chimeric antigen receptor T-cell (CART) and T-cell receptor (TCRT) therapy are immunotherapies developed by modifying immune cells to target cancer. Producing CART and TCRT cells involves transduction with viral vectors that usually contain the Woodchuck Hepatitis Virus Posttranscriptional Regulatory Element (WPRE). As adoptive cellular therapies become more widely used in cancer care, adverse events (AE) and safety monitoring questions have been raised. We developed a PCR assay to target WPRE for use on archival formalin-fixed, paraffin embedded (FFPE) tissues with the goal evaluating CART/TCRT localization in patient tissues which are taken for routine clinical care. We designed WPRE primers to generate short amplicon for use on FFPE tissues. Limit-of-detection experiments confirmed that our PCR protocol detects CART/TCRT constructs for an institutionally-manufactured CD19 CART, and HA-1, and MAGEA1 TCRT products. The limit-of-detection concentration for the CD19 CART was 1000 copies of WPRE DNA/10uL and MAGEA1 at 100 copies/10uL. In fresh samples, we detected CART DNA at 0.0001% dilution (CAR-T cells into PBMC), and TCRT DNA at 0.001%. For extracted FFPE DNA from cells, we detected WPRE in all four product samples of various CART/TCRT admixtures confirmed by in-situ hybridization. We have also detected WPRE sequences in the FFPE DNA of a pre-clinical humanized mouse sample with MAGEA1 TCRT and a clinical lymphoma sample containing CD19 CART. We are in the process of testing our assay on archival patient samples. Detecting CART/TCRT cells in FFPE samples using a WPRE PCR assay is a novel yet simple technique suitable for clinical application in understanding AEs of immunotherapy. In detecting CART and TCRT in FFPE, we are now able to study trafficking of these immune effector cells when AEs occur or when post-treatment biopsies are available.

From previous clinical cases, doctors found that children with Leigh syndrome are sensitive to volatile anesthetics. Leigh syndrome can be caused by defective Ndufs4, a subunit in complex I of the electron transportation chain. Previously, we used the Ndufs4 knockout C57Bl/6 mice to model Leigh syndrome and noticed that individuals with Ndufs4-knockout astrocytes go under anesthesia at a normal concentration, but require a lower concentration to emerge. We also found that isoflurane inhibits the effect of norepinephrine in astrocytes. Since norepinephrine is associated with individual emergence from an anesthetized state, this might help us to understand the mechanism behind our observations of the astrocyte specific Ndufs4 knockout. We furthered our study by assessing the role of gliotransmitters in the mechanism of mitochondrial disease and volatile anesthesia. Gliotransmitters are chemicals released by glial cells and used by astrocytes to modulate neuronal information processing. A pilot study was conducted in vitro in the wildtype mice assessing the release of different gliotransmitters, including cyclic adenosine monophosphate, adenosine, adenosine triphosphate, gamma-aminobutyric acid, serine, glutamine, and glutamic acid. Previously we found that the level of cAMP increased significantly after the norepinephrine treatment. Thus, we expect to see a larger acceleration in cAMP concenration in knockout mice, compared to wildtype. I am continuing this project studying the effect of the gliotransmitters in astrocyte cell cultures from the Ndufs4-knockout mice, to compare to the wildtype counterparts. Each astrocyte culture will be randomly assigned to a treatment: with or without norepinephrine. The amount of each gliotransmitter released per unit of protein is measured. I will analyze the data generated and compare to the wildtype data. Future study includes the assessment of the relationship between the metabolites within astrocytes, and the response to isoflurane and norepinephrine. This study would accelerate our understanding of the mechanism of volatile anesthesia, as well as the mitochondrial disease, which in turn will benefit numerous patients with safer and wiser treatment plans.

The functional connectivity of the brain evolves throughout the life of every individual. These changes, often referred to as neuroplasticity, can be impacted by a wide range of variables from diseases to eating a favorite dessert. How can these changes be modulated to treat neurological diseases and disorders such as post traumatic stress and major depressive disorder? My colleagues and I are intrigued with the prospects of neuromodulation as a therapeutic for abnormal brain connectivity and network dynamics, leading me to the question “At what rate do these connections accumulate and decay with optogenetic modulation; Optogenetics, a technique that uses light to activate or inhibit genetically targeted neurons, offers high cell-specificity and temporal resolution that allows us to zoom into the network dynamics and find more finely tuned results that can help in the development of neuromodulation therapies. I plan to use both single site and paired-pulse optogenetic inhibition to gain a clearer understanding of how functional connectivity behaves during and after repeated modulation periods followed by extended recordings of spontaneous activity with no modulation. By analyzing the pairwise coherence of the local field potentials collected using electrocorticographic recordings in non-human primates, I anticipate seeing targeted changes in functional connectivity when comparing before and after each inhibition session. By analyzing the rate of change in connectivity I plan to understand the timeline of neuroplasticity following optogenetic modulation, thus informing the development of future neuromodulation therapies. This research could have a profound impact on the future therapeutic paradigms for neurological and neuropsychiatric disorders that can accelerate recovery for individuals with these conditions.

Autism Spectrum Disorder (ASD) is a neurodevelopmental disorder that is characterized by difficulties in social communication skills, and repetitive restricted behaviors. ASD has been associated with alexithymia, or difficulties processing one’s and/or own emotions. Prior research suggests, individuals with alexithymia are at increased risk of developing disordered eating patterns, particularly if they are male (Shank, 2019; Larsen, 2006). Disordered eating tends to be associated with other psychopathology and possible to be comorbid with ASD. Individuals with ASD are also at increased risk of developing disordered eating (Huke, 2013), however it is unknown if the relationship between alexithymia and disordered eating is also found in autistic individuals. Thus, the aim of this study is to investigate sex differences in alexithymia and disordered eating patterns in individuals with and without ASD. 108 adults (ASD n=58, Male n=35) were included; all participants had an IQ ≥70. Alexithymia was measured using the Toronto Alexithymia Scale which is a 20-item instrument describing feelings, identifying feelings, and externally oriented thinking. Scores ≥61 indicate alexithymia . Eating behavior was measured using the Adult Behavior Eating Questionnaire which is a 35-item instrument involving 8 subscales including hunger, food responsiveness, emotional overeating, enjoyment of food, satiety responsiveness, emotional undereating, food fussiness, and slowness in eating. We expect to see a correlation between alexithymia and eating behavior in the autistic group, similar to what has been previously found in non-autistic groups. We also hypothesize that this correlation will be present for autistic males but not autistic females. This study will contribute to better understanding if alexithymia and eating behavior patterns are found in individuals with ASD, and whether or not sex mediates this relationship. If this relationship were true, this may affect how interventions for ASD are administered and label alexithymia as a risk factor for disordered eating.

Research suggests that recruitment, the number of fish entering a population in a given year, is influenced by the environment. However, environmental drivers are not currently used to refine the recruitment estimates of most statistical models used in fisheries management (hereafter, population assessment models). This is increasingly relevant as fish populations experience long-term productivity shifts due to climate change. One major goal of the National Oceanic and Atmospheric Administration (NOAA) in recent years has been to incorporate environmental drivers into population assessment models. This is achieved by using time series data of environmental drivers to inform model estimates. One ongoing challenge is determining which environmental drivers have potential to improve model estimates. In this project, we aimed to determine how correlated an environmental driver time series must be to historical recruitment deviations to improve key model estimates – recruitment deviations and population depletion – in recent years for a range of species. We used R to simulate mock environmental driver time series with varying correlation levels to recruitment deviations by randomly sampling data from a normal distribution. We then compared errors in estimates between population assessment models fit with and without the simulated environmental data. Our results suggest that the more correlated an environmental driver is to historical recruitment deviations, the more accurate estimates of both recruitment deviations and population depletion become. However, our results also reveal that the correlation level necessary for environmentally-driven models to consistently produce more accurate estimates than the original model varies across species. These correlation thresholds are also generally higher than observed correlations between recruitment deviations and environmental drivers in actual fish populations. We suggest fisheries scientists run similar simulation experiments to determine which correlation levels have the potential to improve population assessment models for their target species.

To navigate their surroundings, migratory cells respond constantly to many signals in their environment, including both chemical and electric cues. These signals are produced locally by other cells, pathogens, and in the context of electrical signals, by disruption to the normal ionic balance across cell boundaries. Disruption to this ionic balance will create a local electric field to which immune cells will respond to guide their movement and prevent infection. How cells sense or respond to this electrical cue is not known. To better understand this phenomenon, we are using HL-60 cells that are a migratory neutrophil-like human leukemia cell line, which we have found migrates to the cathodal pole of an applied DC electric field. We have identified a number of gene candidates related to glycosylation, the modification of proteins with the addition of sugar molecules, that reduce the directionality of HL-60 cells in an electric field. Using CRISPR interference to create cell lines with reduced expression (knockdown) for eleven of the gene candidates, we are studying how the loss of these genes alter migration. We used video microscopy to track their migration in 3D at different intensity levels of current to see how the loss of these genes affected cell movement when cells are exposed to an electric field. All of these knockdown lines showed marked change in the cell's response, with less persistence towards the cathode at higher currents than control HL-60 cells. Of these eleven, knockdown of UXS1, a gene that encodes for UDP-xylose that is used in the attachment of long sugar chains (glycosaminoglycans) to certain proteins on the cell surface, showed the greatest effect. Our results suggest that UXS1 is critical for neutrophils' ability to sense or respond to DC electric fields. 

Lck is a lymphocyte-specific tyrosine kinase involved in T cell activation, which is essential for the human immune response. Upon antigen engagement with the T Cell Receptor (TCR), Lck phosphorylates the CD3ζ chain of the TCR, transducing intercellular signaling that activates T cells. Recent studies have demonstrated that Lck’s phosphotransferase activity is not only important for T cell activation, but that Lck also plays a critical role in scaffolding the interaction between the phosphorylated CD3ζ chain of the TCR and the kinase ZAP70 using its regulatory domains. Lck’s phosphotransferase activity has been shown to be toxic to yeast, with increased activity correlating with decreased yeast-growth rates. Using a yeast growth-based deep mutational scan (DMS), we calculated the activity scores of ~5,000 single amino acid variants of Lck’s kinase domain. Through this DMS, we identified all positions on the kinase domain that are amenable to substitution without perturbing kinase activity. In particular, we focused on positions where we could install cysteine residues on the kinase domain without perturbing kinase activity. Currently, we are expressing these cysteine variants in primary T cells, and applying parallel chemoselective profiling methods to quantify changes in the electrophilic reactivity of the cysteine side chains upon TCR stimulation. The expected changes in alkylation of the cysteine side chains upon TCR stimulation will provide insight into changes in the conformational flexibility of Lck, accessibility of the substituted residue sites, and intramolecular protein-protein interactions (PPIs) of Lck upon TCR stimulation. Ultimately, this insight into the conformational dynamics of Lck can be applied to deepen our understanding of basic immunology and the T cell activation signaling cascade.

With respiratory diseases, namely COVID, becoming exceedingly present, new diagnostic techniques are important in delivering quick and accurate results to patients. With the broad aim of creating a COVID breath test diagnostic, the project focuses on building a classifier able to detect various volatile organic compounds (VOCs). I applied a panel of VOCs to the antennae of the moth Manduca sexta and recorded the change in voltage across the antenna over time, also known as an electroantennogram (EAG). After recording the voltage response it is essential to extract important features associated with the response to avoid overfitting in the classifier. Each odor will have a unique dose-response curve. By identifying the pattern of intensity-related response for each odor, I have extracted important information that can be useful in classifying EAGs. Going forward, this project will be scaled to include COVID-related VOCs and multichannel experiments to measure electrical response in multiple areas of the antenna simultaneously. Multi-channel recordings will provide an increased number of important features for the classifier to use in learning the unique voltage signature related to each odor in our panel.
Preliminary data has shown that the administration of floral odors to the antenna elicits unique voltage signatures when recorded in single-channel EAGs. I predict that if we record from two sites in the antenna, we will observe a set of unique dose-response curves relative to the differential expression of olfactory sensors in the base and the tip of the antenna. These sets of dose-response curves may provide our classifier with better parameters to categorize and detect the presence of odors associated with COVID, as two dose-response curves must be consistent with an assigned odor’s electrical signature instead of only one. This may improve our chances of creating a classifier able to reliably differentiate between COVID and non-COVID odors.

During DNA replication, the strain of the progressing replication fork induces DNA strands to wrap around each other, termed “positive supercoiling”, a significant obstacle to further replication. Type II Topoisomerases (Top2s) are essential and ubiquitous DNA replication enzymes that remove supercoiling to enable replication. However, we do not understand whether Top2s alone are sufficient to relax DNA for replication. We recently discovered that Growth-Associated Protein in Regulation (GapR), an essential DNA binding protein in alphaproteobacteria, binds positive supercoils and stimulates the activity of bacterial Top2s DNA Gyrase and Topoisomerase IV. Although GapR stimulates Top2s in vitro, we do not know the mechanism by which GapR stimulates Top2s. We hypothesize that GapR recruits Top2s to positive supercoils by direct interaction, and we investigated this mechanism by using a phage homolog that we discovered also stimulates Top2s and leveraged the conserved sequences to predict sites of Top2 interaction with GapR. We used the Bacterial Two-Hybrid assay to screen for GapR homolog interaction with Top2 subunits, and formed GapR truncations to interrogate for interaction with Top2s. We identified an interaction between GapR and the homologous Top2 subunits GyrA and ParC. Next, we aim to identify the surface that mediates direct interaction between GapR and Top2s, revealing a previously unknown mechanism of Top2 recruitment. We hypothesize that disrupting the GapR-Top2 interaction will lead to cell death, and as GapR is broadly conserved by alphaproteobacteria, our research could reveal a novel mechanism to inhibit with antibiotics. If a conserved mechanism, our work could identify new anticancer therapeutics, as human Top2 inhibitors are important chemotherapy drugs.

Peptide cancer vaccines have had limited clinical success despite their safety, characterization, and production advantages. We hypothesize that the poor immunogenicity of peptides can be surmounted by delivery vehicles that overcome the systemic and cellular drug delivery barriers faced by peptides. We introduce Man-VIPER, a self-assembling, pH-sensitive, mannosylated polymeric peptide delivery platform that targets dendritic cells in the lymph nodes and facilitates endosomal release of antigens through a conjugated membranolytic peptide melittin. We evaluated polymers with both releasable (Man-VIPER-R) or non-releasable (Man-VIPER-NR) D-melittin. Both Man-VIPER polymers exhibited superior endosomolysis and antigen cross-presentation compared to non-membranolytic D-melittin-free analogues (Man-AP) in vitro. In vivo, Man-VIPER polymers demonstrated an adjuvanting effect, induced the proliferation of antigen-specific cytotoxic T cells and helper T cells compared to free peptides and Man-AP. Remarkably, antigen delivery with Man-VIPER-NR generated significantly more antigen-specific cytotoxic T cells than Man-VIPER-R in vivo. As our candidate for a therapeutic vaccine, Man-VIPER-NR exerted superior efficacy in a B16F10-OVA tumor model. These results highlight Man-VIPER-NR as a safe and powerful peptide cancer vaccine platform for cancer immunotherapy.

The Stimulator of Interferon Genes (STING) pathway is a promising target for cancer immunotherapies. However, STING agonists have poor cell membrane permeability and also off-site toxicity that limit their therapeutic application. Our motivation is thus to develop a novel method for the delivery of non-cell membrane-permeable STING agonists. We propose incorporating the STING agonist in a self-assembling polymer, which then transports the drug into the cytosol, thereby avoiding membrane permeability issues. The first step is the incorporation of the STING agonist into Man-VIPER, a cytosolic drug delivery system developed by the Pun Lab. Man-VIPER mediates cytosolic delivery via endosomal escape, releasing the STING agonist cargo into the cytosol. Currently, I am working on synthesizing and purifying the small molecule STING agonist called SR-012. I tested many possible reaction pathways to make SR-012, which is unavailable commercially and has only been previously synthesized once. I developed a novel alternative reaction pathway and purification that works consistently. I am also currently synthesizing the polymer building blocks for the Man-VIPER copolymer that will deliver SR-012. After the optimized drug-polymer complex is completed, I will work with collaborators to quantify the max tolerated dose. We hope to demonstrate that specificity is improved through lower toxicity, allowing for a higher maximum tolerated dose than my control, the membrane permeable STING agonist SR-717. Next, I will assay the immunotherapeutic effectiveness of Man-VIPER delivered SR-012 using in-vivo tumor models.

Climate change continues to intensify the hazards we, and our civil infrastructure, experience. The 21st century has marked an increase in frequency and severity of flooding, hurricanes, wildfires, and extreme temperature events. Our new dynamic environment, with concurrent risks from multiple natural sources, needs engineering solutions to enable multi-hazard risk reduction efforts. This project investigates using polymers as an adaptable solution to simultaneously tune the behavior of reinforced concrete structures for multiple hazards. This differs from standard practice, where the response of a structure is determined based on a single load scenario. Polymers that exhibit strain-rate- and time-dependent properties are introduced to tailor the bond characteristics between the rebar and concrete in critical regions, producing improved overall structural performance when considering a multi-hazard environment. Through standard testing, polyurethane was chosen as the polymer based on compression and shear modulus results at different strain rates. To investigate the influence of polyurethane layer thickness, shape, and strength on the bond behavior between rebar, polyurethane, and concrete, cylindrical concrete specimens were tested under cyclic displacements at three different strain rates. The specimens were constructed by casting concrete between a central corrugated duct and a steel tube. Rebar was aligned along the central axis and polyurethane was cast between the steel duct and rebar. The testing data was used to determine the effective bond stress on the rebar as a function of material duct size and shape. The bond was shown to vary based on the geometry, induced strain rates, and strength of the polyurethane layer. This is markedly different than in current practice where the bond stress is assumed to be constant. The results of this project will help equip structures to adapt to multiple worsening climate change driven hazards, reducing the risk of building failure under extreme loading therefore improving community safety. 

Conjugative plasmids are extrachromosomal genetic elements commonly found in bacteria and are capable of being shuttled between different bacterial cells via a process called conjugation. The Luria-Delbruck Method (LDM) is a stochastic based modeling framework used to estimate the conjugation rate of a particular plasmid between bacterial strains. In my experiment, I am probing the theoretical experimental assumptions made by the LDM; in particular, I am testing that when there is variation in the precision of the selection assay, the application of a theoretical correction can result in accurate quantification of the conjugation rate. In the early phases of the experiment, I performed experimental assays in liquid medium to determine antibiotic concentrations in which donors (strains hosting a conjugative plasmid) and recipients (strains able to receive plasmids from donors via conjugation) die and transconjugants (recipient cells that have received plasmid from donor) grow. To test the theoretical correction, I chose two antibiotic concentrations that differ in the amounts of extinction occurring in the transconjugant population. I executed the LDM conjugation assay with these two conditions which produced equivalent conjugation rate estimates, as would be predicted if the correction factor is effective at mitigating the bias produced from variable amounts of transconjugant extinction in the selective conditions. My experiments demonstrate that the LDM continues to be robust in the face of violations to experimental assumptions which affirms the viability of applying the method to a wider range of bacterial populations with variable selective conditions and thereby broadens our ability to understand the dynamic movement of conjugative plasmids.

Arsenic toxicity is a major environmental problem, which causes various diseases including cardiovascular disorders. Several epidemiological studies indicated that arsenic causes cardiotoxicity, but the underling mechanisms remain unclear. The objective of this project is to determine the molecular mechanism of arsenic-induced cell death in cardiomyocytes. I hypothesize that arsenic trioxide induces ferroptosis, a unique form of iron-dependent cell death, in cardiomyocytes, which may serve as a novel therapeutic target for arsenic cardiomyopathy. Ferroptosis is a newly discovered form of cell death characterized by iron accumulation and lipid peroxidation, which is biochemically distinct from other cell death mechanisms such as apoptosis, necroptosis, and autophagy. I am examining whether arsenic trioxide induces ferroptosis in cardiomyocytes using propidium iodide/Annexin V assay along with ferroptosis inhibitors. I am measuring the levels of lipid peroxidation and cellular iron content in cardiomyocytes treated with arsenic trioxide. To understand the mechanism of arsenic trioxide-induced ferroptosis, I am assessing the cellular content of glutathione and the expression levels of glutathione peroxidase 4 (GPX4), a key suppressor of ferroptosis. Moreover, I am investigating the effect of arsenic trioxide on Bach1-heme oxygenase-1 (HO-1) signaling pathway, which regulates heme degradation and iron release. I expect that arsenic trioxide will induce ferroptosis in cardiomyocytes, associated with increased lipid peroxidation and labile iron levels. Expectations are that arsenic trioxide will induce glutathione depletion and GPX4 downregulation. Moreover, I predict that arsenic trioxide will activate the Bach1-HO-1 signaling to promote cytosolic iron accumulation. Together, this project investigates molecular mechanisms of arsenic-induced ferroptosis in cardiomyocytes, which may reveal a new disease mechanism for arsenic cardiomyopathy. Targeting ferroptosis represents a promising therapeutic strategy for arsenic cardiomyopathy and other complications associated with arsenic toxicity.

Circadian rhythms are adaptive biological processes that govern the synchronous timing of biological functions and behaviors with the daily light-dark cycle. These rhythms are crucial for the timed regulation of sleep-wake cycles, metabolism, and hormone release, as well as for maintaining harmonious physiological functioning within the body. Within the mammalian brain, a central pacemaker, the Suprachiasmatic Nucleus (SCN), governs the timing of these circadian rhythms. This area contains a subpopulation of neurons that express and release the neurotransmitter Vasoactive intestinal peptide (VIP). These neurons play a role in synchronizing activity across the entire SCN network. Thus, this project is aimed at better understanding how VIP-neurons change shape throughout the day. Preliminary research in the de la Iglesia lab suggests that these neurons change shape across the day, such that VIP neuron fibers-axons and dendrites- are more branched during the day than the night. These results were obtained through the use of mouse models expressing a red fluorescent protein in the VIP neurons (VIP-TdTomato). The mice were perfused at a range of timepoints, and the samples underwent a tissue clearing protocol so that the entire SCN can be captured in one image. Then the software QuPath was used to train a machine learning algorithm to aid in the identification of VIP neuron fibers based on fluorescence expression. However, the performance of the machine learning algorithm has not been validated. To address this issue, I compared the algorithm-generated segmentations with manual annotations from humans, finding agreement 75.3% of the time in terms of fiber location and 77.4% of the time regarding background. These rather promising results demonstrate the usefulness of the algorithm in aiding the investigation of the entire dataset. This research provides a step towards better understanding the structural organization of the SCN, and thus circadian control of essential physiological processes.

Mutations in β-myosin heavy chain (MHC) have been implicated in the manifestation of cardiomyopathies. One such iteration of disease, dilated cardiomyopathy (DCM), results in a progressive loss of muscle in the heart, causing a dilation of the chambers that makes it more difficult for the heart to pump blood and leads to progressive heart failure. Current methods of treating cardiomyopathies are ineffective and target secondary manifestations of heart disease rather than the mutagenic causes. Our aim is to better understand the pathogenesis of cardiomyopathies by studying a particular disease-associated mutation, R369Q, that resides on loop 4 of the β-MHC structure and is implicated in actin-myosin interaction. Here, I studied the molecular mechanistic effect of the R369Q mutation on β-MHC and its role in the DCM phenotype through in silico molecular dynamics experiments comparing the mutant myosin structure to the wild type. Particularly, I examined the flexibility of loop 4, coordination of the nucleotide binding pocket, and electrostatic interactions along the actin interface. We expect to see decreased electrostatic interactions along the actin interface as the loss of a positive charge in this mutant will reduce the affinity of myosin for the negatively charged actin. This work provides a strong foundational hypothesis for the atomic-level impact of the R369Q mutation on myosin dynamics and will be used to design a therapeutic small molecule as well as corroborate in vitro experiments testing the biochemical function of mutant myosin in human induced pluripotent stem cell-derived cardiomyocytes (hiPSC-CMs). Thus, computational and experimental approaches work in synergy in the comprehensive project, informing each other’s results to get a better picture of R369Q’s role in cardiomyopathies at a molecular level and forming a framework for future analyses of β-MHC mutations.

Cytokines are molecules that mediate cell-to-cell communication in the immune system. Their sensing by immune cells drives their response and differentiation into different functional states, such as into memory or effector states for T cells, to form a proper immune response and combat infections or cancer. Signal transducer and activator of transcription (STAT) family proteins are transcription factors that act downstream of cytokine signaling to regulate the expression of genes driving differential cell functions. Different cytokines phosphorylate and activate different STAT family members to give rise to distinct cellular responses and phenotypic changes. However, there is substantial overlap between STAT members activated by different cytokines. For instance, type I interferon (IFN-I) activates both STAT1 and STAT3 signaling to drive genes associated with growth inhibition, cell death, and anti-microbial responses. Alternatively, Interleukin-2 (IL-2) primarily activates STAT5, but can mediate STAT3, to promote T cell effector differentiation and proliferation. Thus, how different cytokines work through a small common set of STATs to elicit distinct functional phenotypes requires further investigation. Therefore, my project seeks to probe T cell responses and STAT activity with different cytokines. To interrogate this, I will develop an assay to stimulate Jurkat cells, an immortalized T cell line, under various cytokines and analyze STAT1, STAT3, and STAT5 phosphorylation with flow cytometry. We expect Jurkats under IFN-I stimulation to have higher STAT3 and STAT1 phosphorylation than STAT5, but exhibit a more immunosuppressive phenotype, as STAT3 is known to inhibit STAT1-mediated gene expression. With IL-2 stimulation, we expect cells to have higher STAT5 activity with increased proliferation and enhanced effector function. By understanding the complexities of how our T cells differentiate and exhibit certain phenotypes from STAT activity, we can potentially tune the signal a cell interprets and the downstream cellular responses to effectively enhance effector functions, or prevent cell death.

Current sociopolitical climates for LGBTQ+ individuals in South Asian countries are hostile, and South Asian communities within America will often reflect similar beliefs. Likewise, there might be an unfavorable atmosphere for LGBTQ+ individuals at faith-based institutions. As such, for South Asian college students enrolled in Christian institutions, their religious context and South Asian cultural practices and values might combine to shape their attitudes towards LGBTQ+ people. To explore this understudied topic, I utilized semi-structured interviews with South Asian students at a Christian institution. Thus far, I have interviewed four participants and intend to complete at least eight interviews to meet the qualitative analysis standard. Preliminary examination reveals our participants’ tendency to avoid conversations about the LGBTQ+ community, and they connected this tendency to South Asian culture. In contrast, they noted that LGBTQ+ topics were actively discussed on their Christian campus. Our study hopes to expand on the research surrounding intersectional identities and their impact on the individual.

Autism Spectrum Disorder (ASD) is a neurodevelopmental disorder characterized by social communicative impairments and sensory sensitivities. Additionally, the physical and social changes that occur with puberty may be a turbulent time for adolescents. Earlier pubertal timing has been correlated with higher internalizing mental health symptoms for neurotypical girls with earlier onset of menarche in females being tied with higher rates of depression that persists into adulthood. This study investigates the relation between pubertal timing and internalizing mental health problems for autistic and non-autistic female adolescents in a longitudinal study. 23 female ASD participants (ages 8 to 17) and 42 female neurotypical participants (ages 8 to 17) from a NIH-funded project investigating sex and gender differences in individuals with autism are included. Participant data was collected at a second timepoint, 3 to 8 years later. Data on pubertal development was collected using the Pubertal Development Scale, a parent or self-report measure of physical development. Depression and anxiety were assessed using the Child Behavior Check List, a parent-report behavioral checklist of mental health symptoms at the first time point, and a self-report version of the CBCL at the second time point. First, we examine pubertal timing variation by calculating residuals of a pubertal maturation by time regression plot. Second, we will investigate the relationship between puberty timing and depression and anxiety using a correlation test. To further analyze this relationship between pubertal timing predicting future depression and anxiety, we will run a multiple regression test. I predict that the relationship between pubertal timing and depression and anxiety will be greater for autistic girls than for neurotypical girls. This study’s data can add a neurodiverse perspective on how pubertal timing impacts mental health in females and could provide evidence for the need of interventions and additional support to adolescent females with ASD.

Recent studies suggest that errors facilitate learning in certain conditions. Despite this, reinforcement paradigms dominate learning methods, subscribing to the narrative that errorless learning is the foundation of an ideal learning environment. If we continue to view learning from this restrictive perspective, we may fail to capture and apply the benefits of errors. Furthermore, although error learning is now a well-documented phenomenon, research on its underlying mechanisms is sparse. Two prominent theories have arisen out of this research; the elaborative hypothesis, in which meaningful connections are derived from errors, and the mediator hypothesis, in which errors act as secondary cues. To go beyond speculation, both must be examined empirically to successfully leverage error learning. Using a combined approach, data from computational models formulated to reflect different mechanisms of error learning were compared to behavioral data. In the behavioral task, participants (N = 61) learned word pairs in either a study or error trial before taking a final test. Supporting past error learning literature, errors before a study opportunity led to better performance on a final test. Differences in reaction times between conditions support the theory that errors increase learning through mediation by acting as a secondary cue rather than as a way to establish a deeper network between the cue and answer. Furthermore, comparing behavioral results to computational cognitive models provided insight into individual differences in mechanisms of error learning.

Efforts to find disease-modifying treatments for Alzheimer’s disease (AD) have met with limited success in part because they have focused on identifying a specific pathogenic mechanism targeted by a specific drug. AD is a complex disease mechanistically associated with multiple pathways of aging so the probability of effectively targeting all of them would be greatly increased by using drugs in combination, each targeting different pathways. Previous studies have shown that a novel cocktail of the anti-aging FDA approved drugs rapamycin, acarbose and phenylbutyrate prevents age-related cognitive decline in mice by targeting distinct pathways of aging. These findings provided the rationale to test this drug cocktail for ability to alleviate cognitive impairment in a mouse model of AD. Transgenic 5xFAD male and female mice, with multiple mutant amyloid precursor proteins and expression of pathogenic Aβ42 peptide, were fed diet containing all 3 drugs, while control mice were fed a non-medicated diet. After 8 months of treatment, preliminary observations suggest 5xFAD mice fed the cocktail diet performed better in a spatial navigation learning task compared to mice fed the control diet. Laboratory procedures to confirm these observations will include rtPCR and immunohistochemistry to identify differences in expression of specific protein biomarkers of aging pathways in the brains of treated versus control mice. More work would be needed but observations from this study might be helpful in designing potential investigations to alleviate early phases of AD in patients using drugs already approved for human use.

Children with uncontrolled asthma are three to six times more likely to be hospitalized. It is necessary for parents and children to collaborate in order to help the child successfully manage their symptoms, yet few solutions exist to support this parent-child shared management. A novel mobile health application was designed and tested with 54 parent-child dyads in an eight-week pilot randomized controlled trial (RCT). The goal was to see if proper planning, communication and using an asthma monitoring watch would improve symptom monitoring in children with asthma. During this study, the watch detected the children’s asthma-related symptoms as they occurred. On a web application, both the parents and the children were asked to collaborate to enter reminders for medicine, summaries for any symptoms, etc. After 8 weeks, the parents and children completed semi-structured interviews where they reported any improvements in their asthma symptoms and general feedback regarding the app. We conducted qualitative analysis by writing codes based on the patterns observed in the user survey responses analyzed. Finally, we compiled our findings into a code book which serves as a guide for upcoming trials. The interview findings revealed that families found the intervention to be helpful for reducing asthma related flare-ups. However, the sync between the watch and the app, integration of the spirometer results with the app, and making the web application interface more kid-friendly are all recommended refinements to consider before the project is scaled for a larger clinical trial.

As diseases like COVID-19 become endemic, it becomes more apparent that access to low-cost, user-conducted tests with high sensitivity and rapid results are necessary to help reduce the spread of disease and mitigate burden on healthcare and laboratory infrastructure. While paper-based colorimetric tests attempt to fill this gap, they have reduced sensitivity when compared to “gold-standard” tests such as RT-qPCR, which typically exhibit results with fluorescent reporters. The goal of this project is to detect fluorophore activity using a smartphone camera and flash, with zero modifications (or as minimal as possible). As many people have smartphones and the ability to take a picture, but fewer possess lab skills or access to a lab, we aim to develop a smartphone-based system with the highest sensitivity and lowest barrier for entry, that is capable of detecting a fluorescent output. We are experimenting with both biological and technological levers, including combinations of time-delay using FRET and long-lasting fluorophores. On the software side, we are looking into whether we can leverage a smartphone’s built-in bayer filter to better delineate between emission wavelengths of fluorophores, and using timed flashing and recording methods to detect the biological time delay. So far, we have collected preliminary data on colorimetric readout reactions and shown that the difference between reactant and negative control is apparent at fairly low concentrations (250 uM). We expect that with a simple filter setup, we will be able to excite and detect the fluorescent output from a fluorophore. Further research will aim to simply things setup further, to reduce the number of external modifications required for use. When coupled with a diagnostic test, these ideas could potentially bring any test that can be coupled to a fluorescent readout from the lab to the user, increasing accessibility and lowering the costs of such tests.

The SirT6 gene is protective against systemic aging by enhancing DNA repair, decreasing inflammation and epigenetic deacetylation, and maintaining efficient lipid and glucose metabolism. Studies have shown that SirT6 function gradually decreases with increasing age with a loss in protective mechanisms. The role of SirT6 in brain aging has not been well established, and would be of interest to determine possible therapeutic targeting for conditions of age-related neurological dysfunction including cognitive impairment and dementia associated with Alzheimer’s disease. A mouse line was obtained from the NIH National Mouse Repository with genetic inactivation of one allele of the SirT6 gene (SirT6-/+) resulting in a partial loss of function. Older aged mice were tested in a spatial navigation learning task for exploratory behavior and memory. SirT6-/+ mice were unable to find escape holes as quickly as unaltered littermates (SirT6+/+) with a P-value of 0.003 significance. This observation suggests that partial absence of SirT6 function is associated with cognitive impairment. Following cognitive testing, mice were humanely euthanized, and brains collected and formalin fixed for immunohistochemistry staining to identify specific biomarkers of aging pathways including gamma H2AX for DNA damage response, HDAC-2 for epigenetic alterations, MCP-1 for inflammation, nitrotyrosine for oxidative stress, and p21 for senescence. Stains will be digitally imaged and heat maps generated for quantitative analysis of specific areas of brains from SirT6-/+ and SirT6+/+ mice. Results are expected to provide new knowledge on the role of aging pathways in the downregulation of SirT6 and age-related decline of learning and memory, and insight into possible conditions for development of more severe neurodegenerative diseases associated with dementia such as Alzheimer’s disease.

Kidney function declines with age and is accompanied by injury to the nephron glomerulus. A critical cell for filtration in the glomerulus are podocytes, which are lost with aging and non-proliferative. However, the parietal epithelial cells (PECs) lining the Bowman’s capsule of the nephron may migrate to the glomerular tuft to replace podocytes through differentiation. The mechanisms by which PECs differentiate into podocytes is still unknown. Using a mitochondrial intervention peptide, we previously showed reduction of glomerular injury and improved PEC numbers in aged mice. Mitochondrial dysfunction increases in all organs with aging; therefore, we hypothesized that mitochondrial aging dysfunction affects PEC-to-podocyte differentiation. To determine whether mitochondrial aging dysfunction plays a role in the differentiation of podocytes from PECs, we used young (18-30 yrs.) and old (50+ yrs.) primary human cells derived from kidney PECs isolated from urine. Human urine progenitor cells (hUPCs) were sorted for makers CD133+ and CD24+. For hUPC progenitor-to-podocyte differentiation, we used ‘VRADD’ medium (100 nm retinoic acid + 100 nm Vitamin D3). Proliferation and oxygen consumption rate (OCR) were measured during differentiation. To determine the differentiation of hUPC, we looked for the loss of progenitor makers CD133+ and CD24+ by qRT-PCR. In both aged and young cells, hUPC-podocyte VRAD differentiation resulted in a significant increase of OCR that peaked at day 2 relative to control. Both proliferation and OCR normalized to cell number were significantly lower in aged vs. young cells. Cells cultured with VRADD showed decreased progenitor markers CD24 and CD133 (PROM1) as compared to controls, suggesting hUPC differentiation. Our results support an aging decline in PEC-podocyte differentiation Future work will confirm whether podocyte fate was achieved with qRT-PCR and immunohistochemistry for expression podocyte specific genes/proteins WT1, SYNPO, NPHS1, and NPHS2 and additional assays to measure mitochondrial function of hUPCs across differentiation.

Alzheimer’s disease (AD) is a progressive neurological disorder associated with protein deposits in the brain, and causes a decline in memory, cognition, and social skills. There is no cure for AD, and as the disease advances, complications lead to incapacitation and death. Insulin-like growth factor 1 receptor (IGF1r) is a transmembrane receptor that responds to the hormone insulin-like growth factor 1, and is associated with healthy aging. An IGF1r variant in exon 6 (Arg-407-His) was found to be enriched in centenarians compared to shorter-lived relatives. Characterizing the role of this IGF1r variant in the development and progression of AD would provide information into a novel therapeutic target. Older-aged C57BL6 mice expressing a CRISPr-generated human Arg-407-His variant of the IGF1r gene were intravenously injected with a neurogenic AAV vector, consisting of the pathogenic components Aβ42 and p301L tau, or SHAM. After 3 months, mice with the IGF1r variant found escape holes more quickly than mice without the variant, using a spatial navigation learning task. Following humane euthanasia, brains were collected and fixed in formalin for immunohistochemistry (IHC). Brain sections were stained with biomarkers for Aêžµ42, ptau, and inflammatory microglia, and digitally imaged for quantitative analysis. Brains from IGF1r variant mice showed a decrease in expression of Aêžµ42 and ptau in line with improved cognition, and an increase in inflammatory glial cells. These preliminary observations help establish IGF1r Arg-407-His variant mice as a model to better understand the role of IGF1r in AD neuropathology, and provide insight into new potential therapeutic approaches for older human patients with AD.

Using simple behavioral analysis (SimBA) and Deep Lab Cut (DLC), we can create predictive behavior classifiers using pose estimation (PE) data obtained through DLC. PE is a computerized technique to track and predict the location of mice by training the video dataset with labeled frames using specific regions of interest (ROIs). With this, we can create machine-learning (ML) predictive classifiers of complex social behavior in SimBA. Social behaviors and interactions are difficult to manually track due to their rapid successions. To overcome this, I plan to use ML classification using our SimBA pipeline for behavioral classification allowing us to exceed human performance and increase throughput and consistency. I plan to create accurate classifiers for social behaviors that I will use to analyze the behavioral motifs of mice undergoing an operant social stress procedure. First, we train male and female C57BL/6J mice to self-administer (SA) their same sex cage mate. Experimental mice are then subjected to either physical stress for males or witness stress for females. Following social stress, non-reinforced SA is used to assess social reward seeking. Next, social interaction (SI) tests are performed to document time spent approaching the familiar same-sex conspecific cage mates and the aggressive CD-1 mice. All behavior was recorded, and transferred to DLC, followed by frame extraction. Using these frames, we trained the operant behavioral dataset to track the orientation of the mice. Next, we evaluate the dataset for a low error margin as observed by a continuous plateau of iteration loss. Although not complete, I expect to create behavioral classifiers for mice during social decision making in a social reward context following social stress inclusive of sex differences. Providing descriptive statistics of both movement and probability of successive behaviors as they occur in real-time.

Parent-teacher relationships are important in supporting young children’s social and emotional development. Especially in preschool, strong parent-teacher relationships can support a preschooler’s development across home and school. Despite the importance of parent-teacher relationships, parents from racial and ethnic minority backgrounds report having lower-quality relationships with their child’s preschool teacher. In this qualitative study, we sought to evaluate the voices of parents from racial and ethnic minority backgrounds, to understand barriers to and strategies for creating strong parent-teacher relationships. As part of a community-based partnership, we partnered with local preschools that serve a majority of underrepresented students. I assisted in conducting interviews with nine parents, in which three identified as Asian, one identified as Black/African American, three identified as white, and two identified as more than one race. During the interviews we asked parents questions about barriers at the individual, center, and systematic level that stand in the way of establishing close relationships with their child’s teacher, as well as potential solutions. My team is currently in the process of coding and analyzing all transcripts to explore barriers and solutions in more detail. Preliminary results reveal that parents brought up several barriers including time, limited face to face interaction, lack of communication, and feeling unwelcome in their child’s school. These barriers were described as impediments to the parent’s ability to form relationships with their child’s preschool teachers. We are currently analyzing and working with our community partners to identify solutions to improving parent-teacher relationships. The findings of this study are important in understanding how to support parents from racial and ethnic minority backgrounds in forming and maintaining strong relationships with their child’s preschool teacher.

Teaching robots to efficiently search for a target object (such as medication) in cluttered environments (such as a house) with limited prior information is a challenging yet important task, with applications ranging from home assistance to search and rescue. An ideal search policy, i.e. strategy, maximizes the accumulation of the target object while travelling along an efficient search route. We formulate object-search as a combinatorial-optimization problem known as the Stochastic Orienteering Problem (SOP), which is a graph traversal problem where an agent must identify and traverse a subset of nodes (such as furniture items, in our case) in a graph data-structure, with each edge associated with some cost and each node associated with some expected reward. The agent must choose a path that maximizes expected reward and keeps total travel cost under some prespecified bound, where the bound is informed by an unavoidable real-world constraint such as battery-usage. In our formulation, we call each node a "container", a catch-all term for any distinct area that can hold an object (such as a cabinet), and the edge costs represent the distances between each container. In this work, we mathematically show how this SOP can describe object-search tasks at a high-level, and present a simulated agent trained in a basic grid-world environment. We leverage the powerful reward-maximization capabilities of deep reinforcement-learning (a subfield of machine learning) to achieve near-optimal performance for solving this object-search SOP. The broader implication of this work is that real-world robotic object-search tasks are well-described by SOPs, since the multi-objective nature of SOPs forces the agent to choose search policies that both have a high-likelihood of finding the object(s) and do not exceed a hard constraint, such as energy expenditure.

Chimeric antigen receptor (CAR) T-cell therapy is a revolutionary cancer treatment that utilizes the body’s immune system to recognize and fight malignancies. It describes the process of extracting T cells from a patient and genetically engineering them ex vivo to express CARs that direct T cells to kill cancer cells. Multiple FDA-approved CAR T-cell products have shown promising clinical efficacy in treating cancers such as relapsed/refractory CD19+ B-cell leukemia and lymphoma. However, these products still have limitations in targeting other hematological and solid cancers. Solid tumors are difficult to treat due to their heterogeneity and ability to down-regulate or mutate antigen expression in response to treatment. Also, T-cell exhaustion and treatment associated toxicity result from the inability to precisely control CAR T-cell activity with these current treatments. Biological intermediates such as antibodies may be used to address these barriers, but they are expensive and can elicit an immune response. We aim to develop a universal CAR T-cell system that uses synthetic, high-affinity biomaterials to bind receptors expressed on cancer cells for targeted T-cell killing. For this project, we engineered CD8+ T cells, a cytotoxic subset of T cells, with lentivirus to extracellularly express universal CARs. Using flow cytometry, we confirmed strong expression of CARs on the T-cell surface and demonstrated their ability to interact with a synthetic cancer-targeting intermediate. Lastly, we show that CD8+ CAR T cells pre-armed with the targeting intermediate were capable of selectively lysing cancer cells in vitro that express the receptors of interest. For future studies, I hypothesize that we can expand this universal CAR system by utilizing other synthetic intermediates, such as a heterobifunctional small molecule peptide intermediate, for the treatment of solid tumors.

 Subduction zones are regions where two tectonic plates converge, and one is forced underneath the other. They are the primary driver of plate tectonics, and a source of major earthquakes. These earthquakes occur at shallow depths where plates slide past one another quickly, but at greater depths, with higher pressure and temperature (PT) conditions, rocks behave more ductilely. The transition zone between brittle and ductile regions hosts slow slip events (SSEs), which accommodate motion between the plates during events that last months to years, as opposed to the seconds over which earthquakes occur. SSEs are an important mechanism for accommodating plate motion at depth, thereby affecting the occurrence of larger devastating earthquakes, but currently the processes which facilitate SSEs and the rocks that host SSEs are not well understood. By studying rocks formed in and ancient subduction zone from Santa Catalina Island in California, we can learn more about our own modern counterparts, as the rocks record the conditions where slow slip may have occurred. Using optical petrography and data from x-ray spectroscopy, I examine thin sections of epidote-rich blueschist from SSE PT conditions. Optical petrography allows me to characterize the mineralogy of this rock, and the x-ray data provide the chemical compositions of individual minerals. Using image-analysis software, I will pair these two datasets to estimate the bulk-rock chemical composition of my sample. These data will allow me to constrain the starting material (protolith) of this rock before it was metamorphosed in order to determine if it was originally a sedimentary or basaltic component of the subducting oceanic plate. Doing so will improve our understanding of the way in which rocks at those pressure-temperature conditions deform and chemically change to create the context in which modern SSEs occur.

Building strong relationships between parents and teachers is critical to supporting young children in developing key social, emotional, and pre-academic skills. Especially in preschool, parent-teacher relationships can support a young child’s development across home and school. Communication is an important aspect of successful parent-teacher relationships; however parents and teachers face interpersonal, intrapersonal, and structural barriers to communicating with one another. This study aims to elevate the voices of racial and ethnic minoritized parents of a preschooler and preschool teachers to understand barriers to communicating and strategies to overcome these barriers. Using a qualitative approach, we conducted semi-structured interviews with 9 parents of a preschool child and 7 preschool teachers at two local early childhood centers. Using a codebook, I am currently analyzing all interviews to answer the following research questions: 1) What type of communication do parents and teachers want? 2) What barriers do parents and teachers face when communicating? and 3) What are some strategies for improving communication between parents and teachers? Preliminary results indicate that both parents and teachers desire open, honest communication. Parents expressed wanting daily communication related to how their child was doing in school. Teachers expressed a desire for parents to understand more about their kids and to be able to speak to parents when they have a concern about their child’s behavior. Despite a desire for communication, both parents and teachers describe feeling unsatisfied by their current level of communication, citing how COVID-19 has limited their ability to communicate. Some strategies discussed included increasing face-to-face contact, having more events at school, and creative ways for daily communication (e.g., interactive platform, daily notes, etc.). Through listening to parents and preschool teachers about their current experiences, we hope to identify ways to improve communication between parents and teachers, ultimately improving young children’s outcomes.

Dungeness crabs (Metacarcinus magister) are culturally and ecologically essential to Washington; they also constitute the most valuable state and tribal commercial fishery. Recently, there have been sharp declines in adult crab catch, resulting in the closure of the south Puget Sound fishery. Previous research by Alan Shanks has shown larval abundance is a clear driver of adult yield in Oregon, but many gaps in research remain regarding population dynamics in Washington, sustainability, and the impact of shifting environmental conditions. To address these gaps, the Pacific Northwest Crab Research Group (PCRG) was formed by the Swinomish Indian Tribal Community. PCRG is a collective of over 110 state and tribal co-managers, federal agencies, academics, commercial crabbers, and non-profit organizations. As part of PCRG, UWT’s Becker Lab deployed standardized light traps in the south Puget Sound from mid-April to September for two consecutive years, with sampling four days per week. In June 2021, the light trap network experienced a large pulse of Dungeness megalopae succeeding an extreme heat event. With the frequency of heat waves doubling over the last century, understanding temperature and other environmental stress responses in Dungeness crab larvae is imperative. Megalopae (n=55) from six PCRG sites were preserved in the field with 100% ethanol, then returned to the laboratory where I imaged them under a microscope and performed morphometric analysis (carapace width, carapace length, total length) in Image-J. I then compared measurements with recorded temperature, pH, dissolved oxygen, and salinity. Analysis is ongoing, but I expect to see an inverse relationship between environmental factors and Dungeness megalopae size. The aim of my work is to quantify larval growth as it relates to varying environmental conditions in order to better plan restoration and predict adult harvest limits. These data will offer valuable insight for restoration and protection of larval Dungeness crab.

Quantum computing presents a much different challenge than controlling a classical computer. The main difference lies between the methods of control of quantum bits (qubits) and classical bits. Unlike their classical counterparts, which have discrete states defined by voltages, qubits are defined by some quantum state and are not so easily manipulated. Nitrogen-vacancy (NV) centers are defects that occur in diamond that can be utilized as a two-level system, showing promise for a qubit platform. To use NV centers in this manner, microwave excitation must be applied to control their spin states. An external magnetic field is applied to the NV center to lift state degeneracy, allowing us to define a two-level system. Applying resonant microwave excitation causes oscillatory population transfer between the states defining that two-level system. To apply this excitation, we will construct an antenna that is capable of aligning a microwave field to the NV center. These antennas will be designed to maximize the Rabi frequency at lower input powers. To do so, we maximize microwave field strength and optimize power transmission through antenna geometry and impedance matching. Positioning of the antenna on the sample close to the NV center assures the high field strength excites it. We make use of field simulation software to model and simulate various antenna designs. Select designs are chosen for initial fabrication runs on copper, and are used to verify that simulated results align with physical testing. Once that is verified, we finalize designs for fabrication onto diamond via photolithography. We will physically test the antennas by characterizing them using a vector network analyzer. We expect to be able to fabricate and characterize a broadband gold antenna on a diamond sample that matches simulations, and use it to demonstrate spin manipulation through resonant excitation of an NV center.  

One challenge in developing point-of-care molecular diagnostics is achieving a high purity of the protein of interest. Immobilized metal affinity chromatography (IMAC) is a commonly utilized method to rapidly purify polyhistidine affinity tagged proteins. A barrier to accessing purification methods is the cost of materials such as columns manufactured by biotechnology companies at high cost. To address this issue, we have used an (RH)4-tag, a short peptide which consists of four consecutive arginine-histidine groups and can constitute an affinity fusion tag for IMAC due to the arginine interaction with the silica surface via an ion pairing mechanism. Further, the (RH)4 tag can reversibly bind with the silica surface, which allows for the elution of the fusion tag using L-lysine as the elution buffer. Therefore, the silica binding property of (RH)4 enables purification to occur without requiring high cost complex resins. To evaluate the efficiency of the purification process, we have chosen eGFP as the gene of interest of the fusion tag. The green fluorescence of eGFP can be utilized to quantify protein purification efficiency. We can conduct a chromatographic workflow using a column with a silica gel bead matrix, using purified samples of eGFP-RH4 diluted to different concentrations (from 10-100nM). The diluted protein samples are mixed with a silica particle suspension and incubated. The silica beads are removed by centrifugation at 5000xg, and the amount of each protein is derived from the difference between the initial fluorescence and the fluorescence of eGFP remaining in the supernatant. Preliminary results have shown the (RH)4 tag is functional when purifying eGFP on a silica based column and when purifying eGFP using IMAC. Further exploration includes finding an optimized buffer system and using developed methodology to purify different proteins of interest.

In this study, we explore the potential of using data from the DECam Deep Drilling program for asteroid science. The program, originally intended for supernovae and variable star science, produces valuable data that can be used to discover and analyze asteroids. Our focus is on the COSMOS fields, which are observed 5 times in each of the g, r, and i filters every 3 nights. We employ Heliolinc to match the data with known asteroids and discover 296 independent rediscoveries of known asteroids, as well as new discoveries that require further analysis. To analyze the known asteroids, we use forced photometry based on JPL ephemerides to measure their colors. Our results show that the average (g-r) color gets bluer and (r-i) gets redder with increasing distance from the sun. We use this information to develop a distance color metric that combines the colors to maximize sensitivity to distance. Additionally, for some of the best measured objects, we determine their rotation periods using Lomb-Scargle analysis. Our preliminary results demonstrate the potential of the DECam Deep Drilling program for asteroid science, particularly in analyzing asteroid colors and rotation periods.

Autism Spectrum Disorders (ASD) refer to neurodevelopmental difficulties in communication and social interaction. It is thought that 94% of autistic adults have used camouflaging behaviors at some point in their lives, meaning that they have developed certain behaviors to blend in the social world and to “hide” their autistic differences. Camouflaging behaviors include: masking - hiding the autistic features; compensation - practicing certain behaviors to compensate for certain social shortcomings; and assimilation - trying to fit in so they are not singled out (Hull et al., 2018). We are interested in the relationship between camouflaging behaviors and social communication in individuals with and without autism. Data from 85 participants (42 ASD, 48 females) ranging from 15 to 23 years old from the NIH funded study on sex and differences in autism were included in the analysis. Autism diagnosis was confirmed via standardized tests and all participants had an IQ of 70 or higher. Participants completed the Camouflaging Autistic Traits Questionnaire (CAT-Q), a 25-item questionnaire that tests the degree of using camouflaging strategies, and Vineland Adaptive Behavior Scales, a parental interview that informs the diagnosis of intellectual and developmental disabilities. We predict significantly higher camouflaging behaviors and lower socialization skills in the autistic group compared to the non-autistic group. We predict a positive correlation between CAT-Q scores and Vineland socialization scores in the autistic group, since by resembling their peers will make their parents report better social skills. We also predict that the correlation between masking and social skills will be higher in females than males in both groups, as females are found to have higher social motivations (Cook, Ogden, & Winstone, 2018). Camouflaging may prevent others from recognizing the symptoms of autism and fail to get diagnosis. Therefore, it is important to detect camouflaging behaviors so autistic children get timely treatments.

Maladaptive aggression characterizes - or is comorbid with - many neuropsychiatric illnesses, and can have devastating effects on individuals, their caretakers, and healthcare professionals. Human aggression is typically demarcated as exhibiting either reactive (defensive) or appetitive (rewarding) components. Despite a significant clinical awareness of the differences between these aggression presentations, preclinical characterization of their relative circuitry and associated neuronal mechanisms are absent. Using recently established protocols within our lab, we are able to study and compare these aggression phenotypes in outbred male mice in a high throughput manner. Briefly, for appetitive aggression, we train mice to self-administer a novel subordinate intruder over 7 days using a trial design. In the reactive condition, we non-contingently administered intruders with the same frequency distribution as the appetitive mice. In the current experiment, we used CD1xVgat-Cre or CD1xVglut1-Cre mice injected with pGP-AAV-syn-FLEX-jGCaMP7s in the lateral septum (LS) to examine cell-type specific activity via fiber photometry. GABAergic activity in the lateral septum has historically been implicated in the control of reactive aggression, but little is known about the role of excitatory activity in the LS in reactive or appetitive aggression. My roles in this project have included behavioral testing and filming of the mice, as well as scoring these videos for first attacks following intruder presentation. Using these timestamps, I will next analyze the changes in population level dynamics across different time points of aggression motivation, seeking, and consumption using the open source photometry analysis program guPPY. We expect that the photometry results for mice in reactive and appetitive environments will show different patterns of activity, with more glutamatergic activity in the appetitive group, and more GABAergic activity in the reactive groups. I hope to help understand and prevent unnecessary aggression through this research.

Changes within the body that repeat approximately every 24 hours, called circadian rhythms, are controlled by a central pacemaker in the mammalian brain, the suprachiasmatic nucleus (SCN). Circadian rhythms can synchronize to cues like the light-dark (LD) cycle, allowing them to predict the 24-hour environment. SCN neurons are interconnected and connect to other regions within the brain. Our hypothesis is that SCN neurons have the ability to physically change connections throughout the day and that these changes are essential for it to act as a master clock. I explored this plasticity through the study of vasoactive intestinal peptide (VIP) and polysialylated neural cell adhesion molecules (PSA-NCAM). VIP is a neurotransmitter expressed in a subset of SCN neurons and plays a role in the SCN's ability to respond to light. PSA-NCAM is involved in decreasing cell interactions through facilitating events like cell migration and axon guidance; it is only expressed in areas of the adult brain in which neurons display plasticity in their fiber connectivity. Mice house in a 12 hour:12 hour LD cycle were sacrificed at two times, 12 hours apart. I used immunohistochemistry against VIP and PSA-NCAM to determine the levels of these molecules in the SCN. I found that the expression of VIP is higher 9 hours after lights were turned off (ZT 21) compared to 9 hours after lights were turned on (ZT 9). I found that PSA-NCAM has a higher trend of expression levels at ZT 9 than ZT 21. Although these results are preliminary, we find the implication of the results promising. VIP and PSA-NCAM express in anti-phase; as a negative regulator of cell adhesion, higher levels of PSA-NCAM should correlate with lower levels of VIP. Understanding how mammals keep time is important because circadian rhythms are essential for virtually every aspect of an organism's behavior.

Despite the brain being a 3D structure with a complex topography and spatial relationships, neuroscientists currently rely on 2D visualizations. These less informative visualizations obscure the distances between 3D regions, and hinder scientists’ ability to perceive functional correlations and anatomical connections. To provide a more decipherable method of exploring the structure and function of the brain, we built neuroscience tools specifically aimed toward exploratory 3D data visualization. I worked on the development of a Universal Renderer for Neuroscience (Urchin) that lets users plot their data in its original 3D anatomical context. Urchin can perform a variety of different functions such as displaying certain features (e.g. neurons, brain regions, or contextual objects such as probes), or interactively exploring the data within context of brain location via mouse and keyboard navigation. This not only paves the way for new methods of data analysis but also creates a deeper understanding of the structure and patterns found within the data. I worked on building Urchin within the Unity platform, implementing features to enhance data exploration and analysis via scripting in C. Some examples of functionality that I built include implementing 3D mesh rendering for brain regions, primitive models, and changing materials. I also established a proxy server that allows for secure communication between client side browser applications and python notebooks. Along with this, I developed a more intuitive and efficient python API that allows people with minimal coding experience to run the renderer visualizations with ease. Urchin enhances neuroscience research and education by providing a more interactive and immersive experience, allowing students and the public to directly engage with diverse data sets and investigate different aspects and features of the brain.

Human history is marked by intergroup and interpersonal conflict. Over time we have begun to understand that humans, and other animal species, are imperfect decision-makers influenced by learned social biases. Specifically, we are interested in understanding in-group bias: the tendency to favor those of one’s own group over those in other groups. In order to investigate this behavior at the neural circuit and cellular level we developed a social behavior paradigm using male mice. Our paradigm utilizes the resident-intruder assay to determine which social behaviors the resident mouse (C57BL/6J male, n = 16) displays in response to a novel ‘in-group’ (C57BL/6J male) or ‘out-group’ (C57BL/6J albino male) intruder placed in their home cage. We focused on investigative and aggressive behaviors and found that a little over 50% of our resident male mice displayed an out-group aggression bias. This bias was eliminated after early life exposure to a C57BL/6J albino, supporting the hypothesis that this behavior is learned. To better understand the development of in-group bias, our future experiments aim to recapitulate out-group aggression bias without the use of a genetic variant by artificially creating groups with neutral odors. We plan to group-house half of the mice in neutral odor A and the other half in neutral odor B to fabricate an in-group and out-group, and determine whether this model produces out-group aggression bias. These insights will help us to interrogate the neurobiology of aggressive behavior and provide insight on out-group aggression and potential ways to reduce this bias.

During neonatal transport, specialized pediatric transport teams closely monitor the status of critically ill newborns. Hyperspectral imaging, a method of manipulating light, can be used to measure the vital signs along with video of the patient’s physical appearance for remote monitoring. Appropriate light intensity is critical for clear visibility of the newborn and hyperspectral imaging accuracy, but this must be balanced with safety for sensitive eyes. In June 2022, an experiment using light bars and a photometer was conducted at Seattle Children’s Hospital using a newborn manikin in a transport incubator to measure the amount of light needed to view the manikin and the potential light exposure to the eyes of the newborn. Eleven images depicting the visibility of the patient model in the incubator were taken in controlled amounts of light. Upon my work analyzing the experimental results, preliminary light testing in the range of light intensity (0.5 - 1400 Lux) showed that the amount of light that reached the patient’s eyes was significantly lower than the maximum intensity of the light source and did not increase linearly with the increasing light intensity. I found that visibility of the patient relied on the light level, increasing as the light measured increased. My research of optimizing light levels for visibility and safety will inform approaches to remote patient monitoring during neonatal transports. Next steps include: to determine minimum acceptable lighting conditions for patient visibility, to establish minimum lighting conditions for hyperspectral imaging, to compare the spectral properties of measured light with existing data from ophthalmology literature on the safety of the light for newborn eyes to regulate the safest amount of light required for visibility.

Biological age generally occurs earlier or later than chronological age and can be used as a biomarker for aging intervention studies. The rate of wound healing is known to decrease with increasing age, such that a simple skin wound might demonstrate overall aging of all organs and tissues of the body. This concept was tested in a mouse model of wound healing consisting of a 2 mm through and through ear biopsy. Cohorts of male and female C57BL/6 mice at 5, 13, and 21 months of age were biopsied, and the area of closure measured over 3 weeks. Ear biopsy cores were used to obtain DNA methylation signatures to a database of age-related signatures to compare biological age. The 5-month-old mice showed a higher percentage of wound healing than the 21-month-old mice 2.5 weeks following the biopsy with a p-value of 0.04. DNA methylation results used to calculate expected wound healing percentage correlated with measured healing percentage with an R2 value of 0.82. Additional validation of biological age will use a computational paradigm to assess severity of age-related lesions on an inter and intra-organ basis. Preliminary observations from this study indicate that a simple skin biopsy procedure can be used to predict biological age, with important translational implications for the treatment and prevention of aging and age-related diseases.

Electrophysiology experiments targeting deep brain structures require extensive training and expertise. However, even experienced researchers face challenges in placing electrodes precisely within a target location, particularly when using multiple electrodes simultaneously. On average, there is a 400-um (standard deviation) of human error when targeting Bregma and navigating to insertion coordinates. Slow setup time and human error can lead to unnecessary stress in experimental animals and prevent scientists from focusing on data collection. Our laboratory developed an experiment planning tool called Pinpoint to address these challenges. However, even with interactive tools, a typical two-probe experiment setup can take over an hour, increasing as more probes are added in complex experiments. To reduce time inefficiencies and lower the risk of human error, we developed an electrode manipulator automation platform for Pinpoint. Our platform consists of a server application called Ephys Link, which unifies communication between Pinpoint and various electrode manipulator platforms. With Ephys Link, scientists can view the electrodes they are using in their experiment live inside the virtual brain and pre-plan insertions for multiple probes. They can then simply press a button to have their probes automatically move to their chosen targets. We expect our automation pipeline to make multi-probe electrophysiology an easier and more accessible task for researchers, enabling them to focus on gathering high-quality data rather than managing the geometry of their experiments. To measure the impact of our automation platform, we plan to use positional logging, timed recordings, and researcher feedback to evaluate the efficacy of the pipeline in speeding up electrophysiology experiments. We expect to see increased targeting precision, reduced time setup time, and overall productivity boosts for researchers. By reducing electrophysiology's difficulty and time-consuming nature, our automation pipeline helps researchers alleviate cumbersome experiment setups and prevent unnecessary stress on experimental animals.

A major technical limitation in the study of complex social behavior of freely moving rodents is the manual annotation of behavior because it is subjective, extremely time-intensive, and prone to observer drift. Simple Behavioral Analysis (SimBA) utilizes machine learning (ML) applications to automate behavioral analysis by using pose estimation to create supervised ML predictive classifiers of rodent social behavior. In a single project, thousands of videos need to be preprocessed, which includes locating individual trials, identifying behavioral events within each trial, and choosing trimming points to focus on specific outcomes or the presence of multiple animals. Manual editing amounts to thousands of hours, often yielding clips with inaccuracies in timing or content, and leads to inaccurate ML predictive classifiers. To address this problem, my research is centered around integrating behavioral metadata into a tool that can automate preprocessing steps with high precision to improve the quality of resulting classifiers. I attempt this via two major improvements. First, to eliminate the reliance on manual record-keeping, I will implement a function that utilizes metadata to link relevant time-stamped events to their corresponding behavioral experiment video. Second, I will leverage ML-based object detection, such as YOLO4, to determine time points when two animals are present, which often indicates that a social reward has been obtained. Through this project, when compared to manual scoring, I expect that: (1) there will be a significant cut in the time necessary to preprocess videos, (2) the yield of usable trials for SimBA will increase, and (3) that there will be an improved accuracy of pose estimation and classifier performance. Overall, these additions will greatly enhance the ease and flexibility of data preparation for highly specific behavioral analyses during the task, enhancing the efficiency of ML procedures to yield powerful behavioral classifiers.
 

Alzheimer’s disease (AD) is a complex neurodegenerative condition that commonly affects aged populations; therefore, increasing resilience to aging may increase resilience to age-related diseases including AD. To test this concept, a preclinical mouse study was designed to investigate the effects of anti-aging drugs rapamycin, acarbose, and phenylbutyrate in combination (cocktail) previously shown to delay aging phenotypes in mice. Cohorts of C57BL/6 mice, 22 months of age and of both sexes, were fed standard chow containing the drug cocktail or standard control chow for two months. Mice were then given an intravenous injection of a neuronal-specific adeno-associated virus (AAV) vector consisting of Aβ and phosphorylated (p) tau, the major pathogenic components of AD, or AAV sham, and followed for another three months. Mice were then tested for cognitive function using a spatial navigation learning task. Overall, AD mice treated with the drug cocktail showed faster learning times, specifically in trial 2 for females (p<0.05) and trial 3 for males (p<0.05), compared to AD mice not receiving the drug cocktail. Following humane euthanasia, brain tissues will be assessed for Aβ and ptau neuropathology and pathways of aging using a combination of special stains and digital imaging to determine the cellular and molecular effects of the drug cocktail. The preliminary observation that the drug cocktail can prevent cognitive impairment associated with the early stages of AD suggests that targeting resilience to aging has potential translational implications for the early diagnosis and treatment of AD in human patients. Future efforts will work to establish molecular evidence of these observations and validate results in additional models of AD.

The COVID-19 pandemic has changed prioritization and delivery of public health and health care services. Community health workers (CHWs) are an integral part of the healthcare workforce since they connect the most marginalized communities to health and social services. Although there are currently 11 published reviews about CHWs during the COVID-19 pandemic, none focus on the U.S. In this study, we set out to systematically review the literature on CHWs in the U.S. during the COVID-19 pandemic. Specifically, we aim to describe the: 1) roles and responsibilities of CHWs during COVID-19; and 2) organizational settings of CHW integration. We followed systematic review guidelines and focused our search within two major health sciences databases. Included articles were published in English between January 2020-December 2022 and described U.S.-based CHW programs taking place during COVID-19. The initial search retrieved n=322 articles. After removal of duplicates, abstract and title screening, and full text screening by two reviewers, n=26 articles remained. Of the 26 articles, 13 (50%) described CHWs activities to address COVID-19 (e.g., contract-tracing, vaccination) while 15 articles (57.7%) described CHW activities to address non-COVID health conditions (e.g., food security, diabetes). A total of 22 articles (84.6%) described CHW activities to meet individual-level health and social needs of clients (e.g., language translation, patient outreach) while 12 articles (46.2%) described CHW activities to address structural barriers (e.g., advocating for policy change around COVID-19 data equity, increasing healthy food options in underserved neighborhoods). Articles described CHW work across multiple settings including communities (n=18, 69.2%), clinical (n=9, 34.6%), and research (n=8, 30.8%). This study highlights the scope of CHW activities during the COVID-19 pandemic in the U.S. This is important to generate best practices for CHW-led care coordination and structural advocacy post-pandemic to facilitate the health of individuals and populations within U.S. contexts.

Organic mixed ionic electronic conductors (OMIECs) are a class of semiconducting compounds that have recently sparked major interest due to their unique ability to conduct both ions and electrons when electrochemically doped. This unique property of OMIECs make them great contenders for applications in biosensing and neuromorphic computing, since they are soft organic materials that can change their state of conductivity. The rate at which these polymers can undergo redox reactions is known as the polymer’s doping kinetics, which is an important parameter for understanding these materials. In this work, I measured the doping kinetics of the commercially available polymer, poly(3-hexylthiophene-2,5-diyl) (P3HT), using UV-Vis spectroelectrochemistry to measure the electrochemical oxidation rate in solutions of different anionic species and solution concentrations, as well as varying the film thickness. I predicted that anionic species of larger sizes, at higher concentrations, results in faster doping kinetics of P3HT. I also expect to see faster doping in thinner films of P3HT, when compared to thicker films. My results show that the choice and concentration of the electrolyte plays a large part on the kinetics of electrochemical doping. I showed that using electrolytes that have larger anions were able to generate a faster doping kinetics. Increasing the electrolyte concentrations also increased the kinetics of doping the polymer. I also found that the thickness of the polymer film, when decreased, resulted in a faster doping kinetics. Using P3HT as a model system, I have examined the effects of anion, electrolyte concentration, and polymer film thickness, which are important parameters to understanding the factors that go into making these materials good conductors for a range of applications.

The use of computational models of memory has been effective in adaptive learning environments and in determining the memory capabilities of learners. However, these models have not been widely applied in clinical settings. Evaluation of memory loss still heavily relies on extensive neuropsychological testing performed by neurologists or psychiatrists, especially in the context of progressive neurodegenerative disorders. Current evaluation tools lack the necessary reliability, convenience, and repeatability to effectively capture key dynamics of memory decline, including the unique and changing nature of memory over time. The goal of this study was to predict and monitor memory decline in individuals diagnosed with Mild Cognitive Impairment (MCI) using a model-based adaptive fact learning system. Participants, aged 58 to 78 years, were divided into two groups based on their cognitive classification and completed weekly online learning assessments at home, tracking their individual speed of forgetting (SoF) across various study materials. The results showed that this method was effective in accurately diagnosing mild memory impairment, with a success rate of over 80% after a single 8-minute learning session. The study also demonstrated the model’s ability to distinguish MCI subtypes through computations of participants' SoF. These findings offer novel insights into the progressive nature of memory decline and could have implications for early detection and management of Alzheimer’s disease as well as other forms of dementia and cognitive impairment. Further development of this method could serve as an alternative or complement to established diagnostic procedures and be used in clinical settings.

Sickle cell disease (SCD), the most common genetic blood disease in North America, is characterized by recurrent episodes of acute severe pain due to blockages of red blood cells. In past studies, digital cognitive-behavioral interventions have been shown to be beneficial in other chronic pain conditions through teaching pain-management skills. Our research investigates the effectiveness of iCanCope SCD (iCC-SCD), a web and mobile-based pain-management program for SCD pain in youth ages 12-18 years. The final enrolled sample for the study was 137 participants, of which 26 participants were excluded because they did not complete pre-treatment assessments. Thus, the final sample consisted of 111 adolescents (107 caregivers), 54 randomized to Education control, and 57 randomized to iCC-SCD. The iCC-SCD program includes modules teaching coping strategies, symptom and goal-tracking, and peer-based social support, while the attentional-control contains static education about SCD. The efficacy of the program is determined through self-report scales at pre-treatment, post-treatment (2 months), and follow-up (6-months) periods, targeting the primary outcomes of adaptive coding, pain reduction, and pain-related disability. A statistically significant effect of treatment group (iCC-SCD vs. Education) on change over time in average pain intensity from baseline to 6-month follow-up was found. While most youth engaged with the program (40/57, 70%), the overall usage was highly variable. Therefore, I will explore the differences between participant website and app engagement from this study, feedback on why participants may or may not have been able to complete the iCanCope program and determine areas to enhance engagement. The information collected in this analysis can help to improve web- and mobile-based interventions for not only youth coping with SCD pain but also those with other pain-related conditions, given the flexibility and universality of cognitive-behavioral frameworks.

While there is much political science research focusing on Special Interest Groups (SIGs) and how they affect decision making on federal policy there is limited research focusing on municipal policy. Local interest groups play an important role in decision making in city council meetings as they lobby, provide public comment, and help craft legislation. This research aims to study how local SIGs are referenced during city council meetings and to measure and understand the impact they have on decision making and public policies. To do so, we are using Natural Language Processing (NLP) techniques, including training our own span categorization model, to process a dataset of city council meeting transcripts to enable the extraction of specific references to local interest groups from the text transcript of the meeting.. We then tie the detected references of SIGs to legislative outcomes in order to measure the impact that special interest groups have on the local municipal process.My contributions to the research include: experimenting with various Named Entity Recognition (NER) models to identify SIG references, annotating meeting transcripts, and conducting analysis to answer specific research questions. The preliminary result indicates that the NLP approach to this problem is accomplishable, but we will need a customized Span Categorization model to improve the accuracy for SIG identification. This research will have significant implications for local policymakers, researchers, and the general public, due to our improved understanding of how municipal public policy is created and who is involved in the process.

This research project seeks to understand the ways in which United States federal policies and racial capitalism shape the livelihoods of H2-A Visa holders in the U.S. and offer possible changes that could limit abuses of power. As immigration in the U.S. is rising after the pandemic, we are entering a time of increased foreign labor. With such increase, it is imperative that we understand how the ramifications of past legislation may impact our workers. Historically, foreign agricultural workers have faced countless injustices through exploitation due to power relations from racial capitalism. These workers are forced to commodify their bodies, sacrificing health to reach subsistence or retain legal status. Drawing on first and second hand accounts of foreign agricultural workers, we assess how these legislative policies affect their lives. With this research, we ask, how and why have workers on the H2-A Visa sponsorship been exploited? What system changes can be implemented to protect the rights of these workers? There is a gap in accessible documentation so, through creating a zine, we seek to provide this information to a wider audience. By including a policy memo, we offer possible changes that policy leaders, government organizations, and other actors could take to limit the amount of exploitation that these workers face; these include, a) offering a pathway to legal status or, b) growing visibility and awareness of the conditions. Preliminary results indicate that highlighting injustices through public demonstration can be helpful in limiting abuse, as seen in the success of the Familias Unidas por La Justicia Union, a Washington State example of how unionization serves as resistance to these oppressive forces. Our findings will spread awareness of exploitation within U.S. foreign labor, hopefully leading to safeguards against human rights abuses for workers or those wanting to obtain legal status.

Satellite missions generally require real-time knowledge of the satellite’s orientation in space. A star tracker, which operates by identifying constellations of stars in photographs, is generally the most accurate attitude determination system and therefore the preferred method. However, it is not uncommon for small satellite missions to have limited computing resources, such as radiation-hardened CPUs, as well as a limited budget. Commercial star trackers can handle these limitations, but most are prohibitively expensive and do not have public documentation of their software. Existing open-source star trackers exhibit good performance only in specific scenarios or require more powerful computing hardware. In order to reproducibly evaluate star tracking algorithms that are capable of running on low-compute satellite missions, and to provide reusable open-source implementations of these algorithms, we developed LOST: Open-source Star Tracker. We compare a suite of star tracking algorithms on performance metrics such as speed, accuracy, and memory usage, with a testing framework capable of generating realistic star images with various noise sources. Our evaluation determines which algorithms have the strongest performance under varying conditions such as motion blur, centroiding error, and number of false stars. In a scenario representative of a low-cost star tracker, the evaluation finds a set of algorithms that are able to identify over 95% of photos in less than 1 millisecond per image, with a peak memory usage of less than 1 MiB, backed by a database of less than 500 KiB. These results indicate that the algorithms implemented in LOST are suitable for running on embedded or radiation-hardened systems with very limited memory and compute power, while still achieving the high accuracy that is characteristic of star trackers.

With the human life expectancy doubling in only the last 100 years, science has opened us up to this new found idea of longevity and healthy aging. Congruently, people living with HIV have longer life expectancies and can expect to live as long as those who do not have HIV. Healthy aging strategies to navigate living with HIV have only recently developed. The purpose of this study is to explore the associations between physical activity and cardiorespiratory fitness (VO2 peak) in older adults living with HIV. We will conduct a secondary analysis of cross-sectional baseline data of older adults living with HIV, who are participating in the HEALTH randomized clinical trial (ClinicalTrials.gov NCT04550676). This secondary analysis focuses on data involving waist-worn actigraph GT3X/1 monitors, home based actigraphy, and graded exercise tests involving VO2 max that are collected from the ongoing HEALTH clinical trial. We will analyze VO2 max and accelerometry data at baseline between decades of people in their 50, 60, and 70s. This sample is approximately 50 older adults with HIV. We will use descriptive analysis, Pearson correlation coefficient, and Chi-squared test. VO2 max is a valid measure of cardiovascular fitness and aerobic endurance based on the maximal oxygen consumption of individuals during an exercise protocol. This project cultivates an awareness around healthy aging strategies and bio behavioral interventions with a population that has low cardiorespiratory fitness. Both cardiorespiratory fitness and physical activity have been poorly measured using self-report methods in older adults. This secondary analysis uses gold standard objective measures (VO2 Max) to show data points with relation to variability in exercise. This data empowers people living with HIV to engage in strategies to improve their physical function and suggests the need for more bio behavioral interventions to be defined in order to facilitate healthy aging.

Neopterin is a biomarker of non-specific inflammation that may result from infectious or chronic disease. Recent studies have observed declining neopterin from infancy through the juvenile period in non-human primates, as well as associations between higher neopterin levels and lower microbial diversity. These findings suggest that neopterin levels could vary with physiological and immune system development peaking during the time infants rely most heavily on innate defenses such as inflammation. We examined fecal neopterin levels in human infants over their first 16 months and in association with age at complementary feeding to further explore potential developmental patterns of neopterin expression. Samples were collected over 8 months from 35 Tsimane infants in lowland Bolivia. Families were visited every 3 weeks to collect infant stool samples and dietary and health information. Fecal samples were assayed for neopterin concentration at the University of California Santa Barbara Biodemography Laboratory in 2015, using commercial kits (Genway Biotech). Neopterin levels were preliminarily examined in separate linear regression models for infant age and feeding status. Results demonstrated that infant age (in months) was inversely associated with neopterin levels (Est. -16.22 ng/ml, p = 0.02). In the separate feeding status model, infants who had begun complementary feeding trended towards lower neopterin levels as compared to exclusively breastfeeding infants (Est. -119.52ng/ml, p = 0.65). Findings support previous observations of a decline in neopterin levels during infancy. Future work would benefit from longer observation and sample collection periods with more participants. This research has public health implications as it suggests there is age related variance in neopterin, a biomarker of gut inflammation, which should be considered in future studies investigating infant gut health and disease risk.

Every winter, those residing within the eastern half of the U.S. are slammed by powerful storms that pound cities with snow – costing millions of dollars in damage, halting travel, and impacting businesses and schools. Yet, like a thumbprint, each of these winter storms are unique and they can possess a range of tracks, structures, and intensities. This research project aims to provide a greater understanding of the development of such storms and the causes of precipitation variability within them by focusing on a single storm that hit the Midwest on 17 February 2022 as a part of a research flight conducted during the Investigation of Microphysics and Precipitation for Atlantic Coast-Threatening Snowstorms (IMPACTS). I analyzed data from multiple sources to explore the large scale environmental conditions and the fine scale precipitation structure. The environmental conditions included a strong thermal contrast, or a frontal boundary, that provided the lift needed for precipitation as well as sub-freezing surface temperatures that allowed for precipitation to fall as snow. Analysis of the vertical cloud and precipitation structure from radar data collected during the flight revealed regions of higher reflectivity where snow was heavier than in other portions of the storm. Microphysical properties, such as particle sizes, shapes, and ice water content were different within the region of high reflectivity than outside it. Additionally, the strengthening front at the 700-hPa pressure level coincided with the localized region of enhanced reflectivity observed by the ground-based and airborne radars. The high-resolution radar and microphysics data collected by the IMPACTS airborne instruments are used to help identify precipitation-defining processes within these storms, and ultimately will increase the accuracy of snow prediction and remote sensing of snowfall from space-borne instruments.

The Neuropixels (NP) probe is a multielectrode array that can record from large populations of neurons with high temporal and spatial resolution, along a shank spanning multiple brain regions. Identifying specific neural populations recorded along the shank is critical for later determining their structural connectivity, adding further insight into their behavioral function. Due to the shank’s material, fluorescent dyes cannot be used for this purpose as the dye will disperse broadly. To solve this, we will use silk fibroin, a biocompatible molecule derived from the cocoon of Bombyx mori to encapsulate a fluorescent protein-encoding viral vector in a silk film that degrades after a controllable period of time. Viral approaches allow for genetic isolation of specific cell-types and circuits. We will combine herpes simplex virus with the silk film and apply it to discrete sections along the shank before insertion, to induce expression of green fluorescent protein (HSV-GFP) in nearby recorded neurons for visualization. First we will test a range of fibroin/HSV-GFP solutions to optimize targeted expression for acute recording applications. Following optimization, we will test the silk/HSV-GFP solution while recording from the mouse amygdala. Then, we will image the brain to visualize the neural populations that were recorded. We predict that the chosen silk/HSV-GFP solution will yield high expression of HSV-GFP in a localized region of the brain that corresponds to the coated subsection of the probe. In future experiments, we will combine the optimal solution with anterograde and retrograde viral tracers along the probes, allowing us to dissect the connectivity patterns of recorded neuronal populations. These experiments will integrate structure and function to derive greater insight from neurophysiological experiments during behavior in mice.

Since 2013 there has been a decline in the harvest of Dungeness crab (Metacarcinus magister) in south Puget Sound. The Pacific Northwest Crab Research Group (PCRG) is a network that focuses on crab population monitoring. PCRG runs a large-scale larval trapping network that uses light traps to attract Dungeness crab megalopae via positive phototaxis. The light traps span the Salish Sea, to recognize migration patterns and better understand Dungeness crab population dynamics. In addition to Dungeness crabs, different crab species are caught in the traps, creating an opportunity to study more species. All crab larvae follow the same larval stages, called zoea and megalopa, which appear similar to the naked eye. This creates a problem because population counts are often done by volunteers who don’t have prior knowledge of megalopa morphology. Gathering reliable population data of the marine organisms caught in the traps requires a clear procedure to identify bycatch. In this research project, I will classify the unknown larvae into morphospecies by carefully looking and documenting individual characteristics of each organism. Documents will note features such as: carapace shape, carapace width, lateral edges of carapace, telson shape and additions (e.g. setae), number of spines, location of spines, antennae, length and width of thoracic legs, coloration, and overall shape. Measurements will be taken through Image-J, which will be documented along with photographs clearly differentiating anatomical characteristics to compare to DNA barcoding to be conducted by Seattle University on these samples. When DNA results come back, I will determine if specimens that had identical characteristics are genetically matched. This information will be used to make an accurate guide down to the species level. My results will be shared with PCRG to improve the accuracy of population counts of different crab species which will increase reliability of future PCRG data.

The widely accepted theory for how Earth’s moon formed begins with an impact to Earth by a Mars sized protoplanet. This impact creates a disk of debris around the Earth, and the moon is subsequently formed as the debris collides and coalesces. Previous studies have modeled the debris disk in a hydrodynamic environment, but results have found that moon formation is uncommon. This research project models the debris disk after it has cooled and condensed into a collection of solid particles using an N-Body simulation. These simulations are run using the ChaNGa code developed by the University of Washington’s N-Body shop and processed on the Hyak supercomputer. Simulations begin with an initial conditions file that we generate with different parameters, including particle resolution, angular momentum, and coefficient of restitution. From each initial conditions file the simulation runs time-progressions that model each particles position and velocity at every time-step, calculating the collective gravitational forces between all of the particles and recording any collisions that occurred. I analyze the data using plots detailing the eccentricity, mass, and semi-major axis of objects that form. Previous results from work I have completed on this project appear to show robust moon formation, with roughly lunar sized objects forming around the Roche limit. Future work on this project will include running more simulations with similar initial conditions to determine how common moon formation is, as well as analyzing the data using plots of semi-major axis vs. number of collisions/bodies accreted to determine if there are specific regions of the debris disk where the moons’ mass is originating from. While previous studies have found that a moon is only formed at very specific impact angles and sizes, this study looks to see if the moon formation mechanism may be more robust when modeled using N-Body simulations.

Current models of pain research involve restrictive forms of resident-intruder pairing where experimental mice are involuntarily placed in social situations. These methods have limited application as the research does not account for individual variability and the dynamic social decision-making characteristic of humans. Our research uses a novel volitional social procedure that more accurately represents human behavior in the context of pain. I conducted social self-administration protocols on C57 strain mus musculus to quantify changes in voluntary social interaction before and after neuropathic pain has been induced via spared nerve injury. In addition, I utilized a Von Frey filament test to measure changes in pain sensitivity over this time period. Two social self-administration (SA) experiments were conducted on separate cohorts of C57 mice. In Experiment I, SA was run intermittently at 3-day intervals following neuropathic injury, providing lapses between voluntary social engagement. In Experiment II, SA was run continuously following neuropathic injury. We found that the continuously run SA group experienced a rebound in social interaction to levels matching their pre-surgery states and sham controls, whereas the intermittent group displayed a stark decline in voluntary social interaction that reached statistical significance from sham controls on day 8. Interestingly, tests of allodynia that were conducted to determine prolonged mechanical sensitivity typical of chronic neuropathic pain showed that both groups were experiencing equal levels of increased pain sensitivity throughout behavioral testing. Our results show promise in revealing the dynamic connection between social interaction and pain perception. Research has already identified key areas of interest such as the medial prefrontal cortex (mPFC) and nucleus accumbens (NAc) as hubs responsible for regulating social behavior. We aim to further examine the physiological changes that occur in these areas as a result of persistent pain using a variety of sophisticated analytical techniques.

Mytilid mussels are foundation species who serve a vital role in temperate coastal ecosystems. As ecosystem engineers, mussels modify the physical and local chemical environment, which can both inhibit or facilitate other species. Through a mussel’s metabolic process (i.e., respiration and calcification) they have the ability to alter their chemical environment which has been suggested to be influenced by their gaping behavior. The objective of this project is to associate a given gape behavior to a known mussel behavior (e.g. active/passive filter feeding or laying byssal threads). We installed Hall effect sensors – a specialized magnetic sensor– on the posterior end of the mussels to analyze how wide a mussel gapes. A video camera filmed the mussels concurrently with the sensors to verify the gape signal with a known behavior. We recorded and captured mussel behavior for three Mytilus mussel species (M. trossulus, M. galloprovincialis and M. californianus) for 24 hours (n=8 for each species). We hypothesize that behaviors in mussels that are more active (e.g. active filtering or laying byssal threads) may have more variation in gaping behavior than behaviors like passive filtering where mussels could be resting. We also expect that gaping behavior will differ among the three species, with M. californianus spending less time closed compared to M. trossulus and M. galloprovincialis. Our project takes the first step in interpreting how valve gaping and its relationship with a given mussel behavior may determine how a mussel’s behavior plays a role in their ability to modify their local chemical environment.

Substance use disorder (SUD) can be defined as the misuse of pharmaceuticals, illegal drugs, and alcohol, and suggested to be due to the co-opting of existing pathways in the brain controlling natural reward. The endogenous opioid dynorphin (dyn), signaling via the kappa opioid receptor (KOR), has shown great promise in being targeted as an effective treatment strategy for SUDs. However, the role for dyn-KOR signaling in natural reward seeking and specifically, the location of its action in the brain are unknown; information that is critical in informing intervention times for treatment. The Dorsomedial Striatum (DMS) is an area of the brain where dynorphin is ample, and it’s crucial for reward-seeking behavior. However, what dyn is doing to influence these behaviors is unknown. To study natural reward-seeking, we set up an operant behavior task where the mice learn to nosepoke (seeking) into an “active” port for sucrose (reward), whereas nosepoking into an “inactive” port yields nothing. While wild-type mice learn this behavior, we observe that mice lacking DMS dyn are slower and do not seek as many rewards upon learning. This suggests that DMS dyn is necessary for reward-seeking behavior. To determine if the converse is true, we artificially boosted DMS dyn release using in vivo optogenetics. We show that when we stimulated dyn release during reward delivery, mice enhance their seeking behavior. Hence, we hypothesized that dyn may help shape the value of a reward, thereby impacting seeking. We designed a reward devaluation task, where animals are given free access to the reward prior to a session of reward-seeking, to decrease/devalue their seeking. We observe that wild-type animals decrease their responding, but animals lacking DMS dyn don’t devalue their seeking. Altogether, we reveal that dyn transmission in the DMS during reward shapes seeking, thereby enabling value-guided flexibility of reward-seeking behavior.

Chronic kidney disease (CKD) is an incurable, progressive condition that affects up to 700 million people globally. Progression of CKD currently leads to a deteriorating quality of life on dialysis, often resulting in terminal end-stage renal disease (ESRD) and increased risk of cardiovascular disease. A hallmark feature of CKD progression is epithelial-to-mesenchymal transition (EMT), a process by which kidney cells obtain malignant properties like increased mobility and resistance to apoptosis. Despite the pressing burden of CKD, current therapeutics like angiotensin-converting enzyme (ACE) inhibitors and angiotensin-receptor blockers are unable to halt the fibrotic progression of CKD. In recent years, epigallocatechin-3-gallate (EGCG) has been shown to be a promising candidate to inhibit EMT in kidney tubular epithelial cells (TECs). In this project, we conjugated EGCG to a low molecular weight polymer previously engineered at the Pun Lab for enhanced localization to the kidney TECs. In a TGF-β1 induced fibrosis model in human kidney cells, we showed that this polymer-EGCG conjugate (poly-EGCG) could diminish the RNA and protein expression of mesenchymal markers compared to untreated controls. We also confirmed that poly-EGCG was well-tolerated across a broad range of concentrations through in vitro cell viability assays. Finally, immunohistochemistry staining of mouse kidney samples injured with anti-glomerular antibodies displayed partial fibrotic recovery when treated with unconjugated EGCG. Future in vivo studies will aim to optimize the efficacy of poly-EGCG treatments compared to unconjugated EGCG treatments by assessing histology and urine samples for markers of kidney dysfunction. Through improved delivery of EGCG to the kidney TECs, this novel polymer-EGCG conjugate has the potential to halt the progression of EMT for future patients with CKD.

Single cell neural activity mapping is a novel experimental approach used to understand the relationship between neural activity and behavior/thought across the intact brain. The current approach utilizes immunodetection of Fos, a reliable and endogenous protein marker for neuronal activity that has unique induction and decay properties. This method combines whole-mount brain tissue clearing, IHC staining, and high speed volumetric imaging. However, whole-mount IHC is incredibly challenging due to many factors including variable antibody lots, lengthy processing protocols, and inconsistent timing. To overcome these limitations, various genetic methods including direct gene modification and replacement have been produced. However, these methods limit brain-wide expression profiles, display inaccurate signal to noise ratios, and yield low signal expression levels. Here, we have developed a novel activity-dependent tool that allows viral vector-compatible Fos-like reporting of neuronal activity. Our strategy relies upon non-promoter-based regulatory sequences that endows downstream genes with Fos-like induction profiles. Here, we present its effectiveness in ectopically labeling Fos+ cells in the mouse brain in-vivo, and report its comparison to other conventional genetic strategies. Further, we extend its range of use with the creation of multiple versions that enables a range of activity level reporting and through multiple wavelengths of fluorescence. In summary, this novel genetic tool can be used to ectopically map single cell neural activity more effectively in order to better understand the anatomical basis of neural coding driven by specific cell-types distributed across the entire brain.

Describing genetic variation in deep-sea organisms is key to understanding ecological and evolutionary processes shaping biological diversity in these fragile ecosystems that are vulnerable to anthropogenic activity. Among deep-sea species, tubeworms (Class Polychaeta) often dominate faunal biomass in hydrothermal vents where they tend to grow in towering colonies. As foundation species, tubeworms create structural habitats that support assemblages of diverse biological communities across the seafloor. However, heterogeneous environmental conditions throughout their range, such as pH and temperature, and geographic isolation, may cause population subdivision by restricting connectivity between sites. This study aims to further our understanding of tubeworm population structure by investigating genetic relationships between Ridgeia piscesae subpopulations within a deep-sea hydrothermal vent system. At the Axial Seamount, a regularly surveyed area in the study of hydrothermal vent processes on the Juan de Fuca Ridge, our knowledge of the genetic connectivity of R. piscesae subpopulations remains limited. Here, we examined genetic variation in R. piscesae individuals collected from structurally-different sites within the Axial Seamount. Specifically, we genotyped mitochondrial genes and constructed SNP-based phylogenetic trees to elucidate evolutionary relationships between worms inhabiting a chimney and diffuse-flow locations. Genetic differentiation is expected to be low when gene flow is high between populations, but these outcomes may also be influenced by other aspects, such as environmental conditions. These results allow us to evaluate the degree of genetic diversity in tubeworms within this important area and provide insight into the potential impact of human activities, such as seabed mining, on deep-sea vent dynamics.

Indoor air pollution is a major issue in urban homes, where hazardous volatile organic carcinogens (VOCs), including formaldehyde, can accumulate in the air. This study aims to investigate the potential of genetically modified Epipremnum aureum (pothos ivy) in reducing indoor air pollution by degrading formaldehyde into the non-harmful chemical formate. The study will use a flow-through bioreactor and spectrophotometer to measure the rate of formaldehyde degradation. Preliminary work includes creating standard curves of different formaldehyde concentrations and analyzing them using a spectrophotometer. Then, during the experiment, a stream of air containing formaldehyde concentrations typically found in homes will be exposed to three experimental groups: no plant, wild-type plant, and genetically modified plant. The genetically modified plants are engineered to express the enzyme formaldehyde dehydrogenase (FALDH) cloned from the bacterium Brevibacillus brevis, which oxidizes formaldehyde to formate. Any remaining formaldehyde will be collected in an effluent trap and derivatized with DNPH for analysis. Its amount will be measured using a spectrophotometer to determine the percentage of removal. The genetically modified pothos ivy is expected to exhibit a higher rate of formaldehyde degradation than the wild-type plant, owing to its FALDH enzyme. The results of this research aim to provide support for the use of plant-based strategies in combating indoor air pollution and improving human health.

One third of patients in America diagnosed with depression or anxiety are resistant to treatment, creating an urgent need to develop improved therapeutics. In such disorders, motivation to seek rewarding outcomes (‘approach’ behavior) is commonly reduced while apathy (‘avoid’ behavior) is often increased, suggesting that circuitry regulating approach-avoidance (Ap-Av) behaviors may become disrupted in these disorders. Previous research in our lab showed that neurons that release the endogenous neuropeptide nociceptin in the paranigral ventral tegmental area (pnVTA) become highly activated when a large amount of effort is required to obtain a reward, and that activation of these neurons drives avoidance behavior. To investigate pnVTA nociceptin circuitry in directing approach and avoidance behavior simultaneously, I am using NOPLight, a nociceptin biosensor, in an Ap-Av task to record nociceptin release in vivo during Ap-Av decision making in mice. The Ap-Av behavioral assay I am using utilizes a head-fixed apparatus with an aversive LED light positioned at the mouse’s eye level and a sucrose sipper positioned at their mouth. At variable time intervals, either a tone indicating a sucrose reward outcome or a tone indicating an aversive light outcome will play. After the tone plays, the mice will have a short response period where the number of times they lick the sucrose sipper determines the magnitude of the outcome (more licks = more sucrose reward/aversive light, less licks = less sucrose/light). Thus, this task includes simultaneous approach and avoidance components that collectively influence decision-making, and it gives us insight into the role of nociceptin in regulating these behaviors. This research is clinically significant as it can help us understand possible mechanisms underlying the expression of symptoms related to motivation in psychiatric disorders and identify new therapeutic targets to treat them.

Tornadoes are rare events in the Pacific Northwest and are extremely difficult to predict along the coast, causing much surprise when they do form. After witnessing the destruction and rebuilding of a Port Orchard neighborhood that was ravaged by a F2 tornado in December 2018, I was inspired to explore these uncommon occurrences. For this project, I am investigating the near storm environments of tornadic systems that are generated from cold air outbreaks during the winter months along the coastal Pacific Northwest. This is done by analyzing data from massive tornado datasets, METAR (Aviation Routine Air Report) observations of convective precipitation such as graupel, and piecing together upper air reanalysis data to compare them to weather indexes that have been defined to determine atmospheric instability and can be used to predict extreme weather. The goal is to find patterns that are associated with these tornadic events to create more accurate forecasts and to paint a detailed picture of tornado climatology in the Pacific Northwest. My hope for this project is to shed light onto the factors that are at play for tornadoes, hail, and other severe weather that could potentially save lives.

Memory loss is a debilitating symptom of neurodegenerative diseases. The exact process of memory decline or forgetting in the brain remains unclear. To address this issue, the development of technologies to preserve or improve memory is a continuous objective in translational medicine. This study aimed to uncover the brain networks involved in forgetting and investigate if reducing forgetting was possible through the use of transcranial alternating current stimulation (tACS; 60 Hz or sham) targeted to the dorsolateral prefrontal cortex (dlPFC). The dlPFC was considered a potential target for memory interventions as it had been linked to various aspects of memory function including working memory, executive control, encoding, and retrieval, as well as memory and attention functional connectivity networks. Participants took part in four visits, each consisting of three 8-minute memory tasks using an adaptive fact-learning software. The memory tasks assessed recognition memory (multiple choice), recall memory (fill-in-the-blank), and retrieval learning (response generation). The software used a neurocomputational model that adapted to each participant's performance. This cognitive model is based on established cognitive and biological principles and simulates memory encoding and passive forgetting. The model's α parameter, which represents the speed of forgetting and measures how quickly an individual's memories fade, was used as a dependent variable. Additionally, participants completed two resting state functional MRI (fMRI) scans to evaluate their brain's functional connectivity before and after stimulation. The study compared individual speeds of forgetting to individual patterns of functional connectivity to identify the neural networks most predictive of forgetting, and compared functional connectivity between participants who received tACS and those who received a sham stimulation. We hypothesize that tACS to the dlPFC will decrease forgetting rates and be associated with increases in functional connectivity. In conclusion, tACS has the potential to become a low-cost and non-invasive method to ameliorate memory impairments.

We recently introduced operant social stress (OSS), a new operant procedure that classifies social motivation in mice as they lever press for volitional social interactions with a familiar partner before, during, and after social stress exposure. For social stress exposures, male mice underwent social defeat and female mice underwent witness defeat. In social defeat procedures, mice are repeatedly exposed to physical antagonistic interactions by an aggressive, larger mouse, while mice exposed to witness defeat mice observe these interactions from across a perforated barrier. Consistent with the literature, male mice exposed to social defeat exhibited reduced social motivation, while female mice exposed to witness defeat displayed an increase in social motivation. These opposing observations suggest different underlying mechanisms, but it remains unclear whether lever pressing during the task truly represents a motivation for affiliative reward. Thus, to rule out the contribution of non-social factors impacting social self-administration, we performed two control experiments to rule out alternative interpretations in this new operant method. In Experiment 1, we removed the familiar partner from the waiting chamber, in turn removing the social aspect of the reward. In Experiment 2, we unpaired the social rewards from the contingent lever, instead randomly delivering them during each trial. We hypothesized, and observed, that these manipulations would prevent mice from acquiring operant responses in the task and rule out non-social factors in driving operant responding. With the inclusion of these control experiments, we can now directly assess the social motivation of both male and female mice, facilitating deeper investigations into the underlying mechanisms in future studies.

Activins are a class of growth factors belonging to the Transforming Growth Factor-Beta (TGF-β) superfamily that recruit a tetrameric complex of type-I (ACTRI) and type-II (ACTRII) transmembrane serine/threonine kinase receptors to cause downstream signaling in various critical cell-signaling pathways. Inhibition and supplementation of the signaling molecules offer new possibilities in many therapeutic and clinical applications. The overexpression of Activin A has been shown to be a major driver of diseases such as pulmonary hypertension, chronic kidney disease, and cerebrovascular disease. Sotatercept, one of the few existing activin-A-inhibiting therapeutics, is in clinical trials for treating pulmonary arterial hypertension, but, like many ligand traps, it is designed by fusing a large antibody domain to a native activin receptor domain, making it expensive to produce and unstable due to its large size. There is a need for therapeutics that can be produced in bacteria, replicate high efficacy and strong affinity, and minimize side effects. These therapeutics can be developed through de novo protein design, which involves designing proteins from scratch, with a new, unique sequence predicted to fold into its specific corresponding structure or by grafting native protein-protein interfaces onto novel scaffolds. This project aims to use computational de novo protein design methods to develop a therapeutic ligand trap for Activin A. The design pipeline involves scaffolding functional motifs, optimizing protein sequences, predicting protein structures, and filtering designs using metrics calculated by Rosetta, a protein design tool. With this pipeline, we have tested several design strategies, providing knowledge-based guidance and analyzing outputs to inform strategies for future design iterations. Recent designs have passed Rosetta filters, and we have ordered the corresponding genes to express and purify the designed proteins. Once purified, they can be experimentally characterized, testing binding and stability in vitro, and then further optimized to create stable Activin A ligand traps.

 Within the field of neuroscience, optogenetics is an established experimental tool which can be used to alter specific cell function or trigger enzymatic reactions under millisecond time-scale precision. The high temporal precision of optogenetic recombinases allows for precise identification of cell populations which causally regulate specific behaviors in health and disease. Furthermore, the inducible optogenetic control specifically of recombinase activity for cell-type targeting eliminates the use of other inducible methods including exogenous chemicals that operate on lower time-scales and notoriously cause non-specific effects. Currently available optogenetic recombinases are driven by low wavelengths of light (e.g., Yao et al, 2020) which limit their in-vivo use to local and/or superficial areas of the brain in an invasive manner. Our recently engineered optogenetics-based protein pair, NOC (Near-IR Optogenetic Cre recombinase) induces Cre recombinase activity with near-infrared (NIR) light through dimerization of split-Cre fragments. We have previously demonstrated NOC’s capability for functional Cre recombinase activity under 650 nm light administration, and now aim to optimize the inducibility profile of NOC through two additional modifications. These include modifications to Cre split-site locations based off of previously designed blue light-inducible recombinases (Yao et. al, 2020), and a novel 660 nm inducible photoreceptor pair (Zhou et. al, 2022). The inducibility of these new configurations will be tested using our in-vitro fiber optic system. The optimal configuration of NOC will lay the groundwork for NOGen (NIR OptoGenetic ensemble capture), an alternative version of NOC which will include a calcium-sensing domain on one of the protein fragments. This will limit NOGen’s activity to active neurons only, offering greater precision in identifying specific cell-populations which drive particular behaviors. These improved molecular tools can be used to further our understanding of brain anatomy and function, which serve as an important catalyst for the development of improved brain disorder treatment.

COVID-19 is an infectious viral disease that is caused by the SARS-CoV-2 virus entering host cells through surface spike proteins that bind to surface ACE-2 receptors. Some anti-SARS-CoV-2 antibodies allow SARS-CoV-2 to also have antibody-mediated entry (AME) into immune cells, often via Fcγ receptors. This phenomenon has been correlated with cytokine release syndrome, which occurs when the immune system has a highly inflammatory response to infection and is implicated in severe COVD-19 cases. It has also been shown that other antibodies have demonstrated inhibition of SARS-CoV-2 entry. During binding and viral fusion, all three receptor binding domains (RBD) of the spike protein fold to an upward conformation, which is necessary for binding. Inhibitory anti-SARS-CoV-2 antibodies impede this process through mechanisms such as premature cleavage of the RBD or stabilizing a three-down conformation. I hypothesize that inhibitory antibodies can stop AME from occurring, but it is not yet understood which inhibitory mechanisms are most effective at preventing AME. To understand the dynamic between AME and inhibitory antibodies, I am testing the infection levels of monocytes by SARS-CoV-2 pseudo-virus in the presence of antibodies shown to induce AME combined with varying concentrations of inhibitory anti-SARS-CoV-2 antibodies that have different mechanisms of affecting the spike RBD conformation. Preliminary results suggest that high concentrations of multiple neutralizing antibodies inhibit AME. It has also been observed that an inhibitory antibody that activates the up RBD conformation increases entry at certain concentrations, whereas an inhibitory antibody that stabilizes the down RBD conformation does not enhance AME. This work will contribute to our investigation of the connections between AME, spike conformational regulation, and immune cell inflammation. Studies of this type can aid in continued development of safe vaccines and therapeutics, as well as help understand how antibodies affect SARS-CoV-2 spike conformational regulation and therefore viral entry.

Automatically, we consider genes as existing solely to serve the host. Aiding in host survival allows the host to reproduce, causing these genes to propagate in the next generation. However, the existence of selfish genes, which ensure their own survival at the cost of their host, brings this conventional wisdom into question. One such type of gene is called a toxin-antidote (TA) system, which express a molecular toxin and its antidote, the latter of which prevents death, but actively kills hosts that express toxin without co-expressing antidote. The aim of this project is to develop a mechanistic understanding of one invertebrate TA system called PEEL-1/ZEEL-1, which expresses an evolutionarily novel, transmembrane toxin protein PEEL-1, and a transmembrane antidote protein ZEEL-1. Data shows that PEEL-1 co-opts a protein called PMPL-1 to kill animal cells; however, PEEL-1+PMPL-1 do not kill yeast. By identifying why PEEL-1 doesn’t kill yeast, we gain insight into PEEL-1’s toxin mechanism. One hypothesis is that it kills by inducing osmotic stress, which yeast may be invulnerable to due to their cell wall designed to resist osmotic stress. To test this, we’ve expressed PEEL-1, PMPL-1, and PEEL-1+PMPL-1 in separate yeast cultures, chemically degraded their cell walls via Zymolyase treatment, and screened for growth. Preliminary data showing that the digested experimental culture (co-expressing) experiences little post-treatment growth compared to the digested controls (non co-expressing) supports the osmotic stress-related mechanism of PEEL-1 toxicity. Our work in identifying PEEL-1 toxicity will define the first mechanism of an animal TA system and guide our understanding of the different ways that protein-driven cell death can develop in nature.

In mammals, hair cell loss or damage leads to permanent loss of auditory and vestibular function due to the inability of mammals to regenerate these cells. The primary function of hair cells is to respond to auditory and vestibular stimuli to facilitate perception of sound, head movement, and gravity. Hair cells are particularly sensitive to changes in their mitochondria, a membrane enclosed organelle that provides ATP in all eukaryotic cells. Disturbances or damages to the mitochondria can be caused by mitochondrial deafness genes, aminoglycoside-induced death, or senescence. Currently, there is very little known about the biology of hair cell mitochondria.The zebrafish neuromasts within the lateral line can serve as a functional model for cochlear hair cells because of its homology with the mammalian inner ear at genetic and structural levels. We use the zebrafish lateral line system in conjunction with the serial-block face scanning electron microscopy (SBFSEM) to produce three dimensional imaging of hair cell mitochondrial morphology. SBFSEM allows us to measure and quantify mitochondrial phenotypes. We have identified structural characteristics of mitochondrial networks adjacent to post-synaptic release sites that interact with afferent neurons and regulate synaptic transmission. The information gained from SBFSEM on hair cell mitochondrial morphologies will provide valuable insight on protective intracellular mechanisms that can prevent synaptopathy and protect against hearing loss. In our future work, we will quantify this mitochondrial networking morphology. These data will further inform functional experiments regarding the role of mitochondria at these synapses.

Academic literature is built upon citations and supporting sources–and how they are used to support or refute claims. However, it is imperative to understand when these sources are correctly summarized versus when they are exaggerated or misconstrued. Our research project focuses on this idea by using leading edge natural language processing (NLP) tools to evaluate citations in academic literature. More specifically, we are studying citation contexts, exaggeration, and linguistic modality, as pertains to scientific claims made in specific papers in the academic literature. This is crucial to understand how information is warped even in controlled and reviewed academic contexts. Prior work has demonstrated that scientific claims may be exaggerated when scientific results are cited in another source such as news media or social media. By analogy, we are investigating the extent to which this phenomenon exists in citations in the scientific literature, by adapting and developing NLP techniques for sentiment and exaggeration detection over citation contexts. We collected a dataset of citation contexts extracted from one million scientific papers, and have aligned these contexts to the scientific claims made in the original cited publications using the language model SBERT to calculate similarity scores between sentences. Our next step in this quantitative approach will be architecting our own NLP model to determine the distortion of the information from the original claim to the citation. Our preliminary findings suggest that this citation claim drift does indeed occur, but we have yet to complete our analysis on the extent of the issue. Developments in this field of study will help us better understand how information is misconstrued in an academic setting. This is vital in understanding the validity and veracity of research papers and their supporting sources.

High indoor carbon dioxide (CO2) levels have been shown to cause negative symptoms in humans, including dizziness, headaches, and cognitive impairment. Concentrations of indoor CO2 have also been used as an effective proxy for the risk of airborne disease transmission risk. Individuals experiencing poverty may be at increased risk of adverse effects from indoor CO2 concentrations due to historic under-investment in infrastructure, such as high quality HVAC systems, in these communities. Public spaces such as libraries are particularly important for under-resourced communities as they may be the only places with accessible Wi-Fi, reading materials, and indoor bathrooms. This study surveys libraries, in several Seattle neighborhoods with varying rates of poverty. All libraries tested are branches of the Seattle Public Library system. Aranet4 HOME air quality monitors, that measure CO2 levels, were placed in similar central locations in each library for twenty-four hours on weekdays.The highest three recorded CO2 levels in a day were averaged to determine the peak CO2 exposures for library patrons. For instance, at the Ballard Branch, the highest average recorded CO2 levels were 712 ppm +/- 0.577 ppm and the neighborhood has a poverty rating of 2/10 according to the Washington Tracking Network (WTN). At the Magnolia Branch, the highest average recorded CO2 levels were 622 ppm +/- 10.6 ppm and the neighborhood has a poverty rating of 1/10 according to the WTN. Preliminary results thus far do not show significant differences in CO2 levels. The chosen libraries vary in size and may show more CO2 fluctuations once data is collected in additional areas. Documenting air quality differences in public spaces can highlight systemic inequities and help planners allocate limited resources to most effectively and equitably serve all Seattle neighborhood communities.

In the United States, Black adolescent (10-19 years old) girls have the highest prevalence of pediatric obesity. Despite public attention and public health interventions on obesity, current research has yet to evaluate what weight management recommendations are prevalent in mediums most frequently used by Black adolescent girls. Previous scholars show that Black adolescents primarily consume content on Instagram and Tiktok compared to all other social media platforms. Our research seeks to compare the weight management recommendations present in Instagram and Tiktok with those of public health organization websites. Using the rhetorical themes identified, we move to assess the feasibility of health messaging from public policy organizations compared to social media platforms. Ultimately, we seek to evaluate the efficacy of the recommendations based on the availability of the infrastructure accessible to Black adolescents. We analyze weight management messaging on Instagram, Tik Tok, and public policy organization websites. These primary sources are excerpted through simple random sampling and coded for common weight management themes. We seek to determine the feasibility of such messaging as well as points of convergence and divergence between the platforms. We hypothesize that the weight management themes found in social media will not demonstrate consistency with the recommendations made by public health organizations. In addition, we predict that neither the social media nor public policy weight management recommendations will be attainable for Black adolescent girls when assessing their feasibility in relation to the environmental and socioeconomic resources available to them in the United States. In conclusion, there are insufficient resources for Black adolescent girls to make informed weight management decisions and available resources are not effectively communicated.

Plasmodium vivax (P. vivax) is the most widespread malaria species. P. Vivax can lay dormant in hepatocytes and cause recurring malarial infections. Tafenoquine (TQ) is an antimalarial drug approved by the FDA in 2018 for the radical cure of P. vivax. Unfortunately, 8-aminoquinolines like TQ cause hemolytic anemia in G6PD deficient patients. Due to this contraindication, genetic G6PD screening is required before TQ administration. These additional tests pose a significant challenge for broad administration in resource-constrained countries. Our polymer prodrug conjugates (drugamers) are designed to improve TQ delivery to the liver and reduce red blood cell exposure. Using RAFT polymerization, drugamers can be optimized for delivery efficiency and avoidance of hemolytic anemia. Polymer architectures can be further enhanced by utilizing a variety of enzyme cleavable linkers, monomers, and receptor binding cofactors. We previously demonstrated increased liver-to-blood area under the curve ratios in mice using a variety of different polymer architectures. Mice received an IV or subcutaneous dose of drugamer and relevant organs were harvested at previously determined time points up to 48 hours. Pharmacokinetic profiles were created using a plate reader fluorescence assay and tandem LC/MS/MS with tissue samples. These drugamers represent an ongoing effort to iteratively improve our drug-polymer design. The improvement in TQ delivery through our drugamer vehicles could allow for more liberal administration guidelines, completely removing the need for G6PD testing for the treatment of P. vivax.

As tool compounds aimed at profiling drug leads, covalent small molecule probes targeting amino acid residues present great value to the field of chemical proteomics. Recent progress has expanded the search for these irreversible inhibitors to those targeting lysine residues on select kinases. These small molecule probes are typically composed of an aminophilic group that binds lysine, a scaffold that directs the inhibitor to the residue of interest, and a reporter group that facilitates visualization of binding on a gel. Here we present the organic synthesis of numerous novel small molecule inhibitors, as well as their live cell labeling behavior. The inhibitors of choice are designed with a variety of electrophilic groups that serve as aminophiles targeting lysine. Each inhibitor is built around either a Foretinib or Xo44 scaffold, and uses a transcyclooctene (TCO) click handle as the reporter group. The TCO handle rapidly binds tetrazine, allowing for the linking of a fluorophore to the inhibitor, which reports labeling of lysines through SDS-PAGE. An initial live cell labeling assay reveals clear binding activity in a foretinib-based inhibitor with a squarate electrophile, as well as minor bands in select sulfonyl-fluoride based inhibitors. Through mass spec (MS) proteomics, the protein targets of these promising inhibitors will be identified. Assuming MS reveals selective, high affinity binding, these small molecule probes aid the profiling of drug leads, and expand the range of targeted covalent inhibitors available for chemical proteomics. 

Climate change has resulted in environmental changes that pose direct and indirect challenges to marine organisms. One such organism that has been widely studied is the common murre (Uria aalge), which has experienced decreased reproductive success and adult survival in response to climate change-induced ocean warming. Because common murres molt flight feathers relatively synchronously, they may be especially vulnerable to environmental stresses, such as the challenge this may pose on obtaining food. In this study, we explore the degree to which shifting environmental conditions impact adult survival of common murres at a physiologically sensitive point: flight feather molt. The data we used for this study include: monthly expert-verified observations of bird carcasses from the Coastal Observation and Seabird Survey Team (COASST) citizen science program collected from the outer coast of Northern Washington south down to Humboldt, California; significant wave height data from the National Data Buoy Center (as a proxy for storminess); spring transition date (from the Columbia Basin Research website) as an indication of annual production potential; and Bakun upwelling index (from the Pacific Fisheries Environmental Laboratory website) as a measure of upwelling strength and production potential. We annualized both the bird and environmental data over the years 2003-2021. For this project, my role was to conduct statistical analyses using the statistical program R. I employed generalized additive mixed models to determine the relationship between the proportion of adult carcasses in molt and the environmental variables. To select models, I used Akaike Information Criterion corrected for small sample size (AICc). Our research will give insights into how the combined effects of physiological and environmental stressors may impact upper trophic seabirds as climate change continues to intensify.

Autism spectrum disorder (ASD) is a developmental disorder characterized by deficits in social communication and interactions, and repetitive behaviors or interests. Children with ASD are more likely to show food selectivity than neurotypical (NT) children, and their restricted food consumption may be associated with nutritional deficiencies. Eating disorders are serious mental health conditions that can have long term health-related consequences. Understanding behavior surrounding eating habits is paramount to developing treatments that are effective for children with autism. In youth without autism, self-compassion impacts eating behaviors. Higher self-compassion is causally linked to lower eating pathology. This study aims to extend this work to examine whether self-compassion influences eating behaviors in adolescents with ASD. Participants included children with ASD (n = 37) and children with NT development (n = 52) between the ages of 13 - 17 years. Parents of participants completed the Child Eating Behavior Questionnaire, and participants completed the Self-Compassion Inventory for Youth survey. We compared emotional overeating and emotional under eating to the self-compassionate coping scale and self-punitive coping scale. Given the stereotyped and repetitive behaviors of adolescents with ASD, we expect a similar relationship between self-compassion and eating behavior seen in studies with neurotypical individuals, to also exist within an ASD group. Specifically, we hypothesize: (1) a positive correlation between emotional overeating and self-punitive coping, (2) a positive correlation between emotional under eating and self-punitive coping, (3) a negative correlation between emotional overeating and the self-compassionate coping scale, and (4) a negative correlation between emotional under eating and the self-compassionate coping scale. This study will offer more insight into the role of self-compassion and eating behavior of ASD adolescents. If the hypothesized correlations exist within the ASD and NT groups, we can look for similar risk factors of disordered eating behavior within ASD adolescents.

From playing sports to driving a car, our brain constantly receives a barrage of complex visual information. Previous work shows that recognizing two things (e.g., words, animals) presented simultaneously is harder than recognizing one, suggesting that the brain has a limited ability to attend to multiple visual objects at once. In this project, I examine whether American Sign Language (ASL) experience affects sign recognition. Specifically, I hypothesize that signers and non-signers may differ in their ability to attend to multiple signs at once. Participants look at the center of a monitor where a reference letter sign appears, followed by test letter signs on both the left and right. On each trial, either the left or right sign is relevant (single-task condition), or both signs are relevant (dual-task condition). Participants respond, with a button, whether the relevant test sign(s) match the reference. The dual-task deficit (the difference in performance between single- and dual-task conditions) measures how well people can attend to multiple simultaneously presented signs. I compare the dual-task deficit across hearing non-signers, hearing fluent signers, and deaf signers. Previous work has shown a large dual-task deficit for written English letters and a small deficit for objects. I hypothesize that signers’ will have similar dual-task deficit to those of written English letters, while non-signers’ dual-task deficit will be small, similar to objects. So far, preliminary results from two non-signers support this second prediction. This project will reveal how the different sensory experiences and language demands of deaf and hard-of-hearing populations alter how their brains process visual information. Understanding these differences can help improve accessibility for these marginalized groups in public spaces. For example, it can help improve methods for presenting sign information to Deaf students to improve learning outcomes.

Rigorous ethological observation via machine learning techniques, termed computational neuroethology, is a rapidly expanding field. Our lab has created an open-source pipeline for automated behavioral analysis using supervised machine learning called Simple Behavioral Analysis (SimBA), to aid in the high throughput analysis of social behavior. Using pose estimation data of socially interacting animals obtained through open source pipelines such as SLEAP or DeepLabCut, we are able to create large training sets of video frames that are hand scored as positive or negative for a behavior, which we then feed into supervised random forest algorithms. These algorithms then build classifiers which can detect the behaviors in novel videos. My work has focused on building and titrating classifiers for two important social behaviors: face and body sniffing by a dominant mouse toward a subordinate. So far, I have hand-scored a large dataset of social interaction videos to create a sizable training set. I have begun the initial phases of training my classifiers, which involves finding appropriate hyperparameters for the random forest algorithms so that they can differentiate positive and negative behaviors, and refrain from overfitting to our training datasets. Using both machine learning performance metrics as well as hand versus machine comparisons, I am able to understand the generalizability and accuracy of my classifiers. As I continue with this project, I will selectively add more positive and negative examples to correct false positives and boost the confidence of the classifiers through subsequent iterations. This work allows me to gain an understanding of the principles of machine learning techniques, and create classifiers that we openly provide to behavioral neuroscience labs across the world. We expect that the pooling of these classifiers with outside labs will promote a high level of standardization of behavioral definitions in behavioral neuroscience, ultimately increasing reliability and reproducibility.

Phase separation in phospholipid membranes occurs in living systems like yeast vacuole membranes and consists of domains enriched in specific lipid components. Phase separated domains coalesce and merge together into a singular phase as membranes are heated above the phase transition temperature, T_mix. The phase transition temperature depends on the lipid composition of a membrane. In the lab, it is useful to produce simple, model membranes to isolate phenomena like phase separation from the complexity of biological systems. Emulsion phase transfer is one such technique used to generate giant unilamellar vesicles (GUVs) by using a centrifuge to drive emulsion droplets coated in lipids through a lipid-oil solution and water interface. However, there are several specific challenges for emulsion phase transfer that require optimization: drying the lipids down with nitrogen gas into a lipid film, the time sensitive creation and layering of the lipid-oil emulsion, and finding the optimal centrifugation parameters. Here, we optimize emulsion phase transfer in three ways: 1) evenly coating lipids films via swirling, 2) creating the emulsion and depositing it as quickly as possible, and 3) tuning centrifugation to maximize vescile formation and minimize vesicle aggregation. Further, we measure the phase transition temperature for GUVs made of a ternary lipid mixture consisting of DPPC (16:0 PC), DOPC (18:1 PC), and Cholesterol in a 1:1:3 ratio. To visualize membrane phase separation, a fluorescent lipid that partitions preferentially to only one phase was added to lipid mixtures used to prepare GUVs. Due to the crucial role of cholesterol in membrane phase behavior, the phase transition temperature of GUVs generated through this technique will vary from those produced by other techniques due to poor cholesterol incorporation.

Cognitive decline with increasing age is an aspect of growing old. Age-related cognitive impairment (ARCI) entails the early stages of decline and is extremely common, affecting millions of older people. However, little is known about why some people have ARCI and some are cognitively normal at older ages. A recently characterized mouse model of naturally occurring ARCI, showing a distribution of affected and non-affected animals similar to older humans, was used to interrogate brain samples for transcriptomic profiles generated by RNA sequencing (RNA-seq). Hippocampal brain samples were collected from 22-month-old male and female C57BL/6 mice with and without ARCI (as determined by a spatial navigation learning task). RNA-seq was done by the NovoGene UC Davis sequencing Center. Preliminary data show a stronger presence of pathways of neurodegeneration and oxidative phosphorylation in the hippocampus of mice with ARCI compared to mice without ARCI. Detailed computational analysis will be done to investigate gene-expression quantifications using sequencing pipelines aligning Differential Gene Expression, KEGG orthology pathways, and Star RNA-seq read mapper in order to more accurately identify unique transcriptomic profiles in the brains of mice with and without ARCI. These findings will help identify genetic pathways that could be therapeutically targeted to ameliorate and possibly reverse the effects of ARCI, and provide insight into internal brain factors responsible for an increased risk in developing more severe conditions of neurodegeneration and dementia such as Alzheimer’s disease.

Neuropsychiatric disorders pose a difficult challenge for healthcare providers. Treatments for such disorders vary in efficacy and come with detrimental costs for patients and their communities. Historically, preclinical animal models have failed to incorporate the nuances of volitional human social behavior. This project used chronic social defeat stress to induce depression-like behaviors in male and female mice, this was followed by self-administered social interactions within an operant chamber in which lever presses were reinforced by social contact. The goal is to develop preclinical animal models that can be assessed to identify mechanisms responsible for stress-induced social motivation. The mice will be injected with a nuclear localized tag (oNLS) and viral retrograde tracer rAAV2-retro-GFP. Male and female mice will train to self-administer social interaction with a sex and age-matched housing partner over the course of ten 12-trial sessions. Next, experimental male and female mice will be subjected to physical and witness defeats followed by operant social self-administration. Before and after the 10-day operant social stress sessions, we will test social reward seeking via non-reinforced self-administration of social reward followed by a progressive ratio test. Brain tissue will be collected and prepared for immunohistochemistry and iDISCO+ whole-brain clearing for cfos labelling. We predict results will show differential cfos activity in sexually dimorphic brain regions such as the hippocampus, prefrontal cortex, amygdala and the bed nucleus of stria terminalis. We determine that operant social stress can be used to discern differences in social motivation in male and female mice as a result of stress-induced factors. There is great potential in using whole-brain activity mapping to identify brain structures activated during social reward following social stress, as this can also serve as a technical resource for the field by identifying relevant non-canonical brain regions and circuits that govern such behaviors.

Aging is a complex indicator for the development of age-related diseases. Resilience to aging is defined as the ability to experience a stressor and return quickly to homeostasis. It is important to assess biological age quickly and accurately to fine-tune intervention strategies for non-resilient aging populations. The excision repair cross-complementation group 1 (ERCC1) is an endonuclease that plays a vital role in mediating the nucleotide excision repair of DNA, as well as being involved in the interstrand cross-link and double-strand break repair of DNA. Knockdowns of the gene significantly reduce the lifespan of the mouse due to an accumulation of damaged DNA. Previously it has been shown that wound healing is robustly correlated with DNA methylation clocks and age-related pathological features. In this study, we aim to understand whether a non-invasive wound healing assay is sensitive to accelerated aging phenotypes in an ERCC1 -/â–µ progeria model. In a preliminary study, mice 5 months old had a 2mm hole punched in each ear. The area was measured at 0 and 16 days time. The resulting healed area was compared against a standard curve where it was shown the accelerated aging mice were aged significantly older than the wild type (p<0.05). The lifespan of the mice also correlated with the wound healing (p<0.05). These findings indicate that a simple wound healing assay may be able to accurately assess biological age. Clinically, the ability to intervene and treat aging patients before they develop age-related pathology may help lengthen healthspan and postpone the onset of associated diseases. Future work will look to strengthen these findings with molecular evidence and pathological support.

Autism Spectrum Disorder (ASD) is a neurodevelopmental disorder characterized by differences in social interaction and communication, as well as repetitive behaviors (APA 2013). Per Kanne and Mazurek (2011), 56% of 1380 children and adolescents diagnosed with ASD engaged in some form of aggression towards family, teachers, or peers. Aggressive behaviors can prevent youth with ASD from being able to engage in learning opportunities and community events. An important factor in decreasing rates and severity of aggression is through the identification of social and environmental factors that may impact the stability of aggressive behaviors. The aim of this study is to look at factors that may impact the stability of aggressive behaviors in a longitudinal sample of autistic and non-autistic youth. 44 participants (22 ASD) aged 8 to 18 years, from the NIH funded longitudinal study on sex differences in autism were included in the analysis. Aggression was measured using the Child Behavior Checklist (CBCL), a parental report measure on problem behaviors, which includes items related to self aggression (self injurious behaviors) and other-aggression (aggression towards peers and adults). Data was collected at baseline and 3 to 8 years later. We expect low IQ and younger age will be related to higher aggressive scores on CBCL at baseline. We predict that youth with greater social improvement between timepoints and use of psychotropic medication will have lower levels of aggression over time. Identification of factors that impact changes in aggression over time can aid in implementing interventions to aggression and improve quality of life.

The population structure of species occupying deep-sea hydrothermal vents is strongly influenced by geological processes. The formation and maintenance of vents can create a patchwork of habitats across the sea floor, which are subject to catastrophic events that can extirpate whole communities. Therefore, the population structure of vent species is not only influenced by adaptation, life history, and dispersal but also by geological processes and oceanographic processes. Characterizing the genetic diversity and connectivity of species between vents can provide information about these processes. The Axial Seamount, located on the Juan De Fuca Ridge located off the Pacific Northwest coast of the USA, is a well-studied hydrothermal vent system. Here, sulfide worms (Paralvinella sulfincola) can be found on and around chimney vents, building tubes that contribute to chimney formation and habitats for other organisms. We predict low gene flow and low connectivity between different vent populations of this species because their reproductive life history strategies depend on pheromone signaling. Such signaling likely results in individuals mating more frequently with their closest conspecifics. However, little is known about the larval dispersion dynamics of this species. Sulfide worms were collected to investigate the connectivity and genetic diversity of their populations. Mitochondrial and nuclear genes were amplified from DNA extracted from worms that were collected from two locations within the Axial Seamount (Inferno and El Guapo chimneys, located within the ASHES and International District vent fields, respectively), to determine genetic diversity at each site and to test whether these sites constitute one or two separate populations. This research will ¬¬¬¬assist in understanding the connectivity and genetic diversity of sulfide worms within the Axial Seamount system across multiple vent fields and contribute to a broader understanding of how populations are established and maintained in this unique and dynamic ecosystem.

The negatively-charged nitrogen-vacancy (NV) center in diamond, consisting of a substitutional nitrogen atom and an adjacent vacancy defect, can provide an ideal platform for quantum computing. The NV center has many useful properties such as its optical stability and long spin-coherence times. However, due to the high refractive index of diamond, the light-collection efficiency of NV centers is very low. To solve this problem, I registered the positions of the promising NV center candidates in diamond and fabricated solid-immersion-lenses around the pre-selected NV centers. As a next step towards building a diamond quantum processor, here I present the construction of a cryogenic confocal microscope, which consists of a confocal imaging system with 515 nm laser and a 637 nm laser. Through optical pumping by the 515 nm laser and on-resonance driving by the 637 nm laser, this setup will allow for single-shot readout of the NV electronic spin state. This paves the way for our futhure implementation of quantum protocols and small-scale quantum algorithms for both pedagogical and research purposes.

An effective peptide-based cancer vaccine requires efficient intracellular delivery of antigen peptides to activate tumor-killing immune responses. However, the localization of peptide antigens during endosomal release to optimize the immune response remains under-investigated. The Pun Lab has developed the self-assembling Virus-Inspired Polymers for Endosomal Release (VIPER) that can induce endosomal escape of peptide antigens. The current VIPER formulation employs reducible disulfide bonds for antigen conjugation. We hypothesize that the controlled antigen peptides release mediated by endosomal proteases can result in more effective antigen presentation that leads to more potent tumor-killing cell responses. In this project, I replace VIPER’s antigen conjugation strategy with the pentafluorobenzyl (PFB) moiety (VIPER-NR) and introduce an enzyme-labile linker in the antigen sequence to determine the optimal peptide release kinetics and localization for optimal tumor-killing cell responses. I synthesized a library of enzyme-labile linkers for the ovalbumin antigen peptide of VIPER-NR. I utilized a dendritic cell cross-presentation assay to screen for linkers associated with that efficient antigen presentation in vitro. Subsequently, I conducted enzyme-mediated drug release assay and red blood cell lysis assay in vitro to evaluate the cleaved antigen profile and endosomal escape induction capacity of VIPER-NR with cleavable linkers compared to VIPER-NR. We expect early release of antigens during endocytosis with these modified antigen sequences in VIPER-NR in vitro and significantly elevated cytotoxic T-cell response against the model antigen in vivo. This project could improve the effectiveness of the VIPER system as a peptide vaccine delivery platform. It would also provide further understanding of optimal antigen release profiles for a better tumor-killing cell response in cancer vaccine applications.

My research project aims to combat inflammation and fibrosis caused by biomaterials and implants. Nondegradable biomaterials can provide long-term stability in the body but can elicit a foreign body response, such as inflammation. The project focuses on finding ways to repair and replace damaged tissue at the location of the implant.The project involves engineered M1 cells which were created and published by the Giachelli Lab within the Department of Bioengineering at UW. We have two groups of mice: one control group that has been injected with engineered TLR4 (Toll-Like Receptor 4) cells but not given the CID (Chemically Induced Dimerizers) drug, and another group that has been injected with both the engineered TLR4 cells and given the CID drug. The inside of the cell was isolated in both groups of mice and the extracellular domain was removed. For the group with CID, the inside domain of the cell was bound with CID which is thought to result in dimerization and activation of the M1 phenotype.At this stage in the project, we have tissue samples from both these groups, and I will analyze these samples using H&E staining thus allowing me to measure healing parameters, like how dense the collagen structure is around the material and analyze the effect of CID on the state of the tissue. For expected results, I believe the group with CID will have a denser collagen structure around the material than the group without CID.Conducting the analysis on these tissue samples will help address the effect of CID on healing parameters, such as inflammation. Furthermore, this work will help us develop a better understanding of the roles that M1 and M2 phenotypes play in the healing process which can lead to new therapies that reduce the inflammatory response elicited by biomedical devices. 

Reducing the considerable carbon emissions of the built environment industry is vital to addressing the current climate crisis. Though there have been substantial advancements in cutting emissions from building operations (operational carbon), addressing buildings’ embodied carbon is a newer focus, with ongoing research driving industry transformations. Embodied carbon refers to the greenhouse gas emissions arising from the manufacturing, transportation, installation, maintenance, and disposal of building materials. Since a large portion of embodied carbon emissions are upfront, rapid adoption of improved practices is critical. Thus, many architecture, engineering, and construction (AEC) firms around Seattle have initiated a focus on reducing the embodied carbon from their designs and practices. We have selected three Seattle-based AEC firms, and are analyzing each firm’s methods of improving emissions from their practices while considering the lessons and applications of these methods going forwards. The team is conducting in-person tours of firm offices and interviewing key sustainability-focused team members about their approach to improving their projects’ environmental impacts with particular focus on embodied carbon. Beyond broad qualitative data about firm practices, quantitative data on specific low-carbon buildings is collected. This is being reviewed, analyzed, and synthesized into deliverables summarizing common trends, best practices, and future research needs. Due to the relatively recent innovations in reducing embodied carbon, many practices are yet to be adopted. For this reason, we expect that many firms will be following longer-term plans as they gradually integrate sustainable practices into their workflows. Through an advanced understanding of the changing landscape around the impacts of embodied carbon, designers and researchers will be better prepared to eliminate carbon emissions from all sectors of the built environment.

Moss is a bioindicator that can be useful in evaluating air quality in metropolitan areas. One study in Portland used a common moss, Orthotrichum lyellii, to locate sources of cadmium pollution, leading to regulations for glass factories in the area. The current study applied a similar methodology to locate sources of metal contamination in and around the South Puget Sound region. O. lyellii was collected from locations with a wide range of vehicular traffic. Additionally, collection sites were divided between industrial, commercial, residential, and forested areas. Moss samples were dried, digested with acid and peroxide, and analyzed for metal content using ICP-MS. Our study shows increased concentration of trace metals such as titanium and vanadium in industrial areas. Some major metals such as calcium may be more closely linked to vehicle traffic. These results may indicate human health hazards in industrial areas in the South Puget Sound area. 

The interaction between incoming salt water from the ocean, which is driven by tides, and exiting freshwater from rivers drives circulation through estuarine environments. As a result of the interaction between the incoming water and the exiting water, nutrients and sediment are moved around the estuary. This study focuses on the interaction between tides and the Snohomish River as it enters the Possession Sound estuary, located in Everett, Washington. To acquire data, I deployed a boat-mounted acoustic Doppler current profiler (ADCP), which uses sound to measure water current direction and velocity. I collected these data at varying tide stages at three different sites between the Snohomish River’s southern output to nearby Mount Baker Terminal, located 3.6 miles southwest of the river output. I have collected 8 samples over the course of 7 months at both ebb and flood tide stages. Each transect survey lasted 3-6 minutes and collected data from the first 20 meters of the water column. To get accurate analysis of current velocity and direction I split the data into categories based on depth. Preliminary analysis shows a southward current at many sites during all tide stages and depths. This raises questions about the scope of the river influence and the potential for southward currents regardless of tidal stage. However, further analysis of current velocity and river discharge are needed. Due to the complexity of the currents in the area, understanding how the river and the tides are interacting can provide a greater understanding of how these currents are impacting the dispersal of sediment and nutrients throughout the estuary.

Local bathymetry in estuaries strongly affects water current direction and speed. Water current and speed, or the water flow, determine the circulation of nutrients and oxygen within the estuary. To assess the relationship between water currents and slopes in an estuary, I utilized a boat-based acoustic doppler current profiler (RD Instruments Workhorse 600 kHz ADCP) to measure water speed and direction with depth. Based on preliminary analysis, water direction is consistent at surface level but becomes inconsistent beyond that. Speed is mostly between 0 cm/s and 50 cm/s, but becomes more varied beyond 30 meters. However, that may be due to inaccuracies in measurement, as data collection becomes less consistent beyond that depth based on our current ADCP configuration. The average direction of data at each depth doesn’t change significantly with depth. In summary, speed is mostly consistent with depth near a slope, whereas the direction is not. So, the bathymetry may have a greater effect on water direction than speed. For future work, investigating these patterns with higher resolution datasets will shed more light on any potential patterns.

Possession Sound, WA, serves as an important foraging area for a group of seasonally resident gray whales Eschrichtius Robustus. This group of predominantly Eastern North Pacific Gray Whales that visit Possession Sound (Sounders) arrive as early as January and continue migrating towards other feeding grounds near May. If the frequency of sounds within the hearing range of these gray whales (50 to 5000 Hz) exceeds comfortable levels, they may have difficulty foraging. To monitor these relationships, we looked at the frequency and amplitude of sound near Mt. Baker Terminal (MBT) in Possession Sound, WA, from January 2021 to May 2021 with a specific focus on sounds from 50 to 5000 Hz. To gather this data, we used a SoundTrap 300 HF hydrophone, which is currently mounted to a dock at MBT. From January 2021 to February 2021, the hydrophone recorded continuously at a 96-kilohertz sampling rate. From March 2021 to May 2021, the hydrophone was set to record the first fifteen minutes of every hour at the same sampling rate. Preliminary research shows that Possession Sound has a consistent prevalence of ambient and intermittent noise within the established frequency range and peak amplitudes as high as 164 dB. This level of noise may have the potential to negatively affect gray whale behavior and foraging success. Future research should be conducted to see how current and future vessel slow-down trials will impact the frequencies and amplitude of local noise. Future research should also include comparing the MBT sound profile to other sites in the Salish Sea to better understand if the amplitude increase is unique to the area or a cause for wider concern.

The Everett Marina is a heavily developed area that has significantly altered water flow from the Snohomish River compared to its natural state. Anthropogenic alteration of this environment led to buildups of sediment, which has required dredging at increasingly shorter intervals leading up to the present. In order to explain sediment accumulation in the marina, this study examines the movement of currents and the abundance of sediment using an Acoustic Doppler Current Profiler (ADCP); data were recorded from June 2020 to August 2021 and compared to recent data I recorded from February and March of 2023. I hypothesized that current direction would be variable and speed would be sluggish due to the shallow depth. In addition, I hypothesized that seasonal changes such as snowmelt in spring and rain in winter would impact the velocity of the currents. Because sediment movement is largely impacted by currents, I hypothesized that sediment abundance would reflect seasonal changes in water flow. Analysis of water current data between June 2020 and August 2021 demonstrates a significant correlation between the velocity of North/South currents and the magnitude of tide stages, but river discharge levels appear to have less of an effect on current speed in the marina. The susceptibility of this area to tides more than river discharge suggests that it is easier for sediments to accumulate in one area as opposed to being swept away. Future analysis will compare this past data to the present and investigate potential correlations with sediment abundance.

Botryllus schlosseri is a non-indigenous species of colonial tunicate commonly found in many marinas of the Puget Sound. Colonies of Botryllus can grow asexually through the process of blastogenesis (also called ‘budding’) which involves the formation of buds which mature into new zooids on a weekly cycle. Apoptosis and oxidative stress are involved in the final stage of blastogenesis, a time when the system resorbs the zooids and the newly matured buds take over. Although nickel has been found to be genotoxic and can induce many aspects of the cellular stress response in animals, little research has characterized these effects on marine invertebrates. In this study, we performed acute exposures of nickel chloride at sublethal concentrations in B. schlosseri collected from the field to identify changes to blastogenic timing, DNA damage, apoptosis, and the oxidative stress response. These data will establish the in vivo tolerance and stress responses of B. schlosseri to nickel exposure. Furthermore, these data will inform future studies which seek to use nickel as an immortalization agent in cell culture with the goal of generating the first continuous cell line for any marine invertebrate species.

 Reconstructing past environments can help us understand plant community evolution over time. For example, plant silica (phytoliths) can help us reconstruct canopy openness. Phytoliths are formed when plants uptake monosilicic acid from the surrounding soil through their roots and deposit it as opalized silica in and around cells; they have been used as a tool in paleoecology because they are well-preserved in the fossil record. For phytoliths formed in the outermost layers of leaves (epidermis), there is a relationship between morphology and light availability. A previous method established this correlation using modern soils in Costa Rica to apply to sites in the Eocene-Miocene of Argentina. However, it is unclear whether this model can make accurate inferences in other geographic regions. Here, we expand the method using modern phytolith samples from the Southeastern United States to generate a dataset and apply it to fossil phytolith assemblages from the North American Great Plains Region to reconstruct changes in vegetation during Oligocene-Miocene grassland expansion. For this work, we use an optical microscope to observe and count the phytolith assemblages to reflect a range of vegetation types in North America. We focus on phytolith morphotypes representing silicified epidermal pavement cells and measure their size and shape using ImageJ. We expect a linear trend between LAI (Leaf Area Index, the quantified relationship between morphology and light availability) from phytoliths and observed LAI which can be used to form the model for North American environments and applied to the fossil phytolith record of the Great Plains Region. Expanding on this method could make its use more widespread and lead to similar research in other regions of the world. Current models suggest the persistence of closed forests through this entire interval, a result we wish to further test using this updated model.

Climate change and global population growth are driving the need for more sustainable methods for growing crops used in agriculture and the production of biofuels. To address these challenges we are exploring the role of that plant microbiome in host plant tolerance to environmental stresses related to climate change. In particular we are investigating whether endophytes, microorganisms that colonize the internal tissues of plants, make the host plants more tolerant to drought or low-nitrogen conditions. We are currently optimizing the process of DNA extractions of fruit and poplar trees which were inoculated with beneficial nitrogen fixing bacteria, and grown in either water-or nitrogen limited conditions. We then purify high quality microbial DNA, and use polymerase-chain reaction (PCR) to optimize strain specific primers (SSP), which target specific DNA sequences in the genomes of our endophytes, and minimize background noise produced by plant and other microbial DNA. This allows us to reisolate our strains from the plants to gain understanding of where they colonize, and to demonstrate that the trees were successfully colonized by our endophytes to support growth and drought tolerance data collected from inoculated and uninoculated controls. By ensuring the SSPs only target our strains of interest, we differentiate our endophytes from other members of the plant microbiome. These primers are then used in Droplet Digital PCR (ddPCR) to quantify their relative abundance. Using this information we hope to contribute to the project objectives of demonstrating that beneficial endophytes can be used as a sustainable method for improving drought and low nitrogen tolerance in plants, both in agricultural and biofuel applications, reducing the consumption of nitrogen fertilizers and water for irrigation in these sectors.

One of the most striking adaptations in land plant evolution is the specialization of reproductive structures. LEAFY (LFY) is well characterized in flowering plants (angiosperms) as a transcription factor initiating the development of the flower, which contains the reproductive organs. LFY also regulates the first cell division of the zygote (diploid phase) in mosses (a type of non-vascular plant). The fern Ceratopteris richardii is a type of non-flowering plant that is midway phylogenetically between mosses and flowering plants, in the sister clade to seed plants. With a lab-friendly, independent haploid phase (gametophyte), transgenic protocols and a reference genome, C. richardii is ideal for studying LFY’s functional evolution. Previously, targeted silencing of the two fern LFY homologs CrLFY1/2, demonstrated that it maintains the identity of the apical stem cell in gametophytes. To further characterize the function of fern LFY, I study the effects of its over expression on gametophyte development. To that end, I record gametophyte development using bright-field and fluorescent microscopy. Preliminary results suggest that overexpression of CrLFY may affect development of the sperm-producing gametangia (antheridia) in fern gametophytes, with more antheridia found in transgenic plants late in development. Given that antheridia continue to be produced in wild type gametophytes in the absence of fertilization, I test the hypothesis that CrLFY overexpression causes delayed fertilization (by a yet unknown mechanism) and that increased antheridia represent a secondary effect. Here, I experimentally delay fertilization by withholding water needed for sperm release (“flooding”), and compare the number and pattern of antheridia on transgenic and wild type gametophytes with and without flooding. Functional characterization of LEAFY in a fern, and of other master regulators of development more generally, contributes to a better understanding of the evolution of land plants via the potential repurposing of ancestral genetic pathways into novel functions.

By 2050, the global human population is expected to reach 9.7 billion. Supporting this rapid growth will challenge global food systems, increasing the demand for healthier affordable foods such as poultry-sourced products (meat and eggs). Improving the accuracy of genotype-to-phenotype predictions for farmed animals could enable better breeding strategies and management practices that are crucial to meeting this goal. By characterizing regulatory genomic regions within various tissues, epigenetic factors which dictate specific cellular phenotypes can be pinpointed: improving phenotype prediction accuracy. To this end, we genetically sequenced (whole-genome bisulfite sequencing) samples of reproductive tissues (magnum, shell gland, isthmus, and ovary) from farmed groups of chickens (G. gallus). Through bioinformatics, we functionally annotated regulatory patterns of DNA methylation to identify tissue-specific epigenetic variation across the female chicken reproductive system. To tackle this, we utilized CGmapTools software to comparatively analyze tissues in a pairwise manner. In order to quantify each pairs’ differentially methylated regions (DMRs), all methylated regions were intersected and filtered through a statistical t-test. We found the pairwise comparison analysis between isthmus and ovary tissues to show the highest number of significant DMRs, being 51% hypermethylated in the isthmus. On the other hand, a comparative analysis between isthmus and shell gland tissues showed the lowest number of significant DMRs, being 54% hypermethylated in the isthmus. Upon annotating and conducting enrichment analyses on the DMRs, we learned that genes related to ECM-receptor interactions and focal adhesion were most prominent. Results of this research will aid the FAANG consortium (an international effort to improve farmed animal production) in improving genotype-to-phenotype predictions, hopefully enabling more sustainable genomic selection practices and genome-enabled management in the future of agriculture.

A grand challenge in the field of mass spectrometry proteomics is the problem of peptide sequencing. The dominant approach to this problem uses a database search; however, with the use of machine learning, peptide sequencing can be solved without using a database. Casanovo is a recently-developed, state-of-the-art machine learning model that solves this problem. However, Casanovo is trained on biased data, because most mass spectrometry proteomics experiments digest proteins using trypsin, which preferentially cleaves after lysine and arginine. This can result in incorrect predictions for data that was not generated using trypsin. Hence, we hypothesized that using a non-tryptic dataset to refine an existing Casanovo model would produce more accurate predictions on non-tryptic data. I constructed an unbiased dataset by downsampling from preexisting data, yielding a set of peptides with a uniform distribution of n-terminal amino acids. After splitting the data and fine-tuning Casanovo on an unbiased training dataset, I used the model to predict on an unbiased validation set. I also applied Casanovo to two non-tryptic datasets: antibody sequencing data and immunopeptidomics sequencing data. For the latter dataset, an antibody binding affinity tool, NetMHCpan4.0, was used to determine the binding probability of the predictions to test plausibility. We demonstrate that the fine-tuned model, Casanovo_ne, increases performance when predicting on non-tryptic data. Applied to the uniformly distributed validation set, Casanovo_ne predicts more accurately than the original Casanovo model, and predicts more uniform terminal amino acid distributions. Additionally, Casanovo_ne predicts more peptides that are likely to be MHC binders than a database search strategy. Finally, Casanovo_ne accurately represents the digestion rules for most non-tryptic enzymes. As future work, we will modify Casanovo to take as input the identity of the digestion enzyme, alongside each spectrum. We hypothesize this approach will further improve Casanovo’s performance for samples prepared with alternative enzymes.

Genomic amplification of specific genes is a common mechanism of adaptation that also underpins many human disorders. We use yeast (Saccharomyces cerevisiae) to investigate the mechanism of one such gene amplification. When yeast are grown in sulfate-limited conditions for many generations, the population becomes dominated by cells possessing an inverted triplication of the SUL1 gene, which produces a sulfate transporter. Because of increased transporter levels, these cells have higher fitness in limited sulfate conditions. The Brewer Lab proposed a model — Origin Dependent Inverted Repeat Amplification (ODIRA) — where this gene amplification is initiated via a DNA replication error. In the ODIRA model, DNA replication fork regression at short inverted repeats leads to template switching of the replication machinery and the extrusion of a replication-competent hairpin molecule, which after replication, recombines at the original locus to produce an inverted triplication. An alternative explanation behind the amplification is that the hairpin molecule is generated by double-stranded DNA breaks (DSB). To distinguish between these possibilities, we used an engineered strain in which the selectable marker gene, URA3, is split into overlapping fragments (“ura” and “ra3”) on two different chromosomes. The complete URA3 gene is only present in yeast that undergo rare direct recombination between chromosomes or by recombination of the replicated hairpin formed by ODIRA or DSB. We used CRISPR-Cas9 to induce DSBs upstream of the ura fragment and identify the type of event that restores URA3 function with contour-clamped homogeneous electric field gels (CHEF gels), Southern blots, and polymerase chain reactions (PCR). If DSBs drive hairpin formation, cutting the chromosome upstream of the ura fragment should increase the frequency of URA3 assembly via hairpin intermediate. We demonstrate that double-stranded DNA breaks do not increase frequency of hairpin intermediates, providing further evidence that ODIRA is responsible for the inverted triplications of SUL1 in yeast.

Traditional vaccines use inactivated or live attenuated pathogens to elicit an effective adaptive immune response, but these vaccines can lack safety for immunocompromised individuals. Subunit vaccines–which display characteristic components of pathogens–are safe, stable, and readily engineered, but struggle to elicit a strong immune response. These next-generation vaccines require adjuvants (substances that stimulate the immune system) to increase efficacy. However, many currently used adjuvants lack well-understood mechanisms or wide applicability across vaccines. There is a need for new adjuvant platforms, and protein-based adjuvants are appealing because they are stable, readily engineered, and can be co-delivered with antigens on subunit vaccines. Toll-like Receptor (TLR) proteins are promising adjuvant targets that bind pathogen-associated molecules to activate the innate immune system. Of this family, TLR3 binds viral double-stranded RNA (dsRNA) and TLR5 binds the bacterial protein flagellin. Neither native agonist is a suitable adjuvant candidate; dsRNA is unstable and nonspecific and flagellin is degradation and aggregation-prone. Therefore, this project aims to design, test, and characterize novel protein-based adjuvants that can bind TLRs 3 and 5 and activate the immune system. Here, I test and characterize de novo mini-proteins that I have computationally designed to bind mouse TLR3 (mTLR3) and mouse TLR5 (mTLR5). I use yeast surface display, biolayer interferometry, and cell-surface binding assays to identify and characterize successful binders. Preliminary results show de novo mini-proteins specifically bind mTLR3 and mTLR5. Ultimately, this work hopes to provide a mouse model for these novel protein-based vaccine adjuvants with clinical aims. This project has wide-reaching public health implications, as vaccines offer the potential to improve the health and lives of countless individuals.

The Ubiquitin Proteasome System (UPS) is a molecular recycling machine, responsible for  proteolysis and protein activity regulation. The components of the UPS attach a small protein ubiquitin onto other proteins which directly affects their activity or serves as a signal calling for modification or lysis. Ubiquitin-conjugating enzymes (E2) and ubiquitin ligases (E3) are two classes of proteins that determine which proteins are tagged. Ube2W is an E2 with a unique function—it is the only E2 that places ubiquitin onto disordered N termini and amino acylated side chains. In this study we aim to elucidate the mechanism of reactivity and specificity of the enigmatic Ube2W. What structural and chemical features are responsible for its one-of-a-kind functionality? What does this imply about the role of this E2 on the cellular level? We designed a set of Ube2W mutants that had various putatively important features removed or changed to analogs from different E2s. We performed mutagenesis PCR followed by reactivity assays in the presence of known Ube2W substrates. We plan to collect NMR data for the Ube2W-substrate and Ube2W-ubiquitin interactions. We hope to determine which features are critical for this unique E2’s function by following the changes in reactivity when they are removed or altered. The interactions of substrates with these critical residues will help draft an outline for the precise mechanism. Improving our mechanistic understanding of Ube2W will pave the way for being able to control when and under what circumstances this unique biochemical reaction is used by the cell. This work aims to expand the current understanding of the UPS and aid in taming UPS-related diseases.

Deep learning methods for protein sequence and structure generation have shown remarkable success in many design scenarios when combined with structure prediction networks such as AlphaFold2. Despite this advance, many design challenges such as de novo binder design still haven’t been fully solved. Diffusion-based models have demonstrated considerable success in image and language generation yet their application in protein design has not yet been fully explored. Recently, the development of a protein diffusion model called RoseTTAFold Diffusion (RFdiffusion) has shown significant success in protein design and enabled us to explore the challenging problem of designing protein binders. Here I demonstrate utilization of RFdiffusion towards generation of de novo binders to disordered major histocompatibility complex (MHC) peptides. Specifically, we took an MHC peptide from KrasG12D and used RFdiffusion to generate a diverse range of structures that can bind this peptide. To optimize the sequence of these structures we used ProteinMPNN. We used AlphaFold2 to predict the structures of these optimized binders in complex with the peptide and saw promising interaction metrics. Further, structure prediction of the designs in complex with Kras wild type (WT) peptide resulted in lower AlphaFold2 confidence metrics of the interaction occurring. This is a promising preliminary result that RFdiffusion can generate fully de novo MHC-mimics, which can differentiate between neoantigens and WT peptide. Many cancers are caused by a single point mutation such as KrasG12D, thus, designing protein binders with point mutant specificity is exciting as it allows for targeting of disease causing proteins over healthy WT proteins. 

Trauma-induced coagulopathy is a severe complication of trauma that alters the normal mechanism of blood clotting through a number of complex factors. If clots are hypercoagulable, there is risk for dangerous vascular blockages. Conversely, if the clotting is hypocoagulable, it can lead to fatal hemorrhaging. Prior research indicates that actin has a major impact on platelet activity and blood clot formation. Actin is a highly abundant cytoskeletal protein that forms long, insoluble filaments. When released into the blood during cellular death, these filaments have complex effects on blood clot formation. Actin filaments can be integrated into the scaffolding of the clot, increasing strength. My experiment aims to investigate the roles of actin and on human blood clotting. Healthy donor whole blood in 3.2% sodium citrate was spiked with either a saline control or recombinant human skeletal muscle-derived actin (final concentration 200 nM) and allowed to incubate for 5 min. Samples were then activated with either 10 mM adenosine diphosphate (ADP) or 2 mg/mL collagen. The platelet aggregation response was then measured by impedance aggregometry. Each pair of control and actin conditions was run simultaneously. The impedance area under the curve (AUC) was compared between control and actin groups under each activation condition using a paired t-test with significance at p<0.05. Preliminary results show ADP was no different between the control and actin groups (p=0.400, n=5). The AUC in response to collagen was significantly higher in the presence of actin compared to control (p=0.005, n=7). Exogenous muscle actin appears to increase platelet aggregation through the collagen but not the ADP activation pathway. Further investigation is required to better characterize this interaction. A better understanding of the mechanisms of actin on hemostasis could direct research into pharmaceuticals and therapies that could yield better outcomes for trauma patients.
 

With cardiovascular disease being the leading cause of death worldwide, new and improved disease models are required to facilitate the research and production of new treatments. In this research, we are developing improved methods for modeling hypertension in engineered heart tissues (EHTs) to investigate resulting tissue remodeling at the tissue and cellular levels. We developed a model of hypertension using 3D-printed polylactic acid braces that enable stiffness adjustment of the flexible polydimethylsiloxane (PDMS) EHT platform. The braces were validated by mechanical testing to quantify their stiffening effect. Braces were shown to increase stiffness according to beam bending theory, with bracing half of the post’s length resulting in a 7-fold increase in stiffness. Next, we applied braces to tissues that only contain stromal cells, which are responsible for remodeling the extracellular matrix (ECM). The next steps are to quantify how stiffness affects ECM remodeling, including tissue-wide effects such as changes in tissue length and width, and micro-scale effects such as changes in cell migration, apoptosis, and cytoskeletal structure, which are quantified in 3D using IHC and confocal microscopy. We hypothesize that hypertension results in tissue thinning and lengthening, as well as decreased cell density, increased apoptosis, and increased expression of cytoskeletal markers. Next, the braces are applied to EHTs containing human induced pluripotent stem cell-derived cardiomyocytes (hiPSC-CMs). The effect of hypertension on EHT remodeling and hiPSC-CM maturation is then quantified using a custom MATLAB image processing suite. Finally, increasing systolic resistance of novel varieties of EHTs that incorporate hiPSC-derived cardiac fibroblasts (hiPSC-CFs) alongside cardiomyocytes enables evaluation of fibrotic remodeling. We hypothesize that hypertension promotes a hypertrophic response in both hiPSC-CMs and hiPSC-CFs in EHTs, displaying increased sarcomerization and fibrosis respectively. Developing this improved hypertension model will accelerate cardiac regenerative medicine research, and provide new approaches for drug discovery.

Melusin, a chaperone protein expressed in cardiac tissue, induces 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 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 mechanical stress, i.e., high afterload, will outperform the melKO EHTs. To measure this, I will increase the stiffness of the EHT posts and measure contractile force. I have successfully differentiated high-purity WT and melKO cardiomyocytes from iPSCs, essential for creating healthy EHTs. I will cast both WT and melKO tissues on a bed of silicone posts that can be stiffened to varying extents to induce different amounts of mechanical stress on the cells. I will conduct a western blot on EHTs from all treatment groups to determine the level of melusin expression and examine the expression of Heat Shock Proteins (Hsp) 70 and 90, due to their coregulation with melusin. The EHTs that undergo mechanical stress are expected to express melusin and these results will work to establish whether melusin expression in humans is activated by mechanical stress. I will measure and compare 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.

In the early stages of pathological hypertrophic cardiomyopathy, stress-induced signal transduction promotes the addition of new contractile units to maintain tensional homeostasis through poorly understood mechanisms. Our previous data shows that tension can be changed by altering the contractions within the cells. Inhibition of contraction by expression of D65A cTnC (point mutation on the calcium-binding site of troponin C) results in complete myofibrillar disarray. The mechanism behind the maintenance of myofibril and passive tension seen in these non-contractile CMs is not explained. Data has shown that microtubules provide resistance in the cell and go through rounds of rapid growth or disassembly based on the cell’s need which could be caused by the change in tensional homeostasis. With this in mind, my goal was to determine the role of microtubules in maintaining tensional homeostasis in response to changes in internal tension in CMs. Here, wild-type human induced pluripotent stem cell-derived cardiomyocytes were transduced to express cardiac troponin C with point mutations L48Q (hyper-contractile), I61Q (hypo-contractile), and D65A to study the effect of varying levels of contractility or internal load on microtubules. It was found that microtubular remodeling occurred where the noncontractile CMs had an increase in microtubule density. These noncontractile CMs were then cultures on nanopatterns that provided external tension via topological cues. In addition to the myofibrillar alignment seen previously, it was observed that microtubule density decreased further confirming that microtubules play a compensatory role in these CMs. The next step is to determine if a similar increase in microtubule density observed in the 2D culture is also seen on a tissue level by developing engineered heart tissues. This new data gives insight into how the microtubule remodeling in non-contractile and dysfunctional cardiomyocytes maintains tension in the early stages and its possible role in myofibril formation.

A “tough on crime” approach in the late 1900s ushered in more punitive sentencing than ever before in American history. As a result of mandatory minimums, three-strikes laws, and other harsh legislation, the American carceral state boomed. Not only were more people incarcerated, but they were incarcerated for longer periods of time. Since then, federal court cases have challenged the constitutionality of life and lengthy sentences, especially for individuals sentenced when they were juveniles. In the wake of these federal decisions, Washington state has enacted a variety of legal pathways towards post-conviction sentence review and early release. This study explores how learning of the possibility of early release affects incarcerated individuals who previously did not expect to have a chance at release. This research will be conducted through qualitative interviews and a survey with a sample of 12-15 individuals who served lengthy sentences and unexpectedly learned of a chance for early release. The findings of the research are expected to make a variety of contributions. First, the research will fill a gap in the literature on the social-psychological dimensions of imprisonment and on the significance of hope for incarcerated individuals. Second, this research will add qualitative insights to the largely policy-related literature on criminal sentencing. Third, the research may influence early-release policy by demonstrating potential benefits of such programs, which may positively contribute to less stringent sentencing and carceral practices. Fourthly, the research may help to shatter preconceived notions that individuals who have served life/lengthy sentences are “burdens” to society and instead replace such negative views with positive, prosocial, and communal experiences.

International criminal justice is often criticized for being unfairly selective in prosecuting cases. For instance, all suspects brought before the International Criminal Court in The Hague have come from Africa. This is despite the fact that human rights violations have been reported in many other parts of the world during this same period of time. Although restrictions in time and resources limit international courts’ and tribunals' capacity to prosecute all meritorious cases, the criteria used by the Prosecutors of these courts to determine which cases to pursue and which to disregard remain largely unknown, compromising the legitimacy of international criminal law in its application. This raises the question of why international criminal cases were only initiated in certain cases and not in others, and against particular suspects? To address these questions, this research examines four of the most prominent theories on selectivity in the application of international criminal law, including state capacity, popularity (that the courts will single out people from countries that have a bad reputation in their global affairs while granting leniency to others), crime severity, and victor's justice (countries with powerful positions within the international arena are most likely to escape international scrutiny). Most empirical research examines a single theory in isolation and employs a case study approach. However, I compiled an original dataset that encompasses all cases of international criminal law, from the Nuremberg Trials to the most recent cases of the International Criminal Court in order to test all four major theories systematically. I expect multivariate analysis to provide substantial support for the theory of victor's justice by showing that the power of a country correlates with the likelihood of international interference in the prosecution of international crimes committed in the country.

The American prison system is notorious for the mistreatment and abuse of the incarcerated people left in their care. In the past ten years there have been large pushes for prison reform; yet, these programs have had varying results across states. Why is it that some states have a much higher frequency of sexual assaults in prisons then others? I expect to find that prisons in Democratic-controlled states will have lower rates of sexual assault then their Republican-controlled counterparts. Literature on racial and social justice initiatives point to several differentiating factors between the two parties that aids in explaining this issue. Democrats are more likely to support social welfare and the Black Lives Matter movement, because racial justice activism is important to the Democratic coalition and subsequently their voter base. Additionally, Republican leadership supports tax and social welfare cuts while prison reform depends on subsidization from the government to work. In order to test this theory, I gathered data on sexual assaults in prisons from each state and compared them against each other, controlling for certain factors such as age, population and prison demographic. I ran a multivariate regression to see if Republican-controlled states experience greater frequencies of assault. This study focuses on an underserved population in the United States which greatly deserves thought and attention. Additionally, learning what factors contribute to violence in prisons helps provide a framework for improvements in our judicial system. Through research my goal is to contribute new information to a critical issue that has so far been largely understudied.

As of 2022 there are 103 million displaced people, of which 32.5 million are refugees, and 4.9 million are asylum seekers recognized by the United Nations High Commissioner for Refugees. As the number of displaced people grows, it becomes even more imperative that the United States offers asylum seekers a fair trial in court to pursue refuge in order to comply with the Universal Declaration of Human Rights, as well as to uphold strong ethical obligations based on foundational liberal values. However, today the right to seek asylum in U.S. immigration courts is undermined by the stark variation of adjudication rates between immigration judges. In this paper, I use original data from the Transactional Records Access Clearinghouse at Syracuse University to examine asylum adjudication variation systemically. Building from social identity theory, I hypothesize that asylum adjudication variation occurs due to the implicit bias exercised by judges based on their personal identities. I define implicit biases as unconscious learned biases that usually take the form of stereotypes and narratives that one automatically associates with particular people. Using a multivariate regression, I examine how the race, gender, political leanings, and religious affiliations of 314 judges correlate with the judges’ adjudication rate as well as the racial makeup of their asylum applicant pool. I expect to find that judges that have the characteristics of white, male, conservative and Christian will be more likely to deny asylum applications and I posit that this will have a disparate impact on asylum seekers who are black, brown, or are coming from majority Muslim countries.

According to the Corruptions Perception Index, Nepal is ranked 117 out of 180 countries for corruption with 12% of public service users having paid a bribe in the last 12 months. While many studies have analyzed systemic corruption within Nepal, little research has attempted to measure the magnitude of systemic corruption, with particularly limited literature on systemic healthcare corruption. To estimate the prevalence of petty systemic healthcare corruption (i.e. between the public and low-level public officials or doctors), I designed a survey guided by prior United Nations Office on Drugs and Crime and European Commission research, and a series of interviews with Nepalis. Bir Hospital was randomly selected among 5 other public hospitals in Kathmandu, and I administered the survey to 41 participants over two days. 43.2% of respondents paid more than they expected, and 68.6% of these respondents felt this payment was outside of their cultural norms. Moreover, 41.7% of the respondents paid cash directly to a doctor, which interviews indicated is atypical. No correlation was found between income and how respondents rated their care; moreover, no statistical significance was found using a t-test between how respondents rated their care and whether they paid cash directly to a doctor. However, odds ratio analysis on whether a payment was outside of cultural norms and whether the desired care was received yielded a ratio of 1.23, indicating that these payments mildly increased the probability of getting the desired care. This, paired with interviews indicating distrust of the hospital system and prior research demonstrating corruption throughout Nepal suggests systemic healthcare corruption in the form of bribes is prevalent, but does not necessarily guarantee better care. Further research must be done to not only determine the efficacy of this survey method, but also the validity of this model.

Microfinance institutions are considered pivotal in addressing poverty in low- and middle-income countries and providing financial inclusion through loans, savings, and insurance to those typically excluded from traditional banking. Most microloan recipients are women who own small businesses, and thus microfinance is regarded as pivotal to increasing women’s economic status. Some studies, however, highlight the rather lacking ability of microloans to improve household and business outcomes, as well as measures of women’s empowerment. My research explores if targeting such an agenda is the most effective way to uplift women and therefore help economic conditions in middle-income countries. I do this by examining the impact of microfinance loans on women’s autonomy in Vietnam by constructing a panel dataset from the 2006 and 2010 Vietnam Household Living Standards Surveys and designing a causal model. One channel through which microfinance empowers a woman is through her ability to financially contribute to the household, which in turn increases her decision-making ability, and thus changes gender relations in the household. In order to test increased decision-making, I calculate the share of resources in the household that are allocated to each woman and estimate changes in resource shares as a result of receiving a microloan. I expect results to show little to no increase in resource shares as the outcome of a household obtaining a microloan. In order to test changes in gender relations, I compare the previous results across Vietnam’s eight regions, which display varying levels of intimate partner violence. I expect regions with high rates of intimate partner violence to be negatively correlated with increased resource shares for women as compared to regions that have low rates of intimate partner violence. By addressing both the economic and social status of women, I illustrate a more complete picture of the efficacy of microfinance.

Over the last decade-and-a-half, China has seen its financial technology (fintech) industry achieve a level of scale and ubiquity without peer among developed economies — Alibaba’s Alipay and Tencent’s WeChat Pay, to name a few examples, each enjoy over one billion users, and are deeply integrated into daily life. Yet, by its hybrid nature, fintech presents complex challenges novel to both financial and technology regulation, the dramatic collapse of China’s peer-to-peer lending industry being a case in point. In this context, as much as Chinese firms lead the way in fintech development, Chinese regulators also act as innovators in the yet-undeveloped field of fintech regulation. As such, the study of the Chinese regulatory experience may yield insight into how other nations may develop their own regulatory frameworks towards fintech as an emerging industry. This research investigates the characteristics and challenges of Chinese fintech regulation. Specifically, this research considers the current institutional approach to regulation, the financial risks that current regulation seeks to address, and the effects of said regulation on the fintech industry. Given the novelty of fintech as a regulatory field, this research addresses a new and developing niche within the broader study of Chinese economic policymaking. I utilize a combination of general policy analysis and case study of specific regulatory actions to analyze both the regulatory process and its effect on the fintech industry. Qualitative analysis of regulatory documents and materials is complemented by quantitative analysis of industry-level data in examining both regulatory initiatives and their empirical economic effects upon fintech firms.This research is expected to yield the result that, because of its novelty and intersectionality, Chinese fintech regulation is underdeveloped relative to traditional finance or technology regulation. Simultaneously, this research is also expected to indicate a general trajectory towards greater regulatory scrutiny towards fintech firms.

Donald Trump’s presidency and its divisive legacy on the American government and its citizens continues to plague our society years after he has left office. It is crucial that policymakers and social scientists understand what values or grievances resonated with Trump’s voters and drove the rise of the Make America Great Again movement, in order to ensure that his voters do not continue to feel alienated from mainstream US politics. Through this paper I explore the electoral motivations of the US white working class, building on existing research that studies voting patterns and trends in previous presidential elections. I test two popular competing theories, pocketbook voting and social identity voting, and apply these theories to the context of the 2020 US presidential election. Pocketbook voting posits that voters respond to individual economic incentives and vote for who would benefit them economically, while social identity voting theorizes that individuals vote based on their subjective sense of belonging to an in-group and a desire to distinguish their group from others. I expect to find that white working class Trump voters were motivated by social identity voting, voting for Trump because of racial grievances and status anxieties. To conduct this study, I use a racial threat index and an economic well-being index, drawing from survey data to compare the social and economic grievances of white working class Trump voters. I expect to find that social identity voting, driven by factors such as status anxiety and racial threat, is a stronger electoral motivator than economic incentives, such as changes in wages or employment. Understanding such motivations lets us fight polarization and address the concerns of disenfranchised voters in future elections and in politics more broadly.

Policymakers in the United States often express concerns of their state tax base being reduced if taxes are increased because higher taxes will encourage richer taxpayers to relocate. The notion that a taxpayer’s decision to move is influenced by the level of taxation they experience is reinforced by current migration trends. In 2017, the Tax Cuts and Jobs Act placed a limit on the State and Local Tax (SALT) deduction, meaning that high income taxpayers have a limit on how much their state and local tax payments can reduce their federal tax burden. The increase of the share of state and local taxes in the overall tax burden of taxpayers is felt differently based on the level of taxation by state. I researched the extent to which the SALT deduction cap in the Tax Cuts and Jobs Act impacts interstate migration in the United States and its variation amongst different income groups. I conducted a difference in differences analysis using Internal Revenue Service Statistics of Income interstate migration data and taxation data from 2011 to 2020. There was an increase in the migration outflow from states with high taxation levels caused by the tax code change. Such increase was modest because taxation only marginally influences a person’s decision to relocate, compared to other factors such as job prospects and cost of living. This research shows that while the change in migration from taxation should be considered by state policymakers, the concern that the tax base will dramatically decrease from a tax increase is overblown. This research can be built upon by conducting a similar analysis in five to ten years to measure the long-term effects.

Year after year, catastrophic hurricanes rip through the mainland United States and its island territories. And yet, year after year, we hear stories of communities going without electricity or running water for months, disastrous temporary housing units and evacuations, and months-long wait times for immediate needs like food and medical care. Why has the Federal Emergency Management Agency (FEMA) failed to improve its distribution of disaster relief, even after three major reform bills? This paper seeks to provide an answer by investigating how corporate lobbying may be influencing FEMA’s allocation of relief funds between public and private actors. Considering the lucrative nature of post-disaster contracts awarded to corporations, they may use their lobbying powers to pressure the government to allocate more funds for private contracts and less to its Public Assistance (PA) program, which provides grants directly to state and local governments. FEMA’s preference for private contractors, despite their extensive history of performing inadequate work and defrauding the government, may be a significant part of the agency’s overall dysfunction. I conduct a multivariate regression analysis to determine the relationship between lobbying expenditures from top contractors and FEMA’s allocation of relief funds among public and private sectors between 2004 and 2021. I expect to find a positive relationship between these variables, suggesting lobbying does interfere with the delivery of post-disaster aid. Identifying the private sector’s influence in this area is critical to ensuring communities are properly supported after hurricanes and other natural disasters, which will only increase in frequency due to climate change.

 The spread of misinformation has increased rapidly in the last few years on many social media platforms. Our understanding of its effects, strategies, and influence is growing along with the information in real time. During political elections, we have seen that misinformation can become contagious and pose harmful threats to many aspects of our society and our political environment. How exactly does misinformation disseminate online, and are these social media posts used as a political strategy? To delve deeper into this study, I examine the relationship between false information online and legal cases that challenge election results. Using a mix of qualitative and quantitative methods, I analyze articles, data, and social media posts concerning the 2020 and 2022 elections in Maricopa County. With this data, I identify recurring narratives and influential political figures, using Python visualizations and codebooks for the empirical evidence found online. I anticipate that my findings reveal a pattern of legal cases being used to spread false political narratives that mislead the public about the voting process in Maricopa County. Since Maricopa County is the fourth most populous county in the United States, this study provides insight into how online users receive information about political elections and voting processes. I also anticipate that utilizing courts and election lawsuits can be an effective strategy to uphold and spread misinformation. Further research into other counties may demonstrate similar patterns and narratives with misinformation and U.S. elections.

Search engines are the primary gateways of information. However, the veracity of search results is often not considered before the search results are promoted to users. As the most popular video search engine, YouTube recommends misinformation on the treatment, spread, and origins of COVID-19, undermining public health efforts. Despite the global effects of COVID-19 misinformation, the majority of research is confined to the Global North, leaving the Global South behind. My research aims to qualitatively and quantitatively compare the exposure to COVID-19 misinformation on YouTube between a country in the Global North and Global South. I focused on the United States and South Africa, both of which have been heavily affected by the pandemic. Using 48 curated COVID-19 misinformation search queries, I systematically audited YouTube search results for 10 consecutive days with 12 programmed bots emulating “real” users in South Africa and the United States. This sock-puppet audit method ethically prevented harmful exposure to misinformation to real users and provided a scalable, controlled way to collect data. Then, I fact-checked the collected video results and trained a machine-learning model to scale the annotation process, allowing for the measurement of misinformation prevalence in different geolocations. My preliminary findings showed that YouTube search results differ by up to 20% between South Africa and the United States. Based on these early findings, I expect to see potential differences in the veracity and rankings of COVID-19 misinformation search results between users in South Africa and the United States. This research is the first to report a comparative investigation of COVID-19 misinformation on YouTube between a country in the Global North and Global South. It also establishes a novel method of conducting geolocation audits in different countries, paving the way for further audit research in the Global South and ensuring accountability for social media platforms.

The amount of online information is rapidly increasing, including an abundance of potentially misleading content. However, fact-checkers rely heavily on manual search methods to identify this content, leading to a significant investment of time and resources. While social media monitoring tools exist for platforms like Twitter and Facebook, such tools still need to be improved for video search platforms like YouTube. We collaborated with Africa's largest indigenous fact-checking organization – PesaCheck, during the 2022 Kenyan general election. The spread of rumors aimed at voter suppression gave an advantage to the tally of a specific presidential candidate, which created an urgent need for automated fact-checking systems. To address this issue, a team of undergraduates from the information school and computer science department developed a tool to automatically generate search queries related to significant events and topics for fact-checkers to monitor while providing them the flexibility to modify or create their queries. I was in charge of developing a method to identify video ids, extract the keywords with Natural Language Understanding (NLU), and the function that allowed users to choose keyword tags to characterize videos and then link them to the top search queries of the day. During the crucial period of the Kenyan election, ten full-time fact-checkers were using our tool to check and report falsities on the internet. During the four months of deploying this fact-checking tool, 42 misinformation discovery annotations were added by various fact-checkers, and over 500 misinformation queries were generated by the tool. As a result, the new Kenyan president emerged from one of the most competitive elections in the nation's history. Our research project will also be published as a case study paper to discover value-sensitive fact-checking systems through participatory design.

Software services often depend on storing or processing users' personal data. To promote responsible handling of this information, modern privacy legislation such as the General Data Protection Regulation and California Consumer Privacy Act impose strict regulation around demonstrable privacy enforcement for personal data. In addition to privacy legislation, increased social emphasis on accountability for privacy policies and individual user preferences has added requirements to many systems. This landscape creates interest in technical mechanisms for privacy compliance. Traditional privacy methods such as encryption or anonymization are important, but not sufficient, to address the more nuanced aspects of privacy regulations and policies such as data use requirements based on purpose, fine-grained personal data control, or obligations. An influx of research in both industry and academia seeks to confront this challenge of policy-based privacy enforcement. However, the interdisciplinary nature of privacy, wide variety of approaches, and common gap between theory and software development makes it difficult to navigate the space. To help, this research project presents a systematization of policy-based privacy enforcement with a focus on practical software mechanisms, implementations and frequently adopted privacy-by-policy design patterns. It considers deriving software requirements from natural language requirements, expressing privacy conditions in privacy languages, managing data access with privacy conditions, restricting data flow for privacy, and leveraging logs and audits. Within these domains, the research project explores common approaches, mechanisms, and methodologies and further describes key insights, gaps, and future directions for policy-based privacy enforcement. 

There are an estimated 500,000 people in the U.S. who are deaf and use American Sign Language (ASL). Compared to the general population, deaf people are at greater risk of having chronic health problems and experience significant health disparities and inequities (Sanfacon, Leffers, Miller, Stabbe, DeWindt, Wagner, & Kushalnagar, 2020; Kushalnagar, Reesman, Holcomb, & Ryan, 2019; Kushalnagar & Miller, 2019). The longstanding history of inequitable access to language and education, and a lack of printed information and materials, leave people who are deaf and who use ASL unaware of opportunities to participate in cutting-edge research/clinical trials (Kushalnagar & Miller, 2019; Lesch, Brucher, Chapple, R., & Chapple, K., 2019; Smith & Chin, 2012). An unintended consequence, therefore, is that Principle Investigators (PIs) neglect to include ASL signers who are deaf in their subject sample pools, and this marginalized population continues to be at disparity for both health outcomes and clinical research participation. One barrier is the unavailability of informed consent materials that are accessible in ASL. The current research study conducted by our team at the Center for Deaf Health Equity at Gallaudet University attempts to address the language barrier to the consent process through a careful reconsideration of its traditional English format and the development of an American Sign Language (ASL) informed consent app. As part of the project, I successfully leveraged existing machine learning methods to develop a way to navigate and signature an informed consent process using ASL. I call this new method of navigation and signature “ASL Interactability.” In my findings, I found that deaf people who are primarily college educated felt that the process for obtaining ASL consent through an accessible app is just as fluid and easy to understand as traditional English consent. These findings not only show the potential of ASL Interactability in the informed consent process, but in any other digital application that requires the user to interact (e.g. to move between pages, to provide signature, etc).

International students transition from a controlled environment in their home countries to an unfamiliar one with new culture in their host country. This highly complex change can bring about information seeking needs to navigate everyday life. As a result, international students may turn to their host university for answers and resources. This research study aims to examine the perceptions of undergraduate international students at the University of Washington (UW) with regard to the support they receive from their host university for their everyday life information seeking (ELIS) needs. The question guiding this study is: How do perceptions of support from the host university in everyday-life information seeking of 1st-year international students compare with those of 4th-year international students? Findings will be based on data from a survey of UW undergraduate international students about their perceptions of support from their host university. Results of this research study will contribute to the scholarship of Culture Learning Theory, which concerns the challenges experienced by sojourners in navigating through a new culture. Moreover, the findings have scope to support host universities as well as organizations within the host university that serve international students. I plan to disseminate a findings report to UW institutions such as International Student Services (ISS), Foundation for International Understanding Through Students (FIUTS), Center for International Relations and Cultural Leadership Exchange (CIRLCLE), etc. The report will contain a robust data analysis of the satisfaction of international students at UW, and will detail future recommendations from the participants about what will improve their experience abroad. By conducting research on the perceptions of international students pertaining to the support they receive from the host university for their ELIS needs, both scholars and university staff will gain perspective on how international students experience information-seeking aspects of culture learning.

This study examines how undergraduate students majoring in humanities and social sciences navigate the institutional culture of higher education (HE) through a case study at the University of Washington. I identify two different logics within HE that contribute to its institutional culture — the industry logic and the social institution logic. The industry logic refers to the growing trend of business and industry orientations in HE — especially since the emergence of neoliberalism in the 1970s. The social institution logic is the more traditional ideal of HE that aims to cultivate values of citizenship and morals. The goal of this study is to examine how undergraduate students understand and respond to changes in institutional culture. While the commodification of HE is well studied, scholarly attention neglects its evolution and fails to articulate students’ response to this shift. This study is inductive and qualitative — focusing on undergraduate experiences and how students give cultural meaning to their experiences under varying institutional culture. I will conduct 12 semi-structured interviews with undergraduate students majoring in humanities or social sciences to understand their college experiences. Though the anticipated results of the study have yet to be determined due to the inductive nature, I hope to examine how students reconcile their passions and actual experiences under institutional culture of HE. Any disparities observed between universities as institutions and students as agentic individuals might reveal the neglected demands within society. This research will provide insights to which kind of education system our society needs today, which will lead to better policies about the future development of HE.

Several factors influence students’ ability to access the disability accommodations necessary to complete coursework; one of the main factors, however, is the degree to which instructors are willing or able to accommodate their students’ needs. Crucially, students often need to discern if instructors will accommodate their needs before they can register for class. Students must navigate differences in communication styles and perspectives on what constitutes reasonable accommodation. Further, instructors’ knowledge of their own responsibilities, rights, and the process by which accommodations are accessed, is limited. Instructors are not made aware of their role in providing accommodations or the timeline for their involvement. They are often reluctant to provide assistance for fear of overstepping boundaries set by their institutions. The ambiguity of the instructor’s role in accessibility is actively causing harm. Multiply-marginalized students face a number of additional barriers: students who have less wealth have impaired access to healthcare, and are more likely to face poor healthcare outcomes. Further, the effects of marginalization ensure that students with intersectional identities are less likely to be wealthy. While these facts are rarely officially disputed, it is often difficult to determine what supports are missing, why they are missing, and how support can be provided to the benefit of all stakeholders. In order to establish how students and instructor perceptions differ from each other and from the recommended process, more data is sorely needed; this study utilized a basic survey to identify the areas in which instructors and students need further support. Most queries were designed to have quantifiable responses; freeform responses were evaluated to identify the most common topics and positionality respondents presented. Responses which directly oposed the most common positionalities were then quantified. Expected results largely aligned with known areas of need, specifically the need for more transparency and training surrounding accessibility. 

Within the United States, anxiety disorders are the most prevalent mental disorders in adults (Stein et al., 2017), and the use of online platforms to receive support for the disorders has significantly increased (Pendse et al., 2019). Current research has illustrated the promise of online communities in meeting support needs. To build on these findings, I will examine how users elicit support, and whether certain elicitation strategies receive greater engagement from other community members. Thus, using content analysis, this study compares the strategies posters employ to request social support, the types of support (i.e., informational, emotional, esteem, social presence) that creators request, and the frequency of responses that creators receive, by examining r/Anxiety posts with the most (n=100), and least (n=100), engagement. I am contributing to the interpersonal communication literature through my adaptation of support marshaling in an online context (Crowley et al., 2016), to answer: How do posters of the r/Anxiety subreddit elicit support? What type of support do posters request most often? How do posts with more replies differ from those with fewer responses? I anticipate emergent results will indicate that the creators utilizing multiple forms of support elicitation will have greater engagement from the r/Anxiety community. This work will start to fill the gap in knowledge of support marshaling strategies present within anxiety online forums while providing more knowledge about how posters can use the results to form engaging posts and recieve more support.

Photovoice is a research methodology that uses photography as a tool for participants to express their thoughts on a topic of interest. Our project is specified towards marginalized communities and to give them a voice regarding issues each group faces. The main purpose of photovoice is to create change in our community by analyzing photographs provided by the participants.

Recent publications of photovoice projects at universities have yet to focus on a number of groups and their experiences on campus. We have decided to create a photovoice project specifically tailored to this area of interest.

This project focuses on four groups in the University of Washington Bothell campus: Students of Color, Muslim students, LGBTQ students, and first-generation students. 15 students participated in this study, with around 2 to 4 participants in each group. Our goal is to learn how these groups experience college/university differently compared to students outside of these groups. We asked participants to answer prompts that discuss how they experienced college academically, socially, and emotionally. Thus, we analyzed their experiences and formatted them into differing “codes” and “themes”.

Most themes in the project overlapped between the groups. The three notable themes were (1) The disconnect between faculty and students, (2) Expectations of what students should have and have access to, and (3) Struggling in finding ways to express oneself. Two more themes are to be created from the data we collected.

The project is still under development, and we are expecting to analyze these themes more in-depth. The goal of this project is to highlight disparities in the universities’ process of matriculation. Moreover, we hope to use this research to revise the assumptions and rules regarding resources and general student welfare to create more accessible resources and a streamlined transition from primary to secondary education.

Negative life events play an etiological role in posttraumatic stress disorder (PTSD) and depression. Social support and disclosure are associated with resilience following negative events. This secondary analysis examined the relationship between disclosure to specific individuals following negative events and current depression and PTSD symptom severity. Female-identifying undergraduate students (N = 101) were asked to describe "the most negative event" they experienced in the past year and identify individuals to whom they disclosed (e.g. friend, partner, parent, therapist, law enforcement, teacher, and university employee). Using path analyses, I examined whether: 1) for female-identifying undergraduates (n = 89), the identity of the individual to whom participants disclosed their negative memory was correlated with current severity of depression symptoms (Quick Inventory of Depressive Symptoms) and 2) for those who experienced a DSM Criterion A trauma (n = 12), identity of the individual to whom participants disclosed the event was correlated with current PTSD symptom severity (Posttraumatic Diagnostic Scale). Disclosure of negative events to professionals (law enforcement, teachers, university employees, and therapists) were associated, at a trend level, with higher depression severity (B = .56, p = .07); driven by an effect of disclosing to a therapist (B = .96, p = .04), while no strong association was found for disclosure to personal confidantes (friends, parents, and partners). Disclosure of Criterion A traumatic events to partners was associated with higher depression (B = 1.33, p = .07). These findings complicate literature on the mental health correlates of disclosure, which may be associated with increased depression and PTSD symptom severity following negative events, and emphasize the need for trauma-informed care for mandated reporters and others working with individuals who may disclose negative events. 

Racial and ethnic minority groups are less likely to seek or have access to mental health support services. Despite an increase in the quantity of mental health services nationwide, disparities in usage across racial and ethnic minority groups still exist, leaving resources underutilized and many individuals with unmet needs. Previous studies highlight both structural and non-structural barriers, such as income and stigma, which prevent certain racial groups from fully utilizing health care services. Studies often overlook health outcomes associated with immigrant status and overgeneralize findings to all populations. While scholars have studied the structural barriers to accessing mental health care services, there is a need to understand the cultural contexts preventing racial and ethnic groups from reaching out to these services. Using data from the National Health Interview Survey (NHIS), this study examines differences in access to and utilization of mental health care services of U.S born and immigrant populations from the years 2010-2020. The NHIS allows for the control and determination of effects of both structural and cultural factors such as health insurance coverage, financial instability, racial and ethnic characteristics, and migrant status to further understand the dynamics of access to and use of mental health care services. Foreign-born individuals are expected to show lower access to health care resources with varying levels of moderate mental distress. These differences are expected to vary for those who have spent more time in the U.S with more access to resources and higher levels of mental distress. Understanding trends related to mental health care can help develop better public policy responses and improve the promotion of health care services. This study will help address why services are underutilized and how to minimize health service inequalities among racial and ethnic populations. 

Emergency medical services (EMS) are an essential part of the healthcare system in the United States. However, there are many barriers to EMS use among racial and ethnic minorities, which can lead to poorer health outcomes. Language discordance is a crucial barrier that needs to be addressed. My project addresses the interactions between patients with limited English Proficiency skills (LEP) and emergency services in King County. We have partnered with Puget Sound, Bellevue Fire Department, and Renton Regional Fire Authorities to identify patient care data in LEP Spanish-speaking patients. To better understand the experiences and future needs of non-English speaking patrons of these services, we have developed a multi-model survey to collect data and assess communication satisfaction with EMS providers. We also provide a letter explaining the purpose of the project we have designed to inform participants why we are collecting this data and what we hope to accomplish. Data is being collected via an English or Spanish mailed/online survey. The survey includes topics related to the language spoken at home, English proficiency, and questions related to emergency services received in the last six months. From preliminary data collection, we have found that a recurring barrier was diminished access to interpreter services. With increased access to interpreter services, patient experiences will improve. From these pieces of data, our next steps are to introduce phase two, which includes partnering with other fire departments in the area, the Vulnerable Populations Strategic Initiative (VPSI), and sending surveys to LEP Chinese and Somali-speaking patients to obtain a more extensive scope of data. We plan to implement informational workshops in King County fire departments to explain the impacts of language barriers and provide solutions to address these inequities.

 Historical discourse has dangerously misrepresented and normalized the positioning of Black women in various states of vulnerability. Such discourses have then been embodied by society and further perpetuated within institutions- shaping the realities of Black women. This study explored how social services at a Seattle-based women’s shelter affect the experiences of Black women utilizing social services, while also understanding how Black women thrive utilizing such services. In this community-based qualitative research project, I used ethnographic methods to conduct semi-structured interviews with Black women utilizing social services at a Seattle-based womens shelter. I also conducted participant-observation methods to collect data on the shelter’s environment and the dynamic between Black women seeking services and employees providing services. Finally, I reviewed relevant theoretical frameworks such as intersectionality, the criminalization of poverty, and racial capitalism to assist in my analysis of how Black women seeking services at a Seattle women’s shelter have been positioned to experience vulnerability. Key findings include 1) social services have been socially constructed to sustain the experience of vulnerability within the Black community, specifically by Black women utilizing services; and 2) through various levels of gratitude, Black women find spiritual peace and grow new resiliences to systemic challenges. These findings draw awareness to the ways social services have deepened Black women’s dependency to them. Such awareness could serve as a critical framework for reshaping the way social services within the greater Seattle area assist Black women to promote prosperity, dismantle racist rhetoric, and aim to eradicate, not perpetuate, homelessness.

Implicit bias refers to unconscious attitudes and stereotypes in patient-provider communication that can lead to discrimination based on race, sexual orientation, gender, or other characteristics. This disproportionately impacts historically marginalized communities, including Black, Indigenous, and People of Color (BIPOC) and Lesbian, Gay, Bisexual, Transgender, Queer, and/or Questioning people (LGBTQ+). Although interventions have been developed to improve provider awareness of implicit bias, there has been little exploration of patient perspectives. With the help of my team, I conducted an analysis of 7 previously conducted co-design workshops with 32 BIPOC and LGBTQ+ people to understand patient perspectives on interventions to mitigate the impact of provider implicit bias in healthcare interactions. These workshops included group discussions about personal experiences with healthcare discrimination and a storyboarding activity to envision solutions for improving patient-provider interactions. Across workshops, participants created 13 storyboards that depict solutions in a primary care setting, several of which focus on improving patient-provider communication and promoting self-advocacy and empowerment. Through our collaborative qualitative analysis, my team and I identified two prominent themes from the workshops: communication tools and patient advocates. Participants shared experiences of feeling dismissed and unheard during healthcare visits, leading to storyboard proposals of communication tools, such as "smart boards" that allow patients to describe their symptoms in a nuanced manner. Another storyboard proposed a "panic button" that helps patients ask for help or request a different provider. Other storyboards focus on strategies to hold providers accountable, such as a "patient advocate" who approaches the provider about the patient's experience of discrimination and recommends a communication training intervention that raises awareness of bias. These findings can inform future research on interventions to address implicit bias in provider-patient communication. By prioritizing patient perspectives, we can create a healthcare system that is equitable and inclusive for all.

Although social Virtual Reality (VR) has attracted increasing attention as a new way for people to interact, it faces challenges with harassment, a problem other social platforms face as well, online gaming communities in particular. The embodied environment social VR provides also brings new forms of harassment compared to social media, requiring effective responses from social VR platforms. We examined the safety features of four popular social VR games: VRChat, Horizon World, Altspace, and RecRoom to learn the standard safety practices. To understand how social VR communities share and respond to harassment experiences, we collected 134 posts and comments from online communities for these games on Reddit, Twitter, and Oculus Forum. We used inductive coding to identify themes and trends. We found that the four social VR games have common safety features such as Personal Bubble, Block, and Report, but these features differ in name, effect, and ease of access. This can pose an increased learning curve for players and make them less aware of these functionalities. From the online posts, we found the most common harassment experiences include hate, unwanted sexual attention, and embodied sexual harassment. The most common response to harassment experiences is suggesting strategies or resources. However, these responses include a mix of positive (e.g., empathetic, supportive), neutral, and negative (e.g., gaslighting) tones. We also found a difference between the most commonly adopted safety feature and the most recommended feature, where the former is Personal Bubble and the latter is Block. Based on the findings, we provide design implications to improve safety features and build easier-to-access and informed safety systems for social VR games. This research contributes to developing a more inclusive environment for players from diverse backgrounds and identities by identifying opportunities to provide better safety features and improve safety norms in virtual worlds.

Our research group is exploring the feasibility of utilizing nanopore sensors for protein sequencing, whose compact size and ability to facilitate extremely long, uninterrupted reads of protein strands upstage the current procedure of using complex, expensive mass spectrometry (MS) devices. My project predicts the sensor’s raw signal data using a carefully tested combination of each amino acid’s volume and charge properties. Using my model to generate predictions for a specific database of proteins, I can compare the unknown raw signal to each of the predicted signals to single out the best matching/correct sequence. While the protein space of De Novo sequencing is vast (20 to the power of protein sequence length), this method effectively shrinks the protein space to a group of substantive, feasible sequences. Employing the current predictive model on a database of synthetic and natural proteins, when compared against an unknown protein’s raw signal, I found that, on average, the correct prediction consistently ranked within the 99th percentile of matches among a predicted test set of >20,000 sequences. Advancing single-protein sequencing can revolutionize protein research by enabling the identification of low-abundance proteins. Additionally, the increased sensitivity of the nanopore sensor could shed light on the so-called "human dark proteome," composed of approximately 3,000 human proteins that have not yet been identified despite genetic evidence of their existence.

Methanotrophs are prokaryotes that naturally consume the potent greenhouse gas methane for energy. Through metabolic engineering at an industrial scale, these microorganisms hold potential to mitigate the contribution of methane emissions to global warming. In particular, Methylotuvimicrobium buryatense can sustain robust growth both in nature and experimental settings; it is a promising engineering candidate. To develop a robust metabolic engineering platform using M. buryatense, biologists require a deeper understanding of the genetic mechanisms by which it functions. Here, I present an open-source software tool designed to interactively explore the transcriptome of M. buryatense. By integrating bulk RNA-seq datasets collected from experiments over the past decade and applying an array of unsupervised machine learning clustering algorithms, we cluster genes by their expression profiles in differing growth conditions. These gene clusters are annotated with gene ontology (GO) terms using statistical enrichment analysis to assist in functional interpretation of the clusters and the genes that comprise them. To enhance domain-expert researchers’ ability to explore and drill-down into specific queries, I unify these cluster-specific analyses in a web-hosted tool using interactive data visualization techniques centered on a ReactJS frontend and Azure Cloud backend. With both exploratory and query-focused use cases, this software tool can support M. buryatense biologist workflows for predicting functions of hypothetical proteins, showcase new or confirming putative regulatory processes, and generate new experimental hypotheses from the presented transcriptomic trends.

Chronic wounds present a significant burden on healthcare systems worldwide and have a substantial impact on the health and quality of life of affected individuals. The prevalence of chronic wounds is estimated to be 1 to 2% of the population in developed countries, with annual costs ranging from $20 to $50 billion in the United States alone. With an aging population and an increase in conditions such as diabetes, the prevalence of chronic wounds is expected to increase in the coming years. Innovative approaches are required to manage chronic wounds effectively, given the challenges faced by healthcare providers, including overburdened hospitals, inconsistent assessment and documentation by home health nurses, and patient-related barriers in the outpatient setting. One promising solution is the integration of smartphone technology that utilizes the sophisticated imaging capabilities of mobile devices to enable more precise, rapid, and reliable assessments. This project proposes the development of a smartphone-based chronic wound management system that utilizes machine learning (ML) models to gather accurate data on wound measurements and descriptors. The system leverages depth imaging technology on modern smartphones to produce photographs and 3-D scans of the wound, enabling the automated generation of accurate wound measurements and descriptors. These measurements include wound length, width, maximum depth, average depth, surface area, and volume, while descriptors include the percentage of wound epithelization, granulation, slough, and necrosis. The proposed work stems from collaboration with home nurses on a previous study of stoma patient care, with an extension of this study resulting from exposure to the NSF I-Corp grant; it aims to enhance the management of chronic wounds, with a smartphone-based system that facilitates efficient and precise documentation and assessment of patients' wounds. My main role in this project is to provide support in proposal editing, pitch deck creation, and conducting patient interviews to gather information about their current needs and identify helpful technologies; addressing patients' concerns and feedback, and working to incorporate new features into our system to better meet their needs.The system's use of depth imaging technology and ML models will enable healthcare providers to gather accurate data more efficiently and accurately, leading to better patient outcomes and reduced healthcare costs.

Clearance of wound infections can be hindered by a bacterial biofilm; a complex extracellular matrix (EM) secreted by adherent bacteria that allows them to evade the host immune system and obviate antibiotics. A novel, synthetic peptide—known as an anti-α-sheet inhibitor—can disrupt biofilm stability by inhibiting the formation of amyloid fibrils, which contribute to the biofilm EM. This project aims to design and characterize alginate porous scaffolds that elute these synthetic peptides, for use as anti-biofilm wound dressings. The physical properties and peptide release kinetics of the scaffolds will be optimized for clinical applications, supported by in vitro efficacy studies with live bacteria. This project draws upon past work from the Bryers Research Group on engineering infection immunity and tissue scaffolds, in which biofilms are prevalent. Results of this project will provide an alternative approach to biofilm prevention, thus reducing the burden of biofilm-related infection complications.

In the body, cells grow in the extracellular matrix (ECM), which presents biochemical and mechanical signals to the cells inside. Hydrogel biomaterials are water-laden polymer networks that can mimic the properties of the ECM, allowing controlled study of cellular behavior in vitro. Many cells are mechanosensitive, but mechanical cues other than stiffness have not been fully investigated. This project aims to develop a platform in which degradability and strain can be activated by a researcher bio-orthogonally. We have synthesized a cyclic peptide crosslinker for a synthetic poly(ethylene glycol) hydrogel that acts as a Boolean AND-gate: one half is degradable by cell-secreted enzymes, and the other half is degradable by sortase, a bacterial enzyme, added by a researcher. We quantified the degradation of hydrogels made with this crosslink via fluorescence release and demonstrated that degradation only occurs after exposure to both enzymatic inputs. We further demonstrated that cells encapsulated in this material retain strong viability. We predict that cells will be unable to spread in this material until after a researcher adds sortase. After sortase addition, we expect that contractile cells will be able to locally degrade the material, spread, and generate strain. We intend to quantify spreading and strain with encapsulated fibroblasts. We also plan to use this platform to study development, by encapsulating immature cardiac stem cells and investigating the effect of fibroblast driven strain as a model; we predict that strain will trigger further specification of these immature cells. In addition to understanding the pathways for development, this research may help identify new therapeutic targets for disease, and it will also inform new strategies to grow tissue in vitro that more closely mimic the native environment.

Across a variety of signaling pathways, soluble factors in the extracellular matrix bind to protein receptors that span the cell wall, thereby triggering an information cascade that affects cell activity or function. It follows that by controlling the binding of signaling factors to these receptors, cell behavior and activity can be guided with substantial precision. In this project, we aim to design a system that allows de novo-developed protein agonists and antagonists, referred to as binders, to be activated with a high degree of temporal and spatial control within cell-encapsulating hydrogels. Towards this end, we employ methods derived from protein semisynthesis and click chemistry to tether binders to the hydrogel polymer network and then subsequently photo-release them from the network. We expect a difference in the functionality of binders when they are bound to the network compared to when they are released through light exposure and solubilized, thus achieving light-dependent control of the binder-receptor interaction and cell activity. This system will be the first to employ de novo developed agonist and antagonist biomolecules for the interrogation and control of cellular behavior. In so doing, it will expand the tool box of biomaterial engineering to include finer control over cells grown in 3D matrices, with direct implications in fields as diverse as therapeutic development, regenerative medicine, and organ-on-a-chip engineering.

Reproductive and developmental toxicology is an area of importance for public health. Current in vivo methods of reproductive and developmental toxicity testing require large cohorts of animals, lengthy experiment times, and high cost. In vitro models using cultured cells align with the three R’s of toxicology: to replace, reduce, and refine the use of animals in toxicity testing. Our group is developing an in-vitro model of neonatal testis to study developmental testis toxicity while reducing animal use. To test the physiological relevance of our in-vitro model, I collected post-natal day five testis for immunohistochemical analyses. I dissected the testis from the surrounding tissue, fixed the tissue in formaldehyde solution, and left in a sucrose solution overnight. The fixed tissues were then frozen for cryosectioning. I sectioned the frozen tissue into 20µm sections using a cryostat and adhered them to microscope slides. To improve staining, I washed the adhered samples and permeabilized the membranes with detergent. I incubated each sample with fluorescent antibodies to target functional proteins and cell type markers. To visualize the targets of interest in the tissue sample, I used a confocal microscope to generate stacks of images through each section. I will next perform the same staining procedure on the in vitro culture samples for comparison. My poster presentation will present confocal microscopy images showing localization of these functional and cell type markers. These images will provide a comparison to our group’s in-vitro models. These images also give insight to healthy testis formation which can be compared to abnormalities in future pathological studies.

Blast exposure via detonation of explosives results in symptoms such as mild traumatic brain injury, post-traumatic stress disorder, and chronic pain, serving as a major source of trauma for service members, Veterans, and civilian bystanders. These effects characterize the polytrauma clinical triad and pose a risk factor for increased substance use and substance use disorder (SUD). This polytrauma exposure yields diverse symptom trajectories. To understand the interactions between polytrauma and SUD risk, we use a rodent model that utilizes custom, in-house-built polysubstance self-administration chambers, Socially Integrated Polysubstance (SIP) cages, to measure water, alcohol, and fentanyl intake. Two types of tracking are used to monitor drinking: Radio Frequency Identification (RFID) tracking and the volumetric drinking monitor, and these combined tell us which mouse drinks what liquid for a variable period of time. These SIP cages have the advantage to study both voluntary drinking habits and preferences as well as the effect of group housing on these patterns. For this project, we used 69 C57Bl/6 male and female mice aged 9 weeks on arrival. These mice were then single or group-housed in the SIP cages for 9 days to monitor drinking patterns. Testing multiple substances at once can give us valuable insight into substance preference and polysubstance use, making it more representative of the human experience. These mice had behavioral testing before entrance into the SIP cages, and we will explore different methods to characterize these drinking and anxiety subgroups that emerge. In addition, we plan to look at sex differences and how that changes substance use and preference. These factors combined will give valuable insight into classifying substance use that can lead to more optimized treatment for Veterans with polytrauma.

Alzheimer’s disease (AD) is characterized by aberrant cleavage of Amyloid Precursor Protein (APP) leading to toxic β-Amyloid (Aβ) peptide aggregates. Presenilin 1 (PSEN1), and presenilin 2 (PSEN2) are intimately involved in this process. We found that alternative splicing of PSEN2 leads to the increased inclusion of a cryptic exon (part of the RNA that codes for a protein), in the typically non-coding intron 9 of PSEN2, titled exon 9B (PS2x9B), which has elevated abundance in individuals with sporadic AD. My aim is to uncover the link between PS2x9B and sporadic AD. I designed a PCR approach to measure the ratio of PS2x9B inclusion compared to non-mutated Wild Type (WT) in cDNA generated from parietal and temporal lobe tissue samples. I distinguished PS2x9B inclusion by amplicon size on a gel and measured the ratio to WT via band intensity using ImageJ. I found that the ratio of PS2x9B inclusion was significantly elevated in sporadic AD cases in the parietal lobe (p = 0.02) and the temporal gyrus (p = <0.001). Next I transfected SH-Sy5y cells with plasmids containing either WT or PS2x9B PSEN2 joined to a Flag-tag. I extracted proteins from these cells and control empty plasmids, and used Western blot to examine size differences between each plasmid’s protein products to research the impact of PS2x9B inclusion on PSEN2 protein levels. I hypothesize that inclusion of PS2x9B will lead to truncated proteins due to an early stop codon. Additionally, I am working to establish the consequences of PS2x9B on APP processing and Aβ cleavage. I expect that PS2x9B could cause either an increase in Aβ production or modify its length. These findings will allow us to expand our understanding of PSEN2 and alternative splicing in sporadic AD which could guide development of novel gene therapy treatments for AD.

 

Justice-centered approaches to equitable computer science (CS) education frame CS learning as a means for advancing peace, antiracism, and social justice rather than war, empire, and corporations. However, most research in justice-centered approaches in CS education focus on K--12 learning environments. In this position paper, we review justice-centered approaches to CS education, problematize the lack of justice-centered approaches to CS in higher education in particular, and describe a justice-centered approach for undergraduate Data Structures and Algorithms. Our approach emphasizes three components: (1) ethics: critiques the sociopolitical values of data structure and algorithm design as well as the underlying logics of dominant computing culture; (2) identity: draws on culturally responsive-sustaining pedagogies to emphasize student identity as rooted in resistance to the dominant computing culture; and (3) political vision: ensures the rightful presence of political struggles by reauthoring rights to frame CS learning as a force for social justice. Through a case study of this \emph{Critical Comparative Data Structures and Algorithms} pedagogy, we argue that justice-centered approaches to higher CS education can help all computing students not only learn about the ethical implications of nominally technical concepts, but also develop greater respect for diverse epistemologies, cultures, and experiences surrounding computing that are essential to creating the socially-just worlds we need.

Major Depressive Disorder (MDD) is one of the fastest growing causes of global disability and requires a variety of treatment options due to its multifactorial etiology. While it’s long been known that blood levels of the neurotransmitter GABA are predictive of MDD, recent studies have implicated the human microbiome as a potent GABA metabolizer that can affect circulating GABA levels. Our collaborators used bioinformatics to identify bacteria containing putative GABA-synthesizing genes (puuD) that are predictive of host GABA levels and depression scores. However, previous literature indicates that the puu operon is repressed under anaerobic conditions in E. coli and the putative PuuD proteins have low sequence similarity to the model PuuD enzyme. My project seeks to confirm the biochemical activity and substrate-specificity of these genes using in-vitro assays measuring both the putative PuuDs’ chemical reactivity and kinetics. Due to conservation in the active site structures between the putative proteins and the model PuuD, I expect that the novel PuuD-like proteins will have gamma-glutamyl hydrolase activity and substrate specificity for gamma-glutamylated-GABA. This work provides base-level evidence for the use of systems biology techniques to identify enzymatic function and lays the foundation for targeted therapeutics manipulating the microbiome for improved MDD outcomes.

Semiconductors are integral to many industries. As electronics trend towards more powerful devices, research efforts now focus on developing tools with the ability to achieve higher feature densities, such as the use of extreme ultraviolet (EUV) photolithography. Current photoresist technologies center around the use of 193 nm wavelength light with photo-sensitive organic thin films. However, these tools cannot produce feature sizes smaller than 20 nm. To overcome this limitation, semiconductor manufacturing is exploring 13.5 nm (EUV) wavelength light. Current commercial polymer photoresists lose sensitivity at this wavelength due to their low atomic absorption and photoemission of EUV light. Transition metal atoms have higher EUV absorption and can be incorporated to improve polymer photoresist sensitivity. To that end, molecular layer deposition (MLD) is a promising, scalable tool capable of creating thin films with angstrom-level precision. Unlike other deposition techniques, MLD does not require the use of solvents for deposition, boasts high compositional control, and is area selective deposition capable. In this work, the synthesis, characterization, and stability of novel thin films deposited using MLD are tested to determine their suitability as EUV photoresists, with the goal of improving semiconductor feature density, reducing the use of hazardous solvents, and decreasing energy and material costs in semiconductor production. Six films were studied using diethyl zinc (DEZ) as an inorganic EUV absorbent with six organic reactants: ethylene glycol; cis-2-butene-1,4-diol; 2-Methylene-1,3-propanediol; 1,5-hexadiene-3,4-diol; 1,4-butyne diol; and 3,4-dihydroxy-1-butene. Film thickness was measured using ellipsometry. Photosensitivity was measured upon exposure to 254 nm wavelength UV-C light. Degradation upon solvent exposure in an inert environment was examined using acetone, chloroform, ethanol, toluene, and deionized water, which proved most effective at removing the films, with thickness reductions up to ~90%. Results of solvent stability and light sensitivity will be used to propose new EUV photoresist processes for production-scale semiconductor manufacturing.

Illegal, unreported and unregulated (IUU) fishing violates the rights of Indigenous peoples to traditional fishing grounds; compromises food security of legitimate fishers and coastal populations; and facilitates human labor trafficking. Once caught, tails, fins, and heads are cut off for storage and transportation, which makes identification by phenotype impossible. Polymerase Chain Reaction (PCR) and electrophoresis can detect different tuna species but are time-consuming and require access to a fully equipped laboratory and trained personnel. Thus, I developed a novel biological assay and a 3D printable portable device to detect Ahi tuna, one of the species of interest among three tuna species. The biological assay consists of three steps: DNA extraction by crude lysis method; DNA amplification by Recombinase Polymerase Amplification (RPA); and detection by fluorescence using Clustered Regularly Interspaced Short Palindromic Repeats associated (CRISPR Cas) 12a. qPCR verified Ahi tuna DNA extraction by crude lysis method, generating 10⁶ copies of DNA per reaction comparable to the standard silica-based capture method. Nested qPCR and Tapestation verified RPA’s successful amplification of Ahi tuna DNA extracted by crude lysis method. Quantification of fluorescence by qPCR verified that one-pot RPA and CRISPR Cas12a reactions could generate up to 6000 Relative Fluorescence Units above the negative control within 15 minutes. The isothermal device keeps the samples at a constant temperature (37-42℃) for the RPA and CRISPR Cas12a reactions. I successfully demonstrated a <50 min sample-to-result assay to detect Ahi tuna DNA, and this protocol will be further adapted for testing other types of tuna including Bluefin tuna. By developing such a rapid and affordable isothermal biological assay and a point-of-need 3D printable portable device for tuna identification, I aim to contribute in helping individuals and ecosystems impacted by IUU fishing.

 Alzheimer’s disease (AD) is the most prevalent of neurodegenerative diseases, with over 6 million Americans suffering from the illness and cases increasing each year. TREAT-AD (TaRget Enablement to Accelerate Therapy Development for AD) is an NIH-funded, multi-institutional network that identifies and addresses new targets for AD drug development. Genetic targets of interest were identified via RNA-sequencing and proteomic analysis of post-mortem tissue from participants with AD. We tested the effects of inhibiting or overexpressing selected target genes hypothesized to increase the risk of Alzheimer’s. One such target is the CD44 gene, which regulates GABA receptor activity. To efficiently manipulate genetic expression, we used clustered regularly interspaced palindromic repeats (CRISPR) technology to enhance (CRISPRa) or repress (CRISPRi) genetic transcription in neural progenitor cells, stem cells in the process of differentiating into neurons. We used a cell line engineered to harbor CRISPRa and CRISPRi machinery. CRISPRa involves a catalytically inactive Cas9 protein fused to a transcriptional activator. In CRISPRi, the inactivated Cas9 is fused to a transcriptional repressor. This, along with the quantification of molecular pathways linked to Alzheimer’s, permits a window into the conditions that lead to earlier onset of AD, and thereby conditions that might be altered by new drug treatments. Here we report that underexpression of genes related to endosomal trafficking leads to changes in protein buildup that may be related to earlier onset of AD.

The Lieber lab is exploring chemotherapy-drug-free in vivo expansion systems that involve knock-out a gene in hematopoietic stem cells (HSCs) by precision genome editors. Part of this system is an immunotoxin that targets non-transduced HSCs and eliminates them, thereby allowing for the selective expansion of edited HSCs. The goal of my project is to test one of our target proteins CD49f, integrin α6, which has been reported to be expressed on primitive HSCs. In my studies, using flow cytometry with a PE-conjugated anti-CD49f antibody, I have confirmed that CD49f is present on 63% of human CD34+ cells, a cell fraction that is enriched for HSCs. PAI Life Sciences then set out to generate a CD49f-targeted immunotoxin. If the immunotoxin works, CD34+ cells should be highly susceptible to the conjugated immunotoxin. I then tested the immunotoxin on tumor cell lines and primary human CD34+ cells. Measured by flow cytometry, nearly 100% of HEK293T, HeLa and MDA-MB231 cells expressed CD49f. Next, I incubated three cell lines with increasing concentrations of the CD49f-peptide-saponin immunotoxin, ranging from 0.5pg/mL to 10µg/mL. The cell viability and total cell number was measured three days later by two methods: i) flow cytometric quantification, using DAPI staining and ii) counting cells in a hemocytometer after Trypan-blue staining. In tumor cell lines, MDA-MB-231 and HeLa cells, only at the highest immunotoxin concentration a ~58% decrease in total cell numbers was found. The number of viable cells was ~ 4.1% lower than that of untreated controls. Then, I performed cytotoxicity studies with primary CD34+ cells. At the highest concentration tested (10µg/mL), around 6.7% cells were killed by the immunotoxin. Overall, the data indicates that the cytotoxic activity of the new CD49f-targeted immunotoxin is suboptimal. Future steps will include the design and testing of new immunotoxin conjugates.

Wildfire smoke exposure is measured using the surrogate for all pollution by the concentration of particulate matter 2.5 microns wide (PM2.5). According to the CDC, short term exposure to wildfire smoke can result in negative health outcomes. It is highly recommended to stay indoors if your area is experiencing a wildfire smoke event. However, it is inevitable that outdoor air will leak indoors through any holes in the building, open doors, or windows. Occupants can also worsen indoor air quality through the activities they perform in their daily lives. This research is part of an indoor air quality pilot using PurpleAir sensors. We used the statistical methods within R to identify important building and occupant factors that influence IAQ. Participants tracked their IAQ using color changing PA-I monitors and a spike event log noting the time of the event, the color change exhibited, most probable cause, and the action taken to remedy the air quality. Data were analyzed using the tidyverse, caTools, simDesign, and lubridate packages in R. After grouping events across houses by cause, we saw a significant association between cooking and high levels of PM2.5 compared to other short-lived spike causes. The findings of this study will serve to set best occupant practices for indoor air quality within a household both during a wildfire smoke event and under normal atmospheric conditions. While economic barriers may exist when protecting oneself against unhealthy air, it is crucial to be aware of low-cost alternatives to minimize the health threat posed by poor indoor air quality.

Despite heavy exposure to Mycobacterium tuberculosis (Mtb), the bacteria that causes Tuberculosis (TB), some individuals show no evidence of infection and by defining these resistance mechanisms, we may identify novel treatment strategies. Among Mtb resistant individuals, our lab identified the Rab5a protein as differentially expressed as compared to controls with Mtb infection. By regulating vesicle trafficking, Rab proteins modulate a variety of cellular pathways including inflammatory signaling, antigen presentation, and autophagy, likely playing a role in Mtb clearance. We hypothesized that loss of Rab5a would alter IFN-êžµ gene expression. Monocyte-like THP-1 cells were electroporated with siRNA targetting Rab5a and yielded 70-90% knockdown at 24 hours versus scrambled siRNA control. Cells were then stimulated with DNA ligands for four hours before RNA analysis. Loss of Rab5a resulted in lower levels of IFN-êžµ gene expression after stimulation with Sheared Calf Thymus DNA (p=0.002, 53.9% reduction), Poly(I:C) (p=0.01, 42.8% reduction), supercoiled plasmid (p=0.03, 45.3% reduction), and cGAMP (p=0.008, 45.7% reduction). We conclude that Rab5a expression is required for Type I IFN production through the DNA-sensing pathway. By characterizing the pathways by which Rab5a modulates the macrophage Mtb response, we may identify host targets to augment protective responses that may serve as adjuncts to current TB treatments and vaccines.

The snowball Earth hypothesis states that between ~720-635 Ma Earth underwent glaciations during which the planet was covered completely in ice. Scientists use carbonate deposits, called cap carbonates, which appear atop snowball Earth glacial deposits to mark the end of these glaciations. Cap carbonate deposition is currently thought to have occurred during extreme stages of the chemical weathering (breakdown of rock by chemical reactions) that followed snowball Earth. However, there is insufficient geochemical evidence to confidently determine which stage–extreme, mild, or otherwise–of chemical weathering intensity the carbonates were deposited in. Magnesium, Mg, isotope abundance is useful in tracking chemical weathering events because of magnesium’s sensitivity to chemical weathering intensity. Data collected from rock samples from the Yangtze Formation in South China support the conjecture that chemical weathering was most intense immediately following snowball Earth, but it was not until chemical weathering slowed down that cap carbonates were deposited. This scenario allows time for continental chemical weathering to occur and calcium and magnesium cations to become available for the production of carbonates. To revise the snowball Earth hypothesis with this information, samples from more than one region are needed to apply this timeline globally. I will dissolve rock samples collected from the Amazon Craton in Brazil and study the sample powders using mass spectrometry to collect Mg isotope abundance data. I expect the data collected from these samples to resemble the data collected from the Yangtze Formation cap carbonates. This corroboration will help piece together the puzzle of the Snowball earth timeline.

The Developmental Origins of Health and Disease (DOHaD) hypothesis evaluates how the prenatal environment affects health after birth. The placenta is a multi-faceted organ that sustains life during human development and is key to evaluating the DOHaD hypothesis. Glial Cells Missing Transcription Factor 1 (GCM1) is a transcription factor that plays a critical role in placental development. Our goal is to understand the downstream effects of GCM1 on various genes necessary for placental development by evaluating gene expression after GCM1 knockdown. The BeWo choriocarcinoma cell line is a model of placental syncytiotrophoblasts cells which undergo a cell fusion process called syncytialization in the placenta to form multinucleated cells that help exchange nutrients. Previously, we knocked down GCM1 in full-term primary placental cells that spontaneously syncytialize and assessed gene expression using RNA sequencing. We identified 10 differentially expressed genes. Based on those findings, we hypothesized that GCM1 plays a greater role during early pregnancy leading us to repeat the GCM1 knockdown in BeWo cells. BeWo cells were treated with 20µM, 50µM and 100µM forskolin (FSK) for 48hr to induce syncytialization which was confirmed via qPCR of syncytialization markers GCM1 and Syncytin-2 and through fluorescence microscopy. GCM1 expression increased 3.15, 1.3, and 1.2 fold respectively after treatment with 20µM, 50µM, and 100µM FSK, whereas Syncytin-2 increased 78.1 fold after 50µM FSK treatment. We then performed an siRNA knockdown of GCM1 in unsyncytialized BeWo cells with two concentrations of siRNA (25nM and 50nM) for 24hrs and observed a 70% and 80% reduction in GCM1 expression, respectively. Next steps include optimizing the siRNA procedure for syncytialized BeWo cells and comparing these results to our previously conducted experiment. Overall, this will improve understanding of how GCM1 coordinates gene expression in the placenta during pregnancy.

Prior research suggests that people with obesity commonly have diets with more added sugar and saturated fat, worse sleep quality, emotional eating, and lower physical activity time than people with healthy weight. However, do these lifestyle characteristics predict one’s response to a behavioral weight loss (BWL) intervention? We will explore, in people with obesity, if these lifestyle characteristics, individually and/or jointly, are related to the change in adiposity in response to a 6-month BWL intervention. The methodology consists of data from self-report questionnaires administered to participants (N=63) at baseline in the BWL intervention group in the Weight Effects on Brain Health Study. Adiposity measurements were obtained by dual-energy X-ray absorptiometry. Diet characteristics were determined and Healthy Eating Index was calculated by analyzing 3 unannounced dietary recalls from an automated self-administered 24-hour recall system. Eating behavior was measured through the Three Factor Eating Questionnaire-R18. Sleep quality was determined by The Pittsburgh Sleep Quality Index. Physical activity assessed regular activity during the previous 4 weeks and was calculated as MET-h/wk. A composite score will be generated to include the 4 lifestyle factors described. Statistical analyses are undergoing. Anticipated results are associations between poor diet quality, poor sleep quality, less physical activity, and higher scores for uncontrolled and emotional eating and a greater reduction of adiposity over 6 months, as determined by multiple linear regression. Confounding by age and sex will be explored and models adjusted as needed. Additionally, we anticipate improved predictability of lifestyle characteristics, when considered jointly, to the change in adiposity. Participants were 69.8% female with mean age of 42.2±10.9 years, BMI of 37.2±5.3 kg/m2, and visceral adipose tissue of 1875.6±1027.7 grams. This research may help illuminate if lifestyle measures are able to predict one’s response to a BWL intervention and who could benefit most from it.

Cardiovascular disease is the leading cause of death worldwide. A key reason driving the high mortality of heart disease is that the heart is unable to regenerate any muscle that is lost due to injuries like heart attacks. Furthermore, there are no current therapeutics that promote the creation of new muscle. However, in the past decade, scientists have attempted to address this issue by using stem cell-derived cardiomyocytes (iPSC-CMs) to replace lost heart muscle. A key limitation preventing using this therapy in humans has been that cardiomyocytes derived from stem cells remain immature relative to adult cardiomyocytes, and these immature cells cause several complications when transplanted into an adult heart. Identifying cardiomyocyte maturation regulators is needed in order to further develop this technology and translate it to patients. Previous studies from our lab and others have identified the RNA binding protein Muscleblind-like protein 1 (MBNL1) as a key factor controlling muscle maturation. MBNL1 expression increases as the heart matures after birth and it controls expression of many critical regulators of cardiomyocyte maturation, however, MBNL1 has never been studied directly for promoting iPSC-CM maturation. In this project, I am testing the hypothesis that increasing MBNL1 expression will improve the maturity of iPSC-CMs. I am using a genetically engineered stem cell line in which I can overexpress MBNL1 and an isogenic control line to test my hypothesis. I have found that MBNL1 expression naturally increases over time in iPSC-CMs. Additionally, I have validated the MBNL1 overexpression system in iPSC-CMs. Finally, I have used this system to test my hypothesis that MBNL1 will increase iPSC-CM maturity by measuring well-described transcriptional and structural hallmarks of maturity. Ultimately, this project will aid in identifying MBNL1’s role in controlling cardiomyocyte maturation, helping further develop stem cell-based therapeutics to repair damaged heart tissue in humans.

Tropospheric reactive halogens are a sink for ozone and influence the oxidizing capacity of the troposphere. Daily measurements of chloride enrichment, bromide enrichment, and iodine in sub- and super-micron aerosol were collected in June 2022 and January-February 2023 in Bermuda during the Bermuda boundary Layer Experiment on the Atmospheric Chemistry of Halogens (BLEACH) campaign. Gas-phase halogen radicals originate from heterogeneous reactions (chemical reactions involving more than one phase of matter) on the surface of halide-containing aerosol. These reactions lead to enrichment or depletion of aerosol halides (e.g., particle phase chloride, bromide, or iodide) relative to their ratios with sodium in sea water. We compare these measurements with simultaneous observations of ozone and gas-phase halogen concentrations in order to understand the relationship between aerosol and gas-phase halogens and their impact on tropospheric ozone abundance. Observations from these campaigns will aid in improving atmospheric model outputs and environmental policy. I extracted the ions from more than 60 quartz air-filter samples and aided in method development with Ion Chromatography (IC). Inductively Coupled Plasma Mass Spectrometry (ICP-MS) was primarily used for iodine measurements. Data analysis and lab work is still ongoing, therefore only preliminary observations are available. We’ve observed that sodium, iodine, chloride, and bromide agree well with previous observations at Tudor Hill (Arimoto et al., 1995; Sander et al., 2013). Higher depletions of chlorine excess and bromine excess and higher iodine and non-sea salt sulfate concentrations are observed during the first half of the summer campaign.

As part of cellular metabolism, all organisms produce reactive oxygen species (ROS), such as (O₂^– ) and hydrogen peroxide (H₂O₂). ROS can damage multiple cellular organelles and processes, disrupting normal physiology. Proteins, lipids, and nucleic acids can be damaged by ROS molecules, resulting in cell death. Also, several human diseases have been linked to an imbalance between ROS production and antioxidant defenses. Plants' chloroplasts and mitochondria contribute a substantial amount of ROS, as they are responsible for photosynthesis and aerobic respiration. In maize, Whirly ssDNA-binding proteins help to maintain the stability of the plastid genome. We recently demonstrated that maize seedling development is accompanied by increasing oxidative stress to the demise of chloroplasts, mitochondria, and their DNA. We also showed that maize seedlings grown in the light had higher levels of oxidants and lower levels of antioxidants than dark-grown seedlings. Here, our objective is to elucidate the role of Whirly proteins in oxidative damage. We isolated organelles from maize seedlings and performed oxidant and antioxidant assays for both wild-type and whirly-mutant plants. We found a significant difference in oxidation levels between wild-type and mutant plants. Our study should provide a better understanding of the role of ssDNA-binding proteins in oxidative damage to organelles.

When the cell undergoes stress, it leads to an increase in protein instability and misfolded states that prevents proper cell functions. Small Heat Shock Proteins (sHSPs) are molecular chaperones that work to maintain a healthy proteome by associating with misfolded proteins to delay aggregation under stress conditions. Other chaperones and co-factors will then refold or degrade the misfolded protein client. HSPB5 is a human sHSP ubiquitously expressed throughout the body. A HSPB5 disease mutant, where arginine is mutated to glycine at residue 120 (R120G), is a defective chaperone associated with cataracts and desmin-related myopathy. HSPB5 comprises three domains but only one domain—the alpha-crystallin domain (ACD)—is folded. My research aims to understand the effect of the R120G mutation on the folded ACD’s structure. HSPB5 creates a dimer through electrostatic and hydrophobic interactions between ACD at the dimer interface. This network of interactions causes the dimer interface to be highly sensitive to electrostatics, working like a sensor for environmental charges. Wild-type HSPB5 is more positive at its dimer interface, likely facilitating interactions with negatively charged compounds. In the R120G mutant, the loss of arginines at the dimer interface site causes it to be less positive, hypothetically lowering HSPB5’s affinity for these compounds. Through site-directed mutagenesis, I obtained HIS-tagged cleavable constructs for wild type and R120G B5 ACD that allowed for easier purification. Using these constructs, I grew isotopically labelled N15 B5 ACD in minimal media and purified my protein sample through nickel affinity, size exclusion and anion exchange chromatography. Through NMR titration experimentation, I investigate how amino acid identity at the R120 site will affect ACD interactions with charged molecules in R120 mutant of HSPB5. Learning how mutations at the R120 site affect protein dynamics and client interactions will be a step forward in understanding the sHSPs’ overall chaperone mechanism.

The Three Sisters Volcanic Complex is located in Lane County, Oregon, and South Sister is considered an active volcano. The USGS observed gradual deformation and uplift around South Sister during 1996-1997. A previous satellite interferometry study of South Sister found that volcanic activity was ongoing during 2020-2021. The results showed that the input rate of magma into the volcano edifice decreased during 2004-2010. Seismic velocity is sensitive to the pressurization state of the system. We can correlate relative seismic velocity with GPS observations to monitor the dynamics of the subsurface of the volcano. The SeisMIC Model is a Python package that provides functionality to apply concepts of seismic interferometry to elastic wave data, reconstructing continuous Green's functions. The expected findings are the relationship between the inflation of the volcano edifice and the seismic velocity change, which could also reveal the relationship between velocity change and deformation. Seismic velocity change is not dependent on the occurrence and location of seismicity, due to its continuous nature. This study could provide a better understanding of the mechanisms causing seismic velocity changes at South Sister.

Without proper genetic regulation, the creation and maintenance of cells within eukaryotic organisms such as yeast, plants, and humans is doomed to fail before it even begins. Protein corepressors are key to the genetic repression in all eukaryotic organisms and are vital for an organism to be able to properly coordinate their development and respond to environmental stimuli. In Arabidopsis thaliana, a model plant for genetic studies, the corepressor TOPLESS (TPL) is one of the main proteins that is used to repress the auxin pathway, which is essential to development and organ creation. Recently, the active domain of TPL has been pinpointed to an 18-amino acid long region named LIS1 homology (LisH) that is sufficient for activity. Previously, we found that the helix H1 of LisH in a plant corepressor functioned as a transcriptional repression domain in yeast. These observations suggest a broad conservation of mechanisms across kingdoms, suggesting this motif could be engineered to be a potent, short, and adaptable protein domain suitable for synthetic biology and therapeutics. My project aims to test the ability of the LisH protein domain to repress gene transcription in metazoans using mammalian cell culture. We will transfect human cancer cell lines with DNA encoding a dCas9-TPL fusion protein, which can be targeted to promoters of endogenous genes such as the cell surface antigen CD4, or synthetic constructs such as fluorescent reporter genes to detect differences in protein levels. Results of the project are expected to show that TPL and other foreign corepressors can function within the human cell just as efficiently if not more than human corepressors. Research into LisH's abilities will provide knowledge of its active domains and mechanisms in mammalian cells while also having the possibility to aid the scientific community by developing TPL as a rapidly deployable synthetic biology tool.

Pseudomonas aeruginosa is a major cause of opportunistic infections in immunocompromised people. P. aeruginosa uses a cell-cell signaling mechanism called quorum sensing (QS) to regulate virulence functions and cooperative behaviors. QS in P. aeruginosa is regulated by two transcription factors, LasR and RhlR. These proteins control the production of extracellular proteases, “public goods” that benefit the entire population. These public goods create an incentive for individuals to cheat by availing themselves of the proteases without incurring their production cost. In fact, when P. aeruginosa is grown in media that requires QS for growth, cheaters emerge in the population and invariably carry mutations in lasR. We were intrigued by the clinical isolate E94, in which we observed the rapid emergence of cheating. E94 contains an inactive LasR via a transposon insertion. Transposons are DNA segments that move between genomic locations. E94 contains dozens of transposable elements. We hypothesized that transposon movement facilitates the adaptability of the E94 genome. I evolved cheaters from wild-type E94 in casein media, which requires QS for growth. I identified cheaters using a phenotypic assay. I then grew cheaters in non-selective media and identified revertant, protease-producing colonies. I used PCR analysis of the cheaters and their protease-producing progeny to determine if the transposon remains inside the lasR gene. I found no transposon movement from lasR upon cheater reversion to a protease-producing phenotype. We also determined that cheaters display no rhlR activity. We then hypothesized that cheating in E94 occurs by disruption of RhlR QS. We did not find mutations in rhlR itself and are performing whole-genome sequencing to identify other genetic targets. Understanding the mechanism of cheating and reversion in E94 gives us insight into the evolution of cooperation and conflict in populations and, potentially, a non-antibiotic approach to controlling bacterial populations a variety of settings.

Identifying risk factors for alcohol misuse among young adults is a critical public health priority given high rates of heavy drinking and alcohol-related consequences observed in this population. The field of behavioral economics has provided a set of quantifiable metrics that measure individuals’ demand for alcohol, which are important predictors of alcohol use, consequences, and response to treatment. Previous literature has also found that one’s self-reported drinking motives (e.g., drinking to cope with negative affect, to conform to peers, etc.) have important associations with drinking outcomes. Despite this literature, little is known regarding how one’s drinking motives relate to one’s demand. The study aims to investigate how different drinking motives may be differentially related to alcohol demand and whether birth sex moderates these relationships. The current study recruited 220 young adults (18-25 year-olds) from Washington state who report drinking at least twice a week and at least one recent heavy drinking episode (4+/5+ drinks for females/males). Participants completed online assessments that included the alcohol purchase task, which asked how many drinks they would hypothetically purchase and consume at various prices ranging from free to $20. Participants were also asked to report their birth sex and drinking motives (social, coping-anxiety, coping-depression, enhancement, conformity). I will conduct regression analyses to test for associations between drinking motives and alcohol demand, and to examine whether these associations are moderated by sex while controlling for age and discretionary spending. I hypothesize (1) stronger positive associations between coping motives and demand relative to other drinking motives, and (2) this relationship to be stronger for males. Results will improve our understanding of the relationship between drinking motives and demand between sexes and inform interventions focused on reducing alcohol misuse through alternate coping strategies or reducing demand.

The emergence of the SARS-CoV-2 vaccine helped shine a light on protein subunit vaccines that use fragments of infectious protein from viruses to trigger protective immune responses. Normally in subunit vaccines, the immune system stimulation is triggered by a separately provided adjuvant. These adjuvants elicit immune responses in a broad and indeterminate manner. We hope to replace this with a molecule that can provide a more specific immune stimulation: CD40Ligand (CD40L). CD40L is an immune protein present on T cells and works to signal B cells to either replicate or create antibodies. For B cells to replicate antibodies, they need a primary signal from the antigen and a secondary signal, which CD40L initiates. To achieve this, we are using the I53-dn5 nanoparticle, which has the ability to display different ligands on its two components by putting both the antigen and adjuvant on either the pentamer or trimer component. We designed 8 different constructs where we tested two versions of CD40L, the placement of CD40L, and the linker length between CD40L and the nanoparticle surface. Out of the five stages of the project - designing, expressing, purifying, assembling, and evaluating - we have completed the first three. The designs that have expressed the best throughout each stage have been those with the CD40L truncated sequence instead of the full sequence. Furthermore, we have seen a trend with the pentamer subunit being more amenable to the addition of CD40L. Future in vitro studies and re-expressions will determine if the particle will retain stability and native CD40L function. We expect CD40L-displaying nanoparticles will promote B-cell proliferation to a greater extent than the nanoparticle vaccine displaying only hemagglutinin antigen. Ultimately, we hope to examine how co-display of CD40L with antigen will change the quality of immune response and memory in vivo.

Documenting plant-animal interactions allows for a better understanding of biodiversity, the behavioral ecology of frugivores, and the coevolution between plants and animals. Bats are important seed dispersers on hundreds of plant species in the tropics, but their patterns of plant use across habitats is still relatively unknown. The overarching goal of my research project is to characterize the interactions between mutualistic fruit bats and plants across different habitats at a site in Costa Rica (La Selva). My hypothesis is that bats will exhibit frequent interactions with Piper plants overall, with more variable interactions across forest Piper species over time because these species have intermittent fruiting peaks. Existing field data consist of 24h camera trap videos and nightly acoustic ultrasonic recordings taken at dozens of forest and gap Piper plants at La Selva during both rainy and dry seasons between 2019-2021. The acoustic data collected is heavy in background noise from organisms and weather conditions; therefore I developed a program in MATLAB to streamline this analysis. I am using RavenPro to identify relevant parameters of bat calls within the filtered files using focal calls as a guide to later identify the species participating in these visitations. I am comparing the number of calls across 10 P. sanctifelicis plants (open habitat) to the number of calls found across 8 P. generalense plants (closed habitat) to observe the frequency of possible fruit-bat interactions across habitats. This project is significant in the field of ecology because of its focus on plant-animal mutualistic interactions: by understanding the frequency of bat visitations to plants across habitats, we can gain a better understanding of the importance of these frugivores for seed dispersal and survival of plants.

Corepressors are proteins recruited by partner proteins to negatively influence transcription of genes. TPL is a corepressor from the model plant Arabidopsis thaliana, and while we understand a lot about how TPL works, there are still many mysteries remaining. My project aims to identify other proteins that work with TPL to form a transcriptional repression complex at a single-engineered promoter site. First, we created a synthetic repressor called dCas9-TPL that binds and represses the transcription of the RUBY reporter. The RUBY reporter is a visual marker designed to express throughout the entire plant, turning the green plant a bright purple. Our engineered RUBY line also carries two guide RNAs in its promoter with sequences not found anywhere else in the Arabidopsis genome. This allows dCas9-TPL to bind to and repress this particular gene and not affect the transcription of other genes. Visual screening of the repressed RUBY line showed these plants turn a faint whitish-pink instead of bright purple, signifying that the repression by TPL is working. I have identified the promising repressed RUBY homozygous line and have generated three mutagenized populations of 40,000 individuals using the chemical Ethyl methanesulfonate (EMS). The EMS protocol creates new point mutations allowing us to identify genes involved in repression that we can map through DNA sequencing. I will use visual screening to search for plants with bright purple organs, meaning that the repression by TPL is broken and that a putative TPL interactor may be mutated. By identifying regulators of corepressor function in plant biology, I hope to learn principles that can inform cellular engineering across many organisms and better understand why certain mutations associated with transcriptional repression cause developmental defects or diseases like cancer in humans. 

The visual system is a critical portion of the sensory arsenal in many animals, since light is a fundamentally important factor that allows animals to assess and navigate their surroundings. Differences in latitude have measured effects on the quality, quantity, and consistency of daylight, and animals have adapted to these varying light levels in different ways. Research has shown that animals with larger eyes, reflected in their bony orbit dimensions, are able to perceive their environments better in more dimly lit settings. Studies have also suggested that animals at higher latitudes exhibit larger eyes for better visual performance. Our group seeks to understand if there is any significant relationship between latitude and orbital size in Canidae (wolves, foxes, and relatives) due to the difference in light levels at different latitudes. I collected several linear measurements using ImageJ and 3D Slicer from skull 3D scans of 29 species of the Canidae family over a latitude range from -104.07° - 99.02°. Additionally, our team collected data on the average tree coverage, diet, and hunting style of species, to test for additional variables that may affect orbital size. We conducted regressions and ANOVAs among the variables collected. The preliminary results show there is no significant relationship between latitude and orbital size. However, we found that both hunting style and skull length have a significant relationship with orbital volume in Canidae. These results potentially impact the field by allowing us to infer the possible evolutionary trajectories of bony orbital dimensions, and how eye size could allow for more complex hunting styles in Canidae. Future research may seek to validate these findings in other carnivore families.

Meadow and wetland areas serve as critical habitats for many native species in the Pacific Northwest and provide countless ecosystem services such as carbon sequestration, sediment removal, and increased biodiversity. However, most wetland and meadows inventories are incomplete or are biased towards those that have been mapped on the ground and those that are easy to detect directly in aerial and satellite imagery. Furthermore, due to habitat loss and climate change effects, the current state of these ecosystems is highly dynamic and unknown. Remote sensing provides landscape analysis capabilities to map current habitats and compile and analyze variables such as elevation, slope, soil type, wetness, and seasonal glacial recession that may predict where these fragile habitats could be. The goal of our research was to identify and map wetlands and meadows in Mount Rainier National Park. Using topographic, vegetative, hydrologic, and soil indices paired with data points to train the machine learning model, we get an output of wetland and meadow probability. Our work, co-produced with National Park Service biologists, contributes to the database of potential wetland ecosystems in Mount Rainier National Park. and improves remote sensing methodology to predict meadow habitats. WIP tool outputs of predicted wetlands and meadows had a high overall accuracy with documented wetlands and meadows in Mount Rainier National Park. Ultimately, by providing models, processes, and continuing to add to knowledge of wetland and meadow habitats, we anticipate a large potential for expansion to other NPS-protected lands.

Mosasaurs are extinct, enormous lizards that dominated the oceans in the Late Cretaceous, from 90 to 66 million years ago. They were important members of Late Cretaceous marine ecosystems, with some species being the top predators. However, there remain many uncertainties about mosasaur diets, which likely varied considerably among species. Therefore, I aim to investigate mosasaur diets to provide more information on lizard evolution and Cretaceous marine ecosystems. To infer the diets of mosasaurs, I examine the lower jaws and teeth of their closest living relatives, modern lizards, and test for correlations between craniodental morphology and diet. For example, a lizard that eats primarily hard-shelled foods will likely have more robust jaws and teeth than a lizard that primarily consumes insects. To quantify the morphologies of the lower jaw and teeth, I measured the width and height of the jaws at three points, and the height, width, length, curvatures, root length, and cusp numbers of the teeth at the same three points (n = 43 species). I then used the jaw measurements to calculate cross sectional shape values that represent the amount of stress the jaws experience during feeding. Finally, I used phylogenetic regressions and multivariate analyses to test the relationship between jaw/tooth shapes and diets. I find evidence that jawbone heights increase among diets in the following order: insectivores, carnivores, herbivores, and durophagous taxa. Further, bone width is greater in herbivores than in non-herbivorous taxa, and durophagous lizards have the most diverse tooth morphologies. These results provide a foundation for future studies to examine the relationship of jaw/tooth shapes and diet more robustly, with the goal of using modern lizards as analogs for inferring diets of mosasaurs.

Remote collaboration today rarely involves a single communication channel. Instead, teams frequently juggle a myriad of communication tools, such as video conferencing, group chat, and email. Each of these platforms provides different mechanisms for relaying information and media to ultimately meet the needs and goals of the team. While discussions occurring on different platforms are often related, existing tools used to support each type of communication are disconnected. To research how to bridge this gap and support seamless collaboration and communication across different platforms, we developed a toolkit that connects conversations between three of the most commonly used remote collaboration platforms: Slack, Google Docs, and Zoom, covering both synchronous and asynchronous modes of communication. We iteratively designed and implemented features such as adding information from Slack chat directly to Google Docs notes to build up meeting agendas and selecting specific snippets of Zoom meetings to be embedded into notes or sent to chat. We also plan to evaluate the effectiveness of our toolkit in helping streamline the transfer of information across different team communication sites and enhancing the remote collaboration experience for teams via subsequent qualitative user studies. Specifically, we will be conducting a week-long field study with existing teams, such as teams from industry, teams working on school projects, research groups, committees, etc. We will use a combination of experience sampling, diary study and post-study interviews to understand their experience. The results we expect to get from these exploratory user studies will help us answer the following questions: Which aspects of the tools work best for the users? Does the current UI and design make sense for how the user interacts with the toolkit? In which scenarios is the toolkit being used most effectively? These results will also guide us in designing additional features for the toolkit in the future.
 

The Paleolithic era saw the beginning of the development of human language. Furthermore, the Paleolithic is characterized by the appearance of non-figurative, or geometric art. There are extensive examples of signs commonly seen in Paleolithic art, and while over 40 distinct signs have been recorded, we focus on the five most abundant signs in the SignBase dataset (cf. doi: 10.1038/s41597-020-00704-x): notch, line, obline, hatching, and dot. Here we investigate Bacon’s recent (2023, doi: 10.1017/S0959774322000415) hypothesis that geometric signs were a way of recording a phenological calendar. We found an abundance of representation of the notch symbol (254), followed by the line (174). To assess their proposed calendrical function, we report on the distribution of frequencies of the symbols to identify if seasonal patterns are represented. Our study sheds new light not only on the characteristics of geometric art, but also on the likelihood that they encode a phenological calendar as proposed by Bacon et al. (2023).

Lung-resident type 1 conventional dendritic cells (cDC1s) are critical for initiating immune responses against foreign respiratory viruses and endogenous assaults like cancer cells. Importantly, the cDCs of each tissue display unique phenotypes and functions dictated by the environment they populate. However, our understanding of the factors that regulate cDC1 development and function in the lung is minimal. The cytokines, FMS-like tyrosine kinase 3 ligand (FLT3L), and granulocyte-macrophage stimulating factor (GM-CSF) are essential for the development of tissue-resident cDC1, but in in vitro systems, these factors are insufficient to generate cDC1s with a lung-specific phenotype. RNAseq analysis of lung cDC1 identified a clear enrichment in genes associated with transforming growth factor beta (TGF-β) signaling, a factor also known to be enriched in the airspaces of the lung. TGF-β has been previously reported to maintain DC quiescence in the lung, however, our data suggested it may also play a role in differentiation and lung specification of these cells. Based on this, I hypothesized that adding TGF-β to in vitro bone marrow (BM) cultures alongside established cytokines FLT3L and GM-CSF would generate cDC1s phenotypically and functionally similar to in vivo lung cDC1s. The addition of TGF-β, but not GM-CSF, to optimized FLT3L-BMDC cultures resulted in development of cDC1 which highly resemble lung cDC1. The development of a high throughput in vitro system that differentiates functional lung cDC1s will not only inform the in vivo factors required for development of these cells but also provides a useful platform for interrogation of lung cDC1 function and a stepping-off point to begin models for human lung cDC1 production and study.

Pangolins are the most widely trafficked mammal in the world. Pangolin scales are smuggled for use in traditional medicine and this is a concern due to all eight species of pangolins; four in Africa and Asia, respectively, currently being in the vulnerable to critically endangered category. My research provides insight into the practices and routes of smugglers using stable isotope analysis to obtain information on locality of origin from scale samples of Smutsia gigantea, Smutsia temminckii, Phataginus tetradactyla, and Phataginus tricuspis, the four species of pangolins native to the African continent. I collected powdered scale samples from the four pangolin species and analyzed the samples using an Elemental Analyzer attached to an Isotope Ratio Mass Spectrometer (EA-IRMS). Scale samples were sourced from recent seizures in multiple ports. Data from the EA-IRMS provide Sulfur, Carbon, Nitrogen and Oxygen stable isotope composition estimates. This information was then used to place individuals into groups and then predict where those groups lived prior to being poached. Better understanding of smuggling routes and poaching habits is an aim of this project. Stable isotope analysis may also help our collaborators identify the pangolin species when scale samples contain insufficient or otherwise poor quality DNA. This project has valuable implications in future forensic studies of organic materials and will lead to better policing and policy making with regards to pangolin conservation.

The goal of the SQRLab is to develop technologies for a fully fault tolerant quantum computer capable of processing 10,000 qubits of information. One necessary component is a Paul Trap, consisting of two pairs of blades delivering both direct current (DC) and radio frequency (rf) alternating signals in order to trap and stabilize a string of ions. In order for the modes of the quantum states of these ions to be stable, the stability of power delivery to the device is crucial. Given these design specifications a rf resonator circuit is necessary. The goal of my project is to design, simulate, build, and test a low-loss rf resonator to deliver rf signals to the ion Paul Trap efficiently and stably. Using a toroid shape, I experiment with the material of the wiring and the method of winding the toroid to find a wiring scheme that creates the least loss in delivering power to the experiment. The material used in the wire and dielectric material inside the coil directly affects the efficiency of translating signals. It is desirable that this resonator generates a voltage gain at a specified power level, has impedance matching of the coil with the driving circuit, and contains a method of monitoring this voltage. Thus far, I have measured the voltage gain generated by the coil and the quality factor of the coil (the quality of the resonator frequency as it interacts with the rest of the circuit). I have also designed a capacitive “pickup” to sample the voltage level of the delivered rf power. I will produce noise figures to stabilize the trap power to a set-point voltage level. This research contributes to SQRL’s objective of designing useful scalable quantum systems to simulate nature and perform complex algorithms not permitted by classical computers.

Electron paramagnetic resonance (EPR) spectroscopy is a powerful spectroscopic tool for detecting unpaired electrons in molecular systems. By attaching two spin-labels which contain unpaired electrons to different regions of a protein, the distance between the spin labels can be measured, making this technique particularly useful for studying protein structure and dynamics. The signal sensitivity of these measurements is especially sensitive to protons on amino acids adjacent to the spin label. While it is known that the presence of neighboring protons to the spin label decreases the signal intensity, the magnitude in which specific amino acids affect the signal is not well understood. My research aim is to determine how specific neighboring amino acids affect the EPR signal. Here, I design model systems in which spin labels are placed on various parts of maltose-binding protein (MBP) to construct a sample set that contains the spin label in diverse amino acid environments. These spin labels are placed on MBP through a process called site-directed spin labeling. MBP is mutated through site-directed mutagenesis using specific primers, the final plasmid transformed into competent E. coli cells. Through collecting EPR data of these MBP mutants, we can gain insight to which amino acids neighboring the spin label most affect the signal. This project will help us understand how to determine spin-labeling sites to result in maximum EPR signal intensity. Maximizing this signal intensity will enable us to use EPR to study biological systems that could not previously be studied due to lack of sensitivity, such as membrane proteins.

Cell division is essential to all living organisms, and microtubules are critical for this process. Microtubules in bundled kinetochore-fibers generate forces to move chromosomes by stochastically switching between assembly and disassembly states. Electron tomographs of mammalian mitotic spindles show that microtubule tips maintain a high level of coordination despite stochastic switching between states. The collective behaviors of microtubule bundles give rise to chromosome oscillation, which promotes the alignment and separation of chromosomes along the spindle equator during metaphase. To understand how stochastically-switching microtubules can produce synchronized motions in vivo, we use a mechanical model that describes the force-dependent dynamics of microtubules. The model reproduces the bistability of microtubule bundles observed in vivo and suggests that this coordination could be explained by sufficiently stiff mechanical coupling. We also propose a new way to characterize microtubule bundle state based on the substates of microtubules within the bundle. We will use this characterization to calculate microtubule bundle switch rates, which are technically difficult to distinguish otherwise, thereby laying the groundwork for future comparisons between bundle switch rates in vivo and in silico. In the future, we plan to explore the assumptions on which this model is based by analyzing the relationship between microtubule velocity and forces. We predict that this result will validate the assumed force-velocity relation of microtubule growth and contribute to a more accurate understanding of kinetochore-fiber behaviors. 

In comparison to the abundance of research focusing on early Paleocene mammalian recovery from the K-Pg mass extinction, the mid-Paleocene (63–58 Ma) is an understudied period of mammalian evolution, particularly at the Mehling Site near Ekalaka, Montana. Previous work suggests this site dates to the mid-Paleocene, but its absolute age is not well established due to limited ash beds for radiometric dating. An isolated mammalian molar tooth specimen from the Mehling Site had been tentatively identified as Microsyopinae, a subfamily of an extinct clade of stem primates called Microsyopidae. However, the first appearance of Microsyopidae in the fossil record is during the late Paleocene (58–55 Ma). The purpose of this study is to investigate the incongruity between the taxonomic identification of this specimen and the age of the locality it was found in. I conducted a comparative analysis of the molar tooth specimen using fossil specimens, casts, and digital 3D models of the dentition of microsyopid mammals and their relatives in order to identify the specimen down to the finest taxonomic level possible. My preliminary results show that this specimen shares some features with Navajovius and Arctodontomys, two of the earliest possible genera of the Microsyopidae. The findings of this study will enhance our understanding of the origin of Microsyopidae and of this stage of mammalian evolution during the mid-Paleocene. If the specimen is confirmed to belong to the Microsyopidae and the geological age of the site is correct, then this fossil would push back the earliest occurrence of Microsyopidae in the fossil record to the mid-Paleocene, extending the temporal range of this clade by several million years. Ultimately, this knowledge informs our understanding of the origin and evolutionary history of stem primates.

The dynamic expression of genes in an organism creates the biological complexity of life. Many are unique to a given lineage, while other genes are conserved and carry out the essential functions of life. Unsurprisingly, these essential genes are complicated to study, as interfering with their function often leads to death. One critical component of transcription is the multi-protein Mediator complex, which is found at every eukaryotic promoter where it helps coordinate the activation of gene expression. My project focuses on a core component of the Mediator complex, Mediator 21 (MED21). While MED21 is required for gene activation, my lab found that it also plays a role in the repression of gene expression, suggesting a complicated interplay between these two states. This can be challenging as many mutations in MED21 lead to lethal phenotypes. As an alternative, I hypothesize that using an integrase-based molecular switch to create a switchable MED21 will then allow me to differientate the role that MED21 plays in activation through the Mediator complex versus repression through the corepressor protein (TPL) in the model plant Arabidopsis. Integrases are capable of inverting DNA sequences flanked by unique sites, and I am engineering a switch that will turn off MED21 in certain tissues or in response to the addition of a chemical. By expressing an integrase protein from a lateral root-specific promoter, we can engineer a MED21 loss of function only in those specific cells while the rest of the plant is wild type and healthy. Future experiments include a switch from wild-type MED21 to a mutant form incapable of binding to corepessor TPL. This study will help us better understand the role MED21 has in repression versus activation, and also how state switching contributes to organogenesis.