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.

High throughput single cell/nuclei RNA sequencing (scRNA-seq/snRNA-seq) has been used to characterize the gene expression at the cellular level in disease control studies. Differentially gene expression analysis aims to emphasize the biological variation between samples without unwanted technical variation. Batch effect correction is occasionally performed where cells from each individual sample are treated as being generated from a batch. We analyzed snRNA-seq data from ApoE neutral and detrimental mouse models of Alzheimer’s disease (AD) to test whether batch correcting the data using all cells from each individual biological sample as representing a batch would result in 1) loss of disease relevant associations, 2) loss of biologically relevant cell types, and 3) reduced association between cell types and phenotypes. We performed scRNA-seq analysis of seven samples from two ApoE genotypes using Seurat workflow applying Harmony batch correction, using each sample as a batch, and without correction. Since we measured two disease-related phenotypes in mice from the two genotypes, we asked whether cell cluster membership associated with genotypes are also associated with unit changes in brain-diseases related phenotypes. After applying individual sample batch correction, we found differences in number of cell types (clusters) before and after batch correction, we showed loss of cell types/clusters specifically from the detrimental genotype, shrinkage of the differences in cell cluster membership across samples and reduced association between cell type membership, genotypes and phenotypes. In conclusion, batch effect correction should be applied consciously based on the experimental design to avoid over correction of biological variability and an appropriate design should help to avoid unwanted technical variation.

STEM education tends to avoid extensive discussion of ethics on topics such as climate change, treatment of disease, and nutrition. However, as textbooks set the foundation for curricula, it is crucial that they allow students to think critically about the ethics of performing science and societal impacts of biological research. Our work tests the hypothesis that introductory biology textbooks use predictable strategies to humanize science (e.g., inviting the reader to act like a scientist to develop a solution) and that some topics are more likely to have humanizing elements than others (e.g., some topics are better positioned to serve as launching points for instructors who seek to include humanizing elements in their class). Bringing in discussions of ethics into the science classroom is one strategy instructors can use to humanize biology. We define humanization as the act of positioning science in a social context and/or the act of discussing science through the lens of justice and/or injustice. Of the instances of humanization identified in these textbooks, ethics was mentioned in only 4.57% of these quotes. Ethics was discussed in relation to impacts on humans (41.0%), impacts on humans by humans (41.0%), and impact of humans (16.7%). Discussion of ethics was nuanced (43.6%), detailed (30.8%), and rarely included justice (10.3%) and equity/inequity (5.1%). Ethics was most commonly discussed in terms of biotechnology (38.7%), treatment of disease (12.0%), and environment (10.7%). These findings demonstrate that ethics is rarely made reference to in introductory biology textbooks, yet the field of biotechnology is at the forefront of biomedical innovation, thus having nuanced discussions about controversial subjects (e.g., CRISPR, GMOs, and eugenics) rather than only teaching what these subjects are is pertinent to the training of future scientists.

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.

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.

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.

Eukaryotic DNA is compacted into cells by wrapping DNA around nucleosomes. Nucleosomes are composed of core or variant histone proteins. Unlike core histones, histone variants enable specialized chromatin functions such as gene transcription or inheritance. Given their crucial and widespread functions, core histones and their variants are typically evolutionarily conserved in sequence and function. Therefore, lineage-specific differences in histone repertoires present unique opportunities to understand their functional consequences on genomic organization and biological processes.

Two such changes, both likely selectively advantageous, have occurred in budding yeast and flies. In budding yeast, the histone variant H2A.X, involved in DNA repair, entirely replaced core histone H2A. A crucial SQ motif on the C-terminal tail of H2A.X is required for its DNA repair mechanism. In flies, the loss of H2A.X and a fusion of the SQ motif from H2A.X with a conserved variant H2A.Z, which is implicated in gene expression, gave rise to a unique H2Av variant. We are recreating the histone H2A compositions of flies in yeast to determine the functional consequences of these evolutionary re-arrangements. Specifically, in S. cerevisiae, we moved the SQ motif or the entire C-terminus of H2A.X to H2A.Z, creating a fusion histone similar to the D. melanogaster H2Av. Therefore, the H2A repertoire in these engineered yeast resembles a fly's. Upon treatment with DNA damage agents, these “Drosophilized” yeast show reduced DNA damage repair efficiencies similar to mutant yeast with no SQ motif. Thus, we hypothesize that the abundance and/or localization of the SQ motif is critical for efficient DNA repair in yeast. Furthermore, we will test if processes like sporulation, meiosis, or resistance to stressful conditions that require DNA damage repair are affected in our “Drosophilized” yeast. These experiments will reveal the biological consequences and potential advantages of the unique yeast H2A repertoire.

The study of archaeological ceramics is one of the most ubiquitous methods for understanding ancient culture, livelihood, and human habitation. The LEIA project's objective is to address these topics through the examination of ancient ceramic artifacts discovered in Mallorca, Spain. Python coding was used to scan these samples and conduct in-depth image analysis, to identify specific variations found across diverse specimens. In this independent study, I am particularly interested in applying this set of tools to see if I can distinguish how a ceramic vessel was created and to also focus on modifying code to expedite the time-consuming process of hands-on ceramic classification and specific archiving techniques. Through my work, I have carefully sawed samples, converted them into digital images, and helped interpret them using a digital application called Jupyter Notebooks. I have also contributed to the DigAR Lab's implementation of novel Python coding to look at different manufacturing methods. This code helps to identify (in) organic temper found in each piece (e.g. limestone, quartz, grass), to note color distribution observed, make size comparisons, and to determine rotational orientation. All of these offer insight into possible pottery-making methods, outside cultural influences, and various firing techniques. Furthermore, to ensure all pieces were treated with equal care, I worked with the lab to construct a step-by-step procedure, that has been refined through multiple trials to provide standard instructions, on how to properly use heavy machinery to cut these pieces without causing excess damage. Furthermore, this repeatable process will be used by archaeology students and staff during upcoming fieldwork in Spain (Summer of 2023) to document future findings. Overall, this ongoing study will investigate the power of this toolkit to recognize subtle differences that result from varied manufacture methods; if successful this could have major repercussions on how ceramic assemblages are studied.

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.

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.

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.

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.

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.

Recently, archaeologists have been forced to reckon with the fact that the conditions in which they collect their data deeply affects the interpretation of that data. To this end, I have begun a project we are calling meta-archaeology, which offers a glimpse into the factors that contribute to and potentially distract from the collection and interpretation of archaeological data. Utilizing data from the Landscape, Encounters, and Identity in Archaeology Project (LEIAP) based in Mallorca, Spain, this study attempts to explore if weather conditions affect a surveyor’s ability to collect artifacts. The database for this project consists of datetime-stamped metadata associated with the GPS receivers used to map artifacts. To analyze this data, I use various Python packages (e.g. Pandas, Seaborn, Folium, and leiap, a custom package created for the project) to extract relevant weather data, merge the datasets using their datetimes, and subsequently find patterns in how weather affects archaeological data collection. This research hopes to show a correlation between data collection and factors like temperature, azimuth, and wind. For example, a higher average temperature for the day might result in a lower number of artifacts collected as surveyors are affected by the heat. These correlations can be used to structure field school practices to ensure the best possible data collection. In addition, these results can shape future research design to account for the conditions that affect what is or is not found during an archaeological survey.

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.

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. 

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.

A keystone bacterium involved in the pathogenesis of chronic periodontitis, commonly known as gum disease, is Porphyromonas gingivalis. This pathogen produces multiple structures on the surface of its cells categorized as virulence factors, including lipopolysaccharides (LPS) and outer membrane vesicles (OMV). Lipopolysaccharides are anchored to the outer membrane of P. gingivalis by Lipid A structures. Previous studies in our lab have found that the abundance and cargo selection of OMVs released from the cell’s surface can be modulated by the structure of Lipid A on P. gingivalis. The virulence factors investigated assist P. gingivalis in the colonization of the host at a cellular level – such as the formation of biofilm, or aggregated bacteria on a surface. OMVs released from the cell's surface operate as a delivery system for the various structures found on the outer membrane of the bacterial cell. We hypothesize that the biofilm density and morphology formed by P. gingivalis are influenced by the changes in OMV abundance and content derived from the modulations in the Lipid A structure. To test this, we utilize biofilm assays, where live cultures from various strains with differing Lipid A structures can grow and aggregate on a glass coverslip for 48-72 hours. Morphology differences are revealed from the analysis of the biofilms and pixel intensity is quantified and compared among strains. Various assays are used to compare the activity and concentrations of protein and lipid cargoes within the OMVs to understand how they are connected to biofilm morphology. The biofilms formed by P. gingivalis contribute to its pathogenesis, therefore it is important to understand the impact that secreted outer membrane vesicles have on its structure and integrity.

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.

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.
 

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.

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.

Hepatocellular Carcinoma (HCC) is an aggressive primary liver cancer that can be characterized with contrast-enhanced ultrasound (CEUS) by blood flow parameters. The most important blood-flow parameters are wash-in and washout, measured by the rate of contrast flow into and out of the liver and tumor. Currently blood flow is observed by eye, assessing the brightness of the contrast agent over time during the scan, and then scored on the Liver Reporting and Data System (LI-RADS) scale. This subjectivity delays diagnosis and treatment, and increases HCC mortality rate. To aid clinicians in a timely diagnosis, we are creating a quantitative Python algorithm to extract blood flow parameters from CEUS videos. I studied the existing MATLAB code our lab has created and translated its functionality into a Python executable. Since the two languages have different syntaxes and functions, I reconfigured the entire script to run in Python. This Python script will run faster than the MATLAB code, be able to accurately compute blood flow measures from CEUS scans, and be easier to distribute outside of academia. To extract parameters from CEUS liver videos of HCC patients, we processed the video using respiratory gating and motion compensation to ensure the tumor is on the scan and not moving around due to breathing. Then we analyzed the pixel brightness of the liver and tumor over the course of the scan to create a time-intensity curve (TIC). Finally, we compared various points on the curve to quantify the blood flow within the tumor and surrounding liver. Further iterations of the algorithm will include machine learning tools available in Python to increase the level of autonomy and thus the objectivity of the parameters. Using this algorithm, HCC diagnosis using LI-RADS will be timelier, allowing patients access to more effective treatment options.

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.

Ascidians are invertebrate chordates, with tadpole larvae that metamorphose into sessile adults. Molgulidae are a clade of ascidians where tailless larvae have evolved several times independently and our lab is interested in understanding the molecular mechanisms underlying the evolution of taillessness. There are two closely related Molgulidae species that are sympatric in Roscoff, France: Molgula oculata, a tailed ascidian and Molgula occulta, a tailless ascidian. The tailless M. occulta, have 20 notochord cells that do not converge and extend, called a "notoball", and have evolved a number of larval pseudogenes. During embryonic development, the Wnt planar cell polarity (PCP) pathway plays an essential role in regulating cell fate determination and other cell processes. Previous experiments have found that the Stolidobranch ascidian, Halocynthia roretzi, has a Wnt5 duplication, where Wnt5a is invovled in the notochord development whereas Wnt5ß is involved in muscle development. Bioinformatic analysis has been done on several developmental genes involved in notochord formation and the Wnt pathway which showed that most genes are highly conserved between M. oculata and M. occulta. We have identified two Wnt5 isoforms that may play a role in tail formation, and we are in the process of subcloning the 3'UTR regions to obtain gene specific RNA probes for in-situ hybridization. We expect to find Wnt5a expressed in the notochord and Wnt5ß to be expressed in the muscle cells. We are also cloning Dsh to examine gene expression. This information will allow insight into how the Wnt5 genes in M. occulta and M. oculata are implicated in notochord convergence and extension as well as whether the Wnt/PCP pathway contributes to the evolution of tailless larvae. 

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.

 

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.

Chronic kidney disease is the ninth leading cause of death in the United States. The current process for pathological diagnosis involves pathologists manually reviewing histochemically stained tissue slides. This analysis is also used to inform further treatment and is therefore critical to patient outcomes. In this project, we aim to improve the robustness of the diagnostic process by utilizing machine learning models to identify and classify features indicative of kidney disease on whole slide images. We manually annotate Masson’s Trichrome stained kidney tissue images from our collaborators at the University of Illinois for three functional structures (tubular cytoplasm, tubular basement membrane, glomerulus) and three indicators of damage to the kidney (fibrosis, edema, and inflammation). These annotations are used to train our VGG16 convolutional neural network model to classify patches of unmarked whole slide images into the four categories: tubular cytoplasm, fibrosis, inflammation, and glomerulus. We also address data variability that often comes from differences in the histochemical staining procedure across labs resulting in inconsistency across stains/imaging that can typically affect the generalizability of deep learning models. To address this, we are training a CycleGAN for image-to-image translation as a method of stain normalization and investigating the effect on the accuracy of our VGG16 model. Additionally, I will be training a model to identify the cortex versus medulla regions of the kidney to add to the pipeline for area-specific evaluations. Our research with integrating machine learning models within renal pathology aims to decrease the time and manual labor needed in the process and increase the accuracy of diagnoses.

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.

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.

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 Mongol Empire (1206-1368) under Chinggis Khan and his descendants was the largest continuous land empire in history, stretching across 5,000 miles of the Eurasian Steppe. During this period, referred to as the Pax Mongolica (lit. 'Mongol Peace'), the restoration of the Silk Road under a common administration allowed for the trading of goods between the Levant and Orient, and therefore the wider dissemination of technologies, cultures, and religions. This is juxtaposed with the great deal of brutality associated with the Mongol conquests, as evidenced by archaeological and textual records of mass killings during sieges, and modern scholarship regarding the Mongol Empire is tasked with balancing these perspectives. Witness to the Mongols is an upcoming sourcebook which compiles primary source material from all across the known world at the time, creating a complete picture of the life and legacy of Chinggis Khan, from his birth c.1185 to the fall of the last remnants of Chinggisid rule in 1502. Witness aims to compile, translate, and update scholarship for new audiences, both academic and at large, in order to communicate a more nuanced perception of Mongol imperial influence which, in my experience, otherwise propagates in Western education almost exclusively through the writings of Marco Polo. My specific contribution to this project concerns assisting in editing passages to ensure continuity between sources and revising introductory paragraphs and footnote annotations in preparation for publication. My particular fascination within the Mongol imperial sphere focuses on Mongol-Viet relations, especially in interpreting cultural dissonance regarding victory and failure of the Mongol invasions of Vietnam, as the successful defenses of Vietnam are widely celebrated to this day in folk tradition, though largely regarded in scholarship as Mongol victories for establishing a tributary relationship. As such, I am also tasked with investigating these threads for possible inclusion in Witness.

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.

People embody the joy and pain of nature through their own experiences, and have been sharing and cherishing this interconnectedness from time immemorial through paintings, stories, songs, dance, and more. I am a migrant living in a foreign country. i was eating sushi that day…. is a solo dance and an ethnographic research project, exploring ways in which I connect to, resonate with, and embody nature and personal experiences through performance. The awe-inspiring habit of salmon migration sparks my curiosity about the complex and multifaceted nature of human migration. As anadromous fish, salmon spend their juvenile life in rivers, and migrate to the ocean where they spend their adult life. They return to the upstream rivers to reproduce when they reach sexual maturity. Salmon are able to precisely return to their natal river, and even to the very spawning ground of their birth. This creative research explores my questions around identity and the idea of belonging through examining migrating salmon, and my own migrating experiences. What is the definition of home? Is it where you were born, reproduce, and die? Or where you mature? Salmon migrate to optimize their chance of reproduction as it defines their success. What about humans? What are we migrating for? Are we ultimately going to return to where we were from? My creative process starts with producing a soundscore combining text, breathing, and waves. The choreography is inspired by and generated through filmed improvisations as I experiment with different ways to interact with the soundscore and the props, always keeping my research questions in mind. The piece is a product of my desire to understand and reify the fear, confusion, exhaustion, excitement, and hope in the process of migration.

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.

Giardia lamblia is a gastrointestinal parasite which causes diarrheal disease and hinders nutrient absorption. G. lamblia colonizes the small intestine by a two-phase life cycle: the reproducing trophozoite stage and the transmissive, infective cyst stage via a fecal-oral route. How G. lamblia detects encystation signals in the encystation process is unknown. Our laboratory discovered EncystR, a seven transmembrane protein which compartmentalizes after perceiving cholesterol depletion and increased pH. Knockdown of EncystR promoted encystation, indicating negative regulation. We hypothesize that EncystR is responsible for perceiving encystation stimuli and de-repressing cAMP signaling to promote encystation. However, the mechanism responsible for triggering cAMP signaling is uncharacterized. This project hopes to identify EncystR transient interactions using proximity labeling and mass spectroscopy (LC-MS/MS). Proximity labeling of EncystR over an early encystation time course will identify proteins involved in downstream signaling. To determine time points of interest, EncystR was endogenously labeled with mNeonGreen (mNG), and imaging of non-encysting cells displayed EncystR-mNG at the plasma membrane. To delineate the EncystR trafficking pattern, we induced encystation and followed EnystR localization for several hours using fluorescent microscopy. Individual cells were categorized by localization to peripheral vesicles, a novel acidic compartment, or non-responsive cells where localization remained on the plasma membrane. Percent peripheral vesicle localization peaked at 1h and percent compartmentalization stabilized after 3 hours. Proximity labeling proteomics at these time points can identify connections to cell trafficking to the novel acidic compartment. While EncystR does not tolerate TurboID proximity labeling, miniTurbo produced significant biotin labeling after 30 minutes in 50 mM biotin. Biotin-tagged proteins are sequestered using Streptavidin-coated columns through liquid chromatography, then cataloged using mass spectroscopy (LC/MS-MS). Proximity-tagged proteins using miniTurbo can inspire drug inhibition candidates of Giardiasis. Due to Giardia’s model nature to other parasites, such as reliance on cholesterol, parallel drugs may be found as well.

Mitochondria are organelles responsible for Adenosine triphosphate (ATP) production and are central in biological aging research. Laboratory interventions that extend healthy animal lifespans also work to treat severe animal mitochondrial disease, however, how these interventions work at the molecular level is still unknown. Several longevity interventions extend lifespan and treat a model of Leigh Syndrome, a severe mitochondrial disease, in mice. Among these, rapamycin inhibits the metabolic master regulator mTOR (mechanistic target of rapamycin). This evidence suggests that mitochondrial disease and biological aging share a common cause at the cellular level. When mTOR is inhibited, SIRT3 is upregulated, an enzyme that controls mitochondrial fatty acid oxidation (FAO). We are using the mouse model of Leigh Syndrome, Ndufs4 knockout (KO) mice, to ask the following question: Does rapamycin treatment require SIRT3 activity to increase FAO to treat mitochondrial disease? Preliminary results show that SIRT3 is required for lifespan extension in Ndufs4 KO mice with rapamycin treatment. SIRT3 has also been observed regulating FAO. We are using both etomoxir, a drug that inhibits FAO, and rapamycin to answer this question by measuring lifespan. We are also measuring mitochondrial FAO directly in Ndufs4 Sirt3 double KO animals. Our results are allowing us to better understand how mitochondrial disease and normative aging are related, which will streamline targeting the biology of aging and mitochondrial dysfunction in humans.

The protozoan parasite Giardia lamblia infects hosts via the ingestion of cyst-contaminated water. We recently identified EncystR, a 7-trans membrane protein at the cell surface that acts as a negative regulator of encystation and responds to encystation cues by internalizing. By following the localization of EncystR through an encystation timecourse we discovered a novel compartment of unknown function. The Giardia endocytic pathway was only believed to include hybrid endosome/lysosome compartments statically positioned beneath the plasma membrane. We suspect this newly identified compartment may be a lysosome-like compartment. Using EncystR as a marker for this compartment we found that the compartment is highly acidified based on the florescent reporter pHluoren2. Canonically endomembrane compartments are marked by specific phosphatidylinositol phosphates (PIP). Relevant to endomembrane compartments, PI(3)P marks endosomes and PI(3,5)P2 marks multi-vesicular bodies and lysosomes. To test if this newly identified compartment is evolutionarily related to lysosomes, we will generate reporters for these phosphoinositides. Namely, we utilized the FYVE protein’s PIP binding domain as a sensor for PI(3)P which is located on endocytic membranes, the pH domain of PLC delta as a sensor for PI(4,5)P2 or PIP2 which is necessary for endocytosis and membrane-based cytoskeletal protein regulation, and ML1N for PI(3,5)P2 which is localized to lysosomes. Additionally, a mutant variant of the ML1N protein which is incapable of binding to PIPs is utilized as a negative control. These protein sensors were fused to the fluorescent protein mNeonGreen and imaged via fluorescent microscopy. While the experiment is currently in progress, we hypothesize that the localization of PIPs to the novel compartment will likely feature PI(3,5)P2 due to the previously found acidic nature of the compartment, implying a lysosome-like functionality. This possibly novel or conserved compartment could give insight into the evolution of eukaryotic cellular organisms and could potentially offer treatment routes for Giardia.

Alcohol use disorder affects 5.8% of adults in the U.S., incurring a yearly cost of $249 billion annually. The repeated and prolonged use of alcohol creates a variety of physiological and behavioral issues. Acute alcohol withdrawal syndrome encompasses seizures, delirium tremens, and in some cases, death. The dependence and withdrawal cycles lead to neuroinflammation, worsened withdrawal symptom severity, and impaired neuromodulation. The striatum plays an important role in the chronic aspect of addiction. This project focuses on how alcohol alters microglial function in this key brain region. At the Neumaier lab, we found that alcohol withdrawal increased the expression of genes involved in the unfolded protein response (UPR) in striatal microglia, the brain’s immune cells. The UPR is activated when there is an increase of misfolded proteins in the endoplasmic reticulum; which contribute to impaired cell function. The UPR is a protective mechanism in moderation, but when left unchecked, has been shown to increase cell death. We predict that removing CHOP will lead to a decrease in withdrawal symptoms and regulate the need to consume alcohol. Knocking out CHOP involves breeding CHOP fl/fl |Cx3cr1 CreER /eYFPI mice. We observe changes in the offspring via emotional behavioral tests after a 5 week period of CIE (chronic intermittent alcohol exposure). A second cohort’s brains are analyzed using cryosectioning and immunohistochemistry (IHC). My role is preparing the brains for analysis. The first step is removing and perfusing, which prepares the samples for cryosectioning. This is my other specialty, which is freezing and slicing the brains. Lastly, I conduct analysis with IHC, and look for physiological changes in the striatum. We anticipate our findings will have a positive and large impact on treating alcoholism. Our hope is to reduce the stigma surrounding addiction, and instead offer compassionate and scientifically based care.
 

Giardia Lamblia is an intestinal parasite known for causing the diarrheal disease giardiasis in host organisms. It commonly infects humans and companion animals such as cats and dogs. Giardia’s life cycle is defined by its infectious cyst stage and proliferative trophozoite stage. GlRac is a small Rho-family GTPase which we recently determined to play a role in regulating encystation in Giardia, the process of transition from a trophozoite to a cyst. Guanine nucleotide exchange factors (GEFs) and GTPase activating proteins (GAPs) are key regulatory proteins of GTPase activity. The GEFs and GAPs that regulate GlRac activity are currently unknown, but four candidates for GAPs and three candidates for GEFs have been identified. We are testing these GAP and GEF candidates in Giardia with a two-phase approach. First, we are using the protein-protein interaction reporter NanoBit to determine if the candidate GAPs and GEFs interact with GlRac. We are verifying results for NanoBit assays, a split NanoLuciferase reporter that indicates protein-protein interaction. Nanobit can reveal interaction but not the localization of the interaction, so we are performing co-localization with deconvolution microscopy. Candidate GAP and GEF proteins are being visualized using a mNeonGreen fluorescent tag while GlRac is being followed using the halogenase (HALO) tag labeled with Janeliafluor 646. The microscope assays allow us to determine if and where GlRac co-localizes with candidate proteins. Subsequently we will test the role of the identified GAP and GEF proteins in encystation through transcriptional repression using CRISPRi and translational repression using morpholino-modified antisense oligonucleotides (MOs.) If the candidate proteins are truly GAPs and GEFs, the knockdown cells should not progress through encystation as normal. GAPs and GEFs are potential drug targets for treatment of Giardiasis, as well as important in understanding the process of encystation in Giardia.

Additive manufacturing, also referred to as 3D printing, enables the fabrication of objects of any design based on a computer-aided design model. 3D printed structures comprising biodegradable protein-polymer networks have potential use for biomedical applications. The Nelson lab has developed a resin for vat photopolymerization 3D printing based on the protein bovine serum albumin (BSA). In my work, I investigated the response of these materials under different pH environments in order to simulate physiological conditions and gain an understanding of how these hydrogels respond to these different environments. I chose the protein-polymer network MABSA-PEGDA (Methacrylated Bovine Serum Albumin-Poly(ethylene glycol) diacrylate), a functionalized version of BSA that protects the globular structure of the protein. When altering the pH of given MABSA-PEGDA resins they retain their low viscosity, based on rheological measurements, and thus they retain printability. When printed, MABSA-PEGDA hydrogels have altered swelling and water holding capacities in pH 2 conditions as well as altered compressive moduli depending on the pH used to make the resin. Additionally, we performed CD spectroscopy and found that the alpha helicity of the protein was maintained, meaning secondary structure is not altered. The results suggested that there must be a change in the tertiary structure of the protein which induced changes in the protein-polymer matrix and altered the mechanical properties of the hydrogel. The next set of studies will include protein analysis techniques to understand the structure of BSA within the hydrogel constructs. The cumulative results of these studies will enable the use of these BSA-based materials for applications such as oral drug delivery that requires survival in harsh gastrointestinal environments.

This paper describes the expression of a non receptor tyrosine kinase, cymric (Uro-1), a HTK16-like (HydraTyrosineKinase-16) gene in Molgula oculata, an ascidian species with a tadpole larva and proposes that it plays a role in muscle development during the development of the tadpole phase. Cymric is also a member of the SHARK (Src-homology ankyrin-repeat containing tyrosine kinase) family of non-receptor TKs, a group of similar tyrosine kinases that can be found across many invertebrate species, but whose function is not yet known. The role of cymric in the development of the tail in tadpole ascidians was suspected after a subtractive hybridization showed cymric is expressed in M. oculata, a species with a tail and not in Molgula occulta a closely related ascidian whose tadpole is missing a tail. In Situ hybridization shows that in M. oculata embryos, cymric localizes to primordial muscle cells. Through transcriptome and genome analysis using both ANISEED and NCIB we show that the tyrosine kinase of the cymric gene in the M.occulta is disrupted by a large retrotransposon insertion. This indicates that, although the mechanism is still not known, cymric is involved in determination of muscle cells. A better understanding of the role cymric plays in development in ascidian species could provide insight into its importance in the many other invertebrate species which also express SHARK proteins.

Students in a statistics course made concept models throughout the course. Previous studies suggest that making concept models is a useful way for instructors to assess learning. The growth and changes of these student-constructed models may serve as an indicator of how a student constructs and organizes their cognitive structure. But, little is known about how much impact the Covid-19 disruption has had on a student’s cognitive restructuring in STEM courses. Therefore, we ask the following research question: What factors best explain the changes in the student-made models about statistics as representations of their cognitive structure? To address this research question, we analyzed concept models from three assessment points and two quarters of the same course, one taught before the Covid-19 disruption and the other during the Covid-19 disruption, to estimate the impact that the distributions had on their cognitive structures. After converting the 180 student model into graphs, we calculated the number of concepts in each model to build a linear model to compare a quarter taught before and during the major disruptions. First, we created a box and whisker plot that shows model growth across two different quarters, pre and during, and then we created a model to explain how the disruption term influenced the rate of concepts being added to student models at three different assessment points of the course. Our preliminary results revealed that students in the emergency online environment added concepts to their models at a significantly slower rate. Future directions and limitations will be discussed. This work is important because it helps teachers and professors understand how college students are learning in different environments.

Engineered genetic circuits provide an environmentally friendly path to chemical industries, including fine chemicals and therapeutics. To effectively modulate genetic circuits, a programmable tool to control multiple genes is necessary. CRISPR-mediated gene activation (CRISPRa) is an emerging tool suitable for this purpose. In CRISPRa, a nuclease-deficient dCas9 protein is used to deliver a transcriptional activator domain (MCP-SoxS) upstream of genes of interest. A complementary guide RNA (gRNA) enables dCas9 recruitment to any DNA target. Despite the programmability of CRISPRa, the number of genes that can be simultaneously regulated remain unexplored. In this work, we aim to experimentally investigate the number of gRNAs limitation in the chemical bioproduction context. First, we designed CRISPRa circuits with an increasing number of guide RNAs encoded on plasmids constructed with a scalable and high-throughput technique via Golden Gate Assembly. CRISPRa circuit performance was then evaluated by simultaneously regulating multiple fluorescent proteins as a proxy for multi-enzyme cascade in biosynthetic pathways. Increasing the number of gRNAs was found to decrease CRISPRa activity, suggesting competition of CRISPRa components. Furthermore, we applied the constructed circuits for metabolically engineered pathways in P. putida regulating production of p-aminocinnamic acid (pACA), a precursor for polymer synthesis vital in photovoltaic and biomedical applications. Bioproduction of pACA in P. putida was enabled by simultaneously regulating 9 heterologous genes. The outcome of CRISPRa circuits will be analyzed via High-Performance Liquid Chromatography (HPLC).The implication of this work will allow us to construct large scale CRISPR genetic circuits and optimize multi-gRNA CRISPR circuit integrations into other systems such as non-model organisms and cell-free systems, which will expand metabolic engineering capabilities and chemical productions beneficial in a wide range of biosynthetic applications.

 Immune cells make up the body's defense against cancer and observing their spatial distribution in a tumor can provide information about patient prognosis. However, it is difficult and time consuming to identify each immune cell in images from cancer biopsies in order to perform spatial analysis. Additionally, stained immune cells are hard to distinguish by appearance in unprocessed multispectral images due to the overlapping or "mixing" of signals coming from different channels. A computational tool could efficiently identify the immune cells in a tumor. The goal of this project is to build a digital pipeline to identify each immune cell in a multispectral image of a tumor and make it generalizable to multispectral images from any source. First, we use an unsupervised method to break up mixed multispectral images into clusters. The user selects a subset of clusters that do a good job of isolating each type of immune cell. A sample of these user-selected results are used to train a supervised machine learning model. The trained model assigns a label to each cluster to classify the entire image. Preliminary results have shown that clusters can usually be assigned to the correct label with over 50% certainty. We anticipate that the clusters will show good agreement with clinician classifications. This pipeline will allow for immune cell identification with less human involvement than pathologist annotation and without requiring spectral unmixing, a preprocessing step that typically takes hours. In the future, we will test this pipeline with varying amounts of training data coming from different sources and integrate it with spatial analysis to capture immune signatures of disease.

Alzheimer’s Disease (AD) is a neurodegenerative disorder characterized by the aggregation of the amyloid-β (Aβ) peptide into fibrillar β-sheet plaques. While Aβ plaques have been the historical focus in the study of AD, it has recently been shown that Aβ also forms oligomeric intermediates of a novel α-sheet secondary structure along its aggregation pathway. Furthermore, the formation of these α-sheet oligomers is correlated with the neuronal death and subsequent cognitive impairment seen in AD, and it begins up to 10-20 years before plaque formation or symptom development. In this project, I utilize a novel diagnostic technique known as the soluble oligomer binding (SOBA) assay to characterize the in vitro aggregation of Aβ through α-sheet detection in various timepoints of incubated Aβ. Additionally, I use SOBA to characterize AD phenotypes in transgenic mouse models using α-sheet detection in brain homogenate samples. SOBA selectively detects α-sheet oligomers using plate surfaces functionalized with in-house α-sheet peptide designs, followed by the introduction of amyloid samples and then amyloid-specific primary and secondary antibodies for detection. This research allows for the further elucidation of Aβ's structure and aggregation pathway, paving the way for future treatment methods for AD. Finally, I aim to translate my work with AD to develop SOBA for the system of Type 2 Diabetes (T2D) to detect the presence of toxic islet amyloid polypeptide (IAPP), the amyloid peptide implicated in T2D. This will be achieved through the systematic tuning of antibody systems and other procedural parameters such as plate washing methods. Preliminary results have shown the ability of SOBA to detect α-sheet in synthetic IAPP samples with concentrations as low as 10 pM. This novel method for toxic IAPP detection has the potential for T2D diagnosis earlier in disease progression.

Schools across the country struggle with the issue of meal debt and lunch shaming practices used to discourage the accumulation of negative meal balances. These practices include dumping students’ trays in the trash upon non-payment, requiring students to work off their debt, or publicly shaming them. Although lunch shaming was banned in Washington State in 2018, the impacts of this policy shift have not been studied. High-poverty schools shifted to government-subsidized universal school meal programs (USMP) to address students’ food insecurity. Studies show USMP significantly increase the meal participation of students who were already enrolled in free lunch programs. While scholars speculate stigma might explain this phenomenon, it has not been studied directly. This study explores the role of stigma in school meal participation by studying two populations; students who are considered non-poor with meal debt and students who are enrolled in free and reduced priced meal programs. This study considers the role of stigma as a barrier to school meal participation by studying meal debt and students at the eligibility margins in free lunch programs. This study addresses existing gaps in the literature through a combination of in-depth interviews and observations of schools ineligible for government-subsidized USMP. In-depth interviews with school administrators expand understandings of school-level cultures, mealtime procedures, and experiences with meal debt. Observations at a single school over a 2-month period reveal how students experience mealtime, how kitchen workers execute meal debt policies, and the dynamics between students, their peers, and authority figures in the lunchline. Findings show that stigma is reproduced in the lunch line and act as a barrier to student meal participation. 

Osteoporosis, a polygenic disease characterized by low bone mineral density (BMD) and increased fracture risk, is the most prevalent bone disease impacting over 200 million people worldwide. Because of the associated financial burdens and reductions in quality of life, there is an urgent need to determine the genetic causes of osteoporosis. The WNT family of proteins has been implicated in numerous developmental and disease pathways, with WNT16 specifically being linked to osteoporosis risk. WNT proteins contain 24 conserved cysteines, and mutations involving half of these cysteines are associated with human diseases or disrupted development in animal models. While modifications in cysteines 1-6, 8-9, 11-12, and 24 in different WNT proteins have been defined in vivo, the impact of cysteine 10 (c10) alteration remains unknown. Wnt crystal structure suggests that c10 creates a disulfide linkage with cysteine 11 and resides in a region that directly interacts with Frizzled receptors to initiate WNT signaling pathways. My hypothesis is that loss of c10 in WNT16 will result in altered BMD indicative of elevated osteoporosis risk. To test this, I outcrossed CRISPR-generated somatic zebrafish mutants harboring mutations at the wnt16 locus that target the c10 position, and isolated wnt16^w1012 mutants. Sanger sequencing and sequence alignment revealed a three amino acid deletion at Cys214, corresponding to c10 (p.Cys214_Gly216del). Analysis of micro-computed tomography scans showed significant decreases in wnt16^w1012 mutant centrum length, which matches wnt16 knockouts. My data indicates that wnt16^w1012 mutants phenocopy wnt16 knockouts, suggesting that c10 plays an essential role in WNT16 secretion and/or activity. My data further suggests that mutations that alter c10 have potential to contribute to osteoporosis pathogenesis. My ongoing studies are focused on further characterizing musculoskeletal phenotypes in wnt16^w1012 mutants and understanding the consequences of the mutation on protein structure through computational modeling.

Osteoporosis is a polygenic disease defined by low bone mineral density and is associated with increased rates for fractures and mortality. This condition commonly occurs in concert with sarcopenia, which is characterized by loss of muscle mass and function. When these occur in conjunction, a condition termed osteosarcopenia, there is an increased risk of falls which heightens the risk of fracture of already fragile osteoporotic bone. Genome wide association studies have identified genetic variants which influence osteosarcopenia-related traits. One such study identified pleiotropic effects on bone mineral density and lean mass at the CPED1/WNT16 lLocus. CPED1 has been hypothesized to be a causal gene, however there are very few studies characterizing CPED1, and it has no confirmed functions in humans or zebrafish. The goal of this study was twofold: to investigate the necessity of CPED1 for bone and lean mass in zebrafish. We analyzed a single-cell atlas of embryonic development and found that CPED1 is most strongly expressed in muscle. We generated two mutant alleles, CPED1w1003 and CPED1sa20221 via CRISPR gene editing. For analysis, 3 or 14 month old zebrafish were scanned using microCT, and ImageJ and FishCuT software were utilized to measure vertebral morphology and mineralization, lean mass, and standard length. Results showed no significant differences between mutant and control groups for both mutant alleles. The results of this study do not support CPED1 as being a causative gene underlying bone and muscle pleiotropy at the CPED1/WNT16 locus. This study also raises questions regarding the function of CPED1 in muscle and whether its loss may be compensated for by other genes.

Merkel cell carcinoma (MCC) is a rare and aggressive skin cancer with a mortality rate of ~30%. In ~80% of cases, MCC development is attributed to the integration of Merkel cell polyomavirus (MCPyV) DNA into the host’s genome, leading to the expression of viral oncoproteins and tumorigenesis. Developing treatments that sustain immunity against MCC is imperative to address recurrent and/or progressive disease. In many cancers, tumor-infiltrating B cells have been associated with better prognosis and response to immunotherapies. However, the mechanisms by which B cells contribute to tumor immunity in humans have been difficult to resolve in part due to the inter-patient heterogeneity of tumor-specific antigens. The shared nature of MCPyV tumor antigens in MCC allows for MCC-specific B cell responses to be studied across patients. Using DNA-barcoded and fluorescently labeled viral oncoprotein tetramers, we analyzed the transcriptome, proteome, and receptor repertoire of MCC tumor-infiltrating B cells in 12 patient samples at single-cell resolution. From paired heavy and light chain sequences, we cloned 8 antibodies from B cells specific for the MCPyV oncoproteins to confirm binding to MCC-specific antigens. Transcriptomic and proteomic analyses of MCPyV-specific B cells revealed heterogeneity of intra-tumoral B cell responses. Interestingly, we found that the absence of MCC-specific germinal center (GC) B cells in MCC tumors associates with disease progression: ~80% of patients with no detectable GC B cells had MCC progression within a year post-surgery, whereas patients with detectable GC B cells remained progression-free a year after surgery (n=12, p=0.0043). These results suggest strong synergy between B cells and T cells may regulate tumor growth, as B cells rely on signals presented by T cells to differentiate into GC cells. Our long-term objective is to identify B cell phenotypes associated with anti-MCC responses to develop therapeutics that boost cancer-specific immunity.

Massive stars place powerful constraints on stellar evolution and are observed in a menagerie of exotic evolutionary phases. These objects play a crucial role in regulating their environments. They drive the chemical evolution of their host galaxies, and set the energy balance of their surroundings via feedback processes. Due to the importance of massive stars, placing constraints on their evolution serves as a key to understanding galactic ecosystems. Notably, stellar variability is a powerful probe of the poorly-constrained physics of massive star evolution. In particular, variability studies on ensembles of evolved massive stars can significantly constrain stellar evolution. We aim to understand the variability of hot massive stars through a census of these objects. We accomplish this using data from the Gaia mission, cross-matched with light curves from the Zwicky Transient Facility (ZTF). We expect to characterize the evolution of massive star variability timescales and amplitudes along the main sequence and beyond. Our results will place key constraints on the evolution of massive stars. 

Active galactic nuclei (AGN) found at the center of galaxies are a compact region of space that produce significantly higher than normal luminosity. AGN are powered by the accretion of matter into a supermassive black hole and sometimes present winds called outflows. Whether outflows affect the evolution of their host galaxies is still a topic of research. Outflows with speeds of more than 10% the speed of light, called Extremely high-velocity outflows (EHVOs), have not been thoroughly explored, and due to their large energies, they might play a large role in star formation. In the 16th data release of the Sloan Digital Sky Survey, 98 new quasars with EHVOs were identified. With this new sample, I will present the results of my findings on the following questions: (1) What does the average EHVO quasar look like? (2) Do these extreme outflows vary more or less than other previously explored outflows? (3) Can we detect these EHVOs at higher speeds? To answer the first question, I will present a composite of the 16th data release EHVO cases found. To analyze if they vary more often or less than other EHVOs, I will present the results of a longitudinal variability study on the 51 cases that were observed on multiple occasions in the EHVO sample. For the last question, I will show the results of applying code our team has created to remove the Lya lines from our spectra, so the intrinsic ions (such as NV, Lya, OVI) will be easier to analyze at higher speeds.

My project studies Extremely High Velocity Outflows (EHVO) in Quasars. Quasars are particularly interesting due to the fact that they are one the most luminous cosmological objects that we have observed in the universe. They are systems at the centres of galaxies that host supermassive black holes--which have masses that range from millions to billions of solar masses--surrounded by an accretion disk of superheated plasma, gas, and dust. The phenomenon that we are studying are the EHVOs in quasars, which are gas outflows traveling at above 10% of the speed of light from the active central region. My project attempts to answer the question of whether quasars with EHVOs show distinct physical characteristics when compared to Broad Absorption Line Quasi-Stellar Objects (BALQSOs), which are quasars with outflows that show a broad absorption width but at lower outflow speeds, as well as compared to the general parent sample of quasars. We hypothesized that quasars with EHVOs show distinctive physical characteristics when compared to the other quasar categories. To study quasar physical characteristics to test our hypothesis, we used data from the Sloan Digital Sky Survey (SDSS) in the latest data release. Previously, our group has found the measurement values for all quasar samples to be overestimated. Thanks to data provided in Rankine+2020, we developed software and used the data to cross-correlate the values of physical parameters, such as bolometric luminosity (Lbol), Eddington ratio and black hole mass (Mbh). I will present the preliminary results of the analysis on EHVO quasar’s physical properties when compared to BALQSOs and the parent sample. These results suggest that quasars with EHVOs exhibit larger values of their Lbol and Eddington ratio when compared to the other two classes of quasars, while the Mbh parameter does not show significant differences.


 

Early-onset Alzheimer’s Disease (EOAD) patients have a greater risk of developing seizures. Consequently, EOAD patients who develop seizures have worsened comorbidities, including mortality and behavioral outcomes. The causal relationship between chronic seizures and AD is still unknown. Neuroinflammation has been postulated as one of the links between these two disorders. Our lab has previously demonstrated that young mice with a presenilin 1 (PS1) genetic variant and amyloid precursor protein (APP) overexpression, mimicking an EOAD phenotype and genotype, subjected to chronic seizure are at high risk of mortality. This behavior was not observed in young mice with an EOAD-associated presenilin 2 (PS2) genetic variation. We hypothesize that chronic kindled seizures evoked in 2 months-old APP/PS1 mice worsen neuroinflammation and other neuropathological hallmarks of EOAD, including β-amyloid (Aβ) accumulation in the brain. To address this, 2-month-old male and female APP/PS1 and PS2 mice were subjected to seizures through a corneal kindling model of chronic seizures. The right brain hemisphere was collected before and after mice achieve the kindled criterion (five consecutive 5 Racine scale scores). Brains were harvested and cryopreserved for immunohistochemistry. My role in the project was to process tissues for immunohistochemistry. 20-µm thick sections of hippocampus from each mouse were sectioned on a cryostat and slide-mounted before processing with commercially available antibodies for molecular markers of neuroinflammation and neuropathology. Photomicrographs were collected and images were analyzed as the number of immunoreactive cells for each molecular and protein marker. We anticipate increased neuroinflammation and Aβ accumulation in kindled APP/PS1 mice versus their respective wild types and non-kindled littermates. We do not expect differences in PS2 variant animals. These results add to a larger research study in the laboratory to suggest that targeting seizures, and its inflammatory response, may be a potential therapeutic strategy to mitigate the behavioral and neuropathological burden of AD.

My project involves making new tools for the genetic manipulation of Staphylococcus aureus. S. aureus is an important and pervasive human pathogen, however, much is still not known about its pathogenesis pathway and virulence genes. To better understand the genes and mutations that make S. aureus successful at causing disease, it is necessary to induce specific genetic changes and assess their impact on the organism’s virulence. However, currently available tools for bacterial genome engineering have yet to be optimized for S. aureus. Building on a successful recombineering system, previously developed by the Salipante lab, that is able to edit the S. aureus genome, we aim to address this need by using a dominant negative mutant protein of the mismatch repair (MMR) system to achieve suppression of DNA repair. Recombineering is the process of incorporating mutagenic DNA molecules into a host genome through the recombinase enzymes. Dominant negative mutations in the highly conserved MutL protein have been shown to disrupt the DNA base MMR pathway in several other microorganisms but have not yet been evaluated in S. aureus. My project aims to construct a temperature sensitive vector that highly expresses a ssDNA recombinase that is active in S. aureus along with a dominant negative mutL mutant able to bypass the MMR pathway. We anticipate that WT mutL should be able to repair a single base mutation since it has a functional MMR, reducing the number of successful recombinants relative to experiments performed with the multiple base pair mutations. The dominant negative mutL strains should not be able to correct a single base pair mutation, resulting in a similar number of drug-resistant transformats when recombineering with either a single base pair or many base pair mutations. This will allow us to better generate custom mutant strains and subsequently test the functions of various S. aureus genes towards a variety of clinically relevant phenotypes.

Iron centers which feature metal ligand multiple bonds can be powerful group transfer agents, for example, terminal Fe-oxo intermediates in soluble methane monooxygenase can perform oxo-atom transfer for the selective oxidation of methane to methanol. Abiologically, ligand constructs which enforce desirable electronic and structural configurations have been shown to enhance group transfer to a range of organic substrates. We developed and studied an iron (Fe) molecular complex with two aminophosphine selenide ligands (Se=PPh₂NTol; Ph=Phenyl, Tol=4-Tolyl) that chelate the metal center via the selenium and nitrogen. The iron complex (FeL₂) was synthesized by a reaction between Fe(HMDS)₂ (HMDS = bis(trimethylsilyl)amide) and the aminophosphine selenide. Characterization shows a tetrahedral, high spin, symmetric compound. We hypothesized that FeL₂ can activate and transfer heteroatoms and explored the reactivity of FeL₂ with oxidants, oxo atom donors, and organic azides. Treatment with iodine (I₂) results in oxidation of the iron center (Fe(II) to Fe(III)) and coordination of the iodide counterion results in structural reorganization to a five-coordinate square pyramidal complex. Reactivity with oxo atom donors shows that either the ligand or Fe center are oxidized, and we identified a µ₂-oxo dimer, which is the first Fe-O-Fe dimer to have selenium in its first coordination sphere. We found that FeL₂ forms Fe-nitrenoid intermediates and can perform nitrene transfer to form diazos or do C-H amination, when treated with aromatic and aliphatic azides, respectively. The presented complexes are characterized by single crystal X-ray diffraction (XRD), Evan’s method, nuclear magnetic resonance (NMR), and Ultraviolet-Visible Spectroscopy (UV-Vis). This research builds upon the knowledge of transition metal complexes for heteroatom transformations.

Edentulism, or the loss of all natural teeth, is a condition typically resulting from dental caries and periodontal disease, described as the ultimate manifestation of oral health disease burden. Edentulism has significant effects on masticatory function, such as chewing, swallowing, and speaking, as well as mental health and overall quality of life. Food insecurity has been associated with adverse oral health outcomes. However, this relationship has been insufficiently studied among low-income older adults, who are disproportionately impacted by oral health disparities and more likely to be edentulous. We hypothesized that food insecurity would be associated with increased prevalence of edentulism among low-income older adults in Washington state. To test this hypothesis, we collected data at seven community-based sites across Washington, including the Multi-Service Center in Federal Way and the Pike Market Senior Center. We administered a survey containing a 10-item measure of food insecurity to 218 participants aged 50 years or older. We also conducted dental screenings that involved examination of the mouth, gums, and individual teeth. 45% of participants (n=98) had marginal, low, or very low food security. 7.8% of participants (n=17) had zero teeth. We utilized logistic regression models to examine the association between food security and edentulism. Our preliminary analysis indicates that older adults with low or very low food security had 2.44 times the odds of being edentulous compared to those with high food security, after adjusting for age, sex, and race. Further analysis can help inform the development of feasible and effective interventions to address oral health inequities among low-income older adults.

The geologic record provides opportunity to provide actual examples of how plant communities have responded to climatic changes, providing important perspective for modern anthropogenic-driven climate change. Two important climatic events in the Miocene offer such an opportunity, including a global warming event, the Miocene Climatic Optimum (MCO; 17-14 million years ago), and a global cooling event, the Middle Miocene Climatic Transition (MMCT; 14-12 million years ago). This study is assessing how the diversity and prevalence of ecological strategies within Pacific Northwest (PNW) plant communities changed in response to these events, by analyzing ~6 PNW fossil plant sites that span these events in time. At each site I characterize ecological strategies of taxa comprising these ancient communities by measuring leaf vein density (LVD) of fossil angiosperm leaves, which relates strongly to the maximum photosynthetic rates of the plant. Photosynthetic rates influence ecological strategy by placing plants along a spectrum with fast growth but low tolerance to resource scarcity at one end, and slow growth and high tolerance at the other. I am digitally measuring leaf vein density using microscope images of fossil leaves previously taken at several museums where these fossils are housed. I expect that during the MCO, evergreen plants with slower growth rates become more dominant and the diversity of ecological strategies increased (lower mean and higher variance of LVD). Across the MMCT, I expect that deciduous plants with high growth rates became more dominant and stronger abiotic filtering caused a decrease in the diversity of ecological strategies present (higher mean and lower variance of LVD). This study provides a real-life example of how climatic events reshaped the assembly of plant communities and provide an important perspective for present and future climate change.

A feature of the criminal legal system of concern to scholars is court-issued monetary sanctions — the fines, fees, and costs imposed on people convicted of crimes. Prior research suggests these debts exacerbate inequality and perpetuate disadvantages for the affected individuals, families, and communities. While previous studies have found that monetary sanctions negatively affect family members of the debt-burdened individual, the impact of these debts on parent-child relationships remains unexplored. Attempting to bridge this gap in knowledge, this study examines monetary sanction’s influence on the nature of parenting. Scholars understand parents play a vital role in shaping and providing emotional and material resources for their children. Given this, it is important to understand the impact of monetary sanction debt on parents’ ability to provide these resources and ultimately how monetary sanctions impact child well-being. Utilizing interview data from a previous multi-state study of over 200 individuals with legal debt and children, supplemented by an analysis of interviews of similar individuals, this study examines how stress and material deprivation resulting from monetary sanction debt reduce the emotional and material capacity of parents to address their child’s needs. Preliminary analyses show parents frame the impact of debt as generating financial and emotional stress for them, and they attempt to minimize its direct effects on their children. In some cases, it is clear that parents are unable to provide important resources for their children, and the stress of debt negatively affects their relationships. These preliminary results suggest one additional avenue as to how monetary sanctions affect individuals. As other researchers have discovered, the impact is not simply resident with the person in debt but has an additional negative reach that should be understood as we look to reform the practice of monetary sanctions.

Metabolites are small organic compounds that are the products of cellular metabolism and the building blocks of macromolecules. The analysis of a multitude of metabolites in a sample simultaneously is known as metabolomics and is a powerful tool for understanding microbial interactions in the ocean. In particular, metabolomics provides a way to investigate how marine communities vary in composition during shifts in environmental conditions. The North Pacific Subtropical Gyre (NPSG) is a region where inorganic nitrogen availability limits phytoplankton productivity and microorganisms rely partially on diazotrophs for fixed nitrogen in the surface ocean. Because N2 fixation is often iron-limited, bioavailable iron should control fixed nitrogen levels in the gyre. Here, we tested this hypothesis by collecting metabolomic samples during a large-volume incubation in which tanks were amended with various nutrient combinations of iron, nitrogen, and phosphate during a month-long incubation. It was expected to stimulate a diazotroph bloom by limiting the incubation for nitrogen. In these nitrogen-limited tanks, we expect to see a strong metabolic response to the absence of fixed nitrogen, followed by the ingrowth of nitrogen fixers with their own metabolite fingerprints as the experiment progresses. I will compare metabolomes of incubations to those of phytoplankton cultures, including the nitrogen-fixing cyanobacteria UCYN-A and Trichodesmium. I will also use the incubation's nutrient concentration and microbial community metabolomics to test the hypothesis that altering nutrient supply ratios (Fe: N: P) in the NPSG microbial population will result in metabolite shifts. As the critical link between inorganic matter and the formation of the organic material that powers the ocean’s food chains and biological carbon pump, metabolomics provides a way to better understand the critical role that nitrogen fixation plays in regulating the taxonomy and biochemistry of the world’s largest biomes.

A large composition of our universe remains unidentified. Ordinary ‘visible’ matter comprises 5% of the known universe whereas dark matter comprises 27%. The Dark Matter in CCDs (DAMIC) research team hypothesizes that charge-coupled devices (CCDs) may be able to detect weakly interactive massive particles (WIMPs) as a possible candidate for dark matter. The silicon CCDs gather information by measuring the ionized charge from collisions between its silicon atoms and external particles, yet these measurements can become inaccurate in the presence of noise. The leading noise source is leakage current across the CCDs, which can be mitigated by operating the experiment at 100K. Furthermore, CCD performance is highly dependent on temperature so we must assure a constant temperature across the CCDs. Obtaining this temperature is essential in the successful implementation of the DAMIC-M experiment. We started with multiple thermal tests on a single mock CCD module housed in a copper box to ensure proper cooling. We aimed for minimal temperature differences of the box and across the silicon once they reached 110K temperatures. Our initial tests showed large temperature differences leading us to make modifications to the arrangement of the module in the box. Once these modifications were implemented, a consistent trend of minimal temperature differences between the box and silicon was present. Following this development, we began further testing with a new box which holds 13 mock CCD modules. This new arrangement mimics the final DAMIC-M experiment which allows for a more accurate representation for future thermal tests. 

The Miocene Climatic Optimum (MCO) was a period of global warming 17-14 million years ago, where temperatures increased 2-4°C and CO₂ levels increased to ~400-600 ppm. Overlapping with the MCO were the Columbia River Basalt eruptions (CRB: 6.6-15.9 Ma), where extensive lava flows spread across the Pacific Northwest, resulting in primary succession. My study is focused on reconstructing the vegetation across the MCO and during CRB eruptions using epidermal phytoliths (i.e., Microscopic Biosilica) to understand how these conditions impacted plant communities. Epidermal phytoliths are formed within living plant matter reflecting the current environmental conditions in their size and undulation. The plant matter then falls to the forest floor and decays leaving behind the resilient Microscopic Biosilica, which is preserved within that sediment. Leaves formed in ecosystems with an abundance of sunlight reflect open-canopy vegetation, with small circular phytoliths; while large-undulated phytoliths come from closed-canopy, shady environments. Previous work has shown a correlation between the average size and undulation of epidermal phytoliths with leaf area index (LAI; i.e., a measure of canopy openness). I am using this process with sediment samples collected across four sites in Central Oregon to calculate ancient reconstructed LAI (rLAI), and thus reconstruct the canopy cover. Each site was chosen due to the time period it represents, with different exposure to increasing variations of CO₂ and CRB impacts. I hypothesize increased temperature and atmospheric CO₂ concentrations during the MCO created favorable conditions for plant communities, which promoted a productive closed-canopy forest structure. Additionally I hypothesize, the primary succession induced by CRB volcanism prevented the re-establishment of forests, leading to open-canopy vegetation structure. As modern day anthropogenic-driven climate change invokes alterations in our planet's ecosystems, we need to better predict and anticipate future responses of plant communities to these environmental perturbations. 

Quasars are compact regions at the center of a galaxy that have much higher than normal luminosity. Gas outflowing in winds is common in quasars, and it might play a role in regulating the black hole growth and star formation in the host galaxies. In particular, the ones with extremely high speeds (>~0.1c) have not been thoroughly studied and might pose the biggest challenges to the simulations of how these outflows are driven. A 2020 study by Rodríguez Hidalgo et al. identified 40 quasars with Extremely high-velocity outflows (EHVOs) in the 9th data release of the Sloan Digital Sky Survey by detecting absorption in quasar spectra. The C iv emission properties of this sample were examined in a 2022 study by Rodríguez Hidalgo & Rankine. Compared to the general population as a whole, these extreme outflows seem to be more predominant in quasars with large blueshifts of the C iv emission line, an indication of outflows in emission, but the sample was small. My project aims to answer the question: do EHVO quasars show distinct emission features compared with the general population of quasars? To answer this question, I carried out an extension of a 2022 study, but using a larger sample of 98 new EHVOs that we identified from the latest data release. I built on the python code that our team has previously created, which cross-correlates the sample of 6743 quassars from the 2020 study with measurements calculated by a 2020 study by Rankine et al and allows us to place the EHVO quasars in the C IV emission line parameters space (blueshifts vs emission intensity). Potential connection between the maximum EHVO velocity and increasing C IV blueshifts is also explored.

As the planet progressively experiences the effects of climate change, the US government is increasingly more interested in limiting the country’s resource consumption with a focus on limiting the footprint of corporations and manufacturers. The US Department of Energy (DoE) created a national network of Industrial Assessment Centers (IAC) within colleges, including the University of Washington, to provide recommendations that will be backed by DOE matching funds to facilities. The mission of the UW IAC is to reduce the energy consumption and emissions, improve overall efficiency, and implement cutting-edge technologies in a minimum of 20 facilities across Washington state and the Pacific Northwest, annually. We hypothesize that, by giving corporations free energy audits with financial incentives and training students to be energy savvy engineers, Washington state will reduce its overall energy consumption and be a leader nationally in resource management. The main methods to my research include initializing our energy audits with companies, preparing preliminary recommendations based on the company’s industry classification, touring the facility while collecting machinery and energy data, and writing detailed DOE-accredited reports entailing the best potential savings for the facility’s overall energy reduction. To date, the UW IAC has provided 250+ recommendations and 50+ assessments to industry, saving 1.49+ TBtu of energy. We have and continue to analyze a breadth of technologies ranging from air compressors, refrigeration, HVAC, lighting, automation, motors, and overhead operations in corporations across a variety of industries including aerospace manufacturing, food production, wastewater treatment, and paper mills. The significance of this pursuit is providing corporations an incentive to reduce their environmental footprint through an increase of revenue and modernization of their practices. We ultimately strive to bring Washington state to the forefront of efficient and clean energy practices.

Hemagglutinin (HA) is a glycoprotein found on the surface of the influenza virus. HA binds to sialic acid receptors on host cells and mediates membrane fusion, allowing the virus to enter the cell. This project investigates how mutations associated with species crossover affect viral fusion mechanisms in influenza HA. HA from the past outbreaks of H5N1 influenza strains in Vietnam in 2004 (VN04) and Indonesia in 2005 (IN05), are being compared to an HA from an on-going avian influenza outbreak using a strain isolated in Colorado in 2022 (CO22). Through site-directed mutagenesis, mutations that affect acid stability and affinity for the human receptor were added to HA based on the VN04 and IN05 strains; we are studying these effects in recombinant protein rather than on infectious virus. These mutations are believed to enable the virus to increase transmissibility among mammals including humans. To compare how HA from these H5 isolates with and without the adaptive mutations behave, hydrogen-deuterium exchange mass spectrometry (HDX-MS) is being used to measure changes in deuterium incorporation on the protein backbone for specific peptide segments, giving a profile of local dynamics and structure throughout the HAs. By comparing the dynamic profiles for each as pH is lowered, mimicking acid-activation in host cell endosomes, we can probe how their structure in important fusion and human receptor-binding regions change as the fusion protein becomes activated. By comparing the structural dynamic changes of the WT and mammal-adapted, mutated IN05 and VN04 HA to the new CO22, we will be able to increase our understanding of the effect of the mutations that are associated with species crossover and hopefully be able to gain insight into the potential of this new avian influenza strain’s ability to become transmissible among humans.

In face-to-face surveys containing sensitive questions, Social Desirability Bias (SDB), respondent’s tendency to provide socially acceptable responses rather than truthful ones, can compromise data accuracy. Randomized response techniques (RRT) are survey models that allow respondents to provide scrambled responses, thereby circumventing SDB. In this study, we introduce a mixture optional quantitative RRT model that combines the elements of both the Pollock and Bek (1976) additive RRT model and the Greenberg et al. (1971) unrelated question quantitative RRT model. We examine the utility of the proposed mixture model using a unified measure of efficiency and privacy introduced by Gupta et al. (2018) that provides a metric of both predictive accuracy and respondent privacy. We also account for the lack of trust in RRT models. Both empirical and theoretical results show that the mixture model outperforms the two component models. The proposed optional quantitative mixture RRT model provides a survey technique that can account for not only SDB but also respondent lack of trust, leading to more accurate and interpretable data used to inform decision making that does not compromise the privacy of respondents.

In the midst of World War I and the Mexican Revolution, a document known as the Plan de San Diego emerged in South Texas. Discovered by local police in January of 1915 in McAllen, Texas when they arrested a Mexican national, the Plan called for a total racial revolution against Anglo-Texan power. A few months later, raids in support of the Plan broke out. Historians have primarily disputed over whether the Plan was an authentic product of local Tejano radicalism, or part of a wartime master plan by German and Mexican conspirators. The mystery surrounding its authorship and the raids has contributed significantly to this lack of consensus. My research traces the roots of the Plan’s rhetoric and the movement around it through the history of Mexicanos in Texas. I argue that the racial logic of the Plan demonstrates a real grounding in local history, regardless of its authorship. Rather than focusing on the moment in itself, I follow the lineage of the “Mexican race” which it attempted to mobilize. To do so, I closely read the wording and differences across time and space in legal policy, court cases, proclamations, newspapers, and folk music. In particular, I read the operation and formation of social-political categories between the lines of these texts. This approach draws significantly on racial formation theory, which offers a means to understand how such a movement could come about. By incorporating this critical approach, I hope to make a step forward in critically analyzing history as an element in racial history and the development of the identity "la raza," which the Chicanx movement mobilized later in the 20th century.

Radon in high concentrations has been proven to be one of the world’s leading causes of lung cancer. Climate change is an ongoing problem that affects the environment and human beings; however, there is not yet a widely known relationship between radon exposure and climate change. Our research aims to find a correlation between climate change and risk of radon exposure. We are reviewing how radon exposure potentially increases through the lens of greenhouse gas emissions, melting ice caps, and human habits based on increased global warming effects. In our literary review, we are comparing how radon is measured, finding the limitations of each technique and which technique is best suited to measuring radon in air, soil, and water. We are also working with our collaborators overseas to understand the radon concentrations in soil in Hebron, Palestine. We will investigate our hypothesis that radon exposure will increase with climate change.

Climate change is a growing threat to communities worldwide, with extreme weather events like droughts and wildfires causing food insecurity and affecting the lives of millions of people. Despite the availability of research that describes the consequences of climate change, there is a lack of urgency in the response to this crisis. To understand the barriers that inhibit action on climate change, a study was conducted on 206 STEM students at the University of Washington. The study surveyed the students to identify factual and conceptual barriers to addressing climate change. We distributed questionnaires through social media and undergraduate classes. I analyzed survey responses to compare and contrast the concern levels for ecocentric and anthropocentric consequences of climate change. The findings of the study indicate that environmental education was not associated with more climate change knowledge, and students were more concerned with ecocentric impacts and anthropocentric consequences that directly impact basic human needs like water, food, and shelter. We aim to develop a teaching tool that addresses the conceptual barriers identified in their research. The results of the study emphasize the need to shift the focus towards addressing the immediate impacts of climate change that affect human well-being. The lack of urgency in the response to the climate crisis highlights the need for more education and action to mitigate the effects of climate change.

Aging is associated with shifts in the composition of brain extracellular matrix chondroitin sulfate glycosaminoglycans (CS-GAGs). CS-GAGs are comprised of repeating glucosamine and N-acetylgalactosamine units that are either non-sulfated (0S-CS), mono-sulfated (4S-CS, 6S-CS), or di-sulfated (2S6S-CS, 4S6S-CS, 2S4S-CS/Dermatan) and participate in the regulation of brain plasticity. The mono-sulfated 6S-CS isomer is predicted to play a key role in the induction of circuit plasticity during neurodevelopment. Therefore, we asked whether this isomer also shows consistent age-related changes between wild-type mice and humans in the regions of the hippocampus and cortex. Our preliminary data generated from cohorts of mice ranging in age from 7 days to 2 years (50%M/50% F) reveal that 6S-CS abundance is highest at 7 days of age and declines with increasing age (9-22 mice/group). We analyzed the relative abundance of the 6S-CS isomer in n=57 hippocampal and cortical human tissue samples (age: newborn - 95 years, sex: 50%M/50% F). Initially, the human samples exhibited the highest abundance of 6S-CS isomer following birth (<1 month age) that then declined at >1M to 29 years of age, phenocopying the results from mice. However, in contrast to mice in which 6S-CS abundance decreased progressively with aging, we found that in humans, 6S-CS abundance began to increase starting at 30 to 99 years of age (R² = 0.84, p-0.0001). The biphasic model of changes in 6S-CS abundance in humans throughout normal aging was previously unknown. Collectively, these findings demonstrate that age-associated changes in brain extracellular matrix 6S-CS isomer abundance in human tissue do not reflect the age-related decline of 6S-CS isomers that occur in mice. Therefore, additional research is needed to establish the utility and robustness of using rodent models to study aging and other age-related extracellular matrix diseases in humans.

Leigh Syndrome (LS) is the most common form of mitochondrial disease in children. It affects 1 in every 40,000 births and is characterized by ataxia, seizures, failure to thrive and premature death. There are more than 75 gene mutations that have been associated with LS. Among them is NDUFS4, the gene that codes for a subunit of the protein complex I of the mitochondria. Mice carrying a whole-body knockout (KO) of this gene greatly model this illness; they recapitulate multiple phenotypes of LS in patients. Prior studies in the lab have shown that the KO of Ndufs4 in GABAergic neurons, not in excitatory neurons, across all brain regions, reproduce the epilepsy phenotype seen in the global KO mice. Moreover, GABAergic neurons in a specific brain region such as the brainstem are sufficient to lead to epilepsy in mice. Mice with Ndufs4 KO in brainstem and cerebellum interneurons, mediated by GlycineCre, have epilepsy. However, it is still unclear as to what brain regions housed neurons involved in seizure activity in these mice. In this study, brain regions experiencing neuronal hyperactivity and hypersynchrony during seizures in this new model of LS were examined. A thermal seizure was induced in the Ndufs4 GlycineCre KO mice. Forty-five minutes after the seizures, the mice were anaesthetized, the brains were fixed, and harvested. Brain slices were prepared and stained with a c-Fos antibody and finally imaged on the confocal microscope. Surprisingly, high c-Fos immunoactivity was observed in the cerebellum alone and not in other brain regions generally known to be involved in seizure generation. These findings indicate the participation of the cerebellum in seizure generation in Leigh Syndrome epilepsy. In future studies, we will repeat this experiment to increase the sample size and confirm these findings.

The Ndufs4 gene codes for a subunit of complex 1 in the mitochondrial respiratory chain. Mutations causing a loss-of-function of the Ndufs4 gene are linked to Leigh syndrome(LS), a progressive neurodegenerative disorder. LS is characterized by progressive loss of mental, and movement abilities, respiratory distress, and epilepsy, leading to premature death within 2 to 3 years. It is the most common clinical pediatric presentation of mitochondrial disease. Mice with global Ndufs4 knockout(KO) are a good model of LS, exhibiting seizures and other phenotypes of LS. Previous work has shown that epileptic seizures arise from the impact of Ndufs4(KO) in GABAergic interneurons. The objective of my project is to further our understanding of the mechanism of LS-related epilepsy. I assessed the impact of the Ndufs4(KO) on interneuron morphology as a possible contributing factor to the development of seizures. The LS mouse model was generated using the Cre/LoxP mechanism. Two mice with floxed Ndufs4, one is Dlx12cre positive and the other is homozygous Ai14, were crossed creating mutant mice. Control mice were generated similarly, but parents are Wild-Type (WT) for Ndufs4. Mice were perfused with phosphate-buffered saline (PBS) and fixed with 4% paraformaldehyde (PFA). I made 50-um coronal brain slices using the Leica VT1000S Vibratome. Then, I mounted the slices and used the Olympus slide scanner to collect fluorescent images. We found scattered labeling of GABAergic neurons in both the control and mutant forebrains. Our results show that the Dlx12cre+ mouse can label a dispersed population of GABAergic neurons across multiple brain regions. Neural dendrites are visible in our images of control and mutant mice. Optimizations are needed to improve the image resolution for optimal Scholl analysis. This study elucidates the impact of Ndufs4 on interneuron morphology and the contribution of this neuronal characteristic in the mechanism of epilepsy in LS.

Avian scavengers perform a critical ecosystem service by breaking down dead and decomposing organic matter and recycling nutrients. However, the scavenging dynamics of birds have received relatively little attention compared to the dynamics of scavenging mammals. Carcasses provide an ephemeral food source for avian scavengers, which presents them with the unique challenge of locating the carrion. This makes detection and consumption efficiency a topic of interest as not all avian scavengers follow the same pattern of arrival at a carcass. Here, we examine avian scavenger succession – the order in which species arrive and consume carcasses – through monitoring ungulate carcasses in Washington State. We found that turkey vultures outcompeted all other avian scavengers when they were present in summer months, while black-billed magpies and common ravens outcompeted golden and bald eagles in winter months. This confirms previous studies that have found that turkey vultures have morphological and genetic advantages that enable them to readily find carcasses and that body size does not determine succession in this scavenging guild. Our study highlights how social scavengers outcompete solitary scavengers and reach carcasses sooner, regardless of the physical characteristics of a species.

 Dravet syndrome (DS) is a genetic form of epilepsy characterized by febrile seizures in infancy, developmental delays, and sudden unexpected death in epilepsy (SUDEP) as a result of being drug-resistant. Finding new and innovative treatments is essential to reducing the risk of SUDEP and other symptoms in DS patients. Using a mouse model of DS (SCN1a+/- mouse), I showed that a machine learning-based detection algorithm could be used to detect interictal spikes (IS), which are abnormal neuronal discharges typical of epilepsy. The goal of the current experiment is to see whether the prior findings can be generalized to a larger dataset and whether the detected IS can be used to predict seizures before their onset. Data is collected by implanting two electrocorticographic electrodes and one electromyography electrode, as well as a wireless body temperature sensor in DS mice. Ambient temperature is controlled so that the animal’s core body temperature is initially maintained at 37°C and then is gradually increased by 0.5 °C every 2 min until a seizure is observed or the core body temperature reaches 42.5 °C. A machine learning model previously trained using manually scored data from the de la Iglesia lab is used to autonomously detect IS in the collected data. My results so far showed a moderate yet significant positive correlation between ambient temperature increases and IS frequency and points to a positive correlation between IS frequency and seizure onset. However, these results did not include the continuous recordings of body temperature. In the current experiment, I test if these correlations hold using a larger sample size and including continuously recorded body temperature, which may have more predictive power than ambient temperature. Our long-term plan is to design a closed-loop experiment that uses the algorithm to predict and stop seizures before their onset.

About one-quarter of photosynthetically fixed carbon is cycled through the marine microbial community in the form of metabolites, the intermediate compounds or products of metabolic processes. Marine heterotrophic bacteria are largely responsible for consuming these metabolites as a source of carbon, energy, and nutrients, yet little is known about transporter affinity and uptake kinetics of bacteria for abundant substrates. Homarine is a small, nitrogen-containing, zwitterionic metabolite that is produced by the cyanobacterium Synechococcus as well as some diatoms and haptophytes, where it is thought to function as an osmolyte. Dissolved homarine is present in the ocean at very low concentrations (~1.1 nM in Puget Sound). I hypothesize that these low concentrations are the result of high affinity bacterial transporters for homarine. Homarine can be used as a sole carbon and nitrogen source for OBi1, a marine bacterium isolated from Puget Sound. In this study, I investigate the uptake kinetics of homarine by OBi1 in the lab using the Michaelis-Menten model. I compare the uptake kinetics of OBi1 to similar homarine uptake experiments in the Salish Sea in June 2019. I expect that OBi1 will have a high affinity for homarine uptake and will take up homarine at nanomolar concentrations. I also anticipate that the marine microbial community in Puget Sound will have similar uptake kinetics to those observed with OBi1. Understanding the uptake kinetics of homarine by marine bacteria sheds light on the cycling of homarine in marine environments like Puget Sound and can help us understand the processes that keep the dissolved homarine concentration so low.

Understanding how species of kelp perform under different environmental factors is critical for the management of kelp farming and its effects on carbon sequestration. In this study we evaluated how low salinity and water temperature affect two kelp species: bull kelp (Nereocystis luetkeana) and ribbon kelp (Alaria marginata). Pulse-amplitude modulated (PAM) fluorometry was used as a proxy for health, while wet weight and the hole-punch measurement method determined growth. At Friday Harbor Laboratories (San Juan Island, WA), we collected and exposed ribbon and bull kelp to different treatments under grow lights for a standard photoperiod (12 hours/day) in closed-circulatory sea tables for 72 hours. Our treatments were high temperature (20ºC/ 30PSU), low salinity (12ºC/ 25PSU), high temperature with low salinity (20ºC/ 25PSU), and control (12ºC/ 30PSU). The results of the stress test via PAM fluorometry demonstrated 0% survivability of bull kelp for both heat and the combination of heat and salinity at 24 and 48 hours (Fv/Fm = 0) while ribbon kelp survived. When comparing percent change of wet weights, ribbon kelp gave a p-value of <0.05, with significant differences between combined treatment with control and salinity treatments, whereas bull kelp gave a p-value >0.05, however temperature treatments of bull kelp did not survive (Kruskal-Wallis test and Dunn post-hoc). These results indicate that heat has a more significant effect on kelp than salinity. This data is increasingly relevant as the environmental effects of climate change increase global temperatures and could identify which kelp species are most vulnerable.

The modern education system has the opportunity to raise students with a well-rounded, interdisciplinary knowledge base, but that does not begin until textbooks (the backbone of many science curricula) include such topics. We wondered to what extent Multiple Ways of Knowing (MWoK), particularly in the topics of religion, culture, traditional medicine, and philosophy, are represented in introductory biology textbooks. The term MWoK describes these topics and recognizes that there is more than one way to learn and understand, crediting different cultures for their scientific contributions. This study is a spin-off from a greater project in which our team scored and evaluated six introductory biology textbooks on how much and how well they included a variety of social justice topics. Using the data gathered from the aforementioned study, we categorized the instances of MWoK by frequently occuring themes - religion, culture, traditional medicine, and other. We found that across over 9670 pages, these textbooks lack adequate discussion of MWoK, with only 32 mentions. Within these few instances, only one showed themes of justice or injustice, and one demonstrated themes of equity and inequity. Textbooks alone are insufficient for implementing the diversity of science in American classrooms. We envision this research as a starting point for instructors to integrate these topics into their classes. Incorporating more involved conversations about MWoK within the context of science can act as a way to foster a more inclusive learning environment wherein all students are able to engage more meaningfully with the material. Including MWoK in biology textbooks, and thus, biology curricula, would bring the STEM classroom one step closer towards increased diversity. 

Purple sea urchins (Strongylocentrotus purpuratus) pose a serious threat to the environment by consuming entire kelp forests that serve ecological functions like carbon sequestration. We compared the preference of purple sea urchins on various kelp species to understand how feeding habits changed across different environments: temperature (ambient 13 °C, high 20 °C) and salinity (ambient 30 PSU, low 22 PSU). Urchins were collected from the subtidal zone in Friday Harbor, San Juan Island, WA. At the University of Washington Friday Harbor Labs, urchins were exposed to either ambient (6.8L), high temperature and ambient salinity (6.8L), low salinity and ambient temperature (6.8L), or high temperature and low salinity water (3.1L). Within these treatments urchins were given Bull Kelp (Nereocystis luetkeana), Ribbon Kelp (Alaria marginata), and Fringed Sieve Kelp (Neoagarum fimbrata) for 24 hours. To track kelp consumed, we weighed the kelp before and after each trial. Results showed that Bull Kelp was consumed the most in every environment except high temperature, low salinity. In low salinity and high temperature urchin feeding was significantly different and lower from the ambient environment, as most urchins ate nothing over 24 hours (Kruskal Wallis and Dunn’s test, p-value > 0.05). Our findings suggest that in areas with lower salinity and higher temperatures, urchins may be a smaller threat to kelp. In many environments, bull kelp is most vulnerable to urchin feeding, making it an important species for conservation efforts.

 Children are tasked with listening and learning in noisy environments where many people are talking at the same time every day. Conceptual models of listening under complex conditions posit that working memory plays a role in the ability to extract the target speech from the distracting noise. Hard-of-hearing (HoH) children, in particular, do worse listening in noisy environments. Thus, in this study we investigate the relationship between working memory and multitalker speech perception in HoH children. We hypothesized that we would observe a correlation between working memory and speech perception in both HoH and the typical hearing comparison group. Moreover, we expected that HoH children will have worse multitalker speech perception thresholds overall, suggesting difficulty perceiving speech under complex acoustic conditions. We tested 7-to-18-year-old HoH children and an age- and biological sex-matched typical hearing (TH) comparison group. Working memory was assessed in both visual and auditory domains; participants were asked to recall either a sequence of visually presented letters or auditorily presented numbers. Multitalker speech perception thresholds were obtained under 2 conditions: Collocated noise and Segregated noise. In the Collocated Noise condition, the target speaker spoke sentences from 0° azimuth with two additional distracting talkers, referred to as maskers, collocated from the same location. In the Segregated Noise condition, the distracting talkers were spatially segregated to ±90° azimuth, while the target talker remained at 0°. Preliminary analyses suggest that a relationship between working memory and multitalker speech perception is observed. These results will advance our understanding of why HoH children experience difficulty perceiving speech under noisy conditions and have the potential to lay the groundwork for novel assessment and intervention strategies to improve how TH and HoH children listen and learn in a noisy classroom. All authors participated in data acquisition, analysis, and preparation of this presentation.

Phonemic proficiency refers to the ability to manipulate the phonemes, or unit of sounds, in a word. Speech perception deficits has been linked to lower phonemic proficiency, as children have difficulty isolating, manipulating, and blending sounds that they cannot perceive. Autistic children commonly report difficulty perceiving speech in noisy real-world environments where many people are talking at the same time, such as a classroom or playground. Thus, in this study, we investigate the relationship between phonemic proficiency and multitalker speech perception in autistic children. We hypothesized that we would observe a stronger correlation between speech perception and phonemic proficiency in autistic children compared to the neurotypical comparison group. Moreover, we expected that autistic children will have worse multitalker speech perception thresholds overall, suggesting difficulty perceiving speech under complex conditions. We tested 19 7-to-10-year-old autistic children and a comparison group of 19 age- and biological sex-matched neurotypical children. The Phonemic Proficiency subtest of the Weschler Individual Achievement Test – Fourth Edition was administered to assess phonemic awareness. Multitalker speech perception thresholds were obtained under 2 conditions: Co-located Noise and Segregated Noise. In the Co-located Noise condition, the target speaker spoke sentences from 0° azimuth with two additional distracting talkers, referred to as maskers, co-located from the same location. In the Segregated Noise condition, the distracting talkers were spatially segregated to ±90° azimuth, while the target talker remained at 0°. Preliminary analyses suggest that a relationship between phonemic proficiency and multitalker speech perception is observed. These results will advance our understanding of the difficulty autistic children have perceiving speech and have the potential to lay the groundwork for novel assessment and intervention strategies to improve how children with and without autism listen and learn in a noisy classroom. All authors participated in data acquisition, analysis, and preparation of this presentation.

Mutations in the genetic sequences of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS CoV-2) has played a major part of the pandemic. This is evidenced by the increasing number of distinct strains that have appeared. Evaluating these mutations and their frequency within genetic sequences offers the opportunity to identify patterns that aid in increased virility for SARS CoV-2. We identified prevalent SARS CoV-2 strains in GISAID and downloaded genetic sequences from the NCBI nucleotide database. We used MAFFT (Multiple Alignment using Fast Fourier Transform) in Seaview to align SARS CoV-2 strains to the reference genome. We also built a custom python script to identify locations of mutations, and their potential effect on the proteins’ amino acid sequence. Preliminary work identified a mutation in the ORF1ab gene of the omicron strain. Part of this gene codes the typically conserved NSP-16, associated with the product 2’-O-ribose methyltransferase, an enzyme that catalyzes the transfer of a methyl group from a methyl donor molecule. The modification could affect the stability, localization, and function of RNA such as RNA splicing and post-transcriptional modification. We then generated a phylogenetic tree using BEAST/BEAuti to estimate the frequency and history of mutation across different strains. Our analysis identifies mutations accumulated over the course of the pandemic. Studying the effects of these mutations offers insights into SARS CoV-2 virology. These insights can be used to build a predictive model to aid in effective and efficient vaccine development.

The purpose of this study is to establish biomarker assays for physiological stress linked to arsenic exposure and microbiome perturbation in freshwater snails. The ASARCO smelter in Tacoma, Washington polluted soil and water around Puget Sound with arsenic for nearly 100 years. Previous studies have shown that environmental pollutants can alter the gut microbiome and modulate host-microbe interactions in mice. However, little work has been done to understand how chronic exposure to environmental pollutants can impact the microbiota or physiology of primary consumers in aquatic ecosystems. To address this gap in knowledge, we are studying Chinese Mystery Snails (CMS) collected from three lakes in the Puget Sound region: Lake Killarney (20 ppm As), Steel Lake (2 ppm As), and Pine Lake (trace As). We hypothesized that snails exposed to higher concentrations of As are subject to greater levels of physiological stress than those with lower levels of exposure, and that this physiological stress is impacted by the microbiota of snails living in each environment. We measured relative levels of HSP70 expression in snail gut tissues to determine usefulness as a biomarker in our study. We also used inductively coupled plasma mass spectroscopy to determine the amount of arsenic in the tissues of CMS harvested from each lake. Next, we are isolating DNA from snail guts, water, sediment, and plants from each lake. The purified DNA will be subjected to 16S rRNA amplicon sequencing, allowing us to determine the relative abundances of bacterial taxa in each environmental compartment and the overlap between the snail gut vs local environment. Our future research will focus on validating additional stress induced biomarkers, while assessing microbiome alteration linked to the biomarker(s). This work will lay the foundation to future studies focused on understanding the links between arsenic exposure, chronic physiological stress, and microbiome composition.

HIV infection impairs B cell function, in turn, altering immunoglobulin production and function. Immunoglobulins (Igs) exist as isotypes including IgA, IgG, and IgM. Within the IgA and IgG isotypes there are subclasses IgA1-2 and IgG1-4 respectively; all with distinct functions. Previous studies have shown that HIV infection influences Ig isotype and subclass concentrations in serum, but few have explored their concentrations in the breast milk of mothers living with HIV (MLHIV). Widespread use of antiretroviral treatment during pregnancy has led to an increase in the incidence of HIV-exposed and uninfected infants (iHEU). iHEUs have heightened immune activation and inflammation and display high infectious morbidity compared to compared to HIV-unexposed infants. It is plausible that immune factors transferred in breast milk contribute to altered immunity in iHEU. Therefore, knowing whether HIV infection impacts total immunoglobulin concentrations or inflammatory biomarkers in breast milk is important. I used enzyme-linked immunosorbent assays (ELISA) to measure the concentrations of immunoglobulin isotypes and their subclasses and Luminex to profile cytokines and chemokines in breast milk 4 weeks after delivery. Assays were performed according to manufacturers’ instructions and sample values were extrapolated from a standard curve. I compared these factors between MLHIV and uninfected mothers using Mann-Whitney U test. MLHIV had significantly higher mean concentrations of total IgG1 (36.9 ug/mL versus 26.6 ug/mL, p=0.018) and IgG3 (2.9 ug/mL versus 1.3 ug/mL, p=0.0013). There was no difference in concentrations of IgA and IgM between the groups. Furthermore, MCP-1, MIP-1-β, and SDF-F-α were the most abundant chemokines in breast milk in both groups. However, we found no significant difference in concentrations of cytokines and chemokines in breast milk of MLHIV versus controls. Overall, we observed increased breast milk concentrations of IgG1 and IgG3 in MLHIV. Future work will explore implications of these IgG subclasses on iHEU immunity.

WNT signaling plays an essential role in many developmental processes with WNT molecules functioning as directional and differentiation cues. The recapitulation of WNT signaling pathways during embryonic morphogenesis is a promising approach for the development of novel regenerative therapeutics to treat various conditions. Recent work from our lab has demonstrated wnt16, a wnt family member, to regulate zebrafish embryonic myogenesis. We showed that loss of function in wnt16 induced changes in zebrafish muscle morphology. Moreover, myogenic precursors coexpressed wnt16 and pax7, a gene that promotes muscle differentiation and is a marker of satellite cells that support skeletal muscle regeneration. These findings indicate that wnt16 is necessary for muscle morphogenesis, however, its specific function in muscle regeneration remains unclear. I hypothesize that wnt16 influences skeletal muscle regeneration by regulating pax7 in satellite cells. To test this, I am determining the time course of wnt16 expression in pax7+ satellite cells in injured zebrafish muscle. Additionally, I will determine whether wnt16 is necessary for activation of pax7 following muscle injury. Through this study, I expect to establish 1) that wnt16 is upregulated after a muscle injury as an injury response gene, and 2) that wnt16 is necessary for pax7 activation in satellite cells. If the outcomes are as expected, this will show that wnt16 influences skeletal muscle regeneration, mirroring its role in zebrafish myogenesis and that WNT16 may be a target for developing therapeutics to treat muscle injuries.

Weight loss (WL) is recommended for people with obesity to mitigate cardiometabolic risk, but its effect becomes limited when reaching a WL-plateau (WL-PL), when the rate of WL becomes minimal despite efforts to continue losing weight. The biological basis for the WL-PL is not fully understood. The goal of this study is 1) to test two diet-regimens in the development of a WL-PL in mice with diet-induced obesity (DIO), and 2) to identify subsequent changes in mitochondrial function. We hypothesized that despite similarities in caloric intake, higher fat content will make high-fat diet (HFD-CR20) mice protect their adiposity and reach a WL-PL sooner than low fat diet (LFD-CR20) mice. We also hypothesized that mitochondrial function will be reduced in mice that have reached a WL-PL. To test hypothesis 1, individually housed DIO mice were divided into two groups, and were provided with 80% of their ad libitum caloric intake with either a high-fat, or low-fat diet daily for ~2.5 weeks. Body weights were recorded daily. A WL-PL was identified by weight stability (<0.5% change BW/day) following weight loss. HFD-CR20 mice reached a WL-PL phase after 10 days of caloric restriction. LFD-CR20 mice did not achieve a plateau within the study time frame. LFD-CR20 mice lost more weight than HFD-CR20 (-10.8% ± 2.2 vs. -5.2% ± 1.8, p<0.05 respectively), which was attributed to a greater loss in adiposity, measured by an EchoMRI, (-23.3 g ± 6.0 vs. -3.3 g ± 3.0, p<0.05). To test hypothesis 2, mitochondrial function was assessed by high resolution respirometry at the study endpoint. We will further analyze this data to identify differences in mitochondrial function attributed to the WL-PL. This work will improve our understanding on the biological mechanisms behind resistance to weight loss to help advance obesity treatments in humans.

Group B Streptococci (GBS) are gram-positive bacteria that asymptomatically colonizes the vaginal tract of approximately 18% of women worldwide. However, during pregnancy GBS in the lower genital tract can ascend into the uterus and infect the placenta and baby resulting in preterm birth, stillbirth, and neonatal infection. We have used a nonhuman primate (NHP; pigtail macaque, Macaca nemestrina) model to determine differences between GBS strains that confer different levels of invasiveness. The objective of the study was to determine if there were differences in gene expression among animals infected with a “progressive” versus a “localized/resolved” infection. We hypothesized that a greater inflammatory response would be associated with a “progressive” GBS infection compared to the “localized/resolved”. Twenty one NHP received either a choriodecidual inoculation of: 1) 1-3 X 10^8 colony forming units (CFU) of hypervirulent GBSΔcovR (n=15) or, 2) saline (n=6). Cesarean section was performed at preterm labor or 1-3 days after GBS infection or 7 days after saline inoculation. Placental chorioamniotic membranes were sampled near the inoculation site. GBS infections were categorized as “progressive infections”, “localized/resolved infections”, or “resolved” infections at the time of preterm labor or 3 days after GBS inoculation. Next, we prepared mRNA libraries from placental chorioamniotic membranes near the GBS inoculation site, which were sequenced using the NextSeq 550 platform. Data were normalized and then analyzed by Single Gene Analysis, Gene Set Analysis, and Ingenuity Pathway Analysis. The analysis is currently ongoing and will be ready to summarize during the “Revision Window”. Prevention of GBS infection in pregnancy is complex and is likely influenced by multiple factors, including pathogenicity, host factors, and the vaginal microbiome. Understanding mechanisms influencing the invasiveness of GBS infections during pregnancy will facilitate the development of novel therapeutics and vaccines.

Cells communicate with each other and their environment via signaling pathways. When a cell receives a signal, it is processed by several proteins. Oftentimes, the same proteins are used by multiple pathways that process distinct signals and produce distinct cellular outputs. I am investigating how the cell is able to correctly process signals using Wnt signaling as a model pathway. Wnt signaling helps regulate cell growth and differentiation and is therefore tightly associated with many diseases. Both Wnt and insulin signaling processing utilize the enzyme glycogen synthase kinase 3β (GSK3β). Activation of insulin signaling results in the phosphorylation of GKS3β. However, if phosphorylated GSK3β from insulin signaling interacts with Wnt proteins, Wnt signaling can be inappropriately activated in the absence of a Wnt signal. The mechanism by which cells prevent improper activation of Wnt signaling is unknown. I am researching the role scaffold proteins play in signaling pathway insulation. Traditionally, scaffold proteins facilitate reactions by binding enzymes and their substrates, bringing them in close proximity to each other. It has also been shown that scaffold proteins can assist in promoting chemical reactions through mechanisms other than binding. Because the scaffold protein Axin binds GSK3β as well as PP2A, an enzyme that dephosphorylates GSK3β, I propose that Axin promotes insulation of the Wnt pathway. Using in vivo human cell culture assays, I have determined that Axin promotes dephosphorylation of GSK3β by PP2A through a mechanism more complex than bringing the two proteins in close proximity with each other. I will use in vitro kinetic assays to determine the underlying kinetic mechanism of this effect. Determining the kinetics of scaffold-mediated insulation will produce a model that can be applied to other signaling pathways and is important in understanding how to specifically target Wnt signaling for disease treatment without affecting other pathways.
 

Osteoporosis is characterized by decreased bone mineral density (BMD) and increased bone fragility, putting patients at higher risk for fractures. Osteoporosis has a strong genetic component, as indicated by data suggesting that BMD is 50-85% heritable. The aim of genome-wide association studies (GWAS) is to identify genetic variants common in the population that influence disease-related traits. A prior GWAS identified 56 loci harboring variants associated with BMD, including the XKR9 locus. The XKR9 locus comprises several genes, and the causal gene at the locus is currently unknown. This project focuses on TRAM1, a gene in proximity to XKR9, and TRAM2, the homolog of TRAM1. TRAM1 plays an important role in stabilizing proteins during translocation into the endoplasmic reticulum. Though the function of TRAM2 is not well characterized, it is suggested to play a role in collagen translocation. Currently, no in vivo studies have been published investigating the TRAM genes. The goal of this project is to determine how TRAM genes impact bone morphology in zebrafish. We have isolated zebrafish with germline mutations for tram1, tram2, and a combination of the two. Micro-CT scans were generated at 90 days post fertilization, and ImageJ and FishCuT were used to quantify the impacts on vertebral bone morphology. tram1 mutants exhibited significant changes in tissue mineral density (TMD) while tram2 mutants showed no significant changes in bone morphology or mineralization. Additionally, fish with homozygous mutations in tram1 and heterozygous for tram2 showed no significant changes, however double mutants for both tram1 and tram2 were embryonically lethal. These findings identify overlapping and distinct roles for tram genes in vivo. They also provide evidence that variants at XKR9 could act through TRAM1 to influence BMD thereby introducing translocation as an important factor underlying genetic influence on osteoporosis risk.

Obesity is a condition characterized by excessive fat accumulation, resulting in increased risk for chronic diseases like cardiovascular disease and diabetes. Weight loss can effectively reduce the burden of cardiometabolic risk factors, but weight loss maintenance is difficult to achieve. Mitochondria are key organelles within cells that are responsible for the breakdown of substrates to produce energy. Mitochondrial dysfunction is implicated in obesity, but little is known about the role of mitochondrial dysfunction in weight loss maintenance. Additionally, females are often underrepresented in obesity research, partly attributed to female mice being more resistant to develop obesity compared to males. The aim of this study is to compare mitochondrial function in liver, adipose tissue, and skeletal muscle, following weight loss in female mice with diet-induced obesity (DIO). We hypothesized that obesity would result in a reduction of mitochondrial function across tissues, and weight loss to further reduce it. We provided CB6F1 female mice with a high fat diet, where 87% of them developed DIO. DIO mice were separated into two groups: one underwent 20% caloric restriction for 4 weeks (HFD-CR), and the other group remained on ad libitum high fat diet for the same intervention (HFD-AL). A healthy weight control group was maintained on a regular chow diet. Their weight and food intake were recorded daily. Body composition was assessed twice, before and after the 4-week intervention period. We had an unexpected finding, where mice lost 5-10% of their body weight prior to the intervention period. HFD-AL mice regained lost weight at study endpoint, while the weight of HFD-CR mice remained weight reduced until study endpoint. CR mice had lower adipose tissue mass compared to HFD- AL mice. Future analyses will include comparisons of mitochondrial content and function in different tissues. Findings will provide more insight into the effects of weight maintenance and regain on mitochondrial function.

It is important for us humans to take responsibility for how our actions have exacerbated climate change and the disproportionate effects that climate change has had and continues to have on various minority groups. Through educating students about climate change in a humanizing manner, we can hope that students will view science as a discipline willing to confront inequities to seek change. However, the textbooks commonly used in introductory biology classes fail to accurately communicate the full scope of the inequities behind who is intensifying climate change and who is the most impacted. My research serves to determine if the humanization of climate change is communicated to undergraduate students taking introductory biology through aiming to answer two important questions: To what extent are textbooks acknowledging humans’ responsibilities in the severity of climate change today and to what degree is equity/inequity discussed? In order to investigate these questions, my team and I evaluated six popular introductory biology textbooks in the United States by pulling passages that discussed the connection between climate change and society. Coded passages were evaluated on where their level of humanization of science fell on the following scale: none/scarce, detail, nuance, equity/inequity, and finally justice. Out of the 1351 total “humanizing” passages pulled from the text, only 7.8% of the quotes were categorized as relating to climate change. Of these quotes, 19% were coded as none/scarce, 60% had detail, 6.7% contained nuance, 11% discussed equity/inequity, and 4.8% included justice (sum total > 100% due to two quotes falling under multiple categories of humanization). As climate change will continue to negatively impact humans, it is important to teach students the specific inequities connected to climate change in order to spread awareness and help solve issues of justice in the living world.

Many age-related diseases in humans such as Parkinson's and Alzheimer's involve intracellular protein aggregation, but much is still unknown about the molecular mechanisms behind how this occurs. Characterizing these mechanisms is therefore important for developing effective treatments for age-related illnesses. Our work investigates the relationship between cell life span and aggregation of processing bodies (P-bodies), which are cytoplasmic ribonucleoprotein (RNP) granules that form inside cells experiencing stress and perform several molecular functions that appear to benefit cells experiencing stress. Using GFP-tagged Dcp2 as a P-body marker in S. cerevisiae and microfluidics to study single-cell lifespans, I demonstrated that P-bodies aggregated in aging cells that were not experiencing other forms of stress. P-body aggregation also correlated to the remaining lifespan of any given cell. To investigate this link further, I adjusted cytosol pH and observed a relationship between cytosolic pH and P-body aggregation rate. Slowing of P-body aggregation correlated to extension of cell lifespan. This suggests the need for additional research to determine whether there is a causal link between P-body aggregation and fatal single-cell pathogenesis and if so, whether these pathogenesis mechanisms are conserved in human cells and therefore a possible target for treatment for age-related illnesses.

Type 1 Diabetes (T1D) is one of the most prevalent chronic diseases among teens in the United States. Teens with T1D facing socioeconomic disadvantage are disproportionately negatively affected by the burden of T1D and are at-risk for poor mental and physical health outcomes. Limited access to diabetes-related technology may be one factor contributing to these disparities. The purpose is to describe diabetes technology (continuous glucose monitors and insulin pumps) use among teens with T1D according to neighborhood-level socioeconomic disadvantage in Washington. The research also aims to investigate links between neighborhood disadvantage and diabetes outcomes and test whether diabetes technology moderates this relationship. We abstracted demographic, clinical, and psychosocial data from medical records of teens aged 13-18 seen for T1D clinical care at Seattle Children’s Hospital in 2019. We determined state-relative decile scores (1-10) for neighborhood disadvantage using the area deprivation index (ADI) tool, which considers income, education, employment, and housing quality factors. Diabetes management was measured using A1c, a 3-month average of blood sugar levels. Diabetes distress was measured using Problem Areas in Diabetes-Teen, a self-report measure of the emotional burden of living with diabetes. I will perform a descriptive analysis calculating the percentage of participants using diabetes technology for each ADI score and for low and high disadvantaged groups using cutoffs from previous literature to reveal technology use patterns. I will conduct linear regressions exploring relationships between neighborhood disadvantage and outcomes (A1c and diabetes distress) and enter diabetes technology as a moderator. We predict that higher neighborhood disadvantage will be associated with poorer diabetes management and higher distress, but this will vary as a function of technology use. Altogether, this research highlights use of a neighborhood-level tool to identify patterns for an at-risk group of teens and may help to identify intervention targets for public policy addressing health disparities.

Science and biology are intextricably linked to policymaking and thus interconnected to justice and injustice in our society. Yet, STEM education fails to emphasize this perspective. Our purpose in this research was to find ways undergraduate biology students can apply their scientific knowledge in the pursuit of justice, such that they can go beyond reading the text, thinking critically and answering questions applying science to the policymaking process. Accordingly, we asked, to what level of humanization do undergraduate biology textbooks frame scientific influence on policy as a tool for achieving justice? To investigate this, we, along with a larger team, analyzed six popular introductory biology textbooks searching for excerpts that contextualized science in society through ideas such as government policy or the judicial system. If an excerpt was found to contain these topics, it was coded based on topic and degree of humanization (in increasing order of humanization: none/scarce, detail, nuance, equity/inequity, or justice). For this project, we defined humanization as discussing or positioning science within the context of society or justice and/or injustice. We found that textbooks' contextualization of science within society is underdeveloped and does not foster critical thinking about the applications of science in policy and justice. Additionally, where this is addressed, there is limited depth in the text and breadth of examples. While our data suggests that these textbooks rarely contain humanizing concepts related to policy, our intent is not to suggest edits to the textbooks. Rather, we have identified trends in humanizing biology content that instructors can add to their curricula to contextualize the role of science in policymaking and justice in their classrooms. Additionally, these changes can encourage students to acknowledge the applications of their biology knowledge to policy in the pursuit of justice in society outside the classroom. 

The placenta is a crucial fetal organ providing oxygen and nutrients to the developing infant. Researchers typically use placental cell models to study the placenta, which are derived from immortalized cells. The use of in-vitro placental cell models is important because human samples are difficult to obtain, and placental biology is highly species-specific. Despite this, our understanding of the characteristics of these cell lines and how they compare to placental tissue samples is limited. This project aims to determine which placental cell model most directly reflects the gene expression of the human placenta. RNA sequencing data from the placental cell models HTR-8/SVneo, JEG-3, BeWo as well as data from primary trophoblast cells was obtained using the Gene Expression Omnibus (GEO) database or through lab-generated datasets. Data for each cell line was combined into a single dataset of shared genes (n=6835) and individual datasets of genes unique to each cell model. For genes that were unique to each cell model, I performed KEGG pathway analysis and characterized placenta specific genes using the Human Protein Atlas (HPA). BeWo cells expressed the highest number of unique genes (n=355) and shared the highest number of genes with the primary trophoblast cells (n= 1,167). Pathway analysis showed that genes unique to primary trophoblast cells (n=2661) were overrepresented in 24 pathways, unique BeWo genes were overrepresented in 15 pathways, while unique HTR-8/SVneo genes (n=355) were overrepresented for a single pathway- the neuroactive ligand-receptor interaction. Placenta specific genes were expressed within the uniquely expressed genes for JEG-3 (n=1), BeWo (n=1), and primary trophoblast cells (n=17), but not HTR-8/SVneo. Ultimately, the results from this project will provide a tool to evaluate differences in placental cell models and aid the placental biology research community in understanding which cell line is most representative of human placental tissue samples.

The period around birth is when neonates are at the highest risk of neurological injury or death. A common neonatal neurological injury is hypoxic-ischemic encephalopathy (HIE), which occurs after the brain does not receive enough oxygen or blood flow. There is a large disparity in the severity and long-term neurodevelopmental outcomes of HIE between high-income countries (HICs) and low-and-middle income countries (LMICs). In HICs, HIE occurs in 1-4 neonates per 1,000 births. In LMICs, the instance of HIE is at least 2-3 times higher. Furthermore, cases of HIE seen in LMICs suggest a different type of injury - a more prolonged intermittent injury resulting in white matter injury - compared to HIE in high-income countries that is more acute and affects the deep grey matter. Therapeutic hypothermia (TH) has been the standard of care for HIE in HICs; however, TH is not an effective treatment for HIE in LMICs. Thus, the creation of alternative and accessible therapies for HIE in LMICs is crucial. This study will seek to model HIE as seen in LMICs through an in vitro ferret model that may be used to pilot therapies before applying them to in vivo models. Organotypic brain slices from postnatal day (P) 21 ferrets, equivalent to a term neonate, will be cultured and randomized to receive increasing intervals of oxygen glucose deprivation (OGD), with and without serum deprivation. Serum deprivation is defined as culturing in 2.5% serum as opposed to the standard 5% to mimic certain aspects of malnutrition that may be more common in LMICs. Cell death and white matter injury will be assessed 24 hours after OGD. We hypothesize that slices with more rounds of intermittent OGD and serum deprivation will display relatively more cell death and white matter injury, thus serving as a model of HIE in LMICs.

Obesity is associated with mitochondrial dysfunction. A study previously conducted in our laboratory produced preliminary data suggesting a reduction in T-cell mitochondrial function in subjects with obesity relative to healthy weight controls. The purpose of this present study is to determine whether changes in T-cell mitochondrial function (MITO) reflect MITO changes occurring in liver and skeletal muscle, which are known for having greater influence in glucose homeostasis and energy expenditure. We hypothesize that mice with diet-induced obesity (DIO) will exhibit reduced MITO in T-cells that will correlate to a decline in MITO in liver and skeletal muscle. Adult male C57Bl/6J mice were divided into two groups–the control group was fed a standard chow diet whereas the experimental group was fed a high-fat diet for fifteen weeks. Body weight and food intake were measured every week. Body composition was performed at the endpoint. MITO was measured via high-resolution respirometry in permeabilized liver tissue, skeletal muscle fibers, and splenic T-cells. DIO mice had higher body mass than standard CHOW [52.8g±1.8 vs. 35.1g±2.6] that was explained by an increase in fat mass [19.9g±0.9 vs. 6.1g±1.8] and lean mass [31.5g±1.7 vs. 26.1g±1.1]. We found that differences between DIO and CHOW in mitochondrial leak respiration, maximal oxidative capacity, maximal electron transport chain, and ADP sensitivity were not the same across all tissues. We will proceed to determine which aspects of MITO are correlated between different tissues and assess if variations in respiration are associated with differences in mitochondrial content. An improved understanding of how DIO affects different types of cells regarding oxidative capacity might provide key insights into the development of therapeutics and other preventative approaches to improve immunity and cardiovascular fitness in obesity.

CD123 is a cell surface protein expressed on neoplastic cells and underlying cancer stem cells in a variety of hematological malignancies, specifically acute myeloid leukemia (AML), B-cell acute lymphoblastic leukemia, hairy cell leukemia, Hodgkin lymphoma, and blastic plasmacytoid dendritic neoplasm, making it a rational drug target for antigen-specific immunotherapeutic approaches. In some cases, however, cell surface CD123 antigen level may not be high enough to elicit a response with an immunotherapeutic, and so we set out to identify mechanisms of regulation of CD123 expression through genome-wide CRISPR screens, and through testing of CD123 expression level changes following treatment of human AML cell lines with clinically validated AML chemotherapeutic drugs. Using commercial anti-CD123 antibodies, I established baseline CD123 expression level on a variety of AML cell lines. I then treated selected cell lines for various times with chemotherapeutic agents, including azacytidine, histone deacetylase (HDAC) inhibitors, the BCL2 inhibitor venetoclax, all-trans retinoic acid (ATRA), doxorubicin, or cytarabine, and measured for altered CD123 level. Utilizing a FACS-based sorting approach on cells that were lentivirally transduced with a genome-wide CRISPR sgRNA Brunello library covering over 19,000 genes, we identified genes that were associated with either increased or decreased expression of CD123. A subset of these CRISPR screen hits were subsequently validated in a small number of AML cell lines using CRISPR/Cas9 sgRNA against specific targets implicated in CD123 expression changes.

One of the most cutting-edge instruments to probe the origins of our universe is the Murchison Widefield Array (MWA), a low-frequency telescope array located in Western Australia. Arrays like the MWA are best equipped to detect light from the Epoch of Reionization (EoR), which started about 400 million years after the big bang. Throughout this epoch many of the universe’s first stars and galaxies began to form, reionizing the surrounding neutral hydrogen gas. Understanding this period of cosmic history is essential because it reveals the properties of the first stars and galaxies and also impacts modern-day astronomy, for example by providing constraints on dark matter and information about present-day star formation. New ultra-wide angle images are being processed, hopefully giving us snapshots of the early universe. For this project, I searched and corrected for near-horizon contamination from astrophysical and anthropogenic radio emissions not caught by our flagging algorithm SSINS. I read processed Healpix data cubes into a jupyter notebook and Fourier transformed the data in two directions (the XX and YY polarizations) so that I am able to pick out radio frequency interference. After doing this for multiple images, I analyzed whether the consistent appearance of interference is significant enough to reevaluate the flagging software we use. By finding and correcting contamination that wasn’t flagged by SSINS, I was able to support the effort to create the world’s deepest reionization power spectrum measurement, the most powerful tool we have to probe the Epoch of Reionization. I hope to find and correct enough images of radio frequency interference so that we can improve the SSINS pipeline.