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

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

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

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

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

Politicians use inflammatory language to manipulate voters via aspects of identity: race, sexuality, gender, religion. Due to differences in values within each of these groups, word choice significantly impacts ideological viewpoints. This literature review’s purpose is to highlight the study of inflammatory language that manipulates the public’s identity. During the World Warâ…¡Era the Nazis used false information to sway the public toward an identity-based agenda. In a stark comparison, representation of race was essential in the fight for civil rights. Thus, where is the moral line drawn in the use of identity politics? If an individual doesn’t have an egalitarian outlook, words are weaponized against different communities. Later in the Reagan Era, Reagan used religious catchphrases to rally the Moral Majority, in which he used the religion of others to his own advantage. Negative tribalism re-occurs as a socio-political trend reaffirmed by trigger concepts. The findings are that politicians from all over the political spectrum use terms that irrationally anger and rally narrow bases. These dog-whistle-like phrases are used in ways that subvert two group identities in one way or another, like the power dynamic between agents and the oppressed. This project investigates the effects of politicians’ diction in contrast with the reaction of different communities. The use of terminology by powerful people, could be a danger to the survival of the democratic process. Political analysts need to be aware of the intersectional relationship between inflammatory language and identity to better understand hostage holding behaviors of each political party. An inflammation of this vocabulary could spark a similar hatred of the past and leave our democracy left in ashes.

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

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

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

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

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.

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

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

Attention deficit/hyperactivity disorder (ADHD) in girls had been largely under researched up until the 21st century, and still much is unknown or unclear about prevalence, symptomatology, associated impairments, longitudinal trajectories, treatment options, and treatment efficacy. In this study I attempt to characterize the ethnically diverse sample of adolescent girls (n=235) from the ADHD Teen Integrative Data Analysis Longitudinal (TIDAL) dataset (Sibley & Coxe, 2020). I investigate how different types of behavior therapy [engagement-focused (ENGAGE), comprehensive (COMP), standard (STANDARD), community-based usual care (UC), no treatment (NOTX)], medication engagement (consistent, inconsistent, negligible), clinical problem profile (simplex, internalizing, disruptive/disorganized), and family adversity predict changes in ADHD symptoms and related impairment (academic functioning, parent-teen conflict, and organizational functioning) over time. To do so I create a series of hierarchical linear regression models to examine the relationship between the predictive variables and the outcomes, and how each added variable affects the relationship using data from the ADHD TIDAL dataset. I predict an overall decline in symptoms and related impairment with the ADHD+internalizing profile predicting a greater decline than ADHD simplex and disruptive/disorganized ADHD. I also hypothesize that higher family adversity scores will predict a lesser decline in symptoms and related impairment. The results of this study will provide insight different into female presentations of ADHD. This information can then be used to optimize ADHD screening methods to reduce demographic disparities in ADHD and determine which combination of treatments are most effective for different subgroups.

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

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.

Compared to polymerase chain reaction with nasopharyngeal swab specimens, lateral flow assays (LFA) for detecting SARS-CoV-2 antigen in saliva are rapid, inexpensive, simple-to-use, and instrument-free, but have low sensitivity (ca. 11-40%) due to limited LFA sample capacities (ca. 50µL) and preparatory saliva sample dilution. To address this challenge, I developed an osmotic processor, a 3D-printed device, to concentrate target analytes through static and spontaneous osmosis for improving salivary-based COVID-19 LFA. The specimens loaded into the device were separated from an aqueous polymer solution using a dialysis membrane. The polymer solution with high mass polymer concentration resulted in an osmotic pressure difference that caused water transport from the saliva to the polymer solution, while the target analyte – SARS-CoV-2 nucleocapsid (N) protein – remained within the membrane. As the final solution contained the same N protein amount in a lower liquid volume, the overall sample was concentrated, thus improving the antigen detection limit ca. 60-fold, from 62.5 to 1 pg/mL. Combining the osmotic processor and saliva based LFA enables rapid, sensitive, simple, and inexpensive POC testing.

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.

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

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

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

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

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.

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

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

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

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

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

 Attention Deficit/Hyperactivity Disorder (ADHD) is one of the most common psychiatric disorders affecting adolescents. Treatment often focuses on managing symptoms, including distractibility, poor concentration, disorganization, hyperactivity, and impulsivity. A successful transition to adulthood requires interpersonal, organizational, and planning skills, making adolescence a critical time to treat ADHD symptoms. Sibley et al. (2014) reviewed treatment literature on ADHD in adolescents and concluded that medication and behavior therapy both produce similar effects on ADHD symptoms in adolescents. This project aims to update the results of the prior review using the past ten years of research. First, an electronic database search was conducted using four categories of terms: (1) sample age, (2) disorder, (3) treatment, and (4) randomized control trial. Experts were also contacted to request additional articles published during the designated period. Inclusion criteria were then applied: (1) published between 2013-present, (2) ages 10-19, (3) ADHD diagnosis, (4) quantitative data reported for at least one ecologically valid outcome measure (e.g., ADHD symptom severity), (5) in studies where individuals not meeting age or diagnostic criteria are included, data for adolescents with ADHD must be presented separately, (6) must evaluate treatment efficacy. 20% of the studies were also randomly selected for an inter-rater reliability probe. Next, data were collected based on the type of study, methodology, and participant demographics for every included study. Effect sizes were also calculated for several outcome measures. This review is still in its preliminary stages but will provide an updated review of the most effective pharmacological and non-pharmacological treatments for ADHD in adolescents. It will demonstrate the considerable growth in the number and highlight the effectiveness of available treatments. The next step will include quantifying data to determine trends for each treatment and conclude the review by summarizing our findings.

The ZaP-HD Experiment combines the research fields of electric space propulsion and nuclear fusion by stabilizing the confinement of high energy density plasmas by accelerating ions to high axial velocities. This is known as the Sheared Flow Stabilized (SFS) Z-pinch, and has potential applications in both clean energy production and interstellar space propulsion. ZaP-HD employs numerous diagnostics to record plasma behavior with the goal of understanding how to improve the SFS Z-pinch. My research on ZaP-HD aims to create spatiotemporally resolved "contour maps" of the radial electron density distributions at fixed axial locations in the plasma flow. To collect data for these maps, I use a method known as Helium-Neon (HeNe) Interferometry, which records the interference experienced by a HeNe laser beam shining through a plasma to create a time-resolved curve of the chord integrated electron density of the plasma along the path of the beam. For each "pulse" of experimental plasma, I record four of these curves using four parallel laser beams which pass through the plasma perpendicular to, and at different distances from, the center axis of the Z-pinch. By recording electron density measurements under different experimental parameters, I can gain insight on how to increase the plasma density in future experiments. Increasing plasma density directly contributes to increasing the fusion reaction rate, and thus the energy output of a fusion plasma. I have recorded chord-integrated electron number densities on the order of 10^21 electrons/m^2, and I have observed a trend of the electron density increasing radially inward towards a peak at the center axis. My research aims to contribute to the global push for the advancement of clean and renewable energy production, as well as the development of spacecraft propulsion systems which could enable humanity to finally achieve interstellar space exploration.

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

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

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

Phytophthora is a genus of oomycete that causes plant damage expressing a variety of disease symptoms. Phytophthora can live and move in water and soil, and also, they can persist in soil once the host is infectious and will continue to damage the plant tissue. Common symptoms of this infection include blight lesions, dieback, and cankers. Until now, there has been research to identify and classify different species of Phytophthora around Washington State. There is no specific documentation regarding the factors which influence the expansion of the diversity of Phytophthora species. Although limited, previously collected data does suggest human activity near the water source increases Phytophthora diversity in that water. Rhododendron leaves used as bait were placed in Chambers Creek, an area of high human activity. With the Phytophthora isolated from the necrotic lesions on bait leaves, we will use PCR and DNA analysis to identify the species present. We expect to find three or mores species of Phytophthora species in Chambers Creek. This research will contribute to data sets regarding Phytophthora diversity in Washington State further protecting our native ecosystems and highlighting the importance of environmental education to those who use these ecosystems.

Mitochondria are the main oxygen consumers in eukaryotic cells and as such are the primary organelles affected by oxygen deprivation, hypoxia. Hypoxia alters the size and shape of mitochondria (so called mitochondrial dynamics) but the responsible mechanisms and their role in hypoxic cell death is unknown. The Crowder lab has recently discovered that a mutation in the Mechanistic Target of Rapamycin Complex One (mTORC1) protein Raptor confers hypoxia resistance. mTORC1 is a master regulator of metabolism and is known to affect certain aspects of mitochondrial biology. In this work I show that disrupting mitochondrial dynamics with mutants in mitochondrial fission produce hypoxia resistance but that mutants with altered fusion have normal hypoxic sensitivity. I have built compound mutants containing both fission and fusion machinery mutants together with the hypoxia resistant Raptor mutant. Using these mutants, I am testing how Raptor controls fission and fusion and whether either is required for its hypoxia resistance. Our preliminary findings indicate that the hypoxia resistance of the Raptor mutant does not require FZO-1-mediated mitochondrial fusion. By exploring the interaction of mitochondrial fusion and fission with Raptor, we are beginning to understand how these important organelle and metabolic regulators combine to control hypoxic cell death.

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

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.

Kelp is a vital component of our ecosystems, as the base of the marine food web, a habitat for many fished and unfished species, and holds a strong cultural importance to society. Kelps thrive in cold, nutrient-rich waters and are therefore impacted by changing abiotic conditions including warming temperatures and low nutrient availability. Water temperatures and nutrient availability vary across the Salish Sea, therefore different bull kelp (Nereocystis luetkeana) forests experience different conditions. There has been a significant decline in bull kelp forests, associated with warming waters in the Puget Sound, Barkley Sound, and Northern California, as a result of climate change and marine heatwaves. Nutrient levels are strongly associated with temperature, there are higher levels of nutrients in cold oceanic water and lower nutrient levels in warmer waters. To understand differences between populations across a temperature and nutrient availability gradient, we examined the carbon-to-nitrogen ratios and stable isotopes in kelp blade tissue from eight sites in the Salish Sea to determine how nutrient levels in the blade differ. We hypothesize there will be higher nutrient levels in the kelp tissues taken from areas with more oceanic water and colder temperatures than the tissues from warmer, fresher water. Our findings will contribute to kelp restoration efforts by depicting what constitutes a healthy bull kelp population, the differences in habitats across the Salish Sea, and what future conditions could affect populations.

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

Subduction zones are convergent tectonic boundaries on Earth where one slab sinks underneath another. Characterizing the timing of metamorphic events, deformation, and fluid-rock interactions is fundamental for better understanding hazards and the evolution of subduction zones over geologic time. Titanite, a titanium-calcium silicate mineral, can record fluid-rock interactions and deformation, and can provide information on the chemistry, timing, and type of deformation in rocks. The goal of this project is to characterize how titanite records fluids and deformation during subduction and exhumation. Samples were collected from an exhumed subduction complex on Andros Island in Greece which was part of the Hellenic subduction zone. The blueschist and greenschist rocks that form the island, have experienced at least two metamorphic events in the Cenozoic and can be studied to understand subduction zone processes. A glaucophane-bearing garnet mica schist contains titanite crystals within various structural domains allowing for correlation to specific deformation/metamorphic events. Garnet porphyroclasts contain pre-kinematic inclusion trails with minor titanite likely formed during prograde metamorphism. The main foliation fabric defined by predominantly white mica and quartz contains titanite grains elongated to their long axis or titanite grains acting as rigid bodies with pressure shadows around them. To identify how titanite deforms I use a scanning electron microscope with an electron backscattered diffraction detector. Preliminary data show grains within the main foliation with little to no misorientation. This may indicate the lack of deformation or fluid-driven recrystallization/precipitation. Future geochronological work will allow me to set time constraints on the titanite grains within the different fabrics. Obtaining additional data from samples from different facies\locations will aid in understanding the timing and deformation of rocks in the area. Understanding how titanite records fluids and deformation allows to better constrain the timing of deformation and fluid-rock interactions on the subduction interface.

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

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

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

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

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

The mechanistic target of rapamycin, mTOR, is a master regulator of metabolism and aging and as such is critical to cancer and cardiovascular diseases. mTOR functions within a complex called mTORC1, composed of multiple proteins including Raptor. The Caenorhabditis elegans, abbreviated C. elegans, version of Raptor, is encoded by the daf-15 gene. Recently, the Crowder lab identified a missense mutation in daf-15 that resulted in a heat-sensitive reduction of function of Raptor, hereafter referred to as daf-15(rf). At 20°C, daf-15(rf) shows a wild-type level of hypoxia death consistent with normal daf-15 function. However, at 22°C, daf-15 function is reduced and resistance to hypoxic death is observed. The mechanism behind this is not fully understood. This study investigates how daf-15 controls hypoxia sensitivity. One function of daf-15 is to negatively regulate HLH-30, a transcription factor that controls, among other things, proteins involved in a cellular recycling process known as autophagy. Autophagy involves the breakdown of damaged proteins and organelles and is known to be important in times of cellular stress. My mentors and I hypothesize that reduced function of daf-15 at 22°C allows increased nuclear localization of HLH-30, disinhibiting autophagy. The work I am currently doing involves using fluorescence microscopy to visualize and qualitatively assess HLH-30 nuclear localization at different temperatures in two strains of C. elegans that have HLH-30 tagged with green fluorescent proteins (GFP). In one strain, HLH-30::GFP is in the wildtype background and in the other is in the daf-15(rf) background. We expect to see no nuclear localization of HLH-30 in either strain at 20°C but an increase in nuclear localization in daf-15(rf) at 22°C. This study provides a better understanding of daf-15's role in hypoxia resistance in C. elegans and has implications for the versions of DAF-15 and HLH-30 found in mammals.

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.

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

Ovarian cancer is the deadliest gynecological malignancy with an estimated 13,270 women in the United States to die from it this year. Because of its nonspecific symptoms, it is often diagnosed at advanced stages, resulting in lower survival rates. The majority of current in vitro models for ovarian cancer use established cancer cell lines that lack clinical and translational relevance due to their inability to capture the high inter- and intra-tumor heterogeneity. To study tumor heterogeneity and cancer initiation, induced pluripotent stem cells (iPSC) have emerged as a new powerful tool that are both amenable to gene editing and differentiation into different cell types. One group has previously reported the generation of fallopian tube organoids from human iPSC. However, the generated organoids lack the characteristic tube-like structure as well as components of the microenvironment that removes the possibility to address structural factors and the functional role of the extracellular matrix. Bioengineered devices can be used for geometric cues and controlled release of biomolecules that can guide spatiotemporal cell and tissue organization. This project focuses on establishing a model by seeding iPSC-derived fallopian tube epithelium into lumenized microfluidic devices for further study on cancer initiation and drug screening. To confirm the generation of relevant cell types, I will benchmark the iPSCs at different time points throughout the differentiation protocol with qPCR and immunostainings. We expect results to show specialization of iPSCs towards the fallopian tube epithelium lineage and their further maturation (cilia beating and mucus secretion) once incorporated in the designed device. Once a model is established, further work can be done on elucidating factors such as substrate curvature, genetic mutations, and infections on tumorigenesis.

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

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

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.

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.

Phytophthora is a genus of oomycete water molds that harms plants. They are a group of fungi-like microbes responsible for several plant diseases, including blight, canker, dieback, and root rot. Even though approximately 30 species have been identified in Oregon and Alaska, the number of species currently present in Washington is yet to be determined. Our research focuses on the diversity of Phytophthora species. First, in an analysis of previously collected data and US Census data, the Phytophthora species diversity is higher in counties with a higher human population. Based on this analysis, we expected to find more than three species of Phytophthora present in Chambers Creek (our sample site) due to the high human population in Pierce County. Secondly, we sampled Chambers Creek for nine days using Rhododendron leaves, incubated the leaves for two days, then performed a PCR. The PCR product was sequenced using Sanger sequencing and a BLAST was used to identify the species present in our sample. Ultimately, we identified four species of the harmful plant pathogen Phytophthora present in Chambers Creek. From this, we conclude that there is a high diversity of Phytophthora present in this Pierce County water source. Phytophthora can be extremely harmful to trees and crops, and it has caused mass famines in the past. This research is vital because understanding patterns of its diversity allows us to monitor its presence locally; should a particularly harmful species be found, we can work to mitigate its effect on our ecosystems.

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

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.

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

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

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.

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

Alzheimer’s disease (AD) is the most common age associated neurodegenerative disease in humans, with approximately 50 million people living with the condition worldwide. AD is the leading cause of dementia, memory loss, and other symptoms related to cognitive decline. Pathologically, AD is greatly associated with the formation of amyloid-beta plaques (Aβ) forming aggregates within the brain and disrupting critical neurological functions. As current treatments for AD only serve to mitigate symptoms, there is a dire need for new therapeutic drugs that address the causes of AD and more efficiently target Aβ plaque formation. Due to its ease of culturing and short life cycle, Caenorhabditis elegans is well suited for the rapid screening of candidate compounds. In this study, we utilize a C. elegans AD disease model expressing a full-length human Aβ gene for the screening of 26 FDA-approved compounds in a dose-dependent manner. We observe that at least 6 of these compounds result in a robust delay in worm paralysis. To investigate whether these compounds delay paralysis by reducing Aβ protein aggregation, we are staining worms with X-34 – a fluorescent dye that labels amyloid structures – and subsequently comparing staining patterns in worms with and without drug treatment. In addition to recording the timing of worm paralysis, we are studying behavioral changes in drug-treated and control worms to determine the effects our identified drugs on other physiological processes. In our use of a pre-clinical C. elegans model, we can apply our findings to future clinical treatments as most C. elegans genes are also conserved in humans. Therefore, by identifying FDA-approved compounds that reduce the appearance of Aβ plaques within C. elegans, we can fast track drug discovery to better treat AD in humans.

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

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

The land use in and around Mud Bay, South of Bellingham, has changed over time, including logging, mining and quarrying in the late 1800s to early 1900s, as well as railroad and interstate construction in the 1920s and 1960s. Prior work has shown that the bay is filling with sediment at a rate greater than the projected sea level rise. In this project, we want to document the timing of major land-use change and determine whether the shoreline of the enclosed bay has changed over time. In order to precisely document our data, we georeference historic maps, aerial photographs and satellite images with geographic information system (GIS) software to define the shoreline and map land-use and shoreline changes over the decades. We compare the shoreline and land-use changes correlating with previously extracted sediment cores. With this research, we aim to learn about the competing influences of sea level rise and land-use change on the position of the shoreline and sedimentation in Mud Bay. Conducting this research on Mud Bay will also help us learn how to apply these methods and information to other similar landforms around the world.
 

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

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

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

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

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

Myosin modulators are a novel class of pharmaceutical agents designed to treat patients with cardiomyopathies by directly modulating cardiac myosin function in the sarcomere. Compounds including omecamtiv mecarbil (OM), danicamtiv (Dani), and deoxy-ATP (dATP) have previously been shown to increase myofibril ATPase activity while mavacamten (Mava) reduced ATPase activity. In the absence of actin, ATPase activity is a combination of the direct effects of nucleotide binding and the equilibrium between the high activity (DRX) and low activity (SRX) states of myosin. In this study, I investigate how these small molecules affect the single turnover kinetics of pig cardiac heavy meromyosin (pcHMM) in the absence of actin. pcHMM bound to fluorescent mant.ATP or mant.dATP is rapidly mixed with a high concentration of unlabeled ATP. The rate constant for replacement of mant.ADP by ATP defines the turnover of mant.ATP. Preliminary titration experiments demonstrate that OM, Dani,and Mava all inhibit ATP turnover with an IC50 of 0.59 µM, 3.5 µM, and 0.276 µM, respectively. 100% dATP increases the ATP turnover by 100%. These Experiments indicate that each myosin modulator differentially alters cardiac HMM activity. I will discuss how each modulator affects ATP turnover by a direct effect on catalytic activity vs an effect on the amount of HMM in the super-relaxed population. Heart failure is the leading cause of death in America, and can result from diseases such as dilated cardiomyopathy and hypertrophic cardiomyopathy (DCM and HCM, respectively). Current therapies focus on treating the symptoms of the disease and do not directly treat the underlying functional changes. These myosin modulators directly treat the underlying alterations in contractility caused by DCM and HCM, making them a powerful tool in combating heart failure.

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

Chromatin plays a key role in determining gene expression and cellular states. The basic unit of chromatin is a nucleosome composed of ~147bp of DNA wrapped around a histone core with exposed N-terminal tails that help regulate gene expression programs through their post-translational modifications (PTMs). Facultative heterochromatin inheritance, a type of chromatin containing the repressive trimethylation of histone H3 at lysine 27 (H3K27me3) PTM, is necessary for maintaining cell fate, identity, and plasticity. The parental facultative heterochromatin gene repression is maintained during the S-phase by recycling parental nucleosomes containing H3K27me3 onto the daughter strands of DNA and spreading their PTM onto newly synthesized nucleosomes by the polycomb repressive complex 2 (PRC2). Dr. Escobar found that Nucleophosmin 1 (NPM1), a histone chaperone, assists in facultative heterochromatin domain inheritance through interactions with PRC2 in mouse embryonic stem cells. NPM1 is found mutated in roughly 30% of cases of acute myeloid leukemia (AML). Preliminary data finds a significant presence of cleaved NPM1 product at 20 kDa (p20) within the nucleus of normal hematopoietic stem cells (HSCs), but a lack of this NPM1 modification in AML cell lines. Cathepsin B has been shown to cleave normal NPM1 to produce a fragment at p20. I hypothesize that the lack of cleaved NPM1 product factors into leukemogenesis. To test this hypothesis, I have three aims; Aim 1 identifies the Cathepsin B cleavage site of NPM1 using in vitro cleaving assays; Aim 2 assesses the phenotype of HSCs containing a non-cleavable NPM1 mutant; and Aim 3 monitors the phenotype of AML cell lines when inducibly expressing Cathepsin B. This project allows for future investigations into how NPM1 modifications impact facultative heterochromatin inheritance of HSCs and AML cancer cells.

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

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

Hyperspectral imaging confocal microscopy can detect multiple quantum dots with a high spectral resolution in 3D space. This technique improves traditional confocal microscopy by allowing arbitrary digital filtering of pixel-by-pixel spectra. We have developed tools for hyperspectral imaging on a confocal microscope designed for the analysis of light from single quantum emitters at room temperature, such as spin-defects in materials and quantum dots. In the lab we can see that by collecting a large number of spectral images at different wavelengths, the overall signal-to-noise ratio can be improved, allowing for better visualization of weak or subtle signals in the sample. We have designed flexible hyperspectral imaging acquisition and analysis software that allows users to easily modify spectral imaging and digital spectral filtering parameters. It is our hope that this new tool enables tests on the viability of light-emitting and light-scattering materials as elements of quantum processors.

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

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

In the latter half of the 19th century, the world was becoming more globalized both economically and culturally. The Ottoman Empire was no exception to these changes. Joseph Svoboda, a steamship purser for the Lynch Brothers company, was among those who occupied this world in flux. Frequently traveling along the Tigris river for work, Joseph Svoboda wrote upwards of 60 diaries over several decades detailing his daily life in Ottoman Iraq, providing scholars an invaluable historical resource. Within the diaries, Joseph documents his own health troubles and the ailments people around him face. Included are the remedies, herbal, homeopathic, and pharmaceutical in nature, that he and others used. The aim of this research is to investigate the use of medicinal remedies in Iraq during this period using Joseph Svoboda’s diaries as a single reference point. In particular, this project focuses on the use of herbal medicines, drinks, as well as non-herbal remedies, both local and global, that people were using. This project draws upon a wider literature, including 18th and 19th century medical indices, recent ethnographic research, historical analysis, and primary source accounts to understand, in a larger sense, how people in Iraq and the surrounding area treated and prevented illness. Using Joseph’s diaries and external sources, we know that plants like ipecac and compounds like quinine were used to treat various maladies and diseases despite originating in the Americas. This points to the impact of globalization in dispersal of medical knowledge and practice during this period. By investigating medical practices in this milieu, we can come to understand the flow of knowledge of medicine as well as how trade impacted access to material remedies for everyday people. This research is done with a focus on European colonialism and imperialism and its impact on daily use of medicine in Iraq.

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

The Southern Ocean is considered a large part of the global carbon cycle and phytoplankton participate in transferring carbon dioxide (CO2) from the atmosphere to carbon in the deep ocean. Current work examines the number of phytoplankton (using chlorophyll a as a proxy for biomass) and CO2 flux but does not take phytoplankton community composition into account. Previous work has demonstrated that different phytoplankton taxa use different amounts of carbon per other nutrient, so we hypothesize that phytoplankton community composition may impact the amount of carbon transferred from the atmosphere to the deep ocean. We aim to determine the relationship between air-sea CO2 flux, biological production, carbon export and phytoplankton species. While there are many observational datasets of phytoplankton community composition in the Southern Ocean, this data has not been compiled into one database. To address this, I built the Southern Ocean Phytoplankton Database (SOPhy). The database includes ~15 in situ datasets from cruises and features such as full taxonomy and labeled Southern Ocean fronts and sectors, which are used to group the data into regions. The database is built using SQLite and interfaces with Python to transform the in situ observation data and add features such as visualizations, full taxonomy records, and ease of use functions. We will publish the database open access in a Jupyter notebook front-end where researchers can easily interact with data using Python adapter functions that translate input to SQL queries. Next, we will use this database to train a machine learning model to help us study the relationship between phytoplankton community composition, air-sea CO2 fluxes, biological production, and carbon export.

Because of their size-dependent optoelectronic properties, semiconductor nanocrystals play a significant role in the development of materials for a wide range of applications. Magic-sized clusters, a class of nanocrystals, are atomically defined and exhibit a large surface area-to-volume ratio, meaning their surface chemistry will have an even larger influence on their properties. We hypothesize that the surface chemistry of these clusters heavily dictates the structure of the semiconductor core and the resulting optoelectronic properties. While ligand exchange reactions are commonly employed for altering the size, shape, and reactivity of magic-sized clusters, the chemical principles governing this process are not fully understood. Therefore, this project aims to explore how the addition of Lewis bases, or neutral electron-donating ligands, alters an atomically precise CdSe cluster's ligand shell and its resulting physical and electronic structure as a function of initial size and stoichiometries. To investigate this process, two known CdSe clusters were synthesized by injecting the selenium precursor (diphenylphosphine selenide) into the cadmium precursor (cadmium benzoate) at different ratios, producing two clusters of different size, shape, and stoichiometry, characterized by their lowest energy electronic transitions at 350 nm and 418 nm. The clusters were then purified, titrated with varying equivalences of different Lewis bases, and characterized through UV-vis absorbance spectroscopy and ¹H-NMR spectroscopy. While the UV-vis spectra of the titrations exhibit no major changes in the structure and size of the clusters, the ¹H-NMR spectra provide evidence of changing organization of the amine ligands. Future experiments will further distinguish between free and surface-bound ligands on the clusters, as well as the effect of shape and cluster stoichiometry on the ligand exchange reactions. These findings open the door to a deeper understanding of how selective functionalities can be implemented in magic-sized clusters, and more broadly in quantum dots and related nanostructures.

 The southern resident killer whales (Orcinus orca) in the Salish Sea are made up of three pods (J, K, and L). This population is greatly endangered mainly due to persistent anthropogenic stressors including shipping noise, overfishing, and pollution. However, it’s important to understand what other underlying stressors influence the health of this population, including parasitism. This topic is poorly understood and little research has been conducted to determine how parasites are impacting the southern residents, and more fundamentally, what species infect them and how prevalent they are. This study aims to fill that gap in knowledge by assessing parasite infections on both an individual and pod level. I hypothesized that 1) there will be a diversity of parasites infecting killer whales, and 2) the parasitism pressure on the SRKW will be similar across the three pods. Using fecal samples collected from approximately 40% of each pod (J = 60%, K = 37.5%, L = 40.6%), I performed fecal floatation and sedimentation to quantify and identify the parasites present. In addition, I used PCR and eDNA sequencing of fecal samples as a secondary method of parasite identification. I expect to find Anisakis spp., from phylum Nematoda (roundworms), to be the most prevalent across all the samples as they are found to be the most widespread species found in marine mammals. Additionally, I expect the parasitism pressure to be equally represented across the pod level because the pods have similar prey preferences, life histories, and range. This information can be used to further understand the health of each individual we sampled and to inform policy makers and researchers about how widespread the problem of parasitism is in this population. The knowledge obtained from this study can inform future veterinary response to combat this specific threat, further protecting this vulnerable species.

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

People living with HIV (PLWH) can experience multiple symptoms simultaneously that may include but are not limited to nausea, insomnia, pain, fatigue, and changes in appetite, mood, bowel pattern, concentration, and memory. This is known as symptom distress, is multifactorial, and can be attributed in part to the pathogenesis of HIV and side effects of medications used to treat HIV. With a decrease in mortality due to antiretroviral therapy (ART), there is an increase in the prevalence of non-HIV-related physical comorbidities in older adults living with HIV. A common comorbidity is cardiometabolic syndrome, a group of metabolic maladies characterized primarily by insulin resistance, dyslipidemia, hypertension, and abdominal adiposity. The purpose of this secondary analysis is to explore the association between diet and cardiometabolic health of older PLWH, and to bridge the gaps in literature regarding how nutrition specifically impacts symptom distress in PLWH. We hypothesize that dietary intake is associated with cardiometabolic syndrome and symptom distress in older adults living with HIV. The Center for AIDS Research Network of Integrated Clinical Systems (CNICS) enrolled 710 participants who were 18 years of age or older and were receiving ART. The study participants had an HIV Viral Load higher than 200 copies/mL when they were enrolled in the study. Dietary intake data was taken from three 24-hour food recall surveys. We expect to define longitudinal patterns in dietary intake for PLWH, and to identify factors of nutrition that impact symptom distress and cardiometabolic syndrome in older adults living with HIV. Studying various aspects of nutrition in relation to symptom experience and cardiometabolic health in older adults with HIV would yield opportunities to identify mitigation strategies to reduce symptom distress and promote healthy aging within a population that is disproportionately impacted by health disparities.

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

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

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

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

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

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

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

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.

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

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

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

Noxious weeds pose a significant threat to the environmental and economic health of Washington State. Controlling for future introductions requires analysis of the patterns and characteristics of historical noxious weed invasions, particularly directionality, distance, and time to invasion. Herbarium specimen records are an excellent source for these types of data. We scored taxa on the “2021 Noxious Weed List” compiled by the Washington State Noxious Weed Control Board for date of introduction (within Washington (WA) and Western North America (WNA)), introduction category (ornamental or agricultural), region of origin, and life history characteristics (dispersal method, pollination method, etc.). We used herbarium specimen record from the iDigBio and Consortium of Pacific Northwest Herbaria online specimen portals for evaluating directionality, distance and time to invasion. Our results provided few significant predictors of future noxious weed invasion. However, our analyses demonstrated that 1) the majority of noxious weed taxa are ornamental; 2) most taxa invade from south of Washington; and 3) the distance that a taxon travels to WA is not related to the time to invasion. We conclude that human influence remains a prominent, but difficult to quantify factor in the dispersal of noxious weeds. Future research would benefit from several additional considerations, such as how metrics for human population may be used to predict source regions of noxious weed migration, and how the trends reported here might apply to invasive taxa as a whole in Washington.

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

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

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

Computational chemistry can be used to guide experimental studies by giving insight into what could occur in experiments on the quantum level. Although valuable, the information from these simulations is stored in large datasets, which could be difficult to interpret. Thus, visualization of quantum solutions is important. This software development project focuses on the visualization of molecular orbitals for heavy-element systems and time-dependent electron density for systems undergoing an external field with the Chronus Quantum (CQ) computational chemistry program. We visualize molecular orbitals by taking molecular orbital (MO) coefficients from calculations with CQ, and running the data through an algorithm to reformat into a visualization file readable by the commonly used software, GaussView. Visualizations can be done for standard quantum mechanical methods such as DFT; however, we can also visualize complex MOs in the 2- or 4-component formalisms often needed for relativistic calculations, which can account for the spin-orbit coupling important for heavier elements. After transcribing data from CQ to a visualization file, the coefficients and basis functions are processed with the GaussView program, yielding 3D representations of MOs. These visualizations will aid our understanding of quantum phenomena involving heavy elements such as late-row transition metals, lanthanides, or actinides. Additionally, we want to provide a visualization tool for electronic density of time-dependent quantum systems such as those experiencing an electric field. The resulting movies of time-dependent electron density increases the qualitative understanding for researchers in the field, while providing insightful information that is simple to disseminate in the scientific community.

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

Species-level measures of biodiversity inform modern conservation efforts. Therefore, accurate definitions of species are essential for influencing conservation policies. Genetic methods for defining species are now routine because of their speed and accuracy, and the fast rate of evolution in mitochondrial DNA (mtDNA) has made it popular for such studies. While mtDNA provides useful insight into biodiversity, it is only inherited from the maternal genome and thus the evolutionary signal from mtDNA differs from nuclear DNA (nuDNA), which is bi-parentally inherited. By comparing the genetic diversity comprising species (species boundaries) derived from mtDNA to species boundaries from nuDNA we can pave the way for more precise measures of biodiversity and more informed conservation efforts. Our central question is whether species boundaries defined by mtDNA accurately describe species-level diversity. To test this question we needed a system to estimate species boundaries prior to describing new species. The Southeast Asian island of Borneo is ideal because genetic data for lizards on the island indicate many more species than are currently described. We extracted and sequenced DNA from 135 gecko samples representing four species and multiple populations within each to compare the species boundaries estimated using nuDNA and mtDNA. We also tested for a lack of exchange of genetic material between lineages, which would suggest that populations are reproductively isolated, an important property of species. We find that species boundaries suggested using mtDNA differ from species boundaries using nuDNA. Additionally, nuDNA provides evidence for the exchange of genetic material between populations, indicating the lineages are not reproductively isolated, which underscores that mtDNA only shows the pattern of diversity, with no insight into the evolutionary process. Our results indicate that defining species using mtDNA alone does not accurately delimit the genetic populations comprising a species, thus undermining the goal of accurately cataloging biodiversity.

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

The Center for Disease Control estimates that one in three Americans do not regularly get enough sleep per night. This is considering people have access to a bed and a reliable place to sleep, highlighting how arduous it may be for the 500,000 individuals experiencing homelessness in the US to obtain a good night of rest. Seattle is facing a homelessness crisis exasperated by the pandemic and on any given night there may be 11,000 individuals in King County without their own place to stay. This project investigates how sleep differs between individuals living in shelters, tent cities, and tiny homes to determine where the best sleep can be achieved throughout the year. Data was collected using actigraphy watches and sleep diaries for four weeks in September 2022 and four weeks in February 2023. These two time points allow for a seasonal comparison due to the drastic change in light availability and temperature between seasons in Seattle. There were 29 participants across four sites in September and 25 participants across the same sites in February. Interviews were completed to establish a baseline of individuals health and sleep habits. The watch data and interviews were analyzed to compare sleep duration, efficiency, disruptions, and individual consistency, all of which are factors that impact sleep quality which is foundational to mental and physical health. The seasonal comparison is expected to show longer sleep duration in the winter and more efficient sleep for those living in tiny houses or shelters. It is more difficult to control these factors without a home, but it is especially important for people experiencing homelessness who face a disproportionately high incidence of chronic mental and physical health issues. There has been little sleep research in this population and especially for individuals not living in an organized community.

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

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

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

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

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

The rates of obesity around the world are rising greatly, inviting increased risk factors for several chronic illnesses such as heart disease, diabetes, and some cancers. The biological process of aging also contributes to these diseases, and one hallmark of both obesity and aging is dysfunctional mitochondria. Adefovir dipivoxil (ADV) is a reverse-transcriptase inhibitor that I have shown can also induce weight loss in healthy mice and increase lifespan in mice with dysfunctional forms of complex I in the electron transport chain. The goal of my project is to uncover the unknown mechanism of action in this context of use. My initial data indicates ADV is acting as a mitohormetic agent, which increases mitochondrial function by inducing low levels of mitochondrial stress. I have a run quantitative PCR (qPCR) which showed elevated levels of mitochondrial DNA relative to genomic DNA in human fibroblasts only in low-dose ADV treatment (1µM, 2.5µM). I also ran western blots, which showed increased levels of biomarkers indicative of mitochondrial biogenesis (PGC1-α, NRF-2) at the same low-dose ADV treatments. I have run fluorescence microscopy and flow cytometry on fibroblasts treated with low-dose ADV and I observed increased mitochondrial mass and mitochondrial potential. I am currently collecting ADV-treated murine livers and running qPCR to see if the prior results are replicable ex vivo. ADV has been shown to activate CEBP-β, which upregulates β-oxidation. I will also use ADV on cells with inhibited CEBP-β to test whether this pathway is involved in the observed phenotypes from the previously listed experiments. The results of this project will help understand the mechanism of ADV in amplifying mitochondrial biogenesis, only at low doses. Further research could investigate the use of ADV in a variety of other mitochondrial diseased states and could inspire similar experiments in higher order vertebrates.

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. 

Glaucoma is a neurodegenerative disease that causes loss of retinal ganglion cells in the retina, resulting in incurable blindness. While current research efforts have largely focused on regenerating RGCs and other retinal neurons, it has been recently shown that inflammation resulting from immune responses to injury/degeneration can negatively impact retinal regeneration. Microglia are part of the innate immune system and are the only resident immune cell in the retina and brain; they are involved in inflammatory signaling, phagocytosis, and monitoring tissue for foreign pathogens. Previously, our lab has shown that microglia restrict regenerative capacity; microglia ablation improves neuronal replacement strategies in a mouse model. Here, we want to determine if we can develop a new method to ablate microglia from the retina via intraperitoneal (IP) injections, and observe if ablation affects invasion of the peripheral immune system (monocytes) during the inflammatory response post injury. To comprehensively ablate microglia from the retina, we test both dosage and treatment length (days) of IP injections of PLX5622, a drug which inhibits a receptor necessary for microglia survival. After specific treatment courses, mouse retinas are harvested and immunostained for microglia markers to determine the level of ablation. To determine the interaction between microglia presence and monocyte invasion in a glaucoma model, we use a CCR2-RFP mouse line to track monocytes. These mice will be injected intraocularly with NMDA, a toxin that kills RGCs. The number of invading monocytes at each time point post-NMDA-injury can be assessed with and without PLX5622 treatment to see if ablation of microglia impacts the invasion of monocytes. We expect monocyte recruitment to drastically decrease after microglia ablation. This work will allow us to investigate the role of microglia in developmental processes and identify immune targets that would be most amenable to immunomodulation interventions in future therapies for glaucoma.
 

Studies have revealed evidence that some humans have increased midfoot dorsiflexion, or a midtarsal "break", which decreases rigidity of the arch structure during gait. This "break" suggests that more of the sole of the foot is in contact with the substrate in terminal stance, effectively shortening the lever arm during propulsion. This prompts us to wonder: does arch stiffness predict the magnitude of lever arm distance or the forces of peak braking and peak propulsion? The Arch Indices (AI) of 77 people were calculated in dynamic conditions. Locations of the center of pressure (CoP) of the foot at heel strike, peak braking, and peak propulsion were recorded using a pressure-sensitive mat (RSScan International, Olen, Belgium). I calculated the distance from the heel strike CoP to those of peak braking and propulsion. I normalized peak propulsion and peak braking forces by dividing each by weight. All statistics were calculated in STATA (Statacorp, College Station, TX, VBe17). Dynamic AI has a relationship with lever arm distances for heel strike CoP to those of peak braking and propulsion (p=0.042, p=0.005, respectively). Dynamic AI did not demonstrate significance with peak braking and peak propulsion forces (p=0.758, p=0.194, respectively). My results demonstrate an association between AI and the distance of the functional lever arms, suggesting the presence of a midtarsal “break” as flatter feet exhibited shorter lever arms. Midfoot dorsiflexion and loss of rigid arch structure associated with the "break" would result in a decreased lever arm for propulsion, since the anterior midfoot and forefoot are in contact with the substrate at a later point during gait. This analysis has broader implications for foot morphology and midtarsal “break” research. Future work can utilize infrared markers and force plates to create models of the human foot with ground reaction force (GRF) data.

Autism Spectrum Disorder (ASD) is a neurodevelopmental disorder characterized by social communication deficits as well as restricted and repetitive behaviors. Autistic individuals commonly display sensory processing issues, with over 96% of autistic children reporting hyper- and hypo-sensitivities to sensory input of all modalities. Visually, autistic individuals both avoid input and seek stimulation. Visual evoked potentials (VEPs) recorded via EEG are a reliable measure to evaluate the functioning of the visual processing system. Literature suggests a decrease in VEP P100 amplitude in ASD. This study aims to compare adolescents and young adults with and without ASD to evaluate (1) group differences in sensory processing and in VEP P100 and N100 amplitudes, and (2) the relationship between sensory processing and sensory visual behaviors. 91 participants (41 with ASD) ages 12-26 years from the NIH funded ACE GENDAAR study will be included in analysis. High density EEG were collected while each participant viewed 200 trials of flickering checkerboards displayed for 500 ms with a central fixation point. Participants completed the sensory profile self report, a 60 item questionnaire on sensory sensitivities with 10 visual processing questions, and the SP3D sensory processing self report, a 52 item questionnaire with 7 visual processing questions. First, I will analyze VEP P100 and N100 amplitude differences between ASD and typically developing groups, focusing on the midline occipital region. Second, I will analyze the relationship between VEP amplitudes and sensory behaviors, using the aforementioned questionnaires, assessing self reported sensory hyper- and hypo-sensitivity as well as visual specific behaviors. I hypothesize that autistic participants will have decreased P100 and N100 amplitude based on previous literature; in ASD, individuals reporting higher hyper-sensitivities will have increased amplitude and vice versa. This study will contribute to understanding sensory processing issues in ASD and associations between these symptoms and lower order visual processing.

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

As algal blooms continue to demonstrate a great risk to aquatic ecosystems, it’s important to understand the effects aggressive algal growth can have on the organisms that would normally consume them. In a predator-prey ecosystem, stability between grazers and primary producers is determined by the interactions of the species. This study observes this stability using Closed Ecological Systems (CES) containing the algal species Ankistrodesmus, Scendesmus, and Selenastrum, unknown bacteria, and the grazers Daphnia magna. CES are sealed ecosystems that prevent gas exchange with the atmosphere. CES also carry the advantage of repeatability, uncommon in ecological field research. Past research in the Taub lab suggests that if the population of algae increases too rapidly, photosynthesis will cause a pH increase, associated with the death of Daphnia. Understanding which conditions best support D. magna helps us understand how the environment affects a grazer’s ability to compete against rapid algal growth. To determine the optimal initial concentration of algae with their associated nutrients, we set up CES in 6 treatments with ~10% and ~1% algal concentrations, either with or without D. magna, each with 6 replicates. We measure population dynamics by chlorophyll fluorescence, D. magna count and size, ephippia (sexual eggs) presence, and pH indication. CES without D. magna are used to compare how algal growth proceeds without the consumers. The treatments with lower algae concentrations may allow D. magna to persist longer by controlling the algae population and associated pH increase or may experience starvation. The findings of this experiment will give us a deeper knowledge of how algal growth can pose a threat to grazers, and how this information can be applied to other grazer-algae relationships.

Phytophthora is a group of destructive microscopic plant pathogens found in the Kingdom Protista. This water mold poses a substantial threat in the Pacific Northwest, as it infects rhododendron leaves. More Phytophthora are yet to be found here than are currently documented. Understanding the factors that contribute to the diversity of Phytophthora species found in an area is essential in predicting where the spread of this species is most likely. It is hypothesized greater levels of rainfall increase Phytophthora diversity. The sampling location, Chambers Creek in Pierce County, WA, is situated in an area of comparatively moderate rainfall; therefore, about three species are expected to be found. After baiting Chambers Creek with rhododendron leaves, PARP agar was inoculated, then Phytophthora was isolated. DNA was analyzed and bioinformatics was used to identify species present. By understanding the number of Phytophthora species present in local creeks, patterns in WA can be identified to help control this plant pathogen. Our samples identified three species of Phytophthora present in Chambers Creek. This matches our hypothesis that moderate levels of rainfall correspond to moderate species diversity. Based on the specific species found, we suggest to continue monitoring, but no urgent action is needed.

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.

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

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.

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

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

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

mTOR, the mechanistic target of rapamycin, is a serine/threonine kinase which is an enzyme that phosphorylates the hydroxyl group on a serine or threonine side chain. mTOR kinase regulates protein synthesis, cell growth, and metabolism in response to nutrients and energy in most eukaryotes. mTOR consists of two distinct complexes, mTORC1 and mTORC2. These complexes can be further divided into three components: mTORC1 consists of mTOR, Raptor, and mLST8, and mTORC2 consists of mTOR, Rictor, and mLST8. mTORC1 is critical in metazoan development and has been implicated in aging, cancer, diabetes, cardiovascular disease, and hypoxia, a state in which tissues are deprived of oxygen and can not carry out normal metabolic activity. Previously, the Crowder lab conducted a mutant screen in C. elegans, for hypoxia resistant mutations, and has recently identified a missense (changes one amino acid to another) reduction of function mutation in the daf-15 gene, the C.elegan ortholog of Raptor. A unique feature of this mutation is that the function of Raptor can be turned on and off by varying temperature. It has normal hypoxia resistance at 20 degrees, increased resistance between 21-22, and developmentally arrests at 25 degrees. I and the other authors made use of this conditional developmental arrest phenotype to screen for genetic suppressors, mutations that suppressed developmental arrest. Using genetic mapping, sequencing, and complementation testing, we have identified multiple mutations in three different genes responsible for restoring Raptor function. Preliminary results show mutations in the gene rnf-126 (ring finger protein) suppress the Raptor mutation. Current work by myself and others is designed to answer how these genes control Raptor function and hypoxia sensitivity. Elaborating the function of these genes will define novel mechanisms whereby Raptor and mTORC1 controls metabolism, hypoxic injury, and development.

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.

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

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

The metabolic hormone cortisol is associated with biological and social processes, including sleep and stress. Cortisol works on a diurnal rhythm with concentration levels sharply increasing 30-40 minutes after waking (called the cortisol awakening response) and decline gradually throughout the day before increasing around 4:00 in the morning. The diurnal cortisol slope, calculated as the difference between morning and evening cortisol divided by time elapsed, is used as an indicator of daily stress-related health, with steeper negative slopes being deemed more normal. Having a harder time waking up has been associated with impaired cognitive processing and sensory-motor performance throughout the day, thus it is important in understanding how cortisol and stress play a role in sleep outcomes. Some studies have demonstrated a steeper awakening response correlated with easier waking, with other studies failing to replicate. This study aims to investigate if there was instead a correlation between diurnal cortisol slopes and ease of waking in a sample of 20 university students. Students self-collected saliva four times a day (one upon waking, two in the mid-afternoon, and one in evening) over three days, and answered daily surveys that asked hours slept, if they woke up easily that morning (yes/no), and other stress-related questions. Salivary cortisol concentration was measured for each sample with a validated in-house cortisol enzyme immunoassay. Diurnal cortisol slope was calculated across all three sampling days for each student. T-tests were performed between diurnal slopes and ease of waking. All statistical analyses were conducted in R. While preliminary results demonstrated that diurnal slopes were steeper in students reporting greater ease of waking, these differences were not statistically significant. This potentially indicates that diurnal slope correlates with ease of waking, making this study a good framework for future studies.

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

TKIs are a class of targeted chemotherapeutics preventing cancer cell proliferation by inhibiting the Human Epithelial Growth Factor (EGFR) phosphorylation signal cascade. However, the transport of TKI in tissue is poorly understood. In addition, studies of direct drug resistance are hindered by an inability to measure native intracellular drug concentration. Therefore, it is important to understand drug exposure and response at the single-cell level to gain insights into the single-cell drug response and resistance development. The project objective is to quantify the intracellular tyrosine-kinase inhibitors (TKI) drug concentration in human lung cancer tumors using stimulated Raman scattering (SRS) microscopy to better understand cellular drug resistance, drug response, and microenvironmental heterogeneity upon drug exposure. We use the single cell level in vitro model and the mouse dorsal skinfold chamber (DSC) in vivo model. We will use a novel chemical imaging tool, SRS microscopy, to directly quantify single-cell drug concentrations. We first study the cellular-level drug response and resistance in live cells. By comparing the data of MTT Assay and single cellular level image drug concentration, we will be able to study the resistance level of A549 cells.Next, we will move to an in vivo mice model. The dorsal skinfold chamber (DSC) model is well-established for studying tumor development and time-lapse analysis of tumor progression. Quantifying tumor concentration gradient allows for discovering optimal drug dosing conditions that penetrate inner layer tumor cells without harming the host. The SRS microscopy imaging technique enables the quantification of intracellular TKI concentrations within individual cells in the necrotic layer against the proliferation layer of the tumor. By comparing the results from in vitro single-cell image to the in vivo model, we are able to better understand the drug response of A549 to TKI treatments.

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

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

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

Located ~50km northwest of Hokkaido and ~90km southwest of Sakhalin, Rebun Island has served as a conduit to a diversity of cultures moving within and beyond northern Japan. With an uninterrupted occupation sequence spanning three millennia, the north Rebun site of Hamanaka 2 is particularly well-suited to capture the island’s dynamic settlement history. This includes the expansion of the highly mobile Okhotsk culture within the Sea of Japan. Our study investigates the extent of movement and trade on Rebun during the Middle Okhotsk (~6th-7th century CE), widely considered the peak phase of the Okhotsk Cultural Period. To address this question, we seek to identify the number of unique pottery sources at Hamanaka 2; this count may generally be used as a proxy for the number of groups trading with Hamanaka populations during this critical stage. Using laser ablation inductively coupled plasma mass spectrometry (LA-ICP-MS), we quantify elemental concentrations in ceramic samples from the Middle Okhotsk. Unique geochemical source groups are created using principal component analysis (PCA). We then examine thin sections of Middle Okhotsk sherds under a polarizing microscope and categorize them based on their fabric properties (e.g., texture and composition). These fabric groupings are paired with the geochemical groupings to estimate the number of individual pottery sources present at Hamanaka 2. We anticipate that ceramics from the Middle Okhotsk will be exceptionally diverse, both visually and geochemically. This would suggest a high degree of trade, travel, and connectedness – a finding crucial to our understanding of the Okhotsk culture and the sociopolitical history of maritime Northeastern Asia. Finally, our research demonstrates the applicability of material science methods to archaeological research, as well as the unique potential of pairing qualitative and quantitative data to answer archaeological questions.

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.

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

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

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.

Places can change over time with evolving social, economic, and political conditions. However, it can be difficult to understand locations in historical texts using present-day place names. In our project, we use British steamship purser Joseph Svoboda’s personal diaries to learn about the landscape of Ottoman Iraq in the late 19th century. Our research investigates how place names and locations in the diaries compare to that of present-day locations in the same region. First, we generalize a named entity recognition pipeline previously developed to extract person names from the diaries to extract locations instead. We then disambiguate the location names, taking into consideration the different spellings or abbreviations of places, and locate them geographically. This can be accomplished by utilizing services such as GeoNames, which can be used to retrieve location information for large cities such as Baghdad. Other locations, like Jamsheh, cannot be easily found in present-day geographic datasets. We can use the textual context in the diaries to infer the geographic coordinates of these places, using larger cities as references to infer the smaller locations along the Tigris River. Analyzing the coordinates, we see how the associated locations in the diaries have changed in name or location in comparison to present-day locations. We expect to find changes in the spellings of location names, such as “Coot” to present-day “Kut”, and that smaller cities and towns cannot be geolocated because of factors such as historical focus on larger cities, or abandonment. Our work explores how geolocation can be performed on less examined historical regions through this study of the diaries in Ottoman Iraq. It can be applied to other digital humanities projects analyzing primary historical documents, especially personal documents, and expand on existing methods in researching historical landscape change.

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