Corepressors are proteins that do not directly touch DNA but work with other proteins to keep the gene from being transcribed. TPL is a corepressor from the model plant Arabidopsis thaliana. While we understand a lot about how TPL works, there are still many mysteries remaining. The goal of my project is to identify other proteins that work with TPL to form a transcriptional repression complex at a single engineered promoter site. First, we created a synthetic repressor called dCas9-TPL that binds and represses the transcription of the RUBY reporter. The RUBY reporter is a visual marker expressed throughout the entire plant, turning the green plant a bright purple. Our engineered RUBY line also carries two guide RNAs in its promoter with sequences not found anywhere else in the Arabidopsis genome. This allows dCas9-TPL to bind to and repress this particular gene and not affect the transcription of other genes. We then crossed this transgenic plant line with plants expressing the dCas9-TPL repressor and the matching guide RNA. Visual screening of the Repressed RUBY line showed these plants turn faint whitish-pink instead of bright purple, signifying that the repression by TPL is working. I am currently on the next step which is identifying a homozygous line of Repressed RUBY to generate a mutagenesis population using the chemical EMS. Once I have these seeds, I will use visual screening to search for plants that have bright red or purple organs, which means that the repression by TPL is not working as well. By identifying regulators of corepressor function in plant biology, I hope to learn principles that can inform cellular engineering across many organisms and better understand why certain mutations associated with transcriptional repression cause developmental defects or diseases like cancer in humans.

Side-channel attacks on typing input devices can leak private user data such as passwords or other personal information. We have developed a system to perform such an attack by exploiting the timing of keystrokes as an input signal. Prior work has shown it is possible to retrieve this timing information by exploiting weaknesses in operating systems that leak the timing information of hardware interrupts and cache accesses. However, others have demonstrated systems to counter this attack by injecting fake data at various points in the software stack. Other prior work has demonstrated it is possible to infer individual typed keys by analyzing the frequency domain of the sound emitted by each key press, but it has not yet been shown that this type of attack is possible at natural typing speeds. Additionally, homophonic keyboards would be resistant to an attack that exclusively uses acoustic frequency information. We propose an algorithm that uses a combination of the above approaches—infer the timing information of the key presses from an audio recording of a user’s natural typing, analyze the frequency content of the sounds, and predict the typed words. Our preliminary study shows that we can identify boundaries between words with 79% accuracy. We use machine learning models to predict the current word using its inter-keystroke timings and the predictions of previous words. Our initial study demonstrates 76% prediction accuracy on a fixed dataset of 30 words. Overall, we show that it is not sufficient to prevent leaking keystroke information within the device’s own operating system. We present a solely audio-based algorithm to identify typed words, so the ubiquity of other passive recording devices like smartphones and smart speakers may still allow us to identify a nearby user’s typing on a computer keyboard, an important security risk.

Autism Spectrum Disorder (ASD) is a neurodevelopmental disorder characterized by social-communicative impairments and restricted, repetitive behaviors (RRBs). Children with ASD often have impairments in executive functioning (EF), a broad term for cognitive processes including working memory, planning, impulse control, inhibition, and mental flexibility. Previous research has identified direct links between EF problems with RRBs in children with ASD. Intrinsic brain activity measured by Resting-State EEG (RS-EEG), particularly activation of beta (12-30 Hz) and theta (4-8 Hz) bands, has been shown to reflect memory and inhibition. Prior RS-EEG research has found links between reduced theta and beta activation and increased alpha activation in children with ASD. Thus, this project examines the associations between EF problems and resting-state alpha, beta, and theta activation. This study includes 217 participants, ages 8-17 years (ASD=109) from the ACE GENDAAR network, a four-site NIH-funded project investigating sex differences in individuals with autism. ASD diagnosis was confirmed via gold-standard diagnostic measures. EF was assessed using the Behavior Rating Inventory of Executive Function (BRIEF), a parent-report with eight clinical scales measuring specific EF abilities. RS-EEG was measured using an eyes-open paradigm where children sat and looked at screensaver-like videos. Movement and blink artifacts were rejected, and Fast-Fourier Transformation was performed over clean segments. Average power in the alpha, beta, and theta bands was abstracted over 9 different areas across the head for each subject. We hypothesize that EF abilities in participants will correlate positively with theta and beta activity levels and negatively with alpha activity, specifically in the frontal regions. We hypothesize that, similar to children with ADHD, ASD participants will have a greater theta-beta ratio than typically developing (TD) participants. This study’s data can provide a better understanding of the relation between ASD and EF and identify biomarkers to distinguish between ASD and other EF dysfunction prognoses.

The BVF (Boring Volcanic Field) located in the Portland Basin west of the Cascades arc, is home to a wide variety of chemically distinct basalts. These basalts resemble mid-ocean ridge basalts, ocean island basalts, and intra-plate type basalts both chemically and mineralogically. Given the small area of this field, and the availability of all sample types throughout the entire volcanically active period, the cause of this diversity remains a challenge to explain. To investigate this process, we have used a MC-ICP mass spectrometer to collect magnesium isotope ratio data. While this diversity could come from a heterogenous mantle, with each of these sample types coming from a different mantle source, we expect that there are added components which change the chemical composition of the magma. Magnesium can be used as a tracer for added contributions in igneous rocks since the isotopic ratio of this element is not changed by volcanic processes, thus the data we record is representative of the source of these samples. Additionally, magnesium is most largely fractionated by low temperature processes such as carbonate precipitation and weathering. Given this, materials such as subducted crust or sediments would leave a recognizably different magnesium ratio in any basalt produced from this interaction. By combining our magnesium data with previous major (>1 wt. %) and trace element (<0.1 wt. %) analysis, we have tested for the presence of subduction derived isotopic signatures. From these discovered influences, we will produce a more accurate model of magmatism that accounts for the variety found in the BVF.

This research project will focus on the measurement of the influence of the fibers on the strength of fiber-reinforced concrete (FRC), examining both the experimental method used and the theoretical background needed to extract the salient material properties. Here, the primary interest is in the tension strength. The stress-strain relationship of most engineering materials is determined with direct compression and tension tests. However, this method proves to be unsuitable for testing the tension strength of FRC due to various factors. In this research project, we will determine the stress-strain relationship of FRC using a flexural beam test. The beam test is considered more reliable because the load can be controlled better than in the direct tension test, and stress concentrations and eccentricities can more easily be avoided. However, the experimental results must be combined with theory to extract relevant information. In structural analysis and design, it is common practice to begin with a known stress-strain relationship and the dimensions of a beam section and integrate to determine curvature for a sequence of moments. Our approach is the reverse of this process. Using a system of differential equations relating strains, moments, and axial stresses, and with strain measurements from the top and bottom midspans of the beam, we intend to inversely develop the stress-strain relationship of FRC in compression and tension through differentiation of a polynomial regression. We expect results to indicate that fiber-reinforced concrete has a higher residual strength than what is currently accepted and that our testing procedure will yield more accurate and valuable results than traditional tests. These findings could change the way cementitious materials are tested and improve efficiency in the built environment thereby decreasing carbon emissions. This presentation will highlight the steps, challenges, results, and implications of our project.

Syphilis is a sexually transmitted infection that is caused by the bacterium Treponema pallidum subsp. pallidum (T. pallidum). Syphilis is still a global health problem and has been on the rise in the United States for over two decades now. Therefore, an effective tool to perform syphilis molecular epidemiology is needed to track disease spread. Several typing systems have been proposed for syphilis since 1998. This includes the Enhanced CDC (ECDC) system, which is based on several approaches:analysis of amplicon length, restriction fragment length polymorphism (RFLP) pattern, and sequence analysis. A second more recent approach, referred to as the Multi Locus Strain Typing (MLST) system, utilizes sequence analysis alone following target amplification. This MLST method amplifies three very large regions of the T. pallidum genome: the tp0136, tp0548, tp0705, and the 23 rRNA genes. Both ECDC and MLST, however, have  several limitations. The new protocol we are testing aims at reducing the size of the MLST targets to increase efficiency, and at adding new loci to increase the discriminatory power of the method. This new approach is called MLST2. To establish whether the MLST2 protocol is indeed an improvement, we applied it to several patient samples. In more detail, we performed DNA extractions on patient samples as well as eight different touchdown amplifications per sample, one for each gene target. We then performed Sanger sequencing once we had determined that the amplifications worked via gel electrophoresis. We compared the typing results with both the MLST and ECDC results to assess which approach was most discriminatory. If the new MLST protocol provides similar results as the older methods, it will be an improved system for tracking syphilis strain types due to its more sensitive design. This will have important implications for epidemiological surveillance as well as diagnosis and treatment.
 

Long term exposure to air pollution can be detrimental to health, leading to respiratory effects, cardiovascular effects, and total mortality. In the 1930s, a practice called redlining reduced the accessibility of mortgage financing for racial minorities and immigrants, and continues to affect the infrastructure and demographics of neighborhoods today. Understanding characteristics of air pollutants is important because people of color and low income communities have historically been exposed to higher concentrations of air pollution as a result of discriminatory practices. Communities exposed to high levels of multiple pollutants at once may be more at risk for health effects. In this project I aimed to define pollutant mixtures of black carbon (BC), nitrogen dioxide (NO₂), carbon dioxide (CO₂), and ultrafine particles (UFPs) at measured locations in Seattle, then predicted the mixtures at other locations to evaluate exposure disparities due to redlining. Annual average air pollution estimates for BC, NO₂, CO₂, and UFPs were obtained from mobile monitoring measurements of 309 residential locations throughout urban Seattle in 2019 and 2020. Distances to roadways, airports, and other pollution sources were obtained using GIS software, and land use, population density, and greenspace were also characterized. Initial pollutant mixtures were defined at the mobile monitoring locations using principal component analysis. The first PC is a weighted average of pollutants, representing the contrast between high and low exposure locations, and the second PC is a contrast between UFPs and other pollutants. I then predicted the mixtures in redlined neighborhoods using geographic covariates. These predictions provide insight into how the patterns of UFP exposure differ from other pollutants, giving us a better understanding of the pollutant mixtures in our community as a result of urban planning. These insights can lead to further research on the toxicity of these mixtures and to equitably work toward cleaner air.

Previous research documents the influence of colorism (discrimination based on skin tone) on multiple adverse health outcomes among Black Americans. In general, Black Americans with darker skin tones have worse physical and mental health outcomes than their peers with lighter skin tones. Among Black mothers, colorism is associated with delayed prenatal care, low birth weight, and preterm birth. However, the influence of colorism on the risk of miscarriage has not yet been explored. Using data from the National Longitudinal Study of Adolescent to Adult Health (Add Health), I investigate the association between skin tone and miscarriage among Black American women. The study also explores several potential mechanisms that may explain such an association. These include the experience of discrimination by expectant mothers, class-related variables such as education and wealth, and behavioral variables such as nutrition, exercise, and smoking. Finally, it evaluates whether disparities in risk of miscarriage increase with age as psychosocial and physiological stress accumulate at different rates between women with different skin tones. Understanding the role that colorism plays in causing disparities in miscarriage among Black women will help us to identify policy interventions to mitigate this social problem.

Avian scavengers perform a critical ecosystem service by breaking down dead and decomposing organic matter and recycling the nutrients back into the food web. However, the quantity of decaying biomass different avian scavengers seek out has not been well researched in Washington State. This study asks the question: How does the amount of biomass remaining on an ungulate (hooved animal) carcass influence which avian scavengers visit the carcass? I am conducting my study using camera trap image data from the Washington Predator-Prey Project (WPPP) from northeastern Washington. This study placed a trail camera in front of an ungulate carcass and recorded photos using a motion sensor. I extracted information on the number of each type of species present from each of those images. My data set includes over 360,000 images from 51 roadkill carcass sites. I hypothesize that large avian scavengers (e.g. turkey vultures and bald eagles) and small avian scavengers (e.g. magpies and common ravens) will either compete for access to the carcass or will facilitate each other in accessing the food source. The analysis will include comparing the number of photos containing at least one individual of each bird species against the percentage of carcass biomass remaining. Increasing our understanding of what quantity of biomass different avian scavengers seek out will improve our ability to protect them and Washington’s ecosystems.

Colin Kaepernick kneeling on the football field in August of 2016 was not the first instance of athlete activism in history but was incredibly meaningful to our current politics. Two years later, in September of 2018, Nike released their Dream Crazy advertisement featuring Colin Kaepernick. Evidence shows that this campaign had significant economic consequences for Kaepernick and Nike, leading one to believe that there could have been political consequences as well. Therefore, I ask: to what extent did Colin Kaepernick’s campaign with Nike mobilize public support for and against racial justice in the United States? I hypothesize that there is a positive relationship between exposure and donations; as exposure to the campaign increases so do donations to both racial justice efforts and counter-racial justice efforts. I reason that people’s actions are grounded in emotions and morals; with the polarization of the United States growing, a political act like Kaepernick’s taps into people’s allegiances and identities and they will act accordingly. To test this hypothesis and answer my research question I have gathered Google search term data from August 2018-October 2018 to gauge how much attention the Nike advertisement got. Then I gathered donation data from seven political campaigns representing the left and right sides of the political spectrum from August 2018-October 2018 as a measurement of political activism. The campaigns were chosen based on their salience on each side of the Black Lives Matter conversation and include Donald Trump and Alexandria Ocasio-Cortez. Preliminary results suggest that there may be a positive relationship between exposure and donations. This matters because it exemplifies the power that big brand names and celebrity athletes have on the political playing field. The consequences of this participation and influence are vast, it can create polarized divides and mobilize action.

Mycoplasma genitalium (MG) is a sexually transmitted bacteria that causes urethritis in men and cervicitis, pelvic inflammatory disease and infertility in women. MG infections vary in length: some infections are cleared within a few weeks, others last for years despite a robust antibody response that targets the MgpB and MgpC adhesin proteins. Antigenic variation in MgpB and MgpC may allow MG to avoid clearance by host antibodies leading to persistent infection. We hypothesized that infections are cleared in some patients because their antibodies target certain sections of MgpC and MgpB that are important to induce complement-mediated killing. In order to determine which parts of MgpB and MgpC are important targets, we collected antibodies from rabbits immunized with different fragments of MgpB and MgpC. The antibodies were purified from serum, then titered using ELISA assays to equalize their activity. We used EDTA and EGTA to inhibit different complement activation mechanisms to determine which pathways are involved in killing MG. We performed two assays to measure antibody-dependent complement killing. One assay measured colony counts after exposure of MG to antibodies and complement (complement killing assays) and the other measured inhibition of MG growing in broth cultures (metabolism inhibition assay). This information was used to identify which parts of the MgpB and MgpC proteins result in the most efficient killing by antibodies and complement.

The purpose of this study is to test the relationship between xenophobic rhetoric and Asian American and Pacific Islander (AAPI) political mobilization. The COVID-19 pandemic, which originated in China, has led to undeserved blame and hatred towards Asian Americans during COVID’s early stages. As a result, discrimination against Asian Americans had increased by over 150 percent during the pandemic’s first year. I theorize that the increase of xenophobia will fuel mobilization based on feelings of victimization. Expectations from the study stem from a theory of mobilization that AAPI members will strive for political action instead of a withdrawal from politics when racial targeting is solely Asian-oriented and relies on negative, inaccurate stereotypes. In order to test the effects of discrimination, I will employ regression models to examine whether xenophobic tweets from former President Donald Trump lead to increased mobilization and solidarity among Asian-Americans in online settings from late 2019 until the suspension of his Twitter account in January 2021. I expect to find that xenophobic tweets with high exposure levels to these tweets–measured by the number of likes and retweets–lead to increased popularity in Google-searching terms related to AAPI mobilization (e.g., Asian American Resources, Stop Asian Hate, etc.).

Hepatitis C (HCV) is a liver disease caused by the bloodborne HCV virus. When left untreated, HCV can lead to cirrhosis and liver failure. Recent developments in therapeutics present a cure for HCV; however, treatment must be received soon after infection to be effective. Thus, limited availability of HCV testing creates a barrier to treatment distribution as chronic HCV is identified through a detectable viral load. Current HCV testing involves polymerase chain reaction (PCR) testing of blood samples, requiring a central laboratory and technicians to run them. The delay between appointments, sample transportation, running PCR, and receiving results can lead to lost contact with patients, making it difficult to connect them with timely treatment. The goal of the project is to develop a rapid point-of-care assay for HCV nucleic acid testing that allows healthcare providers to diagnose chronic HCV in 30 minutes and immediately prescribe treatments. We designed and validated an isothermal nucleic acid amplification assay for detecting HCV RNA: a two-step process involving reverse transcription of HCV RNA into complementary DNA (cDNA) which is detected by recombinase polymerase amplification (RPA). RPA is an isothermal process held at 40℃ with a runtime of 15 minutes, where a fluorometer collects data from the reaction. We compared the results of our RPA detection assay to the PCR-HCV assay used by the UW Clinical Virology Lab. We tested RNA from all six major genotypes using serum samples from Harborview Liver Clinic, where we had a limit-of-detection of 25 copies per reaction. We were able to match the results of the RPA and PCR assays with 100% agreement. By developing a streamlined detection assay for HCV, we will contribute to HCV testing without the need for expensive machinery or trained technicians, increasing the testing availability to increase HCV treatment rate and decrease HCV prevalence.

Following a seismic event, the serviceability of buildings, bridges and other infrastructure is critical. However, determining the safety of these structures post-disaster is challenging and time consuming. Most damage assessment is done through visual inspection, which can miss structural damage that is hidden from view, behind architectural elements or in hard to access areas. To improve the efficiency of post-earthquake damage assessment, low-cost sensors that could monitor structures and send alerts of significant damage would be invaluable. One specific example of critical damage would be that of steel fracture, which significantly impacts the safety of steel and reinforced concrete structures. Fractures are highly energetic, creating a distinctive gunshot-like sound. Microphones are already used to detect gun fire, and a similar methodology could be employed to detect and locate fractures in buildings. This project explored this possibility. A database of fracture sounds from experimental tests of structural components was built from a variety of sources, including an online research repository maintained by the National Hazards Engineering Research Infrastructure (NSF-NHERI). Specific features of the audio signals, for example Mel-frequency and linear predictive coefficients, were used to train machine learning algorithms  to classify these sounds and detect fractures. Physical experiments were also conducted to record rebar fractures using an array of low-cost microphones. The placement of the microphones and the difference in arrival times were used to estimate the location of the fractures, which were compared to the true location. This research constitutes the first step in the development of a robust acoustical monitoring strategy to aid in efficiently making decisions to restrict service to compromised structures following an earthquake. This concept is becoming increasingly viable as the availability of inexpensive instruments increases. As sensors improve, this approach could become the prevailing method for post-event assessment.

The brain maintains body weight homeostasis via a tightly regulated neuronal circuitry. Microglia, the innate immune cells of the brain, elicit an inflammatory response that triggers increased food intake and weight gain on a high fat diet. We are curious how microglia regulate the neuronal circuitry to affect food intake and body weight. We have developed a chemogenetic mouse model that expresses a modified Gs-protein-coupled DREADD (Designer Receptor Exclusively Activated by Designer Drugs) selectively on microglia. Administration of the ligand Clozapine-N-Oxide (CNO) activates the cyclic AMP signaling cascade in microglia. We have found that CNO administration for three days increases the cytokine IL-1𝞫, and reduces chemotactic signals (P2RY12 and CCL3) and Agouti-Related Peptide (AgRP). AgRP is produced from neurons in the hypothalamus and is responsible for feelings of hunger. I hypothesize that microglial Gs-DREADD activation suppresses AgRP signaling and reduces food intake and body weight. To test this hypothesis, mice expressing the microglial Gs-DREADD (MG Gs-DREADD+) and control littermates (MG Gs-DREADD-) will receive daily intraperitoneal administration of CNO (1 mg/kg), and will be monitored for food intake and body weight for a week. Mice will then be placed on a high fat diet (60% kcal obtained from fat) under daily CNO administration, and will be monitored for food intake and body weight gain for 4 weeks. I hypothesize that MG Gs-DREADD+ mice will show reduced food intake and weight gain on a HFD when compared to MG Gs-DREADD- mice. At the end of the study, I will examine changes in inflammatory mediators and neuropeptides in the hypothalamus of the mice. Overall, this study will help elucidate how microglia alter hunger and satiety signals in the brain to regulate appetite and body weight. Moreover, the ability to modify these signals can help individuals manage their weight and prevent obesity.
 

Farmworkers often experience substandard housing conditions, including crowding, temperature and humidity variability, and limited cooling access. We investigated how in-home temperature, humidity, bedroom crowding, and cooling impacted sleep duration among Washington State (WA) farmworkers. We hypothesized that elevated sleep temperatures, humidity, and crowding would be associated with reduced sleep duration. In the summer of 2019, 81 orchard and vineyard workers in Central WA participated in a baseline housing characteristic survey, three successive monthly sleep surveys, and three sleep temperature measurements. We assessed housing quality, our exposure of interest, defined as: housing type, air conditioning (AC) availability, crowding (> 2 adults in bedroom) and sleeping room temperature and humidity measured with Kestrel Drops. Our outcome measure was self-reported sleep hours per night. On average, participants were 42 years of age, male (64%), had 3.4 years of agriculture experience, and slept 6.5 hours per night at 76°F and 50% humidity. 45% lived in single-family homes, 11% in apartments, 28% in barracks, and 16% in mobile homes. Average temperature did not differ between housing types. Maximum temperature was greatest in barracks (average max=83.3°F) and apartments (85.0°F) versus single-family homes (79.7°F) and mobile homes (80.1°F). Relative humidity was highest in barracks (55.5%) versus single-family homes (48.9%), mobile homes (44.9%), and apartments (45.7%). Crowding and access to AC also varied with housing type, with 100% of barracks participants and 14% of mobile home participants reporting overcrowding, and apartment participants (100%) and barracks participants (97%) being the most likely to report AC. Participants in barracks reported less sleep per night than participants in single-family or mobile homes (6 versus 7 hours, respectively). We found variation in farmworker housing conditions and reduced sleep duration in barracks. We recommend future research examining the role of housing and workplace characteristics on worker sleep quality.

The viability of redox-flow (RF) batteries has, in recent years, become an increasingly prevalent point of interest in the chemical research community. RF batteries make use of the reversible electrochemical conversion of active redox species as a form of long-term energy storage. Currently, the most practical versions of these batteries utilize a vanadium-based solution, which is both costly and difficult to manufacture on a large scale. To solve this issue, researchers explored the possibility of using organic-based solutions and natural solvents. However, most of these batteries are limited to specific classes of organic molecules. Through the development of a generalized predictive model, we will create an accurate method of predicting the redox potential of a wide assortment of organic molecules which can be used to improve downstream generative AI algorithms for molecular design. To create our predictive model, we construct a set of experimental and computational redox potentials, which train our model. After compiling a database of roughly 100 organic molecules, we use our model to find correlations between the molecules’ measured redox potential and additional properties, which are calculated using various cheminformatics packages. We expect to find an approximate correlation within an acceptable range of error, which our model can base its predictions on. The limitations of our predictive model stem from our small sample size—larger data sets directly correlate to more accurate results. The successful development of a predictive model with a bounded range of error largely improves our ability to accurately find candidate molecules with high redox potentials, molecules which could potentially be used in large-scale redox flow battery systems.

Human Herpesvirus-8 (HHV-8) causes Kaposi’s sarcoma (KS)-- a cancer of cells that line lymph or blood vessels. Individuals whose T cells have been compromised by HIV are particularly at risk for KS. The disease remains endemic in many parts of sub-Saharan Africa, making KS a leading cause of cancer death in Uganda. While HHV-8 has been known to cause KS since 1994, and T-cells that can recognize HHV-8 are likely to be critical for control of KS, there is little known about the specific parts of the virus recognized by T-cells. Our goal is to ultimately determine the antigenic targets of HHV-8-specific T-cells. Because recovery of live T-cells from biopsies is challenging, we are re-creating “artificial T-cells” with candidate T-cell receptor (TCR) sequences obtained from KS lesion biopsies from Uganda. These candidate TCRs will be queried for reactivity to HHV-8. To do this, we are generating a set of every known HHV-8 protein by moving cloned DNA expressing these proteins into a specific plasmid that is useful for these T-cell studies. To create artificial T-cells, we are cloning candidate TCRs into lentiviral vectors which allow us to force the TCRs to be expressed in these cells and fluoresce green if the cells recognize a viral protein through their TCRs. These artificial T-cells are then screened against every HHV-8 protein to find which protein they recognize. Currently, flow cytometry results demonstrate adequate expression of candidate TCRs by artificial T-cells, and the HHV-8 protein set is >90% complete. Ultimately, we hope to determine HHV-8 proteins that are recognized by HHV-8-specific T-cells in order to better understand which parts of the virus are targeted by these T-cells and to design T cell or vaccine therapies to treat persons with KS.

Pitch perception in noise is a critical skill for children to have because it allows them to enjoy music, understand speech, communicate, and learn in noisy real-world environments like playgrounds and classrooms. To date, little is known about how well school-aged children can discriminate pitch in background noise. In this study, we evaluated pitch perception in normal hearing children between 8 and 11 years of age (n=32) and adults (n=16) by administering a remote 3-Alternative Forced-Choice (3-AFC) adaptive pitch discrimination task on MATLAB Web Apps while monitoring participants’ behavior over Zoom. The study consisted of three conditions, each with three runs: (1) 200 Hz pure tone in quiet, (2) Resolved harmonics 2 to 9 of a 200 Hz fundamental frequency (F0) in noise and (3) Unresolved harmonics 12 to 19 of a 200 F0 in noise. Musical training and tonal language experience were documented in all participants. My role in this study included participant recruitment, data acquisition, analysis, and manuscript preparation. Preliminary analyses suggest that children perform worse in the condition with the higher numbered harmonics (unresolved condition), which is also more difficult for adult listeners. Moreover, improvement in all three conditions is observed with age, with the older children discriminating pitch as well as adults for both pure and complex tones. This study provides important insight into the developmental trajectory of pitch perception. In the next phase of analysis, we will investigate the role of music experience on children’s perception of pitch in noise.

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 result from circadian rhythm dysfunction. Individuals with ASD also generally demonstrate difficulty with emotional regulation, including internalizing behaviors that can present as disorders such as anxiety, depression, general mood disturbance, and externalizing behaviors such as aggression. Previous studies have suggested an association between increased sleep dysfunction and increased issues with internalizing/externalizing behaviors in children, and have insinuated a possible bidirectional relationship between the two. This study aimed to look at the relationship between sleep quality and emotion regulation (internalizing and externalizing behaviors) in adults with and without ASD. 80 adults (ASD=42) from the longitudinal Autism Center of Excellence 2 study, a five-site NIH-funded study on gender differences in autism, were included in the analysis. Autism diagnosis was confirmed via standardized measures. Participants completed the Pittsburgh Sleep Quality Index (PSQI), a measure of sleep quality and the adult self report (ASR), a measure of internalizing and externalizing behaviors. Analysis included correlations between sleep quality and internalizing and externalizing scores for ASD and typically developing (TD) groups. We hypothesized that individuals with ASD will demonstrate higher internalizing and externalizing scores and higher rates of sleep issues; and stronger correlation between the two. Additionally we explored gender differences in sleep quality within the sample. I hypothesized that decreased sleep quality and increased sensitivity to stimuli will increase emotional regulation problems in individuals with ASD. This study might provide evidence to support the increased use of therapy or behavioral interventions for better sleep to improve mental health in individuals with autism.

Quasars are the most luminous of active galactic nuclei; because of this we can study them at high redshifts to gain more insight of galactic evolution within our own universe. I am presenting a survey of extremely-high-velocity outflow (EHVOs) quasars. These are quasars whose outflows reach relativistic speeds (10-20% the speed of light). Our research group is in the process of compiling the largest catalog of EHVOs to date, which we have done by designing a series of Python modules to automate the search for EHVO quasars in the sixteenth data release from the Sloan Digital Sky Survey catalog. I was in charge of adjusting the absorption algorithm and performing the final visual inspection of EHVO candidates. The latter is performed using plots and key spectral features, which are outputs of the code I co-wrote. I also led the team to document all the programs for a future public release. I also present the analysis of the EHVO we have found in the spectrum of the most luminous quasar found to date, SMSS-J2157-3602, which was observed using Keck/NIRES and VLT/X-shooter. This result emphasizes how these outflows are likely powered by the quasar radiative luminosity, as well as allows us to adapt our codes mentioned above to other non-SDSS quasar spectra. Studies of quasars with EHVOs, especially our survey that will include information of black holes masses and quasar luminosities, are key to understanding how quasar outflows are launched and accelerated away from the central region of galaxies, as they represent some of the most extreme cases.

Plants make their first root in the embryo, which is then called the primary root. Roots that emerge from the primary root later in development are called lateral roots (LRs). LRs are important for providing stability to the plant, and assisting in acquisition of nutrients and water. I am using LRs to understand how cell division (the cell cycle) is connected to developmental transitions. Previous studies have shown plant hormones auxin and cytokinin play important roles in cell division and LR organogenesis. Cells that have the capacity to become LRs with the right signal are called founder cells. Founder cells form when a few undifferentiated cells in the primary root respond to a pulsatile auxin signal to become ‘specified’ LR stem cells, retaining potential to proliferate and the ability to differentiate into LR. These specified LR stem cells arrest in the G2 phase of the cell cycle, respond to auxin signaling, and undergo rounds of cell division, marking the onset of LR development. In this study, I investigated whether G2-arrested cells in the specification stage are receptive to auxin and cytokinin. Specifically, I analyzed LR primordia shape, LR developmental progression, and LR density in response to treatment with auxin and cytokinin in plant lines where the cell cycle is disrupted. Preliminary results reveal an increased density of LRs in plants with a long G2/M transition when they are exposed to auxin. This suggests that progression through the cell cycle may reduce auxin sensitivity. The understanding gained from these experiments is helping build a framework for how the cell cycle contributes to LR development, allowing for future genetic modifications to improve root structure in crop plants.

One of the most striking adaptations in land plant evolution has been the specialization of reproductive structures and strategies. LEAFY (LFY) is a gene well characterized in flowering plants (angiosperms) as a transcription factor that initiates the development of the flower, which contains the reproductive organs. LFY has also been shown to regulate the first cell division of the zygotes in mosses (a type of non-vascular plant). The fern Ceratopteris richardii (CrLFY) is a type of non-flowering plant that is midway phylogenetically between mosses and flowering plants, and belongs to the sister clade to seed plants (angiosperms and gymnosperms). Therefore, C. richardii is an ideal model to study LFY's functional evolution. Previous research has shown, through the suppression of CrLFY expression via RNAi, that it maintains the identity of the apical stem cell in gametophytes, the haploid life cycle stage. To further characterize the function of LFY in ferns, we are now studying the effects of its over expression on gametophyte phenotypes. Given that overexpression of LFY causes early flowering in angiosperms, we might expect to see early development of the sperm and egg producing reproductive structures (antheridia and archegonia) in fern gametophytes. Here, I analyze data on the morphology and developmental timing of antheridia and archegonia of fern gametophytes overexpressing each of the two gene duplicates, CrLFY1 and CrLFY2. Our goal is to address whether CrLFY plays a role in the reproductive development of gametophytes, as it does in the sporophytes of seed plants. Characterizing the function of this gene will help us map how the LFY gene, and other master regulators of development more generally, have adapted through the evolution of land plants to serve vastly different functions in different plant lineages.

Arabidopsis thaliana, a long day plant, has important flowering time mechanisms in place to ensure reproductive success. The FLOWERING LOCUS T (FT) gene encodes a florigen molecule that regulates flowering time in Arabidopsis. In long day conditions FT protein is synthesized in phloem companion cells in the leaf and transported from the leaf through the phloem to the shoot apical meristem (SAM) in order to initiate a flowering response. Here we investigate the Myb-related protein ALTERED PHLOEM DEVELOPMENT (APL) which is believed to cause a late flowering phenotype in Arabidopsis by repressing FT transcriptionally. Flowering time experiments with varying results and gene expression analysis with APL overexpressing transgenic lines indicated that two versions of the APL protein exist. We then hypothesized that there is an alternative start site downstream from the original start site of the APL gene which, when synthesized, becomes a shorter version of the APL protein. When the shorter version of the APL protein heterodimerizes with the full length APL protein, the heterodimer complex is not able to bind to the FT transcription domain, allowing activation of FT and an early flowering phenotype. This was hypothesized because early flowering was observed in further flowering time experiments with the shorter version of APL overexpressed. Studying the FT locus, and factors that affect it, uncovers the mechanism by which plants flower at particular times depending on different light conditions. Understanding this molecular reproductive mechanism in plants is useful for enhancing crop yield.

Designing binders for single beta strand and beta-hairpin peptides could be useful for a wide range of biomedical applications. This project aims to design peptide binders that force unstructured peptides into a beta strand conformation. The computationally designed peptide-binder pairs were expressed and purified utilizing Immobilized Metal Affinity Chromatography (IMAC) and characterized via Size-Exclusion Chromatography (SEC) and biolayer interferometry. Successful binders were redesigned to bind pathogenic fragments of Amyloid-beta, alpha-synuclein and tau. These fragments are known to form beta strand mediated fibrils in the brain that are associated with the development of neurodegenerative diseases like Alzheimer’s and dementia. I am currently characterizing the redesigned binders for Amyloid-beta and expect higher-affinity binding with these designs. Success of this project could provide a new tool in studying the fibril formations and allow for future drug therapies.

In the United States, 296,000 people live with spinal cord injury (SCI)1. SCI is one of the most debilitating neurological conditions due to the crucial role played by the spinal cord in everyday life. The current treatments for SCI involve invasive surgeries, such as spinal laminectomies and decompressions, which are often paired with non-invasive therapies, such as medications and physical rehabilitation. Despite major innovations in medicine, regeneration of central nervous system (CNS) neurons remains challenging. As a result, reorganization and adaptation, promoted by current therapies, play key roles in recovery after CNS damage with physical rehabilitation being the gold standard of treatment after SCI. Recent SCI research in our laboratory has focused on development of neural interfaces for targeted, intraspinal delivery of plasticity-enhancing neuromodulators, such as brain-derived neurotrophic factor and serotonin. In these experiments, neuromodulator delivery was paired with use-dependent physical rehabilitation on a forelimb reach-and-grasp behavior that is directly impaired by the cervical SCI. We found that our combined intervention promoted greater forelimb-motor recovery compared to physical training alone. However, there were variabilities in the recovery profiles across animals with similar injuries within the same intervention group. Low levels of motivation can lead to less engagement in physical therapy and may be contributing to the observed variabilities. The purpose of this study is to assess motivation levels in spinal-cord injured rats to understand how it affects forelimb-motor recovery given our interventions. Motivation levels will be assessed before, during, and after therapy to examine its influence on motor recovery. We will also assess how SCI and motor recovery impact animal motivation. Preliminary analysis in 6 adult female rats, whose motivation levels were compared before and after injury, shows that SCI lowers motivation (t(5) = 3.052, p = .03, paired samples t-test). Experiments in additional rats are currently ongoing.

In this project, we measure electron flow in graphene, a 2-D lattice of carbon atoms, and compare the results to simulations. As current is passed through typical electrical devices, the electron’s diffusion is dominated by collisions with impurities in the atomic lattice, giving rise to the material's resistance, the opposition to flow. This is called ohmic conduction. However, clean graphene permits a more dynamic and exciting type of conduction-- the hydrodynamic regime. Here, electrons’ collisions with each other are significant, and their collective behavior becomes water-like. When measured over a range of temperatures, we find dips in the resistance, resulting from these hydrodynamic electrons’ tendency to “pull” one another along with the bulk. Like honey, these electrons have viscosity, which unlike resistance, is a property of the fluid. This research will further elucidate properties of the electron fluid. To complete this project, we fabricate graphene devices and study them in a table-top cryostat, measuring the current profile from 4K to room temperature. We are particularly interested in how this viscous fluid behaves as it encounters a boundary within the device, an open question in the field. Using a unique homebuilt experimental instrument, called the feedback-lockin amplifier, we visualize the flow of electrons around a small scan probe tip. Comparison with python simulations helps us elucidate the fluid's boundary conditions. This research will directly benefit the electronics industry. The next generation of computer chips will utilize 2-D materials such as graphene, potentially enabling the useful properties of hydrodynamic flow to be harnessed. For example, the reduced resistance inherent to hydrodynamic conduction may increase the power efficiency of transistors.

 Tuberculosis (TB) is the second leading cause of death due to infectious disease worldwide, accounting for 10 million infections and 1.5 million deaths in 2020. The ubiquitin-binding protein, Toll Interacting Protein (TOLLIP), is associated with TB susceptibility in genetic studies and small animal models. In mice lacking TOLLIP (Tollip-/-), lungs develop profuse lipid-laden foamy macrophages, which induces the integrated stress response (ISR), a cellular adaptation to harsh environmental conditions. However, how Mycobacterium Tuberculosis (Mtb) induces foam cells and the relationship between foam cells and the ISR is uncertain. We treated mice with the Mtb cell wall lipid mycolic acid (MA), a model of lipid accumulation, to understand how TOLLIP influences lipid accumulation and ISR activation in macrophages. MA was administered to Tollip-/- mice intraperitoneally and Mtb replication, lipid accumulation, and the ISR were evaluated. MA treatment was associated with increased mycobacterial replication. ISRIB treatment, a drug inhibitor of the ISR, restored immune control in Tollip-/- macrophages. Three and five days after MA administration, Tollip-/-  peritoneal macrophages (PEM) developed increased intracellular lipid accumulation measured by flow cytometry, demonstrating that TOLLIP is essential to prevent MA-induced foam cell formation and intracellular Mtb replication. Future studies will characterize the impact of MA treatment on host cytokine responses and the impact of the ISR on lipid accumulation feedback loops. These findings can contribute to novel therapeutics for the treatment of TB infection.

Impacts of climate change, such as warming ocean temperatures and increased prevalence of disease, greatly affect intertidal marine environments within the Puget Sound. These impacts can alter behaviors of marine invertebrates, resulting in ecological cascade effects within rocky intertidal zones. The goal of this study was to observe variation in growth and feeding behaviors of organisms within a trophic cascade including plankton, pacific blue mussels (Mytilus trossulus), and sea stars (Crossaster papposus and Pisaster ochraceus) as a representation of the rocky intertidal zone in the Puget Sound. Experiments were conducted under two temperatures, 11.8°C and 20.7°C, to simulate a control similar to current water conditions and an increased temperature similar to recent heat wave conditions. Plankton growth rate was measured by counting the change in number of individuals per 1 mL sample over a four day period. Mussel feeding behavior was measured by recording change in fluorescence over a four day period, both with and without the presence of a predator (sea star). Sea star feeding behavior was measured by counting the number of mussels consumed over a 24 hour period. The results showed decreased plankton growth in the increased temperature treatment (t-test, p=0.065). Mussel feeding rate decreased as a result of both increased temperature and presence of a predator (two-way ANOVAp=0.040). Sea star feeding rate additionally decreased under increased temperature (t-test p=0.090). Because these organisms are integral to rocky intertidal zones, we can use their behaviors as bioindicators and conclude that these ecosystems are impacted by climate change. Variation in behavior could result in significant changes in species abundance and ecosystem structure; it is essential to research how ecosystems within the Puget Sound will adapt to future environmental conditions.

Genomic data provide critical information about biodiversity and phylogeography, particularly since genomics has become increasingly used to understand the nature of species boundaries. Species boundaries are difficult to delimit using morphology alone, while genomic data provide direct evidence for understanding the connectivity between populations or species. A recently described horned lizard, Phrynosoma diminutum, inhabits a unique ecological region of Colorado and is miniaturized relative to the surrounding populations of greater short-horned lizards (P. hernandesi). Phrynosoma hernandesi is a wide-ranging species with substantial morphological variation throughout its range, and despite the obvious size difference between P. diminutum and P. hernandesi, a complete lack of gene flow between these populations seems unlikely since there is no clear barrier to dispersal, which would cause speciation. To determine the extent of gene flow between populations and test the genetic support for P. diminutum as a distinct species, we compared P. diminutum genetic samples to surrounding populations of P. hernandesi. Using 3,000+ genetic markers distributed throughout the genome, I found that P. diminutum does not form a distinct evolutionary lineage and is only weakly differentiated from nearby P. hernandesi populations. Comparisons of genetic differentiation among all 17 species of horned lizards using fixation index (FST) values provides further evidence that the low levels of divergence observed in P. diminutum are reflective of population-level and not species-level divergence. Therefore, we propose that P. diminutum be synonymized with P. hernandesi rather than recognized as a distinct species. This conclusion has implications for land management, since it may be necessary to maintain corridors of gene flow between the miniaturized and surrounding populations. Furthermore, we show how genomic data can be used to avoid artificially inflating biodiversity estimates by more accurately testing species boundaries, and this allows managers to make precise decisions for wildlife and whole ecosystem conservation.

Fanconi anemia is a serious genetic blood disorder caused by mutation in the FANC genes, responsible for the regulation of DNA interstrand crosslink repair. Failure of this mechanism results in chromosomal instability and is extremely damaging. Patients are also at a greatly increased risk for malignant cancers such as acute myeloid leukemia. The goal of the project is to develop novel methods to treat Fanconi anemia using gene therapy-based vectors, including a lentiviral vector containing an shRNA CD33 knockdown that confers selective protection, and to eliminate dangerous residual Fanconi anemia cells following treatment. Through in vitro validation, I will test several therapeutic vectors that provide a functional copy of the gene for correction of the FANCA defect and protection of corrected cells from drugs that target CD33, which are commonly used to treat secondary myeloid malignancies that often develop in Fanconi anemia patients. Then, using a FANCA -/- mouse model, I will use in vivo tests to determine if vectors can rescue the FANCA deficiency and provide selective protection using flow cytometry, cell and colony assays, and qPCR. I identify the more efficient lentiviral vectors for further tests. Together, these experiments are crucial in the development of a clinically viable blood stem cell-based therapy for Fanconi anemia that protects patients from the high risk of secondary malignancies such as acute myeloid leukemia that are so prevalent.

In the United States, one-third of the adult population is considered obese. Although excessive food intake leads to obesity, a return to normal body weight is extremely difficult once established. A growing body of evidence finds that changes in the brain prevent a return to normal body weight. In particular, Agouti-related peptide (AgRP)-expressing neurons, which drive feeding and feeding-related behaviors, show blunted activity in response to food and hormonal cues in obese mice. Using a mouse model, our group found that sensed ambient temperature regulates AgRP neuron activity, such that cold increases AgRP neuron activity, and this increase in activity drives food intake, but this temperature sensitivity is lost in the obese mouse model. However, how AgRP neurons receive thermal information is not understood—owing to the speed with which AgRP neuron activity changes in response to cold sensation, thermal information is most likely relayed by an afferent circuit. Here, I report the identification of a novel population of tyrosine hydroxylase (TH)-expressing neurons located in the rostral paraventricular nucleus of the hypothalamus (PVHTH neurons) as candidate upstream mediators of cold-induced AgRP neuron activation. As evidenced by the expression of the immediate early gene, Fos, cold activates this population similarly to AgRP neurons, and these neurons send projections to the arcuate nucleus of the hypothalamus (ARC), where AgRP neurons are located. I hypothesized that activation of this population, as part of a larger thermoregulatory neurocircuitry, would shift the preferred ambient temperature of mice such that they prefer warmer temperatures, as well as increase food intake to levels seen in mice housed in the cold. My findings underscore the link between thermoregulation and energy homeostasis and begin to define a circuit which, if disrupted, might underlie the perseverance of obesity.

Rapid and smooth emergence from the anesthetized state to the awake state is important for patient safety and perioperative efficiency, yet is currently a passive process and the underlying mechanism is not well understood. In mice, emergence from anesthesia is modeled by the return of righting reflex (RORR) signaled by righting from the supine to prone position as the mouse emerges to an awake state. Using this model, it is possible to investigate the neuropharmacological mechanisms of emergence. While commonly studied in concert with neuronal recordings and optogenetic manipulation, these approaches can be combined with high-throughput automated behavior analysis using deep and machine learning approaches. Here, my goal is to create an automated behavioral classification pipeline for annotating the RORR in combination with experimental manipulations and recordings. I aim to characterize the transition between unconscious and awake states to define a binary output. This is accomplished by using DeepLabCut pose-estimation software to track subject mouse body parts, followed by the generation of supervised behavioral classifiers for RORR-related behaviors using the SimBA (Simple Behavioral Analysis) machine learning pipeline. My ongoing directions focus on performing unsupervised classification with this model to cluster additional behaviors. This use of advanced behavioral analysis will enable a better understanding of behaviorally-relevant neural activity in emergence and help bridge the gap between preclinical animal models and clinical intervention.

African Americans are at higher risk for cognitive decline due to historical and ongoing systemic inequities. Research shows that African Americans are often under-included in healthy aging research, contributing to a lack of generalizable data and health interventions specific for this population. The Sharing History through Active Reminiscence and Photo-imagery (SHARP) Study in Portland developed a brain health intervention in partnership with Portland’s elder Black community members. The intervention involves walking routes that prompt conversation of key landmarks in Portland’s historically Black neighborhoods. The purpose of this study is to model the SHARP Portland Study in Seattle’s historically Black Central District neighborhoods and identify key community landmarks and themes through community partnerships. We will use community-based participatory research (CBPR) to collect data to inform the development of the walking routes. With assistance from my colleagues, I conducted two focus groups with a total of ten African Americans aged 55 years and older that live or have lived in Central District’s historically Black neighborhoods. Focus groups solicited information about significant landmarks, people, and events in the community. We anticipate that these findings highlight the history and values significant to the Central District’s aging Black communities. I am helping code the interviews using a thematic analysis to inform the development of the prompted walking routes. This study lays the foundation for translating the SHARP intervention into a Seattle community.

Cells in the body grow inside the extracellular matrix (ECM), which is composed of a combination of carbohydrates and proteins, presenting chemical and mechanical cues to the cells inside. Nearly all cell types are sensitive to the mechanics of the ECM and respond to cues such as stress, strain, and curvature, which influence organism development and disease progression. Hydrogel biomaterials are water-swollen polymer networks that mimic the properties of the ECM in vitro, allowing researchers to study cellular behavior in a controlled environment. In this project, we aim to develop a hydrogel platform where strain on the material, generated by contractile cells embedded within it, can be activated externally by a researcher in order to induce curvature in an engineered tissue, which we will use to investigate the effects of mechanical cues on cells encapsulated inside the hydrogel. We have synthesized a peptide crosslinker that acts as a two-input Boolean AND gate, with one half degradable by cell-secreted enzymes and the other half degradable by sortase, a researcher-added enzyme. We predict that when a cell-adhesive hydrogel is made with this crosslinker, contractile cells will be unable to expand until the addition of sortase; after sortase degrades one arm of the cyclic AND-type crosslinker, they will be able to locally degrade the hydrogel, spread within the gel, and then contract to generate stress and strain. We intend to encapsulate immature cardiac stem cells partway through differentiation, predicting that curvature alone will trigger further specification of these cells into their mature subtypes. Understanding the mechanism by which mechanical cues affect development will help identify new therapeutic targets for diseases where tissue curvature is important, and it will also inform new stimuli to improve the similarity of tissue grown in vitro to native tissue.

The Allen Brain Observatory Visual Coding datasets include recordings from thousands of visual cortical neurons while mice have been presented with a variety of visual stimuli. Furthermore, conditional gene targeting techniques enable the recording of highly specific populations of neurons, producing a vast dataset spanning many cell types, brain regions, and cortical layers. While these neural data are frequently studied in literature, a largely unexplored subset of this dataset involves over 1400 hours of eye tracking videos recorded during experiments. Saccades—fast, fixational eye movements—are known to play a central role in visual processing for foveal animals, such as humans, but it is less clear how they impact visual processing in rodents. This project investigates saccadic eye movements in head-fixed mice: both the patterns of saccades that mice make as well as how these saccades affect neural responses in the visual cortex. We find that mice make infrequent saccades, typically around 4.5 saccades/min, that are predominantly along a horizontal axis. These eye movements appear to not be driven by visual stimulus features, but we do find that mice make more saccades when they are running compared to when they are stationary. Finally, we compare neural responses to eye movements across different cortical areas and layers, and see how they vary with visual stimulus, running speed, and saccade magnitude. Through this neural activity analysis, we gain a better understanding of how saccades influence the underlying representation of visual features.

Plants recognize insect herbivore attack by detecting molecular patterns in their oral secretions. Steinbrenner et al. have recently identified a host plant receptor for one such pattern, termed the Inceptin Receptor (INR). INR binds herbivore-derived inceptin peptide and confers signaling and defense responses in response to inceptin, including a measurable burst of reactive oxidative species and the gaseous hormone ethylene. INR is present only in species of the legume subtribe Phaseolinae (e.g., common bean, Phaseolus vulgaris). INR was previously studied using heterologous expression in tobacco, but the role of INR in beans themselves has not been studied due to difficulty of genetic transformation and knockout approaches. I have created a backcrossed line of common bean introgressing a naturally occurring inr- mutation into a genome sequenced variety. Inceptin response is compromised in inr- near isogenic lines. I plan to use the inr- near isogenic line to measure the contribution of INR to caterpillar feeding relative to wild type plants. To quantify the feeding habit of caterpillar species when fed these two lines, I optimized a high throughput herbivory assay and imaging pipeline to quantify feeding behavior and tissue consumption. We hypothesize that plants lacking INR will show reduced deterrence, increased tissue consumption, and increased larval weight gain upon caterpillar feeding. Understanding how plants sense attack will help us to develop varieties that are resistant to pests and pathogens.

Atherosclerosis is the build-up of cholesterol, fats and other substances in artery walls. These builds-ups (plaques) can cause vessel blockages, leading to heart attacks and strokes. Removal of cholesterol from plaques is facilitated by the physiologic process of reverse cholesterol transport (RCT). In RCT, apolipoprotein AI (apoAI) protein removes cholesterol from vascular tissue, forming high-density lipoprotein (HDL) that is transported to the liver for excretion. Gene-therapy strategies that use vectors to increase apoAI expression in arteries slow and reverse atherosclerosis in rabbits. However, because apoAI has multiple activities including reducing inflammation, it is unclear whether vector-derived apoAI reduces atherosclerosis by contributing to RCT. To determine whether apoAI gene therapy contributes to RCT, I am developing a method that can track HDL that contains vector-derived apoAI in vivo. If we can detect vector-derived apoAI/HDL in treated arteries as well as plasma and liver, we will conclude that vector-derived apoAI contributes to RCT. I am first developing methods that purify and detect endogenous apoAI/HDL; these methods will be applied to detect vector-derived apoAI/HDL (the vector-derived apoAI will have a molecular tag). I used density-gradient ultracentrifugation to isolate HDL from pulverized rabbit tissue and plasma, then immunoblotting to detect apoAI/HDL. I detected abundant apoAI/HDL in plasma, but not in aorta and liver. Immunoblots of artery extracts (before ultracentrifugation) detect apoAI, suggesting that apoAI is lost during ultracentrifugation. I am testing whether other methods can purify apoAI/HDL from aorta and liver (e.g. affinity chromatography to isolate apoAI from tissue extracts, followed by size-exclusion chromatography to isolate apoAI/HDL). After I develop a method to isolate apoAI/HDL from tissue, we will treat rabbit arteries with a tagged apoAI vector and measure tagged apoAI/HDL in arteries, plasma, and liver. Verifying how vector-derived apoAI works will help us to improve its atheroprotective effects.

Autism Spectrum Disorder (ASD) is a neurodevelopmental disorder characterized by social, communicative, cognitive, and behavioral impairments, observable in over 2% of adults in the United States. Hedonic capacity is a concept that is defined as reward responsiveness and has become associated with ASD and related disorders. When faced with stimuli that are typically considered to be rewarding, one’s level of hedonic capacity can be determined by his or her ability to feel pleasure in response. Research has shown that individuals with ASD experience decreased levels of social and interpersonal pleasure when compared to typically developing (TD) individuals. Considering the prevalence of social impairments in autism, I aim to analyze the relationship between hedonic capacity for interpersonal pleasure and autism social traits in ASD and TD adults. 99 adults (ASD = 52) from the longitudinal ACE2 study, a five-site NIH-funded study on gender differences in autism, were included in the analysis. Participants completed the Anticipatory & Consummatory Interpersonal Pleasure Scale (ACIPS), which assesses an individual’s ability to look forward to interactions with other people (anticipatory social pleasure) as well as to experience pleasure for social/interpersonal interactions when they occur. We also utilized the Social Responsiveness Scale (SRS-2) to measure participant social responsiveness, including social motivation. I expect ASD individuals to have a lower ACIPS score and more deficits in social responsiveness. Additionally, I expect that individuals with decreased interpersonal pleasure will have greater social responsiveness impairments and expect this relationship to be stronger in the ASD group. Understanding the relationship between hedonic capacity for interpersonal pleasure and social responsiveness will allow us to further understand how decreased social pleasure may be related to autism traits and symptoms. 

This abstract is no longer available. Please contact urp@uw.edu if you have any questions.

Global climate change is likely to have an effect on plants, pollinators, and the interactions between the two ecological groups. Recent studies have suggested that climate change may affect the growth and development of these organisms in the long-term, but variations in temperature could also change the short-term behavior of pollinators when they visit plants. For instance, pollinators with certain physical traits might be better suited to forage in areas with higher or lower temperatures. In this study, I explored this idea with the assumption that the foraging decisions of pollinators are indicative of the temperatures that they are flying at. I addressed the questions of 1) how variation in temperature affects pollinator traits? and 2) are certain pollinator traits correlated with differences in the identities and traits of the plants that they are captured visiting? To answer these questions, I measured the size of bees collected in the Rocky Mountains during the summer of 2021, and I compared these sizes to the temperatures at the sites at which the bees were caught. I predicted that 1) pollinator traits would correlate with temperature, and 2) the interactions in my data analysis would show trait matching between the pollinators and the plants that they were visiting when caught. The results of this study should help illustrate how the impacts of climate change might affect plant-pollinator communities, which could help to identify potentially advantageous traits as well as interactions that may be flexible or persistent during changing climatic conditions.

Understanding the human health effects from marine plastics is an emerging field of public health. Marine plastic waste contributes to a global plastic problem. Evaluating health impacts from marine litter requires approaches that characterize plastics as well as health perceptions from different populations. This project contains two parts: 1) a focused review of nanoplastic methodologies to frame how standardization is needed to compare findings across studies and measure health effects and 2) a household survey to understand how marine plastics impact well-being in two coastal communities in Ghana. The meta-analysis on nanoplastic techniques showed a variety of techniques are used, among which the most common are Raman spectroscopy and Pyrolysis Gas Chromatography Mass Spectrometry. Different definitions of nanoplastics were identified across studies, where “nanoplastic” was most commonly defined as a plastic polymer with a diameter less than 1000 nanometers. The meta-analysis also showed that many studies analyzed spherical polystyrene because they are easy to obtain rather than other plastic polymers that are representative of environmental exposure. The Ghana survey included a quantitative analysis of demographics, plastic dependency, stress, well-being, and perceptions on plastic waste management. The majority (72%) of Ghana survey respondents were of low socioeconomic status (making less than 355 Ghanaian Cedi a month (~54 United States Dollars) during the pandemic). Many respondents agreed that plastics have improved their quality of life but expressed concern about plastics effects on their health and livelihood. As the field of marine plastics develops, robust standardized techniques must be adopted and real world nanoplastic samples need to be included in studies. Considerations of equity and health outcomes should be in place as well. Understanding how different populations, especially underserved and marginalized communities, perceive and use plastics is instrumental for solving this global plastic problem.

Many synthesized chemicals in current use, based on carbon-intermediates, are byproducts from the crude oil refining industry. Due to the industry's highly efficient infrastructures along with cost-effective methods, it has been hard to think of any chemicals other than petrochemicals. However, with a recently growing desire for alternative carbon sources, more and more research has started to target the biomasses, which are potentially richer sources full of diverse intermediates. Such biomass-derived intermediates convertible to various chemicals are defined as "bioprivileged" by previous work in the field (Shanks, Broadbelt). Still, there is no apparent method to identify the bioprivileged molecules; the existing experimental approach is slow because only a small number of structures may be evaluated at a time. Thus, we use de novo molecular design models trained on a variety of commercially available chemical compounds databases, such as ZINC and PubChem, to generate a massive set of potentially bioprivileged molecules having a set of desired functional moieties. We measure the likelihood of a molecule being bioprivileged by the R0 and R1 reactivity indices, a recursive quantification of the number of reactive moieties used to estimate the reactivity of corresponding species. The reactivity indices serve as a target for optimization within a de novo design framework and allow us to generate candidate molecules that are enriched with the desired functional groups. This method may serve as the foundation for future work on discovering bioprivileged molecules including retrofitting synthetic pathways from biowaste precursors, optimizing reaction kinetics/selectivity through catalyst design, and analyzing the physiochemical properties of downstream products with respect to a set of desired functionalities. It may also be used in more general contexts to generate a set of molecular structures that are enriched with any set of desired substructures.

Wildfire smoke contains fine, inhalable particles called PM2.5, as well as dangerous levels of heavy metals and other toxins. Wildfire smoke can increase emergency room visits for asthma and upper respiratory infections in kids, reduce immune function, lead to cardiovascular and lung diseases later in life, and create long-term cancer risks. When schools close from wildfire smoke, learning loss and lost school days can affect children’s health and wellbeing throughout the rest of their lives. Low-income kids could be left without access to learning resources, meals, or school support services. Installing, improving, and maintaining HVAC (Heating, Ventilation, and Air Conditioning) systems is critical for mitigating exposure to smoke, as well as other emerging challenges. The state does not keep records of the ventilation systems in California’s 10,000 public schools or which schools might need additional support in funding their HVAC. I calculated the cost estimate of installing, maintaining, and upgrading HVAC systems to all K-12 schools in California. Methods I conducted include gathering data from the county Superintendent of education, emailing school admins listed on the California Department of State database, calling over 700 school districts for data collection, and consulting with HVAC contractors and other partners. The estimate for installation, maintenance, and upgrading cost is approximately $4.0 billion. The estimate will be used to advocate for further funding for wildfire preparedness for schools. Results will be used in the policy roadmap for implementing the Green New Deal for Public Schools in California and policy brief.

Pregnant women are particularly vulnerable to influenza A virus (IAV) infections, which increases the risk for maternal mortality, hospitalization, preterm birth and stillbirth. The pathogenesis of IAV infections in pregnancy and the immunologic reasons for greater susceptibility to lung disease in pregnancy remains poorly understood. The CD4+ T helper Type 17 (Th17) cell-mediated response facilitates an early immune response critical for viral clearance of IAV and is impaired in mouse models of severe disease. Whether Th17 responses are important for exacerbating maternal IAV disease is unknown. We hypothesize that pregnant individuals have impaired Th17 responses in the blood and lungs, which exacerbate lung disease. We inoculated pregnant (N=6) and non-pregnant (N=5) pigtail macaques with IAV H1N1 2009 and collected serial blood and bronchoalveolar lavage (BAL) samples until Day 5 post-inoculation (peak disease) when we performed a necropsy. I am extracting RNA from maternal fluids and tissues to determine the IAV viral load and gene expression of Th17 transcriptional activators (e.g., RORc gene) using quantitative reverse transcriptase polymerase chain reaction (qRT-PCR). We will perform qRT-PCR on lung tissues at peak disease and peripheral blood mononuclear cells (PBMCs) across the infection time course. To better understand innate immune activation at peak disease, I will also analyze the expression of a 50-gene panel of innate immune genes in maternal lungs and plasma using a novel technique called Nanostring nCounter, which barcodes and counts mRNA transcripts. The advantage of this technique is that one can accurately quantify mRNA transcripts in a multiplex manner from very small samples. Finally, we will link data from flow cytometry, qRT-PCR and the nCounter to assess the Th17 cell-mediated response and innate immune activation to investigate the susceptibility of pregnant individuals to severe lung disease after IAV infection.

Hovering flight is one of the most energetically expensive forms of locomotion in hummingbirds. While flying animals already dissipate large amounts of muscle-generated heat to avoid overheating (thermoregulation), hummingbirds' expensive hovering flight and extensive muscle use suggests they may need to lose larger amounts of heat to remain normothermic. It is known that hummingbirds dissipate excess heat through heat dissipation areas (HDA) around the eye, shoulder, and feet. Other birds with larger bills use their bills as a supplemental tool for heat dissipation. Given the length of the hummingbird bill in relation to their body size, it could be possible that their bills have potential for heat dissipation. Using the FLIRT6xx-Series Thermal Imaging camera, we measured the temperature gradient between the environment and the bill surface of Anna’s Hummingbirds during flight in a range of temperatures that occur naturally in their home range (for this study, Seattle, WA). We also quantified bill surface area in high-resolution microCT scans of museum specimens, using open-source software (SlicerMorph). Further, we are developing novel scanning methods (macro photogrammetry) to allow for data collection in the field with free-living hummingbirds in situ. We hypothesize that if the bill is used for heat dissipation during flight, we will see a strong correlation between bill surface area and the thermal gradient of the bill-environment interface. Furthermore, we are considering the time of active hovering as a possible cause of variation in heat dissipation. This analysis could lead to more information about the limits of endurance for flying endothermic animals under the effects of climate change. Moreover, the methods developed to analyze bill surface area could be extended to related subjects, such as observing specimens from a variety of time periods, to quantify potential evolutionary patterns.

Prediction of response to preoperative or ‘neoadjuvant’ chemotherapy (NAC) can help guide treatment strategies for patients with triple-negative breast cancer (TNBC), a highly aggressive subtype of breast cancer. Breast magnetic resonance imaging (MRI) can provide noninvasive measurements of the microenvironment across a tumor volume. We hypothesize that pre-treatment measurements from dynamic contrast-enhanced (DCE-) MRI reflecting tumor perfusion and vascular function are predictive of NAC response for TNBC patients. Women with TNBC who underwent pre-treatment MRI and NAC at our institution (2005-2019) were retrospectively identified. DCE-MRI was acquired at 2, 5, and 8 minutes after contrast injection. From DCE-MRI, whole tumor contrast kinetics measures including functional tumor volume (FTV), percent enhancement (PE) at 2 mins post-contrast and signal enhancement ratio (SER) were calculated, and hotspot measures of peak PE and peak SER (representing the highest mean PE and SER, respectively, for 3?3 voxel subregions) were determined. Imaging measurements were compared between those with complete pathologic response (pCR; no residual cancer present in the breast at surgery) and non-pCR patients with a two-tailed Student’s t-Test (p<0.05 considered significant). 95 women (median age: 49, range: 30-79 years) with TNBC were evaluated, of which 29 (31%) achieved pCR. FTV was significantly higher in non-pCR patients (21.1±28.1 cc) compared to pCR patients (8.6±11.3 cc, p<0.01). Peak SER was also higher in non-pCR patients (1.8±0.3) compared to pCR patients (1.7±0.3), trending toward significance (p=0.06). No significant differences between groups were observed in peak PE measures. Patients with lower pre-treatment tumor FTV and peak SER on DCE-MRI were more likely to achieve pCR after standard NAC. These findings indicate that baseline DCE-MRI measurements may help predict response and assist in optimizing treatment plans for TNBC patients, such as selecting more aggressive regimens incorporating immune checkpoint inhibitors or other novel agents in predicted non-responders.

Associations between aggression and social functioning have been identified among typically developing individuals; however, the link between aggression and social concerns among individuals with Autism Spectrum Disorder (ASD) is not well understood. While aggression is not considered a defining feature of ASD, it is observed at elevated levels and is associated with increased risk of harm to the self and others, and reduced opportunities for social relationships and learning. The aims of this study are to determine whether 1) there is a concurrent association between aggression and impairments in social functioning among children with ASD, 2) aggression can predict social functioning among children with ASD six months later (T2), and 3) peer relationships mediate the potential link between aggression and social deficits among children with ASD. We analyzed data from 399 (ASD- 280) children ages 6 -11 years who were enrolled in the Autism Biomarkers Consortium for Clinical Trials (ABC-CT). We used Spearman’s correlation to understand a potential relationship between aggression and social functioning. To investigate whether aggression can be used to predict social impairments, we compared a series of linear models with social ability at T2 as the outcome variable, and age, sex, aggression, and group (ASD or typically developing) as predictor variables. Peer relationship data was only available for participants with ASD so we ran a mediation analysis among this group to determine whether peer relationships mediate the link between aggression and social deficits. We hypothesized that there would be a positive association between aggression and concurrent social impairments, the best-fit model would include aggression as a predictor variable, and peer relationships would mediate the link between aggression and social impairments. The results of this study may provide information that can be used to optimize interventions for individuals with ASD, improving their quality of life.

Polymers are important in all areas of life from commodity plastics to vaccine delivery. Currently, plasticizers are small molecules used to make rigid polymers into the flexible plastics we need. However, the problem with these plasticizers is that by disrupting intermolecular polymer chain interactions, they can degrade the polymer over time and leach out into the environment. When plasticizers escape, they can be toxic to human health and harmful to the environment. By inserting a plasticizer into the backbone of the polymer rather than into the polymer solution, we reduce the risk of toxic molecules escaping the polymer. To solve this problem, a fluxional molecule such as bullvalene can be inserted into the backbone of the polymer. Bullvalene is a small molecule and due to its fluxional property, it will induce flexibility into the polymer as an internal plasticizer. Bullvalene is considered fluxional because it can undergo Cope rearrangements at room temperature. The purpose of this research is to develop the methods for synthesizing a novel polymer and to analyze its chemical and mechanical properties such as glass transition temperature and tensile strength. My project focuses on polycarbonates, a specific class of polymers. Polycarbonates are in many plastic materials such as water bottles and are increasingly important for consumer electronics. The results will have positive implications for human and environmental health by providing methods to develop safer plastic material.

 Quantum dots are semiconducting nanomaterials that are useful in converting solar energy because of their high absorption and tunable photophysical and chemical properties. They can have various organic ligands bound to their inorganic surface, creating quantum dot-ligand systems useful for charge and energy transfers. When a quantum do is excited by external radiation, an electron inside the dot is promoted to a higher energy level and can be extracted form the quantum dot through the ligands surrounding the dot. We hypothesize that by binding the charge accepting ligand directly to the quantum dot, charge extraction from the quantum dot will be promoted. In my experiments, I am trying to determine the extent of ligand binding to the quantum dot and how this binding is affected by the identity of the binding moiety. To do this, I am synthesizing cadmium sulfiide quantum dots and attaching various ferrocene derivatives through a titration experiment. I analyze each step of the titration experiment for each quantum dot-ligand system with cyclic voltammetry (CV), an electrochemical technique that is sensitive to the diffusivity of the charge acceptor. The resulting CV curve can then be modeled with DigiElch to extract the favorability of the binding of the ligand to the quantum dot. Based on the magnitude of the equilibrium coefficients, we can determine which ligand binds most favorable to the quantum dot and compare this to the efficiency of charge extraction. This research has many applications, from solar energy to medical imaging, and the ability to extract charge outt of the quantum dot in an efficient and quick manner is one worth researching. This research is supported and overseen by Prof. Brandi Cossairt, and graduate students, Micaela Homer and Florence Dou. 

Magnetoencephalography (MEG) is a powerful noninvasive technique for measuring the location of brain activity in real time. MEG is used today in research and clinical settings around the world, and is especially advantageous for measurement on children. An array of highly sensitive sensors outside the skull measures the magnetic field produced by current in the brain. Algorithms then localize this synaptic current via a process called the magnetic inverse problem. Critical to this challenge are assumptions intrinsic to the equations that describe magnetic fields. This project explores the assumptions and fundamental structure of major equations used in MEG today. By performing simulations and mathematical modeling we shed light on the interpretations of MEG signal as well as scrutinize what types of synaptic current MEG is capable of seeing. The ultimate goal of our exploration is to help researchers, neuroscientists, and clinicians understand the power and limitations of MEG and make accurate and meaningful claims.

Syphilis is a chronic sexually transmitted infection that is caused by the spirochete bacterium Treponema pallidum subsp. pallidum (T pallidum). Although syphilis is mistakenly believed to be a disease of the past, it is actually still endemic in low and middle-income countries, and it has been steadily resurgent in high-income nations, including the USA, for the past 20 years. An effective syphilis vaccine would greatly help curtail syphilis spread. Our current understanding of syphilis pathogenesis suggests that for a syphilis vaccine to be effective, it must induce antibodies able to opsonize antigens on T. pallidum surface to induce pathogen ingestion by macrophages. To this end, we used three T. pallidum putative surface antigens as vaccine candidates, which belong to the T. pallidum repeat (Tpr) protein family, specifically TprC, TprK, and TprD2. Once synthesized as recombinant antigens, New Zealand White (NZW) rabbits were immunized every three weeks with a total of five injections, and then challenged with infectious T. pallidum on their shaved backs. After the challenge, the efficacy of the vaccine candidate was tested by monitoring several correlates of protection, including lesion development and treponemal burden within the injection sites. Immunization with the TprC and TprK antigens induced attenuated lesions and reduced treponema burden, but not immunization with TprD2. Although at the end of the experiment all the rabbits were positive for syphilis infection based on serology, we demonstrated that TprC and TprK were effective in inducing partial protection, and therefore should be considered as vaccine candidates for this serious infection.

Sexual dimorphism is the presence of morphologically distinct characteristics between males and females of the same species. Our project investigates the evolution of sexual dimorphism in the mandible across the family Canidae. We have created a database of 3D scans of specimens from the Burke Museum's mammalogy collection. We used a macroevolutionary approach to understand why sex-based differences exist today. Rensch's rule states that in male-biased species, sexual dimorphism is more evident in larger species. In female-biased species, the opposite effect is observed with smaller species exhibiting a greater degree of sexual dimorphism. Our project tests Renschs rule across a variety of Canids to determine if the degree of sexual dimorphism is greater in larger taxa. Using 3D models and geometric morphometrics, we placed landmarks on digitized mandibles to quantify sexual dimorphism in mandibular traits between males and females across various Canid species. Landmarked differences quantify sexually dimorphic features in the mandible, which we incorporated into evolutionary models to hypothesize how sexual dimorphism arose through evolution. Our project investigates whether Rensch's rule is applicable in Canids of various body sizes. We hypothesized that Canids will conform to Rensch's rule and that in larger Canid species, there will be a larger degree of sexual shape dimorphism for male-biased species. Rensch's rule is often tested with respect to size dimorphism, but limited studies use a multivariate approach to look at interspecific differences in sexual shape dimorphism. Our study will help answer ecological questions such as whether size and shape dimorphism is more significant in larger Canid species and whether sexual selection or niche divergence may be attributed to their evolution.

Prostate cancer is the second leading cause of cancer death among men in the United States and its detrimental form, known as castration-resistant prostate cancer (CRPC), currently has no cure. The importance of cancer metabolism has been recognized as a potential target of anti-CRPC therapy. The Plymate Lab recently developed compounds known as selective glycolytic inhibitors (SGIs) that target glycolysis in selective types of cancers including CRPC. Specifically, SGI’s block the first step of glycolysis, in which glucose phosphorylation is catalyzed by hexokinases. Nevertheless, SGI proved not to be a traditional catalytic inhibitor. HK1 and HK2 are major hexokinases in prostate and other cells and their mitochondrial localization is pivotal for their activities. The goal of my project is to test the hypothesis that SGIs affect mitochondrial localization of HK1 and HK2. I used immunofluorescence techniques to examine the physical association between the hexokinases and mitochondria. To do so, I treated a prostate cancer cell line, LNCaP, with SGIs for 30 minutes, which is the amount of time I found the anti-glycolytic effect of SGIs to be evident. Upon doing so, I did not see any significant changes in subcellular localization of HK1 and HK2 between treated and non-treated groups. The majority of HK1 and HK2 were associated with mitochondria, which were fluorescently visualized by MitoTracker Red CMXRos, which labels mitochondria with red fluorescence. It has been reported that the association of mitochondria with hexokinases largely relies on its ability to bind to VDAC1. Thus, I am currently carrying out co-immunoprecipitation assay to assess physical association between HKs and VDAC1. This study will help determine whether SGIs display their anti-glycolytic activity by altering subcellular localization of hexokinases.

Recent advances in neural recording technology are allowing scientists to record data at unprecedented scale. For example, the International Brain Lab (IBL) is a consortium of 22 labs working together to produce mouse brain recordings using high-density Neuropixels probes. In total, the IBL stores data from over 1000 sessions which provide a picture of neural activity across the entire mouse brain. At this scale, traditional static images and visualizations fail to communicate the results of neural analyses for brain wide activity and time-dependent behavior. As a tool for researchers in the IBL and undergraduate courses, we are developing 3D visualization software, the Virtual Brain Lab (VBL), capable of rendering a complete view of neural activity in the mouse brain in a simulated interactive laboratory. In my role as a developer, I am building tools to (1) rescale trial-averages around events and replay neural responses with variable event timings and (2) replay a single trial recorded in the IBL. Our simulation is built using the software package ‘Unity,’ allowing easy construction of custom 3D environments and publishing to diverse devices from laptop browsers to tablets, to virtual reality headsets. Displaying event-averaged neuron activity and single-trial replays will help IBL researchers spot anomalous data and holistically view their recorded sessions. Additionally, researchers can use our software to generate high-quality figures and videos for papers, outreach, and presentations. Finally, a host of key neuroscience concepts, such as sensory and motor coding and correlated variability are only communicated to students via dry lectures or textbook figures. Expensive lab classes in which students perform neuroscience experiments to rediscover these concepts are inaccessible to schools with fewer resources. Using our framework for visualization, we can build and distribute simulated tutorials and labs for students at little to no cost – reducing barriers for neuroscience education.

Essential Tremor (ET) is the most common neurological movement disorder, impacting approximately 1% of the global population. Symptoms of the disorder are characterized by involuntary rhythmic motions of affected body parts and range greatly in tremor severity. As the disease progresses, pharmacological treatments often fail, requiring implantation of a deep brain stimulation (DBS) device to suppress symptoms. Effective treatment requires exhaustive physician tuning of stimulation parameters, which include numerous clinician visits for patients. One way that clinicians assess symptoms is to ask patients to perform behavioral tasks such as drawing spirals, which indicate non ideal stimulation through tremor patterns in the drawing. The goal of this study was to explore the feasibility and options for remote collection of symptom assessments, as well as to explore methods for detecting and characterizing tremor based on spiral features. Consented patients performed spiral drawing tasks multiple times a day on a personal digital assistant such as a smartphone with the collected data securely stored on the cloud. To ensure that access to a mobile device wouldn’t disqualify participants, we developed a device loaning process used in addition to an application developed by Runelabs as supporting infrastructure to collect data. The results of our research showed that we could not only collect data remotely over extended periods of time, but also replicated HOG (Histogram of Oriented Gradients) based classification algorithms on existing datasets to distinguish healthy vs tremor spirals with up to 94.5% accuracy. Previous lab-published results on the same dataset demonstrated a 98.3% accuracy using Principal Component Analysis, which illustrates the strength of our lab's prior work, though the higher efficiency of HOG classification is promising for larger datasets. This demonstrates our methods’ potential to allow for larger patient cohorts and possible integration with other inertial sensor data into a tremor classification model for future studies.

 

The Strand Lab Formaldehyde Team studied the use of genetically engineered houseplants to reduce indoor air pollution. Our goal was to make these houseplants accessible to the public, provide environmentally friendly décor, while also making homes safer. Formaldehyde is a ubiquitous carcinogenic chemical found in homes across the world. The houseplants are genetically engineered to express the enzyme formaldehyde dehydrogenase (FALDH) cloned from bacterium Brevibacillus brevis. FALDH oxidizes formaldehyde to harmless formate. Our houseplant, Epipremnum aureum, commonly known as pothos ivy, was chosen for its ease of growth, for its susceptibility to genetic manipulation, and for its inability to flower, which prevents the uncontrolled spread of genetically engineered plants. We tested the abilities of these houseplants to remove formaldehyde from the air. With the use of a flow through bioreactor and high pressure liquid chromatography (HPLC) we determined that formaldehyde was removed more rapidly by genetically engineered pothos ivy compared to the wild-type. By using the bioreactor with a permeation chamber to dose the inflowing air with trace amounts of formaldehyde we exposed the plants to concentrations of formaldehyde typical of those found in homes. We also used 2,4-dinitrophenylhydrazine (DNPH) traps to concentrate the formaldehyde in the effluent of the bioreactor for injection onto the HPLC. Thus, we were able to determine whether and with what rates the genetically engineered plants removed and degraded formaldehyde.

Tuberculosis (TB) is one of the leading causes of death from infectious disease worldwide. Macrophages are the primary replicative niche and provide critical host defense against Mycobacterium tuberculosis (Mtb), the causative organism. A TOLLIP deficiency is associated with an increased risk of TB in human studies and mouse models. TOLLIP is a ubiquitin-binding protein that interacts with toll-like receptors (TLR) involved in modulating inflammatory signaling. TOLLIP has four critical domains: a ubiquitin-binding CUE domain, a membrane binding C2 domain, an autophagosome interacting motif (AIM), and a Tom1-binding domain that participates in endosomal sorting. However, the domains required for TOLLIP’s immune regulatory function during Mtb infection in macrophages are uncertain. To understand the role of selected domains on TOLLIP’s function, we are developing lentiviral vectors to insert TOLLIP with selected protein domains deleted, along with green fluorescent protein (GFP) to tag transduced cells. We measured viral load and transduction efficiency in HEK cells by analyzing GFP fluorescence through microscopy and flow cytometry. We are currently transducing TOLLIP fragments, whole TOLLIP, and control genes into macrophages lacking the TOLLIP gene. TOLLIP (-/-) bone-marrow derived macrophages (BMDM) were infected with lentivirus after 3 days and stimulated with LPS (10ng/ml) after 5 days. Viral supernatants were collected to evaluate TOLLIP gene expression through fluorescent microscopy. The approaches developed in this project will provide the foundation for understanding the critical structural elements of the TOLLIP protein and their role in preventing TB disease.

Exploring the neural mechanisms modulating complex social behavior requires a holistic understanding of both central and peripheral body states. In freely interacting mice, social behaviors are often registered by changes in autonomic nervous function, including altered blood pressure, heart and breathing rates, and core body temperature. Unfortunately, these physiological metrics are difficult to obtain during complex social behavior due to substantial hardware requirements, like collars and tethers, restricting full movement and interaction. In collaboration with an industry partner, we are developing a fully implantable, battery-free device for wireless data acquisition of physiological data, including heart and respiratory rate, temperature, and other behavioral information such as locomotion and orientation of mice using biomechano-acoustic (MA) methods. Here, we validate the use of MA devices in both anesthetized and freely moving mice. First, we tested MA devices during emergence from anesthesia and compared anesthetized recordings using MA devices to a widely used and commercially available rodent pulse oximetry device. Second, we obtained MA recordings in freely interacting mice during complex social behaviors. This technology represents a crucial advanced tool for experimental behavioral research that enables non-invasive operations in cages with simple or complex environments in an individual or groups of animals.

Autism Spectrum Disorder (ASD) is a neurodevelopmental disorder characterized by communication and social impairments deficits. I am investigating alpha power, EEG activity between 8 and 12 Hz, which is found present during quietly resting with greater power (amplitude squared) when the individual's eyes are closed rather than when their eyes are open. This is thought to reflect increased cortical activation (decreased power) when eyes are open in preparation for attention and cognition. Previous research shows lower alpha power in individuals with ASD as compared to typically developing (TD) and has been associated with attention and cognition and social understanding and imitation in individuals with ASD. I plan to evaluate the association between eyes-closed EEG resting-state alpha power and social responsiveness in youth with and without ASD by gender and diagnosis. We collected data from 152 youth (ASD = 76) ages 8-17 years from an NIH-funded study investigating sex and gender differences in youth with ASD. The youth sat with their eyes closed while we collected high-density EEG data. A fast fourier transformation (FFT) was applied to artifact-free EEG data to extract alpha power for central and posterior electrodes. I calculated the Regions of interest (ROIs) for alpha power over: left frontal, mid frontal, right frontal, left central, left posterior, mid central, mid posterior, right central, and right posterior. Parents of children completed the Social Responsiveness Scale-2 (SRS-2), a 65-item rating scale measuring autism traits. I conducted a series of one-way ANOVAs, and correlations to evaluate the differences in frontal, central, and posterior alpha power x group (ASD/TD), gender (male/female), and associations with social responsiveness. Preliminary results comparing alpha power and social responsiveness show significant group differences. This research is important since it helps individuals currently affected with ASD and helps understand the larger class of neurodevelopmental disorders.

Tuberculosis (TB), a respiratory disease caused by Mycobacterium tuberculosis (Mtb) bacteria, continues to be a leading cause of death worldwide. There is an overwhelming need to better understand protective immunity and develop an improved vaccine due to variable efficacy in preventing infection with the current TB vaccine, Bacillus Calmette–Guérin. T cells are required for the protective immune response to Mtb infection. γδ T cells are a subset of T cells known to be involved in Mtb protection, but the mechanisms by which they control Mtb remain poorly understood. However, γδ T cells are a major source of the cytokine IL-17, which promotes lung inflammation, and recruits cells for immune response, suggesting that IL-17 may contribute to γδ T cell control of Mtb. I characterized the T cell secretion of IL-17 in a cohort of South African adolescents that have latent Tb infection or are TB uninfected. I sorted γδ T cells and ɑꞵ T cells from sample PBMCs and stimulated these cells with Mtb antigens to measure the secretion of IL-17 via an enzyme-linked immunosorbent assay. I hypothesized that T cells taken from latently infected individuals would secrete greater amounts of IL-17 compared to those that are not infected due to a preexposure to Mtb antigens. Additionally, I predicted that γδ T cells from latently infected individuals would secrete a higher proportion of IL-17 compared to ɑꞵ T cells. Investigating the IL-17 secretion by T cells can potentially provide us with a better understanding of the role that IL-17 producing T cells play in protective immunity and inform vaccine development.

Coronavirus disease 2019 (COVID-19) is caused by SARS-CoV-2 infection. COVID-19 is associated with higher risk of new-onset diabetes and metabolic complications of diabetes, which may occur via injury to insulin-producing islet β cells due to direct SARS-CoV-2 entry. While the canonical pathway of viral entry via human angiotensin converting enzyme 2 (ACE2) has been established as a major route of SARS-CoV-2 infection in the lung, expression of ACE2 has not been unequivocally demonstrated in beta cells. It is therefore important to understand how other proteins known to be highly expressed in pancreatic endocrine cells may be involved in SARS-CoV-2 entry. Glucose regulatory protein 78 (GRP78), also known as binding immunoglobulin protein (BiP), is an endoplasmic reticulum (ER) chaperone. Under conditions of ER stress, as induced by SARS-CoV-2 infection, GRP78 translocates from the ER membrane to the plasma membrane, where it has been shown to bind to SARS-CoV-2-spike in vitro. Previous studies have found GRP78 to aid the entry of other coronaviruses. As GRP78 is expressed in β cells, we investigate GRP78-mediated SARS-CoV-2 entry into β cells using a mouse β cell line, wherein mouse ACE2 is unable to bind SARS-CoV-2-spike. To promote GRP78 translocation to the plasma membrane, ER stress is induced using thapsigargin or cytokine treatment. Verification studies involve validating the upregulation of GRP78 at the mRNA level and in plasma membrane fractions. A cell fractionation protocol has been adapted to isolate plasma membrane protein from other cellular fractions. Further experiments will involve the use of a pseudovirus system to investigate SARS-CoV-2 entry under conditions of GRP78 overexpression and knockdown. Studying SARS-CoV-2 entry into β cells may illuminate possible therapeutic strategies to protect islets from the deleterious effects of COVID-19, including the development of diabetes.

Batillaria attramentaria (hereafter Batillaria) is a highly prolific mud snail in Padilla Bay, WA, with an estimated 8 billion plus in the bay alone. Understanding the ecology of Batillaria is important, as it is an invasive species and its ecological role within the bay is unknown. This study aims to identify Batillaria’s substrate preference when given access to bare sediment, algae, and Zostera detritus in Padilla Bay. Three experiments were developed to test the hypothesis that Batillaria prefers algae detritus over Zostera detritus, over bare sediment with organic content (hereafter mud). First, a field substrate preference experiment was set up at two locations with three plot types: algae, Zostera, and control (mud). Both sites were resampled three times over a 21-day period. A second experiment was designed to obtain a higher resolution of temporal data, for nine days. The second experiment used two plot types at one location: algae and control. A third experiment was conducted in-lab to see if and how snails would move toward specific kinds of detritus, in which Batillaria were placed in tubs and videoed with a timelapse camera for 1.5 hours. In field experiments, Batillaria highly preferred algae detritus over Zostera detritus at one location (IC) as measured by ANOVA (p<0.01), but at the other, Batillaria did not show a preference between Zostera detritus and algae (West-90) (p>0.01). At both sites, detritus was preferred over bare sediment. In the lab experiment, Batillaria oriented toward detritus, consistent with field findings, but reversed their detrital preference. The effects of Batillaria on decomposition and nutrient cycling within the bay are unknown, so understanding their detrital preferences is the first step in unlocking Batillaria’s role in the ecosystem.

The Miocene Climatic Optimum was a period of rapid warming that occurred from 17 to 14 million years ago where temperatures rose 2-4°C above pre-warming estimates and CO2 concentrations increased to ~400-600 ppm. This event was coeval with the eruption of the Columbia River Basalts (16.6-15.9 Ma), a series of large flood basalts covering much of the Pacific Northwest. The combined forces of these events led to this period being characterized by tumultuous changes to Pacific Northwest plant communities. To quantify these changes, I am reconstructing canopy openness. Ranging from open deserts to closed rainforests, degree of canopy openness describes the amount of sunlight reaching the understory of a plant community. These differences in sunlight exposure affect the size and shape of leaf epidermal cells. Leaves grown in shaded conditions tend to have larger, more undulated epidermal cells when compared to those grown in full sunlight. In the fossil record, silica casts of those cells called phytoliths can be measured to reconstruct the canopy openness of ancient ecosystems. I am using samples from four fossil sites in Central Oregon: Hawk Rim (16.4-16.2 Ma), Mascall (15.1 Ma), Haystack Valley (23-18 Ma), and Picture Gorge Basalts (17.23-16.06 Ma). These sites range from immediately before the Miocene Climatic Optimum (MCO) through the first two million years of warming. They also include samples from sedimentary layers interbedded with basalts. Therefore, they will provide insight on changes that occurred within the plant community both as warming began and because of volcanic eruption. I hypothesize that increased temperature and CO2 concentrations resulted in longer growing seasons and a CO2 fertilization effect. These conditions promoted high vegetation productivity and therefore closed canopies. Additionally, I expect that areas impacted by eruption will exhibit open canopies due to repeated disturbance preventing the re-establishment of forests.

Cholera is a diarrheal disease caused by intestinal bacterium Vibrio cholerae. This enteric disease affects millions of patients each year and it is primarily caused by contaminated food or water. V. cholerae (Vc) infected patients can be asymptomatic or develop severe acute diarrheal symptoms. We previously used metagenomic sequencing to characterize the gut microbiota of household members of patients with cholera and found that gut microbe Rothia mucilaginosa (Rm) is present in higher relative abundance among patients with Vc compared to uninfected individuals. Here we aim to investigate how this gut bacteria interact with Vc and/or impact Vc biofilm formation. To analyze Vc biofilm, we co-cultured Rm with Vc at 37C for six hours and quantified biofilm formation using a microtiter dish assay with crystal violet staining. We first tested the biofilm formation of Vc and Rm in monocultures as controls and then we performed co-culture assays with different ratios including 1:1, 1:10, and 2:1 Vc to Rm. Additionally, heat killed and spent-cell supernatant conditions of Rm were also used to determine the interaction between Vc and Rm. Preliminary results from our biofilm assays suggests that Rothia mucilaginosa promotes increased biofilm formation of Vc. In conclusion, we found that native members of the gut microbiome can induce formation of biofilms and this interaction between gut microbe and pathogen has the potential to affect the disease outcomes.

Chronic wounds affect 20 million people worldwide and are a silent epidemic often occurring with a comorbid condition such as diabetes. Most often, these wounds are treated with wound dressings, topical formulations, and antibiotics; however, their effectiveness is hampered by the presence of biofilms. We have shown that hypochlorous acid (HOCl) is effective against chronic wound biofilms, in particular against Pseudomonas aeruginosa, one of the most persistent Gram-negative bacteria present in most chronic wounds. However, the mechanism of action of HOCl against P. aeruginosa remains unknown. Given the unique behavior of HOCl with P. aeruginosa survival, we hypothesized that the quorum sensing compounds and virulence factors would lose functionality after reacting with certain concentrations of HOCl. Here, we tested the effects of HOCl against elastase and N-3-oxo-dodecanoyl homoserine lactone (AHL), a virulence factor and quorum sensing molecule, respectively, that are excreted for P. aeruginosa survival in biofilms. Our primary aim was to study how hypochlorous acid interferes with elastase activity and modifies the AHL structure. The activity of elastase was monitored by UV-Visible spectroscopy and the effects of HOCl on the AHL was monitored by High-Performance Liquid Chromatography (HPLC). Elastase enzyme activity showed a dose response to various concentrations of HOCl. Simultaneously, we developed a successful method for monitoring modifications of the AHL. Our results suggest that HOCl can act to modulate communication signals used by P. aeruginosa. This opens up further opportunities to understand the mechanism of action of HOCl against quorum sensing compounds and virulence factors and provides useful clinical information for treating chronic wounds.

 Mutations are the main source of diversity due to the random changes in genetic sequence. Mutation rate can be influenced by genetic modifiers, DNA damage, and the environment. Mutator alleles, which cause high mutation rates, are less known about how often they arise in the natural populations and how they interact with other genomic changes, such as recombination and introgression. Using the natural isolates of the 1,011 strains of the budding yeast Saccharomyces cerevisiae, we examined the relative frequencies of different types of mutation calculated from natural polymorphisms, i.e. mutation spectrum, to determine potential historical impacts of S. cerevisiae mutation rate modifiers that affect certain mutation rates disproportionately. From the mutation spectra analysis, we observed African Beer strains are outliers and some French Dairy strains show a mutation spectra more similar to African beer strains than the rest of the strains. Our initial analysis of the two groups of strains suggests potential mutator allele introgression from the African Beer to some of the French dairy strains. We set out to examine de novo mutation spectra from African beer, French dairy strains with and without African beer Introgression. The natural strains have a variety of ploidies so we repurposed our existing mutation accumulation pipeline with haploid strains. Using CAN1 as a reporter gene, we deleted the endogenous locus using CRISPR-Cas9 and inserted a sensitive copy to measure the mutation spectra in these strains to test the hypothesis. We expect to find the introgressed French dairy strains’ mutation spectra resemble that from African beer strains if our prediction is correct. Ultimately, our results will shed light on how mutators behave in natural populations of budding yeast and how they contribute to evolution.

The ‘Pesticides Labels Now!’ mobile application strives to minimize agricultural worker and community exposure and illness from agricultural pesticides through improving access to pesticide labels and safety information in Spanish and English. Pesticide handlers, managers, and supervisors are able to gain access to this information, change behaviors accordingly, and transfer the safety information to others. We hypothesized that user characteristics such as language choice, mobile device type, and location would determine frequency of interactions with the application. This study investigates the application’s user audience and their preferences for app utility. Statistical analysis and graphing was conducted with R Studio (Version 2021.09.1) for users accessing the application over one year starting in August 2020. The raw data set consisted primarily of users from the State of Washington, containing 67,754 interactions and a total of 503 unique users. The results showed that user utilization is predominantly concentrated in central Washington, which is part of the Columbia Basin, and has very productive agricultural land. The overall frequency of each language accessed on the application was relatively comparable - with 59% in English and 41% in Spanish. The analysis further indicated the majority of users utilize the application through an iOS system. An estimated 74% of interactions were accessed through an iPhone device and 26% were accessed through an Android device. By understanding the effect of user characteristics in their interaction with the application, necessary adjustments can be made to the application to create a more user-friendly experience and contribute to improving access to pesticide labels and their safety information.

While it is established that plants generate defenses in response to herbivory, little is known about the specific elicitor-receptor interactions that initiate the immune response. The recently discovered inceptin receptor (INR), which is found in certain legume speices, recognizes an 11-amino acid polypeptide named inceptin (In11) commonly found in caterpillar oral secretions. INR is a receptor-like protein and consequently does not have a kinase domain, which is essential for initiating the signaling pathway that results in an effective plant immune response. However, we hypothesize that INR forms a receptor complex with coreceptors that transmit the initiating signal intracellularly. These coreceptors may also enable INR to recognize and respond to In10, a truncated version of In11 that is only recognized by Phaseolus vulgaris (common bean). To determine the specific function of these coreceptors, a genome-wide association study was performed to identify potential candidate genes; this analysis pointed us to the somatic embryogenesis receptor kinases (SERKs), which are known to play a role in many signaling pathways for plant immunity and have been found to associate with INR in response to peptide treatment. I cloned and coexpressed five common bean SERK proteins along with INR in N. benthamiana via agrobacterium mediated transformation and measured production of ethylene and reactive oxygen species as assays for inceptin perception and immune response. We found that most SERK homologs did not appear to modify INR function, although some homologs showed elevated immune outputs in the absence of inceptin. Further experiments involving these candidate genes, such as a western blot to verify interaction between INR and the SERK homologs, are needed to establish the function of these coreceptor candidates. By understanding cell surface signaling networks involved in INR signaling, we can implement more specified pest management systems that enhance crop resistance, making more sustainable agricultural practices.

Pain is one of the key contributing factors on why people seek medical attention and healthcare globally due to its negative effects on both patients and their families. Therefore, understanding the circuits that control pain and how noxious stimuli contribute to the assignment of negative valence is critical for discovering novel analgesics for pain treatment. Analgesic Screen 1 (AS1), a small molecule screened in our lab, has been shown to reverse the valence of painful noxious stimuli and renders them attractive. Using zebrafish as a model for the study, we performed several different behavioral assays that give them a choice between a neutral and noxious stimulus for various sensory modalities. The stimuli that we tested were temperature, chemical and light/dark preference. Interestingly, we found out that in all these assays, AS1 managed to elicit attraction to the noxious stimuli. We tested different receptor agonists and antagonists to pinpoint the exact underlying mechanisms and found out that AS1 affected the dopaminergic circuitry, specifically the D1 receptors. Therefore, we believe that AS1 is valuable in understanding the neural mechanisms that allocate negative valence to nociceptive stimuli and help us find novel treatments for pain.

Pathogenic missense mutations in the myosin heavy chain 7 (MYH7) gene are the most common genetic cause of hypertrophic cardiomyopathy. While several pathogenic variants have been modeled and studied extensively, the majority of MYH7 variants are classified as variants of unknown significance (VUS) in variant catalogs such as ClinVar, because they lack sufficient clinical and functional data for variant effect interpretation. To model and determine the functional significance of additional MYH7 VUS, I will employ gene-editing techniques to generate single variant repair templates for several VUS of interest in human induced pluripotent stem cells (hiPSC). Following heterozygous knock-in of a variant transgene into the endogenous MYH7 locus, I will differentiate hiPSCs into cardiomyocytes using established, efficient cardiac directed-differentiation protocols for comparison to wild-type hiPSC-derived cardiomyocytes across multiple metrics. Variant effect on contractile function will be measured in engineered heart tissues (EHTs). In addition, cardiomyocyte cell size will be measured across wild-type and variants using flow cytometry. This functional data will inform VUS interpretation as benign or pathogenic and provide healthcare professionals and patients with clinically actionable information.

Autism spectrum disorder (ASD) is a developmental disorder characterized by impairments in behavioral, social, and communication skills. Mental health is defined as one’s cognitive, emotional, and social well-being. Previous research has found associations with maternal prenatal depression/anxiety and mental health disorders in offspring. Females with autism often have a history of camouflaging their autism symptoms to fit in with typical peers, which can lead to a higher risk of developing mental health disorders. The Broad Autism Phenotype (BAP) refers to certain traits involved with impairments in language, communication, and social skills in people and could influence mental health. Mothers who reported having low social support and more autism traits had more depressive symptoms. Considering this relationship, this study will explore how maternal mental health relates to the mental health of their female children with autism. 78 ASD females, ages 8-17, and their biological mothers were assessed; data were from the four site NIH funded study on sex differences. ASD diagnosis in the female child was confirmed via standard assessments. Parents completed the ACE Medical History Interview, which included questions on maternal mental health disorders, a self-report of their autism traits using the Broader Autism Phenotype Questionnaire (BAPQ), the Child Behavior Checklist (CBCL) on their child’s mental health including symptoms of internalizing disorders. We hypothesize that females with mothers who have mental health disorders will have a greater report of internalizing disorders. We also expect to see a positive correlation between BAP scores in mothers and internalizing scores for autistic female children. These analyses might give an insight on mental health development in autistic females and how it links to maternal mental health so therapies can target at the parental level in addition to the individual level, especially where the risk of developing mental disorders is higher.

Avoidable prolonged hospital stays can decrease bed availability for new patients and place patients at risk for adverse events, and be costly for hospital finances. There are few published studies that cover data of patients throughout an entire hospital; most only cover data from a specific service line. Our study aims to review patient data throughout an entire hospital to assess common barriers leading to these avoidable prolonged stays. In our institution, the care management department meets on a weekly basis to review patients who meet the crieteria of having avoidable days. We retrospectively reviewed notes from these weekly meetings and extracted common barriers, which we then organized into categories for comparison. Our study included patients discharged from August 2019 to February 2020, with any avoidable days and 21 or more hospital days. There were 180 encounters that met our criteria. The most common service lines represented are Medicine and Surgery, while the most common discharge locations are SNF and Home. The median for the total legnth of stay was 42 days, while the median for avoidable days was 17.5 days. We identified 21 common barriers. The most common discharge barriers identified are Funding, Long Term Care, COPES, Guardianship, Substance Use, Homelessness, and Care Needs too Great for SNF. In our hospital-wide study, we identified that avoidable days are found across inpatient services and represent a heterogeneous mix of discharge barriers. Further studies should investigate relationships between discharge barriers and whether any patterns exist in patients with avoidable days in service lines. 

The pairing of high-resolution volumetric imaging methods with cellular markers of neural activity holds network-level explanatory power over behavior. However, common statistical analysis approaches fall short in capturing the functional relationships between brain regions across multiple spatial dimensions. Here, we propose combining unsupervised machine learning clustering methods with network graph theory visualization to reveal intricacies from these data beyond conventional standards. We demonstrate the feasibility of this approach on a recent single-cell dataset describing the longitudinal changes of brain-wide activation during relapse to palatable food in mice. We applied a new analytical framework combining the functionality of two open-source programs: (i) Histo-Cytometric Multidimensional Analysis Pipeline (CytoMAP), packaged with unsupervised k-means clustering and t-distributed stochastic neighbor embedding (t-SNE), and (ii) Cytoscape, a network analysis program. Hierarchical radial network diagrams were applied to the dataset in which we visualized the anatomical organization of regions that underwent statistically significant changes in activation. Across abstinence duration, we found an initial suppression in activation followed by widespread increases in activation. This increase correlated with observed behavioral changes and appeared to be triggered by activation hotspots. We next interrogated the co-activational relationships amongst the >900 brain regions by running unsupervised t-SNE dimensionality reductions on the data from each experimental group. These results were validated using k-means clustering and Davies-Bouldin indexing. We observed an intuitive segregation of regions dependent on activation status. Cluster number decreased in a time-dependent manner, suggesting increases in modular processing are associated with increased activation due to abstinence length. This trend indicated that cluster membership of regions likely also changed in a time-dependent fashion, indicating a dynamic recruitment effect at a regional level underlies abstinence-related relapse vulnerability. By analyzing cellular whole-brain data in this novel manner, we gained new insight into a previously unexplored dimension of brain activation dynamics underlying complex behavior.

Oxytocin (OT) is a downstream target of the adiposity signal, leptin, and is an attractive therapeutic target to treat obesity because it reduces body weight in diet-induced obese (DIO) rodents even in the presence of “leptin resistance” that impairs ability of leptin to reduce food intake. Previous studies indicate that CNS administration of OT reduces body weight in DIO rodents by reducing food intake and increasing energy expenditure. We recently demonstrated that chronic hindbrain [fourth ventricular (4V)] infusions of OT (16 nmol/day) reduced body weight by approximately 4.5±1.4% in male DIO mice (P<0.05). What remains unclear is whether chronic hindbrain (4V) infusions of OT (16 nmol/day) elicit weight loss, in part, through peripheral OT receptors (OTRs), following leakage into the periphery. We hypothesized that chronic hindbrain (4V) OT administration elicits weight loss by acting primarily at hindbrain OTRs. To test this, we measured the effects of chronic systemic (subcutaneous) minipump infusions of OT, at the same dose found to be effective in the hindbrain (16 nmol/day), as well as a 3-fold higher dose (50 nmol/day), or vehicle, on body weight, adiposity and energy intake in male DIO mice (N=11-14/group). In contrast to our findings following chronic hindbrain (4V) administration, chronic systemic administration of OT (16 and 50 nmol/day) failed to elicit weight loss (P=NS). However, both doses given systemically were effective at reducing weight gain (P<0.05) and adiposity while the highest dose also reduced energy intake (P<0.05). These results suggest that chronic hindbrain (4V) administration of OT (16 nmol/day) elicits weight loss by acting predominantly at hindbrain OTRs while systemic OT limits weight gain by acting, in part, at peripheral OTRs. Together, these findings support the hypothesis that chronic hindbrain (4V) administration of OT reduces body weight and adiposity in male DIO mice by acting primarily at hindbrain OTRs.

 

Global cycling of elements like carbon, nitrogen, and iron have key roles in maintaining the biosphere. These and other micro- and macro-nutrients undergo important reduction-oxidation and acid-base transformations in the environment. Biologically, iron (Fe) and manganese (Mn) are utilized by microbes as cofactors in many essential proteins and enzymes including nitrogenase, ferredoxin, peroxidase, cytochromes, and phosphotransferase. These elements (most notably Fe) can often limit microbial growth in large regions of the ocean because of their trace environmental concentrations, or due to structural bioavailability, or competitive microbial uptake and utilization. This can impact key ecosystem and cellular processes, including chemosynthetic carbon fixation at hydrothermal vents, nitrogen species reduction, and metabolic electron transport. Here we use flow cytometry measurements (FCM) to quantify bacteria and archaea from hydrothermal vent plumes along the Southern East Pacific Rise. We compare patterns in microbial abundance with total dissolvable Fe concentrations (predominantly Fe3+, including dissolved and labile particulate Fe) at the same locations. I find that bacterial abundance is most strongly related to trace-concentration of Fe below 400nM, and that similar relationships exist with trace methane (CH₄) and dissolved Mn concentrations. These findings suggest that microbial abundances in vent plumes could be partially explained by trace element and methane distributions, but further research is required to disentangle whether these important substrates are covarying with other biochemical factors impacting microbial growth and metabolism in these dynamic environments.

Women with dense breasts have increased amounts of fibroglandular tissue (FGT) and are at higher risk of developing breast cancer. Quantitative measurement of FGT from magnetic resonance imaging (MRI) could provide more robust measurement of density, supplanting conventional qualitative radiologist assessments. Current quantitative methods involve manual selection of a signal intensity threshold, which can be time consuming and subjective. Fuzzy c-means (FCM) clustering is an automated approach to tissue segmentation, offering a reproducible process for quantifying FGT volume. The aim of this study is to evaluate the efficacy of the FCM clustering in identifying FGT compared to manual thresholding. Women (N=10) who underwent screening breast MRIs at our institution were evaluated in this preliminary study. Fat-suppressed T₁-weighted pre-contrast images acquired as part of their clinical breast MRI exams were used for FGT segmentation. Prior to segmentation, I cropped the images to include only the breast. FGT was then segmented two ways, 1) manually, using a signal intensity threshold that I chose and adjusted and 2) automatically, using existing lab software for FCM clustering. The Sørensen-Dice similarity coefficient was calculated between the manual and automatic segmentations for each patient to determine the degree of overlap. The concordance correlation coefficient (CCC) was calculated between automatic and manual segmentation volumes across the whole data set. Across the 10 patients, an average (± standard deviation) Dice coefficient of 0.81±0.04 was observed, indicating good spatial agreement between the manual and automatic segmentations. The CCC between the FGT volume from manual and automated segmentation was 0.89, demonstrating high correlation in volume estimates between the two methods. Fuzzy c-means clustering was determined to be an effective and efficient method of FGT segmentation in breast MRI data. Future work will evaluate the application of this technique in assessment of background parenchymal enhancement, a clinical marker of cancer risk.

One of the most common causes of death in people with the genetic disease Cystic fibrosis (CF) is lung infection by the bacterium Pseudomonas aeruginosa (Pa). Despite aggressive treatment, Pa infections persist for years to decades. One factor that could contribute to poor antibiotic responses is drug antagonism: when one drug reduces the efficacy of another drug when drugs are used in combination. Tobramycin (Tob), an antibiotic, is commonly administered to CF patients to decrease Pa density in the lungs. Azithromycin (Azm), an anti-inflammatory drug, is frequently administered to the same patients. Clinical observations suggest that the clinical efficacy of Tob is reduced in some patients co-prescribed Azm. These observations led us to hypothesize that subjects exhibiting poor clinical responses when co-prescribed Tob and Azm are infected by Pa strains exhibiting greater antagonism than subjects that have good clinical responses to combined treatment. I refined an assay to measure Tob and Azm antagonism by growing a laboratory strain of Pa (PAO1) on plates with varying concentrations of Azm and Tob, and found that PAO1 was able to grow on higher Tob concentrations in the presence of Azm than in its absence. This work demonstrates that measuring antagonism is feasible. I have also identified twelve candidate subjects with banked Pa isolates who exhibited good and poor clinical responses when co-prescribed Tob and Azm. Work is underway to measure Tob-Azm antagonism in these isolates. My preliminary work on isolates from one subject showed a similar degree of antagonism as found in PAO1. Findings from this study could lead to changes in antibiotic therapies used to treat CF and help gain a better understanding of antibiotic resistance in chronic CF infections.

Misinformation is a major problem in today’s online information ecosystem. One way that platforms address this problem is by providing viewers with signals so they can assess the credibility of the content that they encounter. However, there are few existing signals on online video-sharing platforms, which is concerning as video platforms like YouTube are a common way for people to get information. We seek to understand how citations can be applied as credibility signals to videos on the video-sharing platform YouTube. First, in an interview study, we investigated how users interacted with existing credibility signals on YouTube, and found that video intent and context shaped how users would apply both existing signals as well as future citations. We used these findings to inform our design and implementation of a browser plug-in that allows users to create and view citations on all videos they see on YouTube. We now want to explore how users might use this system to apply citations on YouTube and how viewing citations on a video might impact user behavior. In this second study, we plan to observe how the system affects the user's perception of video credibility and the effectiveness of our system as a credibility signal. 

With the exponential growth of data that is used and stored in our world, new forms of data storage will be required as the capabilities of our existing electronics plateau. Synthetic DNA is an attractive medium for data storage due to its density and longevity. With the growth of DNA data storage technology, there comes the need for exploring DNA computation. The potential to form boolean circuits and neural networks has already been actualized using DNA hybridization and strand displacement circuitry. However, in order to use DNA based neural networks to solve larger computational problems, we must improve current circuit designs to become more robust and scalable. In prior works, all DNA species are in a single test tube; the avoidance of cross-interaction from different circuit components is achieved by designing orthogonal DNA sequences. However, because the number of orthogonal DNA species is limited, the size of the DNA neural network is constrained to be quite small. In order to solve these issues, we modularized the circuit using magnetic beads. Modularizing the design not only makes the circuit simple and robust, but it allows for automation using droplet-based microfluidic technology. In this work, we implement a modularized (droplet-based) digital Binarized Neural Network (BNN). We first confirmed that a single binarized neuron functioned as expected by measuring output fluorescence. Next, we implemented a single layer with 5-input neurons to confirm the functionality of the layer. Then, demonstrated the ability to cascade multiple layers by using the outputs of preceding layers as the inputs of subsequent layers. Finally, we automated the BNN on the Opentrons OT-2 robot. Using microfluidic technology we automated the experimental protocol, which is normally performed manually in a wetlab, and by doing so, we are one step closer to building a practical DNA-based computer system.

For over 40 years, various biological activities, like gene regulation, have been tracked by protein reporter systems. However, the number of uniquely addressable protein reporters that can be used together is limited due to their overlapping readout signal. This prevents simultaneous measurement of multiple reporters (multiplexing), which not only impacts scalability and convenience, but also the potential complexity of the system of interest. To overcome this problem, we have previously designed a new class of reporter proteins, Nanopore-addressable protein Tags Engineered as Reporters. These are more scalable and multiplexable than traditional reporter strategies and are read out on a commercial nanopore array. They are detected and distinguished based on their peptide barcode regions which yield distinct ionic current blockades as they dwell within the nanopore sensitive region. Here, we optimize this system for mammalian cell systems, investigate phosphorylation motif-barcodes, and analyze new random and designed barcode sequences. We demonstrate this system in human embryonic kidney 293 cells transfected with differentially barcoded genetic circuits. We aim to utilize this novel reporter system to investigate complex mammalian processes such as chromatin regulation dynamics and the determination of cellular phenotypes using customized reporter cassettes. Ultimately, our technology will increase the scale and complexity at which systems such as these can be studied, leading to deeper understanding of biological programming and thus more robust synthetic gene circuit development.

With the shift towards renewable energy and the promising performance that has been shown by organic-inorganic halide perovskite thin films to harvest solar energy, extensive research efforts have been devoted to further enhancing perovskite solar cell performance. To bring the power conversion efficiency of perovskite solar cells closer to the Shockley-Queisser limit, a high-quality perovskite film with fewer defects is desired. Antisolvent-assisted crystallization is a good way to get compact and homogeneous perovskite films with less defect density. Past studies have demonstrated that additive may be used in both the antisolvent and as a post-treatment to fine-tune perovskite crystallization and passivate defects at grain boundaries or at the surface. Here, we study the influence of multiple guanidinium molecules on the optoelectronic property of wide bandgap perovskite films by using a combination of steady-state and time-resolved photoluminescence (PL). In our testing, we have seen a significant increase in PL emission and PL lifetime of guanidinium molecule treated perovskites, qualitatively indicating that perovskite films with lower defect density is obtained. X-ray diffraction (XRD) and atomic force microscopy (AFM) are used to investigate the effect of these molecules on the crystallinity of wide bandgap perovskite films. From these we confirmed the ability of the tested guanidinium molecules in reducing the defect density of halide perovskite films via antisolvent-assisted crystallization method. This understanding would help us to further push the efficiency of perovskite solar cells and ultimately reach a full carbon-neutral environment.

While millions of Americans have been diagnosed with Attention-Deficit Hyperactivity Disorder (ADHD), many undiagnosed individuals suffer from at least one of ADHD’s symptoms. Symptoms such as poor attention spans, lack of attention to detail, loss of focus, and many more can affect anyone’s life—in the workplace, at school, and during social engagements. This project seeks to explore how technology usage affects the development and existence of attention-deficit behaviors. We want to focus on specific technological platforms and explore any possible influence on attention-deficit behaviors. To do this, we are utilizing a mixed methods approach of case studies and surveys to evaluate the presence of attention-deficit behaviors, frequency and methods of technology usage, and relationships between the two. Using surveys and psychological scales of measurement for ADHD, we can gather a holistic understanding of how the general population uses technology and how attention-deficit behaviors present themselves. Our case studies reinforce information gathered from these surveys and provide more detailed data to enable a comprehensive analysis. We predict that high volumes of technology usage, especially within certain platforms, can encourage the development of attention-deficit behaviors and exacerbate existing issues with attention. If we find this to be true, our results can guide the design and delivery of future informational content within education institutions and workplaces. These results can also encourage a re-evaluation of technology usage to reduce attention deficient behaviors.