Accurately describing a child’s language skills is difficult, but identifying children with atypical language development adds even more complexity. In an ordinary language assessment session, a Speech-Language Pathologist (SLP) will use both standardized, norm-referenced assessments and non-standardized assessments, like Language Sample Analysis (LSA). However, there is little research about how these different assessments relate to one another. To better understand this relationship, the language abilities of children (n=38) were assessed after turning 6-years-old and attending Kindergarten by SLPs using the following norm-referenced tests: a sound-in-words subtest from the Goldman-Fristoe Test of Articulation, 3rd Ed. (GFTA-3); core language subtests from the Clinical Evaluation of Language Fundamentals, 5th Ed. (CELF-5); and a nonverbal IQ subtest from the Kaufman Brief Intelligence Test, 2nd Ed. (KBIT-2). Then, a 10- to 20-minute language sample of the child’s spontaneous speech was collected for analysis. This project extends from previous research by including participants beyond clinical populations and using multiple sampling contexts to holistically capture the child’s naturalistic speech. I transcribed each language sample with Codes for Human Analysis of Transcripts (CHAT) and utilized Computerized Language Analysis (CLAN) software to automatically compute measures reflecting language skills from the language samples. I will conduct correlational analyses to inspect the associations between measures from norm-referenced tests and measures extracted from language samples. I expect to see significantly positive correlations between several CELF-5 measures and LSA measures of morphosyntactic development (i.e., grammar) that demonstrate a convergence between these two methods of assessment. Correlations between LSA measures and GFTA-3 measures are expected as well but to a lesser degree of association because they do not index identical elements of language. Overall, relationships discovered during this process will lend themselves to further understanding the information we gain from these common tools of language assessment.

Dense-core vesicles are membrane-bound structures that carry neuromodulators such as insulin, dopamine, and serotonin. The peptides within dense-core vesicles are initially larger precursor proteins that undergo enzymatic processing to achieve their functional forms. During the defecation motor program in Caenorhabditis elegans, dense-core vesicles released from the intestine harbor neuropeptides that trigger neurons which activate enteric muscles, promoting the act of defecation. Failure of certain proneuropeptides to mature into neuropeptides results in decreased frequency of defecations. CPD-1, a conserved transmembrane carboxypeptidase, is a poorly understood processing enzyme that affects the defecation motor program. I built on our knowledge of EGL-21, another carboxypeptidase known to process neuropeptides and peptide hormones, to better understand CPD-1’s function. I show here that these two carboxypeptidases, EGL-21 and CPD-1, process neuropeptides necessary for successful defecation patterns. Mutants lacking egl-21 had decreased defecation frequency while worms lacking both egl-21 and cpd-1 had an even lower defecation frequency. Additionally, my results show that CPD-1 is expressed in intestinal cells and can compensate for EGL-21’s function. Finally, I am conducting experiments to determine whether one of CPD-1’s targets is NLP-40, an important neuro-like peptide released from the intestine that regulates defecation. These results contribute to our broader knowledge of peptide processing in dense-core vesicles.

Stiffness measures derived from MR Elastography have shown value in guiding treatment decisions and monitoring effectiveness of therapies for liver disease but it requires extra hardware, longer scan duration and is susceptible to motion and breathing artifacts. Recent studies have revealed a strong linear correlation between water diffusion and tissue stiffness, demonstrating that Diffusion Weighted MRI (DWI) can be used to estimate stiffness values in liver tissue. DWI-derived stiffness values may help evaluate treatment-induced changes in breast cancer but to our knowledge, this has not yet been tested. The purpose of my ongoing study is to calibrate DWI estimates of tissue stiffness for the breast by optimizing DWI parameters (diffusion weightings, or ‘b-values’) and  calibration coefficients (a, b), evaluating the potential of stiffness measures for monitoring response to neoadjuvant chemotherapy (NAC) in breast cancer. We collected baseline and early treatment MRI exams from 25 patients undergoing NAC in this IRB approved study along with their treatment outcomes based on pathologic response post completion of NAC. I evaluated  the stiffness values obtained from different b-value pairs (low b-values: 100/200; high b-values: 800,1500,2000 s/mm²) and calibration coefficients(a,b=-9.7,13.9:-10.8,17.5:-8.8,21.2) and compared it to the invasive breast cancer stiffness values reported in literature. I also evaluated the performance of the optimized parameters to predict treatment response. The optimal b-value pairing (b=200,1500s/mm²) and coefficients a=-9.7,b=13.9 produced stiffness values consistent with literature. Using this approach, the performance for predicting treatment outcomes between responder and non-responder groups was AUC=0.84. These preliminary findings suggest that DWI based virtual elastography could serve as a non-invasive tool to assess tumor stiffness and track treatment efficacy, potentially improving breast cancer management.

Electrochemical water splitting is an effective method for generating hydrogen gas (H2) and an attractive means for energy storage. During this process, hydrogen and oxygen bubbles form on the electrode surfaces often lower the efficiency of gas production. The overarching goal of this study is to probe and better understand the nucleation process of small H2 and O2 nanobubbles on the electrode. To do this, we use ultrasensitive fluorescence microscopy to monitor the transient adsorption and desorption of single fluorophore molecules, such as Rhodamine 6G (R6G), on the nanobubble surface. My project aims to study how different fluorophores interact differently with the bubble surface and how they may interact with each other when multiple fluorophores are co-adsorbed on the bubble surface. This research may help us better understand bubble-molecule and molecule-molecule interactions at confined spaces for enhanced chemical labeling of the nanobubble surface. Moreover, it may also help us better understand the chemical nature of the gas/water interface, which has direct implications for more efficient gas productions and energy conversion and storage.

Maintaining the integrity of genetic material and preventing changes over time is essential for normal cellular function. This genomic stability is directly affected by the DNA replication process. Replication must be both accurate and efficient; mutations that affect DNA replication can cause genomic instability and changes in the genetic makeup of the cell. Through a genomic instability screen in mice, researchers discovered a single base pair mutation in a highly conserved gene required for unwinding DNA during DNA replication. The presence of this single base pair substitution, called Chaos3, in both copies of the gene causes female mice to develop mammary tumors. We have found that in the yeast Saccharomyces cerevisiae, the corresponding Chaos3 mutation decreases activation or “firing” of some replication origins—the sites where DNA replication begins. Chaos3 does not affect all early firing origins in the genome; rather, origins near centromeres are specifically affected, thereby delaying replication of those centromeres, causing chromosome loss. We found that when an affected origin is replaced with an unaffected one, firing levels are restored to wild type function and that chromosome loss is rescued. To further understand what components are essential for timely DNA replication, and why only a subset of origin sequences are sensitive to the Chaos3 allele, I am focusing on the origin sequences directly. I am mutating the origin sequence itself and separately deleting different genes whose products have potential interactions with origin sequences. My research aims to advance the understanding of the role these genes play in the activation of origins for timely DNA replication and how the Chaos3 mutation may be interrupting normal function of these processes. This knowledge can help identify key molecular mechanisms that drive cancer development in higher eukaryotes.

Copy number variation (CNV) is associated with genetic disorders in humans. One particular kind of CNV is a gene triplication in which the central copy is inverted. How such structures arise is poorly understood but is of great interest because of their association with cancer and other genetic disorders. We find similar amplified structures in budding yeast Saccharomyces cerevisiae, and therefore, we can use yeast to understand the mechanism that generates them. The Brewer and Dunham labs have proposed Origin Dependent Inverted Repeat Amplification (ODIRA) as a model that explains inverted CNVs. To understand which proteins/enzymes contribute to amplification, we are implementing gene deletions to observe the effect on the production of these ODIRA amplification events. ODIRA events are rare and thus large sample sizes are required to detect them. To streamline their identification, I am developing a system that uses color as a visual indicator of CNV. When a single copy of the bacterial gene, VioA, is expressed in yeast it produces light purple colonies; in multiple copies, the colonies are a darker shade of purple. I am inserting a single copy of the VioA gene into a region of the yeast genome that undergoes inverted triplication events. Simply scanning plates for dark purple colonies will enable me to screen for ODIRA events quickly and measure their frequency. Using this visual indicator will allow me to rapidly screen different yeast mutants and determine the role they play in the ODIRA amplification mechanism.

Gene arrangements are observed in human diseases such as cancer and developmental disorders. In developmental disease, gene triplication with an inverted central copy is observed, while a hallmark of cancer are palindromes, or inverted repeats of DNA. Therefore, testing one mechanism of gene arrangement in an easily studied organism like the  budding yeast Saccharomyces cerevisiae may shed some light on the human genome and disease generation. Yeast cells grown for >200 generations in sulfate limiting media are enriched for triplication of the high affinity sulfate transporter SUL1 with the center copy inverted, as amplification confers a selective advantage. To explain how such a triplication occurs, the Brewer and Dunham Labs proposed a model called Origin Dependent Inverted-Repeat Amplification (ODIRA). The ODIRA mechanism requires a DNA origin of replication and short, inverted repeats flanking the SUL1 gene. During DNA replication, an error of the replication fork, or fork regression, causes annealing of leading and lagging strands to create a hairpin intermediate. The intermediate then replicates and recombines into the genome, forming interstitial triplications, with the middle copy inverted. While the proposed mechanism explains the observed triplication in yeast, the specific proteins involved are not yet known. The genes I've chosen to test are the DNA helicases MPH1 which prevents cross-over between ectopic sequences, and RRM3 which relieves replication fork pauses. Both are predicted to regulate necessary steps of the ODIRA mechanism, making them good candidates for genes that may be involved in these triplications. By deleting each gene, I can then measure the frequency of ODIRA events in those strains and compare them to wild-type strains. Increased ODIRA events in the knockout strains may implicate their role in the ODIRA mechanism and prompt further study of these genes and how they might affect copy number variation in humans.

Cortical tracking, a method that examines how neural activity encodes the dynamic features of the incoming speech stimuli, allows for the study of naturally produced continuous speech. Successful encoding of acoustic features is fundamental for language processing and comprehension. Studies show that cortical tracking of at least some acoustic speech features is already robust in the first year of life. However, it is unclear whether bilingual infants exhibit enhanced cortical tracking of non-native languages compared to monolingual infants, consistent with the idea of having a "bilingual advantage" as suggested in prior research. To investigate this, we recorded neural responses from 11-month-old English learning monolinguals, English-Mandarin learning bilinguals, and two mature comparison groups of English monolingual and English-Mandarin bilingual adults, while they listen to naturally produced, continuous, infant directed speech using electroencephalography (EEG) in three conditions: English, Mandarin, and Vietnamese. Stimuli were presented at an overall level of 70 dB SPL in a sound-attenuated booth. Using a combination of machine learning and linear modeling (i.e., Multivariate Temporal Response Function approach), we analyze the EEG signals using a multivariate encoding model consisting of acoustic features including envelope, envelope derivative, word onset, and phoneme onset. We hypothesize that both bilingual adults and infants will exhibit enhanced encoding of acoustic features in Vietnamese compared to monolingual adults and infants, indicating bilingual advantage in processing a third language. Additionally, we anticipate the bilingual advantage to be more prominent in infants than adults. These findings will contribute to the understanding of how bilingualism influences neural encoding across different languages and provide neural evidence of bilingual advantage in processing and acquiring a third language. I participated in study design, recruitment, data acquisition and analysis.

Adaptive algorithms used in brain-computer interfaces (BCIs) adjust to user strategies by dynamically adjusting how BCIs decode neural data throughout an experiment. Current adaptive algorithms continuously update the decoder using all available data during training. However, if users are unfocused or inattentive, it is likely that some of the training data is unhelpful towards decoder training and could lead to poor decoder performance. Unfortunately, determining attentiveness in a subject is difficult. Non-human animals cannot self-report attention levels, and even in human trials, self-reporting often leads to subjective data that varies between subjects. A non-invasive estimate of subject attentiveness could improve data selection for decoder training. Pupil size is correlated with a participant’s perception of task difficulty, and participants involved in attention-grabbing tasks display blinking rate-inhibition (Kucewicz et al., 2018; Maffei et al., 2019). I hypothesize that these eye data could be used to estimate a subject’s task engagement. I explored data from a novel task where both human and non-human primate subjects controlled a cursor on a 2D screen with 3D hand motions through some unknown mapping. Due to the unknown 3D-to-2D mapping, this task required constant cognitive attention in order for subjects to succeed. I looked at the subjects’ data to identify trends in pupil size and blink frequency across multiple days of task performance. In the future, I aim to build engagement classification models to better select training data for adaptive algorithms and apply these algorithms to realtime BCI experiments.

In spring of 2023, the United States Surgeon General Dr. Vivek Murthy published an alarming report about the impacts of loneliness in America, significantly labeling loneliness as an “epidemic” of fatal impact. As a mitigation technique, Dr. Murthy advised a national response of several steps, with the first one being to improve existing local social infrastructure, such as libraries and parks. To better understand how this mitigation technique can help reduce loneliness rates, my research aims to ask: Is the number of social infrastructures in a neighborhood predictive of loneliness in vulnerable populations in Seattle? To answer this question, I am composing a composite loneliness index scale based on 13 vital social factors, measured in the U.S. Census Bureau’s American Community Survey, which have been shown to be predictive of loneliness. I am then mapping each Seattle census tract’s loneliness categorical rating, as well as libraries (from a Seattle Public Library dataset) and parks (from a Seattle Parks and Recreation dataset) to understand whether proximity to these social infrastructures can predict a lower score on this new scale. The broader aim of this project is to assess the spatial relationship of social infrastructure and loneliness in a major city so that public officials can identify vulnerable locations where social infrastructure is needed to address this epidemic. Ultimately, my goal is for this project to be replicated in other major cities so that other city governments can identify the geographies that are more prone to loneliness in their city and enact appropriate mitigation responses.

This research aims to address the lack of qualitative inquiry into the lived effects of banishment zones to address street sex work in urban criminalized contexts. Sex work is highly stigmatized, with stigma being the primary driver of discrimination, poor health, and harm to mental health for sex workers (Bateman, 2021; Lazarus et al., 2012; Armstrong, 2019). Relatedly, spatial exclusion through banishment zones renders the lives of the most vulnerable more precarious, also harming mental well-being (Becket and Herbert, 2010). The Seattle City Council recently reintroduced legislation to create a Stay Out of Areas of Prostitution (SOAP) zone in Seattle, WA along Aurora Avenue as a punitive measure to curb street prostitution occurring in public spaces. If buyers of sex, pimps, or street sex workers enter this 60-block zone, they can be arrested for violating a SOAP order and face incarceration for up to a year, and fined up to $5,000. Although the legislation seeks to target the buyers and solicitors of the sale of sex, the “end demand” approach perpetuates harm, conspiring that “immodest” women are the cause of social ills (Bateman, 2021). This study proposes a qualitative research design employing semi-structured interviews with community members involved with organizations supporting Seattle’s street sex workers to explore how the reintroduction of the SOAP legislation is felt by the affected sex workers. The proposed research seeks to fill the existing gap in understanding the confluence of spatial exclusion and street sex work within a criminalized context like Seattle, WA. 

This project explores the geography of social dance spaces (such as nightclubs) and their geographic and social responses to gentrification. Social dance spaces serve as critical sites for empowerment, self-expression, and the embodiment of identity, particularly for systematically marginalized communities, including queer and BIPOC individuals. By exploring the spatial distribution and socio-cultural significance of these venues, this research seeks to contextualize how these spaces contribute to and are affected by the gentrification and neighborhood change since the turn of the century. Through a combination of historical contextualization and qualitative interviews, the study emphasizes how life surrounding the outside of the gathering spaces, shapes the life inside these spaces. This methodology will not only showcase the physical geography of the locations in response to changes in the city over time, but also the internal meanings assigned to the spaces while these changes are happening. By looking at both the internal and external geography of these gathering spaces through ethnographic analysis, I will be able to induce information on how this approach reveals the ways in which the geographies of dance spaces both reflect and challenge dominant urban narratives, highlighting their role as counter-hegemonic sites of resistance and identity formation. By situating these venues within their broader historical and geographic context, the research provides insight into how urban spaces intersect with narratives of inclusion, power, and community belonging.

Many scholars have examined Ancient Rome’s reliance on enslaved labor and many more have investigated the inner workings of the cura annonae (“care of the grain supply”), the state-funded welfare program which provided free wheat to citizens under a certain income level. However, few have studied the foundation role that enslaved and other exploited labor played in the administration of the cura annonae. In this paper, I describe the history of the Ancient Roman food supply, the origins of the cura annonae, and its complex logistics. I outline the steps of the supply chain: the wheat plantations, grain ships, ports, mills, distribution, and bureaucratic administration. Using primary sources, archeological evidence, and scholarly theories, I focus on the instances of labor exploitation within the system. By applying world system theory and dependency theory to the institution of the cura annonae, I show how modern sociological and economic theories can enhance our understanding of the ancient world.

Greater than 70% of the volcanism on Earth occurs along mid-ocean ridge spreading centers and plays a significant role in cycling elements into and out of the seafloor due to hydrothermal circulation. My study investigated how temperature and chlorinity/conductivity were changing in two submarine hot springs (hydrothermal vents) from September 12, 2023 – January 7, 2025, with linkages to earthquake activity. I chose this time interval due to heightened seismic activity and inflation of the volcano in recent time indicating an impending eruption at Axial Seamount is likely within a year. These data inform the underlying plumbing system and were utilized to test the hypothesis that the plumbing systems of two ~350°C hydrothermal vents (Escargot and Diva) are not interconnected in the shallow subsurface. Data utilized were from the Ocean Observatories Initiative – Regional Cabled Array (OOI-RCA) underwater observatory and Axial Seamount Earthquake Catalog. These allowed for examination of phase separation and perturbations occurring in each vent. The RCA Instruments utilized were two sensors that stream live temperature and resistivity (converted to chlorinity/conductivity) measurements from the volcano 300 miles offshore. These data, in addition to pressure data from a Bottom Pressure-Tilt sensor (BOTPT) and the Axial Seamount Earthquake catalog are being analyzed with Python to correlate earthquakes to temperature and chlorinity/conductivity and examine lunar-driven tides. Five statistically significant perturbations/events were documented and analyzed. Findings from an additional perturbation showed the occurrence of possible brine release from the subseafloor due to heightened inflation from the magma chamber. This work helped inform on process linkages leading up to an eruption and the sequestration of subsurface brines and their possible release post eruption into the overlying ocean with impacts on novel brine and metal tolerant organisms in these extreme environments. 

The ecosystem of microbes found in the gut, or the gut microbiota, plays a vital role in host health, influencing the immune, digestive, and central nervous systems. Research suggests that the microbiome may be linked with the development of neuropsychiatric disorders, presenting the possibility that altering the microbiome could influence the risk of these conditions. Recent research has explored this link within the context of Parkinson’s Disease (PD), a neurodegenerative disorder primarily known for its effects on motor control. PD patients often suffer from chronic constipation for years prior to diagnosis. Although the mechanisms of this gut-brain relationship are still unknown, many studies have highlighted the potential involvement of the gut microbiome in the development of PD. I explored the specifics of this relationship by developing a metabolic model trained on metagenomic data from PD case-control studies, using a microbial community-scale metabolic modeling (MCMM) approach. MCMMs may provide detailed mechanistic insights into the gut-associated etiology of PD, potentially allowing for the development of preventative therapies that prevent the onset of PD, which could revolutionize our current system of retroactive treatment of the established disease.

The Thermal imaging-based Temperature After Within-limb Calibration (TAWiC) algorithm has been used and validated by our team in detection of arthritis in the knees of children. It has previously performed well through using a smart-phone FLIR thermal camera attachment. We are now hoping to explore and expand its potential by developing TAWic thresholds to find other inflammatory arthritis in the knee, ankle/subtalar, elbow and wrist joints. Patients 4 years or older with suspected active inflammatory arthritis in at least one knee, ankle/subtalar, elbow or wrist were enrolled at Harborview Medical Center or Seattle Children’s Hospital after consent was obtained. Joint exams were conducted and infrared thermal imaging was obtained through the use of a FLIR One Pro camera by doctors. I analyzed images in MATLAB by manually selecting elbow, wrists, knees, and ankle joints to generate reports and scores for virtual doctor evaluation. With 89 adults and 85 children enrolled, we found the most commonly affected joints in children to be knees while in adults, it was the wrists. Further validation of applying the TAWiC threshold to detect arthritis was conducted, and the sensitivity and specificity of this algorithm for adults with active inflammatory arthritis in the knees were 50% and 83%, respectively. To our knowledge, this is the first reported validation of the TAWiC algorithm for knee inflammatory arthritis in adults. Ongoing and future studies will seek to validate use of the TAWiC algorithm for assessing arthritis in other joints. We hope that in the future, the technology can be used remotely by patients in telehealth efforts to send imaging to minimize costs, increase efficiency, and save time in caregiving efforts.

Chronic Recurrent Multifocal Osteomyelitis (CRMO), is an autoinflammatory bone disorder that is notable by the recurrent bone lesions with potential long-term complications that include growth impairment in pediatric patients. Growth impairment can be illustrated through z-scores for weight and height. Z-scores represent how far a patient’s weight and height measurements deviate from the average for their age and sex. Z-scores below -1 and -2 could indicate the negative disturbance by CRMO or inadequate treatment. Standard second-line treatments for CRMO include bisphosphonates, disease-modifying antirheumatic drugs (DMARDs), and tumor necrosis factor inhibitors (TNFi). Bisphosphonates are frequently prescribed pediatric medications for their ability to improve bone health and reduce inflammation. However, the impact of these medications – alone or in combination with DMARDs and TNFis – on growth patterns are understudied. Medication practices may demonstrate varying results on height and weight outcomes in CRMO patients. CHOIR included prospective longitudinal data from >500 patients from multiple sites across continents, which allows us to compare the effects of these treatment regimens on the change of Z-score. We expect that the proportion of patients with low Z-scores is similar across all groups before the treatments. By gathering patients based on treatment regimen, this review will compare the prevalence of lower z-scores. Understanding these correlations is vital for identifying whether certain treatments contribute to growth improvement, offering insights into optimizing care for CRMO patients.

The humble toilet, whose sole function is to transport waste away from us, is a machine. This is how the U.S. government wants us to view immigrants right now, as human waste to be discarded. Not as individuals with loved ones, or stories, or a heartbeat. The machine that facilitates these unruly acts of human departure, has a name: Immigration and Customs Enforcement. ICE frames this act of hate as “disposing of the bad guys”. There has been a massive increase of individuals being deported without even so much as due process of law. ICE is a machine that acts as the judge, the jury, and the executioner. Mahmoud Khalil, a student with legal green card status, was detained in March and deported to a prison out of state and away from his legal team. Mahmoud was not given any trial before being unlawfully imprisoned, just flushed away. Mahmoud and his case are well known, but there are more cases like his every day. As you read this, the federal government is attacking UW’s own international students regarding the legality of their visas, making their current legal standing unclear. My painting aims to protest against these governmental threats and acts of terrorism. The toilet, a disarming appliance that everyone in this audience will be familiar with, is here reframed. Who decides what is waste? Who gets to pull the chain? Can we stop them? While the deeper message of my painting might not be obvious at first glance, I hope that the alien and inhuman shape will captivate individuals enough to read my statement and to learn that this toilet is not just a toilet. What can we do about this inhuman machine?

Nitrogen is often a limiting resource in marine ecosystems, and its availability is heavily influenced by human activities, sometimes causing eutrophication. The study of phytoplankton metabolism under nitrogen-limited and replete conditions is of interest due to eutrophication's ecological and economic implications and the prevalence of nitrogen limitation on marine primary productivity. To investigate the metabolic effects of rapid nitrogen addition on phytoplankton metabolism, 15N-nitrate was traced into polymerized and free amino acids in two treatments of the microalgae Tisochrysis lutea with either initially limiting or replete nitrate concentrations. Using acid digestion, derivatization, and GCMS analysis we found that the culture with a lower initial nitrate concentration incorporated more 15N into alanine, valine, serine, and threonine. This suggests that phytoplankton under nitrogen-limited conditions exhibit greater increases in metabolism than those under replete conditions following rapid nitrogen influxes. Heavy nitrogen incorporation into other metabolites was also detected. This work provides a foundational method for future studies into phytoplankton metabolism under varying environmental conditions.

There is a crucial need for a vaccine that produces a robust immune response against Human Immunodeficiency Virus (HIV), particularly for those without access to effective treatments. We investigated the immunogenicity of a novel self-amplifying RNA (RepRNA) vaccine for HIV in non-human primates (NHPs). RepRNA vaccines encode subgenomic sequences that enable the self-amplification of additional copies of RNA, inducing strong immune responses with lower doses of RNA. The repRNA was formulated with a lipid nanocarrier called LION (HDT Bio), which protects the RNA from degradation and enables its delivery into the cell. This platform has shown success in a licensed SARS-CoV-2 vaccine, suggesting it may be similarly promising as an HIV vaccine. I aim to evaluate whether the RepRNA/LION vaccine can elicit robust systemic and mucosal responses in NHPs. I hypothesized that the vaccine would increase HIV-specific T-cell responses in PBMCs and induce HIV Env-specific antibody production in nasal and rectal secretions. To investigate the immunogenicity of this vaccine, we vaccinated twelve cynomolgus macaques, divided into three groups, with HIV Env and/or HIV Gag-Env. To determine vaccine efficacy, I measured the frequency of antigen-specific T-cells in blood using interferon-gamma (IFN-γ) Enzyme-Linked ImmunoSpot (ELISpot) assays because activated T-cells secreting IFN-γ help eliminate infected cells. I also assessed HIV Env-specific Immunoglobulin A (IgA) levels in nasal and rectal secretions using Enzyme-Linked Immunosorbent Assays (ELISAs) because IgA is key in neutralizing pathogens at mucosal surfaces. My preliminary results show an increase in IFN-γ production after the first vaccination, which indicates a systemic antigen-specific T-cell response. We will continue to run assays to see if further vaccination doses can induce more robust immune responses. Results from this study indicate that the RepRNA/LION HIV vaccine may be a promising approach to induce mucosal and systemic immune responses against HIV.

Tetralogy of Fallot (TOF) is the most common cyanotic congenital heart defect and consists of four structural defects that prevent babies’ hearts from delivering oxygenated blood to their body. When life saving surgeries correct these defects, the resulting scar changes the way the heart conducts electrical impulses, causing abnormal heart beats later in life. These abnormal heart beats, arrhythmias, often present as sudden cardiac arrest. Due to the high risk of arrhythmias in patients with repaired TOF, it is clinically important to understand the exact mechanisms causing them. These mechanisms provide insight that is essential to developing personalized methods for preventing arrhythmias. In our lab, we use late gadolinium enhanced MRI scans from TOF patients to create personalized computational models of their heart and particular scar distribution. We then attempt to induce arrhythmias in our models, which are individualized and represent subcellular and cell-scale electrophysiological phenomena. These models are useful because they allow us to study arrhythmia mechanisms noninvasively. We expect that patients whose computational models are susceptible to arrhythmias will also be more likely to experience arrhythmias in real life. We also aim to use the mechanistic insights from these simulations to determine new ways of predicting arrhythmia risk in this vulnerable patient population. Our results should predict what subset of patients would benefit from invasive preventative procedures, and help give patients with TOF a better understanding of their personal risk with or without those procedures. We hope to use our methods and results to create a simple and accessible arrhythmia risk stratification tool.

Auditory input, such as infant directed speech and music, is integral to childhood language development. However, existing research focuses primarily on examining monolingual English-speaking families, overlooking families of other cultures and languages. Hence in this study, I investigate the naturalistic auditory home environments of Latino and Hispanic infants in comparison with Pacific Northwest monolingual English speaking infants to better understand the differences in auditory exposure. This study uses audio data obtained from daylong recordings of Latino and Hispanic infants' home environments utilizing the Language Environment Analysis (LENA) technology. Infants wear the LENA recorder in a vest for up to 16 hours per day. The selection requirement for Latino/Hispanic infants is that at least one parent identifies as being of Latino or Hispanic origin. I randomly sample short snippets of recordings and upload them to Zooniverse, an online citizen science research platform, which allows volunteers to annotate for types of sounds (music or speech), its source (in-person or electronic), and target audience (infant-directed or not). I quantify the types of auditory input to compare it with an existing study of Pacific Northwest monolingual English infants to uncover differences and understand the impact that culture has on infants' language input and ultimately development.

A factor influencing the ability to tune into a single speaker in the presence of competing speech is speech rhythm. The Selective Entrainment Hypothesis suggests that attention fluctuates periodically and synchronizes with speech, a quasi-periodic stimulus. This synchronization allows the brain to predict when the most salient parts of speech will occur and direct attention towards those moments. According to the hypothesis, more rhythmic speech should be easier to synchronize with, as it is more predictable. This hypothesis has been supported by previous behavioral research, which found that altering the rhythm in the target speech stream decreased comprehension of the target speech, while rhythm distortion in the background improved comprehension, likely because it became a weaker competitor. The present study replicated and extended these findings by recording electroencephalographic (EEG) data from listeners (N = 20) to measure phase locking, or synchronization, between the target speech envelope and neural activities. I ran EEG sessions, which began by exposing participants to the target speaker’s voice on its own. Participants then listened to 300 sentence pairs, which I created by playing a sentence spoken by the background speaker and sentence from the target speaker simultaneously. The sentence pairs were divided into three rhythm alteration conditions: target-altered, background-altered, and neither-altered. After each trial the participants answered a multiple choice comprehension question to collect behavioral data. Using EEG allowed for a more direct measurement of synchronization compared to behavioral results alone. We test the hypothesis that in the conditions there will be the strongest phase locking in the background-altered condition, followed by the neither-altered, and worst in the target-altered condition, a pattern that mirrors the behavioral results. This will provide more insight into the role of rhythm in speech processing and has potential future implications for hearing aid development. 

We explore the Earth in order to discover and understand the ecosystems present on it. Representing 70% of the surface of the globe, the oceans are arguably the place we struggle the most to explore due to their size and depth (we know more about space than we do about our oceans). Dissolved organic compounds, produced by diverse marine organisms for a wide variety of reasons, are present in very low concentration in the oceans. This research was done in order to develop, design, and ameliorate existing techniques to detect and analyze dissolved organic compounds (amino acid in this case) present in seawater. Cation exchange chromatography, derivatization and gas chromatography mass spectrometry were used. The results were not as expected but the methodology is very promising. With some ameliorations, that methodology will be able to help us detect and analyze known and unknown particles at very low concentration in our vast oceans.

The opioid epidemic remains a critical public health crisis, with opioid use disorder (OUD) affecting millions worldwide. Research indicates significant sex differences in addiction patterns, with women exhibiting faster addiction progression, heightened cravings, and increased relapse rates compared to men. However, the biological mechanisms underlying these differences remain poorly understood. This study aims to investigate how chronic heroin use and withdrawal impact gonadal hormone levels in male and female rats, shedding light onto the role of opioid addiction on hormonal regulation. Using a 20-day heroin treatment followed by a 20-day withdrawal period, we examined changes in locomotor response, fluctuations in key gonadal hormones (testosterone, estradiol, and progesterone), and differences in brain activity patterns. Our preliminary data  suggest that females more consistently develop sensitization to heroin and also do so at an earlier time point compared to males. Our ongoing research is working to quantify serum hormone levels across heroin treatment, as well as developing a way to measure neural estradiol activity in real-time during sensitization. Future work will focus on the long-term effects of hormonal disruptions on brain signaling pathways and opioid receptor regulation, with the ultimate goal of informing sex-specific therapeutic interventions for individuals struggling with opioid addiction. Understanding these hormonal changes is crucial for developing more effective, personalized treatment strategies for OUD. By furthering the research on opioid addiction and endocrine function, this research highlights the need to consider sex as a biological variable in addiction studies.

Treatment-related cardiomyopathy is a significant cardiotoxic complication for cancer patients treated with chemotherapy or radiotherapy and a leading cause of premature morbidity in childhood cancer survivors. Predicting a patient’s cardiomyopathy risk could help clinicians intervene early but is not possible with standard echocardiogram analysis methods. Preliminary research at the CardSS lab demonstrated that a deep convolutional neural network has modest success at predicting a pediatric patient’s risk for developing CM but is significantly limited by insufficient pre-diagnosis data for training, impairing its ability to learn generalizable disease progression patterns. This research aims to develop a generative AI model that generates synthetic echocardiogram data for training to improve the prediction model’s ability to learn distinctive patterns representing cardiomyopathy risk. By training on a longitudinal dataset containing echocardiograms from several cardiomyopathy stages before diagnosis, we aim to produce synthetic echocardiograms conditioned on specific classes: 0-1 years before diagnosis, 1-3 years before diagnosis, cardiomyopathy present, and control. Thus far, I have preprocessed echocardiogram data and implemented three experimental diffusion model architectures to investigate how the addition of a cross-attention layer to the encoder, bottleneck, and decoder regions of the model affects its ability to produce echocardiograms of different classes. I also implemented an analysis pipeline that calculates the Fréchet Video Distance (FVD), Structural Similarity Index Measure (SSIM), and Peak Signal-to-Noise Ratio (PSNR) between two sets of echocardiograms, which provide measures of image/video similarity. Using this pipeline, I am evaluating two key standards for synthetic data—intraclass fidelity and interclass separability—to quantify each model’s ability to generate data that is (1) representative of its class and (2) distinct from data produced for another class, and how these metrics change as training progresses. Preliminary data has shown that these models are producing synthetic echocardiograms that closely resemble real echocardiograms, but inconsistently.

Reactive ion etching (RIE) is a critical nanofabrication technique used to pattern silicon substrates for various applications such as computer chips and biomedical devices. The process uses high-energy plasma and electromagnetic currents to direct free ions at a silicon substrate, causing chemical reactions that remove target material. One major challenge in RIE is maintaining etch depth and uniformity, particularly as the etch deepens, making it harder to direct ions precisely. The Bosch process addresses this issue by alternating etch and deposition steps in a cyclic manner, where a thin polymer film is deposited after each etch phase. This process is critical to industry, where it is commonly used to make MEMS devices such as accelerometers and medical sensors. In this project, we aimed to optimize the aspect ratio—the ratio of feature depth to feature width—of silicon substrates by fine-tuning various Bosch process parameters, including etch time, deposition time, pressure, gas flow, DC bias, and number of loops. We conducted etch processes on test substrates made using standard nanofabrication processes. Afterwards, we measured the quality and geometry of the etched features using a combination of metrology tools such as a microscope, contact profilometer, and reflectometer, along with scanning electron microscopy (SEM) for detailed analysis of feature sidewalls and trench angles. To efficiently explore the complex relationship between these parameters and their impact on the aspect ratio, we use JMP software to design a set of experiments. This tool enables us to systematically evaluate the effects of multiple variables and identify the optimal etch recipes for enhancing the aspect ratio. This research provides valuable insights into optimizing the Bosch process for broader applications, potentially enabling the fabrication of devices with unique features that would otherwise not be possible in our facility.

Infants and adults process fundamental sound attributes such as pitch, timbre, and loudness differently, but the underlying neural mechanisms that drive these differences remain unclear. Pitch is the perceptual attribute of sound that can be arranged from low to high as in a musical scale, while timbre differentiates sounds of the same pitch and loudness, such as different musical instruments. Timbre, related to the spectral distribution of frequencies, is perceived as brighter when high-frequency energy increases. In natural sounds, pitch and timbre often covary; for example, a flute’s sound is both high in pitch and bright in timbre. Our prior research showed that infants outperform adults without musical training in pitch discrimination in the presence of random brightness variations. One possible interpretation is that adults have learned the statistical covariation between pitch and brightness, leading to efficient coding but poorer performance when these expectations are violated. To investigate further, we recorded mismatch negativity (MMN)—a brain response to unexpected sound changes—using electroencephalography (EEG) in both 7-month-olds and adults. We measured responses to pitch changes in two conditions: 1) with random brightness variations and 2) without brightness variations. The results are consistent with our prior behavioral findings: infant MMN amplitudes were comparable in both conditions, whereas adult MMNs were larger without brightness variation. These results are consistent with our past behavioral findings and the interpretation that infants have not learned the statistical covariation between pitch and brightness, thus experiencing less interference when discriminating pitch in the presence of random brightness variation. This research offers insight into the differences between how the infant and adult brains process fundamental attributes of sound that are important for speech and music perception. My role in this project involved the acquisition of EEG data, data management, and dissemination of research findings.

Self-splicing domains, called inteins, are part of a class of selfish genetic elements that are present in highly conserved regions of unicellular eukaryotes and prokaryotes. Our research investigates the self-splicing behavior of two different algal inteins in Saccharomyces cerevisiae and the competitive advantages they may confer. We have found that inteins can affect cell viability and plasmid retention in their yeast host over time, and the intein with an enzymatic domain causes different effects than the one without. To identify whether these inteins undergo cleavage, we will construct Leu2 proteins with a 3’ 6xHis tag to be assessed by Western blots. Our set of plasmids contain the LEU2 gene, with or without an intein, and the URA3 gene for double selection. Using PCR and cloning, we are adding the 6xHis tag to the 3’ end of the LEU2 gene in these plasmids. Future research will provide deeper insights into the evolution of inteins as selfish genetic elements and their impacts on protein biology.

Brain-computer interfaces (BCIs) decode neural signals from the motor cortex to enable direct control of external devices. While existing BCI designs often combine signals from the premotor (PMd) and primary motor (M1) cortices, these regions have distinct functional roles and anatomical organizations. Prior research demonstrates that PMd and M1 play distinct roles in movement preparation and execution, with information generally flowing from PMd to M1 (Cisek & Kalaska, 2005). Additionally, cortical processing is known to occur in a layer-dependent manner (Bastos et al., 2012), suggesting that different depths within these motor areas may encode distinct aspects of task-related information, highlighting the need for depth-specific analyses. My hypothesis is that task-related information flows directionally from deeper layers of PMd to superficial layers of M1 as behavior transitions from movement preparation to execution. To investigate this, I used Neuropixel probes, which provide high-resolution sampling of neural activity across cortical depths, and performed simultaneous PMd and M1 recordings in two male rhesus macaques as they performed an arm reaching (center-out) task. Preliminary analyses provide evidence that (1) different cortical depths in PMd and M1 encode distinct movement-related and planning information, (2) neural activity in deep PMd exhibits stronger coherence with superficial M1 compared to other depth pairings within and across regions, particularly during movement-related periods, and (3) information flow between PMd and M1 is depth and directionally organized, with information flowing from deep layers of PMd to superficial layers of M1. These findings suggest that the spatial and temporal dynamics of task-related information across cortical depths are important for motor control. Revealing how task-related signals are organized and transmitted across motor cortical layers can inform the development of BCIs that target recordings to leverage these functional dynamics.

The effects of ongoing climate change on river systems present an ever-growing cause for concern, with flooding and other potential hazards threatening millions of people who live near rivers. To investigate how river systems react to climate change, we must turn to analogous events in Earth’s sedimentary rock record. The Paleocene-Eocene Thermal Maximum (PETM) is one such analog, during which global temperatures and precipitation seasonality rose significantly. Rivers record their response to these environmental shifts through the sedimentary structures they create. For example, we can measure cross-sets, which form as rivers preserve sections of sand dunes and ripples on the riverbed, to determine whether a river was in a state of equilibrium, with a year-round stable flow, or in disequilibrium, with increased flash flooding and river channel migration. Here, I test the hypothesis that river systems shift towards disequilibrium during periods of climate change by measuring cross-sets in PETM-aged rocks of the Bighorn Basin, Wyoming. To generate a large number of accurate measurements, I use three-dimensional (3D) digital reconstructions of rock outcroppings. This study will equip river-adjacent communities with insights on how rivers evolve during climate change, and allow them to make adequate preparations for potential hazards. 

Enteric neurons regulate intestinal immunity, motility, and other functions. However, they are not in direct contact with the intestinal lumen. This creates the question of how they can sense microbes in the intestine. Intestinal epithelial cells are in direct contact with the lumen and have also been described to regulate immune responses to pathogens. We hypothesize that enteric neurons that regulate intestinal immunity are activated by intestinal epithelial cells. To test this hypothesis, my goal was to identify if there are physical interactions between specialized types of intestinal epithelial cells and enteric neurons. To achieve this, I utilized whole-mount preparations of the intestine of mice, imaged by 2-photon microscopy, where sensory epithelial cells and enteric neurons were labeled by immunofluorescence. I further applied advanced computational analysis of the obtained 3D images of the intestine to quantify cellular proximity. By integrating these approaches and performing precise spatial mapping and statistical evaluation, I identified interaction patterns between specialized sensory epithelial cells and enteric neurons. This research provides the spatial fundaments of interactions between intestinal epithelial cells and enteric neurons, which provides the basis for neuronal sensing of luminal signals and control of intestinal immunity, with broader implications for gut health.

The conservation of global marine mammal abundance has been considered largely successful as the widespread ban of the industrial harvest of pinnipeds and large cetaceans has led to their strong recovery in abundance. However, it remains unknown whether the story of their conservation applies to marine mammals that were not heavily harvested such as oceanic dolphins. Here, I plan to fill this knowledge gap by presenting a meta-analysis of global abundance trends of oceanic dolphins by conducting a systematic literature review of government reports, journal articles, and marine biodiversity data sets to gather abundance trend data. I expect to find data for roughly 25% of all 38 oceanic dolphin species, mostly represented by line-transect surveys and mark-recapture evidence in coastal waters. Using a Bayesian multi-population state-space model, I intend to estimate abundance trends for each dolphin population, in addition to the uncertainty in population changes and varying survey methods. I seek to summarize abundance trends of populations by species and regions to identify which of these have declining or highly unknown abundance trends. I expect dolphins with restricted geographic ranges, especially coastal species, to have the strongest declines, and dolphins that occupy high seas to have the least known trends. I aim to highlight which taxa and areas need further conservation and monitoring attention. These findings represent a crucial first step in gaining insight from rising dolphin populations, which can be used to help reverse the decline of other populations.  

Most real-world motor tasks involve a many-to-few input-output relationship, such as many neurons firing or muscles contracting to control a few degrees of freedom of the arm. The brain must form an internal model of outputs to inputs when there are fewer dimensions of feedback than dimensions of inputs to control ("redundancy"). However, motor learning is typically studied in laboratory contexts with one-to-one input-output tasks (Krakauer et al., 2019). To investigate how redundancy influences motor learning, I developed a novel virtual reality (VR) visuomotor perturbation task that can either be fully dimensioned or redundant. Participants are trained on a point-to-point reaching task controlled by hand movements in 3D space. In the 3D version of the task, the 3D cursor motion results from the 3D movements of the hand according to some unknown spatial rotation that the participant will have to learn in order to get to targets. In the redundant (2D) version, 3D hand motions are projected onto a 2D plane oriented somewhere in space that the participant has to learn. In both cases, targets are represented as infinite cylinders such that there is a task-irrelevant dimension, but in the redundant version of the task, the participant receives no visual feedback from this dimension. I hypothesize that providing 3D cursor feedback will enhance the learning of the task-relevant 2D plane by allowing participants to better map redundant hand movements in 3D space onto the constrained 2D plane. In contrast, restricting feedback to only the 2D plane will limit available sensory information, making it more difficult to learn the correct movement strategy. By comparing performance across these two tasks, I aim to clarify how task redundancy influences internal model formation and adaptation, with implications for designing more effective motor rehabilitation and VR-based training protocols.

Heroin, a commonly used opioid, has played a significant role in the escalating opioid crisis, highlighting the urgent need to better understand the neural mechanisms underlying its addictive properties. Despite well-documented sex differences in opioid use disorder (OUD), the majority of preclinical research has been conducted in male animal models, limiting our understanding of how biological sex influences addiction-related behaviors. This study investigates the role of sex differences in heroin-induced locomotor sensitization and hormonal adaptations in a rodent model. Using a rodent model, we administered intravenous heroin and tracked activity to assess sensitization to the effects of heroin on locomotion. Following treatment, the rats underwent 20 days of withdrawal from heroin. Blood samples were collected throughout treatment and withdrawal to track changes in serum hormone levels. Our findings indicate that female rats show locomotor sensitization at an earlier time point and exhibit a greater degree of escalation compared to males. This suggests potential sex-specific mechanisms influencing opioid addiction vulnerability and progression. We aim to continue quantifying gonadal hormone fluctuations throughout heroin exposure and withdrawal with additional cohorts of animals. Future experiments aim to use fiber photometry to image estradiol activity in the brain during sensitization, providing a real-time insight into its role in opioid-induced changes in behaviors.