University Of Washington

NSF Awards · FY 2024 · 2024-10

Zooplankton, small animals that drift with ocean currents, are critical links in marine food webs. Many different types of zooplankton have elongated spines, horns, or hairs. These structures are thought of as predator deterrents or sensory antennae. This project examines other ecologically important functions that spines might impact: feeding, swimming, sinking, and dislodgement from surfaces. These functions depend on how animals interact with the water around them. This study investigates how spines work to alter the movement of the surrounding water and how that water movement varies in the early development of the “nauplius” larval stage of different species of barnacles. Barnacles are a type of crustacean, a group that includes the commercially important crabs, shrimp, and lobsters. Since all crustaceans have a nauplius larval stage, this research will shed light on how this common body form operates, providing information about functional tradeoffs between different behaviors and body shapes. This project -- a collaboration between a small, liberal arts undergraduate college and a big research university -- brings together students and faculty from both to conduct the research and to train undergraduates. In addition, this project crosses disciplinary boundaries between biology and engineering, so students from different fields will learn how to communicate and collaborate. Principles discovered from this study can inform bio-inspired design of aquatic microrobots. The types of experiments designed will also be used to develop new science curricula. Diverse zooplankters bear spines with functions that are poorly understood. This study of the hydrodynamics of different species of barnacle larvae will determine (1) functional consequences of the presence, location, and morphology of spines on hydrodynamic forces and torques; (2) functional consequences of spines and appendage kinematics on the forces and torques generated, and on swimming, sinking, and feeding performance; and (3) hydrodynamic consequences of the change in body design from the planktonic nauplius to the settling cyprid form. Kinematics and flow fields of larvae with distinctive morphologies and ecology are measured using micro-videography and high-speed particle image velocimetry. This comparative study on live organisms is coupled with experiments using dynamically scaled physical models to determine mechanisms by which specific features control forces and torques on, and flow fields around, larvae. Physical models allow parameters – spine size and shape; body size and shape; limb morphology; and kinematics -- to be varied in ways not possible with living organisms. In addition to elucidating general principles about the hydrodynamic consequences of spines at the poorly understood size and speed range of zooplankton – the domain of intermediate Reynolds numbers -- the project will advance understanding of how tradeoffs between ecological functions impose biomechanical constraints that can shape the evolution of form. Collaboration between a PUI college and R1 university integrates research and undergraduate education at both. The question-driven, experience-based learning approach involves research teams of undergraduates from physical and biological sciences to develop their skills at interdisciplinary collaboration. Novel interdisciplinary course materials will be developed with context-rich modules for teaching quantitative skills. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NSF Awards · FY 2024 · 2024-10

A long-standing goal of computing research is to create "tools for thought", in which computers extend our abilities to think and communicate in both work and social contexts. Used carefully, large language models (LLMs) -- and their remarkable ability to process and generate text -- can contribute to this goal. Already, people use LLMs to generate and organize ideas, summarize documents, support writing, plan events or meals, generate computer programs, and analyze data. However, current LLM usage prioritizes conversational "chat" interactions involving a single person and one-at-a-time responses, whereas creative work requires considering a variety of possibilities and may include multiple collaborators. The goal of this project is to leverage and evaluate LLMs as "tools for thought" that support creative, open-ended, and collaborative work. The main aims are to (1) integrate LLMs into larger, interactive systems while safeguarding LLM output quality, (2) help people generate and consider diverse, relevant ideas, and (3) support collaborative work involving multiple people and LLMs interacting together. This project looks beyond current chat-based interactions to leverage LLMs to support people's everyday work in a reliable and effective manner. More specifically, this project develops novel methods, evaluations, and applications to better leverage LLMs as tools for thought in both single-user and cooperative scenarios. The main approach is to scaffold LLM-powered systems to provide higher control and reliability, while focusing on a key step of open-ended information work: "divergent" phases of generating diverse yet relevant candidate ideas, followed by "convergent" phases in which one navigates, selects, and synthesizes the most promising ideas. The first objective of this project is to develop a design space and guidance for building more reliable and controllable LLM workflows, drawing upon over a decade of crowdsourcing research and documenting the adaptations necessary to build effective workflows and evaluate LLM capabilities. The second objective is to enable cycles of divergent and convergent work: developing robust operations for generating diverse yet relevant candidates -- whether they be writing suggestions, brainstorming ideas, or salient quotes to extract from a text -- alongside methods for choosing among and combining responses. The third objective expands this focus to cooperative projects, enabling hybrid multi-user/LLM workflows and investigating how LLMs could improve awareness and coordination among collaborators. In support of these objectives, the project will develop and evaluate user-facing applications for tasks such as scientific writing, text analysis, and design ideation, providing practical examples of LLM-supported "tools for thought". This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NSF Awards · FY 2024 · 2024-10

This project aims to serve the national interest by producing instructional activities to optimize physics quantitative literacy (PQL) development that are grounded in validated ways that students develop reasoning. Introductory physics is required for many STEM majors, in large part, because developing a strong foundation in quantitative reasoning is recognized as being important for their subsequent studies and careers. This project will center on two broad instructional aims: improving quantitative literacy for all STEM majors through physics course-taking, and helping reduce barriers that prevent students from economically disadvantaged communities from entering STEM majors. Instructors can help all of their students improve their essential quantitative reasoning by making PQL an explicit learning objective. In order for that to happen widely, instructors need effective materials and methods they can adopt and adapt in a variety of contexts, as well as validated assessments to measure PQL and models for analyzing and interpreting the results. The significance of this project is the development and dissemination of these instructional materials. This project aims to accomplish two goals. The first goal is to create an emergent model of PQL development based on student resources. Using methods related to item response theory and knowledge space theory, this project plans to augment analysis of existing multiple-choice tests by defining a partial-credit scoring model that recognizes the value of students’ responses to test items that are partially correct. By analyzing data from students in introductory, middle-division, and upper-division physics courses, the project aims to produce an emergent longitudinal model of PQL development based on the landscape of student responses to test items across multiple courses. The second project goal is to develop, implement and disseminate instructional materials and methods that will be founded on the emergent model of PQL development. These materials will help students conceptualize the algebra and calculus quantitative reasoning that underpins STEM quantitative literacy and will be disseminated widely across a variety of learning environments to broaden the impact for a diverse group of learners. The model of PQL development produced will be used as a framework to guide the production and refinement of: 1) modular, cooperative activities that can be used in small group settings, think-pair-share lecture settings, or as homework, and 2) formative assessment questions that can be used on tests and quizzes. The NSF IUSE: EDU Program supports research and development projects to improve the effectiveness of STEM education for all students. Through its Engaged Student Learning track, the program supports the creation, exploration, and implementation of promising practices and tools. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NSF Awards · FY 2024 · 2024-10

The broader impact of this Partnerships for Innovation - Technology Translation (PFI-TT) project is in addressing a prominent complication (5-7%) in the ~93,000 Thyroidectomy procedures each year in the United States. This complication is accidental damage or destruction of the tiny parathyroid glands causing hypoparathyroidism. Complications can be severe and include extended hospitalization, cardiac arrhythmias, and a lifetime of medication and medical follow up exams. The project aims to eliminate complications of thyroid surgery by commercializing an artificial intelligence (AI)-driven, multi-sensor, tissue identification/confirmation instrument. The project will also support and train graduate and undergraduate students working in an interdisciplinary team (engineering, industrial design, and medicine). This project addresses applied and pre-commercialization engineering research in medical technology. Research questions that will be addressed include: Which sensing modalities contribute to accurate thyroid/parathyroid (TPT) discrimination? What is an effective design for a low-cost, compact, efficient sensing system for the parathyroid’s known autofluorescence characteristics? What would be the architecture of a multimodal artificial intelligence model able to make multiple measurements at widely varying data rates and fuse them for a more accurate and robust detection of the thyroid gland and similar classification tasks? These questions must be answered under the practical limits on the size of training datasets that are feasible to collect from surgically realistic settings. Research methods include electronic circuit design fabrication, calibration and testing, experimental data collection under medically realistic conditions, and training and validation of machine learning models. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NSF Awards · FY 2024 · 2024-10

Summer streamflows are critically low in numerous Pacific Northwest watersheds and are projected to decline further as temperatures rise and snowpack diminishes. These flow conditions result in poor quality aquatic habitats that are detrimental to salmon and other fish. The Nooksack Tribe, along with other Tribes in the region, are looking closely at management options that could help to sustain the survival of salmon, which are critical for cultural, spiritual, environmental, and economic uses. Forests are a key influence on the amount and timing of streamflow in a watershed, and forest management approaches such as thinning in lieu of clearcut harvest may drive increased streamflow during the dry summer season. A few previous studies support this concept based on observational data collection and numerical modeling, but there is limited confidence in these effects for western Washington due to a lack of regionally relevant observations and modeling. This project will assemble a regional coalition of scientists, Tribal representatives, and resource managers to collect relevant data, implement modeling, and provide actionable results that can inform strategies, decisions, and policy. In the Pacific Northwest region of the United States, threatened and endangered salmon species sustain continued losses due to low summer flows and elevated stream temperatures. These critical streams are fed by watersheds that have experienced over a century of clear-cut timber harvest rotations, which have resulted in a mosaic of young, regenerating forest stands. Preliminary investigations of the effect of forest age and regeneration on summer low flows indicate that the legacy of even-age management may have contributed to declines in summer flows relative to mature old growth stands, but the issue is still understudied. For example, model representations of forest transpiration as a function of stand age is based on two studies located in the coastal range of Oregon, rather than in upland forest plantations of the western Cascades. This project aims to build a community of Tribal representatives, scientists, and water managers to guide the development of a targeted, decision-relevant research plan. Stage 1 will include workshops, field reconnaissance, and instrumentation testing, and Stage 2 aims to collect sap flux, soil moisture, and snow data across forest types to support testing and implementation of two hydrological models. Together, the field and modeling approaches will build actionable knowledge of the hydrologic linkages between the upper watershed, where forest management is occurring, and the stream channel, where salmon are spawning and rearing. This project is in response to the Civic Innovation Challenge program’s Track A. Climate and Environmental Instability - Building Resilient Communities through Co-Design, Adaption, and Mitigation and is a collaboration between NSF, the Department of Homeland Security, and the Department of Energy. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NIH Research Projects · FY 2024 · 2024-09

Summary Clinical diagnosis and differential diagnosis of Parkinson disease (PD) and multiple system atrophy (MSA), two progressive and fatal neurodegenerative disorders, can be quite challenging, especially at early disease stages, due to the overlapping clinical symptoms among various parkinsonian disorders. Biomarkers such as neuroimaging measurements and α-syn seeding aggregation assays (Real-Time Quaking-Induced Conversion or RT-QuIC) in cerebrospinal fluid (CSF) and some biopsy samples have shown promising results in improving PD and MSA diagnosis, but simpler, less expensive, accurate, and reliable biochemical markers, particularly those in easily accessible body fluids (e.g., blood), are still urgently needed to aid in clinical assessments. Growing evidence suggests that membrane-bound extracellular vesicles (EVs) play important roles in cell-to-cell communication and signaling and the pathology of neurodegenerative diseases, including PD and MSA. Additionally, EVs carrying unique disease-specific and functionally important cargo may cross the blood-brain barrier and be detected in vivo in blood, suggesting that blood-based but brain cell-derived EVs can be a valuable source of biomarkers for neurodegenerative diseases. We have recently developed a new flow cytometry-based technology (Apogee) to analyze individual EVs carrying brain cell-specific and/or disease-related protein markers in body fluids for improved biomarker accuracy and utility. These sensitive and rapid assays directly quantify intact, individual EVs, without extensive purification before quantifying disease markers, which potentially reduce inter-lab variability and increasing the clinical utility of EV-based biomarkers. Further, in recent pilot studies, we and others observed that applying modified RT-QuIC assays to plasma EV samples could clearly distinguish between PD or MSA and healthy controls as well as between PD and MSA. In this study, we propose to further fine tune and optimize our Apogee and RT-QuIC assays to analyze EVs carrying both brain cell-specific markers (e.g., L1CAM or NMDAR2A for neurons, CNPase for oligodendrocytes, and GLAST for astrocytes) and disease-related markers (e.g., α-syn species, amyloid β and tau species). The optimized assays will then be validated for their performance in MSA and PD diagnosis and differential diagnosis in two independent plasma sample cohorts. These proposed experiments will likely establish two compensatory blood-based biomarker assays for MSA and PD – a rapid screening tool (Apogee) and a more accurate assay (RT-QuIC) to replace corresponding CSF assays. Both assays can be used in future larger-scale MSA and PD biomarker studies, which may establish the foundation leading to inexpensive and widely available blood tests to aid in PD/MSA diagnosis and/or disease tracking.

NIH Research Projects · FY 2024 · 2024-09

PROJECT SUMMARY Heart failure (HF) remains a major public health concern as the number of American adults experiencing HF continues to rise. Engineered heart tissues (EHTs) have emerged as a significant advancement for disease modeling and drug screening, better replicating in vivo processes than many small-animal models. However, despite their potential in assessing the impact of drugs on CMs, these EHTs lack vasculature, a critical component of cardiac function. In vivo, cardiomyocytes (CMs) are surrounded by a dense network of vasculature which supplies oxygen and nutrients and regulates blood flow to the heart. Endothelial cells (ECs) lining these vessels emit protective signals, that govern vital cardiac processes including heart development, homeostasis, and tissue regeneration. As such, there is a critical need for a new EHT model which incorporates a perfusable vascular element to study interactions between vascular perfusion, the endothelium, and CMs, shedding light on their impacts on cardiac function and disease. One notable example of the interplay between vasculature and CMs that could be studied using this model is endothelial dysfunction. Linked to HF, endothelial dysfunction results from inflammation, triggered by stressors such as hypertension, hyperglycemia, hemodynamic changes, and viruses. While previous research has focused on impaired vasodilation as the primary link to HF, more recent work has begun to explore the role that disrupted autocrine and paracrine signaling may have on EC-CM communication, leading to cardiac stress, hypertrophy, death, and overall reduced cardiac function. However, no existing in vitro model allows for direct study of the impacts of endothelial dysfunction and its consequences on CMs. Our group recently developed a perfusable collagen-based EHT through injection molding techniques. With precise control of tube geometry, perfusable pressure and flow, and cellular and matrix composition, this new EHT model presents an opportunity to study the interaction of flow, endothelial function, and cardiac function, and the impact of endothelial dysfunction on this relationship. We hypothesize that the inclusion of perfusion within this EHT model will enhance EC survival and function and improve the physiologically relevant cardiac response to altered load and electrical stimulation. Additionally, we expect that induced endothelial dysfunction will lead to increased cardiac dysfunction. To test this hypothesis, we will assess the effect of flow on endothelial cell retention and, consequently, cardiac function within our perfusable EHT model, investigating the phenotypic, functional, and transcriptional changes that are induced by the addition of a vascular component. We will also use this perfusable EHT model to determine our ability to chemically and mechanically induce endothelial dysfunction and study the effect this dysfunction has on neighboring CMs. This model will deepen our understanding of vascular perfusion, endothelial function, and cardiac function in healthy and dysfunctional conditions.

NIH Research Projects · FY 2025 · 2024-09

Alzheimer's disease (AD), the most frequent cause of age-related dementia, constitutes a serious burden for the US health system and economy. In the absence substantial preventative or disease-modifying treatments, AD frequency is increasing as the lifespan increases. Age and genetic predisposition are the largest contributors to AD risk. A substantial fraction of genetic variation in AD are noncoding variants that regulate gene expression, but unlike changes in protein code, impact of regulatory variants is not easily predictable. Currently known genes and risk alleles that change protein coding sequence explain at most 30% of AD susceptibility, emphasizing the need to investigate variants that regulate gene expression and splicing. According to recent estimates, up to 50% of all variants associated with human diseases are variants that have some effect on gene splicing. Triggering receptor expressed on myeloid cells 2 (TREM2) is a microglia-specific immune molecule whose dysfunction causes a continuum of neurodegenerative conditions. Some missense TREM2 variants, exemplified by R47H, are transmitted as autosomal dominant traits, conferring a significant late onset AD risk. The R47H allele is one of the strongest known contributors to the risk, with effect size similar to the APOE e4 allele. On the other hand, biallelic loss-of-function variants that inactivate the receptor cause recessive early onset dementia, such as Nasu-Hakola disorder (NHD). TREM2 is subject to alternative splicing, which is species-specific, but the extent and effect of this process has yet to be comprehensively characterized. We recently identified a novel splice isoform of TREM2 (delta e2) with altered activities due to lack of an important protein domain. In preliminary study, we found that multiple variants that cause NHD or increase risk for AD affect TREM2 splicing and reduce the dosage of functional transcript via competition with the abnormally spliced delta e2 isoform. We hypothesize that a precise balance of isoforms is important for TREM2 function and that cis-regulatory variants, in combination with protein factors variably expressed in AD microglia, reduce gene dosage and increase AD risk. The goal of this proposal is to comprehensively characterize the TREM2 transcript repertoire in human brain in health and disease (Aim 1), assess TREM2 variants that are present in patients with dementia for their effect on RNA splicing and post-splicing processing (Aim 2) and analyze the interplay between AD-associated cis- regulatory TREM2 variants and trans-acting splicing factors that are perturbed in AD brain (Aim 3). To achieve these goals, we will use state-of-the-art long-read RNA sequencing, computational variant effect predictions, high-throughput combinatorial library screening, and unbiased quantitative proteomics approaches. This will generate a cis-regulatory TREM2 map at the nucleotide resolution level that will be used to annotate the regulatory potential of hundreds of variants of unknown significance found in AD patients. Successful completion of the proposal will spearhead application of similar strategies to characterize variants that affect post- transcriptional regulation of other disease-related genes.

NIH Research Projects · FY 2025 · 2024-09

Abstract Chronic pain is common and often inadequately treated in older individuals. Although opioids are often used to treat chronic pain, their use in older adults is associated with increased rates of falls, fractures, and mortality. Advancing our understanding of non-pharmacological chronic pain treatment in Americans ≥60 years of age will substantially alleviate the burdens caused by this condition. Experimental pain paradigms mimic the experience of clinical pain (both neuropathic via thermal paradigms, as well as musculoskeletal via mechanical paradigms) and provide a rigorously controlled approach to advancing the understanding of pain treatments. Two efficacious, non-pharmacological chronic pain treatments are mindfulness meditation (MM) and self- hypnosis (HYP). Prior research using functional magnetic resonance imaging (fMRI) has shown MM and HYP may target changes in both unique and shared central pain mechanisms. However, it is not yet known whether these same neuromodulatory changes underlie treatment-related reductions in chronic pain in older persons. Given that aging affects the prefrontal cortex and both MM and HYP effectively target this region, these interventions may be particularly well suited to enhance descending inhibitory pain control in older adults via prefrontal cortical mechanisms. There is also a critical lack of research examining patient characteristics that moderate treatment outcome. Our preliminary research using electroencephalography (EEG) has identified pre-treatment brain-state variables that may predict who benefits most from MM and HYP. To identify the neuromodulatory mechanisms of MM and HYP for chronic pain in older individuals, the proposed study will include formal statistical tests of both mediation and moderation in a fully-powered clinical trial with N = 375 older adults with chronic pain (enrolled). The design will employ a 3-arm (MM, HYP, attention control) trial, resulting in tightly controlled tests of treatment mechanisms to accomplish the study aims. Treatment will consist of four, 20-minute sessions delivered over four consecutive days. The primary outcome will be change in chronic pain intensity from pre- to post-training. Aim 1 will use perfusion-based arterial spin labelling fMRI to determine the neuromodulatory mediators of treatment-related chronic pain intensity reductions, relative to the control. Aim 2 will identify pre-treatment psychological and EEG-assessed moderators of reduced chronic pain intensity in response to MM and HYP, relative to the control condition. The knowledge gained from adequately powered, formal tests of mediation will provide an empirical basis for developing more efficacious pain interventions that may also have a preventative-medicine role in older adults, thereby reducing the public health burden incurred with chronic pain in this population. Elucidating the moderators of MM and HYP will inform precision medicine and will also optimize the cost-effectiveness of chronic pain treatments.

NIH Research Projects · FY 2024 · 2024-09

SUMMARY The human genome supports billions of potential variants, and the number of variants detected through genome sequencing continues to grow rapidly. However, our ability to interpret these variants and identify those responsible for disease phenotypes still lags. Statistical methods such as genome-wide association studies struggle with rare or de novo mutations. Approaches based on sequence conservation are less reliable for the vast majority of variants that fall outside protein coding sequences. These shortcomings of traditional approaches motivate the development of models for variant stratification. Functional models aim to quantify how a genetic variant impacts a molecular phenotype -- transcription, splicing, polyadenylation, stability, translation, and more -- thus creating a link between a variant and an organismal phenotype. Crucially, such sequence-to-function models can generalize from training data to unseen sequences by learning the regulatory rules underlying the observed molecular phenotype, thus making it possible to even predict the impact of rare variants on the process under investigation. In prior work, we showed that models learned from massive numbers of synthetic reporter constructs could strongly outperform models learned from the comparably small number of natural examples even in predicting the impact of variants on gene expression in humans. Here, we extend our work combining synthetic biology with machine learning to build and integrate predictive models of mRNA stability and translation. In Specific Aim 1, we propose to conduct high-throughput reporter assays to characterize how variants in both coding and untranslated regions impact mRNA stability and translation. Regulatory rules are often position-dependent, and a particular sequence motif might have a vastly different impact on gene expression depending on its location. We thus propose to develop MPRAs that interrogate CDS as well as 5’ and 3’UTR variants. Furthermore, we propose to perform stability and translation MPRAs with multiple cell types to uncover aspects of cell type-specific regulation. In Specific Aim 2, we propose to develop machine learning approaches that enable us to integrate results from multiple measurements and generalize predictive rules learned from such assays. Additionally, we will apply a deep learning model interpretation method developed in our lab to generate hypotheses about biological mechanisms, which will be confirmed via MPRAs in knockdown cell lines. In Specific Aim 3, we propose to develop a novel type of reporter assay that allows us to directly measure the impact of sequence variation on protein levels using high-throughput nanopore sequencing of protein-level barcodes. The use of this protein barcoding technology will improve the resolution, specificity and accuracy of protein measurements by going beyond ribosome loading measurements, reducing the potential for false positives and negatives.

NIH Research Projects · FY 2024 · 2024-09

PROJECT SUMMARY/ABSTRACT Subarachnoid hemorrhage (SAH) accounts for 27% of all stroke-related years of potential life lost before 65 years of age. Sleep disturbance (insufficient sleep, poor quality) and daytime sleepiness (falling asleep during activities) are highly prevalent following SAH. These symptoms negatively impact overall daily function and quality of life and increase healthcare use, yet often go undetected or untreated during clinical care. This proposed study builds upon our prior research, where we found that SAH survivors use patient activation and self-management strategies in an attempt to improve sleep (e.g., seek knowledge and skills, exercise or relax), but become frustrated when there is no support or structure to aid their strategies. Our findings suggest that targeted sleep self-management interventions focusing on patient activation improve sleep in this population. However, effective interventions focusing on sleep disturbance tailored to SAH have not been reported in the literature. In this study, we will integrate input from SAH survivors and their caregivers, employ an iterative human-centered design using a mixed methods approach, and develop a technology-based intervention to improve self-management skills (patient activation and engagement) for SAH survivors with sleep disturbance. We will tailor the face-to-face Sleep BETTER 4-week intervention, effective in improving sleep in other chronic illness populations, to meet the unique needs of SAH survivors, and convert it to a technology-based format using responsive-design web technology to support deployment over web, tablet, and mobile devices. This program includes six components: 1) bedroom environment, 2) exercise, 3) tension, 4) time in bed, 5) eating and drinking, and 6) rhythm for sleep-wake routines. In this study we aim to: 1) Tailor the Sleep BETTER intervention to meet the unique needs of SAH survivors (e.g., enhanced social support and self-management skills) to improve sleep disturbance (i.e., self-report sleep quality and daytime sleepiness; actigraphy total sleep time and sleep efficiency) with 32 SAH survivors and their caregivers, 2) Develop a technology-based intervention, using an iterative human-centered design and qualitative methods (i.e., iterative cycles of semi- structured audio-recorded sessions) with 24 SAH survivors and their caregivers, 3) Refine and test the usability of a technology-based intervention, employing think-aloud observation sessions, the System Usability Scale, and semi-structured interviews with 32 SAH survivors and their caregivers, and 4) Assess the overall feasibility and acceptability of collecting primary (i.e., self-report sleep quality and daytime sleepiness; actigraphy total sleep time and sleep efficiency) and secondary measures (i.e., patient activation, motor or cognitive impairments, and social support) to refine the intervention protocol. A technology-based intervention to improve sleep has the potential to reduce health disparities by providing an intervention for SAH survivors who are typically geographically dispersed with limited access to sleep specialists. Our results will provide critical data for further development of a large scale randomized controlled trial to improve sleep in this population.

NIH Research Projects · FY 2026 · 2024-09

Diets low in fruits and vegetables are associated with chronic disease disparities for Latinos living in rural areas. Furthermore, in rural areas, structural and social factors like low wages, limited public transportation, and inability to access social services, can limit access to healthy food for Latinos. Despite these barriers to healthy foods, many Latinos regularly shop at retail food stores, which provide access to desired foods and services. Our Value is an effective, culturally tailored retail food store intervention to promote the consumption of fruits and vegetables among shoppers. This theory-informed, multi-level intervention addresses customer behavior, social, and structural factors at the store. We propose to shift our knowledge on adapting evidence-based interventions such as Our Value to rural areas. We are partnering with community leaders and members to tailor this intervention in rural communities, retail food stores, and the structural and social factors that impact these communities. Using a hybrid type I cluster-RCT design, we aim to augment and adapt the intervention for populations living and shopping in stores in rural communities; to assess the implementation of the adapted intervention on access to fruits and vegetables at the store level; and to evaluate the effectiveness of the adapted intervention on customers’ consumption of fruits and vegetables. We engage in a community-based participatory research process to create new knowledge on translating evidence-based interventions for rural communities and advance our understanding of addressing social and structural drivers of health while maximizing effectiveness and external validity. This research aims to accelerate the implementation of evidence-based interventions to promote health and reduce health disparities in the United States.

NIH Research Projects · FY 2025 · 2024-09

Benzalkonium chlorides (BACs) are widely used antimicrobials in disinfecting products, medical products, and food processing industries, suggesting humans may be exposed chronically to BACs through various routes. The ongoing COVID-19 pandemic has led to greatly increased use of disinfectants, resulting in a 174% increase in median BAC levels in human blood. We recently analyzed 15 de-identified human fecal samples collected during COVID-19 and detected BACs in all of them, ranging from 55 nM to 2.74 µM (a 50-fold difference). BACs are potent antimicrobials, but their effect on the gut microbiome has not been examined, which is the major gap that this proposal aims to fill. Our goal is to characterize the effect of BAC exposure on gut microbiome compo- sition and function, microbiota metabolism, and altered liver metabolism via the gut-liver axis. We previously reported that BACs are metabolized by human cytochromes P450 (CYP) in the liver. Our preliminary data sup- port biliary excretion from the liver to the intestine being the major route of elimination for BACs. Thus, exposure of gut microbiome to BACs is inevitable regardless of the route of exposure. Disruption of the gut microbiome can lead to changes in endogenous and xenobiotic metabolism through modulating the ligand availability for the bile acid-sensing farnesoid X receptor (FXR), the lipid-sensing peroxisome proliferator-activated receptor-alpha (PPARa), and xenobiotic-sensing constitutive androstane receptor (CAR) and pregnane X receptor (PXR). Im- portantly, in a preliminary study, we found that BAC exposure in mice significantly upregulated the expression of Cyp2c38, Cyp2j6, Cyp4a10, and Cyp4f13 in the liver, which is consistent with the inhibition of CAR and/or acti- vation of PPARa. Thus, we hypothesize that BACs reduce gut microbiome diversity and alter the metabolism of xenobiotics, bile acids, sterols, and lipids in the liver by modulating the activities of nuclear receptors. In Aim 1, we will characterize the impact of BAC exposure at different doses and exposure regimes on gut microbiome diversity and function in mice. We will then correlate the changes in microbiome functional genes with the changes in the gut bile acid, sterol, and lipid profiles. In Aim 2, we will measure the effect of BAC exposure on bile acid, sterol, lipid, and xenobiotic metabolism in the liver of conventional and germ-free mice. Relationships between bile acid, sterol, and lipid profiles and relevant gene expression levels in the liver will be evaluated. Activation or inhibition of nuclear receptors regulating xenobiotic-metabolizing enzymes (XMEs) will be as- sessed. In Aim 3, we will evaluate the relationship between BAC levels and gut microbiome diversity and function in humans. The significance of this project lies in that it will allow us to begin to understand the impact of in- creased BAC exposure on gut microbiome and gut-liver interactions in humans. The innovation of this project lies in that a) it represents the first study to examine the impact of BAC exposure on gut-liver interactions, and b) alteration of XME gene expression by BAC exposure represents a novel gene-environment interaction that could affect the metabolism of endogenous metabolites and other xenobiotics.

NIH Research Projects · FY 2025 · 2024-09

The proposed project entails (1) user-centered development of an innovative web-based intervention to reduce alcohol-related harm among young adults, and (2) pilot testing the intervention to assess indices of acceptability and engagement, as well as preliminary assessment of efficacy, relative to a treatment-as-usual and attention- matched control conditions. Personalized normative feedback (PNF) – i.e., correcting misperceptions about peers’ alcohol use behaviors and contrasting one’s own use to the actual norms of their peers – is an economic strategy that is widely used on college campuses. Although effects of PNF interventions are consistent, and generally maintained, the effect sizes can be improved; thus, innovation is needed to further move the needle. The proposed intervention will expand traditional PNFs that generally only provide normative feedback for ‘typical students’ at participants’ university, by providing options for users to customize their experience and explore a variety of more specific normative feedback modules; for example, providing normative feedback specific to first year students, Hispanic students, or sexual minoritized students (many other modules will be available). This novel paradigm will provide users with a truly personalized and engaging experience in which individuals receive normative feedback on the referent groups that are most meaningful and interesting to them. Although this customizability is anticipated to increase engagement and efficacy, it will also provide more equitable prevention, as many students may not identify with the ‘typical student’ (e.g., minoritized students) and these students may be more receptive to feedback that is more aligned with their own identities. Thus, this pilot project will lay the groundwork for a novel customizable personalized normative feedback (CPNF) intervention paradigm whereby users can choose to explore normative feedback for a wider variety of referent groups (as many as they wish to explore), in addition to typical student norms feedback. In Phase 1 of the pilot project, we will develop and refine the CPNF intervention content, design, and deliverability through a multi-step, iterative process called rapid prototyping (N=30). In line with user centered design, young adults will be incorporated into and provide feedback on all steps to ensure that a relevant and engaging final product is created. Rapid prototyping allows us to quickly gather user feedback and make changes based on user preferences. Once the intervention is developed and fully programmed, Phase 2 will entail a pilot RCT (N=250) of the CPNF intervention. Aim 2 will specifically examine feasibility of the CPNF intervention paradigm in terms of acceptability, engagement, interest, and satisfaction, and will examine whether these indices are higher among students who are in most need of this type of intervention (e.g., heavier drinkers). Aim 3 will entail a ‘proof-of-concept’ test of efficacy, relative to standard PNF and attention-matched control conditions, in terms of reductions in alcohol use and negative consequences assessed at 1- and 3-month follow-ups, and test whether CPNF increases treatment equity for students of marginalized identities (race/ethnicity and sexual/gender minorities), relative to standard PNF.

NIH Research Projects · FY 2025 · 2024-09

Project Summary The negative impact of heavy episodic drinking (HED) among college students continues to be a major public health issue, and students who are members of fraternities and sororities (Greek members) are at particularly greater risk for experiencing negative alcohol consequences due to frequent HED. Individual-level alcohol interventions have limited efficacy among Greek members, which may be because these approaches do not directly account for the greater social ecological and developmental factors which play a significant role in drinking behavior. Young adulthood is marked by an emphasis on developing and maintaining social bonds, and alcohol use is an integral part of social interactions in the Greek environment. This study integrates developmental and behavioral economic models of alcohol use to develop and test an environmental intervention addressing HED and alcohol consequences. The intervention focuses on increasing the availability of and engagement in rewarding alcohol-free social activities, providing alternatives to drinking events for building social connections. Human-centered design principles will incorporate the perspectives of Greek members in the intervention development process to increase usability and contextual fit. This innovative study will proceed in three phases following the Discover, Design/Build, Test framework. Discover Phase: Greek members' perspectives and needs on social activity engagement will be identified by conducting qualitative interviews (N = 30) and a quantitative survey (N = 925) to better understand the intervention setting and the context of social activity engagement in the Greek community. Design/Build Phase: The intervention will be developed and refined in collaboration with Greek members involving co-creation sessions and iterative feasibility and acceptability testing. Test Phase: Feasibility and acceptability of the intervention and the impact of the intervention on alcohol outcomes will be evaluated using a pre-post design with two cohorts of six chapters over two years. This Career Development Award will support the investigator's development as an independent researcher focusing on the development of alcohol interventions addressing reward processes among young adults who engage in high-risk alcohol use. The investigator's long-term career goals will be achieved through training in 1) developmental and reinforcement-based models of young adult high-risk alcohol use, 2) research methods for measuring and increasing substance-free reinforcement, 3) developing collaborative relationships with community partners, and 4) research approaches that emphasize acceptability, effectiveness, and potential for successful implementation. Dr. Lehinger's career goals and project are consistent with NIAAA's prevention goals of a) developing and evaluating strategies to prevent and reduce alcohol misuse among young adults and b) evaluating the effectiveness and implementation of environmental interventions for preventing alcohol misuse.

NIH Research Projects · FY 2024 · 2024-09

Project Summary/Abstract This proposal will provide the foundational tooling for understanding the function of the pan-genome reference through the accurate annotation of regulatory elements within the pan-genome. As the genetic component of the pan-genome reference comes into focus, the next challenge is understanding the functional relevance of genetic variants within this reference. However, resolving this challenge requires tooling that enables users to: (1) get accurate epigenetic data into a pan-genome reference; and (2) use epigenetic data once it is in a pan-genome reference. This proposal leverages our team’s unique expertise in long-read epigenetics, short-read epigenetics, pan-genome assembly, and genomic software development to develop transformative tooling for threading accurate epigenetic information into a pan-genome graph, as well as extracting epigenetic information from a pan-genome in a manner that is compatible with existing epigenetic and genetic analysis tools. Our tooling is grounded in first assembling accurate epigenetic annotations at the level of haploid linear contigs, which are then threaded into a pan-genome reference. This approach significantly improves the accuracy by which both long- and short-read epigenetic features are mapped into a pan-genome, enables our tooling to readily adapt to new pan-genomes, and enables user-generated epigenetic data to be incorporated into a pan-genome reference without having to remake the pan-genome reference itself. Importantly, we are designing this tooling to work for diverse types of epigenetic data acquired across sequencing platforms. In addition, this tooling will be available through AnVIL, Conda, and other platforms, enabling users to readily adopt it into their own research pipelines. Specifically, in Aim 1 we will develop tooling that uses a semi-supervised machine learning approach to accurately classify long-read epigenetic data collected using diverse experimental methods and sequencing platforms. In Aim 2, we will develop tooling that accurately aggregates long-read epigenetic data onto haploid linear contigs, and then threads either long-read or short-read epigenetic data into a pan-genome reference. In Aim 3, we will create fundamental operation tools for processing epigenetic data within a pan-genome to identify epigenetic and genetic features at specific points of interest within a pan-genome in a sample-, path-, and read- aware manner. Finally, we will apply our tooling to existing long-read and short-read epigenetic datasets to identify genetic variants within the pan-genome reference associated with haplotype-, paralog-, and sample- specific epigenetic features.

NIH Research Projects · FY 2025 · 2024-09

Abstract The goal of personalized oncology is to select the most appropriate drug(s) for individual cancers. A number of platforms (e.g., organoids and PDX mice) have been developed to generate human cancer models for drug sensitivity testing, but they have yet to deliver on their promise as an every-day clinical assay for use by oncologists. The major hurdles limiting success of personalized drug sensitivity testing are the long turnaround time and the amount of starting material needed, in addition to the loss of the original tumor microenvironment. To address these shortcomings, we developed an elegant assay to evaluate drug sensitivity based on metabolic changes in fresh tumor tissues obtained through needle biopsies. Our so-called MetaboCore assay takes advantage of an optimized organotypic culture platform that is suitable drug testing immediately upon specimen collection, and a novel single-cell metabolic assay that detects changes in metabolism of cancer cells within a short time of drug exposure. Consequently, quantitative results of relative drug sensitivity can be obtained within a week of the biopsy. In order to advance our assay towards clinical use, we need to create a robust SOP with defined parameters for each step of the assay in order to achieve reproducible results. The objectives of the proposal are to examine how biospecimen preanalytical conditions affect assay performance. Specifically, we will quantify the effects of each of the following variables on tissue viability and drug response: type and size of biopsy needles, transport solution, overnight storage, culture conditions, recovery time, drug concentration, treatment duration, and protocols for tissue dissociation. Based on these findings, we will create a SOP for MetaboCore and test its clinical performance in a pilot study using needle biopsies of human liver cancers.

NIH Research Projects · FY 2025 · 2024-09

Abstract Cardiovascular disease (CVD) caused by atherosclerosis remains the leading cause of mortality in individuals with type 1 diabetes (T1D). Although T cells are well known to play a critical role in T1D development, attacking and destroying the insulin-producing β-cells, very little is known about the expansion of specific T cell populations and clones in cardiovascular complications associated with T1D. Our project aims to dissect the relationship between increased recruitment and expansion of harmful T cells in the atherosclerotic milieu of T1D, leveraging the unique resources of the CaRe-T1D biobank. By employing single cell-T cell receptor- sequencing (scTCR-seq) and cellular indexing of transcriptomes and epitopes-sequencing (CITE-seq) of circulating PBMCs, we will illuminate T cell populations altered in T1D and investigate their adhesion to human coronary artery endothelial cells. By performing TCR-seq on atherosclerotic lesions and elucidate localization of T cell population associated with lesion stage by spatial and global proteomics we will delineate the role these T cells might play in the increased CVD risk associated with T1D. We hypothesize that atherosclerotic lesions in T1D are characterized by increased accumulation of specific T cell populations and clones correlating with lesion severity and necrosis, and that the accumulation of T cells in T1D-related atherosclerotic and renal kidney lesions mirror each other, driven by similar immunometabolic perturbations. Two specific aims will address this hypothesis. We will 1) Clarify mechanisms of increased T cell adhesion and tissue recruitment in T1D cases; and 2) Investigate clonal expansion of CD4+ and CD8+ T cells in atherosclerotic lesions in T1D. By correlating selective T cell markers with a thorough characterization of lesion features, our studies will provide novel information on T cells in the pathogenesis of atherosclerosis and renal kidney injury in T1D in contrast with controls and T2D. Our project is led by a coalition of scientists and physician-scientists with extensive expertise in diabetes, diabetes complications (atherosclerosis and diabetic kidney disease) and immunology, with deep methodological proficiency in human studies, multi-omics analyses, and integrated biology. This diverse expertise ensures a holistic approach and full utilization of the unique resources of the CaRe-T1D, enabling us to navigate the complex interplay of metabolic and immune processes in T1D with unparalleled depth and precision. Our comparative analyses between peripheral blood mononuclear cells, atherosclerotic lesions and kidneys from the CaRe-T1D biobank will provide a robust platform for identifying and testing potential therapeutic targets. Our focus on the metabolic-immune interface within atherosclerotic lesions, and specifically on identifying specific T cell populations and clones, offers a novel perspective on pathogenesis, positioning our study to make significant contributions to the field.

NIH Research Projects · FY 2025 · 2024-09

Project Summary/Abstract Chromatin 3D structure plays an important role in fundamental genomics processes. A variety of experimental methods, such as Hi-C, GAM, SPRITE, and HiChIP, have been developed to characterize chromatin architecture and DNA-DNA interactions genome-wide. Meanwhile, other types of data, such as gene expression and chromatin accessibility profiles, have also been used to refine our understanding of gene regulation and chromatin structure. However, computational tools that can jointly analyze Hi-C and other types of data are still lacking, hindering the process of comprehensively understanding the relationship between genome structure and function. Moreover, the heterogeneous, large-scale, noisy and high-dimensional nature of these data presents computational challenges for effectively integrating Hi-C data with other types of data. Here, we propose to develop a series of machine learning models that integrate contact matrices with RNA-seq, genome sequence, and ATAC-seq data to advance chromatin structure analysis. First, to identify the dynamic in- terplay between cell-type-specific gene expression and chromatin structure, we will extend our Sagittarius model, which obtains state-of-the-art results in modeling RNA-seq time series, to analyze Hi-C time-course data by ex- plicitly modeling the time dimension. This new model will enable spatio-temporal analyses of chromatin structures for differentiation, development, and disease progression. Second, genome sequence has been successfully used to predict 3D genome folding but has not been fully exploited for resolution enhancement. We will develop a graph-based framework to co-embed genome sequences and low-coverage contact matrices for resolution en- hancement. The imputed high-resolution data will enable biologists to identify 3D chromatin features that can only be discovered at high resolution, such as punctate loops and sub-domains. Third, the view of chromatin architecture provided by a contact matrix has not been fully integrated with the linear, high-resolution picture of local chromatin architecture provided by ATAC-seq data. We will develop a translation model between Hi-C and ATAC-seq, which will be used to analyze cell types or species that only have one of these two modalities. This translation model will provide a consolidated view of 3D chromatin architecture and further advance downstream analyses of regulatory processes, such as promoter-enhancer interactions, replication timing, gene expression, and mRNA splicing. All of the software produced by this project will be open source, and all of the imputed data and pre-trained models will be made publicly available, providing a valuable resource for users interested in understanding chro- matin 3D architecture and its relationship to gene expression and other functional cellular processes.

NIH Research Projects · FY 2025 · 2024-09

ABSTRACT Endemic and emerging zoonoses both represent profound threats to public health. While these two disease systems diverge in many ways, fundamental to both is the importance contact networks in which humans and animals mix. In STI research and veterinary epidemiology, analysis of human-only and livestock-only networks have led to significant insights on how transmission occurs, and how best to interrupt it. Yet to our knowledge, no prior research has modeled a human-animal contact network using empirical data, leaving the benefits of network epidemiology inaccessible to zoonotic disease research and control. As a result, researchers must as- sume that humans and animals mix randomly, or rely on weakly-justified assumptions about stratified risk, when building mathematical models, designing surveillance systems, or planning interventions. There is a critical need to characterize the structure and dynamics of human-animal contact across a range of settings and disease systems, in order to reduce the burden of endemic zoonoses and prevent emergence of novel zoonoses. Our long-term goal is to develop a suite of methods for conducing human-animal network analyses. Our overall objective is to demonstrate proof-of-principle: that analysis of human-animal contact networks is feasible, and results in improved inference. Because emergence of novel zoonotic pathogens is a rare event, we will instead use data from four high-burden endemic zoonoses representing a range of transmission modes: brucellosis, Q fever, leptospirosis, and anaplasmosis. This ensures we will have adequate power to achieve our objective, and contributes to the control of high-morbidity, poverty-reinforcing diseases. Across Dornod and Uvurkhangai prov- inces in Mongolia, we will use an egocentric approach to sampling whereby ego households are randomly se- lected and asked to name alter households: those whose animal herd mixes with their own. In Aim 1, following formative qualitative research we will collect empirical human-livestock contact data using surveys and livestock GPS collars. GPS collars will be placed for five months, during which period network changes will be captured using a monthly husbandry log (household) and a 24 hour contact diary (individual) completed once per month. In Aim 2 we will fit a generative network model to the network data gathered in Aim 1. We will simulate synthetic networks from this generative model, and demonstrate their validity using disease data from real-time qPCR testing and molecular strain typing. Finally, in Aim 3 we will combine these synthetic networks and disease data in an epidemic model of disease transmission, separately for each disease, broadly following an SEIR frame- work. Using these models, we will evaluate the added utility gained by incorporating network structure compared with assuming random mixing. We expect our contribution to be methods for measuring and modeling human- animal contact networks. These will provide the necessary foundation for conducting human-animal network analyses across a range of settings, allowing benefits to accrue through improving the validity of zoonotic disease modeling and generating broad insights on human-animal network structure.

NIH Research Projects · FY 2025 · 2024-09

Project Abstract Cognitive impairment is a significant non-motor symptom of Parkinson's disease (PD). At least 75% of PD patients surviving for more than 10 years will develop Parkinson’s disease dementia (PDD) and the incidence rate of dementia in PD is 4-6 times of the general population. PDD and dementia with Lewy bodies (DLB), jointly known as Lewy body dementia (LBD), are both caused by abnormal deposits of proteins in the brain called Lewy bodies, and account for 4-10% of all dementia patients. Cerebral blood flow (CBF) is considered an important biomarker for neurodegeneration. There remains an urgent unmet need to establish reliable and practical neuroimaging biomarkers related to cognitive functions to describe both the spatial and temporal progression of LBD. Arterial spin labeling (ASL) is a completely noninvasive method for measuring CBF and is ideal for frequent non-invasive longitudinal monitoring. ASL methods typically apply spatially selective inversion modules to supply arteries distant from imaging volumes, which is known to render underestimation of CBF due to transit time delay, especially among elderly subjects. Velocity-selective arterial spin labeling (VSASL) was proposed to remove the time-delay artifact. Our group has implemented the first velocity-selective inversion (VSI) based VSASL with 3D segmented GRASE acquisition and demonstrated its higher sensitivity to perfusion signal over conventional ASL methods. Furthermore, our preliminary data showed that VSASL with 3D single-shot stack-of-spiral-based turbo FLASH acquisition delivered better perfusion image quality with fewer artifacts than using segmented GRASE, and high temporal resolution potentially allowing adequate retrospective motion correction. The overarching goal is to test the hypothesis that the VSASL-based CBF pattern is a reliable biomarker for LBD that predicts long-term cognitive impairment and dementia outcomes: Aim 1, we will conduct further technical developments for 3D VSASL with accelerated acquisitions and improved immunity to head motion; Aim 2, we will assess VSASL’s between- session reproducibility and its reliability to detect regional changes in CBF related to movement tasks and the dopaminergic medication; Aim 3, we will investigate VSASL’s sensitivity to early cognitive impairment in patients leading to LBD through both cross-sectional and longitudinal comparisons. These studies are to ensure the optimized VSASL MRI technique with high reproducibility, reliability, and sensitivity to detect early changes in brain perfusion that are correlated with cognitive impairment and dementia in patients leading to LBD.

NIH Research Projects · FY 2025 · 2024-09

Project Summary Vaginal washing is a common practice that many women perceive as hygienic. However, vaginal washing has been linked to adverse reproductive health outcomes including increased HIV acquisition risk. The mechanism linking vaginal washing to HIV risk remains unknown. Although it has been hypothesized that disruption of vaginal microbiota may mediate the relationship between vaginal washing and HIV acquisition, results of studies evaluating this relationship are mixed. In preliminary studies, we found associations between vaginal washing and higher concentrations of IL-1 in cervicovaginal fluid and CD4+ T cells from cervical biopsy specimens. These associations were independent of the presence of bacterial vaginosis (BV), leading us to hypothesize that vaginal washing may increase HIV susceptibility by causing persistent activation of the IL-1 pathway, recruitment of HIV-susceptible target cells, and disruption of the mucosal barrier. The primary objective of this proposal is to test the hypothesis that a vaginal washing cessation intervention will lower concentrations of soluble inflammatory mediators in cervicovaginal fluid, lower total immune cells in mucosal tissue, reduce cervical epithelial disruption, and increase concentrations of protective vaginal Lactobacillus spp compared to control. These biologic changes have the potential to reduce HIV susceptibility based on substantial evidence that cervicovaginal inflammation, tissue breakdown, the absence of a Lactobacillus-dominated vaginal microbiota, and the presence of suboptimal vaginal bacteria increase HIV susceptibility. To achieve this objective, we will conduct a randomized controlled trial of vaginal washing cessation in a cohort of women who engage in sex work in Mombasa, Kenya, and compare the following outcomes between participants randomized to the intervention versus control arms of the study: i) concentrations of cervicovaginal cytokines, measured using a multiplex bead- based immunoassay (Luminex platform); ii) concentrations of activated CD4+ T cells and antigen presenting cells, measured from cervical biopsy specimens using flow cytometry; iii) expression of mucin and tight junction proteins detected by immunofluorescent staining of fixed cervical biopsy tissue sections and quantified using HALO image analysis software; iv) presence of cultivable Lactobacillus spp; and, v) concentrations of key Lactobacillus spp measured using quantitative polymerase chain reaction. Together, these data will provide mechanistic evidence for a causal link between vaginal washing and HIV acquisition risk and could be used to support expansion of public health programs to reduce vaginal washing and lower HIV susceptibility among populations at increased risk for HIV acquisition, such as women who engage in sex work. Furthermore, the detailed evaluation of the cervicovaginal immune system and mucosa may provide valuable insight into the mechanisms underlying other adverse reproductive health outcomes linked to vaginal washing, including increased risk of BV, sexually transmitted infections, and pelvic inflammatory disease, and reduced fecundability. .

NIH Research Projects · FY 2024 · 2024-09

SUMMARY Aging is associated with a decline in the neural substrates and sensorimotor processes subserving speech motor control. In addition, aging-related neurodegenerative diseases such as Parkinson’s disease may lead to severe motor speech impairments. Prior efforts to incorporate known principles of motor learning into motor speech treatment programs are impeded by the lack of empirical data on how the aging process affects different forms of speech motor learning at both the behavioral and neural level. In my predoctoral work at the University of Washington (F99 phase), my dissertation focuses on two distinct forms of speech motor learning: auditory-motor adaptation and syllable sequence learning. No previous studies have directly compared the neural bases of these forms of motor learning or investigated how they are affected by aging. The central hypothesis of this project is that speech adaptation and syllable sequence learning rely largely on distinct cortical-subcortical networks and, therefore, are differentially affected by the aging process. In Aim 1.1, I investigate the subcortical contributions to both forms of motor learning by comparing individuals with Parkinson’s disease who have DBS electrodes implanted in the subthalamic nucleus (STN) in the cortico-basal ganglia circuit, individuals with essential tremor who have DBS electrodes implanted in the ventrolateral nucleus of the thalamus (Vim) in the cortico-cerebellar circuit, and age-matched control participants. Analyses are based on both behavioral data from DBS ON/OFF conditions and neural data from a subgroup of patients whose DBS device allows sensing from the implanted nuclei. In Aim 1.2, I directly study the effects of aging itself on speech motor learning by using EEG to compare cortical neural activity associated with speech auditory-motor adaptation and syllable sequence learning in healthy older adults versus healthy younger adults. In the postdoctoral phase at the University of California San Franciso (K00 phase), I will then further expand my expertise and skills in aging research as applied to speech neuroscience. In Aim 2, I will focus on multimodal neuroimaging and computational modeling to investigate how sensorimotor neuronal networks in the aging brain support different forms of speech motor learning through functional reorganization, and how such reorganization can be accounted for in computational models of speech motor control. This program of training and research will prepare me for a productive career in aging research and speech neuroscience. Findings from the series of studies will advance our understanding of aging-related changes in the speech sensorimotor system and inform the development of effective behavioral and neuromodulation treatments for aging-related motor speech disorders.

NIH Research Projects · FY 2025 · 2024-09

ABSTRACT More than half of Kenyan children under 5 years (~4 million Kenyan children) will not reach their developmental potential, a pathway partly determined by modifiable maternal risk factors such as stress, infection, and inadequate nutrition in pregnancy and lactation. Maternal factors such as older age, anemia, poor nutrition, HIV infection and depression have been associated with adverse effects on child neurodevelopment, although the quality and strength of the evidence varies. Data on the relationship between maternal factors and human milk oligosaccharides (HMOs), one of the most abundant bioactive molecules in human milk, are all from high-income settings, where the composition of HMOs differs by maternal age, nutritional status, depression, and HIV infection. Limited data exists on the influence of HMOs on child neurodevelopment, including in Sub-Saharan Africa. HMOs and maternal factors may act independenly to influence child neurodevelopment. It is plausible that the maternal factors may impact HMO profiles, and, in turn, influence child neurodevelopment. The proposed F32 research project leverages data from an ongoing cohort ongoing cohort of Kenyan mother-infant pairs (N=350) (Tunza Mwana R01HD096999; 1P01HD107669-01) followed up for 2 years from birth to evaluate the association between maternal HIV infection, milk composition, and the infant gut microbiome, and characterize infant growth and neurodevelopment at 24 months of age. In Aim 1, we will determine how adverse maternal factors in pregnancy (older age, depressive symptoms, anemia, HIV infection, and nutritional status) affect HMO composition at 6 weeks postpartum. In Aim 2, we will determine the association between adverse maternal factors in pregnancy and child neurodevelopmental outcomes at 2 years of age. Finally, in Aim 3, we will assess if HMOs mediate the relationship between adverse maternal factors in pregnancy and child neurodevelopment at 2 years of age. This project will provide new insights on modifiable maternal factors and child neurodevelopment in Sub-Saharan Africa region, and inform ways to prevent or reverse the neurodevelopmental consequences of adverse maternal environment by highlighting the potential mechanisms of neurodevelopmental impairment. The research plan will provide the F32 candidate rigorous postdoctoral training including training in 1) child neurodevelopmental assessment and research 3) content area expertise in breastmilk research 3) advanced statistical methods of epidemiologic research 4) strengthen publication record and communication skills.

NIH Research Projects · FY 2025 · 2024-09

PROJECT SUMMARY A growing number of Americans over the age of 65 live with dementia. A set of devastating neurodegenerative diseases cause dementia, including Alzheimer’s disease (AD) and frontotemporal lobar degeneration (FTLD). Neurofibrillary tangles composed of hyperphosphorylated tau are a pathological hallmark of AD and related tauopathy disorders including FTLD-tau. Several other pathologies also drive neurodegeneration in AD related dementias (ADRD), including the aggregation of the RNA binding protein TDP-43 and expansion-related polyglutamine repeat proteins (PolyQ). While the ultimate molecular mechanisms driving neurodegeneration in AD/ADRD are poorly understood, disruptions to many aspects of nuclear homeostasis in neurons contribute to these age-related diseases, including disruptions to nuclear pore complexes, nucleocytoplasmic transport and, as I have helped to show, nuclear speckles and RNA processing. My published work and preliminary data now also nominate nuclear proteostasis and nuclear ubiquitin proteasome system (UPS) machinery as novel and shared regulators of the early pathogenesis of neurotoxic aggregates and neurodegeneration in AD, FTLD, and Huntington’s disease, an inherited early-onset dementia. I previously showed that genetic deletion of SPOP homolog SPOP-1 rescues significant behavioral deficits, protein aggregation, lifespan defects, and neurodegeneration driven by the microtubule-binding protein tau in a Caenorhabditis elegans model of tauopathy. My preliminary evidence suggests that the activity of C. elegans SPOP-1/CUL-3 nuclear substrate BET-2, homologous to the bromodomain and extraterminal domain (BET) family of transcription factor proteins in humans (BRD2, BRD3, BRD4, and BRDT), underlie these results. My early data also show SPOP modifies TDP-43 and PolyQ neurotoxicity in models of AD/ADRD proteinopathy and is translationally relevant in mammalian neurons and to human disease. Altogether, my work has led us to hypothesize that the degradation of BRD transcription factors is a critical and translationally relevant molecular pathway to neurodegeneration in AD/ADRD. We hypothesize disruptions to nuclear UPS machinery and nuclear proteostasis, in general, are also key contributors to nuclear dysfunction in early disease pathogenesis. To investigate these hypothesizes the specific aims of this project are: SPECIFIC AIMS: (1) Determine the impact and relevance of BRD transcription factor degradation in AD/ADRD. (2) Systematically characterize the impact of nuclear proteostasis machinery in AD/ADRD. By completing the proposed work, we will provide further insight into the biological mechanisms underlying the role of the CUL3/SPOP/BRD axis (F99) and, more broadly, the role of disruptions to nuclear protein homeostasis (K00) in driving neurodegeneration in AD and diverse ADRDs.