Washington University

NSF Awards · FY 2025 · 2025-01

This Major Research Instrumentation (MRI) grant supports the purchase of a 3D printer capable of printing features ranging from the nanometer (billionth of a meter) scale to the micrometer (millionth of a meter) and centimeter scales. It will accelerate research by enabling the advanced manufacturing of tiny devices and machines, fostering new ideas in biology, medicine, physics, and engineering, and furthering national priorities in these areas. To build new knowledge of both natural and engineered systems at the molecular and cellular scales, researchers need to manufacture tools that can interface directly with these systems. Traditional additive manufacturing (or "3D printing") can create arbitrarily shaped objects based on computer models, but most existing printers have limited resolution and are unable to fabricate extremely small and complex structures. This award enables the acquisition of a 3D printer that uses a precision laser beam to print objects from a variety of plastic materials, with feature sizes smaller than human cells. These capabilities will allow researchers to probe cell and tissue behaviors, better understand diseases, enhance chemical reactions, explore the optical, electronic, and thermal properties of materials, and create novel devices and microrobots. The discoveries made will have applications in energy, healthcare, environmental science, and materials science, with the potential to benefit society and the U.S. economy for years to come. As a unique manufacturing resource in the Midwest, this advanced 3D printer will also inform engineering education, including increasing the participation of students in technical disciplines, through its incorporation into training, workshops, and outreach activities to the regional academic community and K-12 students. Among the tools capable of achieving submicron feature resolution, conventional semiconductor processing typically yields "flat" topographies. The resolution of even the best conventional 3D printers is two orders of magnitude larger than what is needed to interface with microscopic structures. Two-photon polymerization laser lithography enables rapid prototyping and wafer-scale production of 3D structures with submicron precision. This technology uses a lower-energy near-infrared laser to solidify the printing material only when photoresin molecules simultaneously absorb the energy of two photons. This 3D printer will create structures ranging from nanometer to millimeter scales across centimeter-sized areas. The diverse research team will (i) fabricate micro-/nanophotonic integrated circuits and optical devices, (ii) explore the fundamental mechanobiology of cells and tissues, (iii) develop stretchable electronics for sensing and measurement, (iv) discover new phenomena in atomically thin materials, and (v) probe the behavior of microswimmers using cell-scale acoustofluidic actuators, among other programs in device physics, transport phenomena, and biology/medicine. Thus, the 3D printer will advance both fundamental and applied research across many fields. 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 2026 · 2025-01

PROJECT ABSTRACT In the United States, adolescent and young adults between 13-24 years account for 20% of the estimated 31,800 new HIV infections. Similarly, adolescent girls and young women (AGYW) aged 15-24 are twice as likely to be living with HIV than young men in Sub-Saharan Africa (SSA). HIV prevention strategies available to AGYW primarily depend on male partner cooperation, limiting the ability for these strategies to reduce HIV spread. Pre-exposure prophylaxis (PrEP) is a highly effective biomedical HIV prevention method, giving AGYW more self-efficacy and agency to minimize HIV risks. However, PrEP is still underutilized due to lack of social support, disclosure concerns, financial costs associated with transport to clinics and food to accompany medication are still major barriers. Peer support interventions and PrEP awareness via peers has been associated with increased PrEP uptake. However, these approaches may not be as effective when delivered alone –given that poverty-associated factors, too, greatly undermine PrEP access, uptake and adherence. Thus, combining multilevel interventions, in this case, combining peer support with economic empowerment (EE) targeting poverty and financial constraints, may offer additive effects to overcome these barriers. Combination multi-level interventions focused on poverty reduction, behavioral health, and HIV treatment outcomes among youth affected by HIV, including AGYW in SSA have demonstrated effectiveness in regard to health services uptake and addressing social determinants of health. We assessed PrEP acceptability in a randomized clinical trial (R01MH116768) that includes HIV risk reduction (HIVRR) sessions and PrEP uptake among 542 women (ages 18+) in Uganda. Among HIV negative women (n=286), 45% declined PrEP, due to inability to adhere to daily medication and fear of stigma. Overcoming these barriers is critical to ending the HIV epidemic. We propose a multilevel combination intervention focused on PrEP initiation and adherence among AGYW living in HIV hotpots in Uganda. Suubi(hope)4PrEP will combine: 1) HIVRR that incorporates sessions on PrEP, 2) peer supporters (PS) with lived experiences taking PrEP to facilitate linkage to and continued care, and 3) EE components targeting financial barriers associated with PrEP access. We will randomly assign 600 AGYW (at the community level) to one of the three study arms (n=200 AGYW, n=10 sites per arm): 1) HIVRR only, 2) HIVRR+ PS, or 3) HIVRR + PS + EE. Specific aims are: Aim 1. Examine the impact of Suubi4PrEP on PrEP initiation and adherence. Aim 2. Examine the effect of Suubi4PrEP on hypothesized mechanisms of change and intervention mediation. Aim 3. Use mixed methods to explore multi-level factors that influence PrEP initiation and adherence using CFIR. Aim 4. Assess the cost and cost-effectiveness of the interventions. Study findings will be relevant to the U.S. HIV epidemic, as multilevel factors influencing PrEP uptake and adherence among Ugandan AGYW are similar to those affecting adolescents and young adults in the U.S. and can help to inform interventions to increase PrEP use and adherence.

NSF Awards · FY 2025 · 2025-01

Multivariate and functional time series are prevalent and routinely collected in many fields. Statistical inference of such time series is a fundamental problem in modern time series analysis and has broad applications in many scientific areas, including bioinformatics, business, climate science, economics, finance, genetics, and signal processing. Compared with existing methodologies, this research project will provide nonparametric inference procedures that can accommodate a wide range of dimensionality and require weak assumptions on the data generating processes. The methodology ensuing from the project will be disseminated to the relevant scientific communities via publications, conference and seminar presentations, and the development of open-source software. The project will involve multiple research mentoring initiatives, including efforts on broadening participation, and will offer advanced topic courses to introduce the state-of-the-art techniques in time series analysis. The project will provide a broad range of interdisciplinary training opportunities at all educational levels and will contribute to the future workforce professional development. The project will develop a systematic body of methods and theory on inference for both multivariate (including high-dimensional) time series and functional time series based on sample splitting (SS) and self-normalization (SN). Recently, the SN technique has been advanced to the inference of high-dimensional time series, but it requires the use of a trimming parameter. Also, its scope of applicability is limited to high-dimensional time series with weak panel dependence which might be unrealistic in many modern time series applications. In turn, the existing SN for functional time series relies on dimension reduction by functional principal component analysis and, hence, the resulting procedure may be powerless when the alternative is orthogonal to the space spanned by the top principal components used in the procedure. To address these major limitations, this project will develop a new unified framework based on SS-SN, in conjunction with inference for multivariate and functional time series, and investigate its utility in application to analysis of time series of low, medium, high or infinite dimensions. 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 2026 · 2024-12

ABSTRACT Damage to myelin sheaths and demyelination of axons is a hallmark of multiple sclerosis (MS) leading to neurological signs and symptoms of MS. Failure to remyelinate is an important factor contributing to disability accumulation in progressive MS. Presently, there is a lack of non-invasive imaging methods to monitor myelin changes and remyelination in preclinical and clinical settings. Formation of new myelin sheaths and remyelination is an energetically demanding process ensured by oligodendrocytes, which is associated with modulation of cerebral metabolism. Lactate has emerged as an important metabolite to promote remyelination as it is used by oligodendrocytes for lipid synthesis and myelin formation. Hyperpolarized 13C magnetic resonance spectroscopic imaging (HP 13C MRSI) is an innovative metabolic MR method that enables to monitor enzymatic reactions in vivo in real-time. This method opens new avenues to investigate metabolic alterations and lactate metabolism during successful/unsuccessful remyelination. Although quantification of myelin levels using noninvasive means remains challenging, a recently developed acquisition scheme combining ultra-short echo time and magnetization transfer (UTE-MT) has shown high sensitivity to myelin content in both white and grey matter areas in a demyelinating MS mouse model. However, UTE-MT imaging has not yet been applied to study early remyelination and therapy response. In this project, we propose to investigate the potential of HP [1-13C]lactate and UTE-MT imaging to non-invasively study the role of lactate metabolism and remyelination in two MS mouse models with different remyelination capabilities, during disease progression and following response to a remyelinating therapy. To do so, HP 13C MRSI and UTE-MT imaging sessions will be performed at key time points during lesion formation and during spontaneous recovery/remyelination. Next, HP [1-13C]lactate and UTE-MT will be used to evaluate treatment response from a remyelinating therapy to investigate HP [1-13C]lactate and UTE-MT potential to serve as biomarkers of repair. MRI findings will be confirmed using ex vivo correlates of enzyme activities and histopathological markers for myelin and lesion characterization. Development and validation of the MR imaging tools proposed here has high potential to increase our knowledge on mechanisms involved in remyelination success and failure. Importantly, because the methods developed here are clinically translatable, they hold great promise to providing new tools for diagnosis and monitoring of therapies in MS, and helping define optimal therapeutic windows to speed up repair and prevent disability accumulation.

NIH Research Projects · FY 2026 · 2024-12

The NRF2 transcription factor is active in more than 30% of head & neck squamous cell carcinomas (HNSCC), owing to pathway activating mutations and mutation-independent mechanisms. NRF2 drives a gene expression program that mitigates oxidative and electrophilic stress, reprograms and enables cancer cell metabolism, and suppresses immune cell infiltration. In HNSCC patients, NRF2 activity portends a poor prognosis; its mutational activation is predictive for resistance to radiation and local regional failure. Though frequently active in human cancers, mouse models suggest that constitutive NRF2 activity is not sufficient for oncogenesis, but rather NRF2 synergizes with oncogenes and tumor suppressors to drive tumor progression. Despite great need, proven and efficacious NRF2 therapeutic inhibitors do not yet exist in the clinic. This revised application is a response to PAR-22-198, the Precision Approaches in Radiation Synthetic Combinations (PAIRS) program. We hypothesize that chemical suppression of NRF2 activity will sensitize HNSCC to RT. Our previous functional genomic, proteomic, and small molecule screens revealed therapeutic targets and pharmacological agents that suppress NRF2 activation in HNSCC. Here we focus on two in vivo efficacious, potent and mechanistically distinct NRF2 chemical inhibitors. First, we previously reported the ANCHOR class of KEAP1 mutants which maintain enzymatic activity for NRF2 ubiquitylation but fail to degrade the NRF2 protein. Working with Vividion Therapeutics, we sought cysteine-reactive molecules to reverse the ANCHOR phenotype. This resulted in VVD065, a highly selective and potent small molecule that induces NRF2 ubiquitylation, degradation and radiosensitivity. Second, our drug screens discovered pyrimethamine (PYR), a FDA approved medicine, as an efficacious inhibitor of NRF2 signaling. When administered to our genetically engineered mouse model (GEMM) carrying an inducible activating NRF2E79Q mutation, PYR reversed esophageal and oral cavity hyperplasia with no observed toxicity. Subsequent structure-activity-relationship optimization resulted in 30-fold more potent small molecule we call WCDD115. Because NRF2 activity drives resistance to radiation therapy (RT), our primary goal is to leverage these two novel NRF2 inhibitors as synthetic combination agents for RT in human and mouse models of HNSCC. Importantly for this work, we recently reported the first NRF2-driven GEMM of spontaneous oral SCC. Our proposed experiments use human HNSCC xenografts, mouse syngeneic tumor grafts, our NRF2- driven oral cavity SCC GEMM, and human and mouse 3-D spheroid cultures to test if VVD065 or PYR/WCDD115 synthetically combine with RT to suppress tumor growth while minimizing toxicity to normal tissues. We will also identify patient stratifying genotypes predictive of susceptibility to NRF2 chemical inhibition and RT sensitization. Together, these studies will produce foundational data for the dosing, scheduling, efficacy and toxicity of NRF2 inhibitors as synthetic combination agents with RT in pre-clinical HNSCC models. The impact of this research will be an improved response of HNSCC to radiation therapy.

NIH Research Projects · FY 2026 · 2024-12

SUMMARY Circadian rhythms are daily variations in biological function that adapt physiology to the earth’s day-night cycle18, 19. They arise from a hierarchal system consisting of a master pacemaker in the CNS that synchronizes autonomous circadian “clocks” found within all nucleated cells20, 104. Mounting evidence indicates the circadian system is important to medical interventions18, 19, 29. One reason for this is that circadian clocks temporally organize basic immune processes 2, 31, 32. Another reason is that circadian clocks regulate cellular defenses to metabolic and oxidative stress as occurs during ischemia-reperfusion injury46-49. Together, clock control of immunity and ischemic responses have implications for solid organ transplantation4-7, 105, 106. There is clinical evidence that the risk of solid organ graft dysfunction varies with the time of surgery4-7. However, prior studies of biological rhythms in transplantation do not examine biological mechanisms and focus almost exclusively on the transplant recipient. In this application, we show that brain-dead organ donors frequently exhibit rhythms in core body temperature and cortisol. They also exhibit functioning circadian clocks in transplantable organs like the lungs. Moreover, data in mice suggest that donor clocks and recipient clocks both are important for organ acceptance. Deleting the master clock gene Bmal1 in transplanted lungs or lung graft recipients exacerbates primary graft dysfunction (PGD), a form of ischemic lung injury. Finally, data suggest a pathway for these effects involving clock control of neutrophil glycolysis, which in turn regulates neutrophil extracellular trap (NET) formation. The goal of this proposal is to characterize circadian rhythms in organ donors and to identify mechanisms by which clocks in organ donors and recipients affect transplant acceptance. We focus here on the lung since long-term survival after lung transplantation remains poor (median of about 5 years9), and needs new approaches. Aim 1 will generate an atlas of brain-dead organ donors' biological rhythms and circadian clock function. It will also develop a spot assay to infer circadian clock time and robustness in donors. These experiments leverage a unique collaboration with Mid-America Transplant Services (MTS), a high-volume regional organ procurement organization in our area. Aim 2 will examine how the regulation of donor neutrophil glycolysis by master clock gene Bmal1 contributes to lung PGD. This Aim will employ an established mouse orthotopic lung transplant model to induce PGD in the presence or absence of Bmal1 or circadian clock disruption via chronic jet lag. Together, these two independent but complementary Aims will pioneer the study of biological rhythms in organ donors. It will characterize a novel immune-metabolic mechanism with the potential to improve transplanted organ acceptance. It directly answers NIH research priorities described in NOT-HL-22-043: Basic and Translational Research on Circadian Regulation of Heart, Lung, Blood, and Sleep Disorders.

NIH Research Projects · FY 2026 · 2024-12

This project will develop three new multi-modal atlases based on high resolution Human Connectome Project (HCP) data and its precise methods. 1) The project will create a new data-driven atlas of spatially overlapping weighted grey-matter functional networks, side-stepping current limitations in non-weighted, non-overlapping atlases of functional networks and compare to the prior literature. 2) The project will create a new data-driven atlas of white matter tracts and their corresponding grey matter projection territories and compare these results to traditional ROI-based atlases, which may have biases or have missed tracts. 3) The project will complete the semi-automated multi-modal atlas of human brain areas, building upon the HCP’s prior map of 180 neocortical brain areas per cerebral hemisphere to include the non-neocortical brain areas using surface-based and volume- based methods as appropriate with extensive comparison to the prior neuroanatomical literature. The end result of successful completion of this project will be complete, integrated atlases of human grey matter brain areas, functional networks, and white matter tracts, which will have intrinsic value, e.g., for neurosurgical planning. These atlases and the automated methods for regenerating them in new subjects will enable measuring multi- modal imaging derived phenotypes (IDPs) for HCP-Style neuroimaging data across the whole brain. By collaps- ing non-independent statistical tests within neuroanatomically well-defined brain structures and averaging out random noise, such IDPs will have improved statistical sensitivity and power. This generically useful approach has the most promise for creating interpretable imaging biomarkers useful for elucidating the mechanisms behind both healthy brain aging and Alzheimer’s Disease (AD) and Alzheimer’s Disease Related Dementias (ADRD). Each aim of the project will have a technology development sub-aim (part a) to develop or improve upon the needed methods for generating that aim’s atlas. Then the atlas will be created using data from the young adult HCP (part b) and the findings will be integrated across the 3 aims (i.e., direct comparison and cross-annotation between the atlases of brain areas, grey matter functional networks, and white matter tracts). Finally, we will produce automated pipelines to regenerate the atlases in the data of the HCP Aging project, the Adult Aging Brain Connectome (AABC) project, and the Alzheimer’s Disease (AD) and Alzheimer’s Disease Related Demen- tias (ADRD) Connectomes Related to Human Disease (CRHD) projects, to disaggregate the data by sex, and to generate multi-modal IDPs based on these atlases, pipelines that external investigators can also use in their own studies. These atlases and IDPs will then feed into five ongoing projects studying Alzheimer’s Disease (AD) and Alzheimer’s Disease Related Dementias (ADRD), four that are subprojects of the AABC and an R01 that is working on the AD/ADRD CRHD data. Overall, the proposal will address three key gaps in the current HCP atlases and IDP generation pipelines to accelerate innovation and discovery in the neuroimaging field.

NIH Research Projects · FY 2026 · 2024-12

ABSTRACT Recent work suggests that motor differences in infancy can predict subsequent ASD diagnosis, with the promise of earlier identification of ASD, and faster referral to early intervention than is currently possible. However objectively quantifying these differences has proved challenging. Here we will address this question by leveraging dramatic recent progress in deep learning-driven image processing, combined with emerging techniques in the new field of computational ethology. As a proof of concept, we will apply these techniques to a rich, longitudinal video dataset of semi-structured behavioral assessments on the Autism Observation Scale for Infants (AOSI) from all four sites of the Infant Brain Imaging Study (IBIS). Together this includes videos of more than 400 infants. In Aim 1 we will use OpenPose, a recently developed algorithm for human pose estimation, to automatically extract the location of key infant body joints from each frame of these videos, and then use customized deep-learning approaches to track the movement of the infant from frame to frame. In Aim 2 we will leverage the 24-month diagnostic status and familial liability data to validate the multidimensional computer vision-extracted kinematic data obtained in Aim 1 as ASD motor-function biomarkers. In Aim 3 we will apply unsupervised computational ethology techniques to reveal signatures of ASD in fine motor behavior that will generalize beyond the AOSI paradigm. This will result in a quantitative, precise and naturalistic description of infant motor behavior suitable for predicting ASD diagnosis and severity. By bringing together a computational neuroscientist expert in image processing and behavioral analysis, a clinician-scientist expert in the early development and assessment of autism, and an expert in infant motor development and infant sibling studies for ASD, this work will provide an unbiased and scalable approach to quantifying and categorizing ASD motor function deficits across development, thus critically facilitating high quality and accessible early ASD diagnosis.

NIH Research Projects · FY 2026 · 2024-12

PROJECT SUMMARY/ABSTRACT Heart failure (HF) is a leading global public health problem. The burden of HF is increasing in low- and middle- income countries and clinical outcomes remain poor. Guideline-directed medical therapy (a combination of distinct medications from disparate drug classes) improves morbidity and mortality in patients with HF with reduced ejection fraction (HFrEF). Despite this high-quality evidence, guideline-directed medical therapy remains widely underutilized globally and specifically in India. This gap represents a key target for intervention to save lives. Dr. Agarwal’s K99/R00 proposal aims to substantially simplify HF management by shifting the treatment paradigm for undertreated patients with HFrEF from multi-drug therapy with sequential initiation and titration to a novel late-stage implementation strategy of a HFrEF polypill of guideline-directed medical therapy including a beta-blocker, angiotensin receptor blocker, and mineralocorticoid receptor antagonist. First, Dr. Agarwal will conduct formative mixed methods research including a HF treatment consensus meeting and focus group discussions to guide development of the HFrEF polypill-based strategy in India. Second, she will evaluate whether, compared to usual care, a HFrEF polypill implementation strategy will reduce cardiovascular disease mortality and HF hospitalizations at 12 months in adults with HFrEF in India using a multi-center, type I hybrid randomized clinical trial design. She will also assess the effect of the HFrEF polypill implementation strategy on important secondary outcomes including medication adherence, markers of HF disease severity, health-related quality of life, and safety measured by adverse events. Finally, Dr. Agarwal will apply methods of process evaluation to assess implementation outcomes of the HFrEF polypill in India, a key step in translating evidence generated into broader use globally. The K99 phase will also provide essential methodological training for Dr. Agarwal to transition to research independence in the R00 phase. Dr. Agarwal proposes training in 1) implementation science methods, 2) clinical trial methods including innovative platform trial designs, and 3) regulatory science for global pharmacological clinical trials. This K99 training will prepare her to be a leading clinical trialist in global heart failure implementation science. Dr. Agarwal’s global mentorship team is led by Dr. Mark Huffman (Northwestern University, US), with key co-mentorship provided by experts in cardiovascular clinical trials in low- and middle-income countries, Drs. Dorairaj Prabhakaran (Centre for Chronic Disease Control, India) and Anushka Patel (The George Institute for Global Health, Australia). This mentorship team, supported by key collaborators (Drs. Hirschhorn, Mohanan, Ciolino) and advisors (Drs. Yancy, Lloyd-Jones), will ensure scientific success and oversee the candidate’s advanced training in their relative areas of expertise. This K99/R00 proposal supports Dr. Agarwal’s transition to launch an independent career as a future leader in global, late-stage translational cardiovascular research. Importantly, this proposal has the potential to transform HF care through simplified care in India and other settings, including in the United States.

NIH Research Projects · FY 2026 · 2024-12

Progress has been made over the last decades in the treatment of non-Hodgkin lymphoma (NHL) with several therapies recently FDA-approved, including CD19 CAR-T cells, bispecific antibodies targeting CD20 and CD3, and anti-CD79b antibody-drug conjugates (ADC) but over 20,000 people will die of NHL in the US in 2024. There remains a critical unmet need for innovative, active and accessible therapies of NHL. Radioimmunotherapies (RITs) targeting CD20 (Zevalin® and Bexxar®) received FDA approval two decades ago in follicular and some transformed B-cell lymphomas. These first-generation RITs used immunogenic murine antibodies and were only administered in a single dose in non-myeloablative regimens. While safe, well-tolerated, and active, these treatments were not major commercial successes for several reasons, including economics. Also, 131I and 90Y are suboptimal due to unfavorable high-energy γ-emissions or a long β-particle path length poorly suited to low-burden residual disease, respectively. Given the continued unmet medical needs, additional treatment approaches must be obtained for NHL. To address these unmet needs, we will develop precision next-generation RIT for NHL that we anticipate will result in more cures. Our studies draw on our extensive experience in first-generation NHL radioimmunotherapy (of which the PI was an inventor) and our recent exciting preclinical work with next-generation fully-human anti-CD20 RITs. We will develop and evaluate novel, precision radiopharmaceutical therapies for NHL using preclinical models. In Aim 1), Next-generation anti-CD20 radioimmunotherapies for NHL will be evaluated using single agent and combined β-(Lu177) and α-particle-(Ac225)-emitting labeled ofatumumab in disseminated and solid tumor murine models. These studies will determine how to best utilize these α- and β-particle emitting RIT as single agents with single or multiple doses, or in combination to cure lymphoma. In Aim 2), New α-particle anti-CD20 RITs will be developed and assessed, evaluating both short- lived higher dose-rate (Pb212, t½ 10.6 hr) and long-lived, lower dose-rate (Th227, t½ 18.7 d) α-particle- emitters for NHL RIT in mouse tumor models. Comparative evaluation of multiple α-particle RITs is novel, significant, and clinically relevant. In Aim 3), a highly-innovative approach of combined dual-targeted therapy for NHL will be developed and evaluated for mechanism and for therapeutic efficacy, using an anti-CD79b antibody-drug conjugate, Polivy®, as a radiosensitizer for CD20-targeted RIT. This important, selective and novel dual- targeted approach, with mechanistic studies and therapeutic studies, should improve lymphoma curability and is expected to be broadly generalizable to other tumor types. Together, we expect our precision, next-generation RIT approaches to lead to human translation, facilitating more cures of patients with otherwise incurable NHL.

NIH Research Projects · FY 2026 · 2024-12

PROJECT SUMMARY/ABSTRACT In the past decade, significant progress has been made in identifying genetic variants associated with neurodevelopmental and psychiatric disorders like autism, schizophrenia, and intellectual disability. However, understanding how these genes affect brain function and contribute to disease remains a challenge due to the diverse experimental approaches used. To address this, we have assembled the Washington University Scalable Mouse Assay Center (WU-SMAC), an Assay and Data Generation Center (ADGC) for the SSPsyGene consortium. We will comprehensively investigate the impact of prioritized mutations known to cause neurodevelopmental and psychiatric disorders using over 100 mouse lines. Through a combination of behavioral analysis, anatomical mapping, and molecular assessments, our project seeks to uncover the molecular and spatial changes in the brain caused by these mutations and their subsequent effects on behavior. We will deeply assess the phenotype of each mutant using high-content, machine-learning driven behavioral analysis, automated home-cage monitoring of learning behavior and cognitive flexibility, and careful single nucleus & spatial transcriptomics. We will coordinate data serving and distribution with the other ADGCs and Data Resource and Administrative Coordination Center, and provide a unique mouse neuropsychiatric disease brain bank for the entire consortium to enable the replication of findings from other ADGC's systems within the complex milieu of a fully developed mammalian brain.

NIH Research Projects · FY 2026 · 2024-12

PROJECT SUMMARY / ABSTRACT The goal of the proposed research is to develop and validate a reliable clinical decision support tool (e.g. prediction model) for early risk stratification for cochlear implant (CI) speech perception performance. Hearing loss (HL) is the fourth most common disability worldwide, it considerably affects a patient’s quality of life (QOL), directly linked to cognitive decline, and it poses an enormous financial burden to society (~$980 billion/year).1 CI has become the standard of care for patients that no longer benefit from hearing aids. However, despite the enormous success of CIs, there is a wide inter-individual variability with respect to clinical and biological features and their impact on post-implantation speech perception performance. The heterogeneity in CI performance outcomes is a pervasive challenge for clinicians and families, as the management of poor CI performers is largely reactive, without reliable clinical decision support tools for early risk stratification and/or prognostic assessment at time of CI. If available, such predictive models would provide critical opportunity for risk stratification to improve patient counseling, recommendations for auditory rehabilitation, considerations of device-related underperformance (e.g., mapping, troubleshooting, early device failure), and ultimately future CI clinical trials. There is a critical need for better clinical decision support tools for early risk stratification and prognostication of CI performance. Traditional approaches have shown limited success because we often focus on one or two clinical or biological markers to stratify CI performance trajectory, hindering progress in the development of precision medicine delivery. Second, traditional approaches have shown limited success because current preoperative factors can only account for 10-20% of the observed variance.3,4 In response to these challenges, we propose to develop models to support clinical decision making by (1) integrating novel biomarkers that better account for the variability in CI performance including electrocochleography (ECochG), patient comorbidities, and social determinants of health; and (2) utilizing artificial intelligence (AI)-based approach to analyze how multiple clinical and biological markers interact, are associated with sub-phenotypes of CI performance, and can be used to develop superior decision support tools / prediction models. My long-term goal is to be an independent physician-scientist and deploy innovative and autonomous AI-based decision support tools that can seamlessly integrate multiple variables to improve delivery of precision medicine in CI patient care. This K23 will provide me with the protected time required to develop unique skillsets in AI-based techniques in healthcare, quantitatively compare to modern regression techniques to understand translational clinical value gained, and mixed methods research to improve implementation of AI-based precision medicine models. The proposed research program addresses the mission of the NIDCD Auditory Strategy Themes 3 through 6: to promote precision medicine approaches, to translate and implement scientific advances, to facilitate best practices in biomedical data science, and to harness advanced technology.5

NSF Awards · FY 2024 · 2024-12

Weather and climate extremes profoundly impact human society and the natural environment of all countries, rich and poor. Recent years have seen a number of large losses of life as well as a tremendous increase in economic losses from weather hazards. The start of 2020 found Australia amid its worst-ever bushfire season, following on from its hottest year on record which had left soil and fuels exceptionally dry. The fires have burned through more than 10 million hectares, killed at least 28 people, and left millions of people affected by a hazardous smoke haze. Higher sea temperatures have doubled the likelihood of drought in the Horn of Africa region. Severe droughts have left 15 million people in Ethiopia, Kenya and Somalia in need of aid, and millions of people are facing acute food and water shortages. In the summer of 2020, the West Coast of the U.S. saw its most catastrophic wildfires following the arguably most intensive heat waves in its modern history. According to NOAA’s report (2020), just during the month of August in 2020 the U.S. was hit by four different billion-dollar disasters: two hurricanes, huge wildfires, and an extraordinary Midwest derecho. While extreme weather is a part of the natural cycle, the recent uptick in the ferocity and frequency of these extremes is evidence of an acceleration of climate impacts. This project will support one graduate student each year of the three year project. This project will develop statistical and machine learning methods to study weather and climate extremes from three different perspectives: climate model validation, changepoint estimation for extremes, and integration of multi-model climate ensembles. Climate models are vital tools for scientists studying climate dynamics and extremes. Hence, validating climate models in their capacity of mimicking real climate extremes is a critical task. This involves comparing the modeled and observed spatial extremes, and adjustment for multiple testing is one of the key statistical challenges in comparing random fields. We will develop optimal statistical techniques for comparing the return levels of two spatial extremes random fields. The detection of changepoints and estimation of break time in extreme weather and climate have not received due attention to date, yet changepoints can signal a climate system’s tipping point and thus are important for disaster preparedness and activation of adaptation measures against climate risks. We will also develop a novel method for estimating spatially varying changepoints for functional time series to study abrupt changes in climate extremes. Finally, an array of methodology for multi-model ensemble integration has been developed, ranging from simple or weighted averaging of the models to fully Bayesian hierarchical models. The multiple levels of hierarchy in Bayesian models motivated us to take advantage of neural networks to learn the complex relationship between different climate models and actual observations. Finally, we will develop a Bayesian machine learning approach to integrating model outputs with observations to project future climate extremes. 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 · 2024-12

This doctoral dissertation research project undertakes archaeological research to study hunting and animal herding in arid steppe ecosystems. Understanding the deep history of grassland adaptations and economies is of importance because grasslands cover forty percent of the earth’s surface and are under significant environmental and anthropogenic pressures. This project specifically focuses on examining a long-term human-environment relationships in the world’s most expansive grassland. For thousands of years, animal herding has been the dominant mode of survival in this region, making it key to understanding how farming and herding spread across different environments in ancient times. Commonly viewed as a homogenously arid and landmass, grasslands consist of a complex mosaic of rich environmental pockets with extremely diverse plants and animal inhabitants well adapted to this environment. Although well documented in an ecological sense, very few archaeological studies focus on the use of these resource-rich micro-regions and their importance in facilitating sustainable and successful human occupations. This lack of detailed, micro-environmental archaeological research is especially notable in marginal open steppe environments. Archaeologists do not yet fully understand how humans interacted with and adapted to the dry steppe environment using hunting and animal herding. Of equal importance, this study also has far-reaching methodological implications for the practice of archaeology in grasslands globally. This project contributes to the identification of micro-environments with satellite imagery and develops methods for using zooarchaeological proxies for paleoenvironmental reconstruction. This research specifically investigates: (1) how and when people first started herding animals; (2) how hunting and herding economies evolved over the past twelve thousand years; and (3) how such changes were influenced by the availability of resources. An animal bone dataset is analyzed using four interdisciplinary methods: First, morphological analysis to identify type of animal species present; Second, stable isotopic analysis of ancient animal teeth to study animal diet (influenced by factors such as foddering) and herding patterns; Third, zooarchaeology by mass spectrometry, in order to identify species of highly fragmentary bones; Fourth, radiocarbon dating for tracking the timing of environmental adaptations such as hunting and animal herding. 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 · 2024-11

Hydrogen proton-exchange membrane fuel cells (PEMFCs) are vital for future vehicle electrification, particularly in heavy-duty and long-range transportation applications, due to their high-energy density and high efficiency. However, the expensive and scarce platinum catalysts hinder the widespread applications of PEMFCs and should be replaced by earth-abundant elements. Atomically dispersed and nitrogen coordinated transition metal sites (e.g., iron, cobalt, and manganese) embedded in carbon have emerged as promising low-cost air cathodes in PEMFCs. One technical barrier concerning the catalyst’s use is that their intrinsic activity is difficult to transfer in the membrane electrode assemblies in actual hydrogen fuel cells because of insufficient stability, low catalyst utilization, severe carbon corrosion, and inferior mass transport. This project's outcomes will advance the knowledge of designing sustainable and earth-abundant catalysts and their integration into high-performance electrodes for hydrogen fuel cells and other electrochemical energy technologies. Such inexpensive and clean energy technologies directly benefit transportation electrification and grid-scale renewable energy storage and conversion, which are essential for energy and environmental sustainability. The joint project also provides excellent opportunities for education and outreach activities associated with hydrogen energy science and technologies for under-representative students in southern Louisiana and western New York. The collaborative project aims to incorporate highly active single metal site catalysts into fibrous electrodes via electrospinning approaches to establish favorable and robust three-phase interfaces for efficient air cathodes. The electrospinning technique could also construct effective nanofiber-based morphology and ensure sufficient meso- and macro-porosities in catalytic layers for efficient mass/charge transports and critical proton conductivity, leading to significant performance and durability improvements. The ligand coordination environments and local carbon structures of atomically dispersed active metal sites will be regulated through controlling catalyst precursors and electrospinning polymers. Innovative strategies will be developed to construct fibrous electrode architecture with balanced porosities and morphologies for favorable mass/charge transport, uniform ionomer dispersion, maximized catalyst utilization, and improved stability. The fundamental knowledge and understanding gained from this project include the rational design of catalyst precursors in boosting intrinsic activity and site density based on innovative metal-organic frameworks, the correlations between chemistry and structures of polymer fibers and the derived carbon nanostructure and morphologies, and the precise control of the pore structures and geometry of the derived carbon nanofibers within the three-dimensional air cathodes. 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 2025 · 2024-10

This application is a new submission extending prior research funded by HL102482, initially funded in 2009 to identify the genetic basis for inter-individual variation in platelet function that contributes to ischemic occlusion of arteries. We generated a human reference platelet transcriptome, developed a public, user-friendly interactive web tool to query platelet function and RNA-protein associations, and discovered platelet aggregation through the protease activated receptor-4 (PAR4) thrombin receptor was greater in blacks than whites. We showed this difference was due to a PAR4 Ala120Thr substitution with racially divergent allele frequencies (Thr120: .63 blacks; .19 whites). The Thr120 variant had increased sensitivity to thrombin and demonstrated ex vivo thrombus formation under arterial, but not venous, shear stress. Genotyping >12,000 patients demonstrated the Thr120 allele was associated with an increased risk of ischemic stroke and less bleeding. More recent work has led to new data relevant to basic and clinical aspects of platelet PAR biology, and the overall goals of the current application are to study (1) PAR4 interactions with other GPCRs and proteases and (2) the effect of human PAR4 (hPAR4) and the Ala120Thr variant in an in vivo model of brain ischemia/reperfusion (I/R) injury. PAR4 has slower signaling kinetics than PAR1, and our new data shows that PAR4 co-immunoprecipitates with platelet PGI2 receptor (IP). Compared to PAR4 Ala120, Thr120 is relatively resistant to desensitization in the presence of prostacyclin (PGI2), and generates less cAMP after activation in human platelets and primary megakaryocytes (MKs). We hypothesize IP cross-talks with PAR4, and Aim 1 will assess the role of IP/Gas in PAR signaling and desensitization in genetically altered human MKs and platelets from our novel humanized PAR4 mouse lines. The neutrophil serine protease, cathepsin G (CatG), is a potent platelet agonist that activates platelet PAR4, but not PAR1, and we show CatG induces more platelet activation of PAR4 Thr120 than Ala120. For the first time, we identified CatG enzymatic cleavage sites in PAR4, one of which generates a novel tethered ligand, SRALLLGWVPTR, which induces human platelet aIIbb3 activation, granule release and aggregation. Aim 2 will study CatG-platelet PAR4 interactions. Platelet PAR4, not PAR1, is critical for leukocyte recruitment, rolling and adhesion, and our preliminary data show that murine brain I/R injury in our humanized PAR4 mouse line is hPAR4- and neutrophil-dependent. The role of hPAR4 in stroke and brain hemorrhage after I/R injury has been poorly studied, and the goal of Aim 3 is to utilize our hPAR4 mouse lines to determine how hPAR4 mediates platelet and neutrophil activities in a murine stroke model, and to assess the pharmacogenetic effect of the Ala120Thr variant on hPAR4-mediated infarct, hemorrhage and platelet signaling pathways. Successful completion of the proposed studies is expected to enhance the understanding of the molecular basis of inter-individual variation in human platelet biology and PAR4-expressing tissues, and provide groundwork for individualized anti-platelet therapies in disorders with racial predilections.

NSF Awards · FY 2024 · 2024-10

This project is co-developing Radio Frequency (RF) architectures, analog computing algorithms, and compute-in-memory architectures for code-domain, Multiple-Input / Multiple-Output (MIMO) radar systems. This cross-layer project reimagines the boundary between analog and digital signal processing by moving code-domain radar processing operations closer to the RF frontend. This enables low-power and ADC-free architectures, supporting scaling to large MIMO arrays. The code-domain radar signals will be processed at Gigahertz rates in the analog domain using cross-correlators that operate using a margin-propagation paradigm, resulting in lower power and compute latency. A compute-in-memory (CIM) architecture reduces the data transfer between the high-speed memory and the correlator sub-systems. The proposed approach is expected to achieve a 10-100x reduction in power consumption, and 5x lower compute-time per frame compared to conventional radar systems. The project also aims to prototype a low-power, high-performance radar system-on-chip using commercial Complementary Metal-Oxide-Semiconductor (CMOS) technologies to demonstrate both the cost-effectiveness and the scalability of the proposed approach. The advancements in MIMO radar technology can significantly enhance detection range and target discrimination, improving safety and efficiency in various applications, such as autonomous vehicles, drone navigation, aviation, and security systems. The reduction in power consumption makes these systems more environmentally friendly, reduces the cost of thermal management, and enables their deployment in power and cost-constrained environments, such as in situ sensing and portable devices. Furthermore, the project’s success in demonstrating highly efficient cross-correlations can pave the way for broader adoption of analog computing in edge devices, addressing critical power and latency constraints in real-time applications. Ultimately, this research promises to make technology more accessible, reliable, and sustainable, contributing to public safety advancements and environmental monitoring. The education and workforce development activities within the project will focus on widespread dissemination, broadening the STEM workforce and deepening cross-domain expertise in software-hardware codesign. 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 Washington University in St. Louis (WashU) ADVANCE Institutional Transformation (IT) project called AIM for Equity (Activating Intersectionality through civic Mindfulness for Equity), will target systemic causes of inequity for STEM faculty identified by the institution. The project includes institution-wide efforts to empower department heads and school leaders with knowledge to develop and implement evidence-based faculty policies and practices that create supportive and inclusive academic workplaces and improve work-life balance and job satisfaction. Other components will focus on improving STEM faculty recruitment, retention, tenure and promotion policies to align with the mission and long-term goals in WashU’s 2022 "Here and Next" ten-year strategic plan. The project will draw on concepts of civic mindfulness to scaffold change, ultimately creating an organizational climate and culture where faculty of all backgrounds and social identities can succeed and thrive. The innovation in this IT project is the focus on "civic mindfulness," which is conceptualized as collective responsibility for institutional success. AIM for Equity will pursue culture change by fostering empathy, compassion, and shared accountability among faculty and leaders. The AIM for Equity model of civic mindfulness incorporates cultural humility and anti-racism. This approach is expected to have positive outcomes for all faculty, but particularly women and faculty at the intersection of multiple marginalized social identities. The project will study the benefits of addressing community care and shared responsibility to promote systemic change and equity in STEM academic workplaces. The mindfulness programming is intended to be a model that could be adapted by other organizations/academic institutions. The project includes social science research comparing private institutions’ responses to external forces requiring the implementation of pay transparency policies and practices. Resources, findings, and outcomes will be disseminated internally and publicly through a dedicated website, social media, presentations and convenings, and external publications. The NSF ADVANCE program is designed to foster gender equity by identifying and eliminating organizational barriers to the full participation and advancement of diverse faculty in academic institutions.  These barriers to equity may exist in policies, processes, practices, and the organizational culture and climate. ADVANCE "Institutional Transformation" awards help develop and test new systemic change strategies for gender equity in institutions of higher education. 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 2026 · 2024-09

PROJECT SUMMARY Nanomaterials fabricated from de novo designed peptides, which self-organize into cross-b-rich nanofibers, are a class of molecules with numerous promising applications. Such applications could include the development of therapeutic or prophylactic vaccines against disorders associated with protein aggregation. Synthetic peptide nanofibers (PNFs) exhibit intrinsic self-adjuvanting properties and can efficiently raise antibodies against antigens conjugated at their N- or C-termini. Investigations into the mechanism and safety profiles of PNFs indicate that despite their molecular, structural, and morphological similarity to cross-b-rich pathological amyloids, PNFs are non-toxic and non-amyloidogenic. Further, PNFs induce innate immune signaling mechanisms that drive strong non-inflammatory ‘Th2-type’ antibody responses. This is significant for the development of vaccines against neurodegenerative diseases such as Alzheimer’s disease (AD) and frontotemporal dementia (FTD), which disproportionally impact aged individuals who are known to have an impaired immune response due to inflammaging. A key difference between developing infectious disease vaccines and vaccines for AD/FTD is that amyloid-beta (Aβ) and Tau proteins implicated in AD/FTD pathologies are self-antigens. To subvert this tolerance, vaccines targeting Aβ/tau are mixed with adjuvants that induce strong inflammation to induce robust antibody titers. Data from clinical studies indicate that proinflammatory immune responses can aggravate pre-existing neuroinflammation in AD and lead to serious side effects like encephalomyelitis. Studies show that in contrast to younger adults, adjuvant-related inflammation obstructs immune responses in older adults and that this effect can be mitigated by delivering anti-inflammatory therapies. Here we propose the development and preclinical testing of self-adjuvanting PNF vaccines targeting Aβ and Tau. Due to the modular nature of self-assembly, the same self-assembling domain linked to different conformers of Aβ and Tau can be mixed to improve the breadth of protection against AD/FTD. We hypothesize that i) PNFs bearing Aβ/Tau epitopes do not seed the formation of toxic oligomeric species, that ii) nanofibers bearing Aβ or Tau epitopes will elicit robust titers of functional antibodies in mice, and that iii) vaccination with nanofiber-based vaccines will rescue neuropathology and delay onset of dementia in transgenic mouse models of AD/FTD. Thus, we will meet the following aims: 1) Assess toxicity and seeding capacity of PNFs bearing Aβ and Tau epitopes, 2) Perform quantitative and qualitative characterization of antibody responses to Aβ and Tau PNF vaccines, and 3) Develop multiepitope Aβ and Tau PNF vaccines and determine their efficacy in transgenic mouse models. Upon successful completion of this project, we will establish peptide nanofibers as a safe and effective vaccine platform for inducing non-inflammatory and protective antibody responses against AD/FTD.

NIH Research Projects · FY 2025 · 2024-09

ABSTRACT Psychological symptoms are common when fighting an infection: Illness causes both physical and mental fatigue and loss of motivation. Such symptoms are harmless when they are transient during acute illnesses, such as the flu. However, chronic inflammatory disorders, including cachexia and endometriosis, produce similar but intensified behavioral disturbances, manifesting as extreme fatigue and depression. This phenomenon likely reflects an evolutionarily ancient communication channel between the immune and central nervous systems, prompting the brain to promote rest to adaptively cope with short-term insults. Yet, how this phenotypic convergence on motivational deficits arises at the level of brain regions and neural circuits controlling such behaviors remains unclear. This project aims to elucidate the function of immune-sensing neural circuits using the cutting-edge tools of neuroscience. By utilizing whole-brain cellular resolution activity mapping and cell-type-specific manipulation, coupled with a quantitative dissection of circuit dynamics, it intends to bridge the gap between sensory neuroscience and systems immunology. This will allow characterizing the cytokine codes to elucidate how neural circuits interpret and subsequently guide appropriate behavioral responses. These investigations will use a range of mouse models, spanning both acute infections and chronic inflammatory conditions, such as endometriosis, cardiac cachexia, and cancer cachexia. This research promises a paradigm shift by uncovering the principles through which neural circuits interpret cytokine codes to deduce immune states and reveal novel neuroimmune mechanisms governing mood and motivation. These insights are poised to unlock new therapeutic targets, enhancing treatment strategies to alleviate motivational symptoms for the over 50 million Americans suffering from chronic inflammatory conditions.

NIH Research Projects · FY 2024 · 2024-09

ABSTRACT Dementias lead to disability and dependency and are the leading cause of death among all diseases. While Alzheimer's disease is the most common form of dementia, genetically inherited dementias are epidemiologically relevant and may provide insight into the pathogenic pathways and therapeutic targets for common dementias. Here, we focus on an autosomal recessive microgliopathy, known as Nasu-Hakola Disease (NHD), which is caused by rare homozygous loss-of-function mutations in either TREM2 or TYROBP (encoding DAP12). In contrast to AD, which manifests with aging, NHD progresses quickly, often resulting in death by the fifth decade. We recently examined specimens of brain occipital cortical tissues from three rare DAP12-deficient patients with NHD by single nucleus RNA-seq. This analysis showed that lack of DAP12 is associated with a unique transcriptome microglia profile indicative of enhanced RUNX1/2, STAT3 and TGFβ signaling pathways that mediate tissue repair functions. We postulate that DAP12 attenuates the RUNX, STAT3 and/or TGFβ pathways. In the absence of DAP12 (or TREM2), unrestricted signaling of these pathways may cause maladaptive responses of microglia to stimuli normally received from the brain microenvironment, leading to exaggerated tissue repair reactions, widespread tissue alterations, microvascular alterations, and neuronal loss. In this grant, we aim to investigate whether the lack of DAP12 in microglia leads to heightened signaling of RUNX/STAT3 in vitro. Furthermore, we will explore whether excessive RUNX/STAT3 signaling in microglia, independent of DAP12 influence, disrupts the expression of genes responsible for microglial functions, including phagocytosis, cytokine production, and wound repair. Ultimately, we seek to understand how these mechanisms contribute to brain pathology. In Aim 1, we will investigate the impact of DAP12 deficiency on the expression of RUNX1/2 in human iPSC-derived microglia (iMGL). Regardless of whether DAP12 directly regulates these factors, we will explore the consequences of RUNX1/2 overexpression on transcriptome and functionality of iMGL. Additionally, we will assess the repercussions of altered microglial expression of RUNX in vivo using a mouse model where RUNX2 is selectively induced in microglia. In Aim 2, we will focus on STAT3, which drives macrophage responses to IL-6 family cytokines and IL-10. Our preliminary data show that NHD microglia exhibit a transcriptional signature resembling that of IL-10–STAT3-stimulated macrophages. We also found that DAP12- deficient macrophages contain more phosphorylated and total STAT3 than do wild-type macrophages. We will investigate whether lack of DAP12 increases STAT3 activation in human iMGLs and delineate the molecular and functional changes induced by a gain-of-function mutant of STAT3 in human iMGLs. Furthermore, we will evaluate the impact of STAT3 gain-of-function on glial phenotype and brain pathology using in an vivo knock-in mouse model. Overall, this project will elucidate the role of RUNX1/2 and STAT3 in driving the expression of genes which, if dysregulated, may alter microglial functions inducing brain pathology and dementia.

NIH Research Projects · FY 2025 · 2024-09

PROJECT SUMMARY The prevailing hypothesis in biology is encapsulated by the ‘central dogma’, which posits that our heritable genetic traits are encoded by DNA, transcribed into an RNA intermediate, and translated into functional proteins. However, this model fails to incorporate the contributions of the prevalent expression of non-coding RNA transcripts. Our recent profiling of the developing retina of humans and mice highlighted widespread and temporally dynamic expression of long non-protein coding RNAs (lncRNAs). lncRNAs play essential roles in the regulation of transcriptional and epigenetic programs during cell fate decisions, including those of the developing retina. One mechanism by which lncRNAs function is through initiating scaffolding complexes with proteins and DNA, including interactions with transcription factors to modulate transcriptional activity. We hypothesize that retinal expressed lncRNAs function to control retinal gene regulatory networks, in part through interaction with transcription factors. To test this hypothesis, we first propose to utilize both gain-of-function and a novel loss-of-function models to examine the effect of the lncRNA Gm11454 expression on retinal progenitor cell development and differentiation. Additionally, we will assess the trans functions of Gm11454 in virally mediated rescue experiments. Secondly, the sites of DNA-RNA interaction are determined through Chromatin Isolation by RNA Precipitation. The functional significance of sites of DNA-RNA binding will be determined by assessing changes gene expression and chromatin accessibility because of altered Gm11454 expression. Thirdly, we will characterize RNA-transcription factor interactions. Preliminary results identified Gm11454- transcription factor interactions. We will test the significance of RNA-binding by transcription factors through genome-wide profiling of RNA-guided transcription factor binding to DNA. Finally, we will implement a novel Digital Affinity Profiling via Proximity Ligation approach to identify novel RNA-interactions of retinal transcription factors, performing extensive validation techniques. These studies will provide important insights into the biomolecular regulatory mechanisms by which RNA transcripts control retinal gene regulatory networks. Importantly, these studies aim to provide novel insights into the molecular consequences of altered (lnc)RNA expression during retinal development and disease.

NIH Research Projects · FY 2024 · 2024-09

ABSTRACT: Bacterial infections are a major threat to human health. Many bacteria, particularly Gram-positives, form difficult- to-eradicate biofilms on catheters, cardiac devices and bone implants such as joint replacements. Because of the difficulty in treating established biofilm infections, early detection is advantageous. However, current diagnostic imaging modalities rely on nonspecific host features such as inflammation and edema, rather than detecting the bacteria themselves. The antibiotic vancomycin binds with high affinity and specificity to Gram- positive bacteria, and antibiotic-derivatives have been explored as imaging agents. In this application, we conjugate vancomycin to the siderophore DFOB, which binds with nM affinity to the virulence-essential surface displayed lipoprotein receptor (FhuD2) on S. aureus and other Gram-positives, and is subsequently internalized. DFOB is also an FDA approved chelation agent that forms stable complexes with transition metal PET isotopes (68Ga, 89Zr, and 44Sc). In the first Specific Aim, we test the in vitro affinity and specificity of bivalent radiometal- labeled Vanco-PEG-DFOB on target proteins, on live planktonic bacteria, as well as in clinically relevant biofilm embedded systems. We will determine the role of PEG spacer and transition metal isotope on the binding capability, and compare with monovalent tracers. In the second aim, we test the contrast and detection capacity of Vanco-PEG-DFOB using in vivo models of implant infection for both in-dwelling catheters and periprosthetic joint surfaces. We compare this novel bivalent and internalizing strategy to control monovalent radiotracers, and the clinically applied 18F-FDG, to generate data that may motivate further translational development of Vanco- PEG-DFOB for delineation of sites of infection. Importantly, this discovery platform can be adapted for other microbe-binding compounds to expand utility to a wide variety of infections.

NIH Research Projects · FY 2024 · 2024-09

PROJECT SUMMARY/ABSTRACT Traumatic spinal cord injury (SCI) is a sudden catastrophic neurologic event resulting in incomplete or complete loss of motor, sensory, and sympathetic function below the level of the injury. Consequently, due to the significant physical, social, and vocational impact of this disease, it is not surprising that it results in a notable decline in patient quality of life and increased socioeconomic burden. SCI results when a mechanical force or forces are imparted on the spinal cord causing compression or transection of the cord. The delivery of this mechanical force leads to the primary injury phase characterized by neuronal and glial necrosis, axonal disruption, loss of myelin, disruption of the blood-spinal cord barrier, hemorrhage, edema, and ischemia. These pathologic processes then trigger a self-perpetuating secondary injury cascade, where among other features, a robust inflammatory response including the release of cytokines and chemokines and infiltration by inflammatory cells such as monocytes, macrophages, and neutrophils is a hallmark. Historically it was believed that there was little interaction between the CNS and the peripheral immune system. However, with the discovery of the glymphatic system, meningeal lymphatic vessels, and that the CNS-adjacent bone marrow supplies the CNS borders with a robust and diverse pool of myeloid cells, this concept of CNS immune privilege has undergone significant revision. We now know that following SCI, the CSF is able to communicate with the CNS-adjacent bone marrow compartment through osseous bone marrow-meninge connections in the skull and vertebrae. This signaling stimulates hematopoiesis and egress of myeloid cells from the bone marrow back to CNS borders including meninges and perivascular spaces, as well as to the parenchyma. Currently, the exact mechanism of CSF signaling to the CNS-adjacent bone marrow remains unknown. It is possible that this signaling is simply through cytokines and chemokines carried by the CSF. As there must be bidirectional movement within the osseous marrow-meninge connections, with CSF moving in one direction and myeloid cells the other, an alternative explanation is that CSF can signal to the bone marrow through flow rate. In Aim 1, we hypothesize that the rate of flow of CSF to the CNS-adjacent bone marrow is capable of regulating myeloid egress to the CNS borders and parenchyma. Further, in many CNS diseases it has been demonstrated that impaired glymphatic CSF flow, waste solute accumulation, and neuroinflammation are key pathologic features that tend to feed forward on one another. Consequently, in Aim 2, we hypothesize that following SCI there will not only be disrupted spinal glymphatic CSF flow, but also CSF flow to the CNS- adjacent bone marrow, and that this will promote increased myeloid cell migration into the CNS borders and parenchyma. It is likely this myeloid infiltration assists with the clearance of accumulated waste solute after SCI, ultimately promoting neurologic recovery. We propose that therapeutically manipulating CSF flow to the spinal cord and bone marrow to enhance myeloid egress will lead to improved recovery after SCI.

NIH Research Projects · FY 2024 · 2024-09

Overdose is a national top-three leading cause of pregnancy-associated death, and maternal substance use disorder (SUD) accounts for an estimated $1.5 billion in annual healthcare expenditures. Treatment with medication and behavioral therapy reduces morbidity and overdose risk. However, in published studies and in our data (n=186), 55% to 80% of patients discontinued treatment within one year postpartum. Additionally, as a result of systemic inequities, historically marginalized patients are at greatest risk of overdose or death. We urgently need interventions that can equitably improve treatment retention and SUD outcomes. One of the most effective SUD treatment strategies in non-pregnant populations is contingency management (CM), in which patients receive incentives to adhere to treatment. In pregnant populations, CM is efficacious for tobacco cessation. However, CM has only been tested in small and underpowered trials for other maternal SUDs, and the results have been mixed. Our central hypothesis is that CM will improve SUD treatment retention and reduce maternal morbidity and overdose risk in patients, moderating the impact of social determinants of health (SDoH) on outcomes. To test this hypothesis, we will design and conduct a hybrid efficacy-implementation randomized control trial within the Clinic for Acceptance, Recovery, and Empowerment (CARE) in Pregnancy at Washington University in St. Louis, which offers prenatal care, addiction treatment, and extended postpartum support for ~125 diverse patients per year facing the challenges of a SUD. In the R61 phase, in conjunction with our Community Advisory Board and the Center for Advancing Health Services, Policy & Economics Research, we will gather feedback from our partners (patients, providers, payers) to develop and pilot a standardized protocol to address social needs (Aim 1), and develop and pilot a protocol for delivering CM in CARE (Aim 2). In the R33 phase, we will recruit 270 patients who will undergo standardized documentation and management of social needs, and then be randomized to usual care or the CM program. We will assess the efficacy of CM to improve treatment retention and other SUD outcomes of pregnant patients with SUD for up to three years postpartum (Aim 3), use moderation modeling to define the relationships between SDoH services (exposure), CM (moderator), and treatment retention/maternal SUD outcomes (outcomes) (Aim 4), and assess implementation outcomes of reach, adoption, and implementation (Aim 5). If we prove CM efficacious to improve maternal SUD outcomes, our work will lead to a scalable, sustainable, effective interventions to maximize the health and wellbeing of patients and families affected by maternal SUD. This study is part of the NIH’s Helping to End Addiction Long-term (HEAL) initiative to speed scientific solutions to the national opioid public health crisis. The NIH HEAL Initiative bolsters research across NIH to improve treatment for opioid misuse and addiction.