University Of Washington

NIH Research Projects · FY 2026 · 2024-05

Project Summary/Abstract The goal of most cancer treatments is to induce the apoptotic death of tumor cells; in many cases these treatments also induce substantial off-target apoptosis in healthy tissues. Even in the absence of therapy, the majority of prospective metastatic cells die by apoptosis, resulting in the early metastatic niche being rich in apoptotic cell material. While numerous studies have focused on the features of tumor cells that allow them to survive and metastasize in the face of such treatments, less attention has been paid to the influence of dying cells themselves on cancer progression. The work proposed here will investigate the hypothesis that apoptotic cells drive efficient metastatic spread of healthy cancer cells, because they initiate a cascade of platelet recruitment, coagulation, and myeloid cell reprogramming at metastatic sites. We will address this hypothesis by focusing on three Aims: First, we will address the role of phosphatidylserine exposure on apoptotic cells in recruiting platelets and promoting tumor cell survival within the intravascular niche upon arrival of metastasizing cells to the lung. Second, we will examine the interface between apoptotic cells, cancer cells, and the myeloid immune network of the lung, during extravasation and establishment of the metastatic niche. Third, we will study the effects of apoptotic cells on spontaneous metastasis from a primary tumor, and test whether blocking pro-metastatic features of apoptotic cells can reduce metastasis in this setting. While our work is focused on the fundamental processes by which apoptotic cells influence metastasis, we suggest that it may point toward therapeutic combinations that prevent metastasis.

NIH Research Projects · FY 2026 · 2024-05

Abstract Understanding how T cell receptors (TCRs) see tumor antigens presented by MHCs is necessary to fully understand how the immune system recognizes tumor antigens, and to reap the full potential of antigen-specific immunotherapy. To achieve this goal, a quantum leap forward is required in which the revolutionary advances in machine learning are combined with a large volume of structure, function, data on matched TCR-pMHC pairs. The development of accurate predictors of TCR-antigen recognition will be dependent on the creation and integration sequencing-based datasets with high-throughput structural and functional insights. Our proposal, submitted as a CRUK/NCI Grand Challenge team (MATCHMAKERS) will combine researchers with expertise in immunology, methods development, structural biology, and computation to enable generalized prediction and design of TCR recognition. This work will be spread across four Work Packages (WPs): WP1: Large-scale generation of TCR-pMHC pairs from naturally occurring sources. We will build datasets of naturally occurring TCR-pMHC pairs. Our team will use an array of approaches to collect these datasets, from humans and from mouse models, and in the context of both cancer and immunity more generally. WP2: Ultra-high throughput TCR-pMHC matching using molecular engineering. Efforts to create general models will require a broader array of data than feasible to collect from natural TCR systems. We will use an array of synthetic approaches developed by our team to comprehensively match TCRs with pMHCs to train computational models. WP3: Large-scale structural and biochemical analyses of TCR-pMHC interactions. A key to our team’s vision is to match interaction datasets with high throughput structural and functional insights. A deep understanding of how the TCR contacts with MHC helices control function and orientation will be essential for training and testing computational models. WP4 AI-based prediction and design of TCR-pMHC interactions. We will integrate our data to train next- generation algorithms capable of generally predicting and designing TCR-pMHC interactions. These predictions will proceed through a reiterative testing and feedback circuits for further model optimization.

NIH Research Projects · FY 2025 · 2024-04

Abstract Precision medicine in oncology requires accurate prediction of drug response to guide personalized treatment decisions. We developed a pharmacoproteomics platform that links kinome activity in liver cancer cell lines to kinase inhibitor drug response. Preliminary results indicate that our KI-Predictor’s ability to identify dysregulated kinase signaling is highly dependent on cellular context. To examine and optimize our predictive model, we will use samples of normal human liver tissue and other inputs and evaluate its performance using additional liver cell lines and the Genomics of Drug Sensitivity in Cancer (GDSC) datasets. In parallel, we propose to evaluate our KI-Predictor by profiling kinome activity in clinical liver cancer samples, selecting candidate kinase inhibitors for testing in organotypic slice cultures derived from each individual patient’s tumor. By comparing the predicted drug response with the observed response in the organotypic slice culture models, the accuracy and reliability of the KI-Predictor model can be evaluated. This validation step enables the assessment of the model's ability to capture the complexities of the tumor microenvironment, including interactions between cancer cells, stromal cells, and the extracellular matrix.

NIH Research Projects · FY 2025 · 2024-04

PROJECT SUMMARY Since 1958, public schools in the United States have used school resource officers (SROs) as a community- based policing strategy to prevent school violence. However, recent evidence questions the effectiveness of SRO programs and highlights their link to increased student discipline and arrests, particularly for marginalized groups. Approximately 28 states have passed policy reforms to mitigate the potentially adverse effects of SRO programs on student outcomes. Yet, no study has examined whether and how state SRO laws impact student outcomes, SRO practices, and SRO policies at the local level. This proposed research project will address these gaps by examining the impact and implementation of state SRO laws in schools with SRO programs. Aim 1 focuses on assessing state-level variation in SRO policies, including their presence, scope, and structure, by developing a longitudinal database on state-level SRO laws until 2024. Aim 2 investigates the association between state SRO policies and disciplinary policies/outcomes in schools with SRO programs using a nationally representative sample of US public schools with SRO programs. Aim 3 delves into the local- level implementation of state SRO policies, exploring barriers and facilitators in school districts with SRO programs. Qualitative interviews will be conducted with school administrators, staff, law enforcement, and students to understand how SRO programs and policy reforms have been implemented among a diverse representation of school districts across the US. Aim 4 focuses on the development and testing of a toolkit to implement SRO policy reforms using findings from Aims 1-3. The acceptability, appropriateness, and feasibility of the toolkit will be evaluated with school districts. By examining the complex interplay between state-level policies, district implementation, and disciplinary outcomes, this research addresses the National Institute of Child Health and Human Development's goal of improving child and adolescent health and transition to adulthood through the promotion of positive community-level (i.e., school-level) interventions that prevent youth violence, injury, and mortality. To strengthen my skills and complete this project, I identified three critical training areas: 1) Implementation science, with a focus on educational policy and programming; 2) Program and policy evaluation, with an emphasis on policy surveillance; 3) Qualitative research methodology, with an emphasis on community-based participatory research. My mentorship team has substantive expertise in public health, psychiatry, medicine, criminology, and education. Moreover, their methodological skillsets will strengthen my training goals. The Pathway to Independence award will be my launch pad to become an independent researcher who works with local school communities to design culturally competent, interdisciplinary, and health-oriented violence prevention strategies.

NIH Research Projects · FY 2025 · 2024-04

Project Summary/Abstract An estimated 12 million adolescent girls marry before the age of 18 annually, the majority of whom live in resource-constrained environments in low and middle-income countries (LMIC). Northern Nigeria is a striking example, with 78% of girls married before the age of 18, and 48% before the age of 15. Child marriage worsens not only health outcomes, including early fertility, maternal morbidity and mortality, depression, and sexually transmitted infections, but also important social determinants of health like education, social support, and intimate partner violence. The complex and contextual determinants of child marriage mean that successful interventions are rare, and causal evidence on the effects of delaying child marriage remains limited, with many programs to delay child marriage focusing on a single, limited margin of intervention. A previous cluster-randomized control trial of the Pathways intervention in northern Nigeria led to unusually large reductions in child marriage two years post intervention by combining social, educational, and vocational support with community-based recruitment. By generating a novel dataset from follow up surveys with the original study participants six years after implementation, we propose not only to evaluate the effectiveness of the Pathways program, but also to leverage this unusually successful program to generate rigorous causal evidence on the effects of delaying child marriage. We will generate causal evidence on the intervention's effectiveness on marital, health and related outcomes, and use cost-benefit analysis to translate the results to policy-relevant figures, contributing to the global knowledge base on preventing child marriage and simultaneously informing the design of future interventions.

NIH Research Projects · FY 2025 · 2024-04

Project Summary/Abstract Dental caries is one of the most significant public health challenges in Alaska Native communities. Added sugars from fruit drinks, especially Kool-Aid, are the main behavioral risk factor for caries. Our team developed and implemented a community-based intervention targeting sugared fruit drinks in Alaska Native children (NIDCR Grant No. U01DE027629). The six-month intervention consisted of health education delivered by a trained indigenous Community Health Worker, who taught families about the harms caused by sugared fruit drinks, introduced sugar-free alternatives, and provided parents with self-efficacy training to facilitate the switch. Local stores were recruited to sell sugar- free Kool-Aid. We enrolled 201 Alaska Native children ages 1 to 10 years; 143 children in two communities received the intervention and 58 children a third community were in the delayed treatment control group. The trial ended in March 2023. Our team is currently evaluating the intervention. The main trial outcome is change in added sugar intake from baseline to 6m, measured using a validated hair biomarker. The trial did not include a disease outcome, but we collected supragingival plaque samples from children throughout the trial (baseline, 1m, 3m, 6m) and archived them for future study. We now have tribal permissions to analyze the plaque. The goal of this 2-year R03 is to process and analyze the 594 banked plaque samples. The Aims are to: (1) Assess the relationship between added sugar intake and the oral microbiome in Alaska Native children; and (2) Conduct mediator analyses to examine the effects of the intervention on the microbiome with added sugar as the mediator. We will test the primary hypothesis that lower added sugar intake is associated with increased alpha diversity, which is a signature of a healthy microbiome. The proposed work will be the first known study to evaluate how added sugar impacts the microbiome in Alaska Native children and is expected to provide insight on mechanisms of the original behavioral trial. The knowledge gained will be critical in refining future interventions aimed at reducing added sugar intake, preventing caries, and addressing oral health inequities that disproportionately affect Indigenous communities.

NIH Research Projects · FY 2025 · 2024-04

Human Immunodeficiency Virus (HIV) was diagnosed in 30,635 people in the U.S. in 2020, with about half of people with HIV (PWH) retained in care. HIV health outcomes are impacted by the circumstances in which a person lives and the wider set of social forces that shape a person’s life known as social determinants of health (SDH). Providers can supplement missing or coarsely defined SDH data from structured electronic health record (EHR) sources with clinical notes. Indigenous, specifically American Indian and Alaska Native (AN/AN), PWH have unique histories and sociopolitical conditions that contributes to SDH factors not captured by generic SDH categories. However, culturally congruent Indigenous SDH (ISDH) are not well understood in terms of 1) categorical definitions, 2) discussion in clinical notes, and 3) their predictive power for HIV outcome modeling. In this K99/R00 application, we propose building community collaborations and leveraging EHR data to elucidate how ISDH are defined and can be deployed within the clinical setting. In the K99 phase, we will collaboratively define ISDH with AI/AN PWH through qualitative interviews. In the R00 phase, we will use natural language processing to extract ISDH from clinical notes and measure their predictive power for modeling health outcomes such as retention in care and future risk of HIV. Our specific aims are: (1) describe ISDH through collaborations with AI/AN PWH (n=20) and health organizations; (2) identify ISDH in clinical notes AI/AN patients (n=30,097); and (3) measure the predictive power of ISDH with HIV health outcomes for AI/AN PWH (n=199) and AI/AN patients at risk for HIV (n=359). The training objectives of this project include developing competencies in qualitative methods and data analysis, community-based participatory research approaches, and building strong, reciprocal relationships with Indigenous communities and health organizations. The long-term training goal is to support Dr. Bear Don’t Walk to transition to faculty and build an independent research program. Dr. Bear Don’t Walk seeks to lead an interdisciplinary team of quantitative and qualitative health researchers, clinicians, and Elders, committed to developing analytic methods to better understand indicators, behavioral, and lifestyle characteristics, and other causes of health disparities, with a focus on community engagement. To ensure success for the planned research and training, a multidisciplinary mentorship team with a breadth of expertise, stellar mentorship records, and established, well-funded research programs will advise Dr. Bear Don’t Walk. Additionally, the research and training will be conducted at a world-renowned university and academic medical center with exceptional community engagement resources, and biomedical informatics research expertise. The proposed research is both significant and innovative because it elucidates ISDH from three complimentary views on how ISDH are: 1) conceptualized and defined by Indigenous PWH, 2) understood and discussed by clinicians in the clinical note, and 3) associated with important health outcomes for PWH in the EHR.

NIH Research Projects · FY 2025 · 2024-04

Human Immunodeficiency Virus (HIV) was diagnosed in 30,635 people in the U.S. in 2020, with about half of people with HIV (PWH) retained in care. HIV health outcomes are impacted by the circumstances in which a person lives and the wider set of social forces that shape a person’s life known as social determinants of health (SDH). Providers can supplement missing or coarsely defined SDH data from structured electronic health record (EHR) sources with clinical notes. Indigenous, specifically American Indian and Alaska Native (AN/AN), PWH have unique histories and sociopolitical conditions that contributes to SDH factors not captured by generic SDH categories. However, culturally congruent Indigenous SDH (ISDH) are not well understood in terms of 1) categorical definitions, 2) discussion in clinical notes, and 3) their predictive power for HIV outcome modeling. In this K99/R00 application, we propose building community collaborations and leveraging EHR data to elucidate how ISDH are defined and can be deployed within the clinical setting. In the K99 phase, we will collaboratively define ISDH with AI/AN PWH through qualitative interviews. In the R00 phase, we will use natural language processing to extract ISDH from clinical notes and measure their predictive power for modeling health outcomes such as retention in care and future risk of HIV. Our specific aims are: (1) describe ISDH through collaborations with AI/AN PWH (n=20) and health organizations; (2) identify ISDH in clinical notes AI/AN patients (n=30,097); and (3) measure the predictive power of ISDH with HIV health outcomes for AI/AN PWH (n=199) and AI/AN patients at risk for HIV (n=359). The training objectives of this project include developing competencies in qualitative methods and data analysis, community-based participatory research approaches, and building strong, reciprocal relationships with Indigenous communities and health organizations. The long-term training goal is to support Dr. Bear Don’t Walk to transition to faculty and build an independent research program. Dr. Bear Don’t Walk seeks to lead an interdisciplinary team of quantitative and qualitative health researchers, clinicians, and Elders, committed to developing analytic methods to better understand indicators, behavioral, and lifestyle characteristics, and other causes of health disparities, with a focus on community engagement. To ensure success for the planned research and training, a multidisciplinary mentorship team with a breadth of expertise, stellar mentorship records, and established, well-funded research programs will advise Dr. Bear Don’t Walk. Additionally, the research and training will be conducted at a world-renowned university and academic medical center with exceptional community engagement resources, and biomedical informatics research expertise. The proposed research is both significant and innovative because it elucidates ISDH from three complimentary views on how ISDH are: 1) conceptualized and defined by Indigenous PWH, 2) understood and discussed by clinicians in the clinical note, and 3) associated with important health outcomes for PWH in the EHR.

NIH Research Projects · FY 2025 · 2024-04

Project summary The intestinal protozoan pathogen Giardia lamblia causes considerable morbidity and mortality on a global scale. This parasite inflicts a disproportionate burden on the young, especially in resource limited countries. Furthermore, treatment options are limited, and drug resistance is building, setting the stage for even greater human suffering due to infections caused by G. lamblia. Unfortunately, there is currently little hope to reverse this impending threat due to a lack of effective drugs in the drug development pipelines. Our team will address this urgent need through the establishment of a robust natural-products-focused testing initiative aimed at the identification and development of new chemical matter capable of controlling these intestinal protozoan pathogens. The proposed research takes steps toward realizing the goal of developing new antiparasitic therapeutics for treating G. lamblia infections through a systematic approach outlined in our three research aims: 1) Investigate a library of crude fungi extracts for selective inhibitors of G. lamblia, 2) Use bioassay-guided fractionation to purify bioactive chemical constituents of crude fungal extracts that have antigiardia activities, and 3) Evaluate the biological activities of the purified compounds against G. lamblia trophozoites to determine in vitro and in vivo activity profiles. Such efforts would have a significant benefit to those infected or at risk of infection by G. lamblia as new therapeutic options are desperately needed, especially for those living in resource- poor regions where the moderate-to-severe diarrhea caused by infections leads to stunted growth, neurological defects, malnourishment, and death. Our approach will focus on the application of natural products derived from biologically diverse fungi, which is an underutilized resource as it applies to infections caused by intestinal protozoans. A combination of pre-purified natural products and extracts from a large citizen-science-centered fungal collection will provide thousands of samples needed for bioassay investigations. Bioassay-guided purification processes coupled with advanced LC-MS dereplication strategies, MS, NMR, and other spectroscopic tools will be used to propel studies of the fungal-derived compounds toward the identification of promising therapeutic scaffolds. The early incorporation of in vivo mouse models of PK and efficacy will serve to greatly accelerate the investigative process to reveal promising bioactive chemical matter, which will become the subjects of further biological and early-stage preclinical investigations. Our team, which brings together expertise in neglected infectious diseases drug development (University of Washington) and natural products chemistry (University of Oklahoma), offers an exciting opportunity to uncover new therapeutic leads that will become the subjects of future, focused development efforts aimed at providing the drugs needed to protect those at risk of suffering from these debilitating and deadly parasitic infections.

NIH Research Projects · FY 2026 · 2024-04

Project Summary/Abstract Suicide is a leading cause of death among 10-to-24-year-olds in the United States1-2, and suicidal thoughts and behaviors (STB) in adolescents are prevalent and increase risk of death by suicide3-5. Nearly half of adolescents who die by suicide contact a primary care clinician within one month prior to suicide14, making routinely accessed pediatric primary care (PC) settings a clear target for reducing adolescent suicide. Unfortunately, many PC providers are reluctant to manage STB in PC, resulting in many PC providers triaging youth with any STB to the Emergency Department (ED)19-22. While EDs are an important resource, ED visits are often poorly equipped to handle mental health24 and most youth with STBs are discharged home with minimal mental health support. Consequently, there is a critical need to adapt evidence- based, responsive, just-in-time suicide prevention interventions for use in PC27-29. This would likely enhance clinician’s comfort with STB screening and would enhance access to higher level services through reducing unnecessary referrals for STB. The development, implementation, and adoption of comprehensive STB services (screening, brief intervention, care appropriate referral) in PC would fill an important service gap, reduce healthcare spending, and, critically, reduce suicides38-39. This K23 proposal aims to fill this gap by taking an innovative, user-centered design approach40 to adapt and optimize a brief, evidence-based suicide intervention, SAFETY-Acute33-34 (SAFETY-A; formerly known as Family Intervention for Suicide Prevention – aka FISP33-34), for use in PC to support PC management of adolescents with low to moderate STB. The candidate proposes training in development/adaptation of suicide prevention interventions for youth and families, inclusive of training in implementation science, user centered design, and advanced mixed-methods approaches and analyses with health-systems to carry out the following proposed study aims, partnering with diverse pediatric PC practices in Western Washington: (1) Conduct contextual inquiry to assess needs of PC staff, patients, and parents for suicide prevention services in PC, including context of use, barriers, and facilitators that impact STB screening, intervention, and referral within PC. (2) Based on data from Aim 1, design and build a SAFETY-A based STB model of care prototype for PC, via rapid prototyping and usability refinement with PC stakeholders (PC staff, patients, parents). (3) Pilot test the STB model of care, compared to treatment as usual, with 3 PC clinics, including 48 10–18-year-old patients with STB and their parents (16 dyads per clinic). Using self-report, interview, and clinic medical record and administrative data, assess acceptability and feasibility of (a) the STB model of care and (b) the research protocol, and (c) preliminary intervention impacts and need for further adaptation. The proposed project will yield pilot data to inform a larger R01 hybrid effectiveness-implementation trial of the intervention.

NIH Research Projects · FY 2026 · 2024-04

PROJECT SUMMARY: This proposal is in direct response to NIMH’s Strategic Goal 1, which aims to define the brain mechanisms underlying complex behaviors by using new techniques and multidisciplinary approaches to characterize the cellular and circuit components contributing to brain organization and function. The primary goal of this training proposal is to dissect the neurocircuitry of local projections to the locus coeruleus (LC) from GABAergic pericoeruleus (peri-LC) neurons in hyperarousal and avoidance behaviors. The LC has been implicated in regulating these physiological and behavioral responses, with increased norepinephrine (NE) resulting in increased arousal levels and anxiety-like behaviors. Recent evidence from our lab suggests that peri- LCGABA neurons directly inhibit the LC and respond heterogeneously to different aversive stimuli. However, a direct relationship is not yet established between peri-LCGABA activity, LCNE activity, and aversive behavioral and physiological outputs. The central hypothesis of this proposal is that an ensemble of peri-LCGABA neurons coordinates LCNE activity during acute stress exposure in an anti-correlated manner, which induces stimulus- dependent changes in arousal levels and drives avoidance behaviors. The first aim of this training proposal seeks to characterize the modulation of noradrenergic LC activity by local GABAergic projections during acute stress exposure and examine the resulting changes in arousal levels and avoidance behaviors. Aim 1A uses in vivo 2-photon calcium imaging to observe LCNE and peri-LCGABA activity in response to acute stressors. Aim 1B uses clustering methods to assess the relationship between LCNE and peri-LCGABA activity during each stimulus, while Aim 1C reinforces the specific role of peri-LCGABA activity in the stress-induced modulation of LCNE activity by using a generalized linear model to predict LCNE activity from peri-LCGABA responses to aversive stimuli. The second aim of this training proposal seeks to determine how arousal levels and avoidance behaviors are coordinated by changes in LCNE and peri-LCGABA activity. Aim 2A uses designer receptors exclusively activated by designer drugs (DREADDs) in conjunction with 2-photon imaging to assess how tonic activation or inhibition of LCNE neurons alters avoidance behaviors and phasic LCNE activity in response to aversive stimuli. Aim 2B will modulate peri-LCGABA activity while monitoring LCNE activity using 2-photon imaging to evaluate how changes in peri-LCGABA activity during acute stress exposure alter LCNE activity, arousal levels, and avoidance behaviors. During my training period, I will learn to utilize cutting-edge biological and computational techniques to perform powerful, high-resolution investigations of neural circuitry, and I will gain valuable career development skills through a wide variety of scientific, intellectual, and mentored opportunities. This F31 proposal is specifically tailored to my needs and will allow me to fully engage in my individual development plan and prepare me for a successful career as an independent neuroscientist.

NIH Research Projects · FY 2025 · 2024-04

PROJECT SUMMARY Hallucinations are prevalent in the context of a wide variety of mental disorders but also occur in approximately 10% of the general population. Hallucinatory experiences are readily identifiable by those experiencing them, but they are not always indicators of conditions that lead to serious negative outcomes such as hospitalizations, use of emergency services, and suicide attempt. Our risk evaluation capabilities are hampered, in part, by the limitations of our assessment strategies which typically involve resource intensive clinical interviews, administered by trained clinicians, in clinic settings. Ubiquitous smartphone technologies offer us novel opportunities to administer behavioral measures that can capture the experience and impact of hallucinations at a scope, scale, and ecological validity that far exceed clinic-based assessment capabilities. Applying powerful computational methods to the rich data collected using mobile behavioral tasks has the potential to yield tools for identification of those at heightened risk for major clinical and functional impairments. In response to RFA-MH-23-105, we propose to recruit a large sample of people experiencing hallucinations to install a smartphone behavioral measurement package that will prompt them to complete targeted brief self-report measures, audio diaries describing their hallucinatory experiences, and validated audio-administered verbal memory tasks in their own environments. Participants will also complete clinical outcome measures prospectively. Our team will derive data-driven clinical signatures from the mobile behavioral tasks to predict individual differences in severe negative outcomes among people experiencing hallucinations; identify and mitigate inaccuracies in modelling across groups defined by race, sex, and age; examine whether adding smartphone-captured behavioral data to information that is typically available in the clinical record improves model clinical utility; and produce machine learning-ready data structures that adhere to FAIR (Findable, Accessible, Interoperable, Reusable) principles, and can be shared with the broader scientific community for ongoing iterative testing and refinement. If successful, the project will produce data-driven tools that will advance our ability to allocate the right clinical resources, at the right time, to the right people.

NIH Research Projects · FY 2026 · 2024-04

Project Summary/Abstract Idiopathic inflammatory myopathies (IIM) are systemic autoimmune diseases characterized by specific autoantibodies and upregulation of interferon inducible genes but are not completely understood. We propose a testable novel hypothesis in this K08 award to study the role of short interspersed elements (SINEs) in IIM. SINEs occupy approximately 13% of the genome, are capable of forming double stranded RNA that leads to activation of the innate immune system and production of interferons through MDA5 signaling. This is normally prevented by ADAR1 which edits adenosine to inosine in RNA, thereby disrupting the double strandedness of the structure. The long-term goal of this proposal is to achieve a better understanding of the underlying molecular mechanisms of disease in IIM that may lead to better therapeutics with improved efficacy and lower risk of adverse effects. This may additionally shed light on certain aspects of autoimmunity in general and the specificity of autoantibodies. Aim 1 uses muscle data to study the transcriptome for evidence of SINE overexpression and to quantify RNA editing in IIM and healthy controls. Aim 2 utilizes single cell analysis of the transcriptome and epigenome to identify cell types that contribute the most to interferon production in inflammatory myositis. Aim 3 correlates mutation detection and alternative splicing of ADAR1 and MDA5 with interferon inducible genes. We expect this research plan to unveil novel biology in IIM. The candidate is an MD/MPH rheumatologist at the University of Washington, with a background in immunology, statistics, and computer programming, the proposed research and mentoring plans will ensure rigorous training in advanced immunology, bioinformatics methodologies, and scientific communication to become a successful independent scientist. Dr. Najjar is committed to a career in scientific research using bioinformatics tools to study complex autoimmune disorders. The primary mentor is Dr Tomas Mustelin, MD, PhD who has mentored many scientists throughout his career. The mentoring team will include additionally Dr Arnon Arazi, PhD as a co-mentor and Dr Robert Bradley, PhD as a scientific advisor, both are experts in computational biology. The University of Washington is an excellent environment for scientific research with advanced infrastructure for genomic research. We will utilize the available genomic centers including that of Dr Michael Gale, PhD to study the transcriptome and epigenome at the single cell level. The proposed multidisciplinary training program will ensure Dr. Najjar's transition to an independent investigator.

NIH Research Projects · FY 2025 · 2024-04

Project Summary Inhibition of the mechanistic Target of Rapamycin (mTOR) improves prognosis in a mouse model of Leigh Syndrome (LS) and in a small cohort of Mitochondrial Encephalomyopathy with Lactic Acidosis and Stroke (MELAS) patients, two neurological mitochondrial disorders. However, its specific mechanism of action remains to be determined. We find that the mTOR inhibitor rapamycin reverses metabolic alterations in LS mice lacking the Complex I subunit Ndufs4 (Ndufs4-/-): more specifically, rapamycin reduces the accumulation of glycolytic intermediates and increases the abundance of fatty acids in both brain and liver of Ndufs4-/- mice. Loss of the mitochondrial sirtuin Sirt3 abrogates lifespan extension and the delay of neurological phenotypes in Ndufs4-/- mice treated with rapamycin. In Aim 1 of this proposal, we explore the dependency of mTOR inhibition on Sirt3 to improve disease phenotypes in these animals. Specifically, we hypothesize that expression of Sirt3 in the liver is required to promote the metabolic shift to fatty acid oxidation described above. Treatment with the Nucleoside Analog Reverse Transcriptase Inhibitor (NRTI) Adefovir Dipivoxil (ADV) delays symptoms of disease and improves survival in Ndufs4-/- mice. ADV increases the expression of C/EBP-β, a transcription factor that increases hepatic fatty acid oxidation in response to calorie restriction and mTOR inhibition. In Aim 2 we explore the hypothesis that C/EBP-β guides the metabolic shift induced by rapamycin in Ndufs4-/- mice. With a combination of genetic and pharmacological approaches, both aims will determine the exact nature of the metabolic alterations induced by loss of Complex I, the mechanisms by which this loss of metabolic homeostasis is rescued, and its importance in the etiology and progression of neurological mitochondrial disease. This project will determine the metabolic nature of these disorders and lay the foundation for novel treatments based on fine tuning of nutrient metabolism in patients affected by Complex I dysfunction.

NIH Research Projects · FY 2026 · 2024-04

PROJECT SUMMARY Hallucinations are prevalent in the context of a wide variety of mental disorders but also occur in approximately 10% of the general population. Hallucinatory experiences are readily identifiable by those experiencing them, but they are not always indicators of conditions that lead to serious negative outcomes such as hospitalizations, use of emergency services, and suicide attempt. Our risk evaluation capabilities are hampered, in part, by the limitations of our assessment strategies which typically involve resource intensive clinical interviews, administered by trained clinicians, in clinic settings. Ubiquitous smartphone technologies offer us novel opportunities to administer behavioral measures that can capture the experience and impact of hallucinations at a scope, scale, and ecological validity that far exceed clinic-based assessment capabilities. Applying powerful computational methods to the rich data collected using mobile behavioral tasks has the potential to yield tools for identification of those at heightened risk for major clinical and functional impairments. In response to RFA-MH-23-105, we propose to recruit a large sample of people experiencing hallucinations to install a smartphone behavioral measurement package that will prompt them to complete targeted brief self-report measures, audio diaries describing their hallucinatory experiences, and validated audio-administered verbal memory tasks in their own environments. Participants will also complete clinical outcome measures prospectively. Our team will derive data-driven clinical signatures from the mobile behavioral tasks to predict individual differences in severe negative outcomes among people experiencing hallucinations; identify and mitigate inaccuracies in modelling across groups defined by race, sex, and age; examine whether adding smartphone-captured behavioral data to information that is typically available in the clinical record improves model clinical utility; and produce machine learning-ready data structures that adhere to FAIR (Findable, Accessible, Interoperable, Reusable) principles, and can be shared with the broader scientific community for ongoing iterative testing and refinement. If successful, the project will produce data-driven tools that will advance our ability to allocate the right clinical resources, at the right time, to the right people.

NIH Research Projects · FY 2026 · 2024-04

Project Summary Explainable AI (XAI) techniques are revolutionizing scientific discovery and clinical application by helping biomedical researchers interpret complex, black-box machine learning (ML) models. Given input features (e.g., dermatological image pixels) and an ML model-generated prediction (e.g., a diagnosis), the most widely used form of XAI computes feature attributions, which represent the importance of each feature to the prediction, that drive predictions even in complex models, such as deep neural networks. Biomedical research has successfully applied deep learning using medical images (e.g., chest X-ray images) as input features; feature attributions identify parts of the images that are important for the model, such as the existence of genuine pathologies (e.g., clear lung fields) or artifacts (e.g., medical devices and laterality marks). However, key limitations of current XAI techniques, which provide only attributions for pre-specified input features (here, individual pixels), preclude a clear understanding of the reasoning process of ML models and limit actionable responses by medical providers. First, even the most interpretable model types, such as linear models, can defy understanding if they use uninterpretable features. Second, computing theoretically principled feature attributions involves exponential computational complexity; this challenge is exacerbated when using modern deep models, such as transformers. Finally, the adoption of XAI techniques by multiple stakeholders, such as regulators, developers, scientists, and physicians, requires real-world demonstration of their utility. In this proposal, we introduce the following techniques and principles to fundamentally advance XAI. Aim 1. Generate medically informed explanations. To bridge the gap between pixel-level features and medically meaningful concepts, we propose a self-supervised approach to retrieve semantically meaningful concepts from medical images and edit the images to systematically edit concepts of interest in images and examine the model output changes. We will also develop a new attribution method to make self-supervised learning interpretable. Aim 2. Develop XAI principles and techniques to compute and evaluate feature attributions. We propose theoretically grounded techniques to: rigorously compute SHAP values for transformers; handle multimodality and feature correlations; and evaluate feature attribution methods to help investigators discern the most effective techniques for their applications. Aim 3. Enable real-world application of XAI techniques to benefit multiple stakeholders. Using the improved model explanations, we will develop an actionable XAI framework to audit third party AI devices, improve clinical AI devices, and derive scientific insights. Successful completion of this project will yield new theoretically grounded and principled XAI techniques to provide medically informed explanations, compute accurate feature attributions, and detect and resolve model pitfalls.

NIH Research Projects · FY 2026 · 2024-04

ABSTRACT More than 75% of suicide deaths occur in low-and middle-income countries (LMICs) and almost 90% of adolescents who die by suicide live in LMICs. Globally, suicide is the fourth leading cause of death for youth aged 15-29. Six of the top 10 countries by suicide rates in the world are in the African region. Despite this, there are few to no evidence-based youth suicide prevention packages specifically developed for, and tested in, the African context. This is an urgent need to safeguard the well-being of youth and young adults globally. Data from our team suggest that 15-25% of high school students in Mozambique are experiencing current suicidal ideation, ~40% of those with ideation have past month suicidal behavior, and 9% have had a lifetime suicide attempt. To address this problem, we aim to test effectiveness and implementation outcomes for a novel suicide prevention package organized around the Suicide Safety Planning Intervention (SPI) and a Transdiagnostic Cognitive Behavioral Therapy Intervention for Suicide Prevention (TCBT-S) to be delivered by non-specialists in Mozambican secondary schools. We believe that these two evidence-based practices, both with demonstrated feasibility in Mozambique, have the potential to be powerful interventions to prevent adolescent suicidal behavior. Yet, a recent meta-analysis found lower comorbidity of psychiatric disorders and suicidal behavior in LMICs (~50%) compared to high-income countries (~90%). Therefore, it is possible that applying TCBT-S to address psychiatric symptoms may not lead to significant decreases in suicidal behavior above and beyond SPI alone. Therefore, we aim to evaluate whether the gains in effectiveness for youth suicide prevention justify the addition of a much more resource intensive TCBT-S versus the brief SPI alone. The present study aims to fill this knowledge gap by testing the following specific aims: Specific Aim 1: Test the effectiveness of SPI and TCBT-S for decreasing suicidal behaviors. Using a three- arm parallel cluster randomized trial we will randomize 7 secondary schools each to Enhanced Usual Care (EUC), SPI alone, and TCBT-S (21 schools total) to evaluate effects on suicidal behaviors (primary) and suicidal ideation/depressive symptoms (secondary). Exploratory analyses will examine mechanisms of intervention effects. Specific Aim 2: Assess implementation outcomes, barriers, and facilitators to EUC, SPI, and TCBT-S implementation using the RE-AIM evaluation and CFIR determinant frameworks. Specific Aim 3: Estimate the costs and cost-effectiveness of SPI and TCBT-S compared to EUC. In response to the NOSI for Youth Suicide in LMICs (NOT-MH-21-090), this project proposes to test “prevention strategies to reduce suicide risk and promote resilience among young people aged 10-24 years in LMICs”. Specifically, this study “integrates suicide prevention strategies within existing community-level platforms such as school/university-based programs”. If effective, SPI or TCBT-S have a large potential to be rapidly scaled up for youth mental health globally.

NIH Research Projects · FY 2025 · 2024-03

The goal of this proposal is to investigate the mechanisms through which the enzyme IRG1 and its metabolic product itaconate deplete inflammatory hemophagocytes to prevent severe anemia. Maintaining the balance between the production and clearance of red blood cells (RBCs) is important for proper oxygenation of the tissue and prevention of anemia. During inflammation, this balance often goes askew as the clearance of RBCs by macrophages in a process known as hemophagocytosis in the spleen and liver increases. The enhanced hemophagocytosis observed during inflammation is mediated primarily by monocytes that have differentiated into macrophages with markedly enhanced hemophagocytic capacity as opposed to tissue macrophages. Our collaborators in the Hamerman lab have recently found that Ly6Chi monocytes differentiate into a unique population of specialized hemophagocytes termed inflammatory hemophagocytes (iHPCs) in mouse models of severe malarial anemia and lupus like disease driven by transgenic TLR7 overexpression. During blood stage Plasmodium yoelii-17XNL infection, iHPCs have been shown to contribute to severe malarial anemia. Currently, the mechanisms that regulate the monocyte to iHPC transition remain unknown. The metabolite itaconate, which is produced by the enzyme IRG1, has been shown to alter inflammatory signaling by activating the anti-inflammatory transcription factor NRF2 and inhibiting succinate dehydrogenase (SDH) activity to induce metabolic changes that limit the production of reactive oxygen species (ROS). Surprisingly, we found that Irg1 is highly upregulated in Plasmodium infected Ly6Chi monocytes and iHPCs, indicative of metabolic regulation of iHPCs. Preliminary data from our lab generated using mouse models of both Plasmodium infection and TLR7 stimulation to induce iHPCs have revealed a cell intrinsic role of Irg1 in depleting iHPCs in the circulation and the spleen. To better understand the mechanism underlying itaconate mediated depletion of iHPCs, we isolated WT and Irg1-/- Ly6Chi monocytes and observed reduced cell death in the Irg1-/- monocytes compared to the WT, suggesting that itaconate is inducing death in the precursor population to regulate the accumulation of iHPCs. Our lab has previously shown that activation of the RIP kinases, key components of necroptotic signaling, induce Irg1 expression. Furthermore, itaconate has been shown to itaconylate RIPK3 to enhance necroptosis. Interestingly, knocking out RIPK3 enhanced iHPC accumulation, implicating the necroptotic pathway as one way in which iHPCs are regulated. Based on our findings, the goal of this proposal is to elucidate the interactions between IRG1/itaconate and RIPK3 that promote necroptosis in Ly6Chi monocytes (Aim 1) and to assess how inhibition of necroptosis in vivo alters the accumulation of iHPCs and anemia severity (Aim 2). With the support and training from this fellowship, I will be able to continue advancing my knowledge of immunological techniques and work towards my goal of becoming an independent investigator; so that in the future, I can lead my own group in biotech.

NIH Research Projects · FY 2026 · 2024-03

Abstract Heavy and high-intensity alcohol use often results in negative outcomes such as blackouts, social mistakes, increased vulnerability to alcohol use disorder, and long-term health problems. Social influences have a seemingly paradoxical relationship with alcohol use, serving as a risk for alcohol misuse in some cases (e.g., heavy alcohol use in peer group) and a protective factor in others (e.g., emotional support). Precisely characterizing which aspects of social influence increase short and long-term risk for alcohol misuse will be a vital step in defining more specific intervention targets. To that end, we propose to evaluate links between social influences and alcohol misuse development across individuals (e.g., person-specific variation), social contexts, and timescales (e.g., longitudinal and moment-to-moment). Data will be drawn from real-time ecological momentary assessment (EMA) data from a cohort-accelerated longitudinal burst study of psychopathology and alcohol use supplemented with rich social network interviews (i.e., PEARL study, PI: Foster) and from a large, nationally representative longitudinal dataset of adolescents (i.e., Add Health). The PEARL study uses EMA (smartphone surveys 3 times daily for at least 100 days) to measure reported momentary and daily alcohol use (e.g., quantity, drunkenness) and social interactions (e.g., duration, quality, type of engagement, and person with whom they interacted), among a larger battery of questionnaires. Supplementary information will be gathered from a subset of participants (n=90) from the PEARL study to link features observed in the social network (e.g., perceptions of long-term relationships with others and their involvement in the target participant’s drinking) and their influence on momentary dynamics between alcohol use and social interactions. Add Health (n=14,600) includes four waves of longitudinal assessments spanning adolescence (i.e., age 12-17) through adulthood (i.e., 21-32). Using longitudinal, EMA, and social network data, we will determine how social influences impact participant alcohol use across developmental periods, social contexts, and person-to-person variation. We hypothesize that changes in social influences (i.e., drinking peers, closeness with family and friends who drink) will predict changes in alcohol misuse (i.e., binge drinking, alcohol-related consequences) across development and in daily life. Results from this work will inform future prevention efforts designed to reduce alcohol use using social support across development, which aligns well with NIAAA’s mission. The proposed project will serve as the author’s primary line of research supporting multiple manuscripts. Consequently, the NRSA award would ensure the student is provided with a critical opportunity to build a career as an independent clinical scientist by establishing a research record focused on social influences on alcohol misuse and to obtain training in advanced statistical techniques and developmental psychopathology.

NIH Research Projects · FY 2026 · 2024-03

PROJECT SUMMARY The notion that people consume alcohol in order to regulate both positive (drink-to-enhance) and negative (drink-to-cope) emotions is central to theories of the development and treatment of alcohol use disorder (AUD). Evidence for affect regulation is robust from both experiments and people’s retrospective, global self-reports of their drinking motives. However, evidence from ecological momentary assessment (EMA) studies have failed to produce compelling evidence of affective regulation of alcohol use. A central problem is that affect regulation theories are vague as to when, where, how, and for whom they are relevant, leading to potentially hundreds of ways that these theories can be operationalized. The lack of empirical consensus means that studies designed to test a single affect regulation hypothesis are ultimately less informative because they cannot rule out or rule in plausible alternative hypotheses. We will test hypotheses across timescales, measures, persons, and situations using an adaptive, multi-burst EMA design. Our design will allow us to weigh the evidence for the most theoretically informed and empirically supported affect regulation hypotheses in the same dataset. Using specification curve analysis in combination with cross-validation in a hold-out sample, we will be able to test the robustness and generalizability of each hypothesis across hundreds of specifications of timescale, affect, and alcohol outcomes. We will simultaneously test multiple specific and contextualized predictions of the affect–alcohol use association that can inform etiological and intervention research. We aim to do this in a large (n = 500) adult regular and hazardous drinkers collected across three sites who will complete three high intensity bursts of EMAs (10 per day over 10 days. By using these data to compare all reasonable ways that affect regulation may be specified, the proposed project will identify sets of hypotheses about affect regulation of alcohol use that are either well supported by data, or which should no longer be investigated.

NIH Research Projects · FY 2026 · 2024-03

Title: Distinct functions of adipocyte-derived FGF21 in obesity Summary Obesity is rapidly reaching epidemic proportions, with an urgent need for novel strategies for weight loss. Fibroblast growth factor 21 (FGF21) is a hormone derived from the liver and adipose tissue that plays a beneficial role in energy homeostasis when given pharmacologically, but is paradoxically activated by both fasting and feeding signals. Obesity is associated with elevated levels of circulating FGF21 in rodents and humans, which correlates with adiposity and adipose tissue FGF21 mRNA levels, suggesting that obesity- associated FGF21 derives from adipose tissue. While the beneficial effects of pharmacological FGF21 and hepatic FGF21 on energy metabolism are generally accepted, a clearly defined role for adipocyte-derived FGF21 has not been established, especially in the context of obesity. Preliminary data suggest that adipocyte- derived FGF21 promotes deleterious effects on body weight and glucose metabolism, which is in stark contrast with the beneficial effects observed for pharmacological and hepatic-derived FGF21. Mice deficient in adipocyte-derived FGF21 (FAKO mice) are protected from diet-induced obesity, have less body fat, and exhibit increased energy expenditure and improved insulin sensitivity over wild-type controls. Thus, the hypotheses of this proposal are that: (1) the development of obesity requires FGF21; and (2) adipocyte-derived FGF21 is functionally distinct from hepatic-derived FGF21, and could therefore be targeted pharmacologically. Aim 1 will determine whether adipocyte-derived FGF21 is sufficient or required for obesity-associated adipose tissue expansion and associated comorbidities. We will use several loss- and gain-of-function models of genetically- perturbed mice as well as fat transplantation techniques to ascertain whether adipocyte-derived FGF21 is important for the development and/or maintenance of obesity. In Aim 2, potential mechanisms by which adipose FGF21 modulates local and systemic metabolism will be examined. This will include an assessment of a role for adipocyte-derived FGF21 in thermoregulation, in autocrine signaling in adipose tissue, in systemic signaling in traditional FGF21 target tissues, and the potential for adipocyte-derived and hepatic-derived FGF21 to be differentially processed posttranslationally, which could impact their ability to target local or distal tissues. Reconciling the differences between the beneficial effects of hepatic FGF21 on energy metabolism and the detrimental effects of adipocyte FGF21 in obesity could increase our understanding of adipocyte metabolism in obesity. Such knowledge could lead to novel therapeutic strategies to combat obesity, such as targeting adipocyte-derived FGF21.

NIH Research Projects · FY 2026 · 2024-03

Project Summary My long-term career goal is to become a successful independent investigator in the field of musculoskeletal regenerative medicine, developing therapeutics to promote the regeneration of complex tissues after injury or disease. The objective of this proposal is to help me transition to independence by providing me with critical scientific skills to investigate the cellular and molecular mechanisms of murine digit tip regeneration versus fibrotic scarring. To reach this objective, a thorough training plan has been established, including research aims and tailored training activities. The proposed research project will seek to develop a novel mouse model and an induced pluripotent stem cell (iPSC) in vitro culture system in order to dissect the functional role of regulatory genes involved in embryonic limb development and morphogenesis, including Hox genes. The central hypothesis of the proposal is that HoxA cluster genes, and specifically Hoxa13, are required during digit regeneration to coordinate osteogenic differentiation, outgrowth, and patterning via Eph/ephrin and bone morphogenetic protein (BMP) signaling. We will investigate this hypothesis by conditionally deleting HoxA cluster genes from osteoblast lineage cells in transgenic mice in Aim 1 and by modulating Hoxa13 gene expression in iPSCs in vitro using a lentiviral-mediated approach in Aims 2 and 3a. Finally, we will evaluate the therapeutic potential of Hoxa13-expressing cells delivered to the wound site of non-regenerative digits in Aim 3b. The project outlined in this application combines basic science with a clinically relevant in vivo platform and cutting-edge transcriptomic and bioinformatic technologies to query the gene regulatory networks and signaling pathways that lead to regeneration versus scarring after musculoskeletal injury. This proposal also includes a comprehensive series of educational activities that will prepare me for my independent research faculty position. The world-class institutional environment at Washington University in St. Louis provides a multitude of resources to ensure the successful completion of the proposed work, as well as ample opportunities for career development. Finally, the assembled Scientific and Career Advisory Committee, along with new mentoring relationships that I am fostering in the developmental and regenerative biology communities, will monitor research progress, provide constructive feedback, and advocate for my professional development as I begin my independent research career.

NIH Research Projects · FY 2026 · 2024-03

Project Summary/Abstract Abnormally aggregated tau protein is one of the main neuropathological hallmarks of Alzheimer’s disease (AD), and correlates with disease presentation and severity. The mechanism by which tau causes neurodegeneration is unknown. Abnormal activation of the endoplasmic reticulum unfolded protein response (UPRER) has been implicated in AD and other tauopathies. The proposed project will leverage genetic approaches in C. elegans to identify therapeutically tractable molecular mechanisms in the UPRER that modulate tauopathy. The UPRER also becomes dysfunctional in aging, and tauopathies often coincide with advanced age. Therefore, understanding the aberrant UPRER in the context of tauopathy is crucial for neurodegeneration and aging research. Hypothesis: Abnormal UPRER activation promotes pathological tau accumulation and facilitates synergistic toxicity with TDP-43.The proposed work will address two Specific Aims: 1) Identify UPR-related genes enhancing tauopathy phenotypes by monitoring tau turnover, and 2) Determine the role of UPR activation in TDP-43 cleavage and localization relative to tau. The research and training plan will be conducted in the Kraemer laboratory at the University of Washington with the support of Drs. Brian Kraemer, Nicole Liachko, and Caitlin Latimer. The strong neuroscience, neurology, and C. elegans research communities between the University of Washington, Fred Hutchinson Cancer Research Center, Puget Sound VA, and other institutions will provide resources, scientific expertise, and clinical opportunities that support physician scientist training and enable the successful completion of this proposal.

NIH Research Projects · FY 2026 · 2024-03

Among drug users, polysubstance use is much more common than single substance use. One of the deadliest combinations of substances used in America today is concurrent opioid and stimulant usage, with co-use of these drugs becoming increasingly responsible for overdose deaths. Out of the 2.1 million Americans which had an opioid use disorder (OUD) as of 2017, 11% also had a methamphetamine use disorder. First-time methamphetamine use is more likely after past-month opioid use. Additional research into the neurobiology of polysubstance use is essential for the development of targeted, effective treatments for polysubstance addiction. Addiction behaviors arise from neuroplasticity within the neural circuits responsible for decision - making, motivation, and reward processing. Individually, stimulants and opioids have different actions within these circuits, each targeting distinct regions, receptors, and neurotransmitter systems. Because of this, many of the cellular and molecular adaptations induced by these two drug classes are unique. Yet, it is unclear how the interaction of these compounds within the nervous system produces changes in drug-seeking and taking behavior. The proposed study will explore the neurobehavioral effects of dual opioid and methamphetamine use disorders. The following Aims will guide the proposed study. AIM 1 is to define the behavioral profile of dual opioid-methamphetamine use disorders in a rodent model of addiction. Despite its rising popularity, the underlying behavioral patterns and motivations of polysubstance addiction are not well characterized. Therefore, the first aim will compare and contrast polysubstance and mono substance addiction behavioral patterns (i.e. drug-seeking, drug-taking, and reward valuation) using a reverse-translational rodent self-administration model. AIM 2 is to map neural activation patterns within the cortico-basal ganglia-thalamic (C-BG-T) circuit in response to opioid and methamphetamine self-administration. Alterations in the C-BG-T networks contribute to addiction behaviors, as well as the persistence of individual substance use disorders for both opioids and stimulants. Yet, it is still unclear how chronic, sequential polysubstance use alters neurocircuit activity. Therefore, the proposed study will map neurocircuit activation patterns with a novel viral- mediated gene transfer approach for post-mortem tissue analysis, whole brain lightsheet microscopy, in order to identify differences in C-BG-T network activity between animals with a history of chronic polysubstance or single substance use. We hypothesize that opioid-stimulant polysubstance use will have a unique, synergistic effect on addiction-related behaviors and neural circuit recruitment that is not present when either drug is used alone.

NIH Research Projects · FY 2025 · 2024-02

Project Summary/Abstract This project aims to develop a new optical imaging tool capable of dynamically profiling immune cells in live tissue at a single-cell resolution. The immune system plays a vital role in defending the body against invaders and combating diseases. However, uncontrolled or dysfunctional immune cell activity can worsen various diseases, including cancer and autoimmune disorders. To gain a comprehensive understanding of the immune system, we require tools that not only quantify different immune cells but also observe their functional state changes and dynamic interactions with other cells in tissue. Recent advancements in immune profiling using flow cytometry have provided valuable insights. However, tissue dissociation is necessary, resulting in the loss of spatial information. This is a significant drawback because the spatial context and heterogeneity of immune cell interactions are crucial for immune function. To address this issue, emerging techniques such as spatial transcriptomics and cyclic immunofluorescence imaging have been developed. However, these techniques can only capture static snapshots of cells and are not applicable to live samples. Additionally, they require complex sample processing and time-consuming data acquisition, and are often limited to thin tissue sections. Observing and characterizing the immune response in live tissue or animals at a single-cell resolution remains a major challenge because of the highly dynamic nature of the immune system and its rapid response to external stimuli, such as infection or drug treatment. To overcome these challenges, this proposal seeks to leverage advances in high-speed Raman imaging and deep learning to create a virtual staining tool for dynamic immunoprofiling. Stimulated Raman scattering (SRS) microscopy is a label-free imaging technique that can rapidly examine intact live tissue based on the unique Raman vibrational signatures of molecules. We will employ fast hyperspectral SRS imaging to acquire comprehensive 5D datasets (spatial 3D + spectral + temporal) of tissue. Through iterative deep-learning training using immunofluorescent labeling as the ground truth, we will construct a multiplex virtual staining model capable of classifying multiple types of immune cells and their functional states. Different deep learning models will be tested and compared to traditional machine learning approaches to evaluate the significance of spatial and spectral features in distinguishing immune cells. The accuracy of classification will be quantitatively determined. Validation of our virtual staining technique will involve diverse samples, including isolated immune cells from mouse spleen, mouse lymph node tissue, and mouse tumor tissues. Successful implementation of multiplex virtual staining of immune cells will enable dynamic profiling in live tissue or animals. We anticipate wide-ranging applications of this technology in the study of infections, autoimmune diseases, neurodegenerative disorders, and cancer immunotherapy.