University Of Illinois At Chicago

NSF Awards · FY 2024 · 2024-10

Advanced cyberinfrastructure (CI) is undergoing disruptive changes in system architectures and application workloads. The landscape of cyberinfrastructure workloads is rapidly expanding beyond traditional computational simulations to include a hybrid mix of applications. CI facilities now host diverse high-performance systems with heterogeneous configurations, leading to a complex mix of computing, memory, and storage components. Existing CI management methods, which are heavily heuristic or manual-based, struggle with these evolving challenges. This project addresses the complex challenges of CI resource management by integrating artificial intelligence (AI) technologies with human expertise. UIC is a federally designated Minority-Serving Institution (MSI). An integrated education plan can strengthen diversity-focused programs at UIC, thus promoting greater diversity and inclusion within the scientific community. The project transitions from managing isolated single clusters to coordinating facility-wide management, orchestrating the entire facility as a unified pool of diverse resources for a broad spectrum of applications with various resource requirements. Specifically, it aims to design and evaluate an AI-guided framework named AIMCI (Artificial Intelligence for Managing Cyberinfrastructure). Key research thrusts are: (1) developing new AI models for predictive analysis of resource usage patterns and user behavior, (2) applying reinforcement learning methods to optimize resource management in a complex and dynamic computing environment, and (3) building a discrete event-driven simulator for exploratory simulation of CI resource management with human-in-the-loop interaction. 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 · 2024-09

PROJECT SUMMARY The serine/threonine protein kinase GCN2 (General control nonderepressible 2) is an amino acid sensor that coordinates mRNA translation (also known as protein synthesis) in response to amino acid availability through phosphorylation of eIF2. Despite extensive studies of the GCN2-eIF2 pathway in the context of cellular stress, the importance of this pathway in early embryogenesis and differentiation has not been established. The focus of this research is to uncover the role of GCN2-dependent translational control in mediating the effect of amino acid deprivation stress on human induced pluripotent stem cells (hiPSCs), hiPSC to endothelial cell (EC) differentiation and hiPSC-EC function. Our preliminary data show that the expression of several key pluripotent factors is reduced in CRISPR-engineered GCN2 knock out (GCN2 KO) hiPSCs compared to isogenic control hiPSCs. We also observed that hiPSCs undergo a profound increase in p-eIF2 at an early stage of differentiation toward endothelial cells. Additionally, two downstream targets of p-eIF2, ATF4 and GADD34, were induced on day 3 of differentiation. Given these findings, I hypothesize that GCN2 regulates hiPSCs, hiPSC to EC differentiation and hiPSC-EC function through phosphorylation of eIF2. The proposed experiments will fully assess the self-renewal and EC differentiation potential of GCN2 KO hiPSCs using cellular and biochemical strategies. Importantly, ribosome footprinting, a high-throughput translatome technique, will be used to identify downstream translational targets of the GCN2-eIF2α pathway that regulate hiPSC-EC function in response to amino acid stress. The identified GCN2 targets will be functionally assessed for their role in endothelial cell differentiation and function. The results of this research will provide insight into new candidates for treating endothelial-related diseases.

NIH Research Projects · FY 2024 · 2024-09

ABSTRACT AD disproportionately affects women and people of color. With no cure for AD, it becomes important to identify sex-specific modifiable risk factors at midlife, especially those that affect minority women. For women who reach midlife, the menopause is a universal transition often accompanied by adverse symptoms that may affect their later health. Sleep disturbance and vasomotor symptoms (VMS; hot flashes) are among the most common and bothersome menopausal symptoms and have been associated with AD biomarkers and adverse brain and cognitive outcomes, particularly verbal memory. Black and Hispanic women typically experience more severe and persistent VMS, experience more sleep disturbance, and show more persistent memory declines across the menopause transition compared to White women. Black women also exhibit weaker rest-wake activity rhythms (RAR), which are associated with worse cognitive performance. Considering the increased burden of VMS, sleep disturbance, and weakened RAR in black women, these modifiable symptoms may contribute to their more persistent menopause-related declines in memory and potentially to the greater burden of AD experienced by black women. The objective of this study is to test the hypothesis that VMS, sleep disturbance, and RAR contribute to worse memory performance in black midlife women and to understand the relative contribution of each to memory dysfunction. Building on preliminary data from 20 women recruited to date, 70 black and/or Hispanic peri- and postmenopausal women with moderate to severe VMS will undergo assessment with wearable devices (VMS monitor and actigraphy watch) to objectively measure VMS, sleep disturbance and RAR during three consecutive days/nights. Memory will be assessed with a test of verbal memory as well as pattern separation, a test that yields behavioral indices that align with the function of specific hippocampal subregions. This innovative study is the study to examine objectively measured menopause symptoms in relation to cognition in black and Hispanic women with moderate to severe VMS. The study will yield new insights into modifiable risk factors for memory declines in this understudied group.

NIH Research Projects · FY 2025 · 2024-09

Project Summary/Abstract: Single-cell RNA sequencing (scRNA-seq) has unveiled significant variability among hematopoietic stem and progenitor cells (HSPCs) and developing erythroid cells. Despite these advancements, current computational tools fall short in accurately identifying transient and mixed-lineage states crucial for erythroid fate specification. This gap in understanding and classification poses a significant challenge, as these rare states play a pivotal role in hematopoiesis, characterized by a complex continuum of cellular states rather than a simple branching hierarchy. Addressing this challenge, our research introduces two innovative algorithms: the first aims to classify distinct cell identities and capture elusive transient states without prior biological assumptions; the second seeks to elucidate the optimal trajectory of transcriptional states during HSPC to erythrocyte differentiation. Our primary goal is to identify the mixed-lineage intermediates and the gene regulatory networks guiding erythroid cell fate. This includes investigating Megakaryocyte-Erythroid Progenitors and potential upstream multipotential transition cells, which are currently not well-characterized. In our first aim we will develop a clustering algorithm based on algebraic topology. This algorithm will analyze scRNA-seq data to identify novel cell states and infer their developmental relationships. Our approach surpasses existing methods by eliminating the need for selecting hyperparameters and by effectively capturing intermediate states. We will validate and benchmark our algorithm using established single-cell datasets of early myeloid progenitor differentiation in adult mice. In our second aim, we will create a probabilistic cell pathway trajectory model. This innovative approach incorporates both biological stochasticity and technical measurement noise, enabling a more accurate prediction of activated and inhibited gene programs in erythropoiesis. We envision that our approach will help filter out time-dependent gene regulatory programs, offering a new understanding of HSPC trajectories to erythrocytes. We will validate our predicted genes and their contribution to erythrocyte biogenesis experimentally. Upon completion, this study is expected to uncover novel cell subpopulations and transitional states in adult mouse erythropoiesis. We aim to decode the gene regulatory programs behind these transitions and understand the sequence and interplay of transcription factors and gene programs in erythropoiesis. This comprehensive understanding will enable us to propose new cell engineering protocols for efficient and controlled differentiation, potentially transforming approaches in hematopoietic research and therapy. A comprehensive training plan will develop the principal investigator’s skills as a physician-scientist under the guidance of the sponsor (Jie Liang, PhD, University of Illinois at Chicago) and co-sponsor (Konstantinos Chronis, PhD, University of Illinois at Chicago).

NIH Research Projects · FY 2025 · 2024-09

PROJECT SUMMARY/ABSTRACT Fatal opioid overdoses are more frequent among populations with low access to harm reduction (HR) services and with high substance use-related stigma (a major barrier to accessing HR services). One such population is older Black people who use drugs (PWUD) on the West side of Chicago. In 2022, Black adults aged 55-64 in Illinois had an opioid fatality rate ten times higher than that of non-Hispanic white adults of the same age, and four times higher than younger adults of any racial/ethnic group. Over 34% of Chicago's opioid-related EMS responses in 2023 were located in predominately Black communities on the West side, but Black adults in Chicago access HR services at lower rates than do other racial/ethnic groups (e.g., they comprise only 15% of regular clients at the West side site of our community partner organization Community Outreach Intervention Projects [COIP]), likely due to stigma and other barriers. To help address these barriers and increase HR service access among this population, the proposed clinical trial will evaluate a novel intervention that will recruit non-substance-using friends and family members of people who use opioids and live on the West side of Chicago, educate them on HR tools and services, and train them to become peer HR support champions. We will ask them to recruit one friend or family member who uses opioids to the study, who we will also provide with an educational training on overdose risk reduction and available HR tools and services. The intervention will then facilitate a counselor-led initial conversation between peer HR support champions and their friend or family member who uses opioids to help establish HR support, and provide all participants with naloxone and fentanyl test strip kits. This intervention will not only provide another mechanism through which PWUD can access HR tools and services, thereby reducing logistical barriers, but should also reduce stigma and increase social support by facilitating and normalizing open conversations about HR between PWUD and their non- PWUD HR support champions. Participants of a focus group we conducted among West side PWUD thought this intervention would be helpful, said they would be willing to participate in it, and said they knew someone who could participate as their non-PWUD peer HR support champion. To facilitate recruitment of older adults, we will work with local faith-based and service organizations (with which our consultant from Breakthrough Urban Ministries will help us build relationships) and educate them about the importance of HR. We will evaluate the intervention's efficacy for a) increasing uptake/use of HR services, b) decreasing overdose frequency, and c) decreasing stigma and other barriers to accessing HR services, both i) by examining change over time among intervention participants, and ii) by using propensity-score matching methods to compare outcomes between intervention participants and a comparison group of PWUD who have recently accessed HR services from one of our community partners (COIP or West Side Heroin and Opioid Task Force).

NIH Research Projects · FY 2024 · 2024-09

OVERALL PROJECT SUMMARY The University of Illinois Chicago (UIC) Center for Climate and Health Equity (CECHE) unites multi-disciplinary researchers including cutting edge climate scientists with epidemiologists, physicians, exposure and data scientists, community engagement scholars, urban planners and health policy experts to advance cutting-edge climate health research. These interdisciplinary teams are critical in identifying innovative solutions to promote equity and address climate change threats in urban areas. CECHE's vision is to use team science and a cumulative impacts framework to advance innovative solutions- based research and policies to combat climate health inequity and fulfill its mission of responding to priorities of the most vulnerable environmental justice (EJ) communities in Chicago, the nation, and beyond. The center’s initial research theme “nature-based solutions for mitigating adverse climate health impacts in Chicago and beyond” is in direct response to community partner priorities. As a minority-serving institution, ranked 13th among top public universities and 8th in social mobility, UIC is an ideal institution to establish CECHE and promote diverse perspectives into climate change and health research. The Administrative Core (AC) will provide overall management and evaluation of the Center's activities. An internal advisory committee, external advisory committee, and community advisory board will govern the AC. The AC will also support communication across the center, support career advancement, and create a pilot project program to accelerate innovative climate and health research. The Community Outreach and Engagement Core (COEC) will use an iterative process for capacity building and identification of climate solutions working in collaboration with community EJ partners, healthcare providers, and policymakers. Using a train-the-trainer model, COEC will also establish a Climate Health Institute to build capacity and train community health ambassadors within EJ communities. COEC leaders, with EJ partners, will also conduct innovative urban health design studies to create nature-based toolkits for promoting health benefits of green infrastructure (GI) and policy development at local, regional, and national levels. The Geospatial Data Analysis Core (GDAC) will build a highly resolved spatiotemporal data architecture linking GI with environmental factors (PM2.5, O3, heat, flooding), electronic health records, and different types of nature-based GI features across multiple spatial and temporal scales, advancing multidisciplinary nature-based research. These scales include satellite imagery of tree canopy, the normalized difference vegetation index (NDVI), and Google Street View with land use and cover data. The Research Project will examine how features of urban GI 1) impact air quality and heat islands, 2) mitigate flooding, and 3) influence cardio-respiratory outcomes such as hospitalizations and ED/ER visits in Chicago. Over time, CECHE will work with other Climate and Health Centers to become a pioneer in urban climate health equity and share innovative strategies for building climate-resilient and healthy communities.

NIH Research Projects · FY 2026 · 2024-09

This K08 proposal will address a critical need for evaluating and understanding the implementation of community health worker (CHW) mental health models to increase evidence-based treatment (EBT) in populations who are less likely to receive mental healthcare. The Common Elements Treatment Approach (CETA) is an effective transdiagnostic EBT designed to be delivered by lay providers with little to no prior mental health training (i.e., CHWs). CHWs have demonstrated effectiveness in delivering CETA and other EBTs globally, but there is little evidence to guide domestic implementation of these models. The goal of this project is to evaluate the implementation of CHW delivered CETA with Spanish-speaking Latino parents to establish initial feasibility and proof of concept prior to expanding study of CHW EBT models across a variety of other populations and settings. In Aim 1, the PI will collaborate with stakeholders to refine CETA fit for the local context and population by using ADAPT-ITT, an implementation framework for EBT refinement. Aim 2 will use mixed methods to assess multilevel implementation determinants during the CETA training period, which includes initial CHW implementation with training cases, and use this information for ethics-driven implementation planning. Aim 3 is to conduct a randomized feasibility pilot of CHW-delivered CETA in Spanish with Latino parents to examine intervention acceptability and feasibility; feasibility of recruitment, randomization, and measurement procedures; and treatment engagement. Participants will be randomized to receive CETA immediately or after a 5 month delay. Administrative data (i.e., patient attendance, retention), patient-report data (i.e., validated mental health symptom measures pre-, during-, and post-treatment), and provider-report data (i.e., fidelity) will be used to evaluate feasibility. Dr. Gustafson’s long-term career goal is to evaluate, adapt, and implement CHW mental health models to increase the availability of mental health treatment for populations with unmet mental health needs. To meet her career objectives and the aims of this research project, the applicant requires additional training in: 1) community-engaged clinical trials; 2) implementation science; and 3) ethics related to implementing CHW mental health models. Supported by an interdisciplinary team of experts and an institutional environment invested in supporting innovative initiatives to improve the mental health of all communities, this K08 will launch the PI into a successful career as an independent clinical scientist. This project will also provide necessary data for Dr. Gustafson’s future R01 submission of a large-scale effectiveness-implementation trial of CHW-delivered EBT across multiple clinics and settings.

NIH Research Projects · FY 2024 · 2024-09

Abstract The history of glial cells is neglected in comparison to that of neurons, and this holds true a decade after the first grant application. We can debate about the possible reasons, including the fact that glial cells remain on the fringe of neuroscience, likely because they do not carry nerve impulse and cannot be compared to computers and Artificial Intelligence. A way to enhance the second-class citizen status of glial cells is writing their history. We are currently completing a humanities history book encompassing all glial cell types in the body. We aim for an historical narrative including interactions of glial cells with neurons limited to 5 years ago to avoid scientific artefacts. A decade and several thousands computer files later, the book manuscript merely feels like the tip of an iceberg, despite being a significant dent in the historical treasures waiting to be discovered and translated. The sheer amount of newly discovered material on glia is mind- boggling. This application requests funds to complete a thorough historical account from glia perspective, organized at the cellular level and presenting an up-to-date landscape of all glial cell type interactions with neurons. The book entices writing significant new material for both PI and contributors since no glia history book exists. Twenty two contributors and the PI spent a considerable amount of time to write and research their chapter, often in vast excess of words and references because writing from scratch. The editors successfully negotiated with publisher Wiley a word count increase from 160k to 200k. The current challenge is to finish writing and comply with this word limitation. Practically, a history book will guide scientific readership through the recent explosion of literature that is challenging to capture the whole picture of glia role in the nervous system. A widely acknowledged consensus among scientific historians is that an historical perspective on how our understanding of the nervous system has advanced will lead to new insights on how further advances can be made. No neurological diseases can be understood without an integrated concept of the complexity of glial cells within neuronal networks.

NIH Research Projects · FY 2025 · 2024-09

ABSTRACT Children with developmental delays and disabilities face persistent challenges in accessing recommended clinic- and school-based therapeutic services, which are critical for supporting developmental, educational, and behavioral outcomes. Studies also show parents benefit when their children receive recommended therapies with improvements in mental health, reduced stress, and enhanced quality of life. Thus, a lack of clinic- and school-based therapeutic services during key periods of brain development, including the preschool years, can substantially contribute to preventable morbidity. Disparities in service access are well-documented among children with developmental delays and disabilities, with Black and Latino/a preschool-age children experiencing some of the lowest rates of receipt of recommended care. In response, the scientific community has called for research to advance understanding of the factors contributing to these health disparities. The objectives of this research are to address the following gaps in the literature: 1) to examine how parental knowledge, school resources, insurance coverage, and neighborhood characteristics, including employment rates and transportation availability, influence access to guideline-concordant school and clinic-based therapeutic services for preschool-age children with developmental delays and disabilities (PCw/DD), and how these factors may affect health outcomes; and 2) to identify modifiable protective factors that may buffer these relationships. Our interdisciplinary team will meet the objectives of this study by conducting a mixed-methods longitudinal study enrolling 300 Black and Latino/a PCw/DD and their parents from clinics across Chicago and collecting prospective data at five time points over three years. We will also convene a Multidisciplinary Advisory Board who will meet biannually to consider how our research findings can inform educational and healthcare practice and policy. The proposed research is significant for its potential to advance scientific knowledge of how aspects of a family’s daily life influence access to school- and clinic-based services; how service gaps and delays impact health outcomes; and the role of key protective factors in mitigating these effects. Results will generate actionable data to guide the development of medical, educational, and public health interventions aimed at improving access to recommended services, supporting family well-being, and promoting optimal developmental outcomes for all children.

NIH Research Projects · FY 2024 · 2024-09

Project Summary In this R34 application, we propose to conduct an early phase clinical trial of a mind-body intervention to promote whole person health—specifically, to develop and evaluate the feasibility and acceptability of a tailored progressive muscle relaxation and walking intervention to reduce fatigue for adults with end-stage kidney disease (ESKD). Fatigue is an extremely concerning and debilitating symptom that affects the majority of adults with ESKD. Fatigue has a profound negative impact on whole person health for adults with ESKD through its influence on morbidity, quality of life, social relationships, and functional independence. There are no standard-of-care therapies available to alleviate fatigue in ESKD. There is strong evidence, from rigorous randomized controlled trials, that progressive muscle relaxation can reduce fatigue, yet this approach has been understudied in the diverse population of adults with ESKD in the U.S. Physical activity in the form of walking can also reduce fatigue, but again has been understudied as a way to reduce fatigue in adults with ESKD. There has also been minimal investigation into the feasibility and acceptability of multicomponent mind-body interventions to reduce fatigue in adults with ESKD, with an absence of any studies utilizing both progressive muscle relaxation and walking, or utilizing text messaging as a low-demand method of delivering mind-body intervention content. Our objective is to fill these research gaps by developing and evaluating such an intervention. In Aim 1, we will use content from two established evidence-based interventions—a progressive muscle relaxation intervention and a fatigue-reducing walking intervention—and work with a patient advisory board to develop a mind-body intervention tailored for adults with ESKD and fatigue. In Aim 2, we will evaluate the feasibility and acceptability of the new Fight Fatigue intervention using a two-arm design (n=40 participants, randomized to either the combined progressive muscle relaxation and walking intervention or ESKD education/attention control). The 12-week intervention will be delivered with brief in-person training followed by text messages. Findings from this study will provide the necessary data to design and test a large- scale efficacy trial to reduce fatigue for adults with ESKD and thus promote whole person health for this at-risk population.

NIH Research Projects · FY 2024 · 2024-09

Hemolysis, with the release of extracellular free heme and hemin, is thought to play a major role in the deadly pulmonary complications of sickle cell disease. Acute chest syndrome is the second most common cause of hospitalization for sickle cell disease patients and the leading cause of death. Pulmonary hypertension complicates sickle cell disease in up to 10% of patients and is associated with significant morbidity and mortality. Current therapies, including hydroxyurea and blood transfusions, are mostly supportive and have been used for decades, while specific therapeutics targeting the pulmonary circulation have been elusive. We hypothesize that hemin, as a breakdown product of cell-free hemoglobin, has direct effects on the pulmonary endothelium and that concentration specific effects contribute to both the acute and chronic complications of sickle cell disease. In this proposal, we will evaluate the specific effects of chronic, low concentration hemin in the development of pulmonary vascular remodeling and pulmonary hypertension. We propose direct effects on pulmonary artery endothelial cells through Toll-like receptor 4 lead to endothelial-to-mesenchymal transition. Endothelial cells undergoing trans-differentiation will have increased proliferative and migratory properties as well as cytoskeletal rearrangement leading to an invasive, dysfunctional phenotype. In animal models of chronic hemolysis, this will manifest as pulmonary vascular remodeling with the development and progression of pulmonary hypertension. Similarly, high concentration hemin will have effects on the pulmonary endothelium through Toll-like receptor 4, but overwhelming stimulation will lead to activation of necroptosis and programmed necrosis. This necroptotic cell death will result in endothelial barrier dysfunction and acute lung injury in cell and animal models as a mechanism for the development of non-cardiogenic pulmonary edema and acute chest syndrome. The concentration dependent effects of hemin on pulmonary artery endothelial cells and animal models of hemolysis in our work mimic the spectrum of pulmonary complications in sickle cell disease patients. Therefore, this mechanistic work will complement a translational approach associating circulating hemin abundance with pulmonary complications in sickle cell disease patients and utilizing RNA sequencing technology to identify differentially expressed genes and genomic signatures associated with the presence of pulmonary hypertension and acute chest syndrome. Our long-term goals are to utilize our understanding of the mechanisms of endothelial dysfunction in both acute and chronic pulmonary complications of sickle cell disease and other chronic hemolytic syndrome in order to identify novel molecular targets, develop innovative therapies, impact health and survivorship of patients through our research and clinical care.

NIH Research Projects · FY 2025 · 2024-09

PROJECT SUMMARY Perinatal depression (PND), defined as depression during pregnancy and up to one year postpartum, affects more than 20% of pregnancies and disproportionately impacts Black Women and Latinas. PND increases risk of preterm birth and infant neurodevelopment deficits. Yet we still do not fully understand the pathobiology of PND, which limits efforts to improve its prevention, identification and treatment. Interactions between the host and microbial communities that reside in the gut are essential for human health. Gut microorganisms play an important role in producing beneficial metabolites, including the neurotransmitters serotonin and gamma- aminobutyric acid (GABA). The gut microbiota bidirectionally communicate with the brain, an interaction mediated by the neurological, immune, and endocrine systems and coined as the microbiota-gut-brain axis (MGBA). Our initial pilot results from a longitudinal study of low-income women of color (n=42) early in pregnancy, which showed that multiple attributes of the MGBA were associated with depressive symptom severity, including production of short chain fatty-acids, metabolism of tryptophan and GABA, and systemic inflammation mediated by bile acid metabolism. Although our initial data points to new MGBA signatures linked to depressive symptom severity in the first and second trimesters, additional work is needed to determine whether these signatures and their interactions extend beyond the second trimester. Further, microbial metabolism is driven both by the interactions between metabolites and by the interplay between microbial metabolic systems with maternal inflammatory system and metabolism. Thus, determining the causal influence of these new MGBA signatures on depressive symptom severity during the perinatal period requires using approaches that can establish the effect of systems (networks) coupling in MGBA functioning. Here, we propose a clinical translational study to determine the role of MGBA in PND by using a systems biology framework and an experimental animal model to assess causality. To test this, we will draw from our research infrastructure to recruit 158 women (55% Black, 30% Latina) early in pregnancy (<16 gestational weeks) and follow them bimonthly for up to 6 weeks postpartum. We will assess mood; lifestyle (diet, physical activity, sleep); and heart-rate variability (a proxy for stress) and will measure microbial genome and meta-metabolome and maternal blood transcriptome and metabolome. In Aim 1, we will employ interpretable machine learning models to predict depressive symptom severity concurrently and prospectively. In Aim 2, we will establish coupling mechanisms that regulate symptom severity by modeling the interplay between microbial and maternal metabolic, genetic and regulatory systems using network theory. In Aim 3, we will determine the causal role of gut microbiota in symptom severity in a female pregnant germ-free mouse model using fecal microbiota transplants. Our paradigm-shifting data-driven proposal will identify host-microbial features predictive of perinatal depressive symptom severity and modifiable risk factors for prevention and treatment of PND, with causality tested in animal models.

NSF Awards · FY 2024 · 2024-09

Artificial Intelligence (AI) is making huge strides across a range of areas, including natural language processing, computer vision, reinforcement learning, and other machine learning areas. Researchers at the University of Illinois Chicago (UIC) are uniquely positioned to lead research at the nexus of AI and healthcare using the vast amount of data available from the UI Health system. The Graphics Processing Unit (GPU) Cluster for Accelerating Health Insurance Portability and Accountability Act (HIPAA)-Compliant Data-Driven Research enables the development and use of computationally-intensive artificial intelligence (AI) models for a variety of health-related research projects and applications at the University of Illinois Chicago. The project’s novelties are its research capabilities (HIPAA-compliant data analysis and modeling) in applying AI to sensitive healthcare data within the field of computer science. The project's broader significance and importance is refining health treatments and improving health outcomes for individuals from groups that are not as well-represented in other university-associated health systems. This instrument enables leading-edge, cross-disciplinary research on AI and health/medicine, and is a key catalyst for accelerating AI’s progress in providing health benefits to the diverse population served by University of Illinois Health. This project uses six mini-supercomputers and just under two petabytes of storage, creating a catalyst for AI and Machine Learning research, designed for the handling of sensitive data, and purpose-built for simulation, data analytics, and AI. The software-defined storage is designed to meet the storage requirements of HIPAA data, offering features like encryption, data deduplication, and data-at-rest protection. The instrument is the foundation for transformative research, including: knowledge extraction from electronic health records, language-guided health monitoring and assessment, opioid risk detection, ophthalmic disease detection, prognostication of age-related macular degeneration, and cancer detection using graph neural networks. 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 · 2024-09

Abstract People with type 1 diabetes (T1D) are disproportionately affected by cardiovascular disease (CVD). CVD is a leading cause of death in T1D, contributing to 40% of mortality. Sleep is recognized by both the American Heart Association and the American Diabetes Association as a critical health behavior to maintain glycemic control and reduce CVD risk. Short and/or irregular sleep have been associated with reduced glycemic control and non-dipping blood pressure in T1D, both of which are predictors of CV events. Emerging data suggest that behavioral sleep interventions targeting short or irregular sleep led to improved glycemic parameters. However, little is known about the mechanism by which improving sleep duration and/or regularity improves glycemic control and reduces CV risk in T1D. Our group and others have shown that people with T1D often experience poor sleep health, including inadequate sleep duration, sleep irregularity, and poor sleep quality. In particular, studies from our lab have demonstrated that objectively measured sleep regularity (irregularity in sleep timing or duration) is a strong predictor of glycemic control and insulin resistance. We have tested a behavioral sleep intervention among adults with T1D and demonstrated improved sleep regularity and time spent in a desirable glucose range from continuous glucose monitoring (CGM). Furthermore, we also found that poor self-reported sleep quality in young T1D adults was associated with reduced flow mediated dilatation (FMD), a marker of endothelial dysfunction. These observational studies demonstrate that the timing and quality of sleep are related to key metabolic and CVD risk markers in T1D, but lack the detailed measurements and experimental design needed to determine mechanisms. The goals of this proposal are to examine the mechanisms by which improving sleep regularity through behavioral sleep intervention affects glycemic control and CVD risks in T1D adults. We propose to extend our previous research by conducting a mechanistic study using a sleep stability manipulation. We hypothesize that sleep stability impacts glycemic control and CV outcomes by improving circadian regulation. We will conduct a 4-week behavioral sleep stability intervention in 80 T1D adults with irregular sleep, utilizing a sleep pre/post design. Circadian regulation will be assessed by dim-light melatonin onset (DLMO), melatonin metabolite amplitude (overnight urinary 6-sulfatoxymelatonin levels), actigraphy- derived rest-activity rhythm, endothelial cell CLOCK gene mRNA expression, and known zeitgebers of the central and peripheral circadian clocks (light exposure, meal timing). Main glycemic outcomes will be assessed by CGM, A1C, and assessment of insulin sensitivity. Main CV outcomes will include 24h blood pressure and endothelial FMD and other secondary vascular measures (pulse wave velocity, carotid intima media thickness, and echocardiographic parameters). Sleep will be objectively recorded. All parameters will be measured at baseline and end of intervention. This proposal will advance the understanding of mechanisms by which improving sleep regularity influences glycemic control and cardiovascular risk in T1D.

NIH Research Projects · FY 2024 · 2024-09

Lifestyle health behaviors, such as physical activity, cognitive activity, healthy diet, and social activity, are low- risk, non-pharmaceutical strategies that may help protect against cognitive decline and risk of Alzheimer's disease and related dementias (AD/ADRD). However, causal evidence across observational and trial research is inconsistent. There remains a need to further understand the impact of lifestyle health behaviors on cognitive outcomes, including what type(s) of behavior and magnitude of behavior change have greatest impact, and if impact differs across diverse at-risk subgroups. The purpose of our proposed study, InLife (Individualized Lifestyle Change For Every Aging Brain), is to harmonize existing participant-level data from randomized controlled trials (RCTs) to examine how changes in lifestyle health behavior impact cognitive outcomes across diverse adults. We will leverage previously collected de-identified data from 12 U.S. trials representing 9,570 older adults for de novo analyses. In trials that agreed to contribute data, one or more lifestyle health behaviors (physical activity, cognitive activity, healthy diet, and/or social activity) were targeted and cognitive outcomes were assessed, including change in cognitive function (primary outcome: episodic memory and executive function, secondary outcome: perceptual speed and global cognition) and (in some) incidence of mild cognitive impairment or dementia (exploratory outcome). Aim 1: Quantify impact of changes in lifestyle health behaviors on cognitive outcomes. Following our innovative harmonization methods based on an item response theory framework, we will harmonize data across trials to test hypotheses that (a) the association between amount of change in behaviors and cognitive outcomes will be strongest for those with lower initial levels of the targeted behavior and (b) there will be nonlinear effects of increases in behaviors on cognitive outcomes such that benefits will diminish as behavior change increases (i.e., diminishing returns). Aim 2: Examine determinants of health that moderate (enhance or inhibit) impact of lifestyle health behavior change on cognitive outcomes. We will evaluate whether associations between lifestyle health behavior and cognitive outcomes in Aim 1 differ between subgroups. Informed by National Institute on Aging and World Health Organization frameworks, we focus on subgroups based on determinants of health that are structural/social (age, sex, education, racial background, ethnic background), biological (e.g., cardiometabolic disease), and environmental (e.g., rural vs. urban, U.S. region, area deprivation index [API]). Aim 3 (exploratory): Determine the impact of lifestyle health behavior combinations on cognitive outcomes. We will evaluate whether two or more behaviors together have more impact than one alone and quantify which combinations of behaviors are most impactful. The proposed InLife study will result in the first harmonized dataset of U.S. trials testing lifestyle interventions for cognitive outcomes. This research will be influential in shaping clinical guidelines focused on realistic lifestyle health behaviors for cognitive outcomes across diverse aging populations.

NIH Research Projects · FY 2026 · 2024-09

Young people in the U.S. legal system are more likely to experience adverse substance use and sexual health outcomes compared with peers who have not been arrested. Low emotion regulation appears to function as a common mechanism on the individual level, and it can be improved via mindfulness meditation. Moreover, meditation can be taught by smartphone app, holding the potential to reach youth on probation—who make up the large majority of all young people in the legal system—in their daily lives. In a prior NIDA-funded study (K99/R00DA047890), we collaborated closely with youth and other stakeholders in Cook County, the 2nd largest juvenile legal system in the U.S., to identify determinants of implementing a 1-month mindfulness meditation app with youth on probation, develop a package of corresponding strategies to promote app adherence (i.e., ongoing usage), and run a fully-remote pilot RCT with n=70 youth on probation. The pilot data strongly supported feasibility and acceptability including very high objective app adherence (mean=20.40 of 30 daily meditations, SD=7.99) and retention at 1 (86%) and 6 (80%) months. There were also multiple signals of greater reductions in substance use problems and sexual risk behaviors among youth randomized to the meditation app than to a health promotion control app matched for time and structure. Throughout the pilot RCT, youth and officers requested that the meditation app be sustained in probation programming if it demonstrates effectiveness. This proposal is a response to our stakeholders’ requests. The proposed study will proceed in 2 main steps corresponding to (1) testing the effectiveness and individual-level implementation of the meditation app, and (2) starting to plan for its sustainability on the organizational level. First, we will leverage our successful pilot RCT design to run a hybrid type 2 effectiveness-implementation RCT with N=300 youth on probation in Cook County. Youth will be randomized to use the meditation or health control app daily for 30 days. Objective usage data will identify non-use and trigger adherence support (e.g., texts) via an adaptive design. Youth will report on the health outcomes (substance use and sexual health) and the mechanistic target (emotion regulation) at baseline, 1, and 6 months. They will also complete 1-week “bursts” of ecological momentary assessment (EMA) at baseline and 1 month to supplement the retrospective emotion regulation data with real-time, ecologically valid reports. Together, this will allow us to test if the meditation app is effective in reducing substance use problems and sexual risk behaviors (Aim 1a), if improvements in emotion regulation mediate these effects (Aim 1b), and if youth adequately adhere to the app (Aim 2). To start ystematically planning for sustainability of the meditation app in probation programming (Aim 3), we will interview youth on probation, probation officers, and probation leadership on organizational-level determinants of sustaining the app and implementation strategies for doing so. We will then run a pilot sustainability trial with N=20 youth to test feasibility and acceptability of those strategies.

NIH Research Projects · FY 2025 · 2024-09

The mechanism underlying neuronal hyperexcitability, as a result of excitation-inhibition (E-I) imbalance, leading to cognitive deterioration in Alzheimer’s disease (AD) is not fully understood and effective approaches to prevent or reverse memory deficits are unavailable. Our multimodal MRI connectomics demonstrated a hyperexcitation connectome phenotype in healthy women ApoE4 carriers as they age, raising the possibility that at least some sex differences in AD may be explained by E4 female carrier-specific neuronal hyperexcitation. In support of this, resting state functional magnetic resonance imaging (rs-fMRI) in APPNL-G-F/NL-G-F revealed higher interhemispheric functional connectivity in the hippocampus of female mid-life mice. Further, we observed reduced functional anisotropy, altered myelin and oligodendrocyte count, and importantly, altered transcription phenotype of excitatory and inhibitory neurons in the hippocampus of these female mice. The antiseizure drug Levetiracetam (LEV) is currently being tested in human trials, with early data suggesting that it does improve cognition in those with signs of hyperexcitability. However, there is conflicting information concerning the efficacy of the drug and its mechanism is not fully understood. This collaborative, multidisciplinary MPI program is aimed at unraveling the efficacy of LEV in humans and mouse models by leveraging expertise in computational and experimental neuroscience. We will test the hypothesis that hyperexcitability is more prevalent both in ApoE4 woman carriers and in female FAD-linked APPNL-G-F/NL-G-F and LOAD-linked ApoE4 knockin mice and that LEV treatment will normalize hyperexcitability and cognitive deficits in a sex-dependent manner. In the R21 Phase, the experimental approach will establish feasibility of LEV treatment in APPNL-G-F/NL-G-F female mice. The computational approach will develop new biophysically - informed computational framework for modeling experimental mouse data. In the R33 Phase, we will establish the effect of LEV on hyperexcitability and pathology in association with sex, ApoE4 and amyloidosis, and generalize our computational approaches from mouse hippocampus to the entire brain to characterize the whole-brain biophysical parameters of E-I balance in AD with or without LEV treatment. The results of this program will provide novel insight into the molecular mechanism of E-I and LEV, and its therapeutic value in AD.

NIH Research Projects · FY 2024 · 2024-09

Evidence shows that gay men may be particularly likely to leave their countries, whether by choice or force. Among the general gay population, stigma at multiple levels, and subsequent stress reactions contribute to co-occurring HIV and mental health risks. Stressors negatively influence gay men’ HIV risks and mental health. In the US, the experiences of gay men born outside of the US may be different from those born in the US, in particular because of their exposure to high stigma, high HIV risk, and poor mental health in their home countries. Despite this confluence of risks, there are no interventions that address the magnitude of intersectional stigma on HIV risk and mental health among gay men born outside of the US. Theoretically informed interventions can buffer against the health risks of stigma when tailored to address stress reactions among gay men; however, most interventions do not account for multiple and intersecting sources of stigma, and none focus on stigma related to being born outside of the US. Our intervention, ESTEEM (Effective Skills to Empower Effective Men), a stress focused cognition behavioral therapy (CBT) has shown strong efficacy in improving mental, behavioral, and HIV (e.g., condom use and pre-exposure prophylaxis [PrEP]) health outcomes among gay men. Our preliminary interviews in the US with Arab gay men born outside of the US (N=16) suggest intervention preferences for an online group delivery format that connects gay men with shared experiences, irrespective of their current geographical location in the US, thus facilitating greater reach and effective recruitment, to be led by trained counselors that share similar identities. Following the ADAPT-ITT model, this study aims to adapt and pilot-test the ESTEEM intervention to target the underlying mechanisms linking gay men’ intersectional stressors to co-occurring HIV risks and poor mental health outcomes. In Aim 1, we will seek input from multiple stakeholders using qualitative interviews with 15 mental health experts and 15 Arab gay men born outside of the US and adapt ESTEEM for online group delivery and for Arab gay men in the US. In Aim 2, we will randomize 60 participants to receive 10 weekly, 90-minute online-based group sessions, either immediately (immediate intervention group, n=30) or after 3 months (waitlist control group, n=30) to evaluate intervention acceptability and feasibility and to determine preliminary efficacy on primary (HIV-risk behavior) and secondary (mental health) outcomes.

NIH Research Projects · FY 2025 · 2024-09

Mononuclear non-heme Fe and Cu sites in oxygenases functionalize the highly inert C–H bonds of substrates involved in metabolism, natural product synthesis, and biogeochemical cycles, all of which directly impact human health. Despite the importance of these enzymes, the structures and properties of many key enzymatic intermediates are not fully understood. Synthetic analogs of the intermediates facilitate more in-depth studies, but current models have shown that the protein environment, or lack thereof, significantly affects reactivity. Site-isolation, weak-field ligands, and noncovalent secondary interactions are hallmarks of oxygenase active sites, but these features are difficult to simultaneously replicate in synthetic systems. To address these gaps, our laboratory has developed single-crystalline peptide assemblies (or “frameworks”) that bind metals in their porous channels using amino acid residues. Our central hypothesis is that usage of peptide-based coordinating groups allows direct comparisons between the model system and the enzyme, while the crystalline matrix stabilizes reactive species for structure determination by X-ray crystallography. We have reproduced the critical facial triad coordination (2His/1-carboxylate) for non-heme Fe sites, from which we will explore the structures and chemistry of the fleeting high-valent intermediates relevant to the enzyme mechanism. The Cu versions of these frameworks are also appropriate models for the active site of particulate methane monooxygenase (pMMO), whose active site has been long-debated and recently postulated to be a single Cu site bound to a 2His/Asp ligand set. Given the modularity and ease of peptide synthesis, we will tune the structures of these sites to obtain detailed structure-function correlations that will illuminate how protein environments elicit remarkable inorganic reactivity. The outcomes of this research are expected to fill in key gaps in the mechanism of these enzymes and inform the design of mechanism-based therapeutics, as well as catalysts for pharmaceutical synthesis, and water remediation.

NIH Research Projects · FY 2025 · 2024-09

During chemotherapy, 34% of breast cancer survivors (BCS) experience cancer treatment-related cognitive impairment (CRCI). CRCI degrades memory and executive function as well as quality of life. As the number of BCS is expected to increase by one million by 2030, there will also be an increase in the prevalence of CRCI. One understudied risk factor is diet, with an underlying mechanism being the gut microbiota. Post-treatment, increased fruit, vegetable, and fat consumption protects against CRCI in BCS. However, neither this relationship nor the underlying mechanisms, such as the gut microbiome, has been investigated during treatment, when CRCI begins. Adherence to a Mediterranean diet (Med Diet) has been shown to improve memory and to increase levels of Faecalibacterium prausnitzii, a gut bacterium associated with better cognitive scores in non-cancer populations. In BCS undergoing chemotherapy, this bacterium is linked with neurological toxicity. A Med Diet during treatment may therefore reduce CRCI incidence or severity via the gut microbiome. The objective of this study is to determine if diet is related to CRCI in BCS and if the gut microbiome is a mechanistic link. My central hypothesis is that higher adherence to components of a Med Diet, e.g., fruits, vegetables, monounsaturated fats, and fiber, will be related to higher scores on neuropsychological tests administered during chemotherapy, and that the gut microbiome will mediate this relationship. The aims of this study are as follows. Aim 1: Determine the relationship between components of a Med Diet, gut microbiome, and cognitive function in 30 BCS before, during, and after adjuvant chemotherapy treatment for breast cancer. Aim 2: Develop a Med Diet intervention for BCS by conducting semi-structured interviews among BCS who have recently completed treatment to understand their views and attitudes toward a Med Diet. Aim 3: Conduct a 12-week Med Diet pilot feeding study among 30 BCS undergoing adjuvant chemotherapy. To complete these aims, I need an interdisciplinary mentoring team to train me in 1) conducting research in cancer patients, 2) designing a controlled feeding trial, 3) qualitative data collection and analysis, and 4) advanced analysis of complex dietary, neuropsychological, and gut microbial datasets. Through training with this mentoring team and through the coursework and stellar facilities offered by my institution, I will complete the K99 phase of this proposal and thus (1) understand the relationship between diet, the gut microbiome, and cognition during breast cancer treatment, (2) understand BCS tastes and preferences of a Med Diet during treatment, (3) provide preliminary data for the submission of two R01 grant submissions; and (4) prepare me to lead a feeding trial during the R00 phase of the award to understand how the gut microbiome can be manipulated through a Med Diet to reduce CRCI. This K99/R00 will allow me to become an independent investigator leading gut microbiome-focused, patient-informed dietary trials to reduce CRCI’s negative impact.

NIH Research Projects · FY 2026 · 2024-09

Despite increased clinical awareness, sepsis remains a leading cause of death and high healthcare costs worldwide. Sepsis is a life-threatening condition characterized by an exaggerated immune response to infection, which can lead to organ dysfunction and even death. However, the inflammatory response pathways and molecular mechanisms that underlie the disease remain largely unresolved. Autophagy of endoplasmic reticulum (ER-phagy) serves as a disposal pathway for misfolded proteins and has been implicated in various diseases, including diabetes, cancer, metabolic diseases, and some neurological disorders. Using ER-phagy receptor Fam134b knockout mice, we have identified a novel and essential role of ER-phagy in the host immune response during sepsis. Our findings indicate that depletion of FAM134B entirely abolished NLRP3 (Nucleotide-binding oligomerization domain-Like Receptor containing Pyrin domain 3) inflammasome activation and the generation of IL-1β in macrophages. Additionally, Fam134b knockout mice exhibited higher survival rates, less lung injury, lower bacterial load, and lower levels of proinflammatory cytokines in experimental models of sepsis. Notably, septic patients show upregulation of NLRP3 gene in peripheral blood monocytes and elevated levels of IL-1β and IL-18 in the blood. We propose the central hypothesis that sepsis induces macrophage ER-phagy, driving NLRP3 inflammasome activation, cytokine release, and inflammatory tissue injury. We will use state-of-the-art methods, including intravital microscopy, adoptive macrophage transplantation, and macrophage RNA sequencing, to investigate these hypotheses and validate them in human sepsis samples. Our proposal is organized into three specific aims. 1) To define the role of macrophage ER-phagy in NLRP3 inflammasome activation and lung inflammatory injury during sepsis. 2) To decipher the molecular mechanisms by which ER-phagy drives NLRP3 inflammasome activation. 3) To test the therapeutic potential of targeting macrophage ER-phagy for the treatment of septic injury. The successful completion of our proposed studies has significant potential to impact the future development of novel therapeutic strategies for bacterial sepsis, ultimately improving patient outcomes and decreasing the burden of this life-threatening disease on global healthcare systems.

NSF Awards · FY 2024 · 2024-09

This project focuses on the mathematical area of probability theory, the study of random structures. Random structures are ubiquitous throughout the sciences for their use as models as well as their use in the design of algorithms. The main focus of this project is on random structures in high dimensions, meaning random structures with many degrees of freedom. Some examples are random matrices, random sphere packings and random polynomials. Each of these classes of models has direct application in various other scientific fields such as data science, statistical physics and theoretical computer science. The project includes workshops for early-career researchers and graduate students, with an aim of bringing together disparate mathematical subfields. The project consists of three components, with specific problems chosen with the aim of developing new techniques in high-dimensional probability and the use of analytic approaches in probability theory. The first component of the project concerns universality properties of random polynomials along with their use in optimization and algorithmic problems. The second component focuses on the structure of random sphere packings using connections to more combinatorial objects such as independent sets. The third component studies the non-asymptotic theory of random matrices with a focus on extremal behavior such as understanding the behavior of the least singular value in models without independent entries. 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 · 2024-09

Modern scientific research relies on processing large amounts of data using programs that perform hundreds or thousands of operations in parallel. To make it easier to write these programs, scientists use tools called compilers that automatically translate ordinary, one-operation-at-a-time (“sequential”) programs into massively parallel ones. But these translations may be unreliable: Parallel programs are hard to understand and may suffer from unpredictable interactions. In addition, cutting-edge research in the field is leveraging large language models (LLMs) to generate parallel output, and these models come without any guarantees of correctness. This project aims to improve the reliability and the performance of parallelizing compilers by automatically checking that translated code has exactly the same functionality as the original code. This will involve precise modeling of the behavior of both sequential and parallel programs, developing a tool that can compare sequential and parallel programs, and mathematically proving that the tool’s output is always reliable. If a translation passes the check, the translated parallel code is guaranteed to behave in the same way as the sequential code. This project will improve the correctness of parallel programs across many fields of experimental science, increasing the pace of scientific advancement and reducing the harm from incorrect conclusions based on computational errors. The project will also support the training of the next generation of compiler writers and researchers, who will build more efficient and reliable tools for future scientific computing. As scientific researchers gain access to more powerful computers and larger amounts of data, they become increasingly reliant on correct and efficient parallel computing. Bugs in parallel code can lead to incorrect computations and misleading models -- and waste time, electricity, and money needed to run large-scale computations. The project will involve testing on a real-world LLM-based parallelizing compiler, to show that the tool can guarantee the correctness of its translations, as well as produce hints that help the translator produce more correct and efficient code. 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 · 2024-09

The National AI Research Resource (NAIRR) workshop aims to establish an accessible AI software stack that democratizes AI capabilities and empowers diverse users. By bringing together academics, researchers, and industry experts, the workshop will address immediate and long-term objectives for the NAIRR pilot, pinpointing critical components for various scientific research domains. Focus areas will include real-time data analysis, AI-based decision-making, privacy, security, and software portability across emerging AI hardware platforms. This collaborative effort is designed to ensure that the resulting AI software stack meets the needs of a broad spectrum of users, from beginners to experts, fostering an inclusive AI ecosystem. The workshop's outcomes will emphasize the creation of ethical, transparent, and trustworthy AI software tailored for scientific research. The workshop aims to foster innovation, enhance diversity, and ensure equitable access to AI resources by leveraging existing software stacks from academia, national laboratories, and industry. Discussions will address user-support needs, funding requirements, and procedures for incorporating new software developments into the NAIRR stack. The workshop will culminate in the production of a comprehensive report detailing the necessary AI software stack to serve users ranging from beginners to experts, thereby fostering an inclusive AI ecosystem. This effort will lay the foundation for a robust, democratized AI research infrastructure, driving innovation across the U.S. AI landscape. 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 · 2024-09

Project Summary / Abstract: Healthy individuals have a tremendous intrinsic ability to heal after injury. Wound repair involves complex and coordinated actions of various cell types acting across three sequential healing phases: Inflammatory, Proliferative and Resolution. Efficient wound repair requires a timely progression from one phase of healing to the next, with the ultimate goal of returning the injured tissue to homeostasis. Wounds of the oral cavity heal faster than skin wounds, and their phases of healing are optimized to result in a more regenerative outcome. In contrast, the phases of healing become corrupted by chronic diseases, leading to, on one extreme, pathological tissue under-healing (as in diabetic and chronic wounds) and on the other extreme, pathological tissue over-healing (as in carcinogenesis). However, studies that directly compare models of reparative skin healing with optimized oral healing, or with disease models of pathological under- or over-healing, are lacking. The overall goal of this MIRA research proposal is to understand the progression of healing phases across differential healing outcomes at the spatio-temporal single cell level. We aim to discover critical junctions along the healing continuum where healing becomes optimized (as in oral wounds) or pathological (as in chronic wounds and tumors). Our approaches are innovative because we will use state-of-the-art single cell and spatial sequencing technologies combined within a new spatio-temporal analytical framework to systematically compare cell type dynamics, cell-cell interactions and cell-specific gene regulatory networks across mouse models of successful and pathological healing. In the first project, we will generate a new spatial single cell dataset of oral wound healing and use our network-based analytical framework to identify cell-specific spatio-temporal gene signatures that distinguish optimized oral healing from reparative skin healing. In the second project, we will apply this analytical framework to identify healing-associated bottlenecks in datasets of pathological under-healing (diabetic skin injury model) and over-healing (oral and skin carcinogenesis models). We will validate our findings using existing datasets of human pathology, including those from diabetic chronic wounds and skin/oral cancers, and then experimentally using orthogonal methods in cell and animal models of wound healing and carcinogenesis. Overall, this proposal will increase our understanding of the complex cell population dynamics that result in reparative, optimized or pathological healing outcomes. The projects will result in novel phase-resolved and cell-specific gene expression signatures that describe healing-related stages of disease progression in under-healing diabetic wounds and over-healing tumors. These signatures will have diagnostic, prognostic and therapeutic value for targeting of specific cells and pathways, with the ultimate goal of promoting the healing of surgical, traumatic and chronic wounds as well as inhibiting cancer progression.