University Of Chicago

NSF Awards · FY 2025 · 2025-10

Cells sense and respond to their environments. Immune system cells sense and respond to viruses, bacteria, and even cancer cells. Most sense and response circuits involve several intermediate molecules acting as a cascade. This takes time and makes it difficult to engineer these circuits to respond to new inputs or to generate new responses. Existing circuits often overlap and interact. This makes efforts to modify them subject to possible negative side effects. To avoid these problems, it is proposed to develop a class of molecules that sense and respond directly to environmental cues that can be engineered and can infiltrate existing cells to change their responses. For example, this might be a way that cells in an existing tumor could be directed to break apart and die. This effort will focus on a class of proteins referred to as intrinsically disordered proteins (IDPs). Unlike most other proteins, they do not have a fixed conformation and can rapidly and dramatically change shape in response to stimuli. Because they can be designed to interact with signal molecules and cellular proteins, they could act as a rapid switch for cell metabolism in response to a specific signal. Outreach at the local Southside Chicago Science Festival will make science relatable and help attract students to STEM careers. Supporting undergraduate researchers will grow the synthetic biology workforce. Molecules that drive cell-specific responses based on defined inputs can increase the safety and efficacy of bioengineering and biomedical technologies. This synthetic biology project will establish a new class of dynamic molecules that drive defined, gated output signals based on endogenous, cell-specific input triggers, where the sensing and output functions are entirely contained within a single molecule. Binary interactions between these “smart molecules” and either one of two targets – an effector and sensing target - are weak, but cooperative interactions in the ternary complex are strong; thus, if a function is linked to any of the binary interactions, dependence on cooperative ternary complex formation creates an AND gate for that function. This project will establish this new mechanism by developing dynamic cooperative molecules that elicit a controlled response (i.e., apoptosis) in mammalian cells based on the coincidence of two binding targets – either an exogenously expressed model protein or endogenous proteins specific to a target cell type, such as HIF1a. The novel AND gate-induced molecular technology will define a new mechanism for cell engineering and molecular design and pave the way for a new class of therapeutics with broad potential to impact human health. 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 2025 · 2025-10

The human brain consists of a massive network of interconnected brain cells, and an important unanswered question is to explain how these cells interact to flexibly support different types of behaviors. In this project the principal investigators (PIs) hypothesize that rhythmic waves of neuronal activity—traveling waves—play an important role in allowing the brain to flexibly reorganize and cause task-related activity to move to its proper destination during behavior. This project will measure traveling waves from the human brain directly, using electrodes surgically placed inside the brain in collaboration with neurosurgeons performing clinical procedures. Further, using these recordings, the PIs will create computational models of these waves to test theories for how traveling waves move across the brain and how they change direction in relation to different task behaviors. In addition to explaining the fundamental mechanisms of traveling wave propagation, this work also has practical implications for creating brain-computer interfaces and treating diseases related to disrupted neuronal interactions. This research thus has implications for improving human health by showing how traveling waves should be structured in healthy individuals and demonstrating how they may not propagate properly in people with brain disorders. The project is a collaboration between Columbia University and the University of Pittsburgh and offers valuable educational and outreach opportunities. Specifically, it offers training opportunities in neuroscience methods for undergraduates and other trainees from the New York City and Pittsburgh areas as well as an online monthly meeting group for the discussion of scientific issues related to traveling waves, which is fully open to all. The goal of this project is to perform novel experiments and build computational models to explain the functional properties and mechanisms of traveling waves in the human cortex. Traveling patterns of neuronal oscillations are a widespread but mysterious phenomenon in which neuronal oscillations propagate spatially across the human cortex. The PIs hypothesize that traveling waves coordinate information transmission across the brain such that their direction and timing reveal where and when specific task-related information is processed along large-scale brain regions. This project will create biologically plausible computational models of how neural traveling waves are generated in the human brain and iteratively refine these models by conducting parallel experiments in human neurosurgical patients with implanted electrodes. These subjects will perform realistic spatial memory and navigation paradigms and measure how traveling waves propagate in different directions to support separate behaviors. It will also create computational models to explain these task-related direction shifts. The PIs will analyze how the timing of traveling waves relates to the speed of memory retrieval in the experiments. Specifically, the PIs will create ​​computational models that simulate how the timing of traveling wave propagation relates to the fidelity and speed of neural signal propagation across the cortex. In this work, through close interaction between experiments and theoretical modeling, the PIs will obtain a rigorous explanation of the neural basis of traveling waves for high-level cognition and detailed types of neural computation. This award is being co-funded by the Division of Mathematical Sciences (DMS) within the Mathematical and Physical Sciences Directorate (MPS) and Division of Information and Intelligent Systems (IIS) in the Directorate of Computer and Information Science and Engineering (CISE). 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 2025 · 2025-10

In recent years, preference feedback—comparative inputs such as “A is better than B”—has emerged as a vital resource for guiding decision-making systems. Unlike explicit labels, preference feedback is often easier to collect and can be particularly valuable in subjective tasks where defining ideal outcomes is difficult. However, real-world preference data are often noisy, sparse, and heterogeneous, posing significant challenges to existing statistical methods. For example, recommendation systems may encounter incomplete feedback from users who abandon tasks due to fatigue or provide inconsistent inputs due to individual biases. This project aims to address the challenges of learning from preference feedback by developing robust statistical methods and advancing the theoretical foundations of preference-based learning. Additionally, it seeks to prepare students to tackle these challenges by integrating the research findings into innovative teaching platforms and educational curricula. The project will focus on three key areas of learning from preference feedback: ranking from pairwise comparisons, user-item rating systems, and reinforcement learning from human feedback. To advance the field, the project will (1) develop robust algorithms for ranking that account for ill-conditioned sampling mechanisms and relax parametric modeling assumptions; (2) propose new estimation and uncertainty quantification methods for user-item ratings that work effectively in sparse and heterogeneous settings; and (3) introduce novel frameworks for reinforcement learning that incorporate “out-of-list” preference feedback while addressing the issue of distribution shifts. Through these contributions, the project will bridge the gap between statistical theory and practical applications, creating tools to enhance decision-making systems across diverse domains. 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 2025 · 2025-10

Data science is a transformative field that has impacted virtually every aspect of society. Providing widespread data science education is essential for cultivating a skilled and engaged workforce while ensuring national competitiveness in this rapidly growing domain. This project is a collaboration between the University of Chicago, Olive-Harvey Community College and Middle College High School, Gary Comer Educational Campus, Chicago State University, and Xchange Chicago to establish pathways to data science learning and careers for youth on Chicago's South Side. The work will focus on engaging youth in the community with the goal of increasing their understanding of data science and to increase the number of individuals prepared to work in data science related fields. Over the duration of the project, the partners will build a South Side ecosystem, deepen partnerships, and implement improvements informed by ongoing evaluation. Four pathway entry points will be created: a) high school after-school programming; b) high school introductory data science courses; c) community college data science certificate; and d) university-level data science minor and major. This project includes assessments of the student learning and evaluations of program activities. Each partner will leverage the others' assets to co-create programs with four common elements: a) aligned data science content; b) experiential projects; c) explicit attention to ethics; and d) guidance on pathway progression. Assessed learning objectives represent content areas including data literacy and the data science lifecycle, coding, and foundational mathematics and statistics. Data will be collected through rubrics, questionnaires and interviews. Through these efforts, the project will address critical gaps in data science education and provide real-world learning opportunities while contributing to the development of a competitive and skilled national workforce. This award is jointly sponsored by the Division of Research on Learning in Formal and Informal Settings and the Division of Undergraduate Education within the Directorate for STEM Education. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NSF Awards · FY 2025 · 2025-10

This research aims to develop statistical tools to improve the reliability of artificial intelligence (AI) that is widely used in real-world systems such as automated decision-making, financial forecasting, and neuroscience research. Modern AI often relies on efficient machine learning algorithms to process large-scale, sequentially arriving datasets. While these algorithms are powerful, understanding their behavior and measuring their uncertainty remains a major scientific challenge. To bridge this gap, the investigators will focus on establishing mathematically rigorous methods for uncertainty quantification to build trustworthy AI. Applications will include enhancing theoretical guarantees and interpretability of neural networks, providing robust estimation and inference for econometric and biomedical studies, and detecting real-time change-points in high-dimensional time series data. The projects will promote the progress of science through open-source software and graduate education, and will support the national interest by contributing to reliable, data-driven decision-making in fields important to economic resilience, public health and national security. This research will provide a comprehensive theoretical framework for online statistical inference in machine learning, focusing on constant learning-rate stochastic gradient descent (SGD) algorithms. It addresses fundamental challenges such as non-stationarity caused by arbitrarily fixed initialization and complex dependency structures arising in recursive estimation. The investigators will derive the limiting distributions of SGD-type estimators and construct confidence regions with guaranteed asymptotic coverage. Specific efforts will include (1) establishing Gaussian approximations for high-dimensional dropout regularization, (2) deriving limiting distributions for SGD under non-smooth quantile loss functions using characteristic function techniques, and (3) developing online inference procedures for quantile change-point detection in high-dimensional time series using a novel Bahadur representation. These methods will be supported by numerical experiments and implemented in publicly available software. The results shall provide foundational advances for statistical inference in modern machine learning, bridging theoretical developments with practical applications in dynamic, high-dimensional environments. 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 2025 · 2025-10

Many critical scientific challenges, from understanding complex diseases to designing innovative materials, rely on sophisticated computer simulations. However, scientists often encounter a "silicon ceiling," where current computational power restricts their ability to model these intricate real-world phenomena accurately enough to achieve major breakthroughs. The SINAPSE project directly addresses this issue by developing a powerful, open-source software toolkit that combines Artificial Intelligence (AI) with High-Performance Computing (HPC). This integration promises to enhance simulation capabilities, effectively offering significant orders-of-magnitude performance gains. SINAPSE will provide foundational software that benefits the broader AI-HPC research community, advancing the field itself. The project is also dedicated to supporting education and training for students in these cutting-edge computational methods, fostering the next generation of STEM professionals. By making advanced simulations more powerful and accessible, SINAPSE serves the national interest by driving innovation and enabling solutions to pressing scientific challenges. The project aims to overcome the "silicon ceiling" limiting complex simulations by developing a Scalable Infrastructure for AI-driven Predictive Simulation Enhancements (SINAPSE), delivering an open, sustainable Software Development Kit (SDK) that seamlessly couples Artificial Intelligence (AI) with High-Performance Computing (HPC) workflows. The project will provide functional capabilities through new and enhanced core software elements for AI-coupled HPC and integrated problem-solving frameworks for common scientific discovery patterns. The methodology begins by convening the SDK with a community focus. The SDK will then be populated by creating several novel core software elements and significantly enhancing existing tools like Colmena and RHAPSODY to support diverse AI-HPC coupling needs, including dynamic and asynchronous execution. These components will be assembled into problem-solving frameworks such as "Muse" for online surrogate model training, "Music" for model-directed sampling, and "Melody" for multi-scale campaigns. Finally, the entire SINAPSE SDK and its frameworks will be validated and strengthened through applications in biophysics, focusing on viral glycoprotein dynamics, and materials engineering, specifically for catalyst design. 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 · 2025-09

PROJECT SUMMARY Interleukin 22 (IL-22) is a microbe-induced cytokine that plays a crucial role in tissue homeostasis. The best- known pathway of IL-22 production requires the microbial stimulation of innate immune cells to release IL-23; IL- 23 then activates innate lymphoid cell type 3 (ILC3) and T helper 17 (Th17) cells to produce IL-22. IL-22 acts primarily on non-hematopoietic cells. It is crucial for regulating the production of anti-microbial proteins (AMPs), particularly the Reg gene family, in the intestine to control the microbiota or infections. Conversely, dysregulation of IL-22 is associated with intestinal pathologies. Interestingly, the pancreas is highly responsive to IL-22 and produces REG proteins, but it is not known whether pancreatic IL-22 levels or Reg gene transcription are regulated by the microbiota as is the case in the gut; this would be intriguing as the pancreas itself is a relatively sterile organ. Both elevated IL-22 and Reg levels are associated with poor prognosis in pancreatic diseases including pancreatitis and pancreatic ductal adenocarcinoma (PDAC), suggesting a pathogenic role for IL-22 in these disease contexts. However, the initial triggers of elevated pancreatic IL-22 have not been investigated, nor has a beneficial role for the high sensitivity of the pancreas to IL-22. Thus, this proposal will comprehensively establish the role of gut microbes in modulating pancreatic IL-22 and the consequences of this gut-to-pancreas axis on pancreatic health and disease. I hypothesize that gut microbes are crucial regulators of IL-22 in the pancreas, and while this is beneficial in promoting innate immune defenses to maintain pancreatic sterility, it becomes detrimental in the context of PDAC. Aim 1 will determine the impact of gut microbe induced IL-22 on pancreatic gene expression and the cellular mechanism underlying this phenomenon. In Aim 2, both the beneficial and detrimental roles of microbially induced IL-22 in the pancreas will be determined by modulating pancreatic IL-22 levels in mice challenged with intestinal infections in the context of IL-22 receptor deficiency or pancreatic cancer. This work will provide key insight into a previously undescribed mechanism of communication between the gut and pancreas via IL-22 with the goal of developing more targeted therapeutic interventions for pancreatic diseases. In addition to research, this fellowship will prioritize training and career development activities that will exceptionally prepare me to achieve my career goals of being a principal investigator at an academic institution. My training plan includes presenting my work both internally at the University of Chicago and at conferences, career development seminars, and teaching workshops. My research mentor, Dr. Daria Esterházy, along with the resources provided by the University of Chicago and the Committee on Immunology, will support and enrich my research training. This fellowship is an essential first step towards becoming a successful independent scientist and achieving my long-term career goals.

NIH Research Projects · FY 2025 · 2025-09

PROJECT SUMMARY Thymic selection is crucial for generating functional and self-tolerant T cells, yet the mechanisms underlying the development of unconventional T cell lineages, such as CD8αα intraepithelial lymphocytes (IELs), remain poorly understood. CD8αα IELs possess innate-like features and play essential roles in maintaining intestinal integrity. Dysregulation of CD8αα IELs can contribute to intestinal pathologies like celiac disease. This study focuses on investigating the role of the transcription factor Ets1 in thymic selection and its impact on IEL development and function. Ets1 is a signal-regulated transcription factor that is implicated in the pathogenesis of multiple autoimmune disorders. Despite its known roles in early T cell development and peripheral T cell function, Ets1’s specific role in thymic selection remains poorly understood. Furthermore, Ets1 is implicated in regulating responses to IL-15 and TGF-β, crucial for CD8αα IEL maturation and function, highlighting its significance in intestinal homeostasis. Preliminary data using Ets1-deficient mice indicate that Ets1 restricts the development of IEL precursors (IELps) in the thymus and prevents premature egress of immature thymocytes. Moreover, Ets1 may promote clonal deletion of autoreactive T cells. This study aims to elucidate the molecular mechanisms underlying these observations. Aim 1 aims to determine how Ets1 regulates thymic selection by investigating its impact on positive selection and clonal deletion. TCR-transgenic models, flow cytometry, and CUT&RUN will be used to determine how Ets1 regulates thymic selection. Aim 2 focuses on assessing the functional consequences of Ets1 deficiency in CD8αα IELs. By examining IELp maturation and peripheral function, this aim aims to elucidate how Ets1 influences the development and function of these cells. Overall, this study aims to provide novel insights into the regulatory mechanisms governing thymic selection and the role of Ets1 in shaping T cell development and peripheral immune homeostasis, with potential implications for understanding autoimmune diseases.

NIH Research Projects · FY 2025 · 2025-09

Project Summary NK cells are fast-acting, cytotoxic immune cells vital for protecting against herpesviruses and cancer. Given their ability to identify infected and transformed cells in an MHC class I-independent manner, NK cells have become increasingly studied for their potential as off-the-shelf immunotherapies. While NK cells exhibit tremendous potential for future technologies, many strategies have been hindered by our limited knowledge of the factors that guide expansion, terminal maturation, and cytotoxicity. Here, we propose to study how Ets1, a highly conserved and tightly regulated transcription factor in lymphocytes, contributes to mature NK (mNK) cell terminal maturation and function. To address the role of Ets1 in mNK cells, I generated an NK cell-driven Ets1 conditional knockout mouse line (Ets1 cKO, Ncr1Cre Ets1F/F). These mice generate biallelic deletions of Ets1 in mNK cells without affecting other lymphocyte lineages. Preliminary data presented here demonstrate that the loss of Ets1 in undifferentiated mNK cells results in a severe population defect in the bone marrow and spleen with a specific loss of the differentiated, cytotoxic effector subset. To address the role of Ets1 in cytotoxic effector competent mNK cells, I generated a tamoxifen-inducible NK-cell driven knockout mouse line (Ets1 TAM-KO, Ncr1ERT2 Ets1F/F) that efficiently deletes Ets1 in differentiated mNK cells without inducing a maturation block. Preliminary data from these mice suggests that Ets1 is not required for differentiated mNK cell survival, but may limit terminal maturation and cell activation. The goal of this project is to establish the mechanistic role of Ets1 in mNK cells. We propose two aims that will (i) establish how Ets1 promotes the development of undifferentiated mNK cells into the cytotoxic effector subset and (ii) determine how Ets1 expression in differentiated, cytotoxic effector NK cells regulates terminal maturation and function. Accomplishing the proposed studies will illuminate outstanding developmental and functional questions and contribute to the exciting and growing field of NK cell biology. These studies will help detail molecular mechanisms of Ets1 in mNK cells and may inform the design of improved NK cell-based immunotherapies. This project is accompanied by a training plan developed by my mentors and me that delineates several goals needed to propel me toward becoming a successful independent physician-scientist. These goals include gaining expertise in interrogating transcription factor functions in immune cells, refining my skills in bioinformatics, developing proficiency in scientific communication, and integrating my scientific and clinical training. Realizing these goals will equip me with fundamental skills that will support my aspirations to become a physician-scientist oncologist capable of spearheading novel therapeutic avenues.

NIH Research Projects · FY 2025 · 2025-09

PROJECT SUMMARY Throughout childhood, individual neurons that make up our brain form connections, or circuits, between each other. These circuits guide the flow of activity across our brain for proper functioning. A fascinating feature of the brain is that it’s believed that both our genetics and our experiences as children can influence how neurons connect to each other. Understanding this process is critical to knowing how our childhood experiences influence brain development, and how disruptions in this process result in neurodevelopmental disabilities like Autism. Surprisingly, despite its importance, we have very little direct data on how these physical connections form during childhood development. Rather, our understanding of this process is largely based on interpretations of data that do not directly follow how neurons connect with each other. This is because until recently, these kinds of experiments were difficult if not impossible to do. However, our lab has developed technology that now allows us to investigate how circuits form in a clear and unambiguous way. With these new tools we will first ask how neurons make the correct connections during development by focusing on a well-studied circuit between the eyes and the brain. This circuit will allow us to ask how connections between the left and right eye properly form in concert together to ensure that what our eyes see gets correctly processed in the brain. In the second aim, we will ask how closing one eye, which will block activity, or visual “experiences” from that eye, disrupts this process. We believe that what we learn from studying this visual circuitry will provide clues to how neurons form circuits throughout the brain. We will conduct these experiments in the ferret because there is a lot of existing data on how this visual circuit develops in this animal that we can use to better interpret our results. Additionally, the ferret visual circuit and its brain more closely resembles the human brain relative to mice, another popular model organism in neuroscience. This will make it more likely that the lessons we learn in the ferret will also be true in humans. Overall, we believe results from our proposal will help better understand how brain connections form during childhood which may inform how much we need to worry about the environment our children grow up in. Our proposal might also help with treating neurodevelopmental disabilities by providing additional evidence for treating conditions early in life while the brain is forming new connections and is still amenable to therapies.

NIH Research Projects · FY 2025 · 2025-09

Project Summary Sex differences in cardiometabolic health are driving the call for research focusing on women. Compared with men, women are more vulnerable to cardiometabolic disease, including hypertensive disorders, heart disease, cerebrovascular incidents, and diabetes. Reproductive health factors appear to partially explain the observed sex differences in cardiometabolic health. Although most research to date has been conducted in adult women and has tested associations between reproductive health and overt disease, this research framework can be leveraged for testing hypotheses relevant for preventive interventions. The aim of the present application is to test the relative utility of multiple measures of adolescent reproductive health for predicting risk of cardiometabolic disease in early adulthood. We will use data from The Pittsburgh Girls Study, a longitudinal community-based study that included annual interviews of girls and their caregivers beginning in childhood. We focus on three domains of reproductive health: pubertal (timing and tempo, age at menarche, menstrual cycle regularity), sexual (use of hormonal contraception, HPV vaccination, sexually transmitted infection), and pregnancy health (age at first pregnancy, parity, experiences of miscarriage and preterm birth). These data will be linked to biomarkers of cardiometabolic health in early adulthood (ages 21-24) including waist circumference, fasting serum blood sugars and lipids, and markers of systemic inflammation including TNF-alpha, IL-6, and CRP. Further, we propose to test how patterns in severity, timing, and chronicity of stress exposure, which we have derived from PGS data, impact the association between adolescent reproductive health and risk for cardiometabolic disease. We focus on specific domains of stress exposure: subsistence (e.g., resource strain, overcrowding), safety (e.g., community violence, inter-adult aggression), and caregiving (e.g., separation, maternal depression). We will specify the role of stress exposure on the association between adolescent reproductive health and risk of cardiometabolic disease for different subgroups of women. Our specific aims are to 1: Test the relative utility of multiple indicators of reproductive health for predicting risk of cardiometabolic disease in early adulthood, and 2: Test the impact of stress exposure in childhood and adolescence on the association between reproductive health and risk for cardiometabolic disease. We hypothesize that domains of reproductive health will impact cardiometabolic risk differentially for different subgroups of women, and that moderated models for the associations among stress exposure, reproductive health, and risk for cardiometabolic disease will be differentially specified for different subgroups of women.

NIH Research Projects · FY 2025 · 2025-09

PROJECT SUMMARY Inflammation is at the center of many obesity complications, such as diabetes and heart disease. The most recommended treatment for obesity is weight loss, which results in decrease of the related inflammation and complications, making weight loss a very attractive therapeutic strategy. However, the mechanisms by which weight loss benefits obesity-related inflammation is unknown, representing a major knowledge gap. We recently revealed that in mice, weight loss induced by caloric restriction (CR) promotes resolution of inflammation in atherosclerotic cardiovascular disease. Mechanistically, this is attributed to a new macrophage subtype (termed CR-macrophages) that have increased capability to efferocytose (the phagocytic process by which macrophages clear apoptotic cells) and accumulate mostly in visceral adipose tissue, but also in atherosclerotic plaques. CR-macrophages are distinguishable by their high expression of CD16a, which our data demonstrate is required for their higher efferocytic activity. Therefore, our central hypothesis is that weight loss induces a pro-resolving phenotype in macrophages that subsequently resolves inflammation and improves metabolic health. In the first aim we will determine visceral and subcutaneous adipose tissue macrophage phenotype, function and transcriptome across species (mouse and human) and time of weight loss. Aim 2 will use several strategies, including cell therapy and nanomedicine, to test whether CR-macrophages can be used to treat metabolic dysfunction in obese mice. Our results will unearth novel immunological pathways underlying weight loss-induced inflammation resolution that will suggest new strategies for the treatment of obesity complications, establishing a new paradigm in obesity management.

NIH Research Projects · FY 2025 · 2025-09

PROJECT SUMMARY My NIH-funded patient-oriented research program focuses on improving patient outcomes across the HIV prevention and care continua through implementation of clinical informatics interventions. For HIV prevention, I have developed and implemented electronic medical record (EMR)-based algorithms to identify patients eligible for pre-exposure prophylaxis (PrEP). I am currently PI for POWER Up, an R01 that utilizes clinical informatics as part of an overarching implementation science strategy to improve PrEP uptake in community health clinic settings. I have developed clinical informatics tools to identify people with HIV (PWH) in need of resources to prevent them from falling out of care. I am currently PI of the ePORTAL HIV-S study, an R01 utilizing electronic patient portals as part of a population health approach to screening for substance use disorder (SUD) among PWH. My preliminary research has shown that relying on EMR data alone is often imperfect for predicting PrEP and HIV care continuum outcomes, and that incorporation of social drivers of health and patient-reported data is crucial. However, additional research is needed to understand how to best incorporate patient reported data from individuals vulnerable to HIV and PWH into clinical informatics tools to improve PrEP and HIV care outcomes. I have a strong track record of mentoring junior faculty and trainees, and I am committed to expanding my mentorship program in patient-oriented HIV informatics. I will work with my mentees to carry out two specific aims. Aim 1: Pilot the implementation of electronic patient-reported sexual health data into the EMR to identify individuals who would benefit from PrEP. Guided by the Consolidated Framework for Implementation Research (CFIR) 2.0, we will interview key stakeholders, including both patients and providers/staff, regarding barriers and facilitators. We will then pilot the implementation of an electronic sexual health questionnaire, incorporating questionnaire results into an EMR-based algorithm to identify PrEP candidates. We will refine Clinical Decision Support tools to guide providers to discuss and prescribe PrEP for patients identified by the algorithm. Aim 2: Implement electronic patient portal-based screening for social needs among people with HIV. We will use CFIR 2.0 as a framework as we interview key stakeholders about barriers and facilitators to population health portal-based social needs screening among PWH. Based on these results, we will then incorporate social needs screening into the population health portal-based SUD screening program among PWH. Evaluation will be performed using the Reach, Effectiveness, Adoption, Implementation, and Maintenance (RE-AIM) framework. These aims will be integrated into my existing research program, including my two current R01s. This K24 award will provide the opportunity and infrastructure to build and expand my mentorship program in patient-oriented HIV-related clinical informatics research and address current gaps in clinical informatics interventions for HIV prevention and care.

NSF Awards · FY 2025 · 2025-09

The goal of this conference is to advance the security, sustainability, and inclusivity of open-source (OS) ecosystems by facilitating interdisciplinary collaboration and dialogue. Through participation from academic researchers, industry experts, and community contributors, the conference aims to foster convergence across technical, social, and policy domains to address key challenges in OS development. Key outcomes will include a comprehensive post-conference report that is submitted for publication. This report will distill findings from the event into actionable tools, performance metrics, and design strategies for OS software security, borrowing from successful approaches in adjacent fields. To support practical implementation, the conference will also generate an openly available tutorial or checklist that guides OS developers through secure design practices. The video-recorded keynote sessions, annotated bibliographies, and edited transcripts will be made accessible to increase engagement, especially among students and early-career professionals. Together, these efforts are intended to strengthen the OS developer pipeline, inform future research, and support a more secure and collaborative open-source ecosystem. The Cyber Policy Initiative (CPI), in collaboration with the Harris School of Public Policy, will lead the planning and execution of a dynamic, two-day conference focused on open-source software and cybersecurity. Although much attention has been paid recently to the security of Open-Source Software (OSS) supply chains, questions remain concerning the behavioral and financial incentives for those people (typically volunteers) that work tirelessly to secure OS ecosystems. As such, the conference will conduct a targeted investigation into the conditions for successfully incentivizing a secure OS environment. Topics to be addressed include how artificial intelligence influences how we think about incentivizing the secure development of AI OS, and what parallels exist between security for critical notes in a traditional supply chain and critical notes in the OSE supply chain. The discussion of these questions identifies open-source challenges and bolsters cyber-resiliency by providing adequate behavioral and economic incentives. Research focused on developer incentives for securing OSS and OS ecosystems can intersect directly with expertise from several fields, such as psychology, behavioral economics, cybersecurity, cryptography, and so forth. By examining the interplay between behavioral, economic, and technological considerations, this conference can uncover important lessons that can improve the approach to incentivizing secure OSE for both producers and consumers. The conference can also help replicate appropriate metrics or evaluation methods, as well as critical tools to support dependency transparency and accountability. Ultimately, the OS ecosystem writ large will benefit from a multidisciplinary approach and from engagement across typically segmented communities. 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 · 2025-09

Project Summary. Research. Obesity contributes to increased cancer incidence and mortality, yet the mechanisms involved and impact on therapy remain unclear. Since greater than 50% of adults in the United States are obese, elucidating the mechanistic consequences of high-fat state on cancer is critical to prevent an emerging health epidemic. One molecule of fat, or triglyceride, consists of three molecules of fatty acids and one molecule of glycerol. However, the majority of cancer research focuses on fatty acid metabolism of fats whereas the contribution of glycerol backbone to tumorigenesis and anti-tumor immunity remains largely unexplored. CD8+ T cells are key anti-tumor effector cells as they acquire cytotoxic activity and can directly kill tumor cells. Metabolic pathways are crucial for T cell activation and differentiation, but the mechanisms by which cancer cells compromise the metabolic fitness of CD8+ T cells in the tumor microenvironment, especially in the context of high-fat state, remain largely unknown. Based on my postdoctoral work, I discovered a novel paradigm of tumor-immune interaction mediated by glycerol. I found that glycerol supplementation alone was sufficient to accelerate tumor growth in a CD8+ T cell dependent manner. Thus, I hypothesize that glycerol, as a potential immunosuppressive metabolite, is secreted by cancer cells and catabolized by T cells to impair their anti-tumor functions. To test this hypothesis, Aim 1 will determine the immunomodulatory roles of glycerol on CD8+ T cells and then mechanistically study the metabolic interactions between cancer cells and T cells by using innovative coculture system and spatial mass spectrometry. Lastly, I will improve anti-tumor immunity by manipulating glycerol crosstalk. Aim 2 will define how dietary glycerol remodels the tumor microenvironment and determine cellular and molecular mechanisms by which excessive glycerol reshapes immune landscape and impairs anti-tumor immunity. Candidate. Dr. Conghui Yao, is the PI for this research proposal. She has worked as a postdoctoral fellow for the past four years at Harvard Medical School studying the metabolic regulations for CD8+ T cell activation and anti-tumor functions. She has accepted the tenure-track faculty offer from University of Chicago and will start her own lab this fall. Conghui has mapped out a detailed professional development plan enabling her to transition to an independent research career where she will develop her research program on tumorigenesis and anti-tumor immunity. She aims to become a leader in cancer immunology by applying an innovative systems biology approach and in vivo spatial metabolomics to dissect the tumor-immune crosstalk, which will distinguish her independent work from that of her postdoctoral mentors. Her long-term goal is to lead an independent cancer research program dedicated to the discovery of molecular mechanisms within tumors that regulate local immune responses and tumor progression. Conghui’s work will inform strategies and identify novel therapeutic targets for improving cancer immunotherapy outcomes especially relevant to overweight and obese patients.

NIH Research Projects · FY 2025 · 2025-09

Project Summary Sepsis is a life-threatening multiorgan dysfunction syndrome caused by a dysregulated response to infection, responsible for over half of hospital deaths and the leading cause of readmissions and hospitalization costs in the US. Heart failure in critically ill sepsis patients has a mortality rate of up to 70%. Despite 40 years of research, there is no effective clinical treatment for sepsis-induced cardiac dysfunction (SICD). Vascular hyperpermeability, a hallmark of sepsis, leads to lung edema and breathing problems, but its role in SICD remains underexplored. Our recent study suggests that protecting microvascular integrity and reducing cardiac edema (fluid accumulation in the myocardium) may improve survival in sepsis. Using genetic analysis (gene sequencing), we found that MMP3 is one of the top regulated genes in septic mouse hearts, with its serum levels significantly increased in septic animal models, consistent with clinical reports. Our data also indicate that serum MMP3 has strong diagnostic value for sepsis, surpassing other common biomarkers tested. However, MMP3’s role in sepsis is not yet fully understood. In our pilot studies, MMP3 knockout (KO) mice showed 1) reduced microvascular leakage, improved cardiac function, and maintained normal blood pressure, 2) increased survival rates above 90%, and 3) reduced levels of pro-inflammatory cytokines (i.e. iNOS, IL-6)). Moreover, MMP3 is predominantly expressed in cardiac endothelial cells, and CRISPR/Cas9-mediated MMP3 deletion in endothelial cells further increased survival following sepsis challenge. Additionally, B1R inhibitor treatment in WT mice reduced MMP3 levels and cardiac microvascular leakage during sepsis. We hypothesize that the endothelial B1R/MMP3 pathway, following sepsis challenge, plays a critical role in inducing cardiac microvascular barrier dysfunction, leading to the development of sepsis-induced heart failure. Overall, our proposed studies aim to identify the critical mechanisms behind sepsis-induced microvascular leakage and demonstrate that MMP3 is a novel therapeutic target for sepsis-induced heart failure. Aim 1 will investigate the role of endothelial MMP3 in regulating cardiac microvascular permeability and function in sepsis, contributing to the development of SICD, using an inducible adult EC-specific MMP3 knockout mouse model and EC-MMP3 overexpression via a novel nanoparticle delivery system developed by Dr. YouYang (Co-I). Aim 2 will define the molecular mechanism by which B1R regulates MMP3, focusing on several pathways, using advanced molecular techniques to establish a direct link between B1R and MMP3. Aim 3 will explore the therapeutic effects of MMP3 inhibition through pharmacological intervention using an MMP3 inhibitor and CRISPR/Cas9-mediated endothelial-specific gene editing. Together, these studies aim to provide a comprehensive understanding of the mechanisms underlying septic heart failure and develop novel therapeutic strategies to reduce cardiac edema, prevent heart failure progression, with the hope of improving the survival of patients with sepsis.

NSF Awards · FY 2025 · 2025-09

The goal of this project is to understand fundamental relationships between symmetries arising in different parts of mathematics. An example of such a (still mysterious) connection is between certain 4-dimensional spaces central in physics and collections of reflective symmetries of negatively curved spaces. This project will also have the broader impact of training many PhD students and postdocs. The project is meant to develop a theory of mapping class groups of closed 4-dimensional manifolds by bringing in viewpoints, methods and ideas from the 2-dimensional case. This goal is only one piece of a broader research program of the principal investigator relating the topology of moduli spaces, the monodromy of fiber bundles, the theory of arithmetic/reflection groups and 4-manifold topology. 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 2025 · 2025-09

With support from the Division of Chemistry, Professors David Awschalom and Giulia Galli of the University of Chicago, and Professor Danna Freedman of the Massachusetts Institute of Technology, along with their collaborators at the University of Glasgow in the United Kingdom, are investigating how magnetic quantum-mechanical spin states in molecules can be efficiently measured using light. Molecular magnetic spin states could play an important role in quantum information science. Their long lifetimes, along with the versatility that chemistry offers to manipulate their structure and function, could enable the control of quantum mechanical properties such as entanglement, where the behavior of two or more particles is correlated even when they are separated by large distances. However, a key challenge has been measuring single spins in molecules, where quantum features are most apparent. The research team seeks to address this challenge by creating molecules whose spins can be efficiently interfaced with light. Their discoveries could enable the creation of entangled states that are currently out of reach and contribute to the advancement of quantum-enhanced sensors for understanding chemical and biological systems. This award is made under the NSF-UKRI lead agency opportunity. The project will combine synthetic chemistry, theory, and spin-optical spectroscopies, to develop the systems and techniques that enable entanglement to be created, sustained, and detected in complex molecular systems. Metal coordination complexes will be synthesized that could serve as chemically tunable platforms, in which spatial spin placement is atomistically controlled, and where coherent spin states can be initialized and read out with light, at the single-spin level. The synthesis of new metal complexes containing Cerium and Vanadium will be guided by theoretical prediction of electronic and optical-structure using ab initio methods based on generalized cluster-correlation expansion techniques. Entangled states will be created with microwave-based coherent spin manipulation, and single qubit readout will be accomplished by photoluminescence detection. The ability to generate entangled states and detect them at the single spin level could advance multiple quantum-based applications based on chemical systems, including the development of spin-based quantum sensors. The project will provide research opportunities for students in advanced quantum information science and thus contribute to the development of a quantum-enabled STEM workforce, while the wider public will benefit from the team’s outreach activities. 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 · 2025-09

PROJECT SUMMARY Biological membranes, protein-protein interactions, and membrane targeting and remodeling by proteins are intimately associated with many critical cellular phenomena, including endocytosis, immune response, organelle formation, cell division, signaling, and movement. These processes are inherently multiscale, as they span from the molecular to nanoscopic to mesoscopic time and length scales. For instance, the molecular-level interactions between collections of proteins and the lipid membrane can have a profound effect on the large scale membrane morphology. Likewise, the atomistic details of actin and actin-binding protein interactions propagate to much longer length and time scales involving protein assembly processes in the cellular cytoskeleton. The interactions of cytoskeleton proteins with membranes are key to many phenomena, including cellular adhesions and motility. Therefore, the main scientific premise of this project is that it is critical to study, in an integrated and coupled fashion, the propagation of local molecular interactions upward in scale to the collective behavior at the cellular level. This research also involves the ongoing development and application of novel multiscale, coarse-grained (CG) computational methods that are ideally suited to investigate the collective interactions of proteins with other proteins and with membranes, including details about conformational states and reactive systems, within the context of key cellular phenomena. There are three main overarching themes of this research that involve the study of increasingly complex aspects of large scale protein-protein complex formations and protein-mediated membrane remodeling processes. These are: (1) employ bottom-up CG models to study realistic membrane systems including peripheral membrane proteins, (2) study the mechanism of large-scale formation and remodeling of actin-based networks as mediated by interactions with actin-binding proteins, and (3) elucidating the mechanisms of protein- mediated remodeling of membranes involved in cellular processes such as the formation of micron-size structures like filopodia and lamellipodia, topological changes such as endocytosis, and dynamic processes such as cell migration with continuous actin turnover. In collaboration with leading experimental researchers to both confirm simulation predictions and to validate the simulation-generated hypotheses, the overarching long- term goal of this research is to continue to apply powerful and systematic multiscale computational approaches to the study of realistic biomolecular processes underlying various important cellular phenomena. These phenomena range from specific interactions at the molecular scale to the concerted action of thousands of proteins.

NIH Research Projects · FY 2025 · 2025-09

Abstract: Spatiomolecular Profiling of Human Cancer at Scale The molecular and cellular architecture of a tumor within its tissue environment dictates disease progression and sensitivity to therapy. Therefore, technologies to image and measure the spatial organization of the molecules and cells that form tumors are critical to basic and clinical cancer research. While tumors are routinely evaluated in the clinic using histopathology techniques such as hematoxylin and eosin (H&E) staining, recent technological advances have heralded a revolution in the spatiomolecular analysis of cancer. For example, the development of methods for spatially resolved transcriptomics (ST) have enabled the sequencing of the transcriptome associated with specific areas of tissue sections. The application of ST to cancer research holds the promise to crack the rules governing the structure-function relationships in tumors, but several key challenges in technology must first be overcome. Several ST technologies have emerged from academic labs over the past half a decade, but they remain limited by their low throughput, small surface area, lack of compatibility with H&E staining, and high costs and barriers to adoption. As a result, there is only one ST technology that has spread beyond its institution of origin thanks to commercialization and ease of adoption. Furthermore, the limitations of existing ST methods compound with the issues of standard freeze-sectioning techniques that are prone to section loss and damage and are not compatible with the analysis of large samples, such as surgical resections or whole organs from cancer patients. Therefore, these gaps in ST and histology technologies preclude detailed spatiomolecular analyses for cancer research across many samples, small or large, from cohorts of cancer patients. To address these challenges, we first built a large-format ST profiling platform, Array-seq, by repurposing off-the-shelf DNA microarrays with custom probes into ST-compatible slides. In proof-of-principle experiments, our Array-seq prototype outperformed a widespread commercial ST platform in all metrics tested, including resolution, sensitivity, surface area, and cost. Second, we created a technique for large-format histological sectioning while preserving RNA which, combined with Array-seq slides, enables the spatiomolecular analysis of whole human organs or adult rodents. Here, we propose to develop our Array-seq prototype and histology methods to deliver a scalable, easy-to-adopt, and multimodal ST platform which will enable the high-throughput and cost-effective spatiomolecular analysis of tumors. In addition, we will assess the performance of our spatial technology by applying it to human colorectal cancer, providing a demonstration of the broad applicability of Array-seq for the spatiomolecular characterization of cancer at scale – from whole-organ, human tumors to large patient cohorts. Thus, our technology is poised to contribute to the spatial omics revolution in cancer research by making possible large-scale studies to characterize cancer progression and response to treatment, inform clinical decision- making, or find new therapy avenues.

NIH Research Projects · FY 2025 · 2025-09

Project Summary The objective of this study is to test a novel treatment, sodium glucose co-transporter-2 inhibitor medications, for prevention of recurrent idiopathic calcium phosphate (CaP) stones. Kidney stones are common (>10% in the U.S.) and prevalence is rising, leading to higher morbidity and cost. Idiopathic calcium oxalate (CaOx) and CaP stones are the most common types. Both stone types are associated with high recurrence rates, but CaP stones have the highest. High recurrence rates are associated with acute pain and hematuria, and higher risk of chronic kidney disease and end-stage kidney disease. Recurrent events also contribute to the high economic burden to individuals and the healthcare system, including costs from lost workdays and acute care visits. Yet, the only currently available prevention options have not updated in decades and no previous clinical trials have specifically focused on the highest recurring CaP patients. Prevention programs are key to reducing recurrent kidney stone events. Prevention is aimed at lowering supersaturation (SS) of CaOx and CaP as this lowers stone risk. Prevention strategies are limited for both stone types but more limited for CaP. Limited strategies include lowering SS by increasing urine volume with increased fluid intake or reducing urine calcium with low sodium intake or thiazide medications. Supplemental alkali (e.g. potassium citrate) decreases stone risk by increasing urine citrate, an inhibitor of calcium crystals, and is effective in CaOx patients but it is not known if it is effective in CaP patients. Alkali also increases urine pH which increases CaP SS and can potentially worsen CaP stone disease. It is also known that idiopathic CaP patients have an underlying disordered acid-base handling that is not present in CaOx patients. The underlying acid-base disorder and subsequent different response to alkali therapy highlights that CaOx and CaP are distinct patient populations. For this reason, both groups need to be separately studied in prevention trials. Sodium glucose co-transporter inhibitors (SGLT2i) are associated with improved outcomes in many disease states and have also been epidemiologically associated with lower kidney stone risk compared to other diabetes medications. This is likely because, like alkali, SGLT2i increase urine citrate but unlike alkali, SGLT2i decrease urine pH in healthy volunteers. Both CaOx and CaP will benefit from higher urine citrate but SGLT2i may be uniquely beneficial for CaP patients as the lower urine pH reduces CaP SS and therefore stone risk. However, no previous studies of the effect of SGLT2i on urine composition have included stone patients. We will study the effects SGLT2i have on urine citrate, pH and CaP SS in a highly selected population of CaP and CaOx stone patients. We have engaged with the kidney stone community (Kidney Stone Engagement Core) and will work with them throughout study design, implementation, and conduct. This work will lay the foundation for a future larger trial determining the ability of SGLT2i to prevent both stones but particularly CaP stones.

NIH Research Projects · FY 2026 · 2025-09

ABSTRACT Lung cancer, while the leading cause of cancer-related death in the United States, can, in up to 30% of patients, be treated by surgical resection. Yet, more than half of patients eligible for lung cancer resection are older adults (≥65 years), of which 70% are “pre-frail” or “frail.” Frailty portends poor perioperative outcomes, such as increased postoperative complications, length of stay, hospital costs, post-discharge institutionalization and mortality. The American College of Surgeons and other international societies recommend frailty mitigation by offering patients prehabilitation (prehab) programs that focus on exercise, nutrition, and social support. Despite prehab clinical trials providing strong evidence of efficacy, only 10-30% of patients actually adhere to prehab programs and the translation of these programs into clinical practice has been challenging. In our pilot studies of BeFitMe, a wearable technology-based prehab application that provides, encourages, and tracks self-guided, at-home exercise, based on the National Institute of Aging Go4Life exercises, uptake (enrollment of eligible patients) was 50%, adherence (exercising at least 50% of available preoperative prehab time) was 43%, and performance (exercising at least 150 min/week) was 35%. Lack of “end-user” participation in the design of an intervention, particularly a behavioral intervention such as prehab, can lead to poor uptake, adherence, and performance. Indeed, we are unaware of any current prehab program that applied a user-centered co-design approach to fully ascertain and address the specific needs, values, and preferences of the end-users, particularly the older adult patients. Furthermore, no prehab programs reported using any implementation science principles to integrate and adapt the intervention to varied clinical contexts. As a Stage I study in the NIH Stage Model for Behavioral Intervention Development, we propose to (1) Engage end-users (patients, caregivers, clinicians) in user-centered co-design to enhance BeFitMe and increase its uptake, adherence, and performance by older adults undergoing lung cancer surgery and (2) Apply an implementation framework to increase reach, adoption, and sustainability of the prehab program in clinical care. This project will provide me with experiential opportunity to gain new knowledge, skills, and expertise in user-centered co-design and usability testing, applied implementation science, and clinical trial methods. My long-term goal is to become a surgeon-scientist leader focused on optimizing the pre-hospital, in-hospital, and post-hospital phases of surgical care for prefrail/frail older adults with lung cancer and other surgical conditions.

NIH Research Projects · FY 2026 · 2025-09

PROJECT SUMMARY/ABSTRACT Foraging is fundamental to the survival of all animals and requires choosing which resources to pursue and which to forgo. These choices involve integrating information about the costs and benefits associated with each resource and are affected by the overall abundance of the foraging environment. Despite the importance of this behavior, how cost and benefit information are signaled in the brain to affect choice remains poorly understood. Understanding the neural circuit computations underlying foraging requires methods for manipulating and monitoring neural activity with temporal and cell type specificity. Many such tools are available in mice, but tasks typically used with mice are not well-suited to disentangle how cost and benefit are encoded in the brain. Thus, we developed a new foraging task for mice in which they make sequential decisions to pursue or reject offers with costs (time they must hold a nose poke) and benefits (reward size) that vary independently across trials. Additionally, the quality of the foraging environment changes in blocks, which changes the choices mice make without changing the features of the offers. This allows us to dissociate value and choice, which are often confounded. These features will allow us to disambiguate possible value encoding schemes in the brain. We will test a model of the basal ganglia whereby the direct pathway computes information in favor of performing an action (e.g., benefit) while the indirect pathway computes information against performing an action (e.g., cost). This information converges in an output nucleus of the basal ganglia, the substantia nigra pars reticulata (SNr). Whichever pathway has accrued more evidence biases the level of activity in the SNr, which then drives acceptance or rejection of the offer via its projections to the thalamus and brainstem. Finally, we hypothesize that dopamine release in the striatum signals whether an offer is better or worse than the average reward rate (i.e., environmental value). Thus, dopamine release to an intermediate value offer would be larger in a scarce environment. To test this model, we will image activity in the two major cell types in the striatum, direct and indirect pathway spiny projection neurons, to test the hypothesis that they separately encode the benefit and cost of the offers. Additionally, we will optogenetically inhibit these neurons to test the hypothesis that direct pathway inhibition decreases the relationship between offer benefit and choice while inhibition of the indirect pathway decreases the relationship between offer cost and choice. In Aim 2, we will image activity in the SNr. Here, we expect neural activity to reflect both cost and benefit and to be better correlated with choice than value. In Aim 3 we will use fiber photometry to measure dopamine release in the striatum to determine how it is affected by offer and environmental value. Together, these experiments will provide substantial insight into how cost- benefit decision making is supported by the basal ganglia by revealing multi-area circuit mechanisms regulating foraging behavior.

NSF Awards · FY 2025 · 2025-09

The PI will explore new structures in higher algebra, in collaboration with Dr. Shachar Carmeli at the Weizmann Institute of Science, Israel. This is an emerging field that combines ideas from classical algebra and modern homotopy theory. Classical algebra studies systems like the real numbers, with operations such as addition and multiplication that satisfy several rules (such as associative and distributive laws). Higher algebra studies structures in which these equalities are replaced by coherent witnesses, called homotopies. Over the past several decades, mathematicians have discovered that many important algebraic structures can be refined in this way, leading to many applications to other disciplines, such as mathematical physics and foundations of computer science. The project will study such higher structures in the subfield of stable homotopy theory. Moreover, the project will support the training and development of junior mathematicians in the field. The project aims to use methods from algebraic K-theory and power operations to study chromatic homotopy theory. Chromatic homotopy theory studies questions in stable homotopy theory (e.g., stable homotopy groups of spheres) via tools arising from the algebraic geometry of formal groups. Recently, categorical and K-theoretic techniques play an increasing role in the subject. The PI and collaborator intend to study the chromatic localizations of K-theory and other invariants of ring spectra, and relate them with recent advances in p-adic geometry such as the new theory of prismatization. This collaborative US/Israel project is supported by the Division of Mathematical Sciences of the US National Science Foundation and by the Israeli Binational Science Foundation. 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 · 2025-09

PROJECT SUMMARY/ABSTRACT The extracellular matrix (ECM) is crucial for maintaining the connective tissue in all organs, supporting tissue homeostasis and repair. When tissue homeostasis is disrupted by wounds or injury, fibroblasts become activated to help repair the damage and restore tissue structure by producing fibrillar collagens and other ECM molecules. If fibroblasts produce insufficient collagen, it could lead to nonhealing, chronic wounds. Conversely, excessive collagen synthesis can lead to fibrosis and impairment of organ function, a major healthcare challenge. How fibroblasts maintain the intricate balance between underproduction and overproduction of ECM remains an important yet unresolved question. A key challenge is understanding how fibroblasts regulate the production of ECM proteins, particularly collagen. An important but often overlooked aspect of ECM production is that fibroblasts must meet substantial metabolic demands to produce ECM biomass. These metabolic requirements differ from those for cellular biomass generation during proliferation, including a high demand for the non-essential amino acids glycine and proline for synthesizing collagens. We and others have demonstrated that activated fibroblasts upregulate nutrient uptake and metabolic flux into glycine and proline biosynthesis and that these pathways are required for collagen production. Despite these advances, little is known about how fibroblasts meet the metabolic demands of ECM synthesis physiologically during tissue repair. To address this gap, my research program aims to determine the physiological nutrients and metabolic pathways required for fibroblast ECM synthesis during tissue repair. The central question we will address over the next five years is: how do fibroblasts meet the nitrogen demands of collagen synthesis to drive tissue repair while tolerating toxicity from accumulating reduced nitrogen during this process? To answer this question, we have developed a novel experimental platform to trace nutrients directly into the ECM under physiological conditions. Leveraging this model, we will: (1) develop a long-term in vivo stable isotope tracing platform to determine the nitrogen sources for collagen synthesis during tissue repair; (2) understand how ECM synthesis associated metabolic rewiring allows fibroblasts to tolerate the accumulation of toxic metabolic waste products. Achieving these goals will provide fundamental insights into cellular metabolism and tissue repair and help lay the groundwork for strategies to modulate nutrients and their associated metabolic pathways to overcome healthcare challenges associated with insufficient or excessive ECM synthesis.