Washington University

NIH Research Projects · FY 2025 · 2025-09

PROJECT SUMMARY This project will enhance our understanding of the fundamental biology of Klebsiella pneumoniae, an important human pathogen deemed an urgent threat by the CDC due to escalating antibiotic resistance rates. I seek to understand how a ubiquitous and opportunistic organism, one capable of colonizing many diverse environments, can alter its gene expression to suit its surroundings. Specifically, I am investigating the mechanism by which K. pneumoniae senses increased temperature upon infecting a host and increases expression of its polysaccharide coat in response. This project builds on my experience in bacteriology as well as the importance of physiological temperature differences in pathogenesis by focusing specifically on the known virulence regulator KvrA. KvrA regulates the amount of capsule produced by K. pneumoniae by competing for the same binding site as H-NS, a transcriptional silencer of capsule. Previous work has demonstrated that the translation of SlyA in Escherichia coli, homologous to KvrA in K. pneumoniae, increases in response to temperature. Yet, the mechanism by which the environmental signal of temperature is transduced to increase the translation of SlyA/KvrA, and the subsequent production of capsule is unknown. I hypothesize that temperature regulates the translation of KvrA in K. pneumoniae via an RNA thermometer (RNAT) mechanism and this sensing ability is essential for capsule expression and virulence within the host. RNATs are secondary structures located within the 5’ untranslated region (UTR) of mRNAs that prevent translation from occurring at ambient temperatures but “melt” to free the Shine-Dalgarno (SD) sequence and allow translation at higher temperatures. Through a series of parallel experiments, I will determine whether the temperature regulation of K. pneumoniae KvrA occurs at the transcriptional or post-transcriptional level. GFP and luciferase reporter fusions will be constructed to test the region upstream of kvrA and determine if it acts as a temperature regulator independent of the kvrA coding sequence. In collaboration with Dr. Adrianus (“Jacco”) Boon, an expert in RNA structural biology at Washington University in St. Louis, I will characterize the secondary structure of the 5’ UTR of kvrA at both 37°C and 20°C using SHAPE-MaP. Alternative methods are available to investigate other non-RNAT thermoregulatory mechanisms of KvrA. A well-established murine model of pneumonia will be leveraged to evaluate the significance of this KvrA thermoregulatory mechanism in vivo. I will compare the virulence of strains with stabilizing mutations in the kvrA 5’ UTR predicted to resist melting at 37°C to those with a wild-type kvrA 5’ UTR. I will also evaluate the role of krvA in strains lacking H-NS, thus determining if KvrA’s thermoregulatory effects on capsule are independent of H-NS. With the rise of antibiotic resistance, it is critical to find alternative methods for treating and preventing K. pneumoniae infection. This proposed work will define a critical mechanism of K. pneumoniae environmental sensing that may be amenable for therapeutic targeting.

NIH Research Projects · FY 2025 · 2025-09

Project Summary/Abstract Adam Coffman is a lead software engineer on CIViC, an open access, community-driven web resource for Clinical Interpretation of Variants in Cancer. CIViC is a critical and integral part of the cancer variant interpretation ecosystem, and has been integrated into dozens of academic, clinical, and commercial resources. This application aims to support Mr. Coffman as a Research Software Engineer in the Griffith Lab at Washington University St. Louis School of Medicine so that he can continue to make significant contributions to the CIViC platform under the supervision of Dr. Obi Griffith, PhD. Mr. Coffman studied Computer Science as an undergraduate, has worked as a software developer in industry, and has over a dozen years of experience in research lab settings developing open source web applications in support of precision oncology and bioinformatics projects. The three years of funding provided by the Research Software Engineer award would grant stability and protected time for Mr. Coffman to focus on the CIViC project’s most high priority development needs. He will build features to help reduce the bottleneck caused by editorial review including tools commonly requested by the ClinGen Somatic Cancer Variant Curation Expert Panels (SC-VCEPs) such as dependent task assignment, automated variant coordinate curation, and variant pathogenicity scoring based on assigned criteria. Additionally, he will build out novel visualization and search tools that fully leverage the underlying knowledge graph to allow users to explore the data available in CIViC in a more accessible and intuitive manner. Mr. Coffman will ensure CIViC remains current in implementing emerging data standards for variant representation developed by the Global Alliance for Genomics and Health (GA4GH) and other relevant standards bodies. This support will be critical to maintain and improve upon CIViC’s wide adoption and ease of integration into other resources. Finally, Mr. Coffman will develop new training materials to enable further community adoption and continue to provide direct support to labs, clinics, and companies integrating CIViC’s free and open data into their platforms. Over the course of this award, Mr. Coffman expects to build upon his already extensive experience in web application development by obtaining additional skills in areas such as data visualization and graph algorithms.

NIH Research Projects · FY 2025 · 2025-09

PROJECT SUMMARY/ABSTRACT Trophoblast is the major epithelial cell type in the placenta and provides an essential maternal-fetal interface during pregnancy. Understanding the specification and differentiation of the trophoblast lineage is vital for improved diagnosis and treatment of placental complications, including implantation failure, preeclampsia, and preterm birth. Trophoblast has historically been difficult to study in humans due to limited access to first-trimester placental tissue and the inability of animal models to fully recapitulate human placental development. To enable dissection of early mechanisms of human trophoblast development, we will leverage “naïve” human pluripotent stem cells (hPSCs), which exhibit molecular signatures of pluripotent cells in pre-implantation embryos. We recently showed that naïve hPSCs readily differentiate into human trophoblast stem cells (hTSCs), which can in turn differentiate into specialized extravillous trophoblasts (EVTs) and syncytiotrophoblasts (STBs) or self- organize into 3D organoids that encompass a diversity of trophoblast cell types. Here, we will combine these 2D and 3D models of trophoblast development with epigenomic and single cell approaches to dissect the mechanisms of human trophoblast differentiation and function. Importantly, we have already validated key preliminary findings in human first-trimester placental tissues and will extend this in vivo validation to all the major findings of this project. Aim 1 will establish an epigenome roadmap during the transition from naïve hPSCs into hTSCs and their subsequent differentiation into specialized trophoblast fates. This work will identify functional cis-regulatory elements (CREs) and test the hypothesis that trophoblast specification from naïve hPSCs is primary mediated by transitions between unmarked and actively marked CREs. Aim 2 will define a core transcriptional circuitry governing human trophoblast specification, starting from the results of a genome-wide CRISPR/Cas9 knockout screen in hTSCs. We will test the hypothesis that transcription factors (TFs) enriched at enhancers and promoters of hTSC-specific essential genes constitute an upstream circuitry of trophoblast inducers and integrate these trophoblast inducers and their target CREs into a dynamic gene regulatory network during trophoblast specification. Aim 3 will investigate candidate regulators of trophoblast differentiation into EVT and STB lineages, which perform specialized functions during pregnancy. We hypothesize that the G protein- coupled receptor CCR7 and the TF TEAD1 are required for EVT differentiation. By generating trophoblast organoids from CCR7 and TEAD1 knockout hPSC lines, we will delineate a genetic hierarchy of factors regulating EVT differentiation and invasion. We will also investigate novel regulators of STB differentiation based on their ability to promote cell cycle exit in hTSCs and their enrichment at STB-specific open chromatin. In summary, this project will provide conceptual and experimental advances in understanding the genetic and epigenetic mechanisms regulating specification of the human trophoblast lineage. Our work will also define the action and significance of CREs and TFs in regulating the differentiation of hTSCs into specialized trophoblast cell types.

NIH Research Projects · FY 2025 · 2025-09

Project Summary From infancy to adulthood, the human cortex expands three-fold, with consequences for cognition and behavior. While preclinical and histological research suggests that cortical expansion is driven by underlying microstructural processes including dendritic arborization and synaptogenesis, it remains poorly understood whether patterns of expansion reflect underlying changes in cortical microstructure in human samples. Importantly, this key developmental process of cortical expansion may have clinical implications, as surface area (the end result of expansion) has been linked to both cognitive and psychiatric outcomes in numerous clinical populations. Thus, work exploring the biological underpinnings and functional consequences of cortical expansion in early childhood is critically important. Children born very preterm (VPT; prior to 32 weeks gestation) are a population of specific interest, as they experience increased rates of aberrant brain development as well as comorbid ADHD, autism, and anxiety and impairments in executive functioning (EF) in childhood. Further still, previous work has shown that over the first decade of life, they experience altered expansion in association cortices known to be important for cognitive and psychiatric functioning. However, it remains unclear if these alterations in cortical expansion relate to changes in cortical microstructure and if these patterns of altered expansion underlie the increased rates of EF and psychiatric difficulties common in VPT children. The current proposal will leverage ten years of unique existing data from a highly valuable, prospective, longitudinal cohort of 52 VPT and 41 full-term (FT) children (currently being studied through R37 MH113570) to address these gaps. It is hypothesized that decreased cortical expansion in association cortices will predict greater EF and psychiatric impairments at age 10 years, and that these patterns of expansion will be predicted by cortical microstructure differences already visible in infancy. To test this, in Aim 1, the applicant will innovatively analyze both longitudinal diffusion and structural imaging data to define the relationship between spatial patterns of cortical microstructure and patterns of cortical expansion in VPT and FT children. In Aim 2, the applicant will determine how individual differences in cortical expansion relate to EF and psychiatric functioning at age 10 years in the same sample. By identifying brain-based risk factors for cognitive and psychiatric impairments, this work will expand our understanding of how the brain develops and could facilitate the creation of more targeted, early treatments for at-risk children. Importantly, this proposed project will allow the applicant to develop her skills in diffusion neuroimaging, longitudinal data analysis, scientific communication, and child psychiatry under the highly valuable mentorship of Drs. Cynthia Rogers and Chris Smyser at Washington University. This will provide the candidate with a strong foundation as she pursues her ultimate goal of becoming an academic child psychiatrist who studies how early interventions support brain development and improve psychiatric functioning in children.

NSF Awards · FY 2025 · 2025-09

Non-technical Abstract: This project explores a promising pathway toward fault-tolerant quantum computing by studying spin-triplet superconductors. These materials may host exotic quantum states that could serve as the foundation for robust quantum bits. The research focuses on fabricating and characterizing high-quality Josephson junctions to detect and control these states, addressing key experimental challenges that have limited progress in the field. In addition to advancing quantum technologies, the project includes a strong educational component. Graduate students will gain hands-on training in quantum materials research, while younger students will be introduced to quantum physics through illustrated books. Public interviews with leading physicists will further promote understanding of advanced science among broader audiences. Together, the research and outreach efforts aim to expand both the frontiers of quantum science and access to it. Technical Abstract: Spin-triplet superconductors offer a unique platform for realizing topological quantum states, including Majorana modes and intrinsic pi-junctions, which are essential building blocks for fault-tolerant quantum computing. However, experimental progress in this field has been severely limited by the technical challenges in fabricating high-quality Josephson junctions and characterizing their quantum properties. This project aims to overcome these barriers through the systematic fabrication and investigation of Josephson junctions based on UTe2 and other leading spin-triplet superconductor candidates. The project will establish a robust methodology for creating high-performance junctions, enabling precise measurements of the current-phase relation and direct detection of topological excitations. The research team will implement a combination of advanced fabrication techniques, corner-junction interferometry, and phase-sensitive transport measurements. The integrated experimental framework will also be extended to other spin-triplet superconductors, laying the groundwork for a broader class of topological quantum devices. Specific goals include: (1) Develop high-quality Josephson junctions based on spin-triplet superconductors; (2) Uncover the pi-junction behavior via phase-sensitive measurements; (3) Detect and control Majorana modes to enable topological quantum device applications. 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

Facioscapulohumeral muscular dystrophy (FSHD) is a prevalent form of muscular dystrophy caused by the aberrant expression of the transcription factor DUX4, which leads to muscle toxicity and progressive weakness. While previous research has identified transcriptional changes induced by DUX4, the mechanisms through which DUX4 affects RNA processing, particularly alternative splicing, remain largely unexplored. Alternative splicing is critical for muscle function, and its disruption may exacerbate muscle pathology in FSHD. This project aims to investigate the role of DUX4 in regulating alternative splicing, with the goal of developing an RNA splicing biomarker for FSHD. The proposed research includes three specific aims. First, the project will characterize the interactions between DUX4 and RNA in muscle cells to identify RNA targets of DUX4 that undergo alternative splicing (Aim 1). Second, the role of DUX4 in regulating the alternative splicing of TNNT1—a gene essential for muscle contraction that is abnormally spliced in FSHD—will be explored, focusing on the potential cooperation between DUX4 and splicing factors hnRNP U, DDX5, and FUS (Aim 2). Third, the project will develop an RNA splicing biomarker for FSHD by identifying and validating splicing changes in patient-derived myotubes and iPSC-derived myotubes (Aim 3). To achieve these aims, the project will utilize advanced methodologies, including RNA-seq, CLIP-seq, and splicing analysis tools such as DEXSeq. The research is expected to uncover molecular mechanisms through which DUX4 disrupts splicing in FSHD, which may provide a foundation for future diagnostic and therapeutic strategies. These findings will be crucial for developing clinical trials that assess splicing biomarkers in FSHD patients. This award will provide the applicant with the training and expertise in bioinformatics and RNA biology necessary to become an independent investigator. Under the mentorship of experts in the field, the applicant will gain proficiency in analyzing next-generation sequencing data and conducting complex RNA biology assays. This project will establish a strong foundation for a research program focused on gene regulation in muscular dystrophies and contribute to the development of targeted therapies for FSHD.

NSF Awards · FY 2025 · 2025-09

This project uses machine learning to create a database of State of the State (SOTS) addresses from 1800 to 2016 and state-level agendas. The data collection involves collecting and cleaning the full set of speeches from governors over time. SOTS data are stored at publicly available data repositories and a website developed by the PIs. Methodologically, the project advances the study of unstructured data and the use of artificial intelligence and machine learning. The data support knowledge and scholarship related to public decision and provide a web resource for educators and journalists. This project extends the SOTS dataset that covers state-of-the-state addresses from 1800 to 2016. The PIs collect, process, and analyze SOTS speeches from years prior to 1960, using techniques developed to overcome poor quality documents implemented through software created by one of the PIs. The software applies machine learning to isolate, enhance, and extract text from hard-to-read documents, correcting document layout problems with a novel statistical approach before it runs optical character recognition (OCR). This results in a significantly higher level of accuracy than other current approaches. 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

A key feature of all living organisms is their ability to respond and adapt to an everchanging environment to ensure cellular homeostasis. In response to chemical or physical stress, organisms activate a variety of processes, including quality control mechanisms that preserve the integrity of biological molecules as well as stress response pathways enabling them to mitigate the effect of damage. How and when cells switch between these responses is highly regulated. For example, recent work from my group showed that in response to chemical damage to mRNA, eukaryotes promptly activate ribosome quality control (RQC); on the other hand, if the damage persists, they activate the integrated stress response (ISR). We have known for some time that the ribosome and the translation machinery are key effectors for these pathways. Notably, however, we recently showed that the ribosome itself is widely used as a sensor for these pathways. In particular, our work revealed that collided ribosomes are the key signal for the activation of RQC and the ISR, and that they are in apparent competition with each other, where the induction of one process suppresses that of the other. We note that much of this work was motivated by our initial studies on the consequences of mRNA damage on protein synthesis. However, it is clear that other species of RNA are also susceptible to damage, including ribosomal RNA. Interestingly, the fate of chemically damaged ribosomes has received little to no attention, even though they are known to accumulate in disease states and in response to certain chemotherapeutic treatments. As a result, we will test the hypothesis that cells evolved nonfunctional ribosome decay to recognize and rapidly degrade chemically damaged ribosomes. We are also interested in establishing the mechanism by which such defective ribosomes are identified and distinguished from undamaged ones. Remarkably, emerging from our preliminary studies is the observation that not only is RQC-mediated modification of collided ribosomes critical for the ISR, but also for activation of the DNA damage response. Therefore, we will examine the hypothesis that the response to RNA damage is a hitherto unappreciated pathway for cells to protect themselves expediently from damaging agents. We propose that damaged mRNA and its induction of ribosome collisions serve as a molecular sentinel, alerting cells to hazardous conditions that could damage either DNA or RNA. Finally, in exciting preliminary data, we show that RNA polymerase II stability is intimately coupled to that of the translation factor eIF4E, which binds the capped mRNA products of the polymerase. We propose that this mechanism evolved in eukaryotes as a safeguard ensuring the flux of transcription is fine tuned to that of translation. We will test the model that RNAP II is degraded through a quality-control step during proximal-promoter pause release, acting as a critical checkpoint before elongation by the polymerase can proceed. Collectively, our proposed experiments will reveal fundamental mechanistic insights into how organisms utilize the ribosome and the translational machinery to respond to damaging agents through signaling pathways that also impact transcription and genome integrity.

NSF Awards · FY 2025 · 2025-09

The goal of the proposed research is to advance knowledge of how to apply cognitive principles about the understanding of temporally structured concepts to the design of animated STEM instructional materials. The focus of this research will be on STEM concepts that involve processes and transformations that unfold over time, such as photosynthesis and earthquakes. Relatively little is known about how students learn STEM concepts that involve a sequence of steps or phases compared to how they learn more static concepts, such as kinds of rocks. Analyses show that the current use of animations in practice to teach such concepts does not consistently improve learning. In this project, the research team will build on recent substantial advances in cognitive science about how people understand and remember everyday events and attempt to apply these cutting-edge findings to further the understanding of how people learn about processes and transformations in complex STEM concepts. They will test a theory-driven intervention using real-world STEM instructional material. Should this work be successful, it will help to explain why some STEM instructional animations aid student learning, and why the majority of such animations currently used in educational practice do not. Moreover, the output of this project will provide principles that will eventually guide how such animations should be designed in the future to facilitate STEM learning. In this project, a transdisciplinary team with expertise in psychology, neuroscience, the science of learning, and science education will test a new hypothesis about how students learn temporally structured concepts. Theories and empirical data from studies of everyday event comprehension and memory suggest that segmenting ongoing information into appropriate temporal parts enables people to better learn and remember those parts. In turn, this can protect that information from confusion with other similar information, keeping important concepts distinct. This research will test the possibility that the same comprehension and encoding mechanisms are brought to bear on concept learning when learners interact with instructional materials teaching concepts for processes and transformations. The research team will test this hypothesis by combining experimental manipulations with analyses of individual differences. At the center of their approach will be the deployment of theoretically grounded learning interventions, using authentic STEM education materials. The outcomes of the research will not only advance understanding of basic cognition, but will also form a basis for probing new teaching methods that could be effective in practice. This project is jointly supported by the EDU Core Research (ECR) program and the the Innovative Technology Experiences for Students and Teachers (ITEST) program. ECR supports fundamental research that generates foundational knowledge to advance the research literatures in STEM learning and learning environments. ITEST supports projects that build understandings of practices, program elements, contexts and processes contributing to increasing students' knowledge and interest in STEM and information and communication technology careers. 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

Abstract Text The Artificial Intelligence Ready and Exploratory Atlas for Diabetes Insights (AI-READI) project is one of the data generation projects in the NIH Common Fund’s Bridge2AI program. The project seeks to create a flagship ethically-sourced dataset to enable future generations of artificial intelligence/machine learning (AI/ML) research to provide critical insights into type 2 diabetes mellitus (T2DM), including salutogenic pathways to return to health. The ability to understand and affect the course of complex, multi-organ diseases such as T2DM has been limited by a lack of well-designed, high quality, and large multimodal datasets. The team of investigators will aim to collect a cross-sectional dataset of 4,000+ people and longitudinal data from 10% of the study cohort across the US. The study cohort will be balanced for diabetes disease stage. Data collection will be specifically designed to permit downstream pseudotime manifold analysis, an approach used to predict disease trajectories by collecting and learning from complex, multimodal data from participants with differing disease severity (normal to insulin-dependent T2DM). The long-term objective for this project is to develop a foundational dataset in diabetes, agnostic to existing classification criteria, which can be used to reconstruct a temporal atlas of T2DM development and reversal towards health (i.e., salutogenesis). Six cross-disciplinary project modules involving teams located across eight institutions will work together to develop this flagship dataset. All data will be optimized for downstream AI/ML research and made publicly available. . The AI-READI project will also engage in a tribal consultation to address barriers and facilitators of participation with the goal of collecting similar data within a Native American cohort in an ethical and respectful manner. Specific aims include 1) Collect and share the dataset for AI/ML research according to the Findable, Accessible, Interoperable, Reusable (FAIR) data principles, 2) Create a model for developing large scalable datasets, and 3) Increase access to and quality of AI/ML research by recruiting and training personnel.

NSF Awards · FY 2025 · 2025-09

Many decision-making tasks in healthcare, business, and economics can be naturally framed as online sequential decision-making problems, where decisions are made and outcomes are observed iteratively to achieve long-term objectives. Reinforcement learning (RL) offers a powerful framework and has achieved significant success in engineering domains, including robotics and gaming. However, human-centered tasks — such as those in healthcare and business — pose substantial new challenges for RL. These high-stakes tasks are more complex (e.g., non-stationary environments, heterogeneity across objects, and tension between leveraging historical data and the need to perform well in an interactive online setting) and impose more requirements (e.g., interpretability, performance guarantees, and computational efficiency). This project will address these challenges by conceptualizing and gaining insight into the aforementioned complications and by developing well-rounded methodologies that can effectively handle them and meet all requirements. The research outcomes will be broadly applicable to diverse fields, including but not limited to healthcare (e.g., patient treatment, mobile health), business (e.g., operations management, marketing, financial strategies), and economics (e.g., public policy). This project also integrates research and education by providing research training opportunities for students and incorporating the findings into course materials. In more detail, the project will focus on three interrelated tasks: (1) investigating non-stationarity in a principled way and developing methods that are adaptive and robust to it; (2) developing personalized RL models and methods to address heterogeneity and studying its influence and implications; (3) systematically comparing online vs. offline RL through establishing principled criteria and gaining insights to guide algorithm development and evaluation. Individual tasks also include computational components that examine the trade-off between computational cost and statistical accuracy. Collectively, these components provide a well-rounded solution to online sequential decision-making problems in business and healthcare that face multifaceted challenges. This project is interdisciplinary and will leverage not only techniques in reinforcement learning and general machine learning but also ideas and tools from diverse technical subfields (e.g., nonparametric statistics, high-dimensional statistics, optimization, and applied mathematics), as well as domain expertise in business and healthcare. 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

In this project, artificial intelligence (AI) will be used to design new sustainable polymeric materials with a range of properties and that can be recycled without the need for costly and inefficient separation from mixed waste streams. Today’s plastic waste challenge exists at a scale of megatons per day across tens of thousands of applications and products. The researchers will create new types of depolymerizable plastics derived from simple feedstocks, and they will develop physics-informed AI models to aid design of these plastics such that they meet a variety of product specifications across a wide range of properties. Ultimately, this approach enables products of all different types, functions, and lifetimes to be integrated into a single recycling stream and accelerates their discovery-to-use timeline. The results and methods developed by this research will be publicly accessible for industrial benchmarking and include code and tutorials for users to perform AI-guided design on their own materials. Through this research, a new generation of scientists will be trained to work at the emerging intersection of polymer materials design and AI model development and use. With this award, the project will develop physics-informed AI and synthesize architecturally varied and deconstructable (ADD) polymers by cationic ring-opening polymerization (CROP) with controlled chain length, branching, and dynamic bond incorporation. This work will create new synthetic strategies to control chain end and side chain functionality, branch type and frequency, and dynamic bond incorporation for polymers produced by CROP. Using polyacetals and polyethers synthesized from a select few monomers, these complex molecular architectures will be linked to key properties using physics-informed AI, which both describes polymer architecture through sets of probability distributions and incorporates theoretical estimates of structure-property relationships. This physics-informed AI will be iteratively improved through active learning approaches and subsequently used to perform inverse design for the creation of new ADD polymers with targeted properties within specified tolerances that will be experimentally validated against industry benchmarks. This Molecular Foundations for Sustainability: Sustainable Polymers Enabled by Emerging Data Analytics (MFS-SPEED) award is co-funded by the NSF through the Division of Chemistry (CHE), the Directorate for Mathematical and Physical Sciences (MPS), and the Division of Innovation and Technology Ecosystems (ITE) in the Directorate for Technology, Innovation, and Partnerships (TIP). Additional MFS-SPEED funding is provided by Procter & Gamble, PepsiCo, Dow, BASF, and IBM. 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 A majority of heritable disease-causing variation resides in the non-coding portions of the genome. The leading hypothesis is that these variants perturb the function of cis-regulatory elements, such as enhancers. A remarkable property of enhancers is that they often reside at long distances from their targets. Thus, any framework for interpreting genetic variation must account for the long-range functions of enhancers. There have been many genome-wide studies of enhancers, yet we still lack an understanding of the sequence features that allow enhancers to function over long distances. This lack of understanding is due to the absence of systematic training data that measures the activities of enhancers as they are moved further and further from their target promoters. We propose to address this gap by systematically measuring the activities of enhancers at multiple fixed distances from target promoters. To collect this data, we will introduce a high-throughput, genome-integrated reporter gene system that measures the activities of enhancers at long distances from their target promoters. We propose to quantify the effects of variables that contribute to long-range enhancer function. These variables include the intrinsic strength of an enhancer, the number and arrangement of transcription factor binding sites in an enhancer, and the chromatin environment in which an enhancer resides. A unique strength of our system is that we directly compare the same enhancer sequences at long- and short-ranges, which allows us to identify features required specifically at long distances.

NIH Research Projects · FY 2025 · 2025-09

PROJECT SUMMARY Cardiovascular diseases such as coronary artery disease, heart failure, and arrhythmia contribute significantly to morbidity and mortality worldwide. Cardiac inflammation plays a significant role in disease pathogenesis, and cytokines like the interleukin-1 (IL-1) family contribute significantly to acute and chronic inflammation. Therapeutic approaches that inhibit IL-1β signaling have been shown to improve cardiovascular outcomes in patients with heart failure. However, the precise cellular targets of the IL-1 cytokine family in the heart remain poorly defined, limiting additional therapeutic development. The heart contains two main populations of macrophages: CCR2- resident macrophages and CCR2+ monocyte-derived macrophages, the latter being a significant source of IL-1β during cardiac injury. I have generated preliminary data indicating that IL-1β signaling modulates immune cell behavior and differentiation. The central hypothesis of this research is that IL-1 signaling to infiltrating monocytes and derived macrophages promotes myocardial inflammation by driving their differentiation towards pro-inflammatory cell states, leading to adverse cardiac remodeling. Aim 1 seeks to define the impact of IL-1β signaling to infiltrating CCR2+ monocytes and derived macrophages on cardiac remodeling and fibrosis. Using transgenic Ccr2CreERT2IL1rf/fRosa26tdTomato mice, I will conditionally knock out the IL-1 receptor in CCR2+ monocytes and macrophages and evaluate the effects on myocardial inflammation, fibrosis, and remodeling in two models of cardiac injury: pressure overload (Angiotensin II/Phenylephrine infusion) and ischemia-reperfusion (IRI). This aim will clarify whether IL-1 signaling to CCR2+ macrophages is a viable therapeutic target to mitigate adverse remodeling. Aim 2 investigates the mechanisms through which IL-1β signaling shapes the cardiac immune landscape and immune cell differentiation. By leveraging genetic lineage tracing (Arg1tdT-CreRosa26ZsGreen) and spatial transcriptomics, this aim will explore how IL-1 signaling influences the differentiation trajectories of infiltrating monocytes and their progeny. Computational analyses will be used to examine the regional organization and kinetics of immune cell differentiation during cardiac injury, with the goal of identifying reparative and pathological immune niches within the heart. Overall, this research will address critical gaps in understanding the contributions of IL-1 signaling in cardiac inflammation and remodeling. Defining how IL-1 signaling drives immune cell behavior and contributes to adverse cardiac outcomes will provide key insights into the potential mechanisms underlying IL-1-targeted therapies. Additionally, this work will help inform strategies to enhance the efficacy and safety of these therapies, with the ultimate goal of improving clinical outcomes for heart failure patients.

NIH Research Projects · FY 2025 · 2025-09

Project Summary/Abstract The proposed three-year conference series entitled “Addressing the Complex Driving Continuum: Needs of an Aging Population” (ACDC: NAP), centered around aging, mobility, and transportation safety, aims to bring together leading experts from various fields such as geriatrics, neurology, public health, and transportation and mobility. This series is essential to address the needs of an aging population, particularly in integrating new technologies like Advanced Driver Assistance Systems and artificial intelligence to enhance mobility and driving safety for older adults. The conference series will provide a space for clinicians, policymakers, researchers, community organizations, and industry partners to assess the current state of research, investigate current clinical practices for evaluating crash risk, and examine national public policy/advocacy initiatives surrounding unsafe driving and resources for alternative transportation options with a special emphasis on involving underrepresented communities, rural populations, and low-income older adults. The conference will provide a platform for interdisciplinary collaboration, fostering new research and generating actionable strategies to bridge the current gaps in research and practice. The first conference to initiate this series will be held locally at Washington University School of Medicine in St. Louis in the fall of 2025, followed by national conferences in 2026 and 2027 in partnership with the Gerontological Society of America (GSA). The aims of this conference series will be to examine research that identifies age-related medical risk factors (e.g., visual impairments, Alzheimer’s disease, Parkinson’s, stroke) that increase crash risks and investigate evidence on assessment tools of driving-related abilities. It will also focus on interventions to enhance physical and cognitive skills and technologies to support the unique needs of older drivers and generate consensus on the decision-making process around driving cessation, its impact on older adults’ health and well-being, and alternative transportation options to sustain their independence. The conference will receive guidance and support from aging, transportation, and ADRD experts to ensure a comprehensive and impactful discussion. Dissemination strategies include peer-reviewed publications, webinars, podcasts, and community outreach efforts. By convening national experts from aging, allied health, transportation and mobility, neurology, geriatrics, gerontology, and public health fields, the conference is expected to foster new collaborations and generate actionable strategies to address current gaps.

NIH Research Projects · FY 2025 · 2025-09

PROJECT SUMMARY Cardiovascular disease is the leading cause of death worldwide. While current heart failure therapies primarily target neurohormonal pathways driving adverse remodeling, they do not address inflammation, a key contributor to cardiac dysfunction and fibrosis. Recent studies have highlighted the importance of monocyte- derived macrophages marked by C-C chemokine receptor 2 (CCR2) in cardiac inflammation and remodeling. These CCR2+ macrophages arise from highly plastic monocytes and form a heterogeneous population with both inflammatory and reparative functions. However, little is understood about the mechanisms that govern monocyte fate specification in the heart. This project investigates the GM-CSF/STAT5 signaling axis as a critical regulator of CCR2+ monocyte fate specification during cardiac injury. GM-CSF (Csf2) signaling, which drives STAT5-mediated transcription of inflammatory genes, is upregulated following cardiac injury. My central hypothesis is that GM-CSF signaling to heart-infiltrating monocytes regulates monocyte differentiation, controlling the specification between inflammatory and reparative macrophage states, a process critical for cardiac repair. Supporting this hypothesis, I found that Stat5 deletion in CCR2+ monocytes reduced cardiac inflammation and improved cardiac function in two distinct murine heart failure models. Importantly, I used single-cell RNA sequencing to identify cardiac macrophage states, and I demonstrated that Stat5 deletion reduces inflammatory macrophage subsets and enriches a macrophage population expressing high levels of Trem2 (triggering receptor expressed on myeloid cells 2). Trem2+ macrophages are implicated in resolving inflammation and promoting tissue repair in other organs, but their specification and functional roles in the heart remain unexplored. Aim 1 of this proposal elucidates mechanisms of Trem2+ macrophage specification and fate maps their lineage in the heart. Aim 2 investigates the functional roles of Trem2+ macrophages in murine models of heart failure. By addressing critical gaps in our understanding of CCR2+ monocyte fate specification and the identity and function of Trem2+ macrophages, this work will inform novel therapeutic strategies targeting specific macrophage states to mitigate inflammation in cardiac disease—maximizing treatment efficacy while minimizing off-target effects.

NIH Research Projects · FY 2025 · 2025-09

PROJECT SUMMARY Bacteroides fragilis, which comprises up to 2.5% of the human microbiota, is often acquired within the first month of life. While non-toxigenic B. fragilis (NTBF) is considered a symbiont in humans, enterotoxigenic B. fragilis (ETBF) produces the B. fragilis toxin (BFT), which causes pro-inflammatory damage to the intestinal epithelium and has been associated with colorectal cancer (CRC) development. Since the human microbiota composition becomes stable during early development, the link between early colonization by ETBF and CRC risk requires further investigation to develop preventive therapeutics. To address this, our lab has developed a vertical transmission model to study ETBF colonization in neonatal mice and to assess the impact of the developing microbiota on the host. Using this model, we have demonstrated that BFT facilitates lamina propria (LP) niche acquisition through goblet cell-associated passages (GAPs) during the pre-weaning period. Additionally, neonatal ETBF colonization persists into adulthood and induces crypt elongation and goblet cell hyper- differentiation in colonic tissue. Based on the localization of ETBF in the LP niche beneath the colonic crypt base, as well as its role in BFT-dependent colonic tissue remodeling, I hypothesize that BFT directly influences epithelial stem cell fate signaling by positioning itself beneath the colon crypt base, contributing to CRC progression. To investigate this hypothesis, I will use a neonatal colonization model (vertical transmission model) to study early-life ETBF colonization and advanced microscopic techniques to capture the earliest CRC precursors in ApcMin/+ mice upon neonatal ETBF colonization. Focusing on in vivo studies, I will explore how BFT-mediated ETBF LP colonization modulates crypt cell fate signaling and also assess how early-life ETBF colonization affects CRC susceptibility. This research strategy will provide insights at both the molecular level and the clinical level into how ETBF colonization influences colonic crypt base stem cells and CRC susceptibility. The successful completion of this proposal will address an unexplored gap in ETBF-host epithelial cell interaction in the colon tissue and provide mechanistic insights into the interplay between early-colonizer microbiota and disease risk. Together, these studies will pave a way to investigate microbiome-based therapeutic interventions to prevent CRC.

NIH Research Projects · FY 2025 · 2025-09

Project Summary/Abstract Early human development generates thousands of precise cell fates from a single zygote with extreme fidelity. This is largely accomplished via the coordinated regulation of gene expression in cell type- specific patterns. Extensive observation of these patterns has nominated candidate genes that can be exogenously expressed in non-target originating cell types to generate desired cell types through a process called cellular reprogramming. For instance, the overexpression of defined transcription factors (TFs) in human fibroblasts can be convert them directly into a variety of therapeutically useful cell types, including neurons and cardiomyocytes. However, most reprogramming schemes produce heterogeneously differentiated cells that do not faithfully adopt the gene regulatory programs of the target cell types, and consequently are unsuited for therapeutic applications. It is increasingly appreciated that epigenetic factors, including the structure and composition of chromatin, might influence the efficiency of reprogramming in a given cell. For instance, nucleosomal wrapping of DNA and compaction in heterochromatin can silence natively active genes to promote cell type conversion. Therefore, epigenetic events represent unobserved variables that can confer differential competence for reprogramming. Here we propose to observe these variables directly using a novel time-lapse epigenome profiling method, in which multiple snapshots of heterochromatin protein enrichment and how they change over time are captured in the same single cells. We will use time-lapse information to identify key spatiotemporal changes in chromatin-mediatedgene regulation that are associated with successful reprogramming and use catalytically inactivated Cas9 fused to chromatin regulatory domains to functionally test whether these events can lead to more efficient iEP outcomes. We further will produce rich, standardized datasets from time-lapse profiling of common reprogramming trajectories for public use, with a focus on their utility for deep learning approaches to discover new modulators of reprogramming efficiency In the long term, we anticipate that these improved methods we introduce will improve the rational design of efficient cell type conversion schemes for tissue regeneration and other important therapeutic purposes.

NIH Research Projects · FY 2025 · 2025-09

ABSTRACT The gut microbiome and immune system develop in concert, influenced by environment, diet, infections, and antibiotics. Secretory immunoglobulin A (sIgA) in breastmilk is the primary mediator of coordinated immune and microbiome development, modulating host-bacterial interactions. Breastmilk sIgA is the main source of IgA be- fore the first month of life, and formula-fed infants lack sIgA exposure during this critical period. Antibiotics ad- ministered during infancy lead to dramatic changes in microbiome composition during a critical period for regu- lation of gut inflammation. Preterm infants are more likely to be exposed to antibiotics, are more susceptible to bacterial infection, have less mature gut microbiomes, and have persistent alterations in immune development relative to their term counterparts. Animal models are essential to precisely control the complexity and variables of human immune and microbiome development. Gnotobiotic mouse models have been used to determine how individual strains impact immune development in adults. However, <25% of species tested in these models have >5% prevalence among infants. Therefore, new models are necessary to determine the impacts of microbes that colonize human infants on the developing immune system. We have developed a gnotobiotic mouse model of colonizing germ-free mating pairs with bacterial isolates or fecal samples from human infants. Pups are born microbiome-humanized, avoiding the negative immune consequences of lack of microbial exposure. Just as in human neonates, the gut microbiome of these mice matures over time, and we find that microbiome similarity correlates with cellular and secreted markers of immune response. The rationale for our proposal is to use this model to understand how human-associated microbes impact immune development, sIgA bacterial binding, and susceptibility to antibiotic-mediated disruption and bacterial pathogen colonization. In Aim 1, we colonize gnoto- biotic dams with the most abundant and prevalent bacterial isolates or combinations colonizing human infants from two clinical cohorts of 80,000 fecal samples from over 1,050 hospitalized preterm or community term infants. By using germ free breeding pairs homozygous or heterozygous IgA knockout mice, we will evaluate how ma- ternal or infant sIgA impacts immune development. In Aim 2, we colonize wild-type germ-free mice with preterm or term fecal samples and evaluate immune disruption relative to antibiotic treatment. In Aim 3, we evaluate immune tolerance and susceptibility to E. coli challenge with rescue with IgA supplementation. Our proposal is innovative because our interdisciplinary research team will complement data from unique human cohorts in a gnotobiotic mouse model that recapitulates microbiome and immune development and disruption by antibiotics and infectious challenge. This proposal is significant because we will use sophisticated multivariate analyses to precisely determine how prevalent infant-associated microbes differentially affect immune development. Our work is impactful because we will advance understanding of the co-development of the gut microbiome and immune system and establish a predictive framework for promoting healthy microbiome-immune interactions.

NIH Research Projects · FY 2025 · 2025-09

The removal of misfolded, damaged, and regulatory proteins by AAA proteases is essential for maintaining cellular integrity and health across all kingdoms of life. Disruptions in this process can lead to cellular dysfunction and the accumulation of cytotoxic protein aggregates. Mitochondrial protein quality control is particularly crucial, as proteins within the inner membrane and matrix are highly susceptible to oxidative damage. To prevent inappropriate protein degradation, substrate selection by AAA proteases is tightly regulated. It is thought that these enzymes primarily recognize unstructured sequences at the C- or N-termini of target proteins, using ATP hydrolysis to unfold substrates and translocate them into the proteolytic chamber of a peptidase for degradation. Adaptor proteins add an additional regulatory layer by either promoting or inhibiting the degradation of specific substrates. However, the precise mechanisms by which these enzymes maintain substrate specificity, interact with adaptors, and target substrates under different cellular conditions remain poorly understood. This proposal seeks to elucidate the mechanisms of substrate recognition and adaptor mediated degradation by soluble human ClpXP and membrane-bound m-AAA and i-AAA proteases, along with their accessory adaptors. Mutations in these proteases have been linked to various neurological disorders, and human ClpXP (hClpXP) has emerged as a promising therapeutic target in cancer treatment. Despite the high sequence similarity between bacterial and hClpXP, the mechanisms of substrate recognition and adaptor interaction in the human complex remain unclear. The mechanism by which membrane-bound AAA proteases recognize and degrade both soluble and membrane protein substrates is notably murky. To address these gaps, we will employ a multidisciplinary approach, integrating structural biology, biochemical analysis, genetics, and mass spectrometry to understand the mechanisms of substrate specificity and processing by these enzymes. Pulse-labeling mass spectrometry and genetic approaches will be used to identify substrates for each AAA protease and quantify degradation rates in vivo. This will be followed by biochemical reconstitution of a subset of these substrates in degradation assays to identify degron sequences and understand how adaptors influence substrate recognition and degradation by AAA proteases. Finally, we will determine the cryo-EM structures of these complexes, along with their cognate adaptors, in substrate-free and during substrate recognition, recruitment, and unfolding. Given that many aspects of these degradation mechanisms are still not well understood, the MIRA award will allow the Pl to allocate more time and resources to bridging this knowledge gap while also focusing on training and mentoring a diverse group of scientists. This research will offer critical insights into substrate specificity and adaptor-mediated proteolysis, carrying significant implications for both fundamental science and therapeutic advancements.

NSF Awards · FY 2025 · 2025-09

Cosmic particle accelerators are studied through the detection of photons coming from very-high-energy gamma rays. Examples of such accelerators include black holes, neutron stars and supernova explosion remnants. This project will develop and procure 10 cameras. The cameras will be installed on the Small-Sized Telescopes (SST) at the CTAO Southern Array located in Paranal, Chile. The cameras will increase the sensitivity of the CTAO that will become the most sensitive observatory for very-high-energy gamma-rays in the world. The project will contribute to advancing the US scientific leadership in CTAO. It will also provide the opportunity for the US community to access the data collected by CTAO. This initiative will support the training of early-career scientists and students. The SST camera system will enable precise imaging of gamma-ray showers produced by cosmic particles interacting with Earth’s atmosphere. The SST camera will be equipped with fast silicon photo-multiplier sensors and state-of-the-art readout electronics. Increasing the number of SSTs from 5 to 15 will increase the sensitivity of CTAO by over 2.5 times at an energy level of 10 TeV. That will allow unprecedented studies of morphology and spectra of high-energy gamma-ray sources, black holes, and dark matter. This project goals align with the national and international priorities in multi-messenger astrophysics. 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 Approximately half of the four million women who give birth in the United States each year receive oxytocin to induce or augment labor. However, the effective oxytocin dose varies by up to 20-fold, and there is no way to predict individual response. This unpredictability raises safety concerns since oxytocin use is associated with adverse maternal and neonatal outcomes. One way to decrease morbidity associated with oxytocin is to be able to predict individual response and personalize dosing regimens. In order to do this, we need a better understanding of oxytocin receptor (OXTR) function and dynamics. In the previous funding period, we addressed this issue by constructing an initial computational model of oxytocin-OXTR binding using available binding affinity data for the OXTR. We validated this model by showing that it recapitulates the experimentally established oxytocin dose response for oxytocin-OXTR binding in both a heterologous cell line and in a myometrial cell line. However, we were unable to accurately expand our model beyond the initial oxytocin-OXTR complex formation due to a lack of OXTR- and cell-specific kinetic data. In this next phase, our objective is to fill this gap by conducting experimental studies on OXTR to quantitatively define key steps in trafficking of the OXTR in uterine smooth muscle (myometrial) cells, including membrane insertion, internalization, and recycling dynamics. We have substantial published and preliminary data giving us confidence in our ability to achieve our objective. First, we identified OXTR genetic variants that exhibit reduced trafficking and localization to the cell surface and an attenuated response to oxytocin. Second, our rigorous quantitative analyses revealed that only 10% of endogenous OXTR is localized on the cell surface in myometrial cells. Third, we found that, after four hours of oxytocin exposure in vitro, OXTR is degraded rather than recycled to the cell surface, thereby depleting the pool of OXTR available for activation. Finally, we identified several small molecules that act as pharmacologic chaperones to enhance OXTR cell surface localization. Given these data, our central hypothesis is that enhancing OXTR cell-surface localization can improve the efficacy of oxytocin. We propose to test our central hypothesis while conducting rigorous kinetic experiments to discern fundamental principles of OXTR action and develop data-driven, computational models to predict oxytocin responsiveness. We will pursue the following three specific aims: Aim 1: Determine the kinetics of OXTR surface localization and activation in cells, 2) determine the dynamics of OXTR desensitization and recycling in cells, and 3) determine OXTR responsiveness in vivo in mice and ex vivo in human tissues. The research proposal here will obtain experimentally obtained quantitative kinetic data on the OXTR. We will use this to build a computational model to predict OXTR response, which will allow us to better understand the effects of oxytocin signaling on myometrial contractility. Ultimately, this will move us to our ultimate goal of creating a computational model that can be used to improve clinical oxytocin use and obstetric outcomes.

NIH Research Projects · FY 2025 · 2025-09

PROJECT SUMMARY/ABSTRACT The exact process of episodic memory loss in aging and Alzheimer’s disease (AD) is not understood. The long- term goal is to refine our understanding of this process, and its links to pathology in the brain. Critically, our current ways of assessing memory decline are sufficient to detect frank dementia, but are largely insufficient to identify those at risk before significant pathology has already accumulated. In part, this lack of sensitivity stems from the fact that laboratory tests use simplistic, arbitrary stimuli that do not reflect the complexity of the real world. That is, existing cognitive evaluations are limited due to a failure to capture a central feature of human memories: they are not unitary, but rather feature representations of specific content in a structured fashion. These components of memories rely on different brain networks. The objective of this proposal is to determine the way aging distinctly affects the content (Aim 1) and structure (Aim 2) of memory representations, and how this relates to dysfunction in different brain networks based on their susceptibility to AD pathology (via plasma biomarker status, Aim 3). The central hypothesis is that aging will be associated with distinct profiles of memory deficits for event content and structure, linked to unique brain networks. The rationale underlying this proposal is that completion of the project will identify two distinct cognitive and neural targets for characterizing, clinically assessing, and eventually treating AD in at-risk older adults. Our specific aims will test the following hypotheses: (Aim 1) Aging disproportionately affects memory for local perceptual information, such as people and objects, which will coincide with dysfunction in an anterior-temporal brain network. (Aim 2) Older adults will show a shift in brain networks involved in representing event memories and poor differentiation between events compared to younger adults, leading to a bias toward remembering information at a gist-level and a susceptibility to confusion. (Aim 3) Plasma biomarkers will predict the extent of age-related dysfunction in memory networks. Specifically, tau burden will relate to anterior-temporal network dysfunction and memory loss for local perceptual content in memories, whereas amyloid burden will relate to dysfunction in a posterior-medial brain network and more widespread memory deficits related to context and structure. This work uses an innovative combination of novel behavioral testing techniques, as well as cutting-edge brain imaging and plasma proteomic tools. The proposed research makes a significant contribution, because it will provide foundational evidence that memory loss is not a monolith, but rather a nuanced process with different components that are uniquely vulnerable to the presence of pathological biomarkers in AD. Results of this project will have a positive impact on basic research in memory and aging in that they will provide important evidence for the way the human brain supports the content and structure of memories, and how this changes across the lifespan. Moreover, this work will inform future clinical investigations and interventions by refining their targets for understanding and treating specific memory deficits.

NIH Research Projects · FY 2025 · 2025-08

IDH1R132H mutation is recognized as the most common initiating event for low-grade glioma and IDH1- mutant grade IV astrocytoma. Our recent study (Stegh and colleagues, Cell Report, 2017) indicated that wild-type IDH1 (wt-IDH1) is overexpressed in 2/3 of glioblastoma (GBM) that lack IDH1R132H mutation. Both RNAi-mediated knockdown and pharmacological inhibition of wt-IDH1, alone and in combination with radiation therapy, slowed the growth of patient-derived GBM xenografts, while overexpression of wt-IDH1 promoted intracranial HGG growth. Diminished wt-IDH1 activity in GBM tumor cells correlated with reduced α-KG and NADPH levels and was paralleled by enhanced histone methylation, the expression of transcripts associated with cellular differentiation, and weakened defense against oxidative stress. Our analyses of GBM single-cell RNA sequencing (scRNA-Seq) datasets now demonstrate that in addition to GBM tumor cells, wt-IDH1 is also highly expressed in tumor-associated myeloid cells (TAMCs). To determine the role of wt-IDH1 expression in TAMCs, we generated immunocompetent mice with conditional wt-IDH1 gain- (lox-stop-lox wt-IDH1; wt-IHD1LSL) and loss-of-function (floxed wt-IDH1; wt-IDH1L/L). These genetically engineered mice express or delete wt-IDH1 after tamoxifen-induced LysM-creERT2-mediated recombination selectively in the myeloid compartment. The genetic ablation of wt-IDH1 in murine myeloid cells increased their proinflammatory polarization and tumoricidal activity, similar to the pharmacological inhibition of wt-IDH1 using the wt-IDH1-specific and brain-penetrant small molecule inhibitor 13i, developed by AbbVie4. To assess the effects of myeloid wt-IDH1 on glioma growth, we implanted murine tumor cells into tamoxifen-treated LysM-creERT2; IDH1L/L recipient mice or into wild-type recipients that, upon tumor establishment, were treated systemically with 13i. Genetic ablation or pharmacological inhibition of wt-IDH1 promoted inflammatory myeloid phenotypes, increased CD8+ T cells in the TME, as assessed by scRNA- Seq, and resulted in long-term animal survival and anti-tumor memory. Our central hypothesis is that wt-IDH1, through metabolic and epigenetic reprogramming of TAMCs, maintains an immunosuppressive TME and that the pharmacological inhibition of wt-IDH1, using 13i, represents a novel strategy to increase the efficacy of existing immunotherapies for GBM treatment. We will test these hypotheses in two Specific Aims by determining the cellular, epigenomic, and metabolic mechanisms by which wt-IDH1 controls TAMC phenotypes (Aim 1) and by developing treatment regimens combining 13i with prioritized immunotherapies, including inhibitors of PD1 immunosuppressive signaling (Aim 2). Impact: We will define wt-IDH1 as a metabolic checkpoint of myeloid cell activation and credential the pharmacologic inhibition of wt-IDH1 as a novel and safe immunotherapeutic strategy for patients with GBM.

NSF Awards · FY 2025 · 2025-08

Urbanization has remained a dominant global demographic trend since its origins nearly 6,000 years ago. This doctoral dissertation research project examines what factors are most predictive of urbanization, deurbanization, and urban de-nucleation. Much of the archaeological data has focused on sedentary societies in arable river valleys, which yield models of gradual settlement growth and decline largely based on population and agricultural surplus. A larger, more varied dataset is necessary to get a clearer archaeological understanding of more rapid trajectories toward urbanization and deurbanization among non-farming societies. A crucial component of this research involves using satellite imagery to identify and map small non-urban settlements surrounding known urban sites. In doing so, this project will help to develop U.S. geospatial research capabilities by refining and publishing open-source and reproducible methodologies on a large satellite image dataset. This effort will provide students with valuable training in geospatial methods. This project responds to research priorities in the science of artificial intelligence through the study and usage of computers and software through the development satellite imagery-based machine learning and other deep learning models. To better understand the social and environmental factors surrounding urbanization and deurbanization, it is necessary to determine functional differences between large central settlements and the smaller sites in their peripheries. The investigators use satellite image surveys coupled with systematic soil coring to 1) investigate two settlements in a period of technological development and 2) identify alternative sites in the peripheries of these two sites. Preliminary investigations suggest that metallurgic production may have played a crucial role in the formation of large, fortified pastoralist settlements in this region; therefore, the investigators analyze soil chemistry to find traces of metallurgical activity in both urban and non-urban settlements. These soil cores provide artifacts and organic materials for radiocarbon dating, allowing the investigators to establish a chronology; thereby determining if urban sites were surrounded by smaller contemporary sites that provisioned them with food or metallurgical resources, and illustrating how/when these landscapes were abandoned. These data will help the investigators explore hypotheses to explain the formation and dissolution of pastoralist urban landscapes. 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.