University Of Iowa

NIH Research Projects · FY 2026 · 2026-02

PROJECT SUMMARY Chronic infections caused by persistent viruses or parasites impose a significant burden on human health and healthcare systems. These infections disrupt immune responses, often leading to T cell dysfunction, immune exhaustion, and loss of T cell memory potential. CD4+ T cells are central to immune defense against chronic infections, yet their differentiation and functional responses differ significantly from those in acute infections. During chronic infection, CD4+ T cells exhibit reduced pro-inflammatory cytokine production, increased expression of immunoregulatory molecules, and functional adaptations such as the differentiation of T follicular helper (TFH) cell, which produce IL-10 and IL-21 production to support germinal center B cell responses and humoral immunity. Despite progress in understanding TFH and T helper type 1 (TH1) cell differentiation, the molecular mechanisms regulating CD4+ T cell fate during chronic infections remain poorly defined. We recently identified tumor necrosis factor receptor-associated factor 3 (TRAF3) as a key regulator of TFH differentiation during acute infection. Our preliminary data indicate that TRAF3 modulates TFH cell fate by regulating cytokine responsiveness, lineage- specific transcription factors like BCL6, and chromatin accessibility at key TFH and TH1 lineage gene loci. Notably, we also observed nuclear localization of TRAF3, suggesting a previously unrecognized role in transcriptional and epigenetic regulation. This proposal employs technically innovative and high-resolution approaches, leveraging complementary experimental systems of chronic infection and robust single-cell technologies to dissect how TRAF3 integrates T cell receptor, cytokine, and co-stimulatory signals to regulate TFH, TH1, and memory-like CD4+ T cell differentiation. Using cutting-edge genomic and epigenetic approaches, including single-cell RNA sequencing (scRNA-seq), ATAC-seq, CRISPR/Cas9-mediated gene editing, and retroviral-mediated genetic manipulation, we will define how TRAF3 orchestrates transcriptional programs, chromatin accessibility and nuclear regulatory network to fine-tune immune responses. Given TRAF3’s implication in autoimmune disorders and malignancies, uncovering its role in chronic infection may inform new therapeutic strategies to modulate T cell responses in infection, vaccination, and autoimmunity. By linking TRAF3’s cytoplasmic signaling functions with its nuclear roles, this study aims to provide conceptual advances that could pave the way for novel strategies to enhance immunity and control inflammation in human health.

NSF Awards · FY 2026 · 2026-01

This award is funded in whole or in part under the American Rescue Plan Act of 2021 (Public Law 117-2). The Faculty Early Career Development (CAREER) Program is a National Science Foundation-wide activity that offers awards in support of early-career faculty who can serve as academic role models in research and education and lead advances in the mission of their department or organization. Chemists have played a significant role in solving some of the world's greatest issues and improving the quality of life for all people. Often, this requires that chemists be trained with advanced skills and knowledge only achievable through the completion of a doctoral degree program (Ph.D.). Significant concerns have been raised both inside and out of the chemistry community related to the ability of American chemistry doctoral programs to prepare their students effectively for future careers and scientific endeavors. These shortcomings in doctoral training indicate that the current system is training chemists whose preparation to tackle the world's next grand challenges could be improved. As such, this project will investigate the training of doctoral chemistry students from the faculty perspective to complement existing research that describes student perspectives. The elements used to progress a student from beginning to end of the Ph.D. program are well-known and homogeneous. This project will unearth the specific rationale for how these elements are supposed to develop an independent scientist and identify the specific roles faculty advisors play. Additionally, funding for this project will be used to prompt significant reforms in the graduate programs in five chemistry departments. It is expected that all chemistry graduate programs will gain access to resources that guide potential reforms through this project. These reforms are expected to improve the quality of scientists produced by chemistry doctoral programs for the betterment of society. Three objectives guide this project. The first will build a model that describes how the Ph.D. student develops into an independent scientist based on faculty advisors' stated goals and learning outcomes. Chemistry faculty will be interviewed to discover each core element's role(s) in a typical chemistry doctoral program. From thematic analyses, a model of doctoral education will be constructed and modified/validated by chemistry faculty. Activities in Objective 2 will discover the chemistry faculty's specific values and beliefs pertaining to the training of doctoral chemistry students. This important research will reveal the faculty advisors' goals, roles, and identities and how they affect the training chemistry doctoral students receive. These beliefs are expected to be heavily influential in the practices that are observed in doctoral education. Finally, Objective 3 will develop resources that outline the primary issues with current Ph.D. training and what reforms have been suggested to mitigate them. These resources will be distributed to all chemistry graduate programs across the country. Additionally, the PI will work closely with five specific chemistry departments with the explicit aim of achieving tangible reform in how each trains chemistry doctoral students. This attempt to engage in specific reform aims to produce a generation of chemists that are more prepared for the challenges they will face in their 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 2026 · 2026-01

Project Summary Metabolic Syndrome (MetS) affects over one-third of U.S. adults and is closely linked with oral health issues, particularly periodontitis. The bidirectional relationship between MetS and periodontitis exacerbates both conditions, but the underlying mechanisms remain unclear. Our preliminary R03 data indicate that MetS alters the oral microbiome, creating an ‘at-risk-for-harm’ environment even in the absence of clinical periodontal disease. This project aims to elucidate these mechanisms through a longitudinal systems biology approach, focusing on how restoring metabolic health impacts the functional oral ecosystem. We hypothesize that improved metabolic health will shift the oral microbiome towards a eubiotic state, reduce pathogenic strains, and alter the metabolome to a less inflammatory profile. We test our hypothesis in the following specific aims. In Specific Aim 1: We will track the oral microbiome's temporal dynamics in MetS and Metabolically Healthy Obese (MHO) cohorts undergoing lifestyle or surgical interventions, comparing them with healthy and periodontal disease cohorts. In Specific Aim 2: We will analyze changes in the oral metabolome post-metabolic intervention using advanced mass spectrometry techniques. In Specific Aim 3: We aim to identify and validate oral biomarkers and risk indicators linked to metabolic health improvements. This study will use a causal mediation framework to explore direct and indirect effects, providing crucial insights into the MetS-periodontal health relationship and aiding in the development of prognostic biomarkers and risk indicators in the future.

NSF Awards · FY 2026 · 2026-01

The Earth’s rock record preserves a substantial fraction of its history, attesting to our planet’s unique and complex systems from which tectonics, minerals, climate, and life have emerged. The Geological Time Scale (GTS) is the authoritative calendar of Earth’s history that has resulted from centuries of observation and quantification of this rock record, and which serves as a foundation for research and innovation in Earth systems science. However, the process of GTS construction and revision has yet to evolve into an open science structure that can harness the full energy and potential of the scientific community. This project will build robust connections among disciplinary scientists, data resources, and community organizations to create a new framework of open science GTS construction. The goals of this project are to bring together scientists to: a) discover and translate the existing data, metadata, and algorithms behind the GTS, in order to establish future community-sourced best practices for dynamic time scale construction; b) plan the design of a findable, accessible, interoperable, and reusable (FAIR) data system that leverages and adapts existing standard data formats and open source software into a community-accessible system; and c) explore how these data and algorithms can be best exposed through public-facing online tools that allow visualization and experimentation with the GTS. By engaging and coordinating an open community to lay the groundwork for production of the GTS within a public-facing system, the Open Science GTS will enable input and participation from all scientists, thus accelerating the amount and quality of data that can be compiled into the GTS and increasing its responsiveness to community needs across geoscience disciplines. 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 · 2025-11

PROJECT SUMMARY Stroke commonly disrupts the corticospinal tract (CST) and impairs hand function. Transcranial magnetic stimulation (TMS) interventions that target and strengthen residual CST connections are promising candidates for improving poststroke hand function. To maximize their therapeutic effects, such interventions must repeatedly activate the residual CST and enhance its neural transmission. We and others recently showed in neurotypical adults that resting brain activity spontaneously alternates between EEG activity patterns (brain states) that predict strong and weak CST activation. TMS interventions also preferentially enhance CST transmission when delivered during strong CST states but instead diminish CST transmission when delivered during weak CST states. However, virtually all poststroke TMS interventions are uncoupled from the current brain state, such that only a fraction of TMS stimuli coincide with brain states during which the beneficial effects of TMS are likely to be strongest. To resolve this issue, poststroke TMS interventions should be delivered solely during brain states reflecting strong CST responses. Given that each stroke survivor has a unique pattern of brain damage and recovery-related brain reorganization, these brain states must be fully personalized. We recently developed a personalized machine learning framework that successfully identifies electroencephalography (EEG) activity patterns that predict strong and weak CST states in neurotypical adults. Our framework is fully personalized and is therefore unaffected by lesion-related changes in brain structure and/or function, making it ideal for application in the poststroke brain. In this project, we will use this framework to establish the mechanistic rationale and methodological foundation for future personalized brain state-dependent TMS interventions that target and strengthen the residual CST after stroke. In Aim 1, we will use our machine learning framework to identify personalized brain states that predict strong and weak residual CST activation in chronic stroke survivors; we will also evaluate relationships between our framework’s performance and functional and structural metrics of poststroke CST pathway integrity. Results of Aim 1 will establish poststroke brain state-dependency of residual CST output and the relationship of this state-dependency to CST integrity. In Aim 2, we will develop and validate a real-time EEG algorithm that accurately delivers TMS during personalized brain states reflecting strong and weak CST activation in neurotypical adults. Results from Aim 2 will demonstrate the technical feasibility of personalized, real-time brain state-dependent TMS. Overall, this project fits the scope of the NIMH/NINDS R21 mechanism because it will develop a novel neuroengineering approach that can in the future enhance residual CST transmission and promote paretic hand function in stroke survivors.

NSF Awards · FY 2025 · 2025-10

Today, Europe is leading the way in developing laws to manage the increasing range of harm that artificial intelligence (AI) can and does create. Europe's AI Act focuses on regulating how its businesses develop and use AI. Many experts worry that this heavy-handed intervention into private enterprise will stifle AI innovation, including, ironically, innovations that could ultimately make European citizens safer. The United States urgently needs its own legal approach for managing AI harms. This project's novelty lies in developing an objective standard for deciding who is at fault after an AI harm occurs. This approach avoids Europe's tussle between law and computing because an after-the-harm standard does not directly interfere with business operations. Rather, it provides businesses the space to innovate and the incentive to figure out how best to design accountable software systems that minimize avoidable AI harms. The objective of this project is to bring accountability for AI without impeding the businesses' and researchers' ability to continually innovate and lead in AI. To do so, this project aims to design an objective-fault standard for AI that does not prohibit or censure any AI behavior outright but instead compares AI’s behavior with an external negligence benchmark. Then, by calibrating the benchmark’s standard to the social value and the current safety profile of the AI conduct at issue, the AI law could be applied flexibly, progressively, and across broad domains. The researchers plan to attain this objective by (i) laying the legal foundation for a negligence standard for AI, (ii) developing AI negligence benchmarks for three representative applications, and (iii) evaluating this new standard against the European AI Act. Upon completion, this research would support establishing a distinctly American alternative to the European style AI regulation. 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 project develops new foundations for machine-verified proof in programming languages and mathematics. Formalized libraries of mathematics enable increased confidence in the correctness of proven results, large-scale collaboration on future results, and a database of relevant facts for automated reasoning. However, reuse of formalized proofs and proof components is made difficult by language limitations within theorem provers and incompatible choices between theorem provers. The project's novelty is a new foundational technique based on type theory, with formal tools for proof modularity and reuse at its core. The project's impacts are increased sharing among formalization efforts and a basis for more effectively exploring new proof theoretic foundations for mechanized theorem proving. The project will also train graduate students. The project's core contribution is a new impredicative dependent row type theory. Impredicativity captures expressive features of modern dependently typed languages, like induction-recursion, without further extension. Proof reuse is enabled by row types, used to describe extensible variants and extensible dependent records. Both object logics and constructs within them will be expressed extensible, automatically extending proof terms over simpler objects in smaller logics to apply to more complex terms in larger logics. For example, constructive proofs on groups can automatically be used as classical proofs on fields. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NSF Awards · FY 2025 · 2025-10

This project advances national health and promotes science and technology development by providing algorithms, software, and systems that can train machine learning models on electronic health records (EHRs) for accurate and early prediction of Alzheimer’s Disease and Related Dementias (ADRD). ADRD is a severe neurodegenerative disorder that effects over 5,000,000 people over the age of 65 that is characterized by progressive memory, cognitive impairment and personality changes, which can further evolve to dementia and death. Early prediction of ADRD is crucial for timely intervention and improved patient outcomes. Recent studies have shown that personal risk factors such as education, employment, and lifestyle or family history significantly influence ADRD onset and progression. However, these factors are not recorded in a structured format within the existing EHRs. In contrast, personal risk factors are often embedded within the free text of clinical notes or discharge summaries that are not easily searchable, computable, or standardized. This creates a major technical barrier for their integration into the ADRD prediction models. To address this, this project develops a computational platform using novel machine learning and natural language processing to automatically extract personal risk factors from EHR clinical narratives and leverage them for accurate and early prediction of ADRD. This research significantly improves ADRD prediction accuracy and timeliness, with potential generalizations to other neurological disorders. By exploring the interaction between personal and clinical factors in disease development, this project pushes the boundaries of current knowledge in machine learning and ADRD research, potentially transforming approaches to early detection and management of complex neurological disorders. To achieve the goal of developing personal risk factor enhanced machine learning models for early ADRD prediction, this project develops four thrusts of novel approaches, each addressing key methodological challenges. First, the project develops a domain knowledge guided large language model to extract risk factors from EHR clinical narratives, which can adeptly cope with the complexities inherent in real world EHR clinical narratives, such as noise and incomplete data entries. Second, the project develops an interpretable method using neural additive models that automatically identifies the individual risk factor’s contribution to the early ADRD prediction. Building upon this interpretable result, in the third thrust, the project develops a survival-based ADRD prognosis model that can be used to estimate the likelihood of ADRD development at any given point in the future, capturing the dynamics of risk trajectory. This approach can enhance clinical decision-making by identifying high-risk individuals who may benefit from more intensive care or early intervention. Fourth, this project constructs a personalized knowledge graph that integrates personal and other clinical risk factors into a unified format for capturing the overall health status for everyone at risk of developing ADRD. Moreover, this project develops adaptive machine learning algorithms that can dynamically update this knowledge graph to incorporate the evolving risk factors. Together, these approaches converge to address the fundamental limitations of existing ADRD risk prediction models, such as inability to handle complex and unstructured data, insufficient interpretability, and high computational overhead. 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: The fight-or-flight response is a critical regulator of heart function and major target of cardiovascular therapeutics for heart failure, arrhythmias, and ischemic heart disease. In response to stress, catecholamines released by the sympathetic nervous system stimulate β-adrenergic receptors on cardiomyocytes, resulting in increased heart rate and contractility. Although existing medications targeting upstream components of this pathway are effective therapeutics for cardiovascular disease, they often cause undesirable non-cardiac side effects. Rad, a small RGK-family GTPase and calcium channel inhibitor protein, has emerged as a downstream mediator of β-adrenergic signaling and a promising target for cardiac-specific therapeutics. In response to β-adrenergic stimulation, Rad is phosphorylated by protein kinase A (PKA), resulting in disinhibition of Cav1.2 and an increase in the L-type calcium current responsible for excitation-contraction coupling. However, the molecular mechanism by which Rad phosphorylation results in Cav1.2 current enhancement remains poorly understood. The objective of this proposal is to elucidate the physiological significance of Rad phosphorylation in regulating Cav1.2 function in the cardiac fight-or-flight response to inform the development of novel cardiac-specific therapeutics. To do this, we propose an innovative approach combining chemical biology and electrophysiology to achieve precise temporal and spatial control of Rad phosphorylation. By encoding the unnatural amino acid caged-serine, a derivative of serine that is “decaged” to natural serine by a brief pulse of near-UV light, at phosphorylation sites S273 and S301, we will achieve real-time, site-specific, light-mediated control of Rad phosphorylation during electrophysiological recordings of Cav1.2 currents. In Aim 1, we will employ a heterologous cell culture system to quantify the distinct contributions of S273 and S301 phosphorylation to Cav1.2 current enhancement upon forskolin-induced PKA activation. In Aim 2, we extend these studies to ex vivo cardiomyocytes isolated from Rad-knockout mice, enabling us to examine Rad phosphorylation in the context of native cardiac β-adrenergic signaling pathways. By elucidating the molecular mechanisms of Rad-mediated Cav1.2 regulation, this study will offer critical insights into the cardiac β-adrenergic response. These findings will lay the foundation for developing next- generation, cardiac-specific therapies targeting Rad phosphorylation for the treatment of cardiovascular diseases. The successful completion of this work will provide comprehensive training in biomedical research techniques, supporting the fellowship applicant's long-term goal of achieving a career as a physician-scientist dedicated to advancing the understanding and treatment of cardiovascular disorders.

NIH Research Projects · FY 2025 · 2025-09

PROJECT SUMMARY The human brain's ability to learn and execute behaviors tailored to environmental contingencies is crucial for adaptive cognition. Central to this capacity are neural representations of context, which organize the associations between sensory features and behavior utility. Despite their significance, the neural mechanisms underlying the encoding and updating of context representations remain poorly understood. This gap in knowledge is particularly relevant for understanding cognitive deficits in psychiatric disorders such as schizophrenia and ADHD. Our research proposes to test the hypothesis that the human mediodorsal (MD) thalamus is critical for encoding, updating, and generalizing context representations. This hypothesis is grounded in empirical and theoretical contributions from our team, suggesting the MD thalamus's essential role in context-guided cognitive control and flexibility. Our previous studies have shown that damage to the MD thalamus impairs task switching and working memory in humans, consistent with findings from non-human animal models. Additionally, single- unit recordings in animals reveal that MD neurons rapidly encode task context, a process dependent on the convergence of prefrontal afferents. Preliminary fMRI data from our labs indicate that the human MD thalamus tracks task context and its updates following switches. However, a critical gap exists in interpreting these results due to the lack of quantitative models and advanced neuroimaging approaches to delineate the specific representations and computations carried out by the human MD. To address this gap, we will use a computational cognitive neuroscience approach, integrating computational models with high-resolution 7T MRI and advanced neuroimaging analyses. Our research has three specific Aims. In Aim 1, we will ask whether the MD thalamus encodes context representations that organizes how working memory guides task selection. In Aim 2, we will ask whether the MD encodes context prediction errors that switch prefrontal task representations flexibly. In Aim 3, we will ask whether MD context representations enable generalization to novel stimulus- response contingencies during decision-making. For all aims, we will develop computational models that specify both cognitive processes and neural implementations to predict behavior and guide neuroimaging data analyses. This collaborative effort between the MPIs aims to establish a new conceptual and empirical framework for understanding thalamic computation in humans, with significant implications for theories of cognitive control, adaptive human behavior, and cognitive dysfunction.

NIH Research Projects · FY 2025 · 2025-09

Abstract Misfolded/dysfunctional cystic fibrosis transmembrane conductance regulator (CFTR) protein causes multiple health related issues including lung disease and diabetes in cystic fibrosis (CF). Scientific advancements have significantly prolonged the life span of CF patients. But aging promotes endothelial dysfunction. Importantly, CF patients are known to have impaired endothelial function. Therefore, it is likely that endothelial dysfunction will worsen with age in CF patients. However, how CFTR regulates endothelial function and thereby vascular tone is not known. It is not known whether CFTR modulators are effective against CF-associated endothelial dysfunction. Therefore, it is important to understand the significance of CFTR in endothelial function and to assess the impact of aging on endothelial function in CF patients. Our preliminary data suggests that like CF patients, deletion of CFTR or expression of dysfunctional CFTR exhibit impairment of endothelium-dependent relaxation of coronary arteries in pigs. Even acute pharmacological inhibition of CFTR in mice aortic rings leads to endothelial dysfunction. We have also noted that genetic deletion of CFTR or pharmacological inhibition of CFTR downregulates endothelial nitric oxide synthase (eNOS) expression in endothelial cells. As aging promotes endothelial dysfunction and downregulation of eNOS levels, we propose to evaluate the changes in endothelial function and examine the mechanism involved in CFTR-mediated regulation of NO production with aging. We will use a novel mouse model of CF disease with endothelial deletion of CFTR (e-CFTR-/-) to determine: 1) whether aging-induced endothelial dysfunction accelerates with endothelial deletion of CFTR and 2) the eNOS- CFTR regulation as a mechanism mediating the CFTR-dependent regulation of endothelial function. We will examine vascular function in aged mice having endothelial deletion of CFTR. We will also use cell biology-based assays to determine the functional changes in the endothelial cells due to CFTR and possible ways to modulate such effect. This study will demonstrate the impact of aging on endothelial dysfunction due to loss of CFTR function.

NIH Research Projects · FY 2025 · 2025-09

Hybridoma technology has been critically important for biomedical research, allowing reproducible and scalable production of monoclonal antibodies for research and pharmaceutical development. Traditionally, hybridomas require cryopreservation and specialized cell culture expertise to reproducibly produce the monoclonal antibodies. These processes are also laborious, limiting the amount of antibody or hybridoma cell line that can be shared by the inventor scientist. The Developmental Studies Hybridoma Bank (DSHB) was established under the auspices of the NIH/NICHD in 1986 for the express purpose of facilitating the open sharing of hybridomas and the monoclonal antibodies they produce. Since 1997, when DSHB became fully housed within the Biology Department at the University of Iowa (UI), this international resource has provided hybridomas and antibodies to thousands of institutions and many more investigators, at highly affordable prices. However, DSHB has lacked a centralized facility, its main operations being scattered in different parts of the Biology Department. DSHB is also now outgrowing existing production, storage, and order processing capacity. Further, because the amount of information needed for researchers to make the best-informed antibody choices for their work has grown, it is necessary for DSHB personnel to increasingly collaborate to develop our antibody knowledgebase. This proposal aims to construct a unified, more efficient research facility to consolidate DSHB in renovated space within the Department of Biology on the University of Iowa campus. This facility will allow for expanded production capacity and storage while optimizing workflow, improving environmental considerations, and ensuring future scalability for the business operations. The DSHB Facility will contain state-of-the-art equipment for producing monoclonal antibodies, including recombinant mAbs, at many different scales, as well as upgraded, secure cryostorage capabilities for hybridoma cell lines. Lab research space will accommodate ongoing high-throughput sequencing and creation of recombinant antibodies, and for validation of antibodies using knockout cells. Office space will be placed in proximity to the production and research areas, allowing for more efficient communication and better spontaneous interactions between units. Overall, the strategic goals of DSHB to provide researchers with a comprehensive antibody collection with an associated knowledgebase and to grow additional services, such as recombinant antibody distribution, will be greatly facilitated by consolidating the currently dispersed and inefficient operation sites into a single facility. Considering the constant level of self-sustained success of DSHB under less-than-ideal circumstances, matching the DSHB facilities with the staff's expertise and dedication can only improve DSHB's trajectory, ultimately to the benefit of researchers everywhere.

NIH Research Projects · FY 2026 · 2025-09

Project Summary Over 10% of infants are born preterm (gestational age < 37 weeks), and these rates are on the rise. Preterm-born (PTB) children face an increased risk of academic difficulties compared to Term peers, with specific and persistent difficulties in mathematical development. Success in math is consequential – higher math skill predicts greater school success, wealth, health, and life satisfaction. Despite their prevalence and importance, however, the underlying mechanisms of math difficulties in PTB children remain poorly understood. The goal of this project is to pinpoint the mechanisms that underlie mathematical difficulties in PTB children during the transition to formal schooling. Our central hypothesis is that early mathematical difficulties arise from cascading effects of prematurity on foundational verbal skills that affect specialization of critical neural systems and in turn lead to difficulties in numerical performance, and that these difficulties can be offset by an enriched home environment. The rationale is that better understanding of the mechanisms of PTB children’s math difficulties will improve early identification and intervention efforts, ultimately improving academic outcomes and decreasing societal financial burdens. The central hypothesis will be tested by pursuing two specific aims: 1) Test a serial mediation model that links gestational age to numerical skill through verbal skills and neural systems, and 2) Determine the role of the home verbal environment as a moderator of the link between prematurity and numerical skills. These aims will be pursued through an accelerated longitudinal study of 240 children from diverse backgrounds across the full spectrum of gestational age (23-41 weeks gestational age at birth). We will administer standardized and lab-based measures to assess numerical, verbal, and spatial skills throughout the pivotal transition to formal schooling (pre-K to 1st grade). We will measure brain activity during numerical processing using functional near-infrared spectroscopy (fNIRS). We will assess home environment via parent-child lab observations and questionnaires. Key covariates, including pregnancy factors (e.g., birth complications) and child characteristics (e.g., medical morbidities, sex, executive function) will be considered. The proposed research is innovative, in the applicant’s opinion, because it represents a substantive departure from the status quo by integrating multiple levels of analysis (environmental, behavioral and neural), leveraging a wide range of neuroimaging, behavioral, and observational measures, assessing a broad spectrum of early numerical skills during the significant transition to formal schooling, and incorporating the full spectrum of gestational age. The proposal is significant as it will provide the conceptual foundation for much-needed and effective early prevention and intervention efforts that leverage neural markers and home support to prevent mathematical difficulties in at-risk PTB children and thereby maximize their future potential.

NSF Awards · FY 2025 · 2025-09

The Geospace Environment Modeling (GEM) Workshops provide a uniquely valuable platform for community-driven collaborative research that complements traditional scientific conferences. The structure of GEM permits the identification of shared goals, the formulation of a path to address these goals, and the opportunity to make sustained and measurable progress towards them. This project will offer travel funds and mentoring programs to support scientists in the earliest stages of their career to successfully attend GEM, helping to ensure access for participants from all institutions, and the opportunity for participants to form invaluable connections to the community, develop the skills to succeed as a scientist, and form collaborations and connections with researchers from academia, national labs, and government agencies. Furthermore, GEM science contributes to the understanding and prediction of extreme space weather events, which is crucial for safeguarding humans and hardware in space, aircraft and passengers operating on polar routes, communication networks, and power infrastructure. By supporting scientific advances in space weather, the GEM Workshop serves the public interest and contributes to national resilience, economic security, and technological competitiveness. This project supports organizing the annual GEM workshop for a three-year term from 2026 through 2028. There are 5 Research Areas that make up the GEM Workshop, each focusing on particular aspects of the geospace environment: 1) Solar Wind - Magnetosphere Interaction (SWMI); 2) Magnetotail and Plasma Sheet (MPS); 3) Inner MAGnetosphere (IMAG); 4) Magnetosphere – Ionosphere Coupling (MIC); and 5) Global System Modeling (GSM). By collaboratively addressing the complex and coupled solar wind-magnetosphere-ionosphere-ground coupled system, the GEM Workshop supports NSF's goals for addressing grand scientific challenges through integrative approaches. The GEM Workshop plays a vital role in cultivating an open and collaborative scientific community and expanding opportunities for participation in science and engineering for all Americans. 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 Gene therapies for heritable eye disorders are being developed at an unprecedented rate, but the immune response, despite being a known reaction to gene therapies, is poorly characterized. Side effects to ocular gene therapies do not affect individuals to the same degree clinically, despite receiving similar dosing and treatments, underscoring the need for understanding subject-specific risk. In this proposal, I will 1) determine the effect of immunosuppression on toxicity risks after intraocular gene therapy, 2) discover genetic variants that modify susceptibility to gene therapy-related toxicity, and 3) test if subject-specific risks can be estimated before treatment using blood. Genotype-phenotype correlations will be performed to map genetic loci associated with toxicity phenotypes in mice with a diverse genetic background. To estimate risk specific to an individual animal, biomarkers in blood will be measured and analyzed by machine learning. The overall objective of the research is to use subject-specific characteristics to predict and mitigate toxicity risks. The long-term goal is to achieve precision medicine via individualized risk assessment for ocular and for all gene therapies. Though the proposed research uses mice as a model organism, the outcomes are highly clinically relevant and have immense potential for making a positive clinical impact. The proposed work will advance personalized design and optimization of ocular gene therapies.

NIH Research Projects · FY 2025 · 2025-09

PROJECT SUMMARY / ABSTRACT Cardiac fibrosis is a wound healing response to heart injury that plays a critical role in structural and electrical remodeling of the heart. It is a common feature in most heart diseases, particularly following ischemic events like myocardial infarction (MI). Cardiac fibroblasts (CFs), the prominent nonmyocyte population in heart tissue, are important for maintaining normal cardiac function, facilitating wound healing, and mediating remodeling after injury. CFs proliferate and migrate to the affected areas, where they deposit excess extracellular matrix proteins to aid in tissue repair. Calcium (Ca2+) signaling is pivotal in regulating key aspects of fibroblast biology, including migration, differentiation, and gene expression. However, the mechanisms that establish Ca2+ homeostasis in CFs and their role in cardiac fibrotic remodeling remain poorly understood. In pilot studies, we found, Junctophilin-2 (JP2), a structural protein crucial for organizing the junctional couplings between the T-tubule plasma membrane and the sarcoplasmic reticulum (SR) in cardiomyocytes, is uniquely expressed in CFs and is vital for maintaining their Ca2+ homeostasis. Further work suggests that JP2 deficiency in CFs impairs scar formation and exacerbates heart function after MI, likely due to impaired Ca2+ regulation. Based on these preliminary findings, we hypothesize that JP2-mediated Ca2+ signaling is essential for CF responses to ischemic challenges and that defects in this signaling pathway contribute to aberrant fibrotic remodeling following injury. This project will employ advanced molecular, physiological, and biochemical techniques, along with innovative mouse models, to investigate the specific mechanisms through which JP2 influences CFs and its role in injury- induced cardiac fibrosis. The anticipated outcomes of this research include providing novel knowledge on JP2's physiological and pathophysiological functions in CFs, shedding light on the mechanisms driving cardiac fibrosis and heart dysfunction after injury. Ultimately, these insights may pave the way for the development of new treatments targeting cardiac fibrotic process and improving heart health outcomes.

NIH Research Projects · FY 2025 · 2025-09

Project Summary/Abstract Adolescents are particularly vulnerable to HIV and AIDS globally, including Kenya. In western Kenya, youth are disproportionately affected by HIV due to poverty and lack of education, which can lead to risky sexual behav- iors. Stigma is one of the primary barriers to HIV prevention among youth in Kenya. Our prior research in west- ern Kenya demonstrates that HIV-related stigma among youth is associated with lower odds of condom use and HIV testing, and stigma associated with sexual and reproductive health (SRH) also impacts HIV outcomes. Further, we found that social capital is protective against stigma, and youth are comfortable talking about sex and HIV in trusted groups of peers. However, youth lack skills and confidence to talk to adults and partners about HIV. Therefore, there is a critical need to strengthen young people’s resilience by improving communica- tion and building social capital, which will reduce HIV- and SRH-related stigma and increase HIV prevention in western Kenya. We will use implementation science methods to adapt a theory-based, evidence-informed in- tervention, Sisters Saving Sisters (SSS), in 4 important ways: (1) develop a version for boys (Brothers Saving Brothers [BSB]), (2) develop content on HIV- and SRH-related stigma, (3) add content PrEP and HIV testing; and (4) create content to improve communication between youth and their parents/caregivers. We hypothesize that our adapted intervention (SSS and BSB) will reduce HIV- and SRH-related stigma and increase HIV pre- ventive behaviors among youth in western Kenya. This study will take place in Kakamega County and will build upon an established partnership between the University of Iowa and Africa Community Leadership and Devel- opment to address the following specific aims: (1) Adapt SSS to reflect the experiences and perspectives of youth (ages 15-18) in western Kenya; (2) Determine the preliminary effectiveness of the adapted SSS and BSB intervention; and (3) Evaluate the feasibility, appropriateness, and acceptability of the adapted SSS and BSB intervention. For Aim 1, we will use the ADAPT-ITT framework to adapt and contextualize SSS by using theater testing and focus group discussions (FGDs) with our Youth Action Team (YAT) and Community Leader- ship Team (CLT). For Aim 2, we will implement a pilot randomized control trial by randomly assigning 3 villages each to the intervention and control. In each intervention village, separate groups of girls and boys (n=96) will receive the intervention over 3 weeks. In the control villages, youth (n=96) will receive the standard of care for HIV prevention and SRH. We will assess outcomes before the intervention, and at 3- and 6-months post-inter- vention. Primary outcomes are abstinence, condom use, PrEP use, and HIV testing; secondary outcomes in- clude behavioral intentions and HIV- and SRH-related stigma. For Aim 3, we will use an implementation sci- ence approach to assess acceptability, appropriateness, and feasibility through short surveys and FGDs with participants, parents/caregivers, peer educators, and YAT/CLT members. At the end of this project, we expect to have 2 curricula that will set the stage for a rigorous hybrid effectiveness-implementation study in Kenya.

NIH Research Projects · FY 2025 · 2025-09

PROJECT SUMMARY/ABSTRACT Lower urinary tract symptoms (LUTS) are common and have a significant negative impact on the lives of adult men and women. The Symptoms of Lower Urinary Tract Dysfunction Research Network (LURN) was formed in 2012 to address research gaps related to the care of patients with LUTS. The long-term goals of the University of Iowa LURN Research Site are to better treat and prevent lower urinary tract dysfunction in men and women. Toward this goal, additional research is required to better characterize and understand clinically-useful LUTS patient subtypes and to better measure the full patient experience related to the broad range of LUTS. The Iowa Research Site thus proposes to perform multicenter and multidisciplinary research with other LURN sites to 1) Test and refine LURN symptom-based clusters including a wider range of symptom severity and a wider range of physiological measures than performed in prior studies, 2) Assess the relationship between physical activity and sleep (important non-urologic factors related to LUTS) and LUTS and LUTS treatment response, 3) Determine phenotypic characteristics of women with LUTS by measuring the functional components via urodynamic testing, 4) Identify protein biomarker signatures contained within plasma of specific subgroups of men and women with LUTS, and 5) Validate a comprehensive outcome tool for men and women with LUTS. To address these aims, several distinct but complementary studies are proposed. LURN will perform a 3-year cohort study of men and women with a diverse spectrum of LUTS severity and characterize them with standardized clinical evaluations, self-reported symptoms and associated conditions, quality of life, voiding diaries and detailed information on treatments and treatment response over time. Wearable health tracking devices and smartphone text messaging technologies will be utilized to collect objective physical activity and sleep quality data from cohort study participants. Additionally, participants will complete the LURN Comprehensive Assessment of Self-Reported Urinary Symptoms – Outcome Measure (CASUS-OM) to test its internal consistency, validity and responsiveness to change after LUTS treatments. In another study, women with urgency and urgency urinary incontinence will undergo a battery of standardized urodynamic tests focused on sensory and motor functions of the urethra and bladder. Lastly, analysis of protein biomarker signatures will be performed, using plasma samples previously collected from men and women with LUTS. Important findings from these significant LURN research efforts will help improve the clinical care of LUTS patients and will inform the development of future LUTS clinical studies.

NSF Awards · FY 2025 · 2025-09

An award is made to the University of Iowa Museum of Natural History for a collections curation and access initiative to preserve, digitize, and increase research capacity for more than 140,000 invertebrate specimens. These collections span over 150 years of biodiversity records from Iowa, the Midwest, and beyond, and provide essential data for comparative analysis on environmental change, land use, and species distribution. A centerpiece of the project is the integration of the Iowa Insect Survey collection—approximately 50,000 specimens collected from all 99 Iowa counties between the 1920s and 1960s—rescued from the former Iowa Wesleyan University. To secure these irreplaceable and viable research specimens, the project will consolidate specimens and replace hazardous wooden cabinets and failing drawers with modern, sealed steel cabinetry mounted on compactor carriages in an environmentally controlled facility. During the rehousing process, specimens will be cataloged, photographed, and made digitally accessible through biodiversity data portals. The project will provide paid internships and hands-on training for undergraduate students. Other broader public impacts include the development of a new educational exhibition and outreach programming focused on the ecological roles of insects in Iowa, engaging visitors of all ages. This effort secures and activates one of the Midwest’s most comprehensive historical invertebrate collections for ongoing and future research. By addressing serious storage hazards and consolidating materials in a centralized location, the project supports studies on invasive species, habitat and climate impacts, water quality, and regional biodiversity trends. Digitization of specimen records and images will support both local and international scientific access, while new storage infrastructure will allow for the sustainable growth of the collections as a state repository. The project strengthens biodiversity literacy, provides applied training in museum careers, and preserves Iowa’s natural heritage for scientific and public benefit. 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 (See instructions): Cisplatin, a widely used chemotherapeutic drug, is toxic to mechanosensory hair cells in the inner ear, resulting in permanent hearing loss in up to 60% of cancer patients. However, limited treatment strategies are available that are effective in treating cisplatin-induced hearing loss without reducing the antitumor efficacy of cisplatin, highlighting the need for continued development of therapies. Macrophages, the major resident immune cells in the cochlea, are important drivers of inflammatory and tissue repair responses. Specifically, perivascular macrophages are closely associated with the blood-labyrinth barrier (BLB) in the inner ear and regulate BLB permeability. Macrophage ablation using Pexidartinib (PLX3397) has been shown to provide complete protection against cisplatin-induced hearing loss and reduce cisplatin entry into the inner ear. Given that cisplatin is known to enter the inner ear through the BLB, this suggests that macrophages may play a role in BLB breakdown in response to cisplatin. The goal of this proposal is to identify the mechanism(s) by which macrophages regulate BLB permeability in response to cisplatin-induced ototoxicity in both non-tumor-bearing and tumor-bearing mice, while also determining whether Pexidartinib (PLX3397) compromises the antitumor efficacy of cisplatin. Aim 1A will investigate the contribution of VEGF-A-Flt1 signaling to macrophage-mediated regulation of BLB permeability following cisplatin treatment, using conditional knockout mice that disrupt this pathway. BLB permeability will be assessed through tracer assays, junctional protein expression will be evaluated, and cisplatin levels will be quantified in inner ear tissues to determine the extent of drug accumulation. Aim 1B will identify additional soluble factors that contribute to regulation of BLB permeability within specific cell types of the stria vascularis. Single-nucleus RNA sequencing will be employed to characterize transcriptional changes induced by cisplatin exposure. Aim 2 will address whether macrophage ablation using Pexidartinib (PLX3397) regulates BLB permeability while preserving the antitumor efficacy of cisplatin, using a newly developed tumor-bearing mouse model that exhibits cisplatin-induced hearing loss. Findings from this study will inform the rational design of treatment strategies to prevent cisplatin-induced ototoxicity by regulating BLB permeability and controlling drug delivery into the inner ear. Additionally, the results will provide clinical insights into the potential repurposing of PLX3397 as an otoprotective agent for patients undergoing cisplatin-based chemotherapy.

NSF Awards · FY 2025 · 2025-09

With the support of the Chemical Synthesis Program of the Division of Chemistry, Professor Gregory Friestad of the Department of Chemistry at University of Iowa is developing new ways to create structurally complex small molecules from simple hydrocarbon precursors. The goal of this research is to exploit transition metal-catalyzed additions to alkynes and epoxidations to access enol ester epoxides and related compounds, and to develop novel ring-opening chemistry of enol ester epoxides to prepare densely functionalized building blocks more efficiently for synthesis. The project lies at the interface of organic, medicinal, and natural products chemistry, and it will provide an excellent setting for graduate and undergraduate education in synthetic chemistry and well-trained chemists for academic and industry workforce development. Ruthenium-catalyzed addition of carboxylic acids to alkynes and epoxidation of enol esters have great potential, but thus far have seen limited synthetic application. This project will develop asymmetric catalysis via kinetic resolution of enol esters derived from racemic alkynes, desymmetrization of enol esters derived from achiral alkynes, and group selectivity of intramolecular addition to diynes. The resulting aldehyde-derived 1,2-disubstituted acyclic enol esters, cyclic enol esters, and 1,1-disubstituted enol esters will be employed as substrates for asymmetric epoxidation to generate enol ester epoxides. These are mostly unexplored reactive compounds that offer potential for stereocontrolled and step-economic ring-opening reactions to generate highly functionalized chiral small molecules with broader impacts in medicinal and natural products chemistry. This project will test the scope of the reactions with both the 1,2-disubstituted and 1,1-disubstituted enol ester epoxides. Useful alpha-substituted aldehydes and alpha-haloalkyl esters will be formed. Reactivity and stereoselectivity aspects of carbon-carbon bond constructions of both enol ester epoxides and alpha-haloalkyl esters will also be developed, using carbon nucleophiles, carbon-centered radicals, and organotransition metal compounds to generate diverse 1,2-diol structures. 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

This project addresses the need for statistical models that help biomedical researchers better understand changes in biological markers across populations and within individual subjects over time, using multidimensional tabular data. The investigators will collaborate with neuroscientists at the University of Iowa College of Medicine to adapt and enhance statistical modeling approaches for analyzing data from real-world biomedical studies involving mice. This work seeks to address some of the fundamental statistical challenges associated with these complex datasets. The investigators will accomplish this by leveraging two types of time-dependent modeling approaches and extending these methods to datasets that contain far more variables than observations. The project is significant because these methods will assist biomedical researchers in tackling key healthcare questions, accelerating scientific discovery, and providing tools for interpreting complex biomedical data. To promote broad accessibility and impact, the methods and tools developed will be released as open-source software, advancing both statistical methodology and biomedical research. The project will also strengthen data science training for graduate students and contribute to curriculum development at the undergraduate and graduate levels, thereby preparing students for careers in academia and the biomedical industry. The investigators are committed to mentoring graduate students in both methodological innovation and the adaptation of statistical tools for biomedical applications. Additionally, an open-source software package will be released on a publicly accessible platform to extend the project’s impact across the broader scientific community. In these ways, the project serves the national interest by contributing to NSF’s mission to promote the progress of science and to advance the nation’s health. This project will develop statistical methods for high-dimensional array-variate data with longitudinal and temporal dependencies, motivated by biomedical applications where data are often structured as multi-dimensional arrays with far more variables than observations. The investigators will design a suite of penalized likelihood and generalized Bayesian approaches for array-variate mixed-effects and autoregressive models, with a focus on inducing sparsity and low-rank structures in the mean, covariance, and precision arrays. Key innovations include the use of generalized likelihoods to broaden applicability beyond traditional Gaussian settings, and random projection matrices to compress mean, covariance, and precision array parameters, thus enhancing the computational scalability of Expectation-Maximization and Monte Carlo-based inference in high-dimensional settings. The proposed models and algorithms aim to produce interpretable results and remain computationally efficient even in applications with large numbers of variables and samples. Theoretical investigations will establish the consistency and optimality of these methods under minimal assumptions. In summary, this toolbox will enable flexible, scalable, and principled inference for array-variate data with complex temporal structure, advancing statistical methodology for structured biomedical datasets. 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 Following infection, a subset of pathogen-specific B lymphocytes can rapidly differentiate into germinal center (GC) B cells that undergo rapid proliferation and somatic hypermutation, resulting in the production of high- affinity memory B cells (MBC) and long-lived antibody secreting plasma cells (LLPC). Studies of T lymphocytes and cancer cells reveal that rapid differentiation and proliferation requires key changes in cellular metabolic pathways. During malaria, B cell differentiation and function are suboptimal, leaving individuals in endemic areas susceptible to repeated infection. Published work from our laboratory (Vijay et al. Nature Immunology. 2020) showed that dysregulated glutamine metabolism is linked to energetic shortfalls that limit host protective humoral immunity. In this project, the applicant will investigate how B lymphocytes utilize the amino acid glutamine and its derivative glutamate to power proliferation, survival, and functional differentiation. The applicant’s new preliminary data show that deletion of the mitochondrial glutamate transporter results in drastic reductions in the number of GC B cells responding to Plasmodium infection, parasite-specific secreted antibody, and host resistance to malaria. Despite these striking phenotypes, the specific cytosolic and mitochondrial metabolic pathways fed by these metabolites are not known. It is also not known how these metabolites influence the quantity and quality of GC-dependent MBC and LLPC populations. This project addresses these fundamental knowledge gaps and will utilize in vivo and ex vivo experiments to define the intracellular biochemical dynamics that govern the necessity of glutamine and glutamate, as well as the downstream effects that nutrient starvation plays in how B cells respond to infection. The proposed research will reveal fundamental new information about B cell metabolism, as well as identify the potential for metabolism-based therapeutic options relevant to Plasmodium parasite infection. Aim 1 of this proposal will investigate how metabolite restriction in B cells impacts their proliferation, survival, and functional differentiation by utilizing targeted temporal protein deletion mice and analyzing readouts in blood parasite burden, immune cell expansion in spleen, and per-cell antibody production potential. Aim 2 interrogates the specific biochemical pathways that are impacted by B cell nutrient starvation, utilizing carbon tracing experiments in mice possessing targeted and B cell-restricted metabolite transporter deletions. In addition to critical scientific advances in B cell metabolism, the successful completion of this project will also immerse the applicant in a variety of cutting-edge research methods, gain experience in communication and collaboration with both collaborators and non-scientific audiences, and will condition the applicant to be better equipped his aspired career in academic scientific research.

NSF Awards · FY 2025 · 2025-09

Batteries play a tremendous role in our society and economy. From portable electronics and sensors to hybrid and electric transportation to our nation’s electrical grid, batteries provide an important way to store energy across large differences in scale. However, there is continued need to build better, safer batteries so that they can store more energy, be charged and discharged more times, and be assembled with less expensive and more readily available components. Addressing these challenges starts with the materials inside of the battery. This project will design new battery components that are made from earth abundant materials dissolved in water. These materials can be less expensive and safer than those found in conventional lithium-ion batteries, but they are not currently as powerful. Moreover, as these materials are made from mixtures of different chemicals at different concentrations, the space for design is expansive. To aid in the search through this complex chemical space, this project will develop and deploy robotic experiments and machine learning models to rapidly vary component combinations, record their properties, and make predictions as to new systems to explore. Promising materials will be tested in batteries to evaluate how they perform. Researchers will be trained as new battery scientists who understand both the chemistry and engineering of emerging battery science, and they will learn how to develop and use artificial intelligence to expedite discovery. The results of this investigation will help guide efforts to enhance our nation’s energy economy and support energy security. Water-based battery chemistries offer abundant, non-toxic, and non-flammable solutions to energy storage challenges. The goal of this project is to design and analyze redox electrolytes with large concentrations of redox-active, earth-abundant, ligand-metal coordination complexes capable of storing multiple electron equivalents in the metal and surrounding ligand framework. The hypothesis is that a framework for the co-design of redox electrolytes can be derived from systematic and concerted molecular synthesis and experimental characterization coupled with autonomous materials formulation, electrochemical characterization experiments, and development of aligned machine learning (ML) models. Solubility and stability will be regulated by the chemistry imbued to the metal complexes by sulfonation of the redox-active ligands and through judicious formulation of the aqueous electrolyte. Coupled with the human-centered electrolyte formulation and electrochemical characterization, autonomous formulation and electrochemical experiments and high-throughput computations will be implemented to expand the redox electrolyte chemical space being explored. A publicly accessible data infrastructure will be developed and released, and the data will be used to develop ML models to identify and optimize co-design principles for redox electrolytes. This project will also train professional scientists in a multidisciplinary project combining experimentation, computation, automation, data infrastructures, and artificial intelligence (AI), guiding the nation’s energy economy and supporting energy security. 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 Heart failure with preserved ejection fraction (HFpEF) accounts for half of the heart failure hospitalizations in the US thus representing a major public health priority. However, currently, there are limited effective approaches to preventing and managing this complex syndrome. Systemically, obesity-associated hyperlipidemia, hyperglycemia, and chronic inflammation have been considered as the major factors for the pathogenesis of HFpEF. In the heart, maladaptive cardiac immuno-metabolic reprogramming is a hallmark of HFpEF. In cells, nutrient sensing, macromolecule catabolism, and inflammatory regulation are fine-tuned by the lysosome. However, the extent and mechanisms by which lysosomal dysfunction contributes to the pathogenesis of HEpEF are poorly defined. The objective of this proposal is to determine the pathophysiological impact of cardiac lysosomal dysfunction in the setting of HFpEF. The lysosome contains more than 70 enzymes. As such, murine studies of individual lysosomal enzymes have contradicting observations regarding cardiac pathophysiology. Lysosomal reductase Gamma Interferon-Inducible Thiol Reductase (GILT) is the only identified lysosomal reductase that controls diverse sets of lysosomal enzymes and cargoes. We found that GILT is reduced in the hearts of humans with HFpEF and obese mice, respectively. Notably, both lean and obese mice with a human GILT SNP for CVD risk displayed a significantly reduced diastolic function without other interventions. Furthermore, loss of GILT in cardiomyocytes accelerates the HFpEF-related cardiac decline. Transcriptomic and metabolic analyses further revealed that cardiac GILT deficiency disrupted the immuno-metabolic homeostasis in the heart. Therefore, we hypothesize that GILT protects against cardiac immuno-metabolic imbalance in obesity-associated HFpEF. We will pursue two specific aims to test this hypothesis. In Aim 1, we will investigate the pathological significance of cardiac GILT in the context of HFpEF by using novel gain- or loss-function of GILT mouse lines. In Aim 2, we will elucidate molecular mechanisms for cardiomyocyte GILT-regulated mitochondrial function, glucose homeostasis, and inflammasome activation. To answer these challenging questions, we have assembled a strong collaborative team. Each co-PI is a recognized expert in her/his respective field (organelle functions in obesity, cardiac pathophysiology, and cardiac metabolism). This collaborative research proposal is innovative, combining the use of cellular and molecular approaches, metabolomic analyses, as well as in vivo mouse metabolic and cardiac profiling. Findings from this study will provide insights into interplays between cardiac lysosomes, inflammatory responses, and metabolic homeostasis and should speed the development of novel therapies for improving cardiovascular health.