University Of Michigan At Ann Arbor

NIH Research Projects · FY 2026 · 2026-06

Uterine cancer is the only cancer type for which survival has fallen in the past four decades. This year in the United States, over 13,000 women will die from this disease, surpassing ovarian cancer for the first time: making uterine cancer the deadliest gynecological cancer. Mortality from uterine cancer is primarily due to the aggressive high-grade subtypes of endometrial carcinoma, which include endometrial serous carcinomas, uterine carcinosarcomas, and high-grade endometrioid carcinomas. Molecularly, these high-grade subtypes harbor few mutations, however, almost every high-grade endometrial carcinoma harbors a TP53 mutation, and 30-40% also harbor a heterozygous PPP2R1A mutation, most commonly - P179R, S256F, or R183W. PPP2R1A encodes for the AƒÑ scaffolding subunit of the heterotrimeric protein phosphatase 2A (PP2A). However, a lack of models, particularly transgenic mouse models, of high-grade endometrial carcinomas has limited our understanding of the disease and the preclinical testing of targeted therapeutics directed at the underlying drivers of disease development and progression. Knockout of p53 in mouse endometrial epithelium has been shown to result in the formation of microscopic incompletely penetrant endometrial tumors at 16-20 months of age. Our group has generated novel conditional Ppp2r1a-P179R and R183W knock-in mice. We crossed these mice to the Trp53fl/fl and Ksp1.3-Cre mouse to generate endometrial epithelium-specific knockout of Trp53 and knock-in of either AƒÑ- P179R or R183W PP2A mutant alleles. Preliminary data demonstrate that our mice develop advanced highgrade endometrial carcinomas as early as 5 months of age with 100% penetrance, supporting that PPP2R1A is a driver of high-grade endometrial carcinomas for the first time. Treatment options for advanced high-grade endometrial cancers are limited. Therapeutically, we have developed a series of first-in-class PP2A molecular glues (PMGs) that can specifically stabilize the tumor suppressive PP2A A/B56£\/C heterotrimer. Interestingly, we have found that PMG treatment results in tumor regressions in a dose-dependent manner in PP2A mutant models of high-grade endometrial cancer. Our central hypothesis is that PP2A mutants promote high-grade endometrial tumorigenesis and the Ksp1.3-Cre/Tp53fl/fl/PPP2R1A-mutant mouse models may represent a novel mouse model for tumor development, progression, and detection and molecular glues targeting of PP2A could be a novel treatment strategy for these tumors. The aims of this proposal were formulated to explore the role of PP2A in high-grade endometrial cancer in three predominant areas all of which are NCI mission areas for women¡¦s health research; 1) tumor initiation and progression, 2) modulation of this protein family as a treatment strategy, and 3) substrates regulated by PP2A, which may serve as screening biomarkers of the disease. The use of mice is a crucial component of this proposal as we seek to establish a novel mouse model of high-grade endometrial cancer and test the efficacy of novel therapeutics against high-grade endometrial cancers in vivo. Mice are currently the gold standard for modeling cancer, and we have proposed to test immunotherapy agents, which can only be performed in animal models with intact immune systems.

NIH Research Projects · FY 2026 · 2026-06

PROJECT SUMMARY Coccidioidomycosis (also called Valley fever) results from the inhalation of soil-dwelling Coccidioides fungal spores. Infection is immunizing and primarily manifests as respiratory disease, with symptoms lasting a median of 120 days. Since 2000, the U.S. Southwest has seen >9-fold increases in the incidence of coccidioidomycosis, as well as geographic expansion of the disease into new areas. We hypothesize that low population immunity to Coccidioides could amplify rates of expansion. However, despite its changing epidemiology, surveys of naval recruits and students from 1949-51 provide the most recent estimates of population immunity for most of California’s and Arizona’s counties. This is due in part to unique challenges in establishing prior history of infection for coccidioidomycosis, as skin tests are the only current tool to indicate lifetime infection. Our team has analyzed >230,000 reported and geolocated cases of coccidioidomycosis captured by California and Arizona surveillance systems to generate new insights into the exposures that cause disease. Yet, current healthcare-based surveillance systems vastly undercount infections and do not capture key individual-level risk factors such as occupational dust exposure. These limitations obscure our understanding of the true burden of coccidioidomycosis and hinder our understanding of the specific exposures that drive risk. Further, while a vaccine for coccidioidomycosis is forthcoming, proper planning of trials will require understanding of what proportion of the population already has naturally induced immunity. In this project, we aim to: 1) advance methods for estimating immunity to Coccidioides in the general population using cell-mediated immunity (i.e., skin) tests and population-level serological surveys, and identify exposures associated with prior infection; 2) develop computational approaches to improve estimation of population-level immunity to Coccidioides and case under-reporting via the integration of data from surveillance, serology, and cell-mediated immunity tests; and 3) with an updated understanding of population immunity and case under- reporting, evaluate the risk factors and exposures that give rise to infection. To meet these objectives, we will collect data on prior infection from three potential vaccine trial sites in California and Arizona. We will develop and apply an approach that harmonizes multiple data streams—including from serosurveys, surveillance records from California and Arizona, and >154,000 previously unexamined skin test results from a California male cohort—to estimate population immunity while minimizing data collection. Finally, we will apply time- series analyses that identify exposures and risk factors for infection, while adjusting for population immunity. This project will produce new data and methods to overcome barriers for estimating population immunity for an emerging disease. Our findings will prepare us for coccidioidal vaccine trials; identify the degree of under- reporting and reasons for it; and identify high risk populations to be prioritized for public health interventions now and in the years to come.

NIH Research Projects · FY 2026 · 2026-06

Abstract The use of psychedelics such as psilocybin-containing mushrooms has increased dramatically in recent years, due to rapidly changing scientific evidence, public opinion, and regional policies. Although psychedelics remain Schedule I substances at the federal level, they are unevenly regulated by a patchwork of state and municipal policies. In addition to decriminalized naturalistic use, a growing number of states are creating legal frameworks for the provision of psychedelic services for adults, for any purpose. These environments differ greatly from rigorous clinical trials, where participants are highly screened and known doses of psychedelics are paired with extensive preparation and psychotherapy. Although clinical trial results for psychiatric conditions are promising, research on the use, safety, and health effects of psychedelics in community settings—where most psychedelic use occurs—remains scant. Understanding real-world trends in psychedelic use is of great public health importance given that the rapid speed at which these policies are changing far outpaces the research, with some analyses projecting over half of US states legalizing psychedelics by 2037. Drawing on our substantial expertise in conducting research focused on how and why people use psychedelics as well as associated health outcomes, our objective is to characterize national perceptions of risks and safety, use patterns, and safety outcomes associated with psychedelics. Our overarching hypotheses are: 1) interest in and use of psychedelics is rising–especially in jurisdictions with active psychedelic decriminalization policies, 2) policy changes will impact use patterns (e.g., at licensed centers vs. home) and substance sourcing (i.e., illicit vs. licit), and 3) psychedelic use impacts other drug use, either in polypharmacy or substitution contexts. To test these hypotheses, we propose two aims: 1) Conduct four annual waves of a nationally-representative, probability weighted survey (n=5,000 individuals per wave) via the National Opinion Research Center's Amerispeak Panel to characterize perceptions of harm and safety of psychedelics compared to other drugs, as well as psychedelic use prevalence, and; 2) Among individuals reporting past-year psychedelic use in Aim 1, we will further assess intention for use, use characteristics (e.g., substance used, use with or without a therapist), health outcomes (e.g., mood disorder symptoms), side effects, and impacts of psychedelic use on other substances. In both aims, we will assess relationships between existing psychedelic policies (e.g., decriminalization) and our findings. In the face of rapidly changing policies and public perception, our study will effectively monitor national trends detailing psychedelic safety in real-world contexts, how these substances are used, and their associated health outcomes, including on mood and substance use. We will directly disseminate our results to patient advocacy groups, clinicians, and policymakers, providing critical evidence to inform appropriate public health outreach and education efforts in the era of psychedelic policy reform.

NIH Research Projects · FY 2026 · 2026-06

PROJECT SUMMARY Differentiation of human primordial germ cells (hPGCs) from human pluripotent stem cells is the first step toward in vitro gametogenesis, which would enable mechanistic studies and treatment of infertility due to loss of gametes. The mechanisms of hPGC differentiation are poorly understood. As a result, current protocols produce heterogeneous mixtures of hPGC-like cells (hPGCLCs) and other cell types. Our long-term goal is to obtain a systems-level understanding of the signaling and gene regulatory network that control primordial germ cell differentiation in vitro and use this to improve directed differentiation of hPGCLCs for potential therapeutic purposes. The objective of this proposal is to quantitatively determine cell signaling requirements of hPGCLC differentiation with unprecedented spatial and temporal resolution. The central hypothesis is that heterogeneous differentiation and maturation of hPGCLCs is due to heterogeneous cell signaling activity. The rationale is that if we identify what distinguishes more mature hPGCLCs from less mature ones and other cell types that arise at the same time, we can understand defects in their differentiation in vivo and in vitro and create better hPGCLCs. Our hypothesis will be tested through two specific aims: 1) Determine the combinatorial signaling dynamics responsible for hPGCLC induction by single cell tracking of signaling and fate markers in live cells combined with highly multiplexed immunofluorescence. 2) Determine if there are distinct phases of induction and maintenance and elucidate the signaling logic and gene regulatory network that controls hPGCLC maintenance and maturation. Our approach is conceptually innovative by testing if a unique history of signaling determines hPGCLC fate, by accounting for the interplay between exogenous and endogenous signaling in vitro, and by delineating clearly distinct phases of differentiation that start with induction. More generally we are breaking new ground by taking a systems-level approach to human germ line biology that tests hypotheses rigorously and quantitatively by representing them as mathematical models. The proposed work is also experimentally innovative as we use substrate micropatterning to achieve reproducible hPGCLC differentiation and are the first lab to establish long-term high throughput tracking of differentiating pluripotent stem cells as well as the first to adapt multiplexed immunofluorescence to stem cell models of early development. The expected outcome of our work is better fundamental understanding of human germ line differentiation and improved methods to produce hPGCLCs for research of in vitro gametogenesis.

NIH Research Projects · FY 2026 · 2026-06

PROJECT SUMMARY/ABSTRACT Neurocognitive abilities relevant to adaptive decision making and self-regulation (e.g., inhibition, working memory) mature from childhood through adolescence and play a critical role in the emergence of psychopathology. However, one-to-one mappings between these abilities and risk for specific psychiatric diagnoses have been elusive. The field’s struggle to identify such mappings is nonetheless consistent with high rates of comorbidity among disorders and the presence of a general factor for psychopathology (“p-factor”) suggesting many etiological mechanisms have a broad influence across diagnostic boundaries. Common factors also account for a substantial proportion of developmental change and individual differences in specific neurocognitive abilities, suggesting many of the associations between neurocognition and psychopathology are mediated through general processes that drive adaptive functioning across many tasks, contexts, and diagnoses. Efficiency of evidence accumulation (EEA)—a biologically plausible cognitive mechanism that has been well-characterized in computational modeling and neurophysiological research—is a compelling candidate for a general factor that can explain neurocognitive contributions to transdiagnostic psychopathology risk. EEA is a reliable higher-order factor that accounts for performance across a wide variety of cognitive functions—from simple decisions to complex executive tasks—and is impaired in multiple disorders linked to self-regulatory difficulties and maladaptive decision making. We posit that EEA is a developmental catalyst that supports adaptive decision making across many contexts, that EEA’s development is strongly influenced by the interplay between environmental factors (e.g., family conflict, socioeconomic resources) and the maturation of largescale brain networks, and that aberrant development of EEA conveys transdiagnostic risk for psychopathology. EEA’s well-characterized computational definition and biological underpinnings promise to provide a novel bridge between computational neuroscience and developmental psychopathology research. Furthermore, recent indications that EEA’s development may be impeded by specific adverse environments suggest that knowledge about EEA could inform targeted prevention efforts. To spur a program of computationally rigorous research on EEA as a general, and potentially malleable, neurodevelopmental influence on psychopathology, we will leverage four large longitudinal neuroimaging data sets to accomplish the following aims: 1) map the canonical maturational trajectory and nomological network of EEA across development, 2) quantify the influence of genetic and diverse environmental influences on the development of EEA, and 3) examine EEA’s co- development with psychopathology, environmental adversity, and neuroimaging metrics. Knowledge gained through this project will allow the field of developmental psychopathology to leverage key benefits of well- established computational models to establish precise and biologically plausible accounts of neurocognitive risk factors for psychopathology, their environmental determinants, and potential translational applications.

NIH Research Projects · FY 2026 · 2026-06

Project Summary Biopharmaceuticals, including therapies based on proteins and nucleic acids, are now among the most important classes of modern medicines. While they are used to treat a wide range of diseases, they are most commonly employed in cancer, autoimmune disorders, and infectious diseases, generating over $100 billion in annual sales. Despite these successes, many challenges loom in the discovery of next-generation biotherapeutics. We lack routine technologies that can quickly assess the sequences, chemical modification states, and higher- order structures (HOSs) of protein and nucleic acid products. Some products are known to produce a wide range of non-covalent complexes with targets, further complicating the refinement of their potency and the evaluation of their potential safety. Most biopharmaceuticals target membrane proteins, which are generally refractive to standard structural biology tools and may alter their structures in a manner dependent upon local lipid environment changes, which can thus influence characterization efforts, safety screening, and ultimate efficacy. Nucleic acid drugs (NADs) specifically are often packaged within lipid nanoparticles (LNPs), which have largely unknown influences on NAD structures and stabilities. This application seeks to close the above-noted gaps in technology through the development of new methods based on native ion mobility-mass spectrometry (nIM-MS), a technology platform that can quickly separate and measure both the sizes and the masses of complex biotherapeutic samples. Our approaches will also rely upon collision induced unfolding (CIU), which can be used to quickly assess the structures and stabilities of proteins and nucleic acids. Specifically, we plan to 1) develop rapid, droplet-based enzymatic chemistries for nIM-MS enabled structural analysis of monoclonal antibody (mAb) therapeutics, 2) produce improved access to mAb sequence and chemical modification information by leveraging rapid liquid chromatography and top-down MS approaches based on cyclic IM-MS, and 3) evaluating both the role of lipids on antibody-antigen complex formation and NAD HOS, through the creation of nIM-MS approaches compatible with lipid nanodiscs, vesicles, and nanoparticles. Our efforts will result in a battery of new nIM-MS methods that enable the complete and rapid evaluation of biotherapeutic sequence, modification status, binding preferences, and stabilities, thus enabling a new chapter in the development of biopharmaceuticals for the treatment of human disease.

NIH Research Projects · FY 2026 · 2026-06

PROJECT SUMMARY The dominant trend in healthcare is regional consolidation of hospitals into “hub-and-spoke” health systems. Integrated care across health systems should ensure that multidisciplinary cancer care is coordinated; yet, healthcare silos persist, perpetuating differences in care among individuals. I am a colorectal surgeon and trained health services researcher working in a spoke hospital of an academic health system with a view into the realities of regional consolidation of hospitals. This proposal seeks to study colon cancer as a test case for regional cancer care delivery across hub-and-spoke health systems. Colon cancer is common, ranges in clinical complexity, follows well-established guidelines, and demonstrates known variation in quality. We will leverage the unique portfolio of the collaborative quality initiatives (CQIs) in Michigan to serve as a learning laboratory. First, we will link data from rich claims and registry data sets with health system identifiers to profile quality of multidisciplinary colon cancer care across hospitals within health systems (Aim 1). Second, we will conduct focus groups with stakeholders including multidisciplinary providers, administrative leaders, and patient representatives to characterize determinants to regional coordination of colon cancer care in health systems (Aim 2). Using a convergent mixed methods design, we will elicit qualitative determinants to regional cancer care delivery within the six World Health Organization (WHO) health systems framework domains and quantify participant’s anticipated impact of determinants on clinical outcomes over time. By integrating qualitative and quantitative data, we expect to characterize how determinants differentially influence clinical outcomes at different hospitals within the hub-and-spoke model. Third, we will design a multilevel intervention based on the Implementation Research Logic Model (IRLM) which aligns determinants, implementation strategies, and outcomes (Aim 3). The proposed work will build on my existing quantitative and qualitative skill sets with additional training in (1) performance assessment of hospitals and health systems, (2) systems science approaches including systems thinking and systems dynamics, (3) implementation research in learning health systems, and (4) the pathway to research independence. Aligned with my research and career development goals, I will be mentored by a strong multidisciplinary team with a long track record of success supporting trainees from K- to R-level funding. This proposal addresses “Healthcare Teams and Cancer Care Delivery,” a cross-cutting research priority area outlined by the NCI’s Healthcare Delivery Research Program, which seeks to influence broad access to high-quality cancer care. With the proposed training and mentorship plans, this work will propel me towards independent funding as a surgeon-systems scientist, embedded in the community, with a future R01 hybrid effectiveness-implementation trial.

NIH Research Projects · FY 2026 · 2026-06

Project Summary/Abstract The Center for Chemical Genomics (CCG) at the Life Sciences Institute (LSI) serves as the high throughput screening core facility, available to all faculty at the University of Michigan (U-M) and seeks funding to support the purchase of a new microplate reader, the PHERAstar FSX. The current instruments, a 17-year- old Perkin Elmer EnVision 2104 and a 21-year-old PHERAstar, have each reached the end of their operational lifespan and manufacturer support is being terminated. Given that these microplate readers are used to support approximately 90% of the screening experiments that the CCG performs, they are critical to the continuation of CCG services, and failure to obtain a replacement option for these aging machines will dramatically impact the early phase drug discovery program at U-M. The PHERAstar FSX is the ideal replacement due to its state-of-the-art capabilities, enabling the CCG to conduct a comprehensive array of experiments as requested by U-M faculty, as well as researchers external to U-M. The CCG is a critical component of both basic research and the early-phase drug discovery pipeline at U-M. It conducts approximately 20 high-throughput screening (HTS) campaigns, as well as supporting ~3-5 Structural-Activity Relationship (SAR) campaigns, annually. Despite advances in computational approaches, HTS of large chemical libraries, consisting of over 100,000 samples, remains the most commonly employed method for identifying novel compounds that modulate the activity of a target protein. This “unbiased” screening approach is used to identify active molecules that can be optimized for use as in vitro or in vivo research tools, and/or as potential drug leads. The vast majority of HTS assays are designed to utilize some form of fluorescence or luminescence as the final readout, as this approach can yield HTS assays that are both robust and cost-effective. The CCG’s microplate readers are essential for conducting these HTS assays. The CCG supports NIH projects for U-M researchers and external collaborators across an incredible breadth of research fields, including research on cancer, cardiomyopathy, nicotine and opioid addiction, and drug metabolism. The university is a national leader in academic drug discovery, demonstrated by its 15 drugs in current clinical development. The initial identification of candidate drugs is a vital part of this pipeline and aligns with the mission of the NIH and U-M’s overarching goal of improving public health. Replacing the dated microplate readers in the CCG with the PHERAstar FSX will ensure the continuation of CCG support for groundbreaking drug discovery research at the University of Michigan.

NIH Research Projects · FY 2026 · 2026-06

SUMMARY Lysosomes are central players in cellular catabolism that play a pivotal role in regulating metabolism and signaling. Cellular and environmental stressors that damage the lysosomal membrane compromise organelle function and release toxic content into the cytoplasm that ultimately drives cell death. Building on our discovery that the ESCRT machinery is rapidly deployed to repair lysosomal membrane damage, there has been much interest in defining how cells sense acute changes in membrane structure and organization to coordinate among a growing array of restorative responses. Our goals over the coming five years will address key questions about how local membrane remodeling and reinforcement by ESCRTs integrate with changes in lipid delivery and cholesterol content to maintain integrity, how individual components of the ESCRT machinery contribute to resilience and repair, and how cells recognize unsalvageable lysosomes for removal. Using cell- biological, biochemical, and biophysical approaches, we will integrate studies of individual stress responses with a unified understanding of lysosomal membrane homeostasis.

NIH Research Projects · FY 2026 · 2026-06

Fear of falling (FoF) is a common and distressing concern among persons with multiple sclerosis (MS) due to the gait and balance impairments associated with the disease. FoF – a persistent concern about falling that may cause individuals to avoid activities they are capable of performing safely – is often the focus of clinical care and research. Most efforts concentrate on assessing and reducing degree of FoF with a lack of attention to how FoF affects daily living activities and contributes to poorer function. The Falls Efficacy Scale International (FES-I), the most commonly used FoF measure for persons with MS, asks respondents to rate their FoF in the context of real or imagined activities (including those they do not perform) but does not assess FoF's impact on those activities. For example, a person may report high FoF on a FES-I item that asks about walking in places with crowds, but that high score does not reflect whether they actually do walk in crowded places or avoid that activity because of their FoF. In this scenario, the FoF score on the FES-I, though high, would still mask the functional limitations associated with FoF. Assessing the impact of FoF on daily living activities could serve as a more comprehensive indicator in clinical trials and research, offering a thorough understanding of the challenges faced by persons with MS regarding FoF and guide rehabilitation approaches. Unfortunately, existing measures of the impact of FoF, developed for the geriatric population, have conceptual limitations that may affect their clinical utility for use in persons with MS. The advancement of FoF research among persons with MS is currently stymied by two major factors, 1) the lack of a foundational conceptual model of FoF and 2) the lack of an outcome measure of the impact of FoF that takes into consideration input from persons with MS. The end goal of this study is to develop a validated and reliable Fear of Falling Impact Patient Reported Outcome (FOFI-PRO) measure. First, we will conduct focus groups with persons with MS to develop a patient-centered conceptual model of FoF in MS (Specific Aim 1). Then, we will develop FOFI-PRO item pools, containing a broad range of items that assess the impact of FoF (Specific Aim 2). Finally, we will deliver a finalized, validated, and reliable FOFI-PRO item bank and companion static short form for use in persons with MS (Specific Aim 3). Item pool development will involve a multi-stage process including extensive literature review, development of items based on focus group content, cognitive interviews with persons with MS, translatability and literacy evaluation, and expert input. The conceptual model and the FOFI-PRO measure produced in the proposed study will reveal specific activity groups and domains that are relevant for persons with MS but avoided due to FoF. These findings will guide the development and testing of a multidisciplinary intervention (a subsequent R01 application) to reduce the impact of FoF on daily living activities and promote independence. This study will help to personalize clinical practice, provide tools for new approaches in clinical trials, and ultimately improve the independence and quality of life of persons with MS.

NIH Research Projects · FY 2026 · 2026-06

ABSTRACT Aminoacyl-tRNA synthetases (ARSs) are a ubiquitously expressed, essential class of enzymes responsible for ligating amino acids to cognate tRNA molecules. To date, seven genes encoding an ARS have been implicated in dominant axonal neuropathy with extreme clinical heterogeneity. All seven ARSs implicated function as dimers to charge tRNA in the cytoplasm. Our multiple PI team has previously shown that neuropathy- associated ARS mutations cause a loss-of-function effect, which can be detected in enzyme kinetic and yeast complementation assays. We have also shown that ARS missense mutations associated with dominant neuropathy are toxic when over-expressed in yeast and worm model systems, and that dimerization is required for this toxic effect. Combined, these observations strongly support a dominant-negative mechanism where the mutant protein binds to and inhibits the wild-type protein in a heterozygous affected individual. We present here, an innovative pipeline—including genetic, molecular, in vitro, and in vivo approaches—to comprehensively address two critical, unanswered questions: (1) Do neuropathy-associated ARS variants act via a dominant-negative effect? and (2) By what mechanism—and to what degree—do neuropathy-associated ARS variants impact tRNA charging and cell stress pathways? Our initial efforts will focus on a well- characterized, neuropathy associated variant (R329H alanyl-tRNA synthetase [AARS1]). Future efforts will leverage the strategy developed here to study alleles at all seven ARS loci associated with dominant neuropathy. Our efforts will provide an innovative, effective, and efficient strategy to study neuropathy- associated variants at any ARS locus.

NIH Research Projects · FY 2026 · 2026-06

ABSTRACT Immune checkpoint blockade (ICB) therapies have transformed the landscape of cancer treatment by unleashing cytotoxic T cell responses against tumors. However, a large proportion of patients remain unresponsive, particularly those with “cold” tumors characterized by low pre-existing T cell infiltration and diminished immunogenicity. A key determinant of tumor immunogenicity is the expression of major histocompatibility complex class I (MHC-I) molecules, which are essential for antigen presentation and CD8 T cell-mediated tumor recognition. MHC-I loss is a well-established mechanism of immune evasion, observed in more than half of all cancer patients across multiple tumor types. Strategies to restore MHC-I expression therefore represent an urgent therapeutic need. Our recent studies identify a novel immunosuppressive mechanism involving the tumor cell transporter SLC13A3, which imports the metabolite itaconate from the tumor microenvironment (TME) and promotes tumor resistance to ferroptosis, aligned with low tumor immunogenicity. However, the precise mechanism by which itaconate and SLC13A3 contribute to reduced tumor immunogenicity remains unclear. Preliminary data show that itaconate suppresses IFNγ-induced MHC-I expression in tumor cells, suggesting that the itaconate-SLC13A3 axis functions as a metabolic checkpoint that regulates tumor immunogenicity. We hypothesize that itaconate suppresses MHC-I expression through two complementary mechanisms: (1) Itaconate covalently modifies (alkylates) STAT1, thereby altering IFNγ signal transduction and transcription of MHC-I-related genes; and (2) itaconate alkylates p62, a scaffold protein that interacts with Keap1, leading to activation of the Nrf2 pathway, limiting interferon signaling, and promoting ferroptosis resistance. Together, these mechanisms position the itaconate-SLC13A3 axis as a key regulator of tumor immunogenicity. To test this central hypothesis, we propose two specific aims: Aim 1: Define the role and molecular mechanisms of the itaconate-SLC13A3 axis in regulating tumor MHC-I expression. We will integrate bioinformatics, metabolomics, proteomics, and immunologic approaches to dissect the regulatory effects of itaconate on STAT1 and p62 and their downstream consequences on MHC-I, immune signaling, and tumor cell killing. Aim 2: Develop and evaluate therapeutic agents targeting SLC13A3 to overcome ICB resistance. We have generated a panel of monoclonal antibodies (mAbs) that bind extracellular domains of human and mouse SLC13A3. We will evaluate these mAbs for their ability to inhibit itaconate transport and restore MHC-I expression. In parallel, we will develop bispecific antibodies targeting SLC13A3 and PD-L1 or tumor surface ubiquitin ligases to enhance therapeutic efficacy and promote targeted degradation of SLC13A3. This proposal will uncover novel metabolic mechanisms by which tumors evade immune surveillance and will establish proof-of-concept for targeting the itaconate- SLC13A3 axis as a strategy to restore tumor immunogenicity and overcome ICB resistance.

NIH Research Projects · FY 2026 · 2026-06

Abstract This MPI R01 application is aligned with the PAR-25-107, advancing microbial-based cancer therapy. Over the decades, standard cancer treatments such as chemotherapy and radiation often fail in solid tumors due to poor vascularization, tumor hypoxia, and immune suppression. In recent years, immune checkpoint inhibitors such as anti-PD-1 (aPD-1) have transformed cancer treatment but remain ineffective in many solid tumors due to a lack of pre-existing immune infiltration and an immunosuppressive tumor microenvironment (TME). Meanwhile, adoptively transferred cell therapies, including chimeric antigen receptor (CAR) T and NK cells, face major obstacles such as inefficient trafficking to solid tumors, and rapid exhaustion post-transfer. To overcome barriers to chemotherapy, radiation treatment, cancer immunotherapy, microbial-based cancer therapy has emerged due to its selectivity in solid tumors and enhanced anti-tumor immunity via synthetic biology. As self-regenerating cancer therapeutics, microbial therapies offer significant advantages for global health and low-resource settings. However, modern microbial therapies face challenges, including limited efficacy due to rapid clearance and systemic toxicity of therapeutic agents. To address these limitations, we recently engineered nonpathogenic tumor-tropic E. coli to display membrane-anchored immune cytokines, such as decoy-resistant IL-18 (DR-18), enhancing tumor-localized immune activation while minimizing systemic exposure. Our publication shows that E. coli displaying DR-18 significantly improves immune cell infiltration, reduces toxicity of systemic delivery of cytokines, synergizes with immune checkpoint blockade, and enhances the efficacy of CAR- NK therapy in preclinical mouse models. Building on our preliminary data, this proposal has three specific aims: (1) To elucidate the mechanisms by which tumor-tropic E. coli displaying DR-18 synergize with host anti-tumor immunity by profiling cytokine/chemokine responses and leveraging bacterial surface display to enhance immune cell recruitment. (2) To optimize bacterial safety and efficacy through scaffold protein engineering, genomic integration for stability, and a CRISPR-based failsafe switch to ensure controlled elimination and biosafety. (3) To validate the therapeutic potential of our engineered bacteria in patient-derived tumor spheroids and xenograft (PDX) models of mesothelioma and ovarian cancer using mesothelin-specific CAR NK or T cells, considering the high expression of mesothelin in these two cancer types and our publication record in this area. The combination of syngeneic and xenograft models will help bridge preclinical findings to human cancer biology. Our interdisciplinary team, bringing expertise in therapeutic microbial engineering (Dr. Li), NK cell therapy (Dr. Romee), and cancer immunology (Dr. Barbie), will develop a clinically viable microbial immunotherapy platform. By integrating bacterial surface display with immune modulation, this approach overcomes key barriers in cancer immunotherapy, potentially advancing solid tumor treatment through a safe, tumor-targeted microbial therapy.

NIH Research Projects · FY 2026 · 2026-06

PROJECT SUMMARY/ABSTRACT This K01 proposal seeks to provide Dr. Fiona Molloy, an early career computational cognitive neuroscientist, with the mentorship, training, and resources necessary to launch a career as an independent research- oriented investigator focused on using advanced computational methods to uncover neural and psychological mechanisms of risk for substance use disorders (SUDs) and leveraging this knowledge to inform personalized prediction and early intervention for at-risk adolescents. The candidate will work towards this long-term goal through the completion of a research project focused on computational modeling of the neural and cognitive processes underlying adolescent decision-making, with a focus on the delay discounting (DD) paradigm. Steeper DD, favoring smaller immediate rewards over larger delayed rewards, is associated with problematic substance use, and higher risk of developing SUDs. However, limitations with the measurement of DD behavior, e.g., arising from individual variability in the specific mechanisms people use to make decisions, have limited its value for producing scientific insights and clinical impact. This project aims to address these limitations to better characterize individual behavior by using advanced multi-modal statistical techniques and cognitive process models to quantify distinct psychological mechanisms, such as systematic responding and response caution. The candidate will combine her existing knowledge in cognitive modeling and fMRI analysis with new training to characterize the neurobehavioral decision-making mechanisms underlying DD’s development throughout adolescence and its relationship to substance use. Further, she will investigate modulating these person-specific mechanisms using real-time fMRI neurofeedback. The candidate will leverage three longitudinal datasets spanning adolescence and collect pilot real-time fMRI neurofeedback data with 40 adolescents to 1) Quantify the developmental trajectory of decision- making mechanisms underlying adolescents’ DD, 2) Construct joint models of decision processes in DD integrating neural and behavioral data¸ and 3) Explore the potential of modulating the brain-behavior signature of these distinct mechanisms with real-time fMRI neurofeedback. Concurrent with undertaking this innovative project, the candidate will complete the following training aims: 1) Master principles of analyzing large longitudinal datasets using models of developmental trajectories, 2) Build expertise in real-time fMRI neurofeedback design, execution, and analysis, and 3) Develop deep understanding of the neurodevelopment and clinical management of SUD and use understanding to assess how computational cognitive neuroscience can inform SUD prevention and treatment efforts. Completion of these training objectives will place the candidate at the frontier of affective neuroscience approaches in SUDs and launch her on a pathway to research independence and translational impact.

NIH Research Projects · FY 2026 · 2026-06

PROJECT SUMMARY Adolescent substance use is a pressing problem, with 13.0% of 8th graders, 23.1% of 10th graders, and 37.4% of 12th graders reporting current alcohol, cannabis, or nicotine use. While school attendance is a protective feature against substance use, 22% of students are exposed to substance distribution at school annually. Schools offer opportunities for universal programming to enhance adolescent health and well-being, including to address substance-related behaviors. Technology-facilitated reporting systems (TFRS) are school-based see-something-say-something peer bystander reporting systems. Although originally designed for violence prevention, 10-11% of submitted tips are for substance-related concerns, resulting in thousands of substance- related tips each year. As of 2024, 34 states have statewide TFRS, but empirical literature on TFRS focuses on violence-related tips, and little is known about the specific substances, behaviors, timing, geographic distribution, and outcomes of tips, nor about the practices, policies, and procedures employed by school personnel to respond to substance-related tips. In North Carolina, youth are trained in schools to use the statewide TFRS to submit information about peer concerning behaviors; once submitted, tips are triaged immediately by a trained counselor at the Sandy Hook Promise National Crisis Center, and referred by life- threatening status to relevant responders (e.g., emergency services for imminent threats or school personnel for issues like vaping). Using mixed natural language processing, statistical, and qualitative methods, we will draw tip-level data across 6 years and collect qualitative interviews from school personnel responsible for addressing information submitted through the TFRS to understand the types of substances and behaviors being tipped on, patterns of substance-related tipping, documented outcomes of tips, and the response processes used by school personnel to address substance-related tips. Specifically, we will: 1) use natural language processing and traditional statistical methods to describe the prevalence by specific substance and behavior in the tip line, and temporal and geographic patterns of tips; 2) use statistical methods to describe and compare the outcomes of substance-related tips; and, 3) collect key informant interviews and use thematic analysis to characterize the practices, policies, and procedures used by school personnel to respond to substance-related tips. This work will provide novel information on the types of substances and substance- related behaviors submitted to these systems, identify patterns of tipping that would be helpful for resource planning, and identify procedures that may be ineffective or potentially exacerbate harm (e.g., punitive suspension without connection to interventions/treatment) versus approaches that likely mitigate harm (e.g., counseling, connection to other supports), which we will use to inform the development of best practices and training materials to leverage TFRS in reducing the burden of harm for adolescent substance-related concerns.

NIH Research Projects · FY 2026 · 2026-06

PROJECT ABSTRACT Novel pathogens are constantly emerging and can cause devastating disease, and although we can rapidly sequence their genomes, we cannot yet predict how genotype relates to phenotype. While most approaches rely on sequence orthology to predict gene/protein function, recent technological advances will enable additional data modalities to be used with high predictive accuracy. Being able to rapidly determine functional information from genomic sequences is critical in determining appropriate interventions. Here, we focus on Candida auris, an emergent fungal pathogen of critical concern due to its high rates of antifungal drug resistance and its ability to spread and persist within healthcare settings. In previous work, we demonstrated the efficacy of co-expression analysis in gene function prediction in the fungal pathogens C. albicans and Cryptococcus neoformans using previously available RNAseq data. We further developed a method for high-throughput RNA sequencing in fungi to generate an equivalence of transcriptomic data for C. auris. To complement sequence-based analyses, I have identified cases where protein structure predictions can predict function in cases where sequence homology fails, and experimentally validated some of these predictions in C. auris. This application details experiments to address this gap between genotype and phenotype and provide a framework that can be applied for future emergent pathogens. My hypothesis is that a multi-modal approach combining sequence, expression, and protein structure provides superior functional prediction than sequence similarity-based methods alone. In Aim 1, I will use a high-throughput RNA sequencing approach to build a gene co-expression network to describe expression modules and transcriptional responses to stress in C. auris and predict gene function. In Aim 2, I will use AlphaFold2 predicted protein structures to identify distant evolutionary relationships that can then be leveraged to predict gene function. Both of these aims will be coupled with experimental validation of gene function using genetic and biochemical techniques, ensuring confidence in these predictions. Together, these studies will provide a generalizable framework for rapid functional annotation of genes in emerging pathogens, enabling future targeted therapeutic interventions.

NIH Research Projects · FY 2026 · 2026-06

Project summary Kinase inhibitors (KIs) represent critical advances in cancer treatment, yet their cardiac toxicity profiles are poorly understood. Recent clinical reports highlight significant cardiotoxicity associated with osimertinib, the sole approved therapy for EGFR T790M-positive non-small cell lung cancer (NSCLC). Approximately 3-5% of patients experience clinically significant cardiac adverse effects, including reduced left ventricular ejection fraction, heart failure, and arrhythmias, leading to treatment interruptions or discontinuation. Despite this significant clinical challenge and potential negative impact on patient survival, the underlying molecular mechanisms remain unexplored. Our preliminary studies in mouse models demonstrate early cardiac dysfunction linked to mitochondrial reactive oxygen species (mtROS) generation and increased NOX4 expression following osimertinib treatment. Clinical evidence also suggests that cardiac dysfunction, although often reversible, can seriously compromise the continuity of cancer treatment, emphasizing the urgent need for effective preventive strategies. We propose mitochondrial oxidative stress as a key driver of cardiotoxicity of osimertinib, warranting further mechanistic investigation. This research aims to elucidate the molecular mechanism of osimertinib- induced cardiotoxicity and to evaluate therapeutic strategies targeting mitochondrial dysfunction and oxidative stress through three specific aims. Aim 1 will determine the mitochondrial mechanisms underlying osimertinib-induced cardiotoxicity. Utilizing human-induced pluripotent stem cell-derived cardiomyocytes (hiPSC-CMs), we will measure mitochondrial function (oxygen consumption rate, mtROS levels, mitochondrial dynamics) to validate our hypothesis that mitochondrial bioenergetics disruption drives cardiac injury. Aim 2 will assess the role of NOX4 in mediating cardiac dysfunction. We will use transgenic and knockout mouse models, specifically altering cardiac NOX4 expression, to define its contribution to osimertinib-induced oxidative stress and mitochondrial impairment. In aim 3 we will evaluate cardioprotective strategies with mitochondrial-targeted antioxidants and NOX4 inhibitors. We will test MitoQ (mtROS scavenger) and setanaxib (NOX4 inhibitor), individually and in combination, to assess their efficacy in preventing osimertinib- induced cardiac damage both in vitro and in vivo. This study addresses a critical clinical issue by uncovering novel molecular insights into KI-induced cardiotoxicity, specifically identifying mitochondrial oxidative stress and NOX4 as therapeutic targets. Our findings aim to mitigate cardiac side effects associated with osimertinib, enhancing the clinical safety and efficacy of targeted cancer therapies, and thereby enabling uninterrupted cancer treatment and improving patient outcomes.

NIH Research Projects · FY 2026 · 2026-05

ABSTRACT There is increasing knowledge that volunteering is salutary for volunteers’ cardiovascular health. At the same time, more than 50% of adults over the age of 50 in the U.S. report at least one cardiovascular risk such as hypertension, high cholesterol, obesity, and chronic inflammation. Despite decades of research indicating that frequent volunteers show better cardiovascular disease (CVD) biomarkers, little is known whether frequent and sustained volunteering affects change in CVD biomarkers in multiple population subgroups, net of selection into volunteering. Further, genetic susceptibility to CVD biomarkers has never been studied in the context of volunteering. Our preliminary data show that frequent volunteering (200+ hours a year) predicts favorable CVD biomarkers, including chronic inflammation, systolic, and diastolic blood pressure in longitudinal analysis even when selection effects are considered through inverse probability treatment weighting. This highlights a critical need for understanding the pathways by which genetic, social, and behavioral factors affect cardiovascular health in older adults (NIA strategic research priorities B-2). In response to PA-20-185 and NOT-AG-21-020 Maximizing the Scientific Value of Secondary Analyses of Existing Datasets, the present study uses the Health and Retirement Study and seeks to understand whether changes in volunteering are linked to CVD biomarkers over a decade after adjusting for selection into volunteering and pre-baseline characteristics, and whether these links are stronger for multiple genetic, demographic, and socioeconomic subgroups. Using seven CVD biomarkers and polygenic risk scores, this study addresses three specific aims: Aim 1) examine the longitudinal effects of sustained volunteering on CVD biomarkers (N=18,847), Aim 2) test the associations between genetic predictors of CVD biomarkers, volunteering and CVD biomarkers in multiple ancestry groups (European N=8,400, African N=1,605), and Aim 3) assess the effect heterogeneity of volunteering on CVD biomarkers in multiple genetic, demographic, and socioeconomic subgroups. This project seeks to quantify the effects of volunteering on multiple CVD biomarkers while addressing important questions about selection effects and genetic susceptibility for a better causal inference. Addressing this gap in research is critical for developing new public health policies and biobehavioral and social interventions for heart-healthy older adults.

NIH Research Projects · FY 2026 · 2026-05

Abstract (30 lines) Antibody Drug Conjugates (ADCs) have made tremendous progress in the clinic with 9 new FDA approvals in the past six years and increasing use in combination with other agents, including first-line cancer therapies. ADCs have shown striking responses in combination with immune checkpoint inhibitors (ICIs), and these drugs are ideal agents for immunotherapy due to immunogenic cell death (ICD) from the payload, selective delivery that avoids immune suppression, and direct immune activation via the antibody Fc-domain. However, a major challenge in developing ADC immunotherapeutics and combinations is the lack of mouse cell sensitivity to payloads in syngeneic models and deficiency of humanized models to capture immunosuppressive effects. Therefore, there is an urgent need to outline how ADCs drive immune responses so more effective agents and combinations can be pursued in the clinic. The long-term goal of this research is to quantify the mechanisms behind ADC immune activation to design clinically effective ADC therapeutic combinations. We have identified unique payloads with high potency in mouse and human cells, thereby enabling the study of ADC immune effects at clinically relevant doses. The objective of this proposal is to use these novel payloads to delineate the mechanisms behind ADC immune stimulation and rationally design immunostimulatory ADC therapies. Our central hypothesis, backed by data in multiple syngeneic models and enabled by the unique payloads and protein design from our research groups, is that selective Fc-receptor binding ADCs with enhanced Fc-effector function ‘carrier doses’ of antibody will elicit maximum ICD and Fc-effector function to drive strong innate and adaptive immunity. We have engineered High Avidity Low Affinity (HALA) antibodies that automatically “tune” the number of ADC payloads delivered per cell based on the expression level, enabling efficient delivery in both high and low expression tumors. By modulating the antibody target affinity and Fc domains, we can rationally and independently control ADC payload delivery to cancer cells and immune cells while maximizing Fc-effector function. This unique toolbox will be used to test our central hypothesis through three specific aims: identify the most effective payload class for immune stimulation at clinically relevant doses, engineer the Fc-domains on the ADC and carrier antibody to maximize Fc-effector function and Fc-mediated payload delivery, and select the class of immune agonist payload to induce durable complete responses. We will first compare the immune effects of two major classes of ADC payloads in solid tumors, microtubule inhibitors and topoisomerase inhibitors, for ICD and Tcell recruitment. Next, we will selectively delivery these payloads to cancer and/or immune cells via Fc-engineered antibodies to isolate the impact of Fc-effector function from Fc-mediated payload delivery. Finally, we will leverage innate immune agonists to overcome the myeloid suppression within the tumor microenvironment seen with previous ADC therapy. The successful completion of these aims will enable the design of effective ADC regimens for inducing durable complete responses via selective immune activation.

NIH Research Projects · FY 2026 · 2026-05

ABSTRACT Each year, nearly $350 billion in Medicare spending is distributed across approximately 3,500 acute US hospitals based on a complex set of administrative technicalities. One important technicality is the hospital wage index, which standardizes hospital payments by local labor costs. However, hospitals can obtain exceptions to the wage index formula, resulting in ~$2 billion in additional hospital payments, which are considered by many to be economically unjustified. Compounding these distortionary effects is the wage index’s budget neutrality mandate, such that higher spending from increasing numbers of wage index exceptions is offset by lower payments to all hospitals. Together, the exceptions and offsets may either improve or erode some hospitals’ ability to hire staff and provide high-quality care, with implications for sicker and poorer patient populations who may receive poorer quality of care, thus making the wage index regressive and harmful. Moreover, hospitals receiving exceptions may use additional revenue to shift existing patients or admit new ones into higher-paying services, thereby shifting the composition of services and potentially restricting access to lower-paying services. We will explore the effects of Medicare’s hospital wage index, by examining (1) financial, (2) staffing and quality and health outcomes, and (3) access and costs (because of changes in the mix of hospital services) associated with exceptions and offsets, using 100% Medicare claims and wage index data. Innovation: While of equal or greater impact on hospital revenue, relative to other Medicare payment policies and reforms, the wage index has had limited study. Our econometric analyses can thus offer novel insights beyond current work that primarily consists of reports from contractors and agencies that have not assessed staffing, access, and health effects of the wage index exceptions and budget neutrality offsets. Impact: While theoretically a reasonable accounting tactic, when coupled with unjustified exceptions, budget neutrality may lead to undesirable and unintended effects related to hospital investments and quality, with important implications for older adults’ health. Fewer or lower-quality services, and lower nursing staffing ratios under these remediable payment distortions could diminish patient safety and increase adverse events. Given the push to address the adequacy of payments to ensure patient care access and quality, and growing understanding that Medicare policies may harm less resourced providers, our work can inform future wage index technical choices. Decision makers could use our findings to help understand and redirect reimbursements (without wage index exception distortions) to improve access to certain types of care.

NIH Research Projects · FY 2026 · 2026-05

PROJECT SUMMARY Alcohol, tobacco, and other drug use (ATOD), sexual health risks, and postpartum depression (PPD) are common and significant interrelated factors that are associated with poor health consequences for pregnant women and their infants, especially among rural, under-resourced communities. Thus, there is an urgent need to simultaneously address these health risks together during this vulnerable time. While pregnancy has been recognized as a window of opportunity in which to intervene, there are no empirically supported interventions tailored to specifically address these growing public health concerns together in rural women during pregnancy and postpartum. The objective of this R01 study is to fill this critical gap by building upon our promising R21/R01 findings by (1) partnering with a community advisory board to adapt and optimize the existing Health Check-up for Expectant Moms (HCEM) web-delivered Screening, Brief Intervention and Referral to Treatment or Prevention (SBIRT/P) program to include the interconnected risks of tobacco use and postpartum depression (PPD) among rural pregnant women (herein referred to as HCEM+), and (2) testing the efficacy of the HCEM+ in reducing ADOT, STI, and PPD risk more than a time and information matched control condition in rural pregnant women seeking prenatal care. This research addresses cross-cutting priorities in line with NIDA’s Strategic Plan to advance science on drug use: (1) prioritizing research to combat stigma and improve engagement in treatment, (2) developing and enhancing culturally responsive and tailored interventions, and (3) delivering care for substance use and co-occurring health conditions such as STIs and mental illness. We propose a two-group, randomized controlled trial in which a sample of 250 high-risk rural pregnant women attending prenatal care will be assigned to either (a) a web-delivered, two-session SBIRT/P plus two booster sessions consistent with motivational interviewing and informed by the Information-Motivation-Behavior (IMB) model, the HCEM+, or (b) a web-delivered control condition. Web-delivered follow-up assessments will occur at 8 and 24 weeks antenatally, and at 6 weeks postpartum, extending outcomes to the postpartum period. Specific Aim 1 is to test the hypothesis that HCEM+, compared to an attention, time and information matched control condition, will reduce unprotected sexual occasions and ADOT use among at-risk pregnant women during pregnancy at 2 and 6-months follow-up, and will increase treatment engagement. Specific Aim 2 is to test the hypothesis that HCEM+, compared to control, will reduce STIs and ADOT use at 6 weeks postpartum and will result in better birth outcomes and reduced rates of PPD. An economic evaluation of the costs of the HCEM+ will occur to guide future implementation and dissemination. Results of this program of research are expected to inform the development of a practical, cost-effective, high-reaching web-delivered SBIRT/P program tailored to reach high-risk rural and under-resourced women with extended impact to the postpartum period.

NIH Research Projects · FY 2026 · 2026-05

PROJECT SUMMARY/ABSTRACT This K23 award will facilitate Dr. Grau’s transition into an independent investigator who develops and tests scalable interventions with attention to health disparities to meet the variation in needs among individuals with post-traumatic stress disorder (PTSD) and hazardous alcohol use (HAU). Targeted research and training activities will extend his knowledge and build his expertise in developing and testing scalable interventions that integrate therapist-delivered and digital components to effectively engage and treat patients with PTSD+HAU in under resourced community settings like Federally Qualified Health Centers (FQHCs). Training: Dr. Grau proposes a comprehensive training plan with the following training aims: (1) Develop expertise in mobile health interven-tions, (2) Gain skills in qualitative data collection and analysis and (3) Acquire key skills in and knowledge of optimization trial design and conduct. Context: PTSD is an extremely damaging psychiatric condition when left untreated, especially for individuals with low-income who are served in FQHCs. Brief, modified evidence-based PTSD treatments are effective and feasible in FQHCs; however, co-occurring problems, most notably HAU, negatively impact treatment engagement and effectiveness. As such, there is a critical need to develop scala-ble interventions that treat PTSD+HAU while maximizing engagement in under resourced community settings such as FQHCs. Responsive to the NIMH Strategic Plan, Goal 3 (Strive for Prevention and Cures), Objectives 3.2 (Develop strategies for tailoring existing interventions to optimize outcomes), and 3.3 (Test interventions for effectiveness in community practice settings), the overall research objective is to develop and test a multimodal intervention that integrates therapist-delivered and digital interventions to treat PTSD+HAU in FQHCs. Re-search Plan: Aim 1 will assess the feasibility and acceptability of three stepped care, therapist-delivered inter-vention components for PTSD+HAU in our partner FQHC. Aim 2 will refine the therapist-delivered components and develop digital components (e.g., personalized text messages) in preparation for a PTSD+HAU hybrid ex-perimental design (HED). Aim 3 will assess the feasibility, acceptability, and preliminary effectiveness of a PTSD+HAU HED in FQHCs combining therapistdelivered and digital interventions to maximize engagement in treatment. Aim 3 results will inform a fully powered HED (future R01 submission) to create a multimodal adap-tive intervention for PTSD+HAU with patients in community health settings. Key innovations include state-of-the-art training, PTSD+HAU scalable intervention development with real world patients in community settings, and use of the HED design. Optimization of adaptive interventions for community patients with PTSD+HAU is a critical next step and will have significant impact on PTSD treatment in FQHCs.

NIH Research Projects · FY 2026 · 2026-05

Project Summary/Abstract There is a 10 to 26-fold higher risk of maternal mortality among patients with sickle cell disease (SCD) compared to the general population. Venous thromboembolism (VTE) accounts for nearly 10% of maternal deaths in the United States (US). Reported incidence of VTE during pregnancy and postpartum among patients with SCD ranges from 3-17%, but precise incidence of VTE when accounting for risk factors like SCD genotype or thromboprophylaxis use is unknown. Additionally, routine recommendation for thromboprophylaxis is complicated by higher rates of postpartum hemorrhage in this population. A recent Delphi panel confirms persistent clinical equipoise, but patient perspectives on thromboprophylaxis use in this medically vulnerable period have not been elicited. High-quality interventional studies and guidelines are urgently needed. The long-term goal of this proposal is to improve outcomes and standardize prevention of VTE and bleeding in pregnant and postpartum patients with SCD to improve maternal outcomes. In Aim 1, we will determine VTE and bleeding incidence in patients with SCD by building a data repository of pregnant and postpartum patients with SCD focused on factors associated with thrombosis and hemostasis. In Aim 2, we will elicit patient preferences around thromboprophylaxis using semi-structured interviews followed by a discrete choice experiment to elucidate patient perspectives. This will be critical to integrate into VTE guidelines and full clinical trial design. In Aim 3, we will assess the feasibility of enrolling and retaining postpartum patients with SCD into a randomized trial of thromboprophylaxis vs usual care (no thromboprophylaxis) that will allow for optimization of trial procedures and inform number of centers, time, and budget required for the full phase 3 trial. Completion of these projects will provide the foundation for an R01 grant to support the long-term research goal of a high-quality randomized trial with integrated patient-reported outcome measures that will result in guidelines on optimal VTE prevention for pregnant and postpartum patients with SCD. This research will be complemented by training that will cultivate expertise in health disparities and women’s health research, interdisciplinary and multicenter research, cohort development, mixed methods research, and clinical trial research through formal coursework, workshops, seminars, and a strong team of mentors and collaborators. The work will take place in partnership with multiple comprehensive sickle cell centers that have a track record of collaboration as well as a home institution known for research innovation and early-career investigator success. Together, this research proposal and training plan target the primary investigator’s long-term goal of becoming an independent patient-oriented investigator in health disparities and women’s health in classical hematology. By approaching this problem through 3 independent but inter-related aims, we will fill an important knowledge gap around VTE rates and prevention in pregnant and postpartum patients with SCD, and will also lay the groundwork for an R01 level project.

NIH Research Projects · FY 2026 · 2026-05

PROJECT SUMMARY/ABSTRACT The CardioExcyte 96 is an advanced, label-free, impedance-based electrophysiology system designed for high- throughput, real-time monitoring of cardiac cell activity. Utilizing 96-well plates, it enables the non-invasive measurement of key cardiac parameters such as action potentials, contractility, and heart rate variability without the need for electrodes or dyes. This technology provides a powerful, scalable solution for assessing cardiac function, making it highly suitable for studies involving drug-induced cardiotoxicity, cardiovascular diseases, and diverse cell models. A major limitation in current cardiac research is the lack of platforms that combine high- throughput capability with detailed, non-invasive electrophysiological analysis. This gap has slowed progress in critical areas like drug safety testing, disease modeling, and personalized medicine. The acquisition of the CardioExcyte 96 will directly address this need by providing our institution with cutting-edge technology to enhance both the quality and efficiency of cardiovascular research. Integrating this system into existing workflows will support a wide range of investigations in cardiac electrophysiology, offering researchers the ability to generate high-resolution, real-time data that can accelerate discovery. The primary objectives of this project are to improve the accuracy and throughput of cardiac screening in drug development, advance studies on arrhythmias and cardiotoxicity, and foster collaboration across multiple research domains. Overall, the CardioExcyte 96 will significantly strengthen our institution's research infrastructure, enabling scientists to tackle key challenges in cardiovascular biology and therapeutic innovation more effectively.

NIH Research Projects · FY 2026 · 2026-05

PROJECT SUMMARY Preventable medication errors are a global problem that can cause significant patient harm and annually incur costs of $42 billion worldwide. In the United States, 3 million outpatient medical appointments, 1 million emergency department visits, and 125,000 hospital admissions each year are the result of medication errors. Medication errors result in 3 million outpatient medical appointments, 1 million emergency department visits, and 125,000 hospital admissions each year. Astoundingly, over 4 billion prescriptions are dispensed every year in the United States alone. Although dispensing error rates are generally low at 0.06%, the sheer volume of dispensed medications translates to 2.4 million incorrectly dispensed medications each year. In the pharmacy, dispensing errors arise when pharmacists do not detect that the medication filled inside a prescription vial is different from the medication ordered on the prescription’s label. These dispensing errors can result in patient harm, added strain on the healthcare system, and costly legal action against the pharmacy. Artificial intelligence (AI) can be employed to assist in the verification process to help avoid dangerous and costly pharmacy dispensing errors. However, for the human-AI partnership to function optimally, the AI should be capable of determining the relative risks of medication errors (e.g., warfarin vs. vitamin C, kidney function, pregnancy status) while encouraging providers to make sound cognitive decisions such that optimal trust is maintained (i.e., catching errors), and temporal and cognitive demand is reduced (i.e., improving efficiency and avoiding alert fatigue). Risk-sensitive classification is critical when misclassification errors widely vary in frequency and severity. Imperative to this goal is to design AI from which risk-sensitive information can be extracted and conveyed to calibrate user’s trust in AI as either over-trust or under-trust can lead to near miss and incident errors. This proposed project will further our knowledge for designing risk- sensitive AI outputs and inform the development of AI models that encourage pharmacy staff to make sound clinical decisions that lead to better patient outcomes while improving work-life at lower costs of care. This study develops risk-sensitive AI methods in the context of medication images classification and designs effective AI advice and reasoning that lead to lower cognitive demand and increased trust in the AI. Our hypothesis is that risk-sensitive AI will lead to improved pharmacist work performance and more calibrated trust. The objectives of this proposal are to: 1) design risk-sensitive artificial intelligence to double-check dispensed medication images in real-time; 2) evaluate changes in pharmacy staff trust due to the use of risk- sensitive artificial intelligence; and 3) determine the effect of risk-sensitive artificial intelligence on pharmacy staff work performance.