Johns Hopkins University

NIH Research Projects · FY 2025 · 2025-09

ABSTRACT Shigella is a primary cause of moderate-to-severe diarrhea in children living in impoverished areas of the world. Shigella is known for causing dysentery (blood in the stool). However, majority of the children infected with Shigella present with watery diarrhea. The current World Health Organization (WHO) guidelines for treatment of shigellosis recommend treatment with antibiotics in the presence of visible blood in the stool. Thus, the non- dysentery Shigella associated watery diarrhea (NDSD) cases would not be treated with antibiotics. The absence of dysentery does not necessarily indicate a low risk of death and does not rule out Shigella as a cause of diarrhea. In particularly vulnerable younger children or with malnutrition, identification and treatment of Shigella infection might be lifesaving. Consequently, a critical question remains to be answered. Should cases of NDSD be treated with antibiotics? It may be hypothesized that these cases, if identified quickly, should be treated with antibiotics to reduce clinical severity, improve intestinal pathology, improve long-term developmental potential, and even reduce mortality. Identification of such cases will require a rapid test to document these infections so that treatment can be initiated promptly and is evidence based. and Zambia. To address these critical questions, we will carry out a randomized placebo controlled clinical trial in Bangladesh to determine if antibiotic treatment of NDSD cases in children will improve clinical outcomes, gut health, and growth in children. In addition, we will introduce a novel, simple, and rapid test “RLDT” for the detection of Shigella that has been field tested and shown to be applicable to health care facilities in resource poor endemic countries. We will assess the acceptability and feasibility of implementation of the RLDT assay. This study will help determine if there is a need for policy change for the treatment of NDSD with antibiotics. Importantly, this study will validate the need for a rapid test capable of identifying patients who will benefit from antibiotics.

NIH Research Projects · FY 2025 · 2025-09

Xenotransplantation (XTx) represents a possible solution to the organ shortage crisis and is an imminent clinical reality with long-term xenograft survival in pig-to-nonhuman primate (NHP) heart and kidney large animal models, and short-term success in recent human decedent and clinical studies. We have recently reported consistent >8 months survival in consecutive cases of pig-to-baboon kidney xenotransplantation (KXTx) using source pigs with 10 genetic modifications. These data provide critical supporting evidence for the safety and feasibility of clinical kidney xenotransplantation (KXTx) and resulted in FDA clearance of the first-ever human clinical trial of a xenoorgan. However, these studies also identified new challenges that will need to be addressed to ensure safe clinical translation of preclinical data in xenotransplantation. The overall goal of this project is to address these remaining issues, to elucidate underlying mechanisms of graft loss and injury, and to test novel targeted strategies with the goal of facilitating clinical translation of XTx with consistent and durable graft survival. Accordingly, we have outlined the following specific aims: (1) to optimize a clinically relevant immunosuppression regimen consisting of FDA-approved medications, targeting specific pathways involved in both early and late graft loss, and to characterize the risk of sensitization associated with xenotransplantation; and (2) to evaluate the impact of vascularized thymus co-transplantation on xenograft survival. We will attempt to prolong kidney xenograft survival with FDA-approved immunosuppression by combining innovative strategies: preventing the early graft injury that leads to long-term xenograft dysfunction by targeting evidence-based pathways involved in ischemia reperfusion injury and xeno-specific rejection, using multi-KO and transgenic source pigs, and including the immunomodulatory strategy of vascularized thymic transplantation. If successful, our approach could provide a virtually limitless supply of xenogeneic kidneys for human patients to meet the demands of the organ shortage, and may enable reduction or elimination of lifelong immunosuppression.

NIH Research Projects · FY 2025 · 2025-09

PROJECT SUMMARY/ABSTRACT Congenital diaphragmatic hernia (CDH) is polygenic condition in which the fetal intestines and liver herniate into the thoracic cavity, resulting in lung compression and impaired pulmonary development. Despite being one of the most common and expensive surgical birth defects managed in neonatal intensive care units worldwide, the underlying biomolecular mechanisms of CDH lung hypoplasia remain unknown. Advances in state-of-the-art surgical critical care, including novel pharmacologic agents and extracorporeal membrane oxygenation, have failed to make a substantial impact in improving clinical outcomes in severely affected children, with an overall mortality remaining at 30%, largely due to the devastating degree of lung pathology. There remains a critical need to better understand CDH lung development to offer hope for affected patients. Our overall objective is to examine the mechanistic impact of an experimental prenatal surgical therapy, known as fetoscopic tracheal occlusion (FETO), and YAP/TAZ on CDH lung development. The mechanism of FETO’s impact on reversing CDH lung hypoplasia remains unknown. YAP/TAZ is the core kinase of the Hippo signaling pathway that has been shown to respond to mechanosensory stimuli during fetal lung patterning and differentiation. The proximal-distal fetal lung abnormalities observed with the human CDH phenotype are consistent with those of YAP/TAZ dysregulation in the setting of mechanical compression (reduced intrapulmonary pressures). Although transpulmonary pressures have also been shown to regulate epithelial differentiation, the interplay between FETO and YAP/TAZ translocation are not well understood. Our group has expertise in the creation and manipulation of an experimental CDH mouse model, as well as in the generation of human 3D lung organoids derived from induced pluripotent stem cells in fetuses with CDH. We will leverage these models to address the following aims: (1) To evaluate the role of YAP/TAZ signaling and tracheal occlusion during CDH fetal lung development; and (2) To determine whether tracheal occlusion modulates mechanical compression forces in CDH fetal lung morphogenesis through the YAP/TAZ signaling pathway. These aims are highly feasible given our promising preliminary data and tools currently at our disposal. We hypothesize that YAP/TAZ dysregulation plays an important role in CDH disease pathogenesis and can be reversed by tracheal occlusion. If the proposed aims are achieved, we will have a better understanding of the role of a mechanosensing pathway in CDH lung development and the underpinnings of an experimental prenatal intervention, fetoscopic endotracheal occlusion, and potentially uncover new therapeutic targets for affected children at the more severe end of the disease spectrum.

NSF Awards · FY 2025 · 2025-09

Computer proof assistants, software programs that verify the logical reasoning of mathematical proofs written in precise formal language, offer an exciting new paradigm for mathematical research, enabling large-scale collaborations and empowering individual researchers to interact with theorems in other subfields that can be found in large open-source libraries of formalized mathematics. Computer proof assistants are likely to become more integral to the working life of mathematicians in the future. As different proof assistants often implement the rules of different formal systems, mathematicians may even elect to prove certifiably-correct theorems in a non-standard “synthetic” foundation system. The PI will develop three project clusters that involve computer formalization of higher category theory in parallel with theoretical projects necessary to facilitate this work. The formalization projects each have several student collaborators, who are developing their skills with these tools while making significant scientific contributions. The first project will introduce (∞, 1)-category theory to Lean’s otherwise broad-ranging library Mathlib via the formalism of an ∞-cosmos, developed in prior joint work of the PI. This approach will leverage Mathlib’s existing bicategories library and largely sidestep the apparent difficulty in formalizing proofs that directly deploy the quasi-categories model. A second project also aims to formalize theorems about (∞, 1)-categories, but in a non-standard foundation system designed to make conceptually-simpler constructions and proofs fully rigorous. There is an experimental computer proof assistant Rzk that verifies proofs written in simplicial homotopy type theory, a formal system developed in prior joint work of the PI, and ongoing work to formalize (∞, 1)-category theory in this synthetic framework. This project aims to expand this system, which is insufficiently expressive to encompass the full theory of (∞, 1)-categories, without narrowing its semantics, which include (∞, 1)-categories defined internally to an arbitrary ∞-topos. The final project aspires to develop a prototypical synthetic theory of (∞, n)-categories by developing a new type theory for marked shapes to provide a finitary syntactic encoding of (∞, n)-categorical data with semantics in the new comical spaces model. These pen-and-paper developments will enable (∞, n)-category theory to be formalizable in the future, once a suitable computer proof assistant is built to implement the rules of this new proposed formal system. The medium-term objectives include specific formalization targets that will then be available to other users of Lean’s Mathlib and Rzk’s simplicial homotopy type theory libraries. The long-term objective is to make (∞, 1)-category theory and eventually also (∞, n)-category theory more accessible to non-experts, who could use the computer formalized proofs as ingredients in their work. 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 Invasive fungal pathogens cause 1.5 million deaths a year and Cryptococcus neoformans is the primary cause of fungal meningitis worldwide. Cryptococcus is a ubiquitous fungus that is inhaled from the environment and, through mechanisms that we still don’t understand, disseminates out of the lung and subsequently enters the brain. The Cryptococcus yeast morphotype has been widely studied, and the study of its anti-phagocytic capsule has been critical to combating this pathogen; however, the yeast cell type is not the only morphotype to consider in cryptococcal disease. Cryptococcus produces dormant and stress resistant basidiospores (sexual spores) that are smaller and better aerosolized than yeast and thus more likely to reach the lower airways. Importantly these spores have a distinct surface to yeast, lacking the anti-phagocytic capsule. Spores are the presumed infectious morphotype, yet due to difficulties associated in working with spores, the Cryptococcus spore surface remains undefined and relatively few studies exist evaluating spore-host interactions. Critically, Cryptococcus spores can can disseminate out of the host lung better than yeast which translates to spores of otherwise avirulent yeast causing disease in intranasal murine models of cryptococcosis. This preferential dissemination and disease are likely a result of spores being able to invade host lung cells better than yeast. As spores germinate into yeast, and become more yeast-like, this preferential internalization diminishes probably due to surface epitopes being masked as the yeast capsule is formed. The spore surface components that drive host cell invasion, dissemination and disease remain a mystery. This research, conducted in the Casadevall lab, will be centered on defining the distinct surface components of spores, determining which components drive preferential host cells invasion, and identifying the molecular mechanisms enabling Cryptococcus dissemination and disease. Previous work has shown that cell surface hydrophobicity plays a role in yeast phagocytosis. Additionally, spores have distinct surface sugar epitopes to yeast, suggesting a unique surface glycoproteome. In specific aim 1, the cell surface hydrophobicity of spores will be systematically perturbed and evaluated, and the spore surface proteome will be defined. These surface components will subsequently be probed for roles in host cell invasion. Once surface properties that drive host-cell invasion have been identified, the molecular mechanisms driving dissemination and disease can be identified. In specific aim 2, the role of spore internalization by specific host cell types in disease kinetics will be determined by identifying fungal surface components and host receptors that drive uptake by different resident lung cells. Next, the role of these interactions in murine models will be probed for changes in in vivo host cell invasion, dissemination and disease. This work will identify novel mechanisms of host cell invasion that drive dissemination and disease, which can subsequently be used in the development of novel diagnostic tools and treatments for invasive fungal diseases.

NSF Awards · FY 2025 · 2025-09

Liquid crystal elastomers are soft, rubber-like materials that contain special molecules called mesogens. Mesogens have unique properties that allow them to be manipulated with external forces, independently from the host polymer. Being able to directly manipulate mesogens gives rise to materials that are supersoft, can dissipate large amounts of energy, and can even function as actuators. Potential applications include biomedical implants with programmable dissipation, architected vibration isolators, football helmet liners, motorcycle riders and war fighters, and actuators for soft robotics. To date, most work on liquid crystal elastomers has been performed on material systems whose manufacturing is difficult to scale to the industrial setting. This project proposes to experimentally probe the mesogen scale processes that occur in liquid crystal elastomers, which will be made via economical and scalable batch mixing and cross-linking processes. The plan includes testing materials in several complex states of deformation and developing testable mathematical models for the materials’ behavior. All data and numerical implementations of these models will be made findable, shareable, and publicly available through data repositories and code hosting platforms, allowing for the effective design of engineering products that leverage the unique properties of liquid crystal elastomers. Lastly, the project will integrate undergraduate and high-school students in various aspects of the research to promote the development of the American STEM workforce, as well as engage in outreach to improve public scientific literacy and engagement. Liquid crystal elastomers have been widely promoted as possible materials for soft actuators and high damping materials. Past work on materials and models for engineering design with liquid crystal elastomers has been heavily concentrated on mono-domain materials that require special fabrication steps, which are difficult to scale to industrial settings. More promising from an economic perspective are poly-domain materials that can be made in simple batch processes. In this project, a panel of mono and poly-domain materials will be made using the same chemistry. The materials will be subjected to uniaxial tension, compression, biaxial extension, and plane strain compression, all while monitoring their director fields. The resulting data will be used to calibrate a viscoelastic mono-domain model, which will subsequently be utilized in a representative volume element (RVE) model of the polydomain materials. The RVE model will then be exercised as a tool to develop a continuum level polydomain model based on a variational modeling structure that employs a spatially averaged free energy function and dissipation function, together with a generalized Biot evolution law. 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

SUMMARY It is an exciting time for research in molecular biosciences. The scientific community has amassed a huge database of protein sequences and structures, and techniques to analyze their structures and stabilities have undergone steady improvement. These advances have helped fuel a revolution in computational methods, based on artificial intelligence (AI), to interpret protein sequence information and to predict new structures and sequences. Together, these advances will help treat disease and provide a deep understanding of how proteins work. Research in our lab focuses on protein structure, stability, assembly, and function. We have leveraged large sequence databases to discover ways to stabilize proteins, and to understand the sequence features that contribute to protein function. We have found that “consensus proteins”— where sequence is determined simply selecting the most frequent residue at each position—are extraordinarily stable. These proteins provide a route to design active and resilient proteins that can be used in therapeutic and industrial applications. In the next five years, we will expand our design strategy to include sequence correlations between groups of residues. These correlations have been important for the success of AI in predicting protein structures, and have been suggested to enhance protein stability, fitness, and activity. Our preliminary findings provide a different interpretation, and suggest a new and unrecognized way to stabilize proteins beyond consensus while maintaining biological activity. We will use a set of proteins developed in our lab to test and extend these findings. We will also use this set of proteins to test how well AI-based methods generate high-stability proteins, which will help to evaluate and improve current AI tools. In parallel, our lab studies the molecular fundamentals of a specific signaling system, the Notch signaling pathway, in cell differentiation and disease. We are focusing on a multiprotein transcription complex central to Notch activation, and have developed new methods to measure the overall energy of assembly and dissect the contributions of different parts of the complex. Beyond providing new methods for analyzing molecular complexes, we will learn how disordered chains can couple together distinct binding motifs to enhance binding and switch the complex between different states of assembly. Our studies will also reveal how different but related Notch molecules lead to different biological outcomes, and how disease mutations disrupt different steps in complex assembly.

NIH Research Projects · FY 2025 · 2025-09

PROJECT SUMMARY The Coronary Artery Calcium Consortium (CAC Consortium) is a large, multi-center, retrospective clinical cohort study funded from 2013-2015 by the NHLBI to study the cardiovascular and non-cardiovascular prognostic value of CAC scanning in clinical practice. Despite its productivity, a major limitation for the CAC Consortium is the relatively short follow-up, with vital status ascertainment last conducted in 2014. This limitation becomes more important in an era of 30-year risk prediction ushered in by the publication of the PREVENT equations, as there are no data on the implications of CAC scoring over the 30-year time horizon. We seek to leverage the agreement between the National Institutes of Health (NIH) and the National Death Index (NDI) to extend CAC Consortium follow-up, with important scientific implications for 30-year risk estimation in young to middle-aged adults (age 30-59). Under this proposal, a total of ~5000 patients aged 30- 59 will have 30-year follow-up, and ~30,000 patients will have at least 25-year follow-up, providing sufficient statistical power for our scientific aims. In Aim 1, we see to quantify 30-year survival in patients aged 30-59 with baseline CAC=0. We hypothesize the older patients will gain a great survival advantage compared to younger patients compared to the general age-matched population. In Aim 2, we seek to describe the 10- and 30-year prognosis of individuals aged 30-59 with low absolute CAC scores between 1 and 100. While these patients have a low absolute CAC score, their percentile score is high, which may correlate with similarly poor survival to old age compared to older patients with higher absolute CAC scores. In Aim 3, we seek to evaluate the improvement in 30-year cardiovascular mortality risk prediction when CAC is added to the PREVENT equations. This extended follow-up of the CAC Consortium will leverage previous NHLBI investment in this project and fill critical knowledge gaps that could not be addressed with any other dataset, with specific implications for the critical age range (30-59 years old) where guidelines recommend risk assessment over a 30-year time horizon. We believe this work will have specific implications for future ACC/AHA Prevention Guidelines, which will likely incorporate recommendations based on long-term risk prediction.

NSF Awards · FY 2025 · 2025-09

Erythrophagocytosis is a complex multiphysics process involving recognizing, engulfing, and digesting aged or diseased red blood cells (RBCs) by phagocytic cells. Biochemical signaling pathways mediated by ligand-receptor engagement have been considered as key factors in initiating and driving the phagocytosis of abnormal RBCs by tissue-resident macrophages in the spleen and the liver. However, growing evidence has underscored the effect of the stiffness of RBCs in modulating the engulfment process. Building on this evidence, the project proposes that erythrophagocytosis is not only governed by the biochemical signaling pathways but is also significantly impacted by the mechanics of RBCs. To validate the hypothesis and address the key question of how multiple biochemical signaling pathways and RBC biomechanics are intertwined in dictating the erythrophagocytosis, the project will develop an artificial intelligence (AI)-enhanced multiphysics and multiscale framework validated using multimodal experimental data. The project will apply this framework to quantify the impact of signaling pathways and RBC stiffness on macrophage-mediated RBC engulfment. The proposed framework is transformative to investigate the pathogenesis of various hemolytic anemia and the mechanisms of macrophage-based approaches for cancer immunotherapy. Integration of biochemical and biomechanical modeling using AI approaches bridges the gap between the spatial and temporal scales of molecular and cellular interaction, opening a new avenue to address a wide range of biological and biomedical questions. Research outcomes will be disseminated into three courses at three universities. The project will recruit undergraduate and high school students and actively involve them in the research. The project will develop two multiphysics models using different deep learning algorithms to perform multiscale analyses of erythrophagocytosis. In Model 1, the project will incorporate the role of RBC stiffness into the biochemical signaling model of erythrophagocytosis by adding a new pathway. This system-level model, which is suitable for making predictions across blood samples, will be built using an AI-enhanced pipeline consisting of identifiability analysis and systems biology-informed neural networks (SBINNs). While identifiability analysis is used to optimize model design, SBINNs enhance efficiency in inferring model parameters from limited experimental data. In Model 2, the project will integrate biochemical signaling models with biomechanical models to drive the multiscale process of erythrophagocytosis. This multiphysics and multiscale model enables the simulation of various subcellular processes, i.e., the formation of actin filaments and their interaction with the plasma membrane, and cellular level process including the interaction between the macrophages and their targets as well as the internalization of targets. The project will bridge the sub-cellular model and the cellular model using deep neural operators to improve the computational efficiency. Model 2 is feasible for investigating the molecular mechanisms underlying erythrophagocytosis at the single-cell level. The two proposed models will be informed and validated using data from existing and new phagocytosis experiments. In summary, the project will develop new multiphysics and multiscale models powered by deep learning to elucidate the complex interplay between biochemical signaling and biomechanics in regulating erythrophagocytosis. 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

More than 50% of people living with HIV (PLWH) encounter cognitive dysfunction, and chronic peripheral pain, in the setting of opioid drug abuse. Neuronal circuitry innervating from the prefrontal cortex to the striatum is important in decision-making. Additionally, dopaminergic projections from the ventral tegmental area (VTA) in the midbrain to the nucleus accumbens (NAc) and dorsal striatum are involved in reward and motivational behaviors. We reported that global suppression of secreted phosphoprotein-1 production (OPN/Spp1) increases the expression of the mitochondrial translocator protein (TSPO) in Iba1+ macrophages/microglia across several key brain regions involved in cognition including the substantia nigra (SN). Interestingly, a subset of tyrosine hydroxylase (TH) reactive neurons co-labeled with TSPO, or were closely positioned near TSPO+ TH- cells in the midbrain region. In this regard, substance use disorders (SUD) in PLWH and in particular methamphetamine (METH) continues to be a consequential comorbid condition impacting viral suppression and health outcomes. Findings using rat and mouse HIV-Tat transgenic models have provided insights about how METH alters the expression of genes required for dopamine synthesis, metabolism, and receptor trafficking, and the role of sex as a modifier. However, our understanding of how dopaminergic neuronal-glial communication is altered in vivo during HIV replication, and METH is not understood likely due to the daunting task of deconvoluting multiple intersecting variables. Moreover, we implicated mammalian target of rapamycin (mTOR) pathway activation by (OPN/Spp1) in a mechanism of neuroprotection. Whether mTOR-OPN/Spp1 signaling plays a role in microglial- dopaminergic neuronal crosstalk in HIV-METH infection-exposure in vivo in is unknown. In this R21 application for high-risk/reward ideas, we propose to use our expertise with HIV-infected humanized mice, SUDs and modeling, to develop a rational approach to mathematical model dynamic dopaminergic neural-glial network circuitry. Our overarching hypothesis is that neuro-glial cells upregulate OPN/Spp1 expression in response to HIV-1 infection, which stimulates mTOR pathway signaling thereby, activating neuroprotective signaling to preserve homeostatic neurocircuitry; with acute co-exposure to METH, these pathways are upregulated and reinforced in a time-dependent manner. We will interrogate gene expression among neurons and glia in the nigrostriatal and meso-limbic brain regions to resolve dopaminergic neuronal-glial interactions using prospectively collected in vivo time course data. The analyses will focus on identifying interactions in the presence of HIV infection, with and without ART and acute administration of METH. Our long-term goal is to gain insights into the therapeutic potentials of resilience from cognitive dysfunction and drug addiction. We expect that findings from this project will advance the understanding of immunomodulation and metabolic reprogramming during co-exposure to HIV-1 and METH and will provide avenues for translational and clinical research aiming at improving mental health and substance use.

NSF Awards · FY 2025 · 2025-09

Stars form out of clouds of gas found in galaxies. Most of this gas is in the form of cold atoms of hydrogen, but before stars can form, this gas must undergo several chemical and physical processes that are poorly understood. The investigators leading this proposal will analyze data from both the NSF-funded Green Bank Telescope (GBT) and the Atacama Large Millimeter Array (ALMA), which can be used to measure the amounts of hydrogen gas in a broad sample of galaxies. They will use this to test how the depletion timescales of these gas reservoirs depend on other measured galaxy properties, placing important constraints on the growth of galaxies. At the same time, they will train undergraduate researchers in the techniques of radio astronomy. This program seeks to understand the differences in atomic hydrogen (HI) depletion times using the SDSS-IV’s Mapping Nearby Galaxies at Apache Point Observatory (MaNGA) and HI-MaNGA (21cm follow-up for MaNGA) galaxy surveys to search for evidence of systematic variations due to (1) ionization/heating sources, (2) fractions of diffuse versus dense HI, and (3) internal motions (e.g., velocity dispersion and bulk non-rotational flows), all of which may alter the efficiency with which HI is processed. The investigators will add new data from the GBT and ALMA to quantify the molecular hydrogen (H2) fraction for a subset of galaxies to probe whether long HI depletion times are driven by inefficient H2 formation from HI or inefficient formation of stars out of H2. In parallel with these efforts, the investigator will use the GBT to fully complete the HI-MaNGA survey, improving its legacy value for the astronomical community. 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

Harmful algal blooms (HABs) are increasing in frequency and severity in lakes, rivers, and coastal areas around the world. Fueled by nutrient runoff and changing weather patterns, HABs threaten aquatic ecosystems, harm public health, and damage local economies including fisheries and tourism that depend on clean water. Despite the growing impact, major challenges exist to predicting when and where HABs will occur. This project aims to transform how we forecast these events by understanding the biology of one of the major microorganisms that cause them, cyanobacteria. By linking genetics and laboratory experiments to the environmental conditions that promote or inhibit cyanobacterial growth, we will determine which genes help these organisms thrive under different conditions. We will integrate this data-driven work with cutting edge mathematical models to enhance bloom forecasting. These models will help communities better manage water resources and protect public health. Ultimately, this research will not only improve our ability to forecast harmful blooms, but also enhance our broader understanding of how microorganisms respond to environmental conditions. This research addresses the central question of how cyanobacterial bloom dynamics will respond to changing environmental conditions by integrating molecular, ecological, and statistical approaches. The project will (i) map the ecological niches of key bloom-forming cyanobacteria under a realistic range of environmental conditions; (ii) identify the genetic basis of environmental fitness in the model cyanobacterium Synechococcus elongatus using a high-throughput barcoded mutant library; and (iii) develop a hybrid forecasting model that integrates mechanistic growth responses with correlative environmental models. This approach represents a significant advance over current HAB forecasting methods, which rely heavily on empirical correlations with environmental data and fail to account for microbial physiology or evolution. The research will generate a new class of forecasting tools that incorporate fitness landscapes and genotype–environment interactions, providing a mechanistic link between environmental variability and bloom dynamics. Findings will be broadly relevant to microbial ecology and evolutionary genetics, and will establish a generalizable framework for predicting ecologically important microbial behavior under environmental variability. 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

Part 1: NON-TECHNICAL SUMMARY The prevailing commercial lithium-ion batteries (LIBs) contain a flammable liquid electrolyte that can lead to major safety hazards. Replacing the liquid electrolyte with a nonflammable solid can alleviate these issues, but current batteries using solid electrolytes are unable to maintain high storage and fast charging capabilities. This project, supported by the Solid State and Materials Chemistry program in NSF’s Division of Materials Research, leverages a unique class of porous materials called metal-organic frameworks (MOFs), which are made of metal and organic components that are precisely arranged in an ordered network, as promising solid electrolytes. By selecting appropriate metal ions and organic compounds, the desired chemical and physical properties of the MOF can be tuned to improve battery performance. The expected outcome of this project is the acquisition of foundational knowledge to design solid electrolytes that are safe replacements to existing liquid electrolytes. Such advances are necessary for developing reliable next-generation batteries for portable electronics, electric transportation, and electric grid management. Additionally, through education and outreach activities this project promotes public scientific discourse through the training of early-career researchers in effective scientific communication, an accessible chemistry video series on battery research, and on-site research opportunities for high schoolers and community college undergraduate students. This project thus advances the frontier of energy storage devices, promotes public engagement in science and technology, and aligns with the national interest of a secure energy future. Part 2: TECHNICAL SUMMARY A major bottleneck in advanced energy storage technologies is related to challenges of the electrolyte. The prevailing commercial lithium-ion batteries (LIBs) contain liquid electrolytes that are flammable and can lead to major safety hazards. Owing to the increasing demand of high-capacity, high-power batteries, safety challenges with liquid electrolyte are exacerbated with scaling to large battery packs and to other more reactive chemistries, such as replacing Li graphite anodes in LIBs with Li metal anodes. Solid-state electrolytes can alleviate these issues, but they are limited by low ion conductivity and poor interfacial stability. This project, supported by the Solid State and Materials Chemistry program in the Division of Materials Research, leverages the diversity and modularity of a class of microporous metal-organic frameworks (MOFs), which are known for their molecular sieving properties for gas separation, as solid-state ion conductors. The objectives are to 1) elucidate the mechanism of Li+ transport in a Ca-based squarate MOF, 2) apply mechanistic insights obtained to other metal squarate MOFs to evaluate the role of microporosity on metal ion diffusion, and 3) evaluate the interfacial stability of squarate MOFs and their ability to facilitate reversible Li deposition. In the long term, the researchers plan to build a multidimensional map that connects structural and chemical factors of microporous MOFs to metal ion transport. The acquired knowledge informs the rational design of solid-state electrolytes for Li-based energy storage devices. This project also enhances public access to science, technology, engineering, and mathematics (STEM) through the training of early-career researchers in effective scientific communication, an educational video series entitled, ″Meet a Chemist,″ and on-site research opportunities for local high school students and undergraduates from community colleges. 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

Objective assessment of image quality (IQ) using task-based performance metrics is important for developing deep-learning image reconstruction and post processing algorithms, and for translating the champion algorithms to the clinics. Ideally, task performance evaluation should use human observers. But human observer studies are time consuming and expensive, therefore cannot be realistically applied to evaluating and optimizing algorithms during early-stage development. Computer-based human-performance mimicking model observers (MO) can substitute for human observers and hold great potential as a tool for IQ evaluation. However, MO studies are not often used for DL algorithm evaluation. One possible reason could be due to the weaknesses of MOs for task performance evaluation. Diagnostic tasks are complicated due to imperfect data acquisition, e.g., quantum noise, and the large patient anatomical variation. Historically, the patient anatomical variation is quantitatively intractable, while the quantum noise can be handled well by the known data acquisition model. In this context, the current paradigm of MOs circumvents our inability to quantify patient anatomical variation, but relies on multiple realizations of quantum noise to define a patient population. This approach leads to the intertwined weaknesses of (1) simplified task definitions and (2) burdensome data requirement, which may attribute to the absence of MOs in DL algorithm evaluation. The challenge of characterizing patient anatomical variation can now be overcome, thanks to the advent of score-based probabilistic diffusion models (DMs). Score-based DMs, in addition to generating image samples as in all generative models, have the unique capability of calculating the exact log-density (or log-likelihood) of image samples. This capability can be exploited to calculate (log-)likelihood ratio type test statistics and allows us to define a new paradigm of MOs for realistic clinical tasks with free-form, essentially unlimited signal and background variability, here “unlimited” means “to the extent of variation that the DM training data are curated for.” At the same time, relying on anatomical variation reduces the burdensome, multiple noise, data requirement, so that our new MOs are also data-efficient and applicable to patient data that do not come with multiple noise realizations. Our specific aims focus on (1) developing the computational framework of such diffusion-model enabled MOs, (2) validating MO performance using clinical detection and localization tasks. Our MOs break free from the historical confines that have hindered their adoption for routine task-performance evaluation of diagnostic image quality. They hold great potential for identifying promising early-stage algorithms, for offering a performance predictor that correlates well with diagnostic task performance, and for eventually translating the champion algorithms to clinical deployment for improved patient care.

NSF Awards · FY 2025 · 2025-09

Chromosomes consist of long DNA strands that hold the information coding for life. Chromosomes are extensively wrapped into spool-like structures called nucleosomes in all plants and animals, including humans. Nucleosome packaging provides the sophisticated levels of control needed for turning genes on and off and regulating cellular functions. This project is focused on understanding how nucleosomes slide along DNA and enable dynamic changes in its packaging. Nucleosomes can be actively moved by special enzymes called chromatin remodelers, but nucleosomes can also spontaneously slide within chromosomes. It is currently unclear how easily nucleosomes slide on natural DNA sequences, and how their mobility may be affected by other cellular factors. Nucleosomes are displaced and chromatin remodelers are often disrupted in diseases such as cancer; therefore, new information on nucleosome sliding will advance understanding of fundamental cellular processes important for human health. A new technique has been developed for this research that allows sensing of the force required to mechanically shift nucleosomes along DNA. This technique should be broadly useful to the scientific community for studying how chromosome-interacting factors affect DNA packaging. This project will offer research training opportunities for students in biochemical and biophysical science and includes outreach activities centered on DNA to engage middle school students in STEM. This project is designed to reveal how intrinsic mobility of the histone core on DNA is affected by DNA sequence, histone variants, and exogenous factors like RNA, transcription factors, and linker histones. This work will also determine the processivity and translocation speeds of ATP-dependent chromatin remodelers as they push nucleosomes along long DNA segments. These goals will be addressed by a combination of biochemistry, next-generation sequencing, and optical trap experiments. The results of these studies will provide new information about how nucleosomes are organized in native sequence contexts and reveal new ways of understanding how histone-DNA interactions intrinsically influence chromatin reorganization. This project is supported by the Genetic Mechanisms and Molecular Biophysics programs in the Molecular and Cellular Biosciences Division of the Biological Sciences Directorate and by the Chemistry of Life Processes program in the Chemistry Division of the Mathematical and Physical Sciences Directorate. 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 Fused in sarcoma (FUS) is an RNA binding protein (RBP) capable of undergoing phase separation in the nucleus and is crucial for proper cellular function. Mutations in FUS have been linked to several incurable age-dependent neurodegenerative diseases, including amyotrophic lateral sclerosis (ALS) and frontotemporal lobar dementia (FTLD), leading to progressive dysfunction and loss of neurons. Aberrant phase separation in ALS/FTLD-linked FUS mutants disrupts essential homeostatic mechanisms such as DNA damage response (DDR) and transcription regulation. Despite initial studies linking FUS with both genome maintenance and RNA-related functions, FUS' specific molecular mechanism and potential implications in neurodegenerative diseases, such as ALS/FTLD, remain elusive. We hypothesize that FUS subcellular localization changes under transcription inhibition and DNA damage and is dependent on FUS-RNA interactions. We propose that abnormal RNA interactions induced by ALS/FTLD-linked FUS mutants perturb this dynamic localization process under stress conditions. Advanced microscopy and next-generation sequencing approaches will be used in our model SH- SY5Y cells to test this hypothesis. Aim 1 will dissect the cellular mechanism modulating FUS dynamic localization under DNA damage and transcription stress conditions using immunofluorescence and high-resolution microscopy. Aim 2 will elucidate the RNA-dependent interactions influencing FUS localization through single molecule RNA fluorescence in situ hybridization (smRNA-FISH) and RNA immunoprecipitation sequencing (RIP- seq) before, during, and after stress induction. For Aim 3, we will employ high-resolution microscopy and RIP- seq to investigate how aberrant FUS-RNA interactions in ALS/FTLD-linked mutations disrupt FUS localization under stress, thereby contributing to disease onset. Collectively, these aims will provide mechanistic insights into the functions of FUS under DNA damage and transcription stress, and how these functions may differ in ALS/FTLD-linked mutants, shedding light towards understanding other RBP mutations in age-dependent neurodegenerative diseases. My proposed research is strengthened by collaborations with experts in neurodegeneration, ALS/FTLD, RNA biology, phase separation, next-generation sequencing, and high- resolution microscopy (see support letters). The activities outlined in this proposal, including collaborations, professional development opportunities, engagement in scientific conferences, mentoring students, and improving scientific communication and critical thinking skills, will allow me to successfully complete my Ph.D. and prepare me for a competitive postdoctoral position, ultimately paving the way for a career in academia.

NIH Research Projects · FY 2025 · 2025-09

Amblyopia is the leading cause of poor vision in infants and children. It arises because of abnormal visual experience early in life, during a critical window of development. Leading causes for the disruption of normal visual development are strabismus (misalignment of the visual axes between the eyes), anisometropia (mismatch in refractive error between the eyes) and deprivation (physical obstruction of one or both eyes). Clinically, amblyopia is diagnosed as reduced visual acuity in one eye that is not due to physical reasons and cannot be corrected optically. Consequently, much attention has been paid to amblyopic changes in early visual stages like the primary visual cortex (V1), and to development of treatments that can correct the loss of spatial vision (most prominently patching the weak, amblyopic eye), However, there are also deficits in higher visual functions localized outside of V1. The extent of these deficits, especially at the neural level, remains poorly understood, and even less is known about whether amblyopia treatments can overcome deficits in higher visual functions. The overarching goal of this project is to establish the ferret as a new animal model for studying amblyopia from the perspective of higher visual processing. Ferrets have a complex visual system with established similarities to the primate. This includes our recent demonstration that ferret PMLS functions as a higher visual area specialized for complex motion functions like motion integration, similar to primate MT. At the same time, larger cohorts of ferrets can be tested than is possible in primates, important for a disorder that can be quite variable in its depth between subjects, and is even more variable in the outcome of treatments. To establish ferrets as an amblyopia model, the work proposed here focuses on solving two problems. First, Aim 1 establishes a robust protocol for inducing amblyopia in ferrets. To mimic the human condition as closely as possible, we plan to trigger amblyopia by generating anisometropia early in life through a lens mounted in front of one eye. Second, Aim 2 will focus on establishing chronic recordings from flexible polymer probes to support longitudinal tracking of neural changes during amblyopia treatments. Together, these Aims will generate an experimental platform for future improvements of amblyopia treatments in human patients.

NIH Research Projects · FY 2025 · 2025-09

ABSTRACT A significant portion of the technical errors made by surgical trainees involve the improper use of force on patient tissue. For robotic minimally invasive surgery (RMIS), the improper force problem is exacerbated by the lack of haptic feedback of tool-tissue forces. Expert RMIS surgeons have learned over time to visually estimate these forces in a process known as visual-haptic acuity development. Unfortunately, no training tools currently exist for explicitly catalyzing visual-haptic acuity development in RMIS trainees. The overall objective of this early-stage trailblazer application is to develop and validate an innovative training tool that catalyzes visual-haptic acuity with titrated supplemental haptic feedback. The central hypothesis is that visual-haptic acuity is a critical component of tissue handling skill in RMIS that can be augmented during simulation-based RMIS training using titrated psychomotor-skill specific haptic feedback and assessed using robust measures of tool-tissue interac- tions. The rationale for this project is that tools to support development of visual-haptic acuity provides surgical educators and training institutions with the means to ensure every RMIS surgeon has mastered the tissue han- dling skill necessary to safely operate on patients. The central hypothesis will be tested through the pursuit of two specific aims: 1) Accelerate learning of RMIS visual-haptic acuity using titrated supplemental haptic feedback of tool-tissue forces and tissue-contact accelerations, and 2) Assess and predict RMIS visual-haptic acuity during simulated surgical training. In the first aim, user studies will be conducted to discover and evaluate the optimal haptic feedback titration approach for fostering visual-haptic acuity. In the second aim, structured human grading and data-driven methods will be developed and validated to predict and assess visual-haptic acuity, and the effi- cacy of these approaches will be assessed through surgical task performance on cadaveric tissue. The proposed research is innovative because it focuses explicitly on the development of new tools capable of augmenting and assessing visual-haptic acuity, a critical component of tissue handling skill in RMIS. The proposed research is significant because it will provide an objective, quantifiable, and repeatable means of accelerating tissue handling mastery in RMIS, thereby improving the overall safety of RMIS procedures, regardless of RMIS platform. Suc- cessful completion of these aims therefore enables the creation of validated curricular tools for training the critical psychomotor skills required to reduce iatrogenic tissue injury in RMIS.

NSF Awards · FY 2025 · 2025-09

Modern life depends on powerful computer chips that run everything from smartphones to medical devices. Making these chips requires creating incredibly small features, far tinier than the width of a human hair. To achieve this, the electronics industry now uses a special kind of light called extreme ultraviolet (EUV). This new technology allows the production of smaller, faster, and more efficient chips. However, a major problem is the lack of EUV tools to advance this technology, and they are not easily accessible. This project will install an EUV tool at Johns Hopkins University and make it available as a shared resource for scientists and engineers across the country. The facility will drive innovation in electronics and train the next generation of students to allow them to succeed in fields such as semiconductors, photonics, and quantum technologies, which are areas critical to the nation’s future economy and security. This project will establish a state-of-the-art facility to advance photoresist research in extreme ultraviolet (EUV) lithography. The project will enable systematic investigations that are not feasible with limited beamline access. The new EUV flood exposure tool combines a reliable discharge plasma source with precise dose control and efficient light delivery, providing stable and reproducible exposures. Integrated in situ diagnostics, including total electron yield measurements, Fourier transform infrared spectroscopy, and mass spectrometry, will allow direct observation of chemical changes and outgassing phenomena during exposure. These capabilities are essential for understanding the molecular mechanisms that govern EUV resist performance. Initial projects will include amorphous metal-organic framework all-dry resists, vapor-synthesized metal-containing resists, sequence-controlled polypeptoid resists, and solution-deposited inorganic sol-gel systems. Together, these efforts will broaden the chemical design space for EUV lithography, reveal new reaction pathways, and establish guidelines for sustainable, high-resolution patterning. By coupling in situ diagnostics with systematic material screening, researchers will be able to efficiently select promising resist candidates and define structure-property relationships, paving the way for higher sensitivity, reduced line-edge roughness, and environmentally responsible formulations. Intellectually, this effort will deepen fundamental knowledge of EUV-driven chemistry, inform resist design principles across diverse material classes, and strengthen the scientific foundation for future nanofabrication technologies. 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

Schizophrenia (SCZ) is a chronic neuropsychiatric disorder that affects 20 million people worldwide and is among the most burdensome of all health problems, with enormous implications for individual health, quality of life, and societal costs. Therefore, elucidating disease mechanism with the ultimate goal of developing improved treatment strategies is an urgent priority. Though SCZ is highly heritable, no singular genetic cause has been found and its genetic architecture is complex. A 2022 large genetic study identified rare genetic variants that confer substantial risk for SCZ. Among the 10 most significant is GRIA3, a gene on the X chromosome which encodes GluA3, the 3rd subunit of a major receptor mediating excitatory signals in the brain, the amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid receptor (AMPAR). AMPARs bind the neurotransmitter glutamate and are key components of the cellular mechanisms enabling the encoding, storage, and integration of information throughout the lifetime of an organism. The long-term goal of this proposal is for the principal investigator (PI) to develop as an early independent investigator at the intersection of Neuroscience and Psychiatry, and to leverage training with experts in basic neuroscience to better understand the pathological mechanisms underlying psychiatric disorders such as SCZ with the ultimate aim to identify new therapeutic targets. The major objectives of this proposal are to undergo training in concepts and techniques in basic neuroscience to investigate the functional consequences of SCZ-associated GRIA3 variants in vitro and gene expression changes in Gria3-knockout mice in vivo. The central hypothesis is that SCZ-associated variants in GRIA3 result in partial or complete loss of synaptic GluA3, and alter AMPAR assembly, trafficking, and kinetics, resulting in multiple downstream effects that are phenotypically relevant to SCZ. Aim 1 is functional characterization of SCZ-associated GRIA3 variants, including missense changes as well as those predicted to abrogate protein expression, in order to evaluate effects on RNA and protein levels, AMPAR assembly, GluA3-cell surface delivery, spine-trafficking, kinetics, and binding to interacting proteins, and synapse number and structure, and morphology in neurons and heterologous cells in vitro. Aim 2 is performing single cell transcriptomics of forebrain and various brain regions in Gria3-null mice of both sexes at 1 and 3 months of age followed by validation studies. Expected outcomes of the proposed work are elucidation of the consequences of SCZ-associated GRIA3 variants on AMPAR receptor structure and function in vitro and single-cell transcriptional changes associated with GluA3 loss in mice. In addition to the described Aims, this proposal implements a structured, individualized career development plan specifically designed to support the candidate’s career objectives and facilitate a transition to independence. This plan will involve the guidance of an expert mentoring team, course work, supervised grant writing, and hands-on technical training, all within a collaborative, rigorous, successful academic environment.

NIH Research Projects · FY 2025 · 2025-09

Summary Esophageal nociceptive sensations, such as heartburn and chest pain, are the major complaints that present in many esophageal disorders, including GERD. More than 30% of these symptoms are refractory to acid inhibition by PPIs, making it a significant treatment challenge. Bile acid is a potent substance that can trigger esophageal nociceptive sensations in addition to acid, but the underlying mechanism of its neuronal action is still unknown. Our recent study demonstrated that bile acid not only directly activates esophageal nociceptive C-fibers but also sensitizes their responses to TRPV1 agonist capsaicin. Whether MrgprX4, a newly discovered bile acid receptor, mediates bile acid-elicited activation and sensitization of esophageal C-fibers and enhances their responses to acid are important yet unanswered questions. In the present proposal, we address the hypothesis that MrgprX4 contributes to PPI-refractory esophageal nociception by mediating bile acid-induced activation (independent of acid) and sensitization (increasing acid sensitivity) of esophageal nociceptive C-fibers. Aim 1 will characterize MrgprX4 expression in esophageal afferent C-fiber neuron subtypes. Using MrgprX4-expressing mice, we will first clarify MrgprX4 mRNA expression and co-expression with transcripts of nociceptive neurons by single-cell RT-PCR in esophageal-labeled afferent neurons. We will then characterize MrgprX4 protein expression in esophageal-labeled afferent neurons regarding neuron diameters and co-expression of C-fiber markers (i.e. CGRP/IB4). We hypothesize that MrgprX4-positive neurons are small-size unmyelinated C-fiber neurons (but not NF-200-positive Ad-fiber neurons). Next, we address the hypothesis that MrgprX4 is selectively expressed in subsets of TRPV1-positive (acid-sensitive) nociceptive C-fiber neurons with their nerve fibers richly distributed in esophageal mucosa. Aim 2 will determine MrgprX4-mediated activation of esophageal nociceptive C-fiber subtypes. Our previous study demonstrated that bile acid DCA directly activates esophageal vagal nodose and jugular C-fibers. Using our newly established MrgprX4-expressing and MrgprX4-/- mouse lines, we will address the hypothesis that MrgprX4 specific agonists (SML3371 and nateglinide), mimicking bile acid-induced effect, directly activate esophageal nociceptive C-fiber subtypes. We will then address the hypothesis that bile acid- induced activation effects on the neuron soma and the nerve terminals of esophageal vagal and DRG C-fiber subtypes are absent in the MrgprX4-/- mouse line. Aim 3 will determine MrgprX4-mediated sensitization of esophageal C-fiber subtypes. We will address the hypothesis that MrgprX4 mediates bile acid-induced enhancement of acid response in esophageal TRPV1-positive C-fibers. Using MrgprX4-expressing mouse line, we will first determine bile acid-induced sensitization of acid response in esophageal C-fiber subtypes. We will then determine whether MrgprX4 selective agonists mimic bile acid-induced excessive acid responses in esophageal C-fiber subtypes. Lastly, we will determine, in MrgprX4-/- mouse line, bile acid and MrgprX4 agonist- induced effects on acid responses in esophageal C-fiber subtypes.

NIH Research Projects · FY 2025 · 2025-09

PROJECT SUMMARY Systemic bacterial infections are a major cause of morbidity and mortality globally, and antibiotic treatment failures constitute a major global health issue. In recent years, there has been increasing attention to previously underappreciated mechanisms of antibiotic treatment failure, specifically the role of phenotypically distinct bacterial subpopulations which fail to be eliminated. During an infection, individual bacterial cells are differentially exposed to a wide range of host-derived stressors. This can result in the emergence of phenotypically distinct subpopulations with reduced susceptibility to antibiotics – a phenomenon termed antibiotic persistence. Antibiotic persistence poses a significant therapeutic challenge; surviving bacterial subpopulations can promote long-term and relapsing infections. The development of new therapeutic strategies for antibiotic persistent infections is currently limited by major gaps in our understanding of the mechanisms responsible for the development and maintenance of antibiotic persistence in the context of a mammalian infection. Our laboratory has developed a mouse model for prolonged antibiotic treatment of a systemic bacterial infection, as a system for studying antibiotic persistence within the host environment. Mice are inoculated intravenously (i.v.) with the Gram-negative bacterium Yersinia pseudotuberculosis (Yptb). Yptb is a natural pathogen of humans and rodents, and there are many genetic tools well-established in Yptb. Upon i.v. inoculation, the bacteria disseminate to deep tissue sites (primarily the spleen), where they form structures referred to as microcolonies by 48 hours post-infection. Microcolonies consist of a bacterial center surrounded by host immune cells (neutrophils and monocytes/macrophages). Bacterial centers within each microcolony are complex and dynamic populations, with distinct bacterial subpopulations, making them a powerful model for studying phenotypic heterogeneity. The central hypothesis of this project is that exposure to host- derived stressors will induce persistent bacterial phenotypes, which will be further induced and maintained during the course of antibiotic treatment, until antibiotic levels wane. Here we will use a new bacterial RNA sequencing approach, along with existing genetic tools to study antibiotic persistence mechanisms in our newly developed prolonged treatment mouse model. Through this project we hope to provide mechanistic insight to inform the development of new treatment strategies, including combination therapies to specifically target multiple populations.

NIH Research Projects · FY 2025 · 2025-09

Project Abstract This project aims to assess the potential of pregnenolone, a signaling specific negative allosteric modulator (NAM) of the CB1 cannabinoid receptor, to reverse symptoms of cannabis intoxication. As defined by the DSM- 5, cannabis intoxication involves neuropsychiatric symptoms such as anxiety and impaired motor coordination and physiological symptoms including dry mouth and tachycardia arising shortly after cannabis use. These symptoms can be distressing and associated with significant clinical complications such as car accidents, cardiac arrhythmias, and psychotic episodes. Cannabis’ increasing popularity and potency has seen a surge in emergency room (ER) visits for management of intoxication, yet there are no medications indicated for the treatment of cannabis intoxication. NAMs of the CB1 receptor—the cannabinoid receptor whose activation by tetrahydrocannabinol (THC) facilitates intoxication—have shown promise as novel treatments for cannabis intoxication. Pregnenolone, an endogenous neurosteroid often marketed as a supplement, has been shown to act as a CB1 receptor NAM specifically attenuating the effects of THC. Preclinical studies demonstrating pregnenolone’s capacity to treat cannabis intoxication symptoms have led to interest in applying its mechanism to drug development yet its ability to reverse active intoxication symptoms have not yet been studied in humans. We will therefore set up a within-subjects, double-blind, placebo-controlled human laboratory study investigating whether pregnenolone can treat cannabis intoxication symptoms. Healthy, cannabis-naïve individuals who meet inclusion criteria will be randomized to one of four conditions: cannabis brownie and placebo capsule, cannabis brownie and 250 mg pregnenolone capsule, cannabis brownie and 500 mg pregnenolone capsule, and placebo brownie and placebo capsule (all cannabis brownies will contain 25 mg THC). Following study drug administration, participants will complete questionnaires evaluating subjective effects (via the Drug Effect Questionnaire), psychotomimetic symptoms (via the Positive and Negative Syndrome Scale) and cognitive/psychomotor impairment (via a battery of cognitive assessments). Heart rate will also be assessed. Blood will also be collected at various timepoints for later measurements of serum pregnenolone, THC, and THC’s metabolites 11-OH-THC and THCCOOH to assess any dose-dependent effects of pregnenolone on cannabis intoxication. We hypothesize that pregnenolone administration will be associated with significantly fewer cannabis intoxication symptoms compared to placebo as evidenced by lower scores on the questionnaires, and that higher levels of pregnenolone will also be associated with fewer subjective effects and signs of impairment associated with cannabis intoxication. Results from this study will provide information on whether agents that act as CB1-NAMs can serve as rescue therapies for cannabis intoxication symptoms, while also giving insights into whether pregnenolone itself could fulfill this role.

NIH Research Projects · FY 2025 · 2025-09

Abstract/Project Summary Biobanks, electronic health records, and clinical registries have collectively amassed a massive amount of data on people’s genetic makeups and their clinical trajectories. Information in these data sources, if properly synthesized, provides us an opportunity to identify treatments precisely tailored toward individual patient profiles. However, heterogeneity across sites in patient populations, data encoding procedures, and clinical practices pose significant statistical challenges, compounded by computational challenges these massive data pose. We will meet these statistical challenges by combining Bayesian hierarchical models, biomedical ontological systems, and high-dimensional transfer learning methods: these tools will allow us to bring together the larger amount of data from diverse sources to investigate biomedical questions beyond the scope of any single source. We will scale the developed statistical framework to sizes of modern genetic and clinical data by combining state-of-the-art computational algorithms with hardware optimization techniques, including use of graphical processing units. We will deliver the end products as open-source software packages for deployment in research and clinical settings. We will demonstrate the proposed statistical and computational innovations through direct applications to: genetic risk predictions for under-represented populations and subgroup effect estimation for comparative effectiveness studies of type-2 diabetes treatments using a federated network of healthcare databases. The machinery is more broadly applicable, however; it for example allows integrating insights across data sources that provide different but functionally-related metabolites and/or proteins. The proposed development thus constitutes an important step towards extracting more scientific insights on disease mechanisms and effective treatment strategies by synthesizing information across heterogeneous data sources.

NSF Awards · FY 2025 · 2025-09

Since Charles Darwin's studies of evolution, the field has been fascinated by adaptation or the process by which a species changes its behavior, physiology, or fitness to match a particular environment through genetic changes. Recently, the principal invstigator has found that genomes of many organisms have previously unknown and unseen regions that likely impact adaptation. This proposal will use cutting-edge genomics, genetic crosses, and high-throughput experiments to measure the effects of the genome on environmental adaptation. Using nematode species, these studies enable the first connections between specific genes that vary significantly among individuals to specific environmental factors. We hope to discover molecular details into how evolution impacts genomes. Additionally, we will use custom-built, low-cost microscopes and lesson plans adapted for middle and high school classrooms to run in-person nematode isolation experiments from the natural environment. Our focus will be to teach evolutionary principles and the fun of field scientific research. Short-read genome sequencing has transformed the fields of quantitative and population genetics. It is straightforward to generate whole-genome sequence (WGS) data for many organisms across a species. This explosion of WGS data across populations has led to the mapping of many quantitative trait loci (QTL), but very few of these QTL have been resolved to the level of quantitative trait genes or variants. This missing understanding of trait variation at the mechanistic level impedes our ability to make predictions of phenotype from genotype and to use the power of tractable organisms to translate generalizable results to less tractable species. Model species (e.g., yeast, worms, flies, and plants) have many QTL that have been resolved to genes and ultimate molecular mechanism, demonstrating generalizable features of trait variation across the tree of life. However, even in these tractable organisms, some regions of the genome are inaccessible using short-read WGS because they harbor variation that is far higher than genome-wide averages obfuscating genome alignments and variant calling. These hyper-divergent regions (HDRs) are found from plants to worms to humans and represent genomic “dark matter” because we know that they exist but their biological relevance is still mysterious. We will use long-read (LR) sequencing and de novo genome assembly to identify the highly variable genes or genes missing from reference genomes that play hypothesized roles in gene-by-environment (GxE) interactions, especially responses to pathogens, using high-throughput assays. These regions will be defined at the molecular level to enable phenotypic predictions and fully understand complex multigenic traits. 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.