Vanderbilt University

NIH Research Projects · FY 2025 · 2025-06

Abstract: Multiple sclerosis (MS) is a chronic inflammatory demyelinating disease with over 1 million individuals affected in the US; early diagnosis and effective treatment are thus critical to protect quality of life. MS diagnosis follows from lesions disseminated in time and space, including lesions in the spinal cord (SC). While SC lesions are associated with a higher rate of relapse, the association between neurological symptoms and progression with SC damage has been underexplored due to the challenges of imaging the SC. Functional MRI (fMRI) can uniquely probe SC function in the resting-state and relies on blood oxygenation level-dependent contrast to link neuronal activity with hemodynamic processes which, when spatially correlated, is a measure of functional connectivity (FC). Prior SC resting-state fMRI (rs-fMRI) showed ventral-ventral (motor) and dorsal-dorsal (sensory) gray matter FC at 7T using seed-based analyses, and that lesions can influence FC in patients with relapsing-remitting MS (pwRRMS). At 3T, diffusion-derived indices of microstructural damage were associated with FC, suggesting structural-functional interdependence. However, clinically relevant data-driven rs-fMRI FC signatures have not been explored in depth at 3T, nor their relationship with neurologic deficits. Evaluating data- driven rs-fMRI FC in the SC of pwRRMS and identifying associations with sensorimotor impairment may provide an objective evaluator of pathology in the MS SC, beyond what can be explained by structural (clinical) MRI or neurological evaluation alone. We hypothesize rs-fMRI SC FC is an objective surrogate for neurologic symptomatology, and that alterations in FC can be related to macrostructural (lesions), microstructural (diffusion), and/or vascular hallmarks (susceptibility). Unique to this proposal, we will apply rs-fMRI SC FC as a quantifiable measure to assess motor and sensory integrity of the cervical SC and investigate the complex interactions between disease deficits and SC rs-fMRI using ROI- and data-driven analyses (Aim 1). We will then evaluate how microstructural integrity influences observed FC using novel approaches such as tractography and lesionometry (Aim 2). Finally, vascular hallmarks, such as the central vein sign and paramagnetic rim lesions, have been identified in the MS cord by our group. We will utilize SC susceptibility imaging at 7T in the same cohorts to investigate whether these vascular hallmarks are related to altered FC measured at lower field (Aim 3). The clinical impact of this proposal is to evaluate rs-fMRI as a marker of neurologic impairment, in the same manner that fMRI has been utilized to predict surgical (non)responders in refractory temporal lobe epilepsy. From this proposal, we may better understand the impact of a devastating neurologic disease and empower patients with MS. This proposed fellowship will provide research training in a collaborative research atmosphere, with expert mentors in neuroimaging at a top-tier academic medical center and imaging institute uniquely suited to all aspects of this work. My training will further develop my resources and knowledge to become a physician- scientist focused on clinical investigation of cutting-edge imaging methods.

NIH Research Projects · FY 2025 · 2025-06

PROJECT SUMMARY/ABSTRACT Sudden unexpected death in epilepsy (SUDEP) accounts for up to 18% of all deaths in epilepsy and up to 50% of all deaths in drug-resistant epilepsy. The strongest clinical risk factor for SUDEP is ongoing tonic-clonic seizures (TCS), and failure of cardiorespiratory function during TCS has been implicated as a major cause of SUDEP. Patients with temporal lobe epilepsy (TLE) experience cardiorespiratory and autonomic abnormalities both interictally (between seizures) and ictally (during seizures). These abnormalities have been related to elevated risk for SUDEP and include central apnea during the peri-ictal period and increased cardiac sympathetic modulation during the interictal and peri-ictal periods. However, the neural mechanisms underlying cardiorespiratory deficits in epilepsy and their relationship to SUDEP are largely unknown. Preliminary evidence from animal and human studies suggests that cardiorespiratory dysfunction in epilepsy may be linked to seizure-related disruptions of neural circuits involved in cardiorespiratory and autonomic regulation. In this proposal, we aim to integrate multimodal neuroimaging and electrophysiological data with measurements of cardiorespiratory activity to investigate impaired autonomic brain networks in TLE during the interictal state (Aim 1) and peri-ictal state (Aim 2). Currently, it is unknown how brain network disturbances directly impact cardiorespiratory and autonomic function. Cardiorespiratory activity is not commonly recorded in epilepsy monitoring units or neuroimaging research. We hypothesize that studying dynamic interactions between the central autonomic network and cardiorespiratory activity will reveal neural circuit impairments associated with interictal and ictal cardiorespiratory deficits. In Aim 1, we will analyze simultaneous functional MRI (fMRI), cardiac, and respiratory data to identify cardiorespiratory coupled brain connectivity abnormalities of the central autonomic network in TLE that are related to SUDEP risk factors such as recurrent TCS. This aim will uncover chronic alterations of autonomic circuits that may predispose TLE patients to severe cardiorespiratory dysfunction and SUDEP. We will also leverage advanced preprocessing methods to investigate subcortical autonomic centers that have been under-examined in prior fMRI studies of SUDEP. In Aim 2, we will analyze concurrent stereo-electroencephalography (SEEG) and respiratory data to identify abnormal neural-respiratory coupling and brain connectivity in cortical autonomic regions during temporal lobe seizures with ictal central apnea. This aim will elucidate seizure-induced impairments in respiratory-related neural communication that may serve as a biomarker of ictal apnea. Previous studies have associated ictal apnea occurrence with seizure spread to the amygdala. Here, we hypothesize that that ictal apnea results from transient disruptions of a wider network of brain regions involved in voluntary and autonomic control of respiration. If successful, the proposed aims can guide discovery of novel neural biomarkers of SUDEP risk and cardiorespiratory dysfunction, improving risk stratification and identifying neuromodulation targets for preventive treatment.

NSF Awards · FY 2025 · 2025-06

This Faculty Early Career Development (CAREER) award supports research on miniature soft robots with magnetically controlled microfluidics for precision medicine, enabling safe, precise, and rapid access to confined spaces within the body for minimally invasive procedures. Despite recent advancements in the actuation, control, localization, and navigation of magnetically actuated soft robots, their functionality remains constrained by size and structural simplicity. To overcome these limitations while enabling complex and multifunctional performance, magnetically controlled microfluidics will be incorporated into miniature soft robots. The strategy of bridging mechanical deformation with magnetic control will be used to address the challenges associated with coupling fluidic operations and robot locomotion. The resulting robot looks to be able to navigate complex terrains and perform targeted procedures such as drug delivery, on-site biofluid pumping, and liquid biopsies facilitating early disease detection and therapeutic interventions with minimal invasiveness and side effects. Finally, a wide array of educational and outreach activities will complement the research effort, e.g., a new undergraduate course on bioinspired robotics, undergraduate research opportunities, and deployment of educational bioinspired soft robots in high schools, university classrooms, and a local adventure science center. The objective of this award is to develop miniature soft robots with integrated magnetically controlled microfluidics to enable liquid manipulation, while supporting multi-modal locomotion, including climbing, walking, crawling, and rolling in confined spaces. The remotely applied magnetic field will enable liquid pumping mechanisms as well as wireless valves for regulating fluidic operations. Strategies for the decoupled control of fluidic functions and robot locomotion on biological tissue surfaces look to be developed, e.g., magnetic thresholding and leveraging of spatial confinement, allowing for both precise fluid manipulation and effective navigation across complex terrains. Furthermore, intelligent control strategies seek to be implemented to enhance closed-loop control and intelligent navigation capabilities based on medical imaging and combination of model-based and data-driven techniques. The project looks to cover the full gamut of miniature soft robotic development, including design, fabrication processes, modeling and control methods, and software. 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 · 2025-06

The field of nanotechnology, dedicated to understanding and controlling matter at the nanoscale, has generated immense global interest. Materials at the nanoscale exhibit physical, chemical, and biological properties that differ significantly from their bulk counterparts. Harnessing these unique characteristics through nanostructuring has the potential to substantially enhance and revolutionize numerous technological and industrial sectors, including information technology, medicine and health-care, transportation, energy, food safety, and environmental science. To continue to spur development in the field of Nanotechnology for societal benefit, it is imperative for global researchers to engage, discuss latest advancements, and establish impactful collaborations. This award will provide partial travel support for students and early-career researchers to attend the 6th African Nano Conference/Workshop on Applications of Nanotechnology to Energy, Environment, Agriculture, and Health. The conference, which will take place July 14-19, 2025 at the University of Nigeria, Nsukka, will gather international research leaders, students, and industry representatives to explore innovative applications of nanotechnology across these critical fields. The nanotechnology conference offers extensive opportunities for U.S. researchers to engage with their global peers, fostering meaningful exchanges and expanding perspectives and knowledge in pivotal areas such as energy, water, agriculture, environment, and health technologies. In addition, the conference will also cover the computational aspects of nanotechnology through a special session that is focused on latest computational tools for materials discovery including machine learning to advance the field of nanotechnology. It also serves as an essential platform for establishing and nurturing collaborative relationships between U.S. and African researchers, laying the groundwork for significant international research initiatives. Furthermore, the conference supports the growth of a globally connected STEM workforce and will serve to strategically attract students to STEM disciplines, thus playing a critical role in meeting the rising global demand for skilled STEM professionals. 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 · 2025-06

The Department of Mathematics of Vanderbilt University will host the Constructive Functions 2025 conference on May 19-22, 2025, to be held in conjunction with the 37th Shanks Lecture, featuring the distinguished mathematician Professor Doron Lubinsky as the Shanks Lecturer. The meeting will bring together leading experts and early-career researchers for in-depth discussions on all aspects of constructive function theory and its applications. This subject has a long and rich history, and its current vitality is attested to by the large number of well-established journals, and recently founded research centers paying attention to the subject. In addition to providing a forum for the exchange of ideas, the meeting will also help identify trends and areas for future research. This award will provide funds to support travel and lodging for participating students, early career researchers, and mathematicians without other sources of federal funding. More information can be found at the conference website https://my.vanderbilt.edu/constructivefunctions2025/. The theme of the conference broadly covers orthogonal polynomials, potential theory, discrete and continuous energy problems, special functions, approximation theory, random matrix theory, numerical analysis, and various problems related to optimization and efficiency. The fields mentioned above are particularly significant as they have relevance to a variety of mathematical sub-disciplines in addition to several scientific areas. The main aim of the current conference is to foster interactions between researchers from a wide range of subareas represented at our meeting leading to synergistic collaborations. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NIH Research Projects · FY 2026 · 2025-06

PROJECT SUMMARY The reversible phosphorylation of proteins is an essential process controlling cellular homeostasis. Protein kinases catalyze the transfer of phosphate from ATP to tyrosine (Tyr), serine (Ser), and threonine (Thr) residues in target proteins; protein phosphatases are responsible for removal of the phosphate group. Although Tyr phosphorylation is far less abundant than Ser and Thr phosphorylation (<0.1% of the total cellular phospho- amino acid content), it plays essential roles in many cellular signaling events. But Tyr phosphorylation is especially difficult to study, because it is low abundance and functions in rapid signaling events with a lifetime that is usually transient, increasing and then disappearing within minutes. Among the most useful tools for examining protein phosphorylation are phospho-specific antibodies (Abs), which can be used to readily quantify changes at phosphorylation sites and changes in their localization under various cell conditions. However, reliable phospho-specific Abs are difficult to obtain, due to poor specificity, limited availability of large-scale homogeneous preparations, and their inability to monitor protein phosphorylation in living cells. An attractive alternative to Abs is nanobodies (Nbs) – small (15 kDa), single domain, antigen binding fragments derived from camelid heavy chain-only Abs. Nbs targeting PTMs such as pTyr would be extremely valuable for the scientific community but reports describing such are very scant or non-existent. Although it has proven to be difficult developing Nbs targeting PTMs, our recent findings demonstrate remarkable success in developing Nbs targeting specific pTyr epitopes in two important families of signaling proteins – protein phosphatase 2A (PP2A) and the mitogen-activated protein kinase (MAPK) family member, ERK1/2. This proposal focuses on the development, characterization, and application of Nbs recognizing specific phosphosites in different subunits of PP2A, as well as the major MAPK family members, ERK1/2, JNK, and p38. We also will develop pan Nbs as probes for total protein abundances. Our approach will characterize the binding specificity, recognition, and affinity of each Nb for their targeted epitopes. We will determine the precise binding determinants by solving atomic resolution structures of Nb-peptide and Nb-protein complexes. We will systematically test our Nbs for their ability to recognize their respective phosphosite or protein target by Western analysis, immunoprecipitation, and immunohistochemistry, and determine effects of Nbs on MAPK and PP2A activity. Finally, we will develop Nb-based biosensors and PROTACs to respectively visualize phospho-epitope localization in cells and target them for degradation in living cells. The proposed work is responsive to PA-22-127, a technology development FOA requesting hypothesis-independent, broadly useful reagent and technology development. Completion of the proposed studies will not only yield novel tools for investigating signaling enzymes, but it will also open the door to a new technology that can be broadly applied to defining the phosphotyrosine proteome and expanding knowledge about the functions of this essential protein signaling event.

NIH Research Projects · FY 2026 · 2025-05

PROJECT SUMMARY/ABSTRACT In this proposal, we will leverage "Machine Learning to Modulate Influenza Immunity" by developing and implementing computational tools tailored towards the design of broadly protective vaccines against influenza viruses. Machine Learning (ML)-based algorithms pioneered by us and others have revolutionized protein structure prediction (AlphaMask, AxIEM, AlphaFold, or ESM) and design (ProteinMPNN, Rosetta) and have improved accuracy and speed of protein engineering. Here, we will integrate Artificial Intelligence/Machine Learning (AI/ML) and traditional computational biology to create a novel class of immunogen candidates that overcome the inefficacy of current influenza vaccines which fail to elicit broad and long-lasting protection. We will explore three immunogen design strategies: 1.) germline-targeting on the lateral patch of hemagglutinin (HA), one of the most conserved epitopes in the highly immunogenic HA head domain; 2.) HA heterotrimerization to create immunogens exposing various HA types and/or subtypes; and 3.) epitope-focusing to shift the immune response from highly variable regions to more conserved epitopes. Each aim will develop a computational pipeline with new algorithms for their respective immunogen design objectives that will be iteratively refined by experimental feedback, thereby successively improving the performance of the computational tools. In vitro experiments will provide high-throughput feedback from mammalian surface display, including deep mutational scanning of germline-targeting mutations and deep glycosylation scanning to evaluate the potential for immune evasion through hyper-glycosylation of HA. These large datasets will be integrated in AI/ML tools to extend predictions to other strains and further guide future vaccine design. To validate the effect of novel immunogen candidates, we will employ human Ig loci transgenic mice capable of producing fully humanized B-cell receptors. To simulate the effects of original antigenic sin, a mechanism in which primary contact with a novel immunogen has a lasting impact on subsequent antibody responses, we will analyze immunogenicity in animals pre-immunized with wildtype HA, thereby obtaining insights into the interaction of computationally designed immunogens with human-like antibody responses. The in vivo experiments will be complemented by ex vivo sorting of human naïve and memory B cells with computationally designed immunogens. All experiments will be supported by structural characterization through computations, X-ray crystallography, electron microscopy, and mass spectrometry to identify determinant mechanisms of protections. The efficacy of promising immunogens will be tested in lethal challenge experiments. We ensure the AI/ML-based computational tools developed in this project are readily available free-of-charge and transferable to other immunogen design challenges. The deepened understanding of the interaction of the immune system with rationally designed immunogens will support the future development of vaccines.

NSF Awards · FY 2025 · 2025-05

This I-Corps project focuses on the development of a computational ecosystem for intelligent protein engineering that enables the rapid and efficient design of enzyme variants for applications in biomedicine, biotechnology, and sustainability. The ability to engineer proteins with desired functional properties is essential for addressing challenges in pharmaceutical development, industrial biocatalysis, and environmental remediation. However, traditional experimental approaches are costly and time-intensive, limiting the accessibility of enzyme engineering to a broader range of researchers. The technology provides a scalable, high-throughput solution that integrates molecular modeling with artificial intelligence to streamline protein design. By improving the efficiency of enzyme discovery, this technology enhances the ability to design novel routes for drug synthesis, improve diagnostic tools, and create environmentally friendly catalysts. The adoption of this platform has the potential to significantly reduce industrial waste, lower energy consumption, and accelerate scientific progress in multiple industrial sectors. This I-Corps project utilizes experiential learning coupled with a first-hand investigation of the industry ecosystem to assess the translation potential of the technology. This solution is based on the development of an integrated computational platform that combines quantum chemistry, molecular simulations, bioinformatics, and machine learning to predict the functional effects of enzyme mutations. The approach leverages high-throughput molecular modeling to generate large datasets of molecular features that augment deep-learning algorithms, improving the accuracy of mutation effect predictions. Unlike traditional experimental screening methods, which rely on costly and time-consuming assays, this computational approach significantly reduces the time and resources required for enzyme optimization. Complementary to existing machine learning models that are trained solely on enzyme sequences, these molecular features inform the structural basis underlying enzyme functions, thereby enhancing the interpretability of the model. The platform's predictive capabilities allow for the rational design of protein variants with enhanced activity, stability, and selectivity, broadening its applicability across pharmaceuticals, industrial enzyme manufacturing, and synthetic biology. 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 · 2025-05

The objective of this project is to support research on deep learning (DL)-based methodologies for discovering the governing equations of traffic dynamics and probing how connected and automated vehicles (CAVs) behave and interact with other road users. With rapid development of artificial intelligence and availability of ubiquitous traffic data, the project aims to transform the methods of learning traffic dynamics from conventional studies to a DL-based automatic paradigm. New traffic dynamics models with CAVs are essential for achieving safety, mobility, and other goals related to future transportation systems. The project team adopts an “open science” approach to encourage collaborations, stimulate interests, and grow research capacity for this important topic. Results are integrated into existing and new courses and provide opportunities for graduate and undergraduate students to participate in cutting-edge research. Findings are broadly shared with transportation agencies, academic communities, and the industry via publications, meetings, and presentations/webinars. This project develops specialized, effective methods for learning traffic dynamics, especially for traffic flow with CAVs, from data directly. This is accomplished by designing new DL structures to address data noises, a coordinated learning framework to deal with the unique features of traffic dynamics due to diverse vehicle classes and/or driving behaviors. Equally important, it formulates new metrics and methods for four essential objectives: accuracy, parsimony, interpretability, and generalizability. Understanding of governing equations of traffic dynamics is fundamental to traffic prediction, transportation planning, traffic management and control. The project thus advances the scientific discovery of new traffic dynamics with CAVs and informs society to better prepare for the wide deployment of emerging 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.

NSF Awards · FY 2025 · 2025-05

The 15th Workshop on Cyanobacteria will bring together experts in ecology, biotechnology, and basic cell biology to focus on the latest advances in cyanobacterial field. The conference is organized into sessions to include topics from both traditional and emerging areas of cyanobacteria research while providing leading-edge examples of “what cyanobacteria can do.” A major goal of the conference is to create an environment where researchers can gather and exchange information. Also, by providing an opportunity for students and early career professionals to share their work, to network with the foremost leaders in the field, and to develop their careers, the workshop aims to infuse the cyanobacterial field with new energy and ideas. Cyanobacteria are indispensable model organisms for research on photosynthesis, nitrogen fixation, cellular metabolism, microbial interactions, and gene regulation. Besides offering critical insights into these fundamental biological processes, cyanobacteria also enable applied biotechnological innovations, such as by combining synthetic biology and metabolic engineering approaches to produce biopharmaceuticals and bioplastics. This workshop aims to bring together life science researchers and engineers to discuss cutting-edge research and new technological advancements and to foster interdisciplinary collaborations centered around cyanobacteria in a highly interactive and engaging meeting. The conference organizers aim to provide opportunities for graduate students, post-doctoral researchers, and early-career faculty to present their findings, to network with the foremost leaders in the field, and to develop their careers. The formal and informal events will promote the exchange of knowledge, discussions of challenges in the field, and collaborations to address these challenges. 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 · 2025-05

The project aims to investigate the metal-insulator interfaces in thin film Metal-Insulator-Metal (MIM) structures for their applications in the fields of nanophotonics, biosensing, and imaging. The proposed research will be useful for the broader realms of thin film and semiconductor research. The outcome of the work will be directly applied to mass manufacturing of reliable, high-performance detectors and sensors for imaging and energy conversion applications. Although MIM-based sensors, also known as plasmonic sensors, have promising applications, their realization to real-world devices is delayed due to a lack of understanding of the fundamental properties of the MIM stack. The objective of this research is to carry out systematic studies on the properties of the metal oxide and metal-organic materials used as insulators in MIM junctions. The research described in this proposal is on the edge of interdisciplinary involving materials science, nanofabrication, and Physics. It involves almost every stage in the development of a micro-device, i.e., design, fabrication, integration, characterization testing, and optimization. The project will strive to hire a graduate student, preferably from underrepresented groups, who will be trained to learn, practice and develop boundary-spanning skills. Such skills are highly recommended for the nanotechnology workforce in the industry and academia. The training and mentoring of the graduate student on this interdisciplinary project will enable them to successfully transition to the diverse STEM workforce. The results will be published in peer-reviewed journals and have interest to diverse audiences in the field of nanotechnology, materials science, electrical engineering, and physics. The proposed research is designed to gain a broader understanding of insulating materials, which are currently being explored to gain desired MIM diode and MIM -plasmonic structure characteristics. In the past, metal–insulator interfaces have been studied; however, with the advent of the newer concept of MIIM (double insulating layer), to attain better response of the diode, there is a need to study insulator-insulator interfaces. In this proposed work, we will conduct extensive modeling and simulation, and experimental work along with detailed materials characterization using state of art techniques such as Ellipsometry, Atomic Force Microscope, Transmission Electron Microscope, Secondary Ion Mass Spectroscopy, Xray-Photoelectron Spectroscopy, X-diffractometry to understand the effect of bandgap, point defect, and oxygen transport in the interfacial layers. The new knowledge generated from these experiments will be used in mass manufacturing of high-performance sensors and detectors. The proposal aims to compare the device fabrication techniques such as vacuum-based sputtering, atomic player deposition, and ambient atmospheric pressure plasma deposition for improved fabrication. The knowledge developed from this work will be successfully disseminated in improving the quality of the MIM/ MIIM stack, thereby improving the efficiency of plasmonic sensors. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NIH Research Projects · FY 2026 · 2025-05

Project Summary/Abstract Myelodysplastic syndrome (MDS) is a hematologic disorder characterized by ineffective hematopoiesis, cytopenias, and a risk of progression to acute myeloid leukemia (AML). While immune dysregulation is seen almost universally in MDS, studies have observed immunologically distinct phenotypes in low-risk (LR-) or high- risk (HR-) MDS. Inflammation is often seen in LR-MDS while HR-MDS is associated with immune suppression. For example, HR-MDS has been associated with an increased frequency of inhibitory myeloid-derived suppressor cells (MDSCs) and a skewing of macrophages towards anti-inflammatory (M2-like) phenotypes. However, how these contrasting immune profiles influence MDS pathogenesis and progression is not well understood, and efforts to target immune suppression in HR-MDS with available immune checkpoint inhibitors (such as anti-PD-1/PD-L1 therapy) have had limited success, indicating the presence of other immune suppressive mechanisms. VISTA (V-domain Ig suppressor of T cell activation, also known as PD-1H) is a co- inhibitory checkpoint molecule known to suppress the inflammatory activation of both T cells and myeloid cells. In myeloid cells, VISTA can promote M2-like characteristics in macrophages and mediate the immune suppressive functions of MDSCs. Our group recently reported that myeloid-expressed VISTA is a significant contributor to AML immune evasion in vivo. In my preliminary studies, I have found that VISTA is overexpressed in HR-MDS, particularly by monocytes and macrophages, but how this VISTA expression influences the immune microenvironment in HR-MDS and regulates MDS immune evasion is unknown. Therefore, this proposal will test the hypothesis that VISTA expression by host immune cells promotes MDS immune evasion in high- risk MDS. Aim 1 will use spectral flow cytometry (CyTEK) and highly-multiplexed immunofluorescence (CODEX) to profile and spatially resolve the bone marrow microenvironment of LR-MDS and HR-MDS. These studies would help to clarify the role of VISTA in HR-MDS and identify cell-cell interactions mediated by myeloid VISTA. Aim 2 will further investigate the role of myeloid and macrophage VISTA in MDS. In vitro experiments will reveal the VISTA-mediated mechanisms of macrophage anti-MDS immunity while in vivo experiments will assess the impact of myeloid VISTA on MDS progression and immune evasion using a myeloid-specific conditional knockout (LysM-Cre+;VISTAfl/fl). Finally, ex vivo experiments will validate the role of VISTA in human MDS and test the utility of anti-VISTA antibody blockade in the treatment of HR-MDS. Together, the studies in this proposal will deepen our understanding of how immune dysregulation facilitates MDS disease progression and help elucidate the immune suppressive mechanisms present in HR-MDS, providing a preclinical basis for the development of VISTA antagonists to treat high-risk MDS. Furthermore, funding of this fellowship application will provide comprehensive scientific training in basic and translational cancer immunology and outstanding career mentorship for a future hematology-oncology physician-scientist.

NIH Research Projects · FY 2026 · 2025-05

Project Summary The overarching goal of this proposal is the development of new reactions, and the reagents that control them, to generate enantioenriched organic compounds. These products are valuable precursors to more elaborate small molecules that are medicinal agents and/or more complex biologically active natural products. The proposed methods target the concise synthesis of secondary amines, tertiary amines, and vicinal diamines as single stereoisomers. These methods are based on the development of bis(amidine) reagents that form chiral proton complexes (a polar ionic hydrogen bond) when a strong acid is added, or when used with acidic substrates. Exploration of a new catalyst design is also described, asking whether reactivity and enantioselectivity can be managed using achiral species involved in the reaction. These studies continue the successful application of bifunctional organocatalysts to the stereocontrolled creation of structural and functional motifs that, while common, are otherwise difficult to prepare using conventional alternatives. A hypothesis-driven approach is outlined to explore an entirely new mode of activation that involves achiral Brønsted acid activators. A range of innovative multicomponent coupling reactions will be developed using chiral proton catalysis as the means to control enantioselection. These studies have the potential to impact small molecule synthesis, and ultimately the development of therapeutic agents. Moreover, the methods enable the metal-free production of functionally dense, single enantiomer (and diastereomer) organic compounds.

NIH Research Projects · FY 2026 · 2025-05

Damage and injury are a part of life. To survive, every animal must be able to repair tissue damage to restore function and keep out pathogens. Repair requires coordinated cell migration and proliferation, as well as rebuilding extracellular matrix. As in other animals, tissue repair and wound healing are essential in humans, and there is a clinical need for therapies that promote repair to treat non-healing wounds and injuries. However, tissue repair must be regulated: tumors are wounds that do not heal, with cancer cells inappro- priately activating wound-healing programs of migration and proliferation. Moreover, too much deposition of ECM during repair causes fibrosis and scarring, limiting function. Thus, understanding the regulation of repair may have broad clinical applications. My lab investigates repair mechanisms of two common tissue structures that are highly conserved across the animal kingdom: epithelia, the basic cellular building block of animal organs; and basement membrane, the most ancient type of extracellular matrix that underlies epithelia and surrounds muscles, nerves, and organs. We use a Drosophila in-vivo model system for its extraordinary genetic tractability, and we collaborate with physical scientists to address important gaps in understanding these repair processes. For epithelial repair, we collaborate with physicists on high temporal-resolution live-imaging of events happening within milliseconds to seconds after wounding to understand how they lead to later repair behaviors of cells. Although trauma wounds are a chaotic mix of many types of cellular damage, our previous work found that laser damage is in a patterned gradient, enabling us to discover that plasma membrane damage and cell rupture each initiate different but simultaneous signaling pathways. We are addressing how those signals result in cell behaviors that promote wound stabilization and repair. With respect to basement membrane repair, virtually nothing is known about how damage is detected and repaired. We previously developed an assay to analyze matrix damage and scar-free repair using the adult Drosophila gut. Collaborating with a biomedical engineer, we have determined that the surrounding cells detect damage by sensing basement membrane stiffness. We are addressing how that information is conveyed to the cells and how they use it to promote repair. We will address these questions using rigorous genetic approaches combined with the quantitative insight of our physical sciences collaborators. Our results will provide a foundation for understanding the regulation of tissue repair in clinical settings.

NIH Research Projects · FY 2026 · 2025-05

PROJECT SUMMARY/ABSTRACT Glucagon-like peptide-1 receptor (GLP1R) agonists are an emerging class of drugs used to treat obesity due to their ability to lower body weight. While GLP1R action in the brain is essential for the weight-lowering effect of these drugs, little is known about the molecular mechanisms engaged by GLP1R agonists that promote weight loss. Studies conducted by our group made the novel discovery that the GLP1R agonist liraglutide stimulates activity of the nutrient-sensing protein complex mechanistic Target of Rapamycin Complex-1 (mTORC1) via phosphorylation of the mTORC1 accessory protein Raptor in Serine791 by the canonical GLP1R signaling target protein PKA. Furthermore, we show that global mutation of Serine791 in Raptor renders mice partially resistant to liraglutide-induced weight loss, indicating that this signaling mechanism contributes to the anorectic effect of GLP1R agonists. The goal of this project is to identify the key neuronal population and circuit in which GLP1R agonists engage this non-canonical PKA-mTORC1 interaction to promote weight loss. I hypothesize that GLP1R agonists promote weight loss by stimulating the PKA-mTORC1 interaction in Proopiomelanocortin (POMC) neurons of the Arcuate nucleus of the hypothalamus (ARCPOMC) that synapse onto Melanocortin- 4 Receptor-expressing neurons in the Paraventricular nucleus of the hypothalamus (PVHMC4R). The focus on ARCPOMC neurons is based on our preliminary findings that deletion of the GLP1R in POMC neurons significantly attenuates liraglutide-induced weight loss. ARCPOMC neurons synapse onto PVHMC4R neurons, and activation of this ARCPOMC → PVHMC4R circuit promotes weight loss. However, it is not known whether GLP1R- expressing ARCPOMC neurons form part of this functional ARCPOMC → PVHMC4R circuit. I will test my hypothesis using sophisticated genetically encoded protein activity reporters, transgenic mouse lines, imaging analyses, circuit mapping approaches, and metabolic phenotyping techniques. Aim 1 tests whether GLP1R activation specifically in ARCPOMC neurons promotes weight loss through the PKA- mTORC1 pathway. This includes in vivo measurements of PKA activity in ARCPOMC neurons in freely moving mice in response to GLP1R agonist treatment as well as performing comprehensive metabolic phenotyping tests in novel transgenic mice expressing a PKA-resistant Serine791 Raptor mutant specifically in POMC neurons. Aim 2 investigates whether GLP1R- expressing ARCPOMC neurons form an anatomical and functional ARCPOMC → PVHMC4R neurocircuit regulated via the PKA-mTORC1 signaling pathway in ARCPOMC neurons. This will involve rabies-virus based monosynaptic circuit mapping approaches and functional tests of neuronal activity. Completion of the experiments proposed in this application will provide me with extensive training in experimental design and data analysis and interpretation as well as in mastering concepts and methods relevant to neuroendocrinological regulation of metabolic phenotypes. My Sponsor and co-Sponsor are fully committed to my training and to helping me develop into an independent academic research scientist.

NIH Research Projects · FY 2026 · 2025-05

PROJECT SUMMARY/ABSTRACT An aging human population has revealed the burden of chronic illness and age-related diseases. By understanding the cellular and molecular drivers of aging, we will be better equipped to develop therapeutics that delay age-related diseases. Mitochondrial dysfunction is a cellular driver of aging, yet strategies to therapeutically target mitochondrial dysfunction are lacking. It is well established that the accumulation of mutations in mitochondrial DNA (mtDNA) contributes to mitochondrial dysfunction in aging. Recent work has demonstrated that increased absolute levels of wild-type mtDNA can compensate for the effects of pathogenic mtDNA mutations and promote mitochondrial function. Thus, a therapeutic strategy to target mitochondrial dysfunction in aging is to elevate mtDNA copy number. However, the molecular regulators of mtDNA copy number are poorly defined. Moreover, recent evidence suggests that mtDNA copy number declines with age and, in addition to the accumulation of mtDNA mutations, may directly contribute to aging. To establish mtDNA as a therapeutic target in aging, we need to better characterize the mechanisms of mtDNA copy number regulation and to determine the direct impact of altered mtDNA copy number on aging phenotypes. In this proposal, I have discovered that C. elegans experience a significant age-dependent loss of mtDNA. Surprisingly, this loss of mtDNA is not associated with a decline in mitochondrial organellar content, suggesting that there is a sub-organellar mechanism selectively driving the loss of mtDNA. Additionally, I have found that this loss of mtDNA is suspended during an alternative developmental stage of C. elegans called dauer. My preliminary data demonstrates that reduced signaling drives mtDNA maintenance during the dauer state. Thus, I hypothesize that a sub-organellar mechanism eliminates mtDNA in C. elegans with age (Aim 1), that pathways downstream of reduced insulin signaling drive mtDNA maintenance during dauer (Aim 2), and that mtDNA depletion impairs mitochondrial function and causes aging phenotypes (Aim 3). This work will be conducted at Vanderbilt University under the supervision of Dr. Maulik Patel, PhD, Assistant Professor of Biological Sciences, who has made fundamental discoveries regarding mtDNA regulation and inheritance. Additional support will be provided by Dr. Patrick Hu, MD, PhD, a practicing physician-scientist and C. elegans geneticist who studies fundamental mechanisms that govern development and aging, including dauer formation. I will receive feedback from a strong advisory committee with experience in mitochondrial biology, genetics, and aging physiology. Successful completion of this project will advance our understanding of fundamental mechanisms of mitochondrial DNA regulation and establish therapeutic targets for preserving mtDNA copy number.

NIH Research Projects · FY 2026 · 2025-05

Project Abstract Sepsis is a critical problem around the world causing 20% of all global deaths. The lack of effective therapeutics leaves critically ill patients with systemic organ dysfunction often caused by damage to the vascular endothelium. The damage induces micro-vessel dysfunction and increased permeability. Increased permeability can be attributed to tight junction and adherens junction disruption within endothelial cells. All blood vessels are lined with a single cell layer of endothelial cells that regulate exchanges between the bloodstream and the surrounding tissues and modulate inflammation. During sepsis, endothelial cells secrete circulating inflammatory mediators such as monocyte chemoattractant protein-1 (MCP-1) which cause upregulation of cell adhesion molecules that facilitate leukocyte trafficking and also MCP-1 also disrupts tight junctions in endothelial cells. Given the widespread vascular inflammation and breakdown of endothelial tight junctions in sepsis, therapeutic approaches to maintain and restore endothelial tight junctions is a compelling treatment strategy. GLP-1R agonists have unexpected anti-inflammatory and permeability attenuation effects. Preliminary in vitro studies suggest that the protective effects of the GLP-1R agonist, liraglutide, in sepsis are mediated through microvascular endothelium. Pre-treatment of primary human lung microvascular endothelial cells with liraglutide improved lipopolysaccharide-induced barrier dysfunction indicating important effects of liraglutide in protecting the endothelial barrier. In Aim 1, I will define the ability of liraglutide to attenuate microvascular permeability in vitro and in a clinically relevant murine model of polymicrobial abdominal sepsis. Additionally, in my preliminary studies, treatment of wild type mice with the GLP-1R agonist liraglutide significantly decreased plasma MCP-1, attenuated organ injury, and increased survival in a model of polymicrobial abdominal sepsis. MCP-1 secretion is regulated by p38 MAPK pathway activation. Interestingly, GLP-1R agonists regulate the activation of MAPK. Therefore, there is rationale that liraglutide inhibits MCP-1 secretion via MAPK regulation. MCP-1 attracts monocytes to the site of inflammation, but also promotes their adhesion by inducing them to upregulate ICAM-1 that is expressed in the activated endothelium. My preliminary data suggests that liraglutide decreases endothelial ICAM expression in vitro. These adhesion molecules allow the attachment of leukocytes to the endothelium and permit their transmigration into peripheral tissue. In Aim 2, I will define the mechanism by which Liraglutide restores the endothelial barrier through downregulation of MCP-1 and the subsequent leukocyte recruitment and tight junction and adherens junction stability. Completion of these aims will determine whether liraglutide attenuates sepsis-induced microvascular permeability and how liraglutide is vasculoprotective through an anti-inflammatory mechanism. This proposal will promote advancement of an endothelial targeted drug to treat sepsis and further my goal to become an independently funded principal investigator studying the mechanisms of endothelial injury in sepsis.

NSF Awards · FY 2025 · 2025-05

This award is to support participants to attend the workshop: Groups in Geometry, Analysis, and Logic, to be held at Vanderbilt University in May 2025. The organizers plan to hold a series of workshops at Vanderbilt University under the common theme annually. The primary objectives of these events will be to foster collaboration among researchers in these fields, identify compelling research problems, and provide educational opportunities for graduate students and early-career researchers. The inaugural edition of the workshops will bring together up to 50 researchers for a five-day event at Vanderbilt University in May 2025. The main focus of this first workshop is to prioritize topics at the interface of group theory and logic. The following distinguished mathematicians, including two International Congress of Mathematicians speakers, will give teach mini-courses: Isaac Goldbring, Thomas Koberda, Andrew Marks, Katrin Tent, and Simon Thomas; these mini-courses will cover the necessary background and review recent developments in areas of current interest. In addition, the workshop will feature invited research talks, problem sessions, and small group discussions. More information can be found at https://sites.google.com/view/groups-geom-analysis-logic2025 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 · 2025-04

PROJECT SUMMARY Working memory, the ability to maintain information in mind over a period of seconds, is compromised in several mental illnesses and neurological conditions, including schizophrenia. The prefrontal cortex has been thought of as the primary site of working memory maintenance, though conflicting results have been obtained from human imaging and animal neurophysiological studies. To resolve this question, we will obtain neurophysiological recordings from human patients implanted with intracranial electrodes prior to epilepsy surgery and isolate spiking activity and local field potentials. The patients will perform working memory tasks closely modeled after tasks used in the non-human primate neurophysiological literature, requiring maintenance in memory of visual spatial, and shape information. We will thus be able to address the neural basis of memory at the level of neuronal firing in the human prefrontal cortex and other cortical areas, and compare our findings with the large literature of similar studies in non-human primate animal models. Specifically, we will address whether neuronal spiking in the prefrontal cortex exhibits selectivity for spatial locations objects held in memory or plays a more general supervisory or control role. Further, we will test predictions of competing models of working memory by using electrical stimulation to perturb neural activity and behavior. We will characterize the selectivity of sites isolated from each electrode contact when different stimuli are held in working memory, and we will apply electrical stimulation at either high (gamma) or low (beta) frequencies to disrupt or reinforce the memory of the stimulus. Results from these experiments will inform strategies for effective remediation of working memory deficits in patient populations.

NIH Research Projects · FY 2026 · 2025-04

PROJECT SUMMARY/ABSTRACT K99 research: Habits are inflexible behaviors that occur independently of the outcome of a given action. In cocaine use disorder, habits are often discussed in the context of drug use; however, equally important is the impact of cocaine consumption on habitual behaviors that form in relation to non-drug stimuli. Indeed, clinical evidence suggests individuals suffering from cocaine use disorder rely on habits at the expense of goal- directed control in non-drug contexts. At the center of goal-directed and habitual control are the dorsomedial and dorsolateral striatum (DMS, DLS), respectively. Efficient action control depends on balanced activity between these two regions – a process that critically depends on dopamine modulation of D1- and D2- expressing spiny projection neurons (SPN). Importantly, repeated cocaine use in humans and animals results in deficits in dopamine release and striatal activity. Thus, both dopamine release and SPNs activity are necessary for adaptive behavioral control and are thought to be impaired in cocaine use disorder. I will ask: 1) Does a history of cocaine self-administration alter dopamine release to promote habitual behavior? Mice with a history of cocaine use will perform a sucrose-based operant task that generates both habitual and goal-directed behavior. Using fiber photometry and optogenetics, I will test the hypothesis that a history of drug use results in stronger dopamine deficits in DMS compared to DLS and that this imbalance promotes habits. 2) Does cocaine self-administration change neural activity patterns associated with habits differently than those related to goal-directed actions? Using cellular resolution in vivo calcium imaging, I will test the hypothesis that the cell-type specific activity related to habits in DLS is less variable than activity related to goal-directed movements and that these patterns are differentially affected by a history of cocaine. R00 research: I will transition into my independent research for the R00 phase of this award by asking: 3) What mechanisms allow specific behaviors to be differentially affected by a history of cocaine use? I will use video-triggered optogenetic stimulation of dopaminergic neurons to test the hypothesis that cocaine use affects how temporally precise dopamine release changes the encoding of specific actions. Training in applying optical tools to addiction research and in computational analysis during the K99 phase will be crucial to successfully carry out R00 experiments. Training: This proposal is designed to provide me with training in utilizing circuit neuroscience tools in the context of addiction models and with new skills in computational analysis. My mentorship team of Dr. Calipari, Wassum, Womelsdorf and Rubinov is well-suited to ensure success in the technical and theoretical aspects of my training. My plan also focuses on career development training, with a focus on writing and managing federal grants. These training goals are crafted to allow me to produce impactful contributions to addiction research in the short term and to rapidly acquire R01 funding upon transitioning to independence.

NIH Research Projects · FY 2026 · 2025-04

PROJECT SUMMARY Neurofibromatosis Type 1 (NF1) is an autosomal dominant disorder characterized by the growth of nerve tumors, skin pigmentation abnormalities, and optic gliomas. NF1 is caused by mutations in neurofibromin (NF), a protein that increases the hydrolysis of Ras-bound GTP, resulting in Ras inactivation. Loss of NF leads to unchecked cellular growth, resulting in the neurofibromas characteristic of the disease. In addition to these symptoms, up to 75% NF1 patients present with learning disabilities, including dyslexia and spatial learning challenges, and almost 40% of children with NF1 have attention deficit hyperactivity disorder (ADHD). The incomplete penetrance of the learning disabilities suggests that there may be modifier genes that enhance the susceptibility of an NF1 patient to learning difficulties. Metabotropic glutamate receptor 7 (mGlu7, GRM7) is a group III metabotropic glutamate (mGlu) receptor that regulates presynaptic neurotransmitter release. Primary mutations in GRM7 cause severe neurodevelopmental phenotypes including seizures, ADHD, and intellectual impairments. The receptor is required for the induction of long-term potentiation (LTP) in the hippocampus by reducing GABA release, and Grm7-/- animals show deficits in learning and memory paradigms and a blunted response to amphetamine. A PheWAS study performed using the Vanderbilt BioVU database identified a correlation between a GRM7 SNP (rs9870680) with NF1, and we have found that this SNP also correlates with mGlu7 protein expression in the human brain. Mice modeling NF1 exhibit deficits in hippocampal LTP and behavioral abnormalities in learning and memory paradigms caused by excessive presynaptic GABA release; we hypothesize that increasing mGlu7 activity will reverse this effect. In support of this hypothesis, a single dose of a positive allosteric modulator (PAM) with activity at mGlu7, VU0422288, corrects a contextual fear learning deficit in an Nf1 mutant mouse line that exhibits learning impairments in multiple cognition models. In NF1 patients, the rate of learning deficits and ADHD is significantly higher than the general population; however, there is incomplete penetrance of these phenotypes, suggesting a possible modifier role for other genes when a patient also has NF1. PheWAS analysis has linked GRM7 gene with neurofibromatosis, and primary mutations in GRM7 cause ADHD and learning impairments. Coupled with the observations that genetic status at one of the identified SNPs correlates with mGlu7 protein expression and the finding that mGlu7 potentiation corrects impairments in Nf1 mutant mice in a learning model, our overall hypothesis is that mGlu7 potentiation represents a novel therapeutic strategy to address learning challenges in NF1. The goal of this R21 application is to test the hypothesis that the interaction of mGlu7 and neurofibromin lies at the level of GABA release and to validate that mGlu7 may represent a novel drug target for learning deficits in NF1.

NIH Research Projects · FY 2026 · 2025-04

PROJECT SUMMARY/ABSTRACT The ability to detect fiber pathways and assess tissue microstructure in vivo has opened a new window on the brain, with important applications ranging from brain connectomics to stroke detection and surgical planning. Diffusion Magnetic Resonance Imaging (DMRI) has the unique ability to reveal anatomical connectivity and tissue microstructure using noninvasive imaging methods. The development of open-source software packages for DMRI analysis has fueled the rapid growth of applications in both systems neuroscience and clinical neuroimaging. However, these applications have raced far ahead of the validation effort required to establish the reliability of the methods and quantify the impact of basic assumptions made by competing algorithms. For example, simplifying assumptions in commonly used analysis packages preclude detailed tissue characterization, ignoring untapped information in the diffusion weighted MRI signal. On the other hand, many microstructural analysis methods ignore fiber dispersion, which is prevalent throughout the white matter. The goal of this project is to quantify and improve the reliability of sub-voxel measurements of fiber properties by simultaneously improving angular resolution and sensitivity to fiber-specific diffusion properties. The project has 3 specific aims. The first aim is to develop and validate improved methods for sub-voxel fiber identification and tissue characterization. Results of our previous studies show that current methods have limited ability to resolve complex fiber distributions when crossing angles are less than ~40-60° (depending on data acquisition parameters). This limit biases fiber tractography and precludes the possibility of accurate fiber-specific microstructure measurements. We will compare the ability of our new method and current leading algorithms to segment and characterize sub-voxel fibers, using confocal microscopy data from the squirrel monkey as ground truth. The second aim is to determine the reproducibility of fiber-specific diffusion properties, both through space (uniformity along a pathway) and time (test-retest reproducibility) and the dependence of these properties on tissue microstructure, as measured by optical microscopy. These data will be used in critical tests of key assumptions made by analysis algorithms in current use. The third aim is to quantify the intersubject variability of fiber-specific diffusion properties, both in squirrel monkeys and human subjects. We will expand our squirrel monkey brain atlas to include the new fiber-specific diffusion properties and test the hypothesis that these measures are highly reproducible across healthy individuals, as suggested by our preliminary data. Creation of a similar human atlas will provide a framework for testing the hypothesis that intersubject variability of fiber-specific diffusion properties is lower than that of current DMRI measures, which do not fully account for fiber dispersion or crossing. In combination, these aims have the potential to improve the sensitivity of DMRI to white matter injury, while providing a clear link between the imaging biomarkers and biophysical properties of the tissue, thereby improving the specificity of DMRI in detecting changes due to injury, recovery, and aging.

NIH Research Projects · FY 2026 · 2025-03

SUMMARY The brain does not contain any significant energy stores but relies on blood flow to supply its metabolic needs, needs which vary both by region and over time. Neurovascular coupling (NVC) refers to the coordinated activity of multiple cell types within the brain to respond to spatially and temporally varying levels of neural activity (and associated metabolic needs) by dynamically modulating vessel lumen diameter and thereby redirecting cerebral blood flow to regions of greatest need. Dysfunctional NVC is closely associated with the cognitive decline seen in many diseases, and thus a better understanding of both the mechanisms of healthy NVC in humans as well as approaches to rescue impaired NVC in a diseased state could yield crucial information regarding potential therapies to aid in the recovery of cognitive ability. Current human microphysiological models of the cerebrovasculature and surrounding environment (the “neurovascular unit” or NVU) are unable to model NVC because 1) they lack the contractile mural cells needed to constrict or dilate the vessel and 2) the ability for cells in culture to transduce the relevant signals has not been established. To overcome this critical gap in NVU model functionality, we will develop the first engineered NVU capable of demonstrating any aspect of NVC. While there are many mechanisms involved, we choose to model the well-established glutamate-NMDA-nNOS- NO pathway that occurs at cerebral parenchymal arterioles and is thought to contribute to a substantial portion of NVC response. In this pathway, glutamate released from active neurons stimulates N-methyl-D-aspartate (NMDA) receptors in interneurons, causing an increase in intracellular Ca2+ and activating the Ca2+-dependent enzyme neuronal nitric oxide synthase (nNOS), resulting in release of NO that can act directly on smooth muscle cells (SMCs) as a vasodilator. In Aim 1, we focus on the “actuators”: the SMCs. We will conduct studies both with SMCs alone and in co-culture with endothelial cells (ECs) in a coaxial configuration on the wall of an engineered microvessel, and demonstrate appropriate vasoconstriction or vasodilation in response to vasoactive agents. Aim 2 focuses on producing a population of iPSC-derived nNOS+ interneurons and validating their ability to transduce glutamate signaling into NO release, first in 2D culture and then in a tubular volume surrounding the lumen of our 3D culture model. Finally, in Aim 3, we demonstrate optogenetic stimulation of iPSC-derived glutamatergic neurons and measure resulting release of glutamate, first in 2D culture and then in 3D. Subsequently, we incorporate the other stages of our model: the nNOS+ interneurons (transducing released glutamate into NO) and the SMCs (responding to secreted NO by relaxing and causing vasodilation). Successful completion of all three Aims will result in a human NVU model in which optogenetic stimulation of neurons results in vasodilation of a nearby engineered microvessel. Such a model would be a first (but crucial) step towards an in vitro human model of NVC in health and disease, enabling future identification of therapeutic targets and screening for drug candidates to rescue dysfunctional NVC and restore impaired cognition.

NSF Awards · FY 2025 · 2025-03

This project investigates the factors that influence how humans speak and understand language. It looks at the impact of the specific language that an individual encounters in day-to-day life (i.e., specific websites, videos, books, magazines, and social media), as well as factors like memory, the speed with which information is processed, and the ability to mentally track ideas. Understanding how each of these factors influence language processing and language learning informs an understanding of how humans learn language, with the translational potential of developing more effective methods of language acquisition. The goal of this project is to gain a better understanding of how an individual's experience with language affects language processing abilities. Factors like reading habits, exposure to different types of text, and cognitive abilities (such as working memory, attention, and processing speed) are measured to determine how each factor influences an individual's preferences and performance when processing complex English sentence structures. Although the scientific literature suggests that speakers are extremely sensitive to the linguistic frequency of grammatical structures and words in a language, how exactly frequency is used is unclear. Some work proposes that speakers' linguistic preferences match the frequency with which they encounter these structures in day-to-day life, but more recent findings suggest that people with more experience with language are more flexible in their language preferences. The project will involve two main experiments. The first experiment assesses how much experience with language, as measured by self-reported reading habits and the characteristics of the texts that participants read online, impacts preferences for dative sentences and phrasal verbs. The second experiment examines how reading experience and cognitive abilities interact to influence how quickly and accurately participants process sentences with complex syntactic structures. The findings help inform language teaching practices and help to develop interventions that better support learners based on their unique experiences and cognitive profiles. This project is jointly funded by the Perception, Action, and Cognition (PAC) program and the Linguistics (LING) program. 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 · 2025-02

This Cyber-Physical Systems (CPS) project will accelerate the design of controllers for large-scale engineering systems, focusing on the application of artificial intelligence in transportation. Traditional methods often rely on simulations that do not accurately represent real-world complexities, leading to an inefficient and costly process of collecting data, calibrating models, and testing controllers. This project aims to bridge the gap between simulated cyber environments and real-world physical operations by utilizing extensive offline datasets and offline reinforcement learning. Specifically, the research team will harness data derived from millions of vehicle miles collected on the I-24 MOTION open road testbed in Nashville, Tennessee. By developing efficient and adaptive control systems, such as improved cruise control for vehicles, the project seeks to enhance safety, reduce traffic congestion, and improve overall driving comfort. The anticipated result is a tenfold reduction in societal-scale transportation systems’ design cycles, leading to significant societal benefits in emissions reduction, air quality improvement, and transportation costs. Moreover, the project will contribute to education by offering courses that equip students with the skills needed to deploy these innovative systems, thereby preparing them to tackle future societal challenges. The collaborative project will explore critical questions surrounding the deployment of offline reinforcement learning in societal-scale cyber-physical systems in transportation. It addresses three key challenges: first, ensuring that controller designs align user preferences with system objectives; second, effectively processing and extracting useful information from vast time series datasets; and third, significantly reducing the number of iterations required in the design process. To achieve these aims, the multidisciplinary research team will develop novel reward functions informed by inverse reinforcement learning principles to encourage user participation. Additionally, advanced methods will be employed to explore the rich data generated by the open-road testbeds. The implementation of hybrid reinforcement learning strategies will facilitate real-time interactions of deployed controllers, enhancing design efficiency. Validation of the controllers will occur through extensive testing with vehicles on the open road, using the I-24 MOTION framework to ensure practical reliability and safety. 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.