Vanderbilt University

NIH Research Projects · FY 2026 · 2026-03

The World Health Organization characterizes neurological disorders as one of the greatest threats to public health, a leading contributor to disability-adjusted life years, and the second leading cause of global deaths. Across the world, mental disorders represent 10% of global disease burden, impacting an estimated 1 billion people. These disorders carry a huge economic burden, and while estimates and projections of total costs vary wildly, mental health carries a cost in the United States of at least $200 billion annually. This significant burden motivates improvements in understanding of disease etiology, diagnosis, prevention, and treatment. Many tools exist to examine such issues, but there is still a need for a functional imaging tool that is low-cost while maintaining high-spatial and temporal resolution. This need can be met with transcranial functional ultrasound imaging. Here, we build off new functional ultrasound imaging techniques demonstrated in rodent models, human neonates and in adult humans with exposed brains, to develop fully non-invasive, functional ultrasound for adult humans. Translating functional ultrasound to humans in a broadly useful way has been difficult because transcranial imaging requires lower imaging frequencies to better penetrate the skull, but this in turn reduces the sensitivity to small changes in blood flow-the source of the functional ultrasound's signal. New signal processing and machine learning techniques-developed by our group and others-enhance the performance of low velocity blood flow imaging, particularly in the high clutter and noise environments encountered transcranially, and using some of these methods, our preliminary data provides the first ever demonstration of transcranial functional ultrasound in adults. Additionally, because transcranial ultrasound struggles with establishing precise anatomical orientation and general localization, we will integrate image-to-physical tracking and a two-sided, dual-transducer imaging configuration with our advanced imaging methods to turn transcranial functional ultrasound into a broadly useful tool. We hypothesize that our advanced techniques integrated with tracking and multiple transducers will enable reliable ultrasound-based functional assessment in nearly all subjects.

NSF Awards · FY 2026 · 2026-03

Many industries, such as semiconductor manufacturing, mining, and electroplating, produce wastewater that contains salt and heavy metals. It is difficult and expensive to treat this type of wastewater. This project will develop a new technology called Electrochemical Ion Pumping (EIP) to remove salt and recover valuable metals like copper and nickel in a single step. EIP uses electrical control to separate salts from metals. This method is energy-efficient, scalable, and has low waste generation. It can help reduce industrial pollution, recover useful materials, and support a circular economy. The project will develop hands-on educational kits to teach high school and college students about electrochemical separation to prepare the next generation of STEM workforce. Many industries that are important to the U.S. economy and supply chains produce wastewater that contains salt and heavy metals. Treating these wastewaters involves complex, multi-step processes that use large amounts of chemicals. The project will establish a new electrochemical platform based on EIP that combines high-frequency circuit switching with narrow-window electrode potential control to enable pseudo-continuous desalination and electrowinning of heavy metals. The research will define mechanistic principles for stabilizing electrode potentials through ultrashort cycling at specific electrode saturation levels and apply these principles to selectively recover redox-active metals from saline wastewater. A multi-electrode EIP stack will be developed and tested for scalability and long-term performance. By integrating desalination and redox-selective metal recovery in a single process, this project will advance electrochemical separation science and provide a sustainable approach based on process intensification for treating complex industrial wastewater. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NIH Research Projects · FY 2026 · 2026-02

PROJECT SUMMARY This NIH F30 grant proposal investigates how somatic mutations in hematopoietic stem cells (HSCs) contribute to aging-related diseases through clonal expansion of mutated blood cells. This phenomenon, called clonal hematopoiesis, becomes more common as individuals age, affecting over 10% of in people over 60 years old. This study focuses on mosaic chromosomal alterations (mCAs), large-scale mutations that are under-studied compared to smaller mutations like clonal hematopoiesis of indeterminate potential (CHIP). mCAs are linked to lymphoid malignancies and infection susceptibility due to lymphoid-biased differentiation, while CHIP correlates with cardiovascular diseases and myeloid malignancies through myeloid-biased differentiation. I hypothesize that mCA expansion is determined by individual factors rather than mCA genetic change and that clones with greater expansion rates will have increased disease risk. Aim 1 examines the influence of mCA characteristics and environmental factors on clonal expansion rates using longitudinal blood samples from 30,000 individuals in Vanderbilt’s BioVU genomic and clinical biobank. Using longitudinal mCA trajectories, I will quantify the contribution of the mCA mutation and individual characteristics (e.g., age, sex, BMI, smoking, type 2 diabetes, lipoprotein levels) to clonal expansion rate and build a predictive model for mCA clonal expansion. My working hypothesis for Aim 1 is that mCA expansion varies widely among individuals with the same mCA and thus modifiable lifestyle exposures are major contributors to clonal expansion rate. The longitudinal samples in BioVU will not be sufficient to test genetic and phenotypic associations with clonal expansion rate. Therefore, Aim 2 expands the study to detect mCAs in > 1 million individuals across various genomic biobanks with single blood draws (i.e., NHLBI TOPMed, NIH All of Us, UK Biobank, and BioVU). To determine mCA clonal expansion rate from a single timepoint, I will apply Passenger-Approximated Clonal Expansion Rate (PACER), which estimates mCA expansion rate from a single blood draw to build upon my measured mCA analysis by two orders of magnitude. A genome-wide association study and a phenome-wide association study will be conducted to identify germline variants and phenotypic correlations related to mCA clonal expansion rates. My working hypothesis for Aim 2 is that 1) certain germline variants predispose individuals to faster mCA growth and 2) specific disease phenotypes, including chronic lymphocytic leukemia and infection susceptibility, are associated with faster mCA clonal expansion rate. This research aims to significantly enhance our understanding of mCA clonal expansion, addressing a fundamental biological mechanism of aging to prevent multiple diseases. Collectively, these insights will contribute to mCA risk prediction models and highlight potential biological pathways or lifestyle strategies to slow mCA expansion.

NIH Research Projects · FY 2026 · 2026-02

PROJECT SUMMARY Autoimmune diseases impact ~25 million people in the United States and are increasing in prevalence. Autoimmune diseases are driven by a failure of immunological tolerance that triggers aberrant immune responses against self-antigens that can impart debilitating morbidities and even death. There are no cures for autoimmune disease and current treatments non-specifically blunt immune responses against both self- and non-self-antigen, requiring life-long treatment compliance that leaves patients more susceptible to infection and malignancy. We propose to develop a develop and test a new strategy for targeted treatment of autoimmune diseases that harnesses the intrinsic immunoregulatory properties of extracellular vesicles (EVs). EVs are secreted by all cell types as a mechanism for promoting transfer of molecules between cells and have been implicated in the maintenance or induction of immunological tolerance through their ability to deliver diverse immunoregulatory cargo. We hypothesize that EVs derived from immunosuppressive cell sources and engineered to deliver autoantigens can be employed as a tolerogenic vaccine (i.e., inverse vaccine) that promotes antigen-specific T cell tolerance that abrogates autoimmune disease. Towards this end, we have devised strategies for exogenous loading of peptide antigens onto EV surfaces, thereby enabling coordinated delivery of antigens and immunosuppressive EV cargo to antigen presenting cells (APCs), resulting in the presentation of autoantigen in a potently tolerogenic context. While our EV-based tolerogenic vaccine platform – tolEVax – is amenable to EVs isolated any cell source and can be applied to several autoimmune diseases, we will focus on engineering of EVs derived from mesenchymal stem cells (MSC-EVs) and will test our approach in a model of multiple sclerosis. We propose to establish tolEVax as a promising strategy for promoting immune tolerance and treating autoimmunity through two Specific Aims. In Aim 1, we will load MSC- EVs with peptide antigens, evaluate effects on antigen biodistribution and uptake by APCs, and characterize effects on antigen-specific CD8+ and CD4+ T cell responses to model antigens. In Aim 2, we will evaluate the capacity of tolEVax to inhibit autoreactive T cell responses and self-antigen mediated inflammation and pathology in a model of multiple sclerosis. We expect these studies to identify MSC-EVs as potently tolerogenic antigen nanocarriers, to provide new insight into how EVs modulate adaptive immune responses, and to demonstrate the efficacy of tolEVax as a potential treatment for MS. Overall, this research will result in a platform technology that addresses the unmet need for effective antigen-specific immunotherapies for autoimmune disease by exploiting the inherent and multimodal immunosuppressive functions of EVs.

NIH Research Projects · FY 2026 · 2026-02

Project Summary One of the hallmarks of aging is a decline in the function of mitochondria, which is associated with changes in mitochondria morphology as cells age. However, mechanisms contributing to mitochondrial dysfunction in aging cells are not well understood. We have determined that interventions that lower sphingolipid levels preserve mitochondrial function and morphology in aging cells leading us to hypothesize that localized accumulation of sphingolipids contributes to the decline of mitochondrial function during aging. Mechanisms contributing to mitochondrial sphingolipid homeostasis during aging are not well understood. However, our results suggest that targeting lipid transfer activities at inter-organelle junctions which control the flux of sphingolipids into and out of mitochondria could promote longevity and healthspan. This highly collaborative project will leverage live cell imaging, genetics, and quantitative mass spectrometry approaches across two complementary aging models to test our central hypothesis and address the mechanisms that couple sphingolipid metabolism and mitochondrial health during aging. In the first aim, we will dissect the mechanism of sphingolipid-dependent changes in mitochondrial morphology as cells age, focusing on the role of sphingolipid trafficking and alterations to lipid composition of mitochondrial membranes. This aim will also dissect mechanisms for restoring young mitochondria after age-associated mitochondria remodeling has occurred. In the second aim, we will define mechanisms that drive mitochondria remodeling during oxidative stress. These studies will contribute to a deeper understanding of the relationships between sphingolipid metabolism and oxidative stress in aging cells. In the third aim, we will examine the relationship between sphingolipid metabolism and mitochondrial stress responses. This project will contribute new insights into the relationships between aging, mitochondrial health, and sphingolipid metabolism, with the long-term goal of informing novel strategies for preserving mitochondria function in aging cells.

NIH Research Projects · FY 2025 · 2026-01

PROJECT SUMMARY Immune checkpoint inhibitors (ICIs) have transformed the landscape of cancer therapy by unleashing the body's natural defenses to fight against tumors. However, this potent immunotherapeutic approach is not without its drawbacks, as it can trigger immune-related adverse events (irAEs), including potentially life- threatening myocarditis. The pathogenesis of ICI-associated myocarditis (ICI-MC) is poorly understood, but recent evidence from our lab and others suggests a crucial link to α-myosin, a cardiac muscle protein that is abnormally expressed in some cancer cells. In this proposal, I seek to extensively investigate the role of tumor- expressed α-myosin in the development of ICI-MC. My proposal is based on the central hypothesis that tumor expression of α-myosin can activate T cells specific to this antigen, driving an autoimmune response that culminates in myocarditis. To test this hypothesis, I will conduct a series of experiments involving mouse models bearing tumors that do or do not have enforced expression of α-myosin. I will compare the rate and severity of ICI-MC in these mice to that in mice bearing tumors without α-myosin expression. To assess the potential of using tumor-expressed α-myosin as a biomarker to predict the development of ICI-MC, I will analyze RNA and protein expression levels of α-myosin in tumor tissues from patients who developed ICI-MC compared to those who did not. I will further elucidate the mechanism through which the immune system interacts with tumor cells through innovative in vitro and in vivo approaches. In vitro, I will perform co-culture assays to establish whether cancer cells expressing α-myosin can effectively present this antigen and activate T cells. To validate the T cell activating capacity of α-myosin-expressing tumors in vivo, I will infuse fluorescently labeled T cells expressing T cell receptors specific for α-myosin into mice bearing tumors expressing this antigen, and track clonal expansion across tissue sites (heart, tumor, peripheral blood, lymph nodes). My approach is innovative in that it will be the first study to focus on features of tumor biology, such as expression of α-myosin, that are associated with an increased risk of ICI-MC. The potential impact of this research is significant. In completing this proposal, I will deliver urgently needed insights into the pathophysiology of ICI-MC, with the potential to unveil new approaches for screening and prevention of the disease. If a definitive association between tumor expression of α-myosin and the development of ICI-MC can be made, this could serve as a much-needed biomarker to identify patients at risk of developing this severe irAE. It would also provide a foundation for the development of new strategies to prevent irAEs in patients undergoing ICI therapy. This research could contribute to a broader understanding of the immune response to cancer therapy, ultimately enhancing the efficacy and safety of ICIs for a wide variety of cancer patients. Furthermore, the completion of this project will facilitate the development of my technical, critical thinking, and communication skills that will be crucial to my success as an independent physician-scientist.

NSF Awards · FY 2025 · 2025-12

This research project aims to study arithmetic properties of geometric objects such as curves and abelian varieties defined over different types of fields such as number fields, finite fields, global function fields and their extensions. Instead of studying each individual object one at a time, the principal investigator and her collaborators will take these objects and pack them into various types of families, and then use the geometry of the spaces parameterizing these families to deduce properties of the original objects. The main question that the principal investigator and her collaborators aim to answer is to estimate the number of special objects in these families and how often or rarely they occur. These special objects present useful and important properties making them central topics of research in many areas and directions in number theory and arithmetic geometry. Some of the target results will generalize important prior work of other mathematicians. The research program will provide many projects suitable for undergraduate and graduate students research which the principal investigator will supervise. There are two main directions the principal investigator and her collaborators will pursue with the projects, namely, to study the p-divisible groups for families of high dimensional abelian varieties and to study the structure of the ideal class groups of certain families of global function fields. There are different types of families in the research projects, such as the reductions of an abelian variety defined over a global field parameterized by the places of the base field, algebraic families of abelian varieties parameterized by a Shimura variety and sets of global function fields ordered by their discriminant. Specifically, one project aims to prove the set of ordinary primes in the reduction of certain abelian varieties with nontrivial endomorphism groups has density 1. In the opposite direction, another project aims to construct infinitely many primes at which these abelian varieties admit basic reduction, generalizing the work of Elkies’ on the infinitude of supersingular primes for elliptic curves. For ideal class group, the principal investigator and her collaborators will use Galois cohomology and computational tools to predict and prove properties of the distribution of l-torsion classes for degree l extensions of the rational function field. 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 · 2025-12

ABSTRACT Type 2 diabetes (T2D) is a common multifactorial metabolic condition characterized by persistently elevated blood glucose concentration. T2D is a major driver of global health burdens, with a disproportionate impact on historically marginalized populations, specifically, US Hispanic or Latino (HL) populations. HL populations have an increased prevalence of T2D compared to non-Hispanic whites; however, they are often underrepresented in genetic studies and have strikingly limited representation in multi-omic studies. The current work proposes to use deeply phenotyped cohorts in conjunction with multi-omic data at multiple timepoints to better understand the biological mechanisms contributing to T2D. Aim 1 will identify molecular markers associated with T2D cross-sectionally by leveraging transcriptomics, proteomics, and metabolomics data in multiple cohorts. We will perform differential abundance analyses in the available omic platforms from Mexican American participants in the Cameron County Hispanic Cohort (CCHC) and the Hispanic Community Health Study/Study of Latinos (HCHS/SOL) using linear regression. We will assess replication and generalizability of significant markers from each omics platform by analyzing Mexican American and non-Mexican American holdout sets from the CCHC and the HCHS/SOL. To explore molecular profiles associated with disease onset, Aim 2 will utilize longitudinal data across available omics to pinpoint signals associated with incident T2D. Using multiple time points collected from Mexican American participants in the CCHC and HCHS/SOL, we will perform multiple linear mixed model analyses. We will assess replication and generalizability of significant markers from the transcriptomics and metabolomics results in holdout sets from the CCHC and HCHS/SOL, as in Aim 1. Aim 3 will identify likely functional mechanisms underlying T2D risk and associated causal relationships. We will utilize ancestry-informed colocalization, Mendelian randomization, and phenome-wide association studies, to better characterize biological processes involved in T2D in HL individuals by leveraging electronic health record data available from BioVU and AllofUS. These analyses will explore causal and functional evidence for molecular features identified in Aims 1 and 2, our preliminary data, and the literature. We anticipate that results from Aim 3 will illuminate specific biological mechanisms contributing to risk and progression of T2D via genetic mechanisms. Together, these aims will characterize molecular factors associated with T2D and development in HL populations, enhancing our understanding of cellular changes associated with T2D in blood, and potentially illuminating clinical and therapeutic targets for future research.

NSF Awards · FY 2025 · 2025-10

The objective of this Civic Innovation Challenge (CIVIC) project is to support research on building and piloting a prototype system that uses artificial intelligence and sensor data to automatically detect unpermitted closures. It seeks to enable real-time monitoring of road closures, guide inspectors with optimized routing tools, and support permit staff with better data for future planning. Right-of-way closures—such as the blocking of streets, sidewalks, and bike lanes for construction, delivery, or special events—are an everyday reality in cities. When these closures are not properly permitted or monitored, they disrupt traffic, endanger pedestrians and cyclists, and negatively affect small businesses. While cities like Nashville are working to improve enforcement, they face challenges due to outdated systems, limited inspection staff, and the sheer number of closures. By combining technology with direct input from city officials, field staff and civic organizations, the project seeks to produce a practical, tested system that improves how cities manage public space. Its deployment would support compliance of existing right-of-way closure procedures, recuperation of lost revenue from missing permit application fees, and improve traffic flow and the safety of urban transportation. Importantly, the tools seek to be designed for reuse by other cities and other sensor modalities. The project will release open-source software, deployment guides, and training materials for public access. The project seeks to advance the automation and optimization of right-of-way closure enforcement through new contributions in machine learning, optimization, and systems engineering. The novelty lies in: 1) the joint integration of anomaly detection and multi-objective inspection routing to support real-time, scalable enforcement; 2) the use of uncertainty-aware learning and human-in-the-loop active validation to improve robustness to noisy, incomplete, or imbalanced urban sensor data; 3) the co-design of a web-based inspector and permit manager interface for operational deployment; and 4) the creation of a generalizable, open-source civic AI framework that can be adapted to infrastructure-constrained transportation departments across the United States. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NSF Awards · FY 2025 · 2025-10

Currently it is costly and difficult to simulate complicated physical scenarios such as tsunamis, earthquakes, or explosions. The mathematical and physical models that describe these effects are highly complex, and solving these models to produce realistic simulations can often require tremendous computing power. Yet physical simulations and digital twins are becoming increasingly crucial tools for researchers in the NSF Directorate for Computer and Information Science and Engineering (CISE), especially as artificial intelligence (AI) models are starting to interact with the real world. Whether considering models that power self-driving cars, household robots, or industrial design tools, a software platform for "physical intelligence" could allow researchers to create a new generation of innovations guided by mathematics and physics. In light of this, this collaborative project brings together investigators from Vanderbilt University, Georgia Institute of Technology, University of California Davis, and Stanford University to create a new, sustainable, community-driven software platform for physical intelligence. The project consists of several main thrusts to build the proposed platform, COSTA (a Community Open Simulation, Training, and Applications framework). The first thrust focuses on developing highly-optimized graphics processing unit (GPU) implementations of common data structures and algorithms used in physical simulations, such as uniform grids, particles, octrees, and linear solvers. The second thrust consists of developing a novel differentiable physics system on top of this GPU infrastructure, based on a partial differential equation (PDE) adjoint framework. This physics system includes algorithms for fluids, solids, and their two-way coupled interactions. Given these capabilities, the project's third thrust involves building a node-based graphical user interface for building physical simulations, as well as integrations with popular AI frameworks like PyTorch. The final thrust of the project involves designing COSTA with a novel cloud-native architecture that will facilitate efficient, large-scale physics simulations on the cloud. Throughout the project, a central aim is broad community involvement, outreach, and impact. For instance, the project involves hosting public workshops on COSTA, building a community governance organization to manage COSTA development, and offering cloud computing credits and training to help onboard the greatest number of users onto the platform. Curricular materials on physics simulation, machine learning, and their combination are another result of the project, and these materials will see integration into undergraduate and graduate courses at the investigators' institutions. Further information about COSTA and its development is available at https://costaproject.github.io/. 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 Asthma is a common chronic disease among children and is a significant cause of morbidity. As children, males have a higher incidence and prevalence of asthma compared to females at a 2:1 ratio. Yet, it is unknown why there is a sex disparity in asthma prior to the upregulation of sex hormones during puberty. Maternal asthma is a risk factor for childhood asthma, suggesting an in utero effect. Additionally, infection with respiratory syncytial virus (RSV) during the first year of life is also associated with increased risk of developing childhood asthma. The sex difference in airway inflammation in childhood asthma may be regulated at the intersection of genes and environmental exposures, but the mechanisms are unknown. My proposal will determine the mechanistic role of in utero allergen exposures and sex chromosomes in early-life immune responses to respiratory syncytial virus (RSV) infections. I have developed a mouse model of in utero exposure to house dust mite (HDM) allergen followed by RSV infection with 01/2-20 clinical isolate (3x107 PFU/ml) in male and female pups to answer this question. My preliminary data shows that, following infection with RSV, male pups exposed to in utero HDM had increased IL-13+ CD4 T cells and a decreased ratio of Tregs to Th2 cells compared to in utero HDM exposed RSV-infected female pups. Additionally, in bronchoalveolar lavage (BAL) fluid I determined an increased trend (p<0.08) of eosinophils in male pups exposed in utero to HDM following RSV infection compared to females. These results show sex differences in airway inflammation and Treg numbers following in utero exposure to allergen, providing a potential mechanism for the sex disparity in childhood asthma prevalence and severity. Based on these data, I hypothesize that in utero exposure to allergen increases airway inflammation and drives Treg instability and dysfunction in males more than females. I will test my hypothesis using mechanistic approaches that examine the differential contributions of sex chromosome dosages versus sex hormones to airway inflammation by using the “four core genotypes” (FCG) mice. FCG mice allow for XY phenotypic females and XX phenotypic males due to mutations in the Sry gene on the Y chromosome. In this proposal, I will: (Aim 1) Elucidate how the X chromosome restricts RSV-induced airway inflammation in pups exposed to allergen in utero, and (Aim 2) Determine how the X chromosome increases Foxp3 expression and Treg suppressive function in pups exposed to in utero allergen. Understanding how allergens and sex chromosomes impact immune-mediated responses in early life is critical for generating new prevention and treatment approaches that target the early life immune system in utero and postnatally.

NIH Research Projects · FY 2025 · 2025-09

ABSTRACT: Up to 75% of patients diagnosed with high-grade, non-muscle-invasive bladder cancer (BC) will develop recurrences. Left undetected or untreated, recurrent bladder cancer leads to muscle invasion and radical cystectomy, a major surgery with high morbidity and mortality. Thus, clinical guidelines recommend surveillance every 3–12 months, making BC the costliest cancer to treat over a patient’s lifetime. The standard- of-care tool for BC surveillance, in-office white light cystoscopy (WLC), has low sensitivity and specificity for the leading cause of recurrence: urothelial carcinoma in situ (CIS). The most promising technique to improve the sensitivity of CIS detection, blue light cystoscopy (BLC), has low clinical adoption because it is costly, time- consuming, and has low specificity for CIS. Our long-term goal is to improve the detection of CIS during in- office surveillance. The main objective of this proposal is to develop a multimodal tool with high sensitivity and specificity for CIS that is appropriate for in-office surveillance: real-time digitally stained WLC (dsWLC)–guided polarization-sensitive optical coherence tomography (PS-OCT). Digital staining uses deep learning to convert WLC images into accurate, low-cost, BLC look-alikes. PS-OCT is a microscopic imaging technique proven to improve the specificity of BLC. Our preliminary data and published literature confirm that PS-OCT has the specificity to differentiate CIS from inflammation, a primary contributor to false positives in WLC and BLC that leads to unnecessary biopsies and associated co-morbidities. The proposed two-prong strategy of dsWLC and PS-OCT will thus bring the benefits of BLC (high sensitivity) to the office while 1) removing the administrative burdens that prevent its widespread adoption and 2) adding the specificity that it lacks. Our central hypothesis is that dsWLC-guided PS-OCT has better sensitivity of detection for CIS than the standard of care for in-office surveillance (WLC), comparable sensitivity to BLC, and better specificity than both. Our specific aims are: 1) Improve the sensitivity of in-office CIS detection by developing dsWLC, 2) Improve the specificity of in-office CIS detection by building a miniature PS-OCT probe, and 3) Demonstrate the clinical effectiveness of real-time dsWLC+PS-OCT for bladder cancer detection. Aim 1 will build on our expertise in machine learning and our preliminary data showing the first application of digital staining to cystoscopy. In Aim 2, we will develop a miniature PS-OCT probe, delivering a technical innovation in size and speed that meets the clinical need for in- office surveillance. Aim 3 will assess the clinical effectiveness of dsWLC+PS-OCT by comparing its sensitivity and specificity to existing clinical standards, WLC and BLC. Individually, both dsWLC and PS-OCT bring significant innovation to the clinical workflow by improving, respectively, the sensitivity and specificity of CIS detection. Used together, they will inspire a new paradigm for the bladder cancer surveillance workflow to increase confidence in detection and eradication of high-grade disease, lower morbidity due to unnecessary biopsies, lower BC recurrence and progression, bring significant healthcare savings and raise quality of life.

NIH Research Projects · FY 2025 · 2025-09

Modeling and Removing Visual Impairments for Endoscopic Kidney Stone Surgery PROJECT SUMMARY/ABSTRACT The importance of achieving stone-free status during endoscopic kidney stone surgery is emphasized by the high rate of repeat stone procedures due to residual fragments after index surgery. Residual stone fragments are caused by incomplete stone treatment and can lead to obstruction, pain, kidney injury, and recurrent infections. Among other issues, blood and debris can frequently obscure the already limited field of view during endoscopic stone surgery, impairing the surgeon’s ability to visualize kidney stones. Importantly, endoscopic video is the primary means of locating and tracking stones during treatment. Though technical constraints of scopes may also impact surgical kidney stone outcomes, the above limitations of endoscopic stone treatment prevent many surgeons from achieving a complete stone-free status. My goal is to test whether computer vision models can be used to quantify and remove visual impairments during kidney stone surgery. I propose two Specific Aims to achieve these two objectives: Aim 1 will develop an automatic, real-time method for quantifying visual impairments and seek to associate impairments with surgical outcomes. Aim 2 will develop models for the virtual removal of visual impairments during surgery. These studies will produce a novel method for the objective quantification of visual impairments during surgery and means for the real-time digital removal of visual impairments from endoscopic stone surgery video. Success in visual impairment removal could decrease the frequency of residual fragments and reduce the risk of repeat stone surgeries. It could also lead to more efficient stone treatment, reducing operative time and decreasing the risk of injury to the collecting system. As these models would require only software integration to deploy in real-time on current endoscopic surgical cameras, all existing endoscopic surgical systems could in principle immediately benefit from the results of this project.

NIH Research Projects · FY 2025 · 2025-09

Project Summary Down syndrome (DS) is the most common chromosomal cause of cognitive disability, and it affects approximately 1 in 700 live births. Although the genetic etiology of DS (a complete or partial third 21st chromosome) has been known for over 50 years, many fundamental questions about how to support high quality of life for individuals with DS remain unanswered. One area of relative weakness in DS is Inhibitory Control (IC). This skill is important for daily tasks such as following directions, making decisions, and managing money among other tasks. Existing research demonstrates a clear link between playing the drums and IC. In the proposed research, we will conduct an experiment in which 7- to 12-year-old children are randomly assigned to the Experimental (EXP) and Wait List Control (WLC) conditions. In the EXP condition, children will receive drumming lessons between Visit 1 and Visit 2, and in the Wait List Control group, children will receive drumming lessons after Visit 2. In this way, all children will receive drumming lessons, but only the EXP group will show effects of the drumming lessons in Visit 2. Testing conducted during Visits 1 and 2 will include behavioral and neural measures of inhibitory control and drumming, neural measures of beat perception, and parent report of social behavior (via Standardized questionnaire). Our predictions are that children in the EXP condition will show improvements in both measures of IC and increases in precision in the beat perception and drumming tasks. We also expect that parent report of children’s behavior on the social skills questionnaire will show improvement. Across the EXP and WLC conditions, we expect no differences at Visit 1 but significant differences between conditions at Visit 2. If we obtain these predicted results, we will conclude that drumming lessons can improve the inhibitory control skills of children with DS. Building on this work, there are two main directions we would like to take this research in the future. In one, we will explore whether learning more complex rhythmic drumming patterns would show a greater impact on 7- to 12-year-old children’s inhibitory control skills. In the other, we will test younger children with DS: those in the 3- to 4- year-old age range. Beginning drumming lessons that early in life, when brain plasticity is greater than it is later in childhood, might show even more of a positive impact for the children’s daily skills that are affected by IC. Taken together, this whole project promises to have a substantial impact on our understanding of how perceptual-motor activities during childhood can improve IC skills for children with DS.

NIH Research Projects · FY 2025 · 2025-09

PROJECT SUMMARY Group III metabotropic glutamate receptors (mGlu4/ 7/ 8) have emerged as targets for modulating glutamatergic synaptic transmission and plasticity in the brain areas implicated in schizophrenia and for regulating various symptoms associated with schizophrenia. Further, emerging literature suggests that polymorphisms in genes encoding for mGlu4 and mGlu7 are associated with increased risk of a schizophrenia diagnosis and may predict improvement in symptoms after treatment with antipsychotics. However, the circuit-specific mechanisms by which activation of these receptors can affect schizophrenia-like physiological and behavioral deficits in rodent models relevant to schizophrenia are not clear. We present extensive data that a novel agonist of mGlu4/7 receptors, LSP2-9166, decreases excitatory neurotransmission at synapses from thalamic (TH), but not basolateral amygdala (BLA), afferents to dopamine receptor 1 expressing medium spiny neurons (D1-MSNs) in the nucleus accumbens (NAc). LSP2-9166 also corrects phencyclidine- (PCP, which causes pathophysiological changes and behavioral disturbances relevant to schizophrenia in rodents)-induced increases in glutamatergic neurotransmission at TH-D1-MSN synapses in the NAc. These novel findings provide mechanistic insights into gene polymorphism studies showing associations between mutations in gene encoding for mGlu4/7 receptors and risk for developing schizophrenia and suggest that agents modulating mGlu4/7 signaling may provide symptomatic relief in schizophrenia patients. We will now use selective negative allosteric modulators of mGlu4 and mGlu7, as well as optogenetic approaches, to modulate the activity of specific neuronal populations to test the proposed aims. In specific aim 1, we will use LSP2-9166, either alone or in the presence of selective pharmacological tools to test the hypothesis that LSP2-9166 acts at mGlu4/7 and selectively reduces glutamatergic neurotransmission from thalamic afferents in the NAc. In specific aims 2 and 3, we will directly test the hypothesis that activation of mGlu4/7 will normalize abnormally high glutamatergic signaling through thalamic afferents in the NAc and rescue sociability deficits in mice treated with PCP during juvenile development. These results will provide important information about the function of mGlu3 in brain circuits relevant to schizophrenia and will guide discovery efforts to develop highly selective modulators targeting either mGlu4 or mGlu7 receptors as novel therapeutics for treating behavioral deficits in schizophrenia.

NIH Research Projects · FY 2025 · 2025-09

Project Summary This program focuses on the development of a new class of antiarrhythmic agents that normalize dysfunctional RyR2 channels, the calcium release channel in the sarcoplasmic reticulum (intracellular) membrane. Human RyR2 mutations cause two distinct genetic arrhythmia syndromes: (i) Catecholaminergic Polymorphic Ventricular Tachycardia (CPVT) due to RyR2 gain of function mutations, and (ii), Calcium Release Deficiency Syndrome (CRDS) due to RyR2 loss of function mutations. RyR2 gain of function due to post-translational modifications has been implicated mechanistically in heart failure and atrial fibrillation. RyR2-selective modulators are lacking. The overarching goal of this transdisciplinary program is the selection of antiarrhythmic clinical candidates based on ent-verticilide, a potent inhibitor of RyR2-mediated calcium release in cardiomyocytes. Preliminary data for this first potent and selective inhibitor include efficacy in several models of disease, and PKPD in a chronic dosing study. Our collective results support the rationale that selective therapeutics can improve our understanding of RyR2 biology and lead to preclinical candidates. Since ent-verticilide is not a natural product, all compounds must be obtained by de novo chemical synthesis. Chemical synthesis has provided renewable access to drug, and served as a platform for rapid analog development to support pharmacology studies. A comprehensive study of verticilides for therapeutic development is outlined in three Aims. Aim 1 describes the use of cryo-EM and photocrosslinking studies to further elucidate mechanism of action and create a platform for structure-guided design. The goal of Aim 2 is to increase the bioavailability of ent-verticilide and test efficacy of oral dosing in atrial fibrillation and heart failure models. Aim 3 describes lead backup development using ent-verticilide B1, an 18-membered ring oligomer. A strength of this approach is its ability to adapt to changes in the state of the art in RyR2 structural biology, an effort to which we will contribute (Aim 1). Highly potent and selective compounds will be advanced to in vivo safety and efficacy studies (Aim 2) with backup lead identification to de-risk the overall program. This program is highly collaborative and transdisciplinary in nature, and the studies will advance a novel class of compounds never-before- used in therapeutic development. Preliminary results have already advanced our understanding of RyR2 molecular pharmacology and promise new antiarrhythmic agents to improve human health.

NIH Research Projects · FY 2025 · 2025-09

PROJECT SUMMARY: The overarching goal of the project is to develop a caregiver-implemented early intervention model available in English and Spanish to improve speech and language outcomes for young children with NSCL/P. We will test if caregiver-implemented Enhanced Milieu Teaching with Phonological Emphasis (EMT+PE) can reduce the severity of speech sound disorders and language delays in toddlers with NSCL/P. Caregivers will receive systematic coaching on utilizing EMT+PE strategies with their toddlers in a telehealth format. EMT+PE implemented by speech language pathologists (SLPs) has been shown to improve child language and speech outcomes in young children with NSCL/P in two randomized trials. 6,8Caregiver-implemented EMT+PE has been shown to be effective in three single-case design studies.39-41 The study will enroll 102 participants, children 24- 26 months old with NSCL/P and their caregivers. The intervention group will be compared to a control condition. Four specific aims guide the study: 1. To prepare for implementation of the multisite clinical trial during the 2-year planning period. 2. To examine the effects of caregiver coaching delivered via telehealth on caregivers’ use of EMT+PE strategies to support children’s speech and language development in a randomized clinical trial. 3. To examine the effects of caregiver-implemented EMT+PE on children’s speech and language outcomes immediately after intervention and at age 3. 4. To assess the feasibility, acceptability, and perceived effectiveness in improving child outcomes of the EMT+PE model with caregivers participating in the study.

NIH Research Projects · FY 2025 · 2025-09

PROJECT SUMMARY Recurrence remains a significant challenge for triple negative breast cancer (TNBC) patients despite treatment with surgery, chemotherapy, and radiotherapy (RT). Although irradiation of the resected tumor bed decreases recurrence in most patients, patients with chronic lymphopenia and a high neutrophil-to-lymphocyte ratio (NLR) following RT experience relapse at high rates. The mechanisms underlying this association of high NLR with recurrence are poorly understood. However, a growing body of literature shows that irradiation of mammary adipose tissue initiates an innate immune cell-driven program that facilitates tumor cell reseeding. Additionally, preliminary evidence suggests that irradiation promotes recurrence via neutrophil-mediated vascular remodeling and senescence. Therefore, the central hypothesis of this proposal is that neutrophils facilitate formation of a pro-recurrent niche in irradiated mammary adipose tissue through release of pro-inflammatory proteins and in- duction of vascular remodeling when primed by senescent cells. The rationale for the proposed research is that understanding the impact of post-therapy immune cell infiltration on tumor cell reseeding and vascular remodel- ing will identify candidates for targeted therapies. The central hypothesis will be tested by pursuing two specific aims: 1) Determine neutrophil phenotypes and functions associated with tumor cell reseeding in irradiated adi- pose tissue; and 2) identify the effect of neutrophil activation on pro-angiogenic signaling and vascular remodel- ing. In Aim 1, I will use a lymphopenic mouse model to represent at-risk patient populations and establish how neutrophil infiltration to irradiated mammary adipose tissue facilitates recurrence. To confirm that neutrophils are necessary and sufficient for tumor cell recruitment into adipose tissue, I will develop a neutrophil-depleted mouse model. In Aim 2, I will determine the influence of the senescent endothelial cell secretome on neutrophil activa- tion, using a well-characterized microfluidic model of the mammary vasculature to analyze how this activation promotes NF-κB and pro-angiogenic signaling in endothelial cells. I will then evaluate the impact of neutrophil proteins on NF-κB signaling and vascular remodeling as well as on tumor cell recruitment to irradiated adipose tissue in vivo. These studies will identify mechanisms of neutrophil-mediated vascular remodeling and tumor cell reseeding after RT, providing two potential points of intervention to prevent recurrence in patients with TNBC.

NSF Awards · FY 2025 · 2025-09

Integrated Cyber-Physical Systems (i-CPS) have transformed industries like manufacturing, transportation, healthcare, and energy management. I-CPS is characterized by multiple CPS services functioning concurrently within the same environment, high involvement of domain experts and everyday users in decision-making processes, real-time interactions with other systems, and operation within uncertain and constantly changing physical environments. Examples of such systems include smart cities, smart agriculture, and intelligent transportation, among others. However, stakeholders often hesitate to trust these systems due to a lack of explainability, which raises concerns about reliability, especially in safety-critical areas. Additionally, while advancements in deep learning have enabled powerful CPS capabilities, understanding of these systems is declining. Despite the significance and urgency of enabling explainability for i-CPS, research in explainable CPS with AI-driven components is still in its infancy. This research aims to develop explainable and trustworthy i-CPS capable of justifying their decisions and incorporating field operators’ queries and domain knowledge to adapt to evolving environments. The technical contributions to CPS research and education encompass four thrusts. Thrust I develops a new explainable architecture with formal explainers that interpret individual components of i-CPS and their interactions. Innovations include the first explainable CPS architecture, novel formal methods-based approaches addressing five layers of i-CPS, and explainable online decision support for “what if” scenarios. Thrust II formalizes and incorporates user domain knowledge, specifications, and feedback to enhance the learning-enabled components of CPS. Key advances include developing new formal knowledge distillation and unlearning approaches with uncertainty quantification that quickly adapt the system to shifting distributions in a lifelong evolving deployment. Thrust III evaluates the proposed methods through a real-world emergency response deployment in Nashville, TN, involving multiple CPS-based city services and stakeholders from different departments. Innovations include a logic-based LLM-enabled system that connects our proposed explainers to field operators, real-world deployment principles, and qualitative and quantitative metrics to assess explainability and impact. Thrust IV develops an interdisciplinary education plan. The key innovation is to bring rigorousness and explainability to CPS classes in Computer Science and create a new course, CPS in the field, for multi-disciplinary students. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NSF Awards · FY 2025 · 2025-09

This project aims to develop an intelligent microscopy system that will transform how scientists observe and analyze live cells over extended periods. Traditional systems passively collect data and often require substantial time, expertise, and computational resources for post-experiment analysis. In contrast, the proposed Intelligent Cyber Microscopy System (iCMS) introduces a cutting-edge, AI-powered cyber-physical system (CPS) that integrates light-speed, energy-efficient meta-imagers with holistic AI image analysis, as well as remote monitoring and control capabilities to optimize the operation of large-scale imaging facilities. This innovation will fundamentally improve efficiency, reduce operational costs, and accelerate scientific breakthroughs in fields such as biology, medicine, and drug discovery. By integrating advanced optics, artificial intelligence, and CPS, iCMS will enable researchers to dynamically adapt experiments as they investigate processes like cancer cell behavior and treatment response at unprecedented scale and speed. Beyond its scientific contributions, this project will strengthen the national biomedical research infrastructure, drive technological innovation, and support education and workforce development in STEM. The primary objective of this project is to develop a new biological imaging CPS system to revolutionize long-term live cell imaging by (a) transitioning from current sequential digital microscopy system to an integrated and interactive CPS system, (b) enabling intelligent meta-imager based AI image analysis for long-term microscope imaging, and (c) facilitating near-real-time remote monitoring and controlling for optimized operation of large-scale imaging facilities. The key idea is to transform the long-term live cell imaging from passive, resource-intensive digital microscopy system to an active and near-real-time CPS system. The proposed iCMS system will provide unprecedented capability of dynamically adjusting imaging settings, near real-time AI interpretation and modal adaptation during imaging, and granting scientists access to long-term imaging from anywhere, anytime, using any device. The broader impacts include improved efficiency and accessibility of high-throughput biological imaging, advancement of CPS research, and the development of future STEM leaders. 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

With the support of the Chemical Catalysis Program in the Division of Chemistry, Professor Schley at Vanderbilt University is developing new synthetic methods for the synthesis of organic molecules containing bicyclic groups. These methods will equip synthetic chemists with the means to craft molecules of increasingly complex three-dimensional shape and structure, contributing techniques to enhance innovation in the US fine chemical and specialty chemical industries. Members in Prof. Schley’s team will receive training in advanced chemistry techniques necessary to become part of a skilled and competitive workforce. Researchers at Vanderbilt University will partner with local community colleges in the greater Nashville area to establish undergraduate research and training opportunities for local Tennessee community college students to conduct research at Vanderbilt University. With the support of the Chemical Catalysis Program in the Division of Chemistry, Professor Schley at Vanderbilt University is developing methods for the synthesis of organometallic compounds of strained bicyclic groups via radical hydrometalation of the corresponding propellanes. The resulting bicycloalkyl organometallics will be applied as nucleophilic coupling partners in palladium-catalyzed cross-coupling chemistry, and as reagents in 1,2-hydrometalation chemistry of carbonyl derivatives. Whereas existing methods primarily allow for difunctionalization of propellanes via radical reactions, the proposed methods will provide synthetic chemists with the means to introduce bicycloalkyl substituents as terminal groups through transition-metal catalyzed processes already familiar to and broadly applied in chemical industry. The conformational inflexibility of bicycloalkyl substituents accessible by this approach will be applied in the synthesis of bicycloalkyl phosphines, aiding in development of phosphine ligands for chemical catalysis. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NSF Awards · FY 2025 · 2025-09

This proposal aims to unlock a deeper understanding of how intelligent minds communicate, delivering potentially transformational insights into how we talk and listen in day-to-day life, including when communicating with artificial intelligence (AI) systems. By studying how people remember and use language in everyday conversations, the proposal explores the distinct cognitive processes of speakers and listeners. Through a combination of empirical data collection and computational modeling, this work provides critical insights into when and why communication fails and how we can change the way we communicate in order to achieve success. These insights can support efforts to define new goals for advancing artificial intelligence systems, and critical insights needed to develop computer dialog systems that mimic human interaction more closely. These novel insights can also be leveraged to improve educational outcomes in the classroom by offering evidence-based insights to improve communication. Multiple students will gain hands-on research experience, inspiring the next generation of scientists. The project investigates cognitive processes governing language use and memory during conversation. The aim of the work is to test predictions of a proposal which argues that the way you use language shapes how you remember it, in turn guiding future language use. Data from thirteen behavioral experiments are analyzed using advanced statistical methods. In addition, computational modeling of key predictions using artificial neural networks make explicit precisely which theoretical assumptions are made and test the implications of these assumptions. This rare combination of the study of unscripted language use with computational models provides insights into real-time language processing which can be leveraged to advance AI dialog systems and offer evidence-based approaches for pedagogy and mediation. This project is jointly funded by the Perception, Action and Cognition program and the Linguistics 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.

NIH Research Projects · FY 2025 · 2025-09

PROJECT SUMMARY AND ABSTRACT Cocaine use disorder (CUD) is a significant public health crisis with no FDA-approved pharmacotherapies. Routes of administration that deliver cocaine to the brain most rapidly, such as inhalation and intravenous (IV) injection, have a greater likelihood of abuse and dependence compared to slower routes like intranasal use. Indeed, even at the same equivalent dose, inhalation of crack cocaine is associated with greater risk for addiction than insufflation of powder cocaine. Thus, the speed of cocaine administration is a key factor that determines its addiction potential. The goal of this proposal is to define how faster infusion of the same dose of cocaine results in increased drug taking and seeking. The nucleus accumbens (NAc) is a critical hub within the brain’s reward circuitry for encoding drug-cue associations. This region is composed of two non-overlapping populations of medium spiny neurons (MSNs) based on their expression of D1 or D2 type dopamine receptors. While D2 MSNs are inhibited by cocaine, D1 MSNs are activated by cocaine and cocaine-predicting cues, undergo robust drug-induced plasticity, and causally drive drug-seeking. Thus, cocaine and cocaine-associated cues selectively recruit specific subsets of NAc neurons (i.e. neuronal ensembles) to mediate addiction-like behaviors. However, it is unknown whether the speed of cocaine delivery alters neural ensemble responses to cocaine and its predictive cues, as well as its role in drug-seeking. There are two key questions that guide this research proposal: 1) Does the speed of cocaine administration influence ensemble activity and drug-cue associations? 2) Does the speed of cocaine administration influence how associated cues drive drug-seeking? I hypothesize that fast cocaine delivery enhances drug-cue associations by more robustly activating D1 MSNs in the NAc, increasing drug-cue ensemble stability and driving drug-seeking. In Aim 1 of this proposal, we will use in vivo cellular resolution calcium imaging to record neural responses to fast and slow cocaine infusions to determine how cocaine infusion speed alters the activity of cocaine ensembles. In Aim 2, we will use calcium imaging to track the same cells over time to determine how cocaine infusion speed alters the development and stability of drug-cue ensembles. Finally, in Aim 3, we will optically stimulate cue-ensembles associated with either fast or slow cocaine infusion to assess their role on the reinstatement of drug-seeking. The training plan in this fellowship will build upon my background in systems neuroscience by providing rigorous training in in vivo cellular resolution calcium imaging, behavioral models of addiction, and viral and genetic approaches for cell-type specific manipulation. Altogether, this project will answer a fundamental question in the addiction field, while also providing exceptional training in my development as an independent physician-scientist.

NIH Research Projects · FY 2025 · 2025-09

Project Summary: Alzheimer's Disease (AD) is a fatal neurodegenera�ve disorder characterized by progressive memory loss and execu�ve dysfunc�on. Recent research has highlighted the cri�cal role of inflamma�on in AD pathogenesis, with secreted phosphoprotein 1 (SPP1) iden�fied as a key driver of neuroinflamma�on. SPP1 levels are increased in both the cerebrospinal fluid and serum of AD pa�ents and are associated with faster cogni�ve decline. While global SPP1 knockout in mouse models of AD has been shown to decrease amyloid plaques and reduce neuroinflamma�on, the specific contribu�ons of SPP1 from different cellular sources, par�cularly perivascular cells, remain unclear. The primary objec�ve of this project is to develop novel siRNA delivery pla�orms to selec�vely target and knockdown SPP1 in perivascular cells, specifically border-associated macrophages (BAMs) and perivascular fibroblasts (PFBs), to elucidate their role in AD pathogenesis. This approach aims to address fundamental gaps in our understanding of how the spa�al origins and temporal expression paterns of SPP1 contribute to AD progression. In AIM 1, I will u�lize a first-genera�on lipid-siRNA conjugate (siRNA-L₂) to inves�gate the impact of perivascular SPP1 on AD progression. This will involve administering siRNA-L₂ targe�ng SPP1 at early (2 months) and mid (6 month) �mepoints in the 5xFAD mouse model of AD, followed by assessment of amyloid burden and neuroinflamma�on. In AIM 2, I will characterize novel siRNA-complex chemistries to op�mize cell-type specific delivery to BAMs and PFBs. The efficacy and specificity of these conjugates will be evaluated both in vitro and in vivo. This project leverages the specificity of siRNA technology and innova�ve delivery strategies to dissect the temporal and cell-specific contribu�ons of SPP1 to neuroinflamma�on in AD. Successful comple�on of this research will not only enhance our understanding of AD pathogenesis but also lay the groundwork for developing targeted interven�ons that can effec�vely modulate SPP1's impact on AD at the appropriate �me and loca�on. Moreover, the cell-type specific siRNA delivery pla�orms developed in this project could have broader applica�ons in inves�ga�ng and therapeu�cally targe�ng other key drivers of age-related neurodegenera�ve diseases.

NIH Research Projects · FY 2025 · 2025-09

PROJECT SUMMARY/ABSTRACT Social anxiety disorder (SAD) is one of the most prevalent psychiatric conditions worldwide, with a lifetime prevalence of 12.1%. SAD is associated with immense societal burden, including poorer educational and occupational outcomes and reduced quality of life. A sizeable subset of SAD patients (~1/6) do not respond to evidence-based treatments, and even more (17-60%) experience relapse following effective treatment. Accordingly, there is a pressing need to identify novel mechanisms that may be effectively targeted in treatment to improve patient outcomes. Biases in the attentional system may hold promise for future translational work. Attentional bias (AB) describes the preferential allocation of attentional resources to certain types of stimuli over others. In SAD, an AB to external, social-evaluative threats (i.e., angry/disgusted faces) has been reliably observed in the laboratory. However, interventions targeting this bias do not meaningfully reduce SAD symptoms, suggesting that ABs to external threats may represent a disease correlate, not cause. A more meaningful form of AB in SAD may be the extent to which individuals attend internally vs. externally in social situations. Indeed, excessive internally focused attention (i.e., on one’s anxiety-laden thoughts, emotions, and interoceptive sensations) is reliably linked to SAD severity and may contribute to disorder maintenance by increasing perceptions of threat and thus triggering anxious responding across multiple levels. However, researchers have not yet identified if, how, and for whom excessive internally focused attention plays a causal role in SAD maintenance, which is essential to know to inform optimized interventions. The proposed research will utilize an ecological momentary assessment-delivered experimental manipulation to compare the role of internally vs. externally focused attention in the maintenance of SAD. Outcomes will be explored longitudinally across self-report, behavioral, and cognitive levels of analysis, and mechanisms (i.e., threat detection, state anxiety) and moderators (i.e., attentional control) of the effects will be tested. The overarching goal of this project is to identify patterns of attention that play a causal role in the maintenance of SAD to inform novel treatment targets. Specific training goals include conducting experimental psychopathology research from an RDoC-informed framework, acquiring a deeper knowledge of the theory, assessment, and modeling of cognitive systems, applying advanced quantitative methods, and developing professional skills needed for a successful career in clinical science. By integrating theory and methods from multiple areas of basic and clinical science, the PI will acquire a strong foundation for building an impactful program of translational research that investigates the role of cognitive systems in the maintenance of anxiety disorders.