University Of California, San Diego

NIH Research Projects · FY 2026 · 2025-05

Project Summary For over a decade our group has studied the coevolution of interactions between bacteriophage λ and Escherichia coli as a model system to study species interactions as well as molecular interactions such as between λ’s receptor-binding protein (RBP) and outer membrane receptors. Using this model system, we have had success with studying many important subjects including the evolution of novelty, species, evolvability, and complexity. The next stage of this research is to more thoroughly understand the molecular drivers of RBP evolution, from understanding what types of mutations allow RBPs to gain new function, to what constrains their evolution and the properties that enhance their evolvability. Recently, we published a molecular model for how λ’s RBP evolves new function through a two-step process. The first is to gain mutations that destabilize protein quaternary structure that cause the protein to form a range of confirmations, creating new geometries of the RBP binding surface. Next, mutations in the RBP loops that create the binding surface evolve to further augment the chemical properties of the surface to facilitate interactions with new receptors. This model is in line with classic predictions that innovations evolve through non-genetic phenotypic heterogeneity (initial destabilizing mutations that create confirmational heterogeneity) and then canalization of new function (loop mutations). We propose to collect data on massive RBP genetic libraries to test this model and to further refine it. To do this, we will use high throughput RBP gene-editing and phenotyping assays that we have developed over the past decade. We will also assemble a library of 96 E. coli outer membrane proteins to test activity of the RBP variants on a diversity of receptors. For Aim 1, we will test the molecular model by determining which mutations cause RBP gain-of-function. Aim 2 builds on 1 by examining what protein characteristics constrain RBP gain-of-function evolution and these data will be used to test protein tradeoff theories. Aim 3’s goal is the opposite of Aim 2 and is designed to determine which protein features drive increased gain-of-function evolvability. Aim 3 data will be used to test theories on protein robustness and evolvability. Overall, our goals are to establish a molecular model for RBP gain of function that can be generalized to other viral systems with the goal of predicting viral host-shifts, and to test general evolutionary theories on how novel protein-protein interactions evolve, test which physical principals cause protein tradeoffs, and identify determinants of protein evolvability.

NIH Research Projects · FY 2026 · 2025-05

Abstract Individuals at high-risk of suicide vary substantially from one another. Over time, risk factors for suicide may change within the same individual. Despite these differences, most treatments for suicidal thoughts assume that the same intervention works equally well for all individuals at high-risk of suicide. Intensive longitudinal data combined analyzed with network science, integrated with coaching, could be used to personalize suicide prevention interventions to make them more effective and efficient. This K23 Career Development application involves refining and testing a novel personalized treatment for individuals at high-risk called PeRsonalizEd Clinical Intervention for Suicidal Events or PRECISE. PRECISE leverages idiographic statistical techniques adopted from network science applied to ecological momentary assessment data to inform the tailoring of Safety Planning and skills from Dialectical Behavior Therapy, two existing evidence-based treatments for suicide. In Aim 1, a user-centered design approach will be used to refine PRECISE. Following the refinement of the intervention, informed by data from a case series in Aim 1, we will then conduct a randomized controlled trial comparing two different intensities of personalization. In the low-intensity arm, the 8-week treatment will be tailored based on an initial two-week burst of ecological momentary assessment and one idiographic model. In the high-intensity arm, participants complete eight weeks of ecological momentary assessment and idiographic models are generated between each session. Coaches use the idiographic models to identify an individuals’ drivers of suicidal thoughts and conduct behavioral chain analyses to tailor specific skills to then teach, shape, and reinforce in their individual clients. Assessments are completed pre-treatment, 8-weeks post-enrollment, and 32-weeks enrollment. We hypothesize that both arms will demonstrate clinically significant reductions in suicidal ideation, but the high-intensity arm will be superior to the low-intensity arm in reducing ideation. Furthermore, we anticipate that increases in effective emotion regulation skills and reductions in negative affect will account for the decrease in suicidal ideation. As individuals learn more effective emotion regulation strategies, they will experience less distress and thereby lower levels of suicidal ideation. This project is responsive to Objective 3.2 of the NIMH Strategic Plan and is integrated with a mentored research training plan focused on 1) suicide-specific rigorous clinical trials, 2) user centered design in digital health, and 3) applications of network science to intensive longitudinal data. The project and training goal will support the Candidate’s overarching goal to become a clinician-scientist engaged in independent research on personalized, impactful, rapid acting suicide prevention interventions for at risk adults.

NIH Research Projects · FY 2026 · 2025-05

PROJECT SUMMARY In the vertebrate heart, the atrial and ventricular chambers contain distinct types of cardiomyocytes with specific molecular, morphological, and physiological properties. Atrial and ventricular specification are thought to occur in the early embryo, and chamber-specific gene expression patterns are apparent before the heart tube forms. However, the early assignment of atrial and ventricular cardiomyocyte fates is not sufficient to ensure commitment to a particular identity: chamber fate decisions seem to be malleable and can be reversible, even after differentiation initiates. Although the stability of chamber-specific characteristics is crucial for effective cardiac function, we do not yet understand the mechanisms responsible for maintenance of cardiac chamber identity. Our research addresses this significant gap in our knowledge by focusing on the genetic pathways that reinforce ventricular cardiomyocyte identity in the embryonic zebrafish heart. Several lines of evidence indicate that the ventricular myocardium harbors considerable plasticity: under certain circumstances, ventricular cardiomyocytes can transform, gradually losing their ventricular traits and simultaneously acquiring atrial traits. Our recent work has demonstrated that a FGF-MEK-ERK signaling pathway plays a pivotal role in the maintenance of ventricular identity, enforcing the retention of ventricular characteristics and suppressing the appearance of atrial characteristics. Building on this discovery, we are now well positioned to illuminate novel aspects of the mechanistic basis for chamber identity maintenance. First, we will elucidate the downstream effectors that mediate the impact of FGF-MEK-ERK signaling on the maintenance of ventricular identity. Our data suggest that dynamic patterns of ERK activation, downstream of FGF signaling, act cell-autonomously within ventricular cardiomyocytes to regulate transcription factors that promote ventricular gene expression and repress atrial gene expression, and we will test this model using real- time biosensors, chimera analysis, and transcriptomics. Second, we will identify factors that confer differential plasticity within distinct ventricular regions. The inner and outer curvatures of the ventricle differ in their inherent malleability; these differences may reflect local dynamics of ERK activity, regional distributions of biomechanical cues, and/or spatially distinct gene expression patterns, and we will test each of these hypotheses. Third, we will examine whether the signals that maintain ventricular identity in zebrafish play similar roles in human cardiomyocytes. Using pharmacological and genetic tools, we will test the hypothesis that FGF-MEK-ERK signaling and its effectors act to reinforce the stability of ventricular cardiomyocyte identity during differentiation of human pluripotent stem cells in vitro. Overall, our studies are likely to provide novel insight into crucial and conserved mechanisms that strike a balance between ventricular commitment and plasticity. Moreover, our results have the potential to inspire innovative strategies for regenerative medicine and to reveal new perspectives on the origins of congenital heart disease.

NIH Research Projects · FY 2025 · 2025-05

PROJECT SUMMARY / ABSTRACT The UC San Diego School of Medicine Microscopy Core is the largest light microscopy core facility on campus and has been serving UCSD researchers since 2003. It is accessible by all UCSD researchers regardless of department affiliation and currently has over 200 registered user labs across the campus. The Core enjoys strong support from the faculty and our institutional leadership. The current array of 12 instruments at the Core includes multiple confocal systems, light sheet, Gatan 3View serial block face scanning EM, slide scanning, lattice structured illumination, among others. However, there is a clear gap for a cutting-edge multiphoton microscope, which is currently lacking as a core resource on campus. Our previous Leica SP5 multiphoton system is no longer operable, and a replacement system is urgently needed to continue with multiphoton research. Here we seek funding to acquire a Leica Stellaris 8 DIVE (Deep In Vivo Explorer) multiphoton as our replacement multiphoton system. The spectrally tunable detection of Stellaris 8 DIVE offers substantial advantages compared with other multiphoton systems. The system is also equipped with integrated FLIM capabilities, which can be readily used to generate channels based on fluorescence lifetime. Our on-site instrument demonstrations validated Stellaris 8 DIVE as a capable and versatile system. The proposed user labs illustrate a critical need among local investigators for the proposed system in advancing their NIH-funded research. They come from all corners of the campus, and their research programs collectively cover a range of biomedical research fields with many disease areas represented. If funded, the Stellaris 8 DIVE system will be extensively utilized by proposed users and additionally will reach a potentially much larger user base as our core has proven capable of disseminating cutting-edge microscopy technologies to the wider local research community. Adequate space and infrastructure, capable staff, robust faculty oversight, and strong institutional commitment along with a track record of program-leading core grant citations will ensure the effective and efficient use of the proposed instrument for years to come. The Leica Stellaris 8 DIVE system will fill a current void in our instrumentation portfolio and generate a sustained, powerful influence on the biomedical research enterprise at UC San Diego.

NIH Research Projects · FY 2026 · 2025-05

PROJECT SUMMARY The purpose of this proposal is to investigate the association between hearing impairment and hippocampal function, and how this association relates to memory function, in cognitively normal middle-aged and older adults. Hearing impairment has been identified as a modifiable risk factor for Alzheimer’s disease and dementia, however the mechanism for this is unknown. The central hypothesis in this proposal is that hearing impairment is associated with poorer hippocampal function and memory, and that differences in memory are mediated by hippocampal function. This hypothesis is informed by the current literature, which shows reduced hippocampal volume in humans and reduced plasticity in animal models with impaired hearing. However, the relationship between hippocampal function and hearing impairment in humans has not yet been explored. Aims 1 and 2 of this proposal will use data from the UK Biobank to investigate the association between hearing impairment and hippocampal activity, and their relationship with memory. The dataset includes: 1) hearing ability categorized into impaired and unimpaired; 2) functional MRI of hippocampal activation; and 3) memory performance assessed by a Paired Associates task. There is also evidence from animal models to suggest that hearing impairment and Alzheimer’s pathology may exert a compounding effect on hippocampal function, but this also has not been examined in humans. Therefore, Aim 3 will collect pilot data to examine associations between hearing impairment, fMRI hippocampal activation, amyloid-beta deposition, and memory performance in 30 cognitively normal older adults. The findings from this work will provide critical evidence for existing theories on the association between hearing impairment and dementia risk and will inform future hearing-based interventions. Importantly, this work will highlight the need to treat hearing impairment as part of a comprehensive approach to reducing Alzheimer’s disease risk. The Principal Investigator, Dr. Megan Fitzhugh, is currently a postdoctoral scholar at the University of California San Diego (UCSD). Previously, she conducted studies investigating sex differences in the association between hearing impairment and dementia risk, and studies of longitudinal changes in brain volume and functional connectivity associated with hearing impairment. Her career goal is to become leading investigator at the intersection of auditory neuroscience and Alzheimer’s disease, focusing on risk factors of Alzheimer’s disease, such as hearing impairment. Toward this goal, Dr. Fitzhugh’s career development efforts during this award will be dedicated toward four areas: advanced statistical methods, audiology, Alzheimer’s disease and dementia, and mentorship. UCSD is an ideal location for career development due to the expertise and multidisciplinary nature of the Department of Neurosciences and its associated Shiley-Marcos Alzheimer’s Disease Research Center and the Alzheimer’s Disease Cooperative Study. This proposal will position the PI to begin an independent research career and successfully submit an R01 proposal in a faculty position.

NIH Research Projects · FY 2025 · 2025-05

ABSTRACT Airway abnormalities in children, such as subglottic stenosis (SGS) and Robin sequence (PRS), may result in breathing difficulties, risk of recurrent infections, hypoxia, respiratory insufficiency, life-threatening events, and long-term morbidity. In children with airway abnormalities, a multidisciplinary approach to care involves selection from a variety of medical and surgical interventions. Therapy is typically directed by the clinician's experience and preference, rather than based on normalized, quantitative physiologic and anatomic metrics. Static computed tomography (CT), dynamic CT, and bronchoscopy have been considered for quantitative diagnosis and assessment. However, quantitative measures of what constitutes normal airway geometry and how normal airway geometry changes with respect to age, weight, and sex are lacking. Such normative measures can be used to score the degree of airway abnormality, define thresholds for abnormality, and better understand surgical interventions' impact. In previous work, we developed the Pediatric Airway Atlas to provide spatially localized normative measures for upper airway cross-sectional areas in children derived from a population of static 3D CT images. The goal of the proposed study is to build upon our database of 3D CT images and associated clinical measures to develop the computational methodology for a Pediatric Airway Shape Atlas (PASA), which will model the upper airway as a 3D shape instead of restricting airway characterization to cross-sectional area only. The PASA will allow for a comprehensive characterization of 3D geometry. Specifically, the core of the PASA will be a new, innovative neural additive shape model that is designed to allow for interpretable results, captures the effects of relevant covariates (such as age, sex, and weight), and allows within the same framework to predict likely airway changes over time for individuals thereby providing a means to quantify the effect of surgical interventions on 3D airway geometry. Our approach will provide improved, non-invasive quantification of airway abnormalities. Automated data analysis will allow for rapid refinement of atlas-based analyses and will greatly simplify use by other research and clinical groups. The resulting software will be open-source. Furthermore, the new methodologies developed will be broadly applicable to multiple, common causes of airway obstruction in children and adults.

NSF Awards · FY 2025 · 2025-05

Sex differences in health and disease have often been attributed to sex hormones, but there is a growing appreciation that sex chromosomes directly impact sex differences in disease progression. The goal of this CAREER project is to improve the understanding of how two X chromosomes in female cells contribute to female-specific aortic valve stenosis progression, the most common aortic valve disorder that can lead to sudden heart failure. To accomplish the research objectives, sex-specific cell culture platforms will be engineered using hydrogels that mimic the soft tissue microenvironment of the aortic valve. These platforms will be used to investigate how X chromosome genes contribute to female-specific valve cell phenotypes. Using various biomaterial tools, female-specific genes on the X chromosome will be linked to increased aortic valve tissue stiffening in females. In parallel, the educational objectives focus on clarifying and communicating the importance of sex as a biological variable in biomedical research to undergraduate students, the UC San Diego community, and the public. Specifically, the importance of sex as a biological variable in biomedical research will be promoted though undergraduate senior design projects, campus-wide symposia, and public science communication events. Biological sex influences the progression of aortic valve stenosis (AVS), with males exhibiting increased valve calcification and females experiencing severe valve fibrosis prior to eventual calcification. The biological mechanisms underlying sex-dependent fibro-calcification of aortic valves remain poorly defined, partly due to significant challenges in disentangling the effects of sex hormones from those of sex chromosomes on sexually dimorphic VIC phenotypes in vivo. Existing in vitro strategies rely on cell culture substrates that fail to replicate the time-dependent dynamic changes in extracellular matrix (ECM) structures observed in health and disease. This CAREER project aims to engineer dynamic in vitro systems to investigate how X chromosome-linked genes modulate female-specific fibrosis during AVS, while isolating these effects from hormone biology. Valvular interstitial cells (VICs), the primary fibroblast population within aortic valve tissue, are believed to drive sex-specific differences in aortic valve fibro-calcification. In XX female VICs, X-inactive specific transcript (XIST), a long non-coding RNA that silences one of the X chromosomes during X chromosome inactivation (XCI), is expressed. The central hypothesis of this work is that reduced XIST expression in VICs regulates dynamic ECM remodeling and fibrosis during aortic valve stenosis. To test this hypothesis, the research objectives will focus on engineering hydrogels as cell culture platforms using biorthogonal chemical conjugations to create culture systems that mimic the dynamic ECM. These hydrogels will allow for spatial and temporal evaluation of XIST expression dynamics independently of sex hormones. Collectively, this proposal seeks to establish fundamental knowledge regarding how XIST expression regulates ECM alterations during valve fibro-calcification, independent of sex hormone effects. Future efforts will explore the independent and synergistic roles of sex hormones and sex chromosomes to fully elucidate the mechanisms defining AVS. 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

Tuberculosis (TB) causes over 1.3 million deaths per year and active TB (ATB) disease in over 10 million new individuals annually. However, in 2022, over 40% of reported TB patients were diagnosed based only on clinical judgment, while an additional ~3 million individuals with ATB were neither detected nor reported. This lack of diagnostic rigor results in an inefficient health system that perpetuates TB transmission, fuels drug resistance, and jeopardizes global goals to end TB by 2035. Current diagnostic solutions depend on the detection of Mycobacterium tuberculosis (Mtb) in patient sputum, despite sputum's limitations as a diagnostic sample, making it difficult to obtain from patients with paucibacillary TB, such as those living with HIV (PLWH), young children, and patients with extrapulmonary TB. While rapid, sputum-based molecular diagnostics like GeneXpert (Cepheid, CA) are replacing slow, growth-based Mtb detection as the reference standard globally, most ATB is still diagnosed with sputum smear microscopy, despite its low sensitivity and specificity. Our long-term goal is to transform TB diagnosis for all age groups with a blood or urine test that accurately distinguishes patients with ATB from other pathologies, regardless of HIV co-infection. The objective of this study is to demonstrate the analytical and clinical performance of a novel assay that combines the sensitivity of our proof-of-principle bioelectrical TB (BET) assay with the ease of use of paper-based lateral flow immunoassays (LFAs) to create a highly novel electrochemical LFA (eLFA) for point-of-need TB detection. Our central hypothesis is that our proposed eLFA test will enable us to diagnose ATB with an accuracy that meets or exceeds the WHO Target Product Profile (minimum accuracy: 90% sensitivity and 70% specificity for a triage test for TB). We will achieve our objective through the following specific aims: AIM 1: Determine the operating characteristics of the eLFA using contrived samples and bio-banked blood from patients at risk for TB. We will obtain estimates of precision, cross-reactivity, and accuracy using GeneXpert and culture status as references. AIM 2: Determine the operating characteristics of the eLFA using contrived samples and bio-banked urine. We will obtain estimates of precision, cross-reactivity, and accuracy using GeneXpert, and culture status as references, along with a combination of contrived and clinical samples.

NIH Research Projects · FY 2024 · 2025-05

PROJECT SUMMARY/ABSTRACT Opioid use disorder (OUD) is a pernicious and highly prevalent threat to public health, affecting 6.1 million US citizens in 2022. Buprenorphine is one of the most efficacious treatments for OUD, yet half of patients treated buprenorphine return to drug use within six months, suggesting that additional adjunctive interventions are indicated. Ketamine, a FDA-approved medication commonly used as an anesthetic agent, is a NMDA antagonist that has demonstrated efficacy for the treatment of depression and holds significant potential to improve OUD treatment outcomes—especially when combined with targeted psychotherapies for addiction. We have successfully integrated ketamine with Mindfulness-Oriented Recovery Enhancement (MORE), an evidence-based psychotherapy for OUD with established efficacy in treating opioid misuse and preventing OUD relapse. Building upon our pilot data indicating that MORE + ketamine reduces drug use in patients treated with buprenorphine, here we first propose a UG3-funded, Phase 2 placebo-controlled randomized clinical trial (RCT) to investigate the safety, preliminary efficacy, and psycho-physiological mechanisms of MORE + ketamine for treatment-resistant patients receiving buprenorphine for OUD. To enhance blinding integrity, this study will compare MORE + intramuscular (IM) ketamine to MORE + IM diphenhydramine as an active placebo condition. We will also examine whether MORE + ketamine reduces drug use by a) enhancing mindfulness-related psychological processes, b) modulating neurophysiological reward responses, and c) altering theta oscillations in frontal midline brain regions. If MORE + ketamine demonstrates safety and preliminary indications of efficacy in the UG3 study, we will proceed to the UH3 phase to confirm the efficacy of the MORE + ketamine intervention in a community- based Phase 3 RCT conducted in three clinic sites recruited from the NIDA Clinical Trials Network. Our central hypothesis is that relative to MORE + placebo, MORE + ketamine will result in less drug use, better treatment adherence, and more improvement in craving and psychiatric symptoms though a 12-month follow-up. Unfortunately, ketamine is currently being marketed for a wide array of applications, including the treatment of OUD, in the absence of efficacy data from controlled studies. Should MORE+ketamine demonstrate efficacy in the proposed trials, this therapy will be advanced along the FDA approval pathway into standard care for treatment-resistant patients with OUD on buprenorphine to reduce opioid-related mortality and morbidity in the United States.

NIH Research Projects · FY 2026 · 2025-04

Abstract This proposal outlines a five-year career development program for Dr. Saravanan Raju M.D., Ph.D. with the goal of preparing him for an independent research career as an academic physician-scientist. Dr. Raju completed his M.D. and Ph.D. in Immunology at Washington University in St. Louis and his medical residency in Clinical Pathology at Barnes-Jewish Hospital/Washington University. With the goal of dissecting the basis of broad and durable immunity to pathogens, Dr. Raju sought the mentorship of Dr. Michael Diamond, who is a Professor of Medicine and Co-Director of the Center for Vaccines and Immunity to Microbial Pathogens. Dr. Diamond is an expert in the field of viral immunology and has previously served as a mentor to physician- scientists who have transitioned to independent positions in academic medicine. Washington University provides an outstanding environment for Dr. Raju to develop his independent research career. First, Dr. Raju’s Advisory Committee comprised of Drs. Ellebedy, Fremont, Amarasinghe, and Murphy has diverse and extensive scientific expertise relevant to all aspects of this proposal and highly successful track records as scientific mentors. Second, Dr. Raju will acquire additional scientific, grant-writing, and laboratory management skills through resources available within the School of Medicine and Office of Postdoctoral Affairs. Third, the research infrastructure within the Diamond laboratory and on-site core facilities will enable Dr. Raju to efficiently perform the scientific aims described in this proposal. The goal of the proposed research is to study the basis by which cross-reactive B cells are induced to arthritogenic alphaviruses in mice. As the genus of alphaviruses includes several related but antigenically distinct species with established epidemic potential (e.g., Chikungunya virus and Mayaro virus), knowledge gained from this proposal may inform the development of pan-alphavirus vaccines. Dr. Raju will engage in formal coursework, workshop attendance, and mentored practical training in both B cell repertoire analysis and structure determination by cryo-electron microscopy to accomplish the aims in the proposal. Upon completion, the studies outlined in this proposal will yield insight into germinal center dynamics in a relevant infection model that can be expanded to other virus families and serves as a launching point for Dr. Raju’s independent research career.

NIH Research Projects · FY 2026 · 2025-04

SUMMARY/ABSTRACT Ultrasound is one of the most versatile tools in medicine for non-invasive imaging and therapies. As with any wave phenomenon, one of the limitations in ultrasound resolution is the diffraction limit. In this project, we propose the use of negative-index non-resonant acoustic metamaterials (NRAM) for ultrasound focusing exploiting their negative-index refraction and sub-wavelength focusing. Negative acoustic metamaterials have shown exciting properties such as amplification of evanescent waves,1–3 negative phase velocities (phase propagates in opposite direction to group propagation),4–7 impedance matching to enhance ultrasound transmission,7 and negative refraction angles.8,9 Using these properties, NRAM have demonstrated experimentally novel capabilities such as ultrasound sub-wavelength imaging, and imaging and focusing with rectangular slabs that produce mirroring images of ultrasound point sources.1–3 Many of these properties could bring major benefits for biomedical ultrasound.6,7,10,11 However, such capabilities have been shown only at low frequencies in the 1-60 kHz range,3,7,9 impeding their study and application at biomedical ultrasound frequencies. The low-frequency operation of metamaterials has been due mainly to technology limitations. However, recently our research group demonstrated a novel metamaterial technology achieving a 1-D negative-index behavior at 300 kHz in water incorporating <100 micrometer membranes and Helmholtz resonators,12 placing us in an ideal position to study the potential impact of NRAM for biomedical ultrasound. For this exploratory R21 project, we aim to build 2-D and 3-D negative electroactive metamaterials operating at 2 MHz to demonstrate negative refractive index and dynamic sub-wavelength focusing. Specifically, we aim to 1) demonstrate negative index and negative-angle refraction to achieve ultrasound focusing at 2 MHz frequency using negative metamaterial slabs, 2) demonstrate sub-wavelength focusing targeting 0.250.1 mm lateral focusing at 2 MHz, and 3) demonstrate electroactive dynamic focusing and acoustic index tuning at 2 MHz using piezoelectric-based NRAM. This exploratory project aims to demonstrate the technological capability of negative-index acoustic metamaterials to facilitate ultrasound focusing and improve resolution. The success of this exploratory project will provide experimental evidence to expand this effort and aim for higher frequency operation towards 5 MHz and to develop electro-active tunable metamaterials that can lead to active and adjustable focusing for ultrasound applications such as transcranial ultrasound imaging, therapies and stimulation.

NIH Research Projects · FY 2026 · 2025-04

Summary. Despite effective antiretrovirals (ARV), Human Immunodeficiency Virus (HIV) spreads within the central nervous system (CNS) and establishes persistent infection precipitating cognitive impairment (CI). Recent findings suggest that HIV protein (namely VPR) expression in the brain activates the inflammasome pathway in neurons leading to gasdermin E pore formation as a key mechanism of neurodegeneration. Mitochondrial damage is a critical mediator of inflammasome activation and may be a primary catalyst for the heightened inflammation and neurotoxic effects induced by HIV. This already complex scenario is further compounded by opioids. Yet, no studies have investigated the individual and combined impact of HIV and opioids on inflammasome-mediated neuro-inflammation and neurotoxicity at the cellular level using fresh, high-quality human CNS specimens. To address this knowledge gap, we have assembled a team with complementary expertise in virology, inflammasome, pharmacology, neuropsychology, and biostatistics. Through a comprehensive investigation employing neuropathology and complementary ex vivo and in vitro methodologies, our overarching goal is to uncover the mechanistic intersection through which HIV and opioids heighten inflammation, offering insights for targeted interventions to improve CI. Using a unique set of archived and fresh brain specimen from persons with HIV (PWH) and persons without HIV (PWoH) with thorough evaluation of opioid use and neurological conditions enrolled in the Last Gift cohort, we will analyze CNS specimens across 5 brain regions (frontal, occipital and parietal cortex, basal ganglia, and hippocampus) collected during rapid research autopsy. • Using flash frozen brain specimens with varying tissue concentrations of opioids from PWH (n=30) and PWoH (n=10) and with a defined history of opioid use, we will determine the relationship between HIV transcriptional activity, opioid exposure and inflammasome activity in neurons and BrMCs (Aim 1). • Next, we will use BrMC cultures generated from freshly autopsied brain tissues (n=10 PWH/5 PWoH) and in vitro models for neurons to probe underlying mechanisms of inflammasome activation by using small molecules to promote mitochondrial function and siRNA to knockdown inflammasome pathway proteins (Aim 2). Through this comprehensive examination of the separate and combined effects of HIV and opioids, our study endeavors to elucidate how the convergence of these factors leads to more severe neurological consequences. By understanding the nuanced interactions and synergies between HIV infection and opioid use, we aim to contribute valuable insights into the mechanisms underlying neurotoxicity in the context of HIV-associated CI ultimately paving the way for targeted interventions and therapeutic strategies.

NSF Awards · FY 2025 · 2025-04

When navigating in complex environments, fixed landmarks and moving obstacles are crucial features that influence efficient and robust path planning, optimal route finding, and minimization of navigational errors. Autonomous vehicles are severely limited by their inability to reliably anchor their navigation to landmarks and predict and avoid the movement of others. The research team proposes to develop and refine a computational model of spatial navigation and spatial representation using neural data obtained wirelessly from animals navigating in the two largest electrophysiology-compatible rodent mazes in the world, which are known as “megaspaces.” These studies explore the influence of stationary landmarks and moving objects as rats optimize their routes: a classic paradigm (the Traveling Salesperson Problem) in Computer Science. In addition to their technological impact in robotics and autonomous vehicles, these investigations can be extended to human mental health dysfunctions that are often accompanied by deficits in spatial processing such as in early onset Alzheimer’s disease, attentional deficit hyperactivity disorders, schizophrenia, or depression. This investigation is novel and unique in trying to understand how the interactions between the hippocampus and entorhinal cortex, two main components of the brain’s ‘GPS’ system, facilitate navigation, learning, and complex decision making in very large spaces. The research involves using experimental data to constrain a detailed biophysical neural model and testing experimentally its predictions about the properties of neural representations of megaspaces in challenging navigational tasks. The model will provide a new tool for the detailed study of the use of fixed landmark and moving obstacles in very large environments for efficient navigation. The work will contribute to robotics and computational neuroscience along two different axes: (1) using data-constrained modeling to propose concrete mechanisms explaining the nature of the interactions between self-motion and landmark-based navigational information and (2) using neural representations of large space to achieve efficient solutions or approximations for generally hard spatial navigational problems that could have significant impact in many disciplines. A companion project is being funded by the Department of Science and Technology, India. 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 · 2025-04

This EAGER project will demonstrate how National Artificial Intelligence Research Resource (NAIRR) Pilot resources can facilitate the development of a new service to the cybersecurity research community, specifically to infer the utility of datasets and software tools based on their documented use in scientific publications. The service will enable the assessment of scientific data utility to address a growing need in the scientific research community: optimizing AI-ready data investments. The research will help funding agencies optimize investments in AI-ready datasets, provide a scalable model for other similar scientific disciplines, and enhance the broader research community's ability to evaluate and sustain valuable data resources. State-of-the-art techniques for automatically extracting links between resources cannot handle the complexity, variability, and contextual nuances of natural language, e.g., in discerning a reference to a resource from its use in a paper. This project will require data collection, preprocessing and labeling, model selection and training, as well as evaluation and deployment. The approach will leverage techniques such as prompt engineering and fine-tuning to extract relevant metadata from unstructured text, and associated inference of relevant annotations. The research will utilize multiple NAIRR compute resources and aims to provide a repeatable, AI-based method for inferring the utility of datasets and software tools. This capability will enable more accurate interpretation and explanation of complex relationships in scientific publications. The resulting service will address a persistent and growing cybersecurity research challenge, and serve as a model for other disciplines. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NIH Research Projects · FY 2026 · 2025-04

Project Summary The proposed project will develop living biosensors for detecting and analyzing DNA at the single- base level, without requiring sample purification or any equipment. DNA is the prime information carrier for life, and DNA analysis provides valuable information for, e.g., diagnosing microbial infections or tracking disease outbreaks. Many techniques exist for detecting and analyzing DNA, but these generally require processing steps to extract and purify samples, and most require expensive equipment and significant training and expertise. This proposal will transfer that complexity into the biosensor itself, harnessing functions that evolved into living bacteria over billions of years to pull DNA out of raw samples, analyze it, and produce easily read output. The biosensors will pull in DNA using natural competence, and analyze it with single-base precision using their endogenous CRISPR-Cas system. Upon detecting a target sequence, the living biosensors will release thousands of signal molecules that can be detected using a lateral flow assay, similar to a consumer pregnancy or Covid-19 test. Several target DNA sequences will be used for demonstrations: urinary tract pathogens, E. coli, and Salmonella. The target uropathogens are difficult to diagnose with standard culture tests. Using single-base sequence analysis, the biosensors will subtype E. coli as likely pathogenic or likely commensal. A similar strategy will be employed to detect single-base mutations responsible for the majority of fluoroquinolone-resistant Salmonella isolates. DNA biosensing will be demonstrated in clinically relevant human samples, without the extensive purification required by other methods. The result will be a hybrid living biosensor / lateral flow assay that requires minimal sample preparation, produces rapid results, and can achieve single-base resolution. The biosensors developed in this project could find applications any time DNA monitoring is needed that is inexpensive, requires minimal sample preparation, equipment, and expertise, or takes place at the point of care. Examples include clinical diagnostics, monitoring disease outbreaks for public health, or environmental monitoring, with particular benefits where resources are limited.

CIHR Grants and Awards · FY 202526 · 2025-04

Depression is a serious health condition that can significantly impact brain health. In Latino communities, which are often underrepresented in medical research, the effects of depression on the brain are not well understood. This is concerning because Latinos are the largest minority group in the United States and experience high rates of depression. Depression is known to increase the risk of dementia, a condition where memory and thinking abilities decline over time. Our research aims to explore how depression affects brain health in Latino populations. We will examine blood-based markers of brain health and cognitive function to better understand how depression contributes to cognitive decline. By studying these markers, we hope to uncover early signs of cognitive impairment in individuals with depression. This research could help identify people at higher risk of developing dementia and lead to better monitoring and treatment strategies. Latino communities have unique social, cultural, and genetic factors that may affect how depression impacts brain health. By focusing on this group, we aim to address an important gap in research and develop tailored guidelines for managing depression. Ultimately, our goal is to reduce the risk of dementia in Latino communities by improving early detection and treatment of mental health conditions like depression. Keywords: AGING; BLOOD BIOMARKERS; NEUROIMAGING; DEPRESSION

NIH Research Projects · FY 2026 · 2025-04

Project Summary The key focus of this project is to determine the link between genotype and phenotype in the context of Tibetan adaptation to high altitude and to elucidate the currently unresolved mechanism of action through which Tibetans are conferred protection from pulmonary arterial hypertension. The project’s long-term goal is to further the understanding and use of carbon monoxide releasing molecules (CORMs) in treating pulmonary arterial hypertension. Pulmonary arterial hypertension is a global health concern that is characterized by pulmonary arterial wall thickening, vasoconstriction, and thrombus. Recent investigations of populations residing at high altitude revealed that many Tibetans residing at 4,200 m of altitude are protected from maladaptations to hypoxia relative to other populations resident at comparable high altitudes. Specifically, many Tibetans exhibit lower hemoglobin concentrations and pulmonary arterial pressures as well as elevated levels of nitric oxide. The Simonson lab previously conducted a genome wide selection scan of 31 Tibetan individuals, revealing a strong signal of natural selection in a region of the genome encompassing the gene coding for the constitutively active heme oxygenase isoform 2, HMOX2. In a study of individuals of Tibetan descent, they also determined that Tibetans have higher levels of carboxyhemoglobin than individuals of Han Chinese descent living at similar intermediate altitude. Recent studies demonstrate the therapeutic potential of carbon monoxide and CORMs through regulation of inflammatory and vasoactive responses. Together, these findings and preliminary data point to the hypothesis that adaptive changes in Tibetans are associated with a heme oxygenase-mediated increase in carbon monoxide, which confers protection from pulmonary hypertensive indications arising from chronic hypoxic stress. The design of this project’s research strategy is divided into two parts: (1) bioinformatics and functional analysis of Tibetan genetic variation at HMOX2, (2) biochemical and transcriptomic investigation of CORMs. The project’s focus and goals are aligned with NHLBI’s mission. It aims to investigate newly discovered cardiopulmonary traits in Tibetan populations that are key to their adaptation to high altitude and may provide insight into treating pulmonary arterial hypertension. The project seeks to understand, on the genetic and the cellular level, the mechanism by which carbon monoxide might affect the onset and progression of pulmonary arterial hypertension. Importantly, this project sheds light on differences in health in a unique population and identifies factors at the individual level which will contribute to our knowledge of human response to hypoxia.

NIH Research Projects · FY 2026 · 2025-04

Project Abstract The Molecular Signatures Database (MSigDB) knowledgebase, which we introduced almost 20 years ago, is an open access resource of well annotated Human and Mouse gene sets. It is used with multiple gene set based genomic analysis methods to elucidate the biological mechanisms associated with disease and other biological phenotypes, generating hypotheses for further study and experimental validation. As of January 2024, MSigDB provides over 50,000 expertly annotated sets of genes that share common biological function or regulation. MSigDB’s support of a pathway- and biological process-centric view of data analysis has a history of biomedical impact significantly contributing to the study of important questions in biology and medicine across many domains. The impact and popularity of MSigDB are evidenced by its large citation count (>34,000 citations in Web of Science); its continually growing user community (>350,000 registered users from >70 countries worldwide); and its highly used portal (hundreds of thousands of page hits per week). We derive the gene sets in multiple ways: through manual curation of results in scientific publications; computational analysis of publicly available transcriptomic data sets; and mining and curating of public pathway and ontology databases and other public resources. The sets are provided in multiple gene identifier namespaces, using the latest versions of standards established by community-recognized authorities. They are continually reviewed and updated. As we continue to grow the knowledgebase, we prioritize thoughtful selection of new sources and development of gene sets with careful and expert annotation. The sets are available both as investigator- friendly gene set webpages which include information on the origin of the set and biological annotation, as well as machine readable forms for use by software developers and bioinformaticians for programmatic access, testing of new methods, and inclusion in other resources. The interdisciplinary MSigDB team includes computational and genomic scientists, a scientist curator with a PhD in biology, computer science experts in natural language processing, and experienced software engineers. We seek funding of MSigDB for the next five years to continue our support of the large community of biomedical investigators who depend on it for their work. We will: 1) continue to thoughtfully expand the content of MSigDB and keep it up to date with semiannual releases; 2) enhance and optimize the MSigDB build and quality assurance process; 3) explore the use of large language models (LLMs) to assist in gene set annotation; 4) perform a major update of the MSigDB portal architecture and implementation; 5) enhance the MSigDB tools for gene set exploration; 6) continue our high-value user support and increase community engagement.

NIH Research Projects · FY 2025 · 2025-04

Project Summary: Discovery of glia-to-neuron identity conversion has opened the door for generation of new neurons to replace those lost to injury, aging or neurodegenerative disease including Huntington’s disease (HD) and Frontotemporal dementia (FTD). To this, I have used a therapeutically viable approach to successfully generate new neurons in the neurogenic niches of the aged adult mouse brain by transiently suppressing the RNA binding protein Polypyrimidine Tract Binding Protein-1 (PTBP1) using an antisense oligonucleotide (ASO) delivered by a single injection into cerebral spinal fluid. I further identified that Radial glial-like and subependymal-like cells (not astrocytes) convert into new neurons over a two-month period, acquire mature neuronal character, and functionally integrate into endogenous circuits that modify mouse behavior. Not yet established are the molecular events underlying glia-into-neuron identity conversion, including identification of the initiating glial cell(s), the events driving its conversion and subsequent maturation into a functional neuron, and application to HD and FTD. Additionally, the challenges pertaining to astrocyte-into-neuron conversion upon PTBP1 reduction have yet to be resolved. In this proposal, I will utilize combination of traditional single nuclear sequencing and immunofluorescence with a transformative single cell spatial transcriptomics technology, termed Multiplexed Error Robust Fluorescence In Situ Hybridization (MERFISH), to define the pathway(s) of generation of new neurons in aged neurogenic niches following a therapeutically viable injection to produce transient, ASO-mediated suppression of synthesis and accumulation of PTBP1. I will then extend the effort to test in mouse models of Frontotemporal dementia ( FTD) and Huntington’s disease (HD) whether glia-to- neuron conversion can generate functional replacement neurons. By leveraging my expertise with a network of collaborators I have assembled at UCSD and the surrounding research communities in San Diego, as well as strong collaboration with field leaders abroad, I will systematically identify the functionality, localization, cell origin and molecular pathways of glial cells undergoing identity conversion at multiple time points post conversion in healthy, FTD and HD contexts. During the mentored K99 phase, I will receive training under the guidance of Prof. Don Cleveland, who has trained more than 65 postdoctoral fellows, including 42 who at the end of their training obtained faculty positions. I have also assembled an outstanding team of collaborators including MERFISH pioneer Dr. Bogdan Bintu (UCSD), the Chief Scientific Officer of Ionis Pharmaceuticals Dr. C. Frank Bennett, neurogenesis expert Dr. Alysson Muotri (UCSD), and single nuclear sequencing expert Dr. Xin Jin (Scripps Research Institute) to assist my proposed research and provide me with additional scientific training and career support before, during, and after transitioning to an independent tenure-track faculty position. In the R00 phase, I will begin my long-term career goal of establishing a research program to understand adult neurogenesis and use mechanistic insights in reprograming for therapy development.

NIH Research Projects · FY 2025 · 2025-04

Abstract Repetitive transcranial magnetic stimulation (rTMS) has emerged as a promising intervention for treatment- resistant depression (TRD), yet substantial uncertainties persist regarding its efficacy as a maintenance treatment. This prospective study seeks to investigate the efficacy of maintenance rTMS in individuals with TRD who have previously responded to an acute course of rTMS. In the R61 phase of the study, we will recruit 75 participants across three study sites, the University of California San Diego, Cornell University, and Australian National University, into a double-blind, three-arm maintenance treatment trial. In this trial, participants will be randomized to receive either standard maintenance rTMS, clustered maintenance rTMS, or sham maintenance rTMS for a duration of 6 months. Our primary aim is to examine the efficacy of maintenance rTMS on sustaining connectivity between the dorsolateral prefrontal cortex (DLPFC) and subgenual cingulate cortex (SGC) measured through concurrent TMS and electroencephalography (TMS-EEG) at baseline and every six weeks throughout the 6-month treatment period. We will also assess changes in depressive symptom severity using clinical scales including the Montgomery-Asberg Depression Rating Scale (MADRS) as a secondary outcome measure. It is hypothesized that stimulation with clustered maintenance rTMS will demonstrate superiority in sustaining DLPFC-SGC connectivity compared with standard maintenance rTMS and sham maintenance rTMS. In the R33 phase, we propose to conduct a randomized 2-arm double-blind, parallel clinical trial comparing the superior arm of the R61 phase with sham maintenance rTMS in 144 patients with TRD who have responded to an acute course of rTMS treatment. The primary outcome of interest for this phase will be clinical symptom maintenance measured with the MADRS, with the expectation that the active arm will lead to significantly better sustained symptom relief than sham. As a secondary analyses, DLPFC-SGC connectivity derived through TMS- EEG will be evaluated to compare between treatment arms and correlate with symptom change. It is anticipated that active maintenance rTMS will lead to more sustained DLPFC-SGC connectivity than sham and that connectivity will correlate with symptoms, providing a biomarker of treatment response that can potentially be used for prescriptive selection of patients for maintenance treatment and as a measure of neuroplasticity for continued scientific discovery. The overall goal of this research is to determine the most effective form of maintenance rTMS treatment for patients with TRD and to understand the neurobiological underpinning of maintenance rTMS treatment response.

NIH Research Projects · FY 2026 · 2025-04

ABSTRACT Intraductal papillary mucinous neoplasms (IPMN) are common cystic neoplasms of the pancreas that may progress to pancreatic ductal adenocarcinoma (PDAC), a lethal disease with a current 5-year survival rate of 12%. The management for patients with IPMN high-risk features, mandates surgical resection in patients fit for surgery. While surgical resection is curative for some individuals, pancreatectomy carries significant risk of postoperative morbidity, and IPMNs reoccur in 30 – 60% of patients with invasive disease. Strikingly, 4-5% of patients with IPMN biopsies containing pathological features that reveal high grade dysplasia will be diagnosed with invasive PDAC within 5 years of their pancreatectomy. As such, identifying effective interception strategies for IPMN is a significant unmet need. Here we have based our research approach on reverse translational experiments where we have identified that the presence of co-oncogenic driver mutations in KRAS and GNAS renders multiple cancer types originating from different organs susceptible to CDK4/6 inhibition in patients. As ~70% of IPMN tumors contain KRAS and GNAS co-mutation, here we will determine the impact of CDK4/6 inhibition on IPMN tumor progression in genetically modified mice and PDX models of IPMN, where we can tightly regulate the timing, dosing, tumor genetics, as well as analyze tumor responses in pre-clinical models. In addition to studying endpoints of tumor progression and survival, we will determine the effects of CDK4/6 inhibition on the tumor microenvironment of IPMN. The results of these studies will provide key translational data that will propel future human clinical trials.

NSF Awards · FY 2025 · 2025-04

Conversational models are permeating all aspects of society, including systems for clinical support, education, gaming, etc. Such systems have remarkable capacity to personalize their outputs. For example, a user wishing for movie recommendations might describe their current circumstances and the types of movies they normally enjoy. In response, a language model might suggest a list of movies that use similar descriptions related to the request. This project will explore limitations of conversational models for problems related to personalized recommendation. Specific areas of focus include collecting new datasets for model training and evaluation; ensuring that language models recommend items fairly; and exploring evaluation protocols to make sure recommendations are aligned with human preferences. This project will have benefits in settings where language models are used to make personalized recommendations, spanning applications from movie recommendation to personalized clinical support. General-purpose language models act as powerful conversational recommenders despite having never been trained for the specific purpose. This project will explore new approaches to conversational recommendation, revisiting issues of data, methodology, and evaluation. First, the project will collect new datasets that are large, naturalistic, highly contextual, and carefully annotated. Second, the project will explore knowledge grounding and controllability in conversational recommenders, especially with a goal of performing fairness and bias interventions. Finally, the project will explore model evaluation, especially by developing simulation approaches that allow conversational models to be evaluated offline by mimicking the behavior of real users. This project extends research in each of the areas in which it builds: recommender systems, NLP, controllability, and fairness. Closing the research gap between these areas enables a host of exciting new applications dealing with mixed datasets that combine language with user interaction data, ranging from standard recommendation problems, to personalized language understanding tasks in fashion, health, and therapy, among others. The project aims at fostering the retention and involvement of groups including underrepresented minorities, high-schoolers, and engineering 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.

NIH Research Projects · FY 2026 · 2025-04

Project Summary/Abstract: Biophysical modeling of membrane curvature generation for inward and outward budding. Curvature generation of cellular membranes is important for communication between the intracellular and extracellular space. During endocytosis, cells curve their plasma membrane inward to take up cargo from the extracellular space. In contrast, during the formation of extracellular vesicles, the plasma membrane curves outwards. Both of these processes are fundamental to cellular function and defects in these processes are implicated in cancer, altered neurotransmission, inflammation, and heart disease. While many distinct proteins are involved in membrane curvature generation, they ultimately work together to generate mechanical stress at membrane surfaces. As a result, biophysical modeling has become an important tool for understanding how curvature may be generated. These models often treat the membrane as a thin lipid bilayer without detailed considerations of the interactions of the membrane with the environment. As a result, many of these models ignore the fundamental aspects of curvature generation: the lipid and protein compo- sition of the membrane, interaction of the membrane with the actin cortex, and interaction of the membrane with key components of the extracellular matrix including the glycocalyx. Research in my group in the past 5 years has made fundamental advances in our understanding of the biophysics of membrane curvature generation that support the hypothesis that interaction of the lipid bilayer with the cytoskele- ton and the glycocalyx generate differential stresses across the membrane, which ultimately controls the direc- tion of membrane bending. The magnitude of these stresses depends on the specific biochemical properties of the molecules involved. Specifically, in endocytosis, we showed that membrane composition can alter membrane tension and therefore the energy required for endocytosis. Furthermore, we showed that the organization of the cytoskeleton and linker molecules along the endocytic pit is a critical determinant of force generation during endocytosis. We also showed that detachment of the membrane from actin cortex is a critical determinant of effective outward budding for extracellular vesicle formation. These findings lead us to the following urgent questions about how cellular membranes might generate curvature for endocytosis and extracellular vesicle formation: First, how does the asymmetry due to lipid and protein composition determine the direction of membrane budding? Second, how does the interaction with the actin cytoskeleton drive membrane bending for endocytosis and extracellular vesicle formation? And finally, what role does the glycocalyx play in altering the direction of membrane bending? Building on our recent discoveries, we aim to answer these questions using computational modeling to generate experimentally verifiable predictions. These predictions will be tested by experiments conducted in the Stachowiak, Wehman, and Drubin labs. By incorporating the mechanistic details of the composition of the plasma membrane, glycocalyx, and the actin cytoskeleton, the quantitative modeling framework we propose to develop will be applicable to wide range of cellular phenomena.

NIH Research Projects · FY 2025 · 2025-04

Project Summary/Abstract Cardiac fibrosis remains a global health problem that results from highly coordinated interactions between macrophages, versatile cells of the innate immune system, and fibroblasts, cells responsible for extracellular matrix production. Initial stages of fibrosis are characterized by an acute inflammatory response that spans a period of hours-days and is followed by a healing phase which lasts days-weeks. This creates a complex microenvironment consisting of biochemical stimuli that modulates cell function resulting in the replacement of native tissue with a more elastic and less viscous scar tissue. However, while the effects of biochemical cues have been studied, traditional co-culture methods lack spatial and temporal control to mimic the in vivo environment. For example, static culture methods, including conditioned media transfers and direct co-cultures, are unable fully recapitulate the close proximity of cell-cell signaling and the dynamic switch from inflammatory to healing responses in macrophage activation state to study biochemical and physical cell-cell interactions. In addition to biochemical cues, the altered mechanical environment also exposes cells to biophysical stimuli, including tissue elasticity and viscosity, that have been shown to regulate macrophage and fibroblast function independently, but the effects of mechanical stimuli in modulating macrophage-fibroblast interactions are unknown. Moreover, Marfan syndrome, an autosomal dominant inherited disorder characterized by mutations to the fibrillin-1 gene, results in enhanced cellular oxidative stresses which promote pro-fibrotic cell function and alter cardiovascular tissue mechanics. However, the resulting effects on macrophages and fibroblasts as well as the role of a changing mechanical landscape in pathology are unknown. Preliminary work identified the importance of macrophage-fibroblast signaling in promoting fibrotic responses. However, several key questions remain. In this study, I hypothesize that a fibrotic environment, characterized by enhanced elasticity and reduced viscosity, promotes macrophage pro-fibrotic signaling to cardiac fibroblasts which, in turn, exacerbates cardiac fibrosis. To evaluate this hypothesis, I will develop and utilize a modular engineered cell culture system to investigate the effects of elasticity and viscosity in macrophage and fibroblast function independently and in dynamic cell-cell interactions to promote pro-fibrotic signaling (Aim 1). Additionally, I will elucidate the role of elasticity and viscosity in regulating oxidative stresses to promote pro-fibrotic macrophage- fibroblast signaling in Marfan Syndrome (Aim 2). The completion of these aims will not only provide a better understanding of material mechanics within cardiovascular disease but may also uncover molecular targets which can directly influence macrophage-fibroblast signaling and the progression of cardiovascular fibrosis.

NIH Research Projects · FY 2025 · 2025-03

PROJECT SUMMARY/ABSTRACT The overall objective of the R25 Focused Research Education and Experience using Multimodal and Interdisciplinary NIH Datasets (FREEMIND) Program is to develop a diverse workforce in biomedical research who will also be long-term users of datasets supported by the National Institutes of Health (NIH), including NIH Common Fund datasets. The proposed program is designed to expand and diversify the pipeline of new investigators in biomedical research. The program will include an intensive, two-week, in-person bootcamp course at UC San Diego designed around providing hands-on instructional guidance for using data from two Common Fund Programs, Bridge2AI and SPARC, as well as the NIH All of Us Research Program. Jointly, these datasets provide a multimodal set of data (e.g. electronic health records [EHRs], imaging data, waveform data, omics data) and offer great potential to train participants of the program in analyzing large complex datasets across multiple disciplines (diabetes research, neuromodulation, biology, etc.). This program will be led by an interdisciplinary team with a wide range of research expertise and a strong track record of training, education, and mentorship. Participants will be graduate students, medical students, postdoctoral fellows, and early career faculty (early stage investigators). They will engage in virtual didactic instruction both before and after the bootcamp. The program includes a strong mentoring component, with faculty mentors providing input on designing and executing projects using the NIH-supported datasets. During the bootcamp, participants will complete projects in small groups and deliver oral presentations to discuss their results. The educational program will include instruction on accessing and analyzing these datasets as well as in rigor and reproducibility, responsible conduct of research, team science principles, and the practical aspects of conducting large-scale, multi-disciplinary scientific collaborations. Innovations in this program include leveraging real-life datasets, emphasizing multimodal analyses, and providing intensive guidance in a focused format accessible to a broad array of participants, including clinician-scientists. The program will support participants as they pursue publication and presentation opportunities to advance their careers. Broad outreach will be conducted to enable diverse recruitment, and intensive program evaluation will be conducted to facilitate iterative improvements to the syllabus and program administration. Program faculty include leaders of the NIH-supported datasets being taught. By completing these aims, we will promote the broad and rigorous use of Common Fund and other NIH-supported data among diverse participants in the formative stages of their careers and help facilitate their advancement toward independent research careers and to becoming long-term users of NIH datasets.