University Of California, San Diego

NIH Research Projects · FY 2025 · 2024-09

PROJECT SUMMARY/ABSTRACT Tumor vascular networks are highly abnormal and complex, vary significantly by tumor type and on a patient- by-patient basis. More importantly, patient-specific tumor vascular properties are known to regulate cancer progression and treatment response in patients with primary or metastatic liver cancers. Non-invasive rapid diagnostic methods to characterize unique tumor vascular properties in liver malignancies, and to provide clinical decision-support, are currently not available. Our goal is to introduce computational approaches to characterize complex attributes of vascular networks by considering the interconnected nature of voxels in 3D dynamic contrast-enhanced ultrasound (3D DCE-US), and to validate these as biomarkers for diagnostics or treatment monitoring. We have already contributed to pioneering 3D DCE-US liver imaging in the clinic and have demonstrated its ability to minimize 2D-based sampling errors and improved prediction of treatment response longitudinally. However, current quantification approaches are designed for 2D imaging and do not take into account vascular heterogeneity and the contrast flow field. In addition, conventional parameters that are typically extracted from averaged intensities in large regions of interest fail to account for spatial variations of perfusion common in complex tumor tissues. The exclusive volumetric nature of our data along with the intravascular nature of ultrasound contrast agents, has allowed us to demonstrate that additional information is encoded in spatial flow maps beyond convention, and that this information is sensitive to treatment response and representative of the underlying true vascular network. Thus, our hypothesis is that characterizing the interconnected nature of voxels in 3D DCE-US can capture new information from volumetric tissues for cancer applications, and beyond cancer. Therefore, we propose a set of specific aims designed to test this hypothesis by: i) further developing and ii) extensively validating new perfusion measurements to characterize different tumor vascular properties and detect subtle microvascular changes following therapy, and iii) clinically validating their clinical utility for diagnostics and treatment monitoring in real patients imaged with 3D DCE-US. Our proposal takes advantage of the recent clinical introduction of commercial ultrasound contrast agents and 3D imaging probes to advance non-invasive bedside liver imaging for capturing complex flow beyond convention.

NIH Research Projects · FY 2025 · 2024-09

Project Summary Genitourinary syndrome of menopause (GSM) is an extremely prevalent condition consequent to the hypoestrogenic changes in the genitourinary tract that affects up to 85% of perimenopausal and menopausal women. Major symptoms of GSM include vaginal dryness, itching, discomfort, burning, and pain; thus, GSM significantly impacts quality of life during everyday activities and severely impairs sexual function. Despite its high prevalence and interference with healthy aging, current treatments for GSM are suboptimal, with many issues related to accessibility or long-term efficacy. Despite an astoundingly low satisfaction of only 35% with treatments for GSM, whether prescribed or over-the-counter, women continue to suffer from lack of better options. Thus, there remains a need for a safe and accessible therapy for this morbid condition that can both alleviate symptoms and restore a healthy vaginal phenotype. The proposed study will determine if a low-cost, acellular, tissue-specific, and minimally invasive regenerative therapy can repair the atrophic vaginal tissue, resulting in an accessible, high-impact intervention for GSM. Given our previous successes with tissue-specific pro-regenerative biomaterials, we opine that a novel vaginal tissue-derived ECM hydrogel (vECM) will reverse vaginal atrophy by inducing epithelial cell proliferation and differentiation as well as neovascularization when delivered as a topical treatment, and by improving tissue elasticity and smooth muscle phenotype when delivered via injection. Using a validated preclinical model of GSM and an array of diverse multi-scale tools, we will comprehensively characterize alterations in vaginal structural and functional properties due to menopause. We will then create a novel biomaterial designed specifically to women’s health and assess its efficacy in treating GSM – a chronic and understudied condition that negatively impact lives of millions of women world-wide.

NIH Research Projects · FY 2026 · 2024-09

Project Summary/Abstract Surgical complication represents one of the biggest factors impacting quality of care and is one of the major burdens on the healthcare system. There are 40-50 million surgical procedures performed in the US annually with a mortality rate of 1.3% (650,000 people) and morbidity rate of ~14% (7M people). The mortality rates significantly increase for patients who are frail, with a heightened risk of 5.1%, and continues to increase into 90 and 180 days for those who are deemed very frail, reaching a staggering 43%. The difficulty in increasing surgical success is not necessarily in improving the surgical procedures, but rather the perioperative care that surrounds the surgery: pre-habilitating the patient into fitness prior to surgery, improving patient recovery to discharge patients to recover comfortably at-home, detecting onsets of complications early to provide non-emergent treatment. The main objective of this project is to develop a hand grip strength (HGS) measurement solution based completely on a smartphone application that converts the phone’s vibration motor and sensor into a mobile dynamometer. Our scientific premise, demonstrated by a berth of clinical evidence, is that hand grip strength provides a biomarker of physical frailty that corresponds to general physiologic reserve and cardiopulmonary status, as well as systemic inflammation. Prior studies have linked a diminutive HGS preoperatively to heightened risk of surgical complications. This corresponds well to evidence that frailty, which correlates strongly to a weakened HGS, is a major risk factor for surgical complications due to the extremely taxing nature of surgical procedures on the body requiring a level of fitness to recover after the operation. Although HGS as a measure is possible with commercial HGS dynamometers, a smartphone-sensor enabled digital dynamometer can make measurements guided through adaptive interface, automatically digitized, and integrated with ML analytics. With the patient’s own smartphone, progress of pre-habilitation can be assessed to determine fitness to undergo surgery, changes in health status can be detected, and timely changes in surgical plan can be made. To increase the scalability of HGS screening, we propose a smartphone assessment that patients, including older adults, can administer themselves at home that tracks changes in HGS during the preoperative period. We will further develop and evaluate different machine learning algorithms that use the HGS feature biomarkers measured by the phone to perform automated risk prediction of postsurgical outcomes. Because the project would be carried out in the rich research context of UC San Diego Division of Perioperative Informatics in the School of Medicine in conjunction with the Anesthesiology Preparedness Clinic, it will be possible to validate the mobile dynamometer assessments with a cohort of surgical patients undergoing medium to high-risk procedures that would benefit most from a stratified risk assessment protocol. Our translational goal is to provide access to low- cost, digital at-home HGS monitoring to transform the way perioperative care is conducted, from one that is sparse and poorly assessed, to one that is highly integrated through close monitoring and feedback.

NIH Research Projects · FY 2026 · 2024-09

We will conduct a hybrid type 1 study to evaluate efficacy and preliminary implementation considerations for a novel intervention to promote uptake of drug checking services (DCS) and safer drug use behaviors among people who use drugs (PWUD) to reduce incidence of overdose (OD) in San Diego County. Along with ~50 other syringe services programs (SSPs) in the US, a local SSP recently began CheckSD, a DCS using test strips (TS) and Fourier Transform Infrared Spectrometry (FTIR) that allows people to submit drug samples with non-nominal identifiers and obtain personalized results. While CheckSD and most existing DCS with FTIR offer some counseling about DCS results, no theory-based interventions to increase DCS uptake and promote post-DCS adoption of safer drug use behaviors have been rigorously evaluated. We drew from the Social Ecological Model and Social Cognitive Theory (SCT) to develop and pilot MI-CHANCE (Motivational Interviewing for Community-based Harm reduction And drug-Checking Empowerment), a brief, bilingual, peer-led MI intervention. We culturally-tailored MI-CHANCE because Latinx PWUD are less likely to access harm reduction services, contributing to racial/ethnic disparities in OD rates. Our Aims are: Aim 1. To test the efficacy of MI-CHANCE on rates of combined fatal and non-fatal OD over 30 months and examine SCT-informed mediators and moderators of intervention effects (i.e., knowledge, outcome expectancies, self-efficacy). Aim 2. To conduct an inward-looking implementation evaluation to examine MI-CHANCE acceptability, feasibility and experiences among i) trial participants and ii) SSP staff in San Diego County; iii) collect data on implementation costs of MI-CHANCE and CheckSD to inform adoption by SSPs and policy-makers. Aim 3. To conduct an outward-looking exploration of MI-CHANCE's scalability among SSP staff at 20 other U.S. locations, purposively sampled to represent nascent and established DCS. To meet Aim 1, we will recruit 588 PWUD who have not yet used CheckSD into a two-arm RCT (N=294 per group). Both arms will have access to CheckSD's standard of care (SOC) already available at SSP sites (i.e., FTIR, and overdose education and naloxone distribution). PWUD randomized to receive MI-CHANCE will receive it from peer counselors trained in MI to encourage CheckSD uptake and safer drug use behaviors. Those in the attention-control SOC arm will receive COVID-19 education. All will undergo semi-annual follow-up for 30 months. Aims 2-3 will be guided by the revised RE-AIM/PRISM implementation science framework. This will be the first trial to rigorously evaluate efficacy and preliminary implementation of an intervention to optimize DCS uptake and behavioral outcomes for reducing OD. Despite the high promise of DCS, it is an innovation for which real world implementation is ahead of—but could be strengthened by—empirical research on behavioral intervention and implementation supports. If MI-CHANCE is efficacious, it could be rapidly deployed at harm reduction programs across the country to reduce OD deaths and disparities due to changes in the drug supply. This study is part of the NIH’s Helping to End Addiction Long-term (HEAL) initiative to speed scientific solutions to the national opioid public health crisis. The NIH HEAL Initiative bolsters research across NIH to improve treatment for opioid misuse and addiction.

NIH Research Projects · FY 2025 · 2024-09

PROJECT SUMMARY IDHwt glioblastoma (GBM) patients still live an average of ~15-months, despite advances in multimodal therapy. A central issue confounding treatment is the heterogeneous nature of this aggressive tumor. Transcriptomics has defined three GBM molecular subtypes - proneural (PN), classical (CL), and mesenchymal (MES).7 Individual tumors typically harbor mixtures of all three subtypes in spatially distinct subpopulations with different mutation profiles, making mutation- or pathway-specific therapies less effective. While cell-intrinsic mechanisms of therapeutic resistance have garnered considerable scientific attention, much less is known about cellular interactions in the tumor microenvironment that contribute to therapeutic recalcitrance. A hallmark mutation in 60% of GBM is amplification and mutation of the epidermal growth factor receptor (EGFR). The most common EGFR alteration, EGFRvIII, results from deletion within its extracellular domain, yielding a constitutively active receptor that conveys tumor-enhancing and therapy-resisting functions.8 Genetic and pharmacological data from our lab show that EGFRvIII activity, specifically in the context of PI3K pathway activation, results in nuclear localization of the NF-kB subunit RelA (p65), its association with members of the BET (bromodomain and extra terminal domain) family of acetylated lysine-binding proteins, and transcriptional activation of inflammatory genes.6,9 The requirement of RelA acetylation at lysine 310 (acK310-RelA) for BET bromodomain interactions10 and the central role of NF-kB in driving a PN/CL to MES phenotype transition (collectively MES transition – MESt),6,11 immune evasion,3 and therapy resistance12 leads us to postulate that the acK310- RelA:BET protein complex is a druggable regulatory switch mediating MESt and treatment resistance. The goal of this project is to dissect and target mechanisms whereby tumors undergo MESt and acquire therapeutic resistance through the acK310-RelA:BET switch. We have identified a druggable node of specific bromodomains, through precise drug targeting, that controls the pro-inflammatory activity of the acK310- RelA:BET complex.6 The following lines of experimentation will be employed in the newly diagnosed and recurrent GBM settings. SA1 will use genetic and pharmacological approaches to determine upstream effector mechanisms mediating RelA K310 acetylation and associated MESt, including abundance of tumor-associated microglia and macrophages (TAM), and resistance to standard-of-care (SOC) therapy. SA2 will functionally analyze BET family members BRD2-4 through gene knockout, gene editing, inducible protein degradation, selective bromodomain (BD1, BD2) drug targeting, and assessment of acK310-RelA:BET induced transcription programs and associated epigenomic rewiring. SA3 will specifically focus on the recurrent GBM setting, where we will investigate direct drug targeting of the acK310-RelA:BET interaction to mitigate resistance to salvage radiation and promote phagocytotic recognition by TAM. These studies will be central to identifying a therapeutically tractable node promoting MESt and nominate a specific drug for further development.

NSF Awards · FY 2024 · 2024-09

This project will advance national health and promote science and technology development by providing algorithms, software, and systems that can train foundation models on clinical time-series data for accurate and early detection of sepsis. Sepsis is a life-threatening condition that occurs when the body's response to an infection is out of control, leading to widespread inflammation, multiple organ failure, and eventually death. Early prediction of sepsis is crucial for timely intervention and improved patient outcomes. The detection of sepsis hinges on the interpretation of clinical time series (CTS) data. These data are inherently complex, characterized by their high-dimensional nature and the inconsistent timing of measurements. This project will build innovative technologies to develop robust foundation models, also known as large pretrained models, to process and learn from these intricate CTS data streams for acquiring a deep understanding of the temporal patterns leading to septic shock and enabling the detection of early warning signals that conventional methods might miss. The project will significantly improve the accuracy and timeliness of sepsis detection, which enables physicians to take early life-saving treatment interventions to prevent septic shock, organ damage, and death. Furthermore, pretrained on a broad spectrum of CTS data, these foundation models will effectively accommodate the variability across different patient populations and clinical settings. In addition, these models do not require large amounts of labeled data, reducing the burden on healthcare systems to provide extensive annotated datasets. To achieve the goal of developing foundation models on CTS data for sepsis early detection, this project will develop four thrusts of novel approaches, each pivotal to the lifecycle of developing foundation models. First, the project will develop CTSformer, a new Transformer-based model specifically for clinical time series (CTS) data. CTSformer is designed to adeptly cope with the complexities inherent in CTS datasets, such as irregular intervals and incomplete data entries. Second, the project will develop a pretraining method capable of automatically discovering an optimal masking strategy for time points in CTS data, eliminating the need for extensive manual tuning. Third, the project will develop a new parameter-efficient finetuning approach that differentiably optimizes layer-specific ranks within low-rank adaptation, enhancing finetuning accuracy and computational efficiency. Fourth, this project will develop bi-level optimization-based methods to enhance the interpretability of CTS foundation models. The proposed approaches are underpinned by a cohesive methodological foundation, which is bi-level and multi-level optimization, enabling end-to-end learning at task level. Together, these approaches converge to address the crucial medical challenge of early sepsis detection. This project effectively addresses a fundamental knowledge gap that existing foundation models are inadequate in dealing with complex CTS data, incur high computational cost, require time-consuming labor-intensive manual tuning, and are difficult to interpret. It represents the first one developing effective, computationally efficient, and interpretable foundation models on CTS data for sepsis early detection. 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 2024 · 2024-09

Project Summary/Abstract (max: 30 line limit) Adult neurons in the central nervous system fail to regenerate after spinal cord injury (SCI). Large-scale screens performed in vitro and in vivo have identified many genes that regulate axonal regeneration, including PTEN, SOCS3, c-Myc, the KLF family of transcription factors, and more. In the optic nerve model, the greatest enhancement of axonal regeneration is achieved by targeting multiple genes in combination, such as co-deletion of PTEN and SOCS3, or PTEN deletion combined with overexpression of c-Myc and CNTF. However, no screens have systematically compared the combined knockdown or overexpression of different gene combinations, and the power of large in vivo screens may be limited by the need to individually test every candidate and between-subject variability. In this study, we propose to perform the first pooled in vivo screening of regenerative combination therapies in a mouse model of SCI, which could identify new combinations of genetic targets that more potently enhance both the number of regenerating axons and the distance of axonal regeneration after SCI. We will employ newly available tools for genetic knockout and overexpression to efficiently perform multiple in vivo screens, using a Cre-dependent barcode and next-generation DNA sequencing to simultaneously compare a pooled library of 36 candidates in a single animal. Our proposal is divided into two Aims. Aim 1 will use CRISPR to first compare the genetic knockout of 36 individual candidate genes that are known to limit axonal regeneration. After identifying the 9 individual knockouts that most potently enhance regeneration, we will then screen every possible pair of the top 9 gene knockouts in combination. Aim 2 will first compare the overexpression of 36 individual candidate genes that are known to promote regeneration. We will then combine the 6 most effective overexpressed genes with the 6 most effective knockout pairs to screen 36 unique combinations of one overexpressed gene and two gene knockouts. Every screen will use a pooled library to directly compare all 36 candidates within the same animal. To our knowledge, systematic screening of multiple gene knockouts, or of combined knockout and overexpression, has not been previously performed in any model of axonal regeneration. Future studies will evaluate the functional benefit of the most effective combination therapies in a clinically relevant SCI model. We thus propose a new method for pooled in vivo screening of genetic therapies for SCI, which could identify new translational combination therapies that enhance axonal regeneration and improve functional recovery.

NIH Research Projects · FY 2025 · 2024-09

Mortality statistics in the United States show a steady increase in deaths due to prescription opioids over the past two decades, accompanied by a steep increase in heroin-related deaths from 2011 onward and deaths from synthetic opioids such as fentanyl from 2014 onward. An unexpectedly steep rise in the drug-related overdose rate for middle aged to older adults (50-65) in recent years has placed attention on the specific health risks for this population. Lethality data are but the tip of the iceberg of a much larger problem of opioid misuse and opioid use disorders. Therefore, these studies seek to explore how the middle age range of adulthood may influence opioid reward and addiction. The proposed studies will first determine any age-related differences in the involuntary effects of opioids on locomotion, nociception and thermoregulation. Studies will also use well established rat models of intravenous self- administration to model reward, initial acquisition and escalation of opioid drug seeking in young-adult and middle-aged rats. Additional experimentation will determine how brain reward may be modified across the lifespan and how these changes may produce liability for, or resilience against, prescription opioid abuse. Together, the Aims will investigate how the middle- aged adult developmental stage may influence in vivo sensitivity to oxycodone, heroin and fentanyl, relative to younger adulthood, and ultimately will investigate if middle age conveys any change in the propensity for self-administration of opioids.

NIH Research Projects · FY 2025 · 2024-09

PROJECT SUMMARY Withdrawal is a major obstacle in overcoming opioid dependence and addiction. Identifying the neural circuits involved and how opioids modulate the activity of those circuits is essential for developing new therapeutic approaches to prevent or treat opioid use disorder. The medial habenula (MHb) projects primarily to the interpeduncular nucleus (IPN) and has long been known to express high levels of the Mu-opioid receptor (MOR). Activity in this circuit has been associated with expression of fear and anxiety; and repeatedly implicated in mediating aversive qualities of nicotine and nicotine dependence. Emerging evidence also supports a role for MHb projections to IPN in the somatic and affective symptoms of opioid withdrawal. Despite this, there is remarkably little information on what cell types in both MHb and IPN express MOR, how MOR signaling influences this circuit, and whether chronic MOR signaling induces physiological changes in this circuit that contribute to withdrawal. In this proposal we propose experiments to inform each of these questions using a combination of molecular, physiological, and behavioral approaches to investigate MOR-expressing neurons in both MHb and IPN of mice. Based on prior literature and preliminary data we posit an important role for excitatory neurons in lateral MHb and inhibitory neurons in rostral IPN in mediating aversive qualities of opioid dependence that contribute to withdrawal and relapse.

NSF Awards · FY 2024 · 2024-09

The University of California, San Diego will generate and evaluate culturally relevant computing resources for Latine students in undergraduate Computer Science (CS) programs by creating a culturally relevant textbook for introductory programming and conducting controlled experiments to compare its effectiveness against traditional textbooks. Latin Americans (Latines) have historically been underrepresented in computing in the United States. To address challenges of diversity, equity, and inclusion, Culturally Relevant Computing (CRC) has been gaining popularity, showing increased student engagement, interest, and understanding, especially in K-12 education. However, there is limited research on CRC's effectiveness in higher education. One popular CRC method in higher education is bilingual education, where teaching is conducted in both the students' native language and English. Prior studies in bilingual education (in India and the United States) have shown that although bilingual teaching improves student engagement, there is no evidence on the effectiveness of bilingual education on student learning, if the study resources (e.g., textbooks) that students use are still in English. At the same time, a series of studies in bilingual education by Yogendra Pal et. al show that there is an improvement in student learning, if the study resources are culturally relevant (e.g., resources in students' native language). This Broadening Participation in Computing Demonstration Project seeks to address a critical gap in the research of CRC in higher education and contribute valuable insights into the effectiveness of CRC resources in attracting and retaining Latine students in the field of computing. The project team will conduct these interventions at both a Hispanic-Serving Institution (HSI) and an emerging HSI to understand the impact of culturally relevant resources on Latines in majority- and minority-Latine classrooms, as well as on non-Latines. The control group will be students taking their CS1 course using their original, traditional textbook that has previously been used for that course. The experimental group will be students taking their CS1 course using our newly generated, culturally relevant textbook. Our culturally relevant textbook will cover all the topics that are typically covered in a CS1 course (e.g., functions, conditionals, loops, lists) taught at these institutions. The experiments will focus on evaluating the efficacy of CRC resources with respect to student learning, retention, sense of belonging, self-efficacy, attitudes towards the culturally relevant material, and attitudes towards computing in a CS1 course. The findings from this research can serve as a model for creating inclusive computing curricula that resonate with diverse student populations. By improving the learning experiences of Latine students in introductory programming, this project could positively impact retention rates and inspire more Latines to pursue advanced studies and careers in computing. 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 2024 · 2024-09

Project Summary/Abstract Chronic pain is a debilitating condition that is widely treated with prescription opioid drugs over extended periods of time. The high prevalence of opioid addiction with abuse and death is now a severe national crisis in the US. In Jordan, opioid analgesics are highly restricted in their use, and many people suffer from untreated pain. To address these unmet needs, the goal of this project will be to discover novel natural products that are potent BBB permeable inhibitors of cathepsin L to produce a lead candidate drug molecule(s) that reduces spinal dynorphin and attenuates chronic pain without addiction. This goal is based on compelling evidence showing that spinal dynorphin is a key mediator of chronic pain, and cathepsin L is largely responsible for the production of dynorphin from its inactive prodynorphin. These findings support the hypothesis that inhibition of cathepsin L will lead to reduction of dynorphin and alleviation of chronic pain. An important dimension of this project will be to enrich for BBB permeable natural products and plant extracts early in the discovery process using an in vitro-parallel artificial membrane permeability assay (PAMPA-BBB) in a CNS-targeted workflow. For the purpose of screening, we will choose three distinct sets of natural product extracts and pure compound libraries from various sources and regional areas, thereby enhancing the diversity in this project. The University of Jordan (JU), UC San Diego and the NIH-DTP Repository will be subjected for initial screening for their cathepsin L inhibitory activity at concentrations from 1-10 µg/mL. Active crude extract materials from these screenings will be subjected to the PAMPA-BBB assay. Permeable eluents and impermeable retentates from this assay will be evaluated for cathepsin L activity and profiled by LC-MS/MS metabolomics. Finally, focused/targeted isolation and structure elucidation efforts will be done on fractions that show several positive selection criteria: promising biochemical activity against cathepsin L, BBB+ in the PAMPA permeability assay, novel structural features compared to known cathepsin L inhibitors, and a molecular weight <500. The target fractions will be purified by HPLC, and the pure product structures will be elucidated using the AI-based tools, Small Molecule Accurate Recognition Technology (SMART) and DeepSat. The collaborative effort involving the Almaliti laboratory in Jordan and the Gerwick laboratory in La Jolla offers a remarkable chance to bolster the University of Jordan's staff capabilities and elevate their expertise in discovering natural products in a region renowned for its historical use of plants as traditional remedies. These training initiatives in both La Jolla and Jordan will be further enriched by hosting a natural products symposium in Jordan during the project's second year. Future collaborations will be established to obtain additional funding and expand this work to other projects in Jordan and the US.

NIH Research Projects · FY 2025 · 2024-09

PROJECT SUMMARY Early word learning is a major developmental achievement that rests on a foundation of visual category learning: to learn that the word “dog” refers to a category dog that includes chihuahuas and excludes wolves, children must make an impressive visual generalization. However, deep neural networks—our best models of category learning—are unable to learn from the same visual diet as children, limiting our ability to construct mechanistic accounts of early category and word learning. While infants learn the categories that words refer to while experiencing a few categories (e.g., spoons, cups) dramatically more often than others (and while experiencing certain categories as drawings or illustrations), current models learn from uniform distributions of categories where exemplars are photos taken from the adult perspective. The proposed work will overcome these limitations and use deep neural networks to understand how children’s everyday visual experiences interact with statistical learning mechanisms to yield the category representations that support early word learning. In Aim 1 (K99 phase), I will determine how variability in children’s visual experiences relates to early word learning outcomes. To do so, I will collect a representative dataset of the categories in the infant view using a parent-report measure and photographs taken from the infant perspective, and determine whether variance in visual experience with different categories predicts which words are learned earlier in development. In Aim 2 (K99/R00 phase) I will evaluate how well current models and infants learn from diverse sets of realistic visual inputs using looking-time experiments and model simulations, evaluating whether networks with more neurally plausible architectures are better predictors of infant learning. In Aim 3 (R00 phase), I will adapt an existing deep neural network for infant categorization. To do so, I will build output layers on top of a state-of-the-art unsupervised model of object segmentation to identify the categories in the infant view and to make principled generalizations from frequently experienced to infrequently experienced but similar categories—much like young children in early development. The empirical findings and resulting computational model will provide insight into the relevant visual experiences for learning the categories that words refer to. This understanding of how typically-developing children learn rapidly and efficiently in everyday environments is essential to improve interventions for children struggling to learn the categories that words refer to, including late talkers, children with ASD, and children recovering from blindness (e.g., after cataract surgery). This award will build upon my strong background in visual category recognition and provide me with relevant training in both early language acquisition and deep neural networks via interdisciplinary workshops, coursework, and the scientific expertise of a team of mentors and consultants. This award will thus facilitate my transition to become an independent investigator at the forefront of cognitive development, vision science, and machine learning.

NIH Research Projects · FY 2025 · 2024-09

PROJECT SUMMARY A central problem in neuroscience is to understand how the brain controls innate behaviors. While reductionist experiments have been invaluable in isolating specific neural functions and their links to behaviors, they may not capture the full complexity of the brain performing ecologically relevant tasks; natural signals and natural behaviors are inherently complex, context-dependent, and continuous. Like other complex behaviors, vocal communication is facilitated by the coordination of networks of neurons that integrate auditory perception and motor planning for goal-directed decision-making. Linking neural signaling to the production of flexible vocal communication behaviors therefore requires characterization of the properties of network level neural interactions across multiple contexts. This proposal meets this challenge by leveraging a well-developed model for vocal communication, songbirds, a species that produces and relies on complex acoustic signals. The overarching goal of this proposal is to investigate how context in the form of acoustic cue, internal states, and behavioral motivations affect neural population dynamics during vocal communication behaviors. The central hypothesis of this proposal is that context-dependent interactions shift neural population dynamics to allow auditory and motor regions to affect different perceptual experiences or behavioral goals. This hypothesis will be tested through the following two phases: With my dissertation, I will determine how neural population dynamics in an auditory region are differentially structured and coordinated across internal and acoustic contexts during auditory perception. Preliminary data demonstrate significant alteration in temporal processing of auditory information as a function of context during perceptual categorization. In the F99 phase, I leverage innovative latent space models and state-of-the-art dynamical systems theory to asses network-level interactions across predictive cue conditions in addition to active and passive auditory perception. Primary results will enable novel insight into the mechanisms that allow populations of neurons to create different perceptual experiences across acoustic and internal contexts. In the K00 phase, I utilize advanced electrophysiological methods to assess neural population dynamics, recording activity from large populations of single neurons within a pre-motor area during vocal production (singing) in various behavioral contexts. I will employ the same analytical framework to measure neural dynamics across behaviors in order to characterize the links between neural dynamics and context. These findings will provide a mechanism for how neural interactions across the network coordinate to produce vocal gestures across behavioral contexts. The carefully designed training plan integrates scientific and professional development activities to support my goal of becoming an independent neuroscience researcher leading an academic laboratory. I will work with my sponsors to continue acquiring the proposed skills and to enable me to find the right postdoctoral training environment that aligns with my long-term research and career goals.

NIH Research Projects · FY 2025 · 2024-09

PROJECT SUMMARY The onset of a first episode of psychosis (FEP) in late adolescence or early adulthood often leads to lifelong disability. Timing and precision of treatment are of the essence during this critical developmental period. Unfortunately, FEP patients who do not respond to a conventional first-line antipsychotic (FL-AP) are often delayed in transitioning to clozapine (CLZ) - or never switch at all - despite the clear superiority of CLZ to FL- APs in treatment resistant individuals. However, CLZ treatment involves risks of severe side effects, including agranulocytosis and weight gain. Currently, clinicians and patients currently have no objective, clinically validated tools to guide this complex decision making in FEP. Our collaborative group has recently published work showing that a functional brain scan can help predict which FEP patients might not respond to FL-APs, such as aripiprazole and risperidone. Further, we have shown that a simple genetics test can help predict who is less likely to gain significant weight, and, similarly, who is less likely to develop agranulocytosis. We propose to conduct a multi-center, harmonized, randomized clinical trial with the goal of testing whether the use of biomarkers can lead to better outcomes for FEP patients. The goal of the proposed study is to develop a clozapine decision support tool based on these biomarkers. First, we will characterize 410 people with an FEP using three specific biomarkers: a resting state fMRI scan from which we will derive the striatial connectivity index (SCI) and two genetics tests (one for weight gain and the other for agranulocytosis). Those patients who are predicted to not respond to FL-APs, and who also have low risk of weight gain and agranulocytosis (approximate n=180), will be randomized in a triple-blind controlled study to either clozapine or an FL-AP (either aripiprazole or risperidone) for 12 weeks of treatment. Our main outcomes relate to clinical response, including positive symptoms, suicidal thinking, and days of hospitalization. We will also perform an MRI at study end to determine whether functional patterns in the brain distinguish CLZ responders from non-responders (target engagement). Critically, we are partnering with people with lived experience of psychosis and family members to help guide us during this trial, and to inform the study design and outcomes; information and choice are amongst the strongest elements of a successful therapeutic relationship. Overall, our study will evaluate the efficacy of whether using three biomarkers at the beginning of a first psychotic episode can lead to better patient outcomes for patients at risk for poor response, by rapidly introducing CLZ rather than waiting for multiple failures of FL-APs. Our key deliverable would be a clozapine decision support tool, consisting of the three biomarkers combined with our CLZ dosing strategy for FEP. Such a tool would be a necessary step in the development of precision psychiatry; if this efficacy trial is successful, a future study would then utilize implementation science to optimize strategies for dissemination of the decision support tool.

NIH Research Projects · FY 2025 · 2024-09

Project Summary / Abstract Degeneration of dopamine neurons in the substantia nigra pars compacta (SNc) and resulting pathophysiology in basal ganglia circuits are central to the core motor impairments in Parkinson's Disease (PD). A variety of non-motor symptoms also are highly prevalent in PD, including motivation-related deficits manifesting as apathy, fatigue, and depression, which have significant negative impacts on quality of life for patients and caregivers. However, we still have limited understanding of how nigrostriatal dopamine contributes to specific aspects of motivated behavior spanning action selection and invigoration, particularly in the context of cost-benefit decisions entailing effortful reward seeking. Recent work has increasingly highlighted a remarkable diversity of midbrain dopamine neurons, and indeed some subpopulations of SNc dopamine neurons are preferentially vulnerable in PD. Defining the circuits regulating distinct nigrostriatal dopamine projections and determining their subtype-specific roles in motivated behavior will address critical knowledge gaps and represents important first steps toward developing more effective and specific treatments for disorders such as PD. Our preliminary data suggest that manipulating afferent inputs can drive highly divergent responses in different nigrostriatal dopamine projections. In particular, stimulating subthalamic nucleus glutamatergic neurons drives diametrically opposed responses in nigrostriatal dopamine projections to distinct striatal subregions. Additionally, stimulating different populations of descending striatonigral projections evokes opposing patterns of dopamine release within the same region of the striatum. However, the circuit interactions underlying these divergent effects remain unknown. Beyond its recognized role as a major basal ganglia output nucleus, the substantia nigra pars reticulata (SNr) provides critical inhibitory regulation of SNc dopamine neurons, and we propose that this may differ between dopamine neuron subtypes and mediate their divergent responses to other basal ganglia afferent inputs. Given the anatomically segregated projections of SNc dopamine neuron subtypes to different striatal subregions, we will test the hypothesis that these dopamine subpopulations differentially contribute to dissociable aspects of effortful reward-seeking behavior. The major goals of this proposal are therefore 1) to characterize how SNr GABA neurons regulate divergent nigrostriatal dopamine pathways and potentially mediate pathway-specific responses to distinct afferent inputs, and 2) to determine the roles of these SNc dopamine neuron subpopulations in effort-based decisions and instrumental action invigoration. Collectively this research program will yield important advances in understanding basal ganglia circuit regulation of diverse dopamine neuron subtypes and their contributions to motivated behaviors often impacted in PD.

NIH Research Projects · FY 2025 · 2024-09

Summary/Abstract Genome-wide association studies (GWAS) have associated hundreds of thousands of genetic variants with human disease and complex traits. 90% of associated variants reside in noncoding sequences that can enhance or suppress gene expression levels. While GWAS does not reveal the target genes of associated variants, extraordinary effort has been dedicated to mapping target genes that carry out the functional effects of noncoding genetic variation. While knowing which genetic variants cause disease is not often sufficient for clinical intervention, identifying disease genes can efficiently accelerate the development of therapeutics. Correlations between genotype and gene expression, known as expression quantitative trait loci (eQTL) studies, can provide valuable insight into the mechanism of disease-associated variants. For example, a previous study found MAPK3 to be associated with schizophrenia and neurodevelopmental phenotypes via a key role in neuronal proliferation. Thousands of genetic associations are still uncharacterized in terms of their target genes and cell types of action. This proposal will develop new algorithms to robustly map disease- associated variants to disease-critical genes and infer their cell-type-specific regulatory behavior across three aims. First, we hypothesize that new disease-critical genes will be discovered if variants are accurately mapped to target genes in non-Europeans, where cohorts are small and variant-to-gene mapping is imprecise. To this end, we will develop a novel gene-disease mapping technique for understudied populations. Second, we hypothesize that linking distal regulatory variants to target genes should provide mechanistic explanations for many uncharacterized GWAS variants. To this end, we will develop a high-dimensional feature selection technique to detect distal effects on gene expression. Third, we hypothesize that novel variant-to-gene links can be identified by analyzing rare cell types from single cell RNA-sequencing. To this end, we will link variants to genes in cell-type-specific contexts using mixed models for heritability estimation. Overall, while gene expression prediction models are a powerful tool to link genes to disease, they have been applied to only limited study designs: single ancestry gene expression cohorts (which are not powerful in non-European populations with limited sample sizes), predictor variants in the cis regulatory window, and bulk tissue or cell type gene expression data. There are many open questions due to these limitations that our proposal aims to address including the degree to which genetic variation regulates gene expression in population-specific manners, via long-range mechanisms, in cell-type-specific or cell-state-specific manners, and in ways that are relevant to complex traits and diseases. Our contribution is expected to be significant because still 30% of disease-associated variants have no known target gene and because this work will diversify genetic discovery to populations who are most at risk.

NIH Research Projects · FY 2025 · 2024-09

SUMMARY Obesity-Induced Inflammatory Mediators Predict Lack of Response in Patients with Rheumatoid Arthritis Starting Biological Therapies There is an unmet need to identify predictive biomarkers in rheumatoid arthritis (RA) with respect to outcome and response to therapy. Numerous efforts to identify patients who will respond well to specific biologic agents have begun to yield profiles that might allow more personalized use of these agents, but much more work needs to be done. Given the complexity and heterogeneity of RA, it seems doubtful that a single cytokine or biomarker will be sufficient to inform the optimal choice of therapy. Instead, the inclusion of multiple biomarkers into ‘biomarker signatures’ may represent a more fruitful approach for the future of personalized therapeutic approaches. While clinical factors predicting disease outcomes are few, prior studies have highlighted strong associations between body weight and RA outcomes, although the mechanisms behind these associations are not defined. Obesity-induced inflammatory mediators include both proteins (such as adipokines) and lipids (such as fatty acid–derived bioactive lipids). Both types of obesity-induced mediators have been hypothesized to predict clinical responses in patients with RA, either by directly contributing to lack of response by promoting subclinical inflammation and disease relapse, or by describing metabolic phenotypes that may have prognostic value. Prior studies from our and other groups have described bioactive lipids disturbances in early stages of RA that are linked to therapeutic response. Additional preliminary results on samples from Comparative Effectiveness Registry to Study Therapies for Arthritis and Inflammatory (CERTAIN) cohort, revealed that distinct bioactive lipid profile (including those in the prostaglandin, leukotriene, resolvin, and eicosatrienoate pathways) was associated with response to different biologic therapies (categorized by minimal clinically important difference (MCID) in Clinical Disease Activity Index (CDAI) at 6 months after treatment initiation). Of interest, one of them, the 15-oxoEDE, which derives from eicosadienoic acid, a n-6 polyunsaturated fatty acid (PUFA) that has been associated with obesity and diabetes, was associated with both lack of response to anti-TNF therapy and obesity in the CERTAIN cohort. Taken together, our work suggests that obesity-induced inflammatory mediators profiling has the potential to identify metabolic phenotypes and effectively predict patient response to therapy prior to administration, and has also the potential to identify metabolic pathways that relate to response to biological therapies with distinct mechanisms of action.

NIH Research Projects · FY 2026 · 2024-09

Project Summary (Overall) The goal of this P30 application is to support the community of scientists who use outbred heterogeneous stock (HS) rats to understand the genetic basis of individual differences in vulnerability to substance use disorders (SUDs). Although this is a new grant, one of its main goals is to provide core services that have been offered for the past 10 years by our NIDA P50 grant. When that grant was originally funded, mice were the mainstay of mammalian quantitative genetics. A major study using HS rats had recently been completed in Europe, and Dr. Leah Solberg Woods (PI of Core B) was maintaining the only US-based colony of HS rats, which was supported by an R01 from NIDDK. A central theme of our initial P50 was that establishing the HS rat as a platform for quantitative genetic studies would allow us to examine complex behavioral traits that were difficult or impossible to study in mice. Ten years later, we have established a vibrant community of investigators who use HS rats not only for genome wide association studies (GWAS) but also to study the genetic basis of individual differences in vulnerability to SUD-like behaviors. We have also accumulated a database of more than 15,000 deeply phenotyped and genotyped rats. This community depends on several critical core services that will be provided by this P30. First, and foremost, Core B, the Breeding Core, will maintain two HS rat breeding colonies, located at Wake Forest University and the University of California San Diego. An innovative new component of Core B is our introduction of RATTACA, which uses data collected over the last decade to predict phenotypes of newborn HS rats based on their genotype. As we describe, RATTACA allows us to provide groups of rats with high and low phenotypes, allowing non-geneticists to study individual differences using statistically valid methodology. Core C, the Genotyping, Analysis and eQTL Core, provides services including genotyping of HS rats, GWAS, mapping of expression quantitative trait loci (eQTLs), and transcriptome wide association studies (TWAS). In addition, the Administrative Core (Core A), will maintain and distribute data from more than 15,000 HS rats that have been accumulated over the last decade, as well as newly collected data, following FAIR (Findable, Accessible, Interoperable, and Reusable) practices as described in our Data Management and Sharing Plan. The Administrative Core will also provide oversight, coordination, education for high school and undergraduate students and will implement several aspects of our Plan for Enhancing Diverse Perspectives (PEDP). Finally, Core D, the Pilot Project Core, will provide grants and free services from Cores A, B and C in an effort to support early-stage investigators, broaden the impact of our center, and execute our PEDP. These cores will provide both stability and innovation that will promote the use of HS rats to study the genetic basis of individual differences.

NIH Research Projects · FY 2025 · 2024-09

Project Summary/Abstract Optic neuropathies and retinal diseases are leading causes of irreversible blindness worldwide. Currently, there are no therapies to restore vision loss. Whole eye transplants could restore vision if the neural circuits between the eye and the brain could be restored. The long-term goal of this proposal is to develop therapies that regenerate lost retinofugal pathways and enable whole eye transplants. In experimental spinal cord injury models, neural stem cells (NSCs) have been used to form neuronal relays that restore injured connections and function. Similarly, NSCs have demonstrated the capacity to form neuronal relays in the optic nerve and integrate into the injured visual system. The overall objectives in this application are to (i) determine the degree of visual function recovery from long-term NSC-derived neuronal relays in the injured optic nerve and (ii) develop methods to guide neuronal relay axons through the optic chiasm and to appropriate synaptic targets. The central hypothesis is that stem cell-derived neurons transplanted into the optic nerve form neuronal relays that can be guided to appropriate targets to restore vision-related function. This proposal will test this hypothesis by pursuing the following specific aims: 1) measure the functional recovery from long-term optic nerve grafted NSCs in the injured visual system, 2) investigate the role of canonical chiasmal guidance cues on neuronal relay axon guidance, and 3) target neuronal relay axons to host vision-associated nuclei. In the first aim, rodent optic nerve transection models will be treated with NSCs to restore retinofugal connections with neuronal relays. Long-term integration and function of NSC-derived neuronal relays in restoring vision will be evaluated with visual function testing and histological assessments for the structural indicators necessary for effective neuronal relay conduction. For the second aim, NSCs with genetic modifications of canonical optic chiasm guidance pathways that are important in development will be transplanted into a rodent optic nerve transection model. These modified NSCs will be used to assess the effect of developmental guidance cues that persist in the adult optic chiasm on the decussation of growing axons in the injured visual system and the manipulability of those pathways. In the final aim, transduction of vision-associated nuclei to express neurotrophins using an adeno-associated virus will be used to guide NSC-derived optic nerve neuronal relay axons to innervate specific targets and facilitate recovery of visual function. The research proposed is innovative because it overcomes current limitations in optic nerve regeneration by leveraging stem cells and enables research on important downstream considerations necessary for successful optic nerve regeneration. The proposed studies are significant because they develop a novel use of stem cells to form neuronal relays to regenerate the optic nerve and advance axon guidance and targeting strategies in optic nerve regenerative research. The positive translational impact is the potential development of therapeutic strategies that restore vision, including whole-eye transplants.

NSF Awards · FY 2024 · 2024-09

This award concerns Number theory, the analysis of equations involving integers and their solutions, which is one of the oldest branches of mathematics. As such, it has a long history of being driven by empirical observations; such important results as the law of quadratic reciprocity and the prime number theorem originated from numerical experiments. With an eye on the ongoing revolution in artificial intelligence, the PI will combine the latest theoretical developments in number theory with a big data approach to uncover hidden structures in the theory of L-functions. The PI will also promulgate this work through mentoring of PhD students, dissemination of advanced course materials, organization of workshops, and nonprofit governance, all with a view towards broadening participation. The PI will study Hasse-Weil L-functions associated to algebraic varieties over number fields through a mix of theoretical and computational techniques. On the theoretical side, the PI is investigating recent evidence pointing towards a global cohomological interpretation of these L-functions, using as a test case the families of motives parametrized by hypergeometric differential equations. On the computational side, the PI is developing streamlined algorithms to compute hypergeometric L-functions, partially informed by q-de Rham cohomology; this yields a rich data set for investigating Frobenius distributions, special values, murmurations, and other phenomena. 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 2024 · 2024-09

We are requesting funds for a ZetaView® x30 QUATT Multi-Fluorescence Nanoparticle Tracking Analyzer with colocalization of four lasers. This instrument is essential to biomedical research involving extracellular vesicles and other bio-nanoparticles. It enables high-throughput measurements of the size, concentration, zeta potential, and fluorescence of nanoparticles with the unique feature to assess colocalization of fluorescence signals on the particles. This allows molecular characterization and phenotyping of various subpopulations of extracellular vesicles, which is critical for the precision and accuracy of research. Currently, there is no similar instrument that can perform the colocalization analysis at the UC San Diego and the surrounding areas. Providing local researchers with access to this instrument will expand state-of-the-art technologies, enable new methodologies, and facilitate synergistic discoveries in multiple fields. The ZetaView® x30 QUATT will be placed in the Pathology Department Diagnostic Discovery Laboratory (PDDDL) centrally located on the UC San Diego main campus, maximally facilitating access by users from the School of Medicine, Skaggs School of Pharmacy and Pharmaceutical Sciences, Moores Cancer Center, and other Schools and Departments at the UC San Diego and the surrounding areas. The web-based Facility Online Manager (FOM) will be used for maintaining the services and resources offered, managing requests and reservations, completing billing events, running reports and managing settings as needed. The Department of Pathology will provide full administrative support. The institution will guarantee any shortfall for the service contract for at least five years. An advisory committee has been formed to oversee the usage and management of the instrument. Current Major Users are from several departments at the UC San Diego Health Sciences and nearby research institutions, and represent a diversity of research fields including cancer, metabolic diseases (diabetes and obesity), cardiac homeostasis, prenatal conditions and embryonic development, circulating RNA markers, therapeutic development, and neuroscience. The 10 NIH-funded Major Users will have protected use of ~80% of the instrument time whereas Minor Users and new users will be able to use the remaining instrument time. This instrument will be a worthwhile and timely investment to improve the research environment overall and enhance the quality of science performed at the UC San Diego. It will result in clear benefits for the research community of extracellular vesicles and other bio-nanoparticles at the UC San Diego and surrounding research institutions. This cutting-edge technology will not only directly benefit the faculty on campus but will also help trainees and junior PIs to launch a successful career in related research areas.

NIH Research Projects · FY 2025 · 2024-09

PROJECT SUMMARY/ABSTRACT Adolescence is when many individuals begin to seek increased levels of autonomy from their families and experience pubertal-related brain changes, often leading to increased reward seeking and subsequent risk- taking behaviors. Risky behaviors can lead to injuries, such as traumatic brain injuries (TBIs), which in adolescents and young adults account for a large portion of emergency room visits. TBIs can impact normative brain development and put adolescents at elevated risk for increased mental health symptoms, such as anxiety, depression, and addiction. In fact, peak substance use often occurs during the adolescent period of development, (i.e., alcohol, nicotine, and cannabis) and TBIs may further increase this risk for substance misuse through damage to impulse control regions of the brain, such as the frontal lobe. Personality factors such as impulsivity may also predispose some adolescents to engage in more behaviors that culminate in TBIs and increase risk for poorer health outcomes. However, little is known about the prospective relationships between TBI history, mental health functioning, and substance misuse among individuals as young as 9-14 years of age. Therefore, this project will use data from the Adolescent Brain Cognitive Development (ABCD) Study cohort to examine how mental health symptoms might mediate the association between TBI and substance misuse behaviors and how trait impulsivity might moderate this association. These associations will be examined longitudinally where TBI, mental health symptoms, and substance misuse will be examined at baseline (ages 9-10), year 2 (ages 11-12), and year 4 (ages 13-14) using a cross-lagged panel mediation model with baseline impulsivity as a moderator. The results from this project will inform behavioral challenges, prevention strategies, and functional targets for intervention development for adolescents with history TBI.

NIH Research Projects · FY 2025 · 2024-09

Project Summary/Abstract: This proposal details a 5-year plan to provide the candidate, Dr. Taha Gholipour, with the knowledge and expertise to become an independent investigator. He is a board-certified neurologist and epileptologist with research training in neuroimaging. The candidate's training will be guided by established mentors with expertise in the field of epilepsy research, functional imaging, advanced statistics and machine learning, and an advisory committee of scientists with collective expertise in clinical neuroscience and image analysis across prominent institutions. Uncontrolled seizures from epilepsy are associated with high morbidity, mortality, and cost. Current clinical and imaging predictors of response to surgery are inadequate, and surgical treatment outcomes are mixed. Predicting treatment outcome is critical for clinical decision making. Functional MRI (fMRI) offers noninvasive and accessible means for assessment of brain networks and may complement current methods of surgical planning to guide treatment. Statistical constraints from abundance of variables and data heterogeneity in fMRI analysis can be addressed by application of novel statistical and machine learning methods. The candidate will conduct a study with retrospective analysis of large multicenter datasets of resting state fMRI studies from adult and pediatric focal epilepsy patients, and a prospective arm to identify preliminary predictors of treatment response to guide future multi-site studies. The candidate will use functional anomaly mapping method to identify associations of this method with commonly used functional connectivity analysis and treatment outcomes 12 months after surgery. Post-surgical resection masks, clinical outcomes of seizure control and cognitive decline from surgery are collected in prospective arm. The goal is to identify common features in patients who become seizure-free following surgery. This study will use innovative methods to improve non-invasive evaluation of patients with refractory epilepsy, which can expand surgical candidacy for patients with or without apparent lesions on MRI. This project aims to help overcome current barriers to personalized care for people with epilepsy. The innovative use of advances statistics for solving clinical challenges in epilepsy imaging will have a fundamental impact on designing future investigations focused on developing biomarkers, predicting response to treatment, and understanding the disease mechanisms in epilepsy, as advocated by the 2021 AES/NINDS Epilepsy Research Benchmarks.

NIH Research Projects · FY 2025 · 2024-09

PROJECT SUMMARY Cardiovascular disease affects nearly half of all American adults. Achieving cardiovascular health is associated with lower mortality and morbidity, but modifying and adhering to health behaviors such as diet and other healthy lifestyle factors remain challenges to achieving it. Additionally, there are historically marginalized communities of individuals who suffer the greatest burdens of cardiovascular disease and are in urgent need of effective, pragmatic, and culturally appropriate interventions. To address these issues, we must train the next generation of patient-oriented investigators who are rigorously mentored in cardiovascular disease epidemiology, health equity, health disparities, and translational research methods; and who are committed to doing the work with cultural humility and a global perspective. This proposal focuses on necessary steps for developing a novel comprehensive and structured mentorship and research program that will support mentees. This K24 award will provide protected time for Dr. Cheryl Anderson, a mid-career clinical investigator who has her own independent peer- reviewed research support to recruit and mentor a diverse group of trainees in clinical cardiovascular epidemiology and health equity. Dr. Anderson proposes to facilitate a training environment that is rigorous, supportive, creative, and collaborative where mentees develop their research in a manner that capitalizes on her expertise and preserves their independent lines of research. The research program she proposes will build on her current grants and support her ability to pursue developing new skills in health equity and global policy and strategy. More specifically, the award will support the building of two new areas of research: 1) integration of the science of global policy and strategy into multilevel interventions to improve cardiovascular health, and 2) development of skills to train others to be effective change agents to disrupt health inequities via the creation of an “Advocacy Laboratory.” The environment for this K24 is the University of California San Diego, a world-class institution with extensive resources to support research that is patient-oriented and integrated with research in health equity and global policy and strategy.

NIH Research Projects · FY 2026 · 2024-09

OVERALL – PROJECT SUMMARY This is a resubmission application for a new U2C/TL1, requesting support to promote high quality, collaborative training in kidney, urology, and hematology research in the San Diego area. The application represents a collaborative submission from the 3 major academic research institutions in the region inducing UC San Diego (UCSD), The Scripps Research Foundation (TSRI), and San Diego State University. This U2C/TL1 is designed to address the KUH mission areas, foster collaboration, and comprehensively address training and mentoring across the continuum of career stages. The San Diego U2C/TL1 builds upon the outstanding local resources and prior experience in pre- and post- doctoral research training. It builds upon recent successes fostering nephrology training through a T32 (2016- 2021), and recent post-doc successes at TSRI and SDSU. TSRI in an outstanding research institute, with 2 of the last 5 years’ Nobel Prizes in Chemistry, and is ranked in the top 10 for graduate training in biology and chemistry and has an outstanding track record for recruiting and training both pre- and post-doctoral scholars. SDSU offers a pool of over 30,000 undergraduate 3000 graduate students annually, with nearly 30% from under-represented minority (URM) backgrounds, and is a federally designated Hispanic serving institutions. It already has multiple joint programs with UCSD and is heavily invested in expanding pre- and post-doctoral training. UCSD is also a top 10 graduate program, offers over 6000 graduate students annually, and the only academic medical school in the region, providing a link to outstanding Departments and Divisions of Nephrology, Urology, Hematology, and other affiliated programs. With only 5 years of support, UCSD Nephrology’s T32 graduated 66% of its post-doc scholars with K-series or VA Career Development Awards (CDAs) – all of these individuals also secured faculty positions at research intensive institutions. Similar parallel successes occurred at TSRI and SDSU. These scholars came from a wide variety of disciplines but all focused on KUH research careers, demonstrating our abilities to guide young scientists to KUH research pathways. The grant is structured around 5 core pillars learned and carried forward as best practices from our recent training experiences, as we now expand our focus to hematology and urology, and across the career continuum. With highly successful and engaged TL1 faculty, pilot grants to foster collaboration across KUH disciplines, and to drive young scientists into KUH research careers, a vibrant network, substantial and well developed programs for professional development, and robust infrastructure and administrative support, this U2C/TL1 is uniquely positioned to train outstanding scientists in KUH research topics, and supply the workforce with innovative scientists making groundbreaking discoveries in KUH throughout their careers.