University Of California Los Angeles

NIH Research Projects · FY 2026 · 2026-05

Chronic Inflammatory Demyelinating Polyneuropathy (CIDP) is the most common acquired chronic autoimmune neuropathy and occurs more frequently in the aged, with a peak incidence in those 70-79 years of age. How aging predisposes to peripheral nervous system (PNS) autoimmunity, however, is unclear. Early aging-associated changes include the acquisition of T cell immunosenescence, a dysfunctional, pro- inflammatory state that can lead to the spread of senescence to neighboring cell types. Our data demonstrate an increased burden of senescent T cells in patients and mice with CIDP, compared to age-matched controls. Moreover, our data suggest that peripheral nerve-infiltrating CD4+ T cells actively signal to adjacent PNS cell types, including Schwann cells, in a mouse model of CIDP. Thus, in this R21 proposal, we will test the hypothesis that senescence-associated CD4+ T cells predispose to PNS autoimmunity by inducing neighboring Schwann cells to acquire a senescent, dysfunctional state. In Aim 1, we will test how adoptive transfer of senescent T cells into an immunodeficient mouse recipients alters Schwann cell phenotype in the peripheral nerves of recipients. We will also assess whether conditioned media from senescent T cells of CIDP patients will induce senescence in a human Schwann cell line. In Aim 2, we will examine how disease protection is conferred by a senomorphic agent, ruxolitinib, in mice with CIDP and through the use of CIDP patient samples. Completion of these Aims are important steps toward a more comprehensive understanding of autoimmune mechanisms in CIDP and may point to the use of senomorphic therapies for the benefit of CIDP patients.

NIH Research Projects · FY 2026 · 2026-05

PROJECT SUMMARY Radioembolization (RE) with yttrium-90 (90Y) microspheres is a promising treatment for primary and secondary liver cancer, but the success of the treatment is user-dependent and relies on the optimal distribution of 90Y particles within the tumor. The current method for determining how 90Y microspheres are dispersed in a tumor requires the tracking of Tc-99m-labeled macro-aggregated albumin (MAA) distribution after the mapping procedure. This methodology is labor-intensive and cumbersome, and does not account for flow dynamics within the tumor. Variations in peri-tumoral and intra-tumoral blood flow can significantly impact final 90Y microsphere distribution, leading to undertreated cold spots or overtreated embolic regions that cause beads to reflux backwards. There is thus an unmet need for an advanced tool to predict 90Y distribution accurately based on tumor flow characteristics. This project aims to overcome this current barrier by developing an in vivo imaging biomarker of 90Y microsphere distribution that leverages AI-optimized perfusion analyses and a biological model of liver flow dynamics. The project will be conducted via two aims: 1) Development of an AI-optimized liver perfusion analysis tool using routine clinical MRI scans. Quantitative dynamic contrast-enhanced (DCE) MRI will be used to obtain insights into tumor blood flow and vascularity. With standardized data collection and curation, we will develop advanced deep learning-enabled perfusion analysis to analyze liver perfusion characteristics in routine clinical DCE-MRI. A physical model of particle flow will be integrated with perfusion MRI for accurate prediction of RE microsphere distribution, and preclinical evaluation will be conducted with patient- derived liver tumor phantoms, allowing for precision measurements of the MRI-based perfusion protocol. 2) In vivo validation of AI-optimized perfusion protocol for accurate prediction of 90Y particle densities. We will test intra-subject and inter-subject variability of the perfusion MRI protocol by repeating DCE-MRI scans at multiple time points with concomitant repositioning. Once intra-subject and inter-subject reproducibility are validated, the AI-optimized perfusion MRI will be leveraged to quantify perfusion parameters in an in vivo porcine liver cancer model intra-arterially infused with 90Y microspheres. Histopathological and imaging analyses of 90Y microsphere distribution will then be correlated with the MRI perfusion markers against those from the standard Tc-99m MAA administration. The results of this project will have significant implications for the treatment of liver tumors by providing a foundation for more effective and precise 90Y-based therapies. By optimizing 90Y particle density with tumor perfusion characteristics, we can improve the outcomes and safety of RE, ultimately transforming it into a more effective and precise therapeutic approach for liver cancer patients.

NIH Research Projects · FY 2026 · 2026-05

PROJECT SUMMARY This proposal outlines a five-year research and career development plan that will prepare Dr. Annette Dekker to become an independent physician-scientist. Dr. Dekker is an emergency physician and health services researcher committed to studying policy interventions that reduce opioid use disorder-related morbidity and mortality. The proposed study focuses on evaluating the role of health policy and the emergency department (ED) in initiating treatment of opioid use disorder, a critical intervention point for individuals at high risk of mortality. The project introduces the concept of the ED-Bup cascade—a continuum of prescriptions from ED-initiated buprenorphine to linkage to care to continuous treatment. Guided by the Donabedian framework, the study will assess how California’s CA Bridge initiative (structure) impacts the ED-Bup cascade (process) and subsequent mortality (outcome). Aim 1 will use a staggered difference-in-difference analysis to estimate the effect of CA Bridge implementation on the ED-Bup cascade for individuals who present to the ED with an opioid use disorder- related concern. Aim 2 will use a retrospective cohort study to evaluate how the ED-Bup cascade impacts mortality. Aim 3 will examine whether these patient outcomes vary by urbanicity. Analyses will use linked state- level claims, prescription drug monitoring program, and mortality data. The findings will inform state and national policies to address opioid use disorder morbidity and mortality. In this proposal, Dr. Dekker builds upon her prior experience in descriptive and mixed-methodological health services research to perform causal inference analyses of administrative data to understand the impact of California policy initiatives to increase low-barrier buprenorphine treatment from the ED. Her training plan includes developing advanced skills in 1) addiction health services research, 2) quasi-experimental and causal inference methods, and 3) health policy analysis through coursework and mentorship. She will be supported by her primary mentor, Dr. Elizabeth Samuels, who is a leader in ED-based addiction medicine, as well as a multidisciplinary team of co-mentors and advisors. Through UCLA’s Clinical and Translational Science Institute CTSI, Dr. Dekker will have access to numerous career development seminars that address such topics as grant writing, manuscript preparation, and ethical research. Throughout the proposed project, Dr. Dekker will have strong institutional support and access to UCLA’s renowned research infrastructure.

NIH Research Projects · FY 2026 · 2026-05

Project Summary Targeting structured RNAs with small molecules dramatically increases the number of potentially “druggable” therapeutic targets, representing a major opportunity for anti-cancer drug discovery. The precursors (pre- miRNAs) of oncogenic microRNAs (oncomiRs) fold into hairpin structures that are recognized and cleaved by microRNA (miRNA) processing enzymes. Thus, the pre-miRNA structures provide binding sites for small molecules that can inhibit the production of specific oncomiRs. Using this strategy, eleven previous studies have identified eighteen diverse small molecules that bind to prominent oncomiR precursors, pre-miR-21 and pre- miR155. However, most of these compounds lack drug-like properties and further improvement has been hampered by lack of underlying structural details. We propose to perform fragment-based drug discovery (FBDD) via high-throughput crystallographic screening, enabled by a newly established facility at the National Synchrotron Light Source II. FBDD focuses the initial screening on compounds with molecular masses less than 300 Da to reduce the size of the screens while sufficiently covering the chemical space. In Aim 1, we will execute fragment-based crystallographic screening campaigns against three prominent oncomiR precursors, pre-miR- 21, pre-miR-155, and pre-miR-10b. In preliminary studies, we have obtained diffraction-quality crystals of these pre-miRNAs and determined several structures of pre-miR-21, which revealed previously unknown rare structural features as potential drug-binding sites. Through a preliminary screen, we have identified fragment hits for a pre-miR-21 construct. Similar screens will be performed for other pre-miR-21 constructs, as well as pre-miR-155 and pre-miR-10b (Aim 1a). Since the fragment libraries currently used were tailored for targeting proteins, we will acquire and test an RNA-specific fragment library (Aim 1b) and make it available to the research community. We will also determine the structures of pre-miRNAs bound with previously reported ligands (Aim 1c), which will facilitate potential merging or linking of these ligands to fragment hits. In Aim 2, we will first confirm and optimize the fragment hits, then merge and link the fragment hits to drug-sized compounds that bind the pre-miRNAs tightly, and finally validate the drug-like hits using a comprehensive set of biochemical, structural, and cellular assays. The development of fragment hits into drug-like leads should be greatly facilitated by the structural information offered by our crystallographic approach. If successful, our study will identify novel small molecule inhibitors against oncomiRs that will be ready for lead optimization and pre-clinical studies. To our best knowledge, fragment-based crystallographic screening has not been performed for RNA-only targets. The proposed study will pave the way for similar studies in the future.

NIH Research Projects · FY 2026 · 2026-05

This K99/R00 award will position the candidate to become an independent clinical researcher with expertise in individualized novel phenotyping and prediction of risk and resilience to psychosis and bipolar spectrum disorders (PBSD). Background. PBSD are among the most disabling conditions worldwide, evidenced by poor quality of life and premature mortality. These disorders demonstrate pluripotentiality and heterotypic continuity across clinical, cognitive, and neural phenotypes. The ability to predict transdiagnostic functional outcomes is critical for implementing precision-based interventions. Despite advances in identifying shared risk factors and pathophysiological mechanisms, translating research findings into clinical practice remains a challenge. Specific Aims. This project synthesizes data from NIMH-sponsored clinical high-risk (CHR) cohort, the North American Prodrome Longitudinal Study 2 and 3 (NAPLS-2, NAPLS-3) and Accelerating Medical Partnerships – Schizophrenia (AMP-SCZ), and translates empirical findings to electronic health records (EHR). Aim 1.1 will leverage the NAPLS cohorts to identify novel combinations of demographic, social determinants of health (SDOH), clinical, cognitive, and biological factors associated with risk, remission, and resilience using machine learning. Aim 1.2 will externally validate these models in AMP-SCZ and investigate the predictive power of digital phenotyping measures. Aim 2.1 will apply temporal deep learning and explainable artificial intelligence (XAI) to test these predictive models and align CHR variables with unique XAI-derived common data elements in the demographically-diverse Epic EHR using a longitudinal retrospective design. Aim 2.2 will design a clinician-facing nomogram for future deployment as an automated real-time predictor of PBSD as preparation for an R01 application. Training. The candidate will achieve these goals through a resource-rich institutional environment and cohesive training plan in: (1) PBSD etiology and course, including SDOH and immunological biomarkers; (2) advanced statistical modeling and machine learning techniques; and (3) optimization of EHR tools and registries. This training will support the development of an independent research program integrating novel digital and EHR phenotyping with clinical practice. Mentorship. The candidate will be supported by an expert interdisciplinary team: Robert Bilder, Ph.D. (primary mentor), Carrie Bearden, Ph.D. (co-mentor), David Miklowitz, Ph.D. (co-mentor), Steven Cole, Ph.D. (consultant), and Douglas Bell, Ph.D. (consultant). Impact. This project directly aligns with the NIMH’s Strategic Goals related to the pressing need to improve assessment platforms within healthcare to screen, detect, and treat mental illnesses; optimizing real-world data collection systems with computation modeling; evaluating the role of social determinants of health in the onset and course of mental illness; and developing decision-support tools for interventions and stepped care. The research outcome will develop innovative methods to prospectively identify individuals likely to demonstrate risk, remission, or resilience, enabling real-time individual- and population-level detection and interventions.

NIH Research Projects · FY 2026 · 2026-05

Abstract The Department of Anesthesiology and Perioperative Medicine (DAPM) at UCLA has a long tradition of academic productivity and excellence as reflected by our consistent ranking among top 10 Anesthesiology departments in the country. The department has trained many leaders in the fields of Anesthesiology, Critical Care and Pain Medicine and has a long history of excellence in both basic and clinical research. The main goal of our T32 training program is to provide training and mentoring to anesthesiology residents/fellows/junior faculty early in their careers in basic, translational, and preclinical research in the department. Our T32 research training program has four main research themes: 1) Perioperative Organ Protection, 2) Cardiovascular, 3) Neurosciences and Brain Health, and 4) Biocomputing/Bioengineering and Health Informatics. The department has strong leaders in each of these fields. We have recruited 27 exceptional faculty mentors (13 PhD scientists and 14 physician-scientists) from the Department of Anesthesiology and other departments across UCLA, including the Departments of Medicine, Bioengineering, Physiology, Surgery, Pathology, Molecular, Cell, and Developmental Biology, Psychiatry and Biobehavioral Sciences, Computer Science, and Human Genetics. Our faculty have expertise in a wide range of research areas broadly related to the anesthesiology specialty. Eleven of these faculty are from the Department of Anesthesiology. We have also recruited eight junior anesthesiologist scientists from our department as “Up and Coming Faculty”. All of these junior faculty are on track to becoming independent physician-scientists and are dedicated to training the next generation anesthesiologist-scientists. We request two trainee slots for the first year and three slots thereafter. We will focus our recruitment efforts towards outstanding MD and MD/PhD candidates from the pool of our residents (mainly from Research Scholars Track, which is a five-year program that includes almost two years of protected research time junior faculty, or Research Pathway that includes up to 11 months of research during residency) as well as our fellows and junior faculty. We will require a minimum two-year commitment from our T32 trainees but will extend the training to three years if the additional year is beneficial to the individual upon approval from the T32 Executive Committee. Our T32 training program is specifically designed to train the next generation of academic anesthesiologists to become independent physician- scientists in the field of Anesthesiology and Perioperative Medicine.

NIH Research Projects · FY 2026 · 2026-05

The training and research plans described in this K23 Career Development Award will enable Dr. Kunmi Sobowale to achieve his long-term career goal of becoming an independently-funded investigator using mobile device technologies to facilitate screening, risk stratification, and personalized prevention and treatment for perinatal and infant mental health. To accomplish this goal, Dr. Sobowale aims to 1) Develop proficiency in the design of longitudinal studies and the statistical methods and skills to process and analyze intensive longitudinal data with a focus on mobile technologies; 2) Develop competence in signal processing and the methods of feature selection, and in particular the application of these methods to speech acoustic analysis; 3) Develop skills in research methods to assess the parent-child interaction and emotion regulation in early childhood. UCLA provides a rich environment for this training plan with a combination of didactic support and hands-on mentorship from leaders in depression neurobehavioral phenotyping, longitudinal study design and analysis, mobile health research, and child socioemotional development as well as the caregiver-child interaction in clinical and non-clinical populations. The training goals will be supported by and applied to the proposed research study. The objective of this longitudinal study of mother-infant dyads is to use mobile sensing devices (audio recorders and Bluetooth sensors) to enable daylong naturalistic assessment of the mother-child interaction. The focus will be mother-infant conversational turns, a key indicator of interaction quality, that are negatively affected by postpartum depression. The study will examine, in turn, how conversational turns affect child emotion regulation and, finally, will explore whether conversational turns are associated with mother-infant co-regulation and relationship quality. Aim 1 of this prospective longitudinal study investigates whether maternal postpartum depressive symptoms at 6 weeks are associated with conversational turn consistency at 3 and 6 months postpartum. Aim 2 examines whether conversational turn consistency at 3 and 6 months is associated with mother-reported child emotion regulation and whether it moderates the effectiveness of infant use of regulation strategies on distress (i.e., emotion regulation) during the still-face paradigm at 6 months postpartum. Aim 3 examines the association between conversational turn consistency at 3 and 6 months with observed mother-child co-regulation (mother-infant affect matches during the still-face paradigm) and mother-reported relationship quality at 6 months. This proposal is aligned with the National Institutes of Mental Health Strategic Objective to develop and assess novel mobile technology and digital health tools to enable objective measurement of behavior and intervention effects on symptom expression and functional outcomes in naturalistic environments. Ultimately, this sensor-based approach will facilitate large-scale assessment of the maternal-child interaction for screening and risk stratification and inform parent-child interventions for mother-infant dyads in the context of maternal postpartum depression.

NIH Research Projects · FY 2026 · 2026-05

Project Summary Corneal diseases pose a significant public health challenge in the United States, often leading to vision impairment and decreased quality of life. Mesenchymal stem cell (MSC) delivery to the cornea after a severe injury has shown promise by accelerating repair and significantly suppressing inflammation. However, a major bottleneck in developing MSC therapy for corneal repair is the lack of effective delivery methods. Moreover, optimizing the dosage and timing of MSC therapy is crucial for achieving therapeutic outcomes while minimizing side effects. MSCs must also survive and integrate into corneal tissue to exert their therapeutic effects. To date, MSCs have been delivered via surface injection, fibrin gel, or as a sheet on an amniotic membrane. However, these methods are limited by poor MSC survival and/or rapid matrix degradation. To address these issues, we propose the development of adhesive hydrogels that can effectively encapsulate and release MSCs in a sustained manner while having similar biomechanics as the corneal tissue. Our platform composed of a single hybrid polymeric structure with tunable variables to generate two distinct mechanical properties and degradation rates: 1) a soft/controlled degradable adhesive hydrogel to function as a bandage containing MSCs that release secreted factors for promoting corneal epithelial regeneration and 2) a strong/highly adhesive hydrogel that can adhere to corneal stromal defects and simultaneously serves as a stromal replacement while providing a platform for the delivery of MSCs to promote repair of stromal injuries/ulcerations. Our proposed biomaterial is a photocurable adhesive composite hydrogel based on chemically modified gelatin and hyaluronic acid (HA), encapsulated with MSCs. First, gelatin will be dual-functionalized with methacrylic anhydride (MA) and phenylboronic acid (PBA) to control mechanical properties and promote tissue adhesion. The incorporation of methacrylate HA derivatives in the hydrogel will also control the viscosity of the prepolymer and improve its mechanical properties. The physical properties of the resulting hydrogels, such as stiffness, swelling ratio, and degradation rate, which affect MSCs differentiation, will be tuned by varying polymer ratios, degree of polymer functionalization, final polymer concentration, and crosslinking time. We will first optimize the mechanical properties of the proposed hydrogels, and their degradation rates will be tuned to achieve a rate supporting MSCs growth and proliferation (Aim 1). We will then assess the in vitro epithelial proliferation and MSCs differentiation using in vitro models developed in our labs (Aim 2). Finally, we will test the in vivo efficacy of MSC-laden hydrogels using two animal models: a corneal epithelial wound healing model and a corneal stromal injury model (Aim 3). Based on our preliminary data, we anticipate that successfully achieving the Specific Aims of this project will result in a novel treatment that enhances MSC survival and retention by providing a 3D environment resembling the corneal extracellular matrix. The treatment is expected to improve visual outcomes, seal and repair stromal injuries, facilitate re-epithelialization, and reducing the healthcare system burden.

NIH Research Projects · FY 2026 · 2026-05

PROJECT ABSTRACT Over 9.2 billion metric tons of plastic were manufactured between 1950 and 2017, and the world continues to produce >400 million metric tons annually. Waste management systems available to cope with the mounting burden of plastic waste include landfills, incineration, and recycling. Emerging technologies have also focused on the incorporation of recycled plastic waste into construction materials as an alternative with several benefits. Purchasing plastic from municipal waste sites or collecting plastic garbage from the environment is cost effective, making plastic bricks an inexpensive alternative to traditional construction materials, a cost-effective way to confront pollution, and a simple approach for local communities to access needed building supplies. The research objectives in this proposal will integrate work in both exposure assessment and health effects in order to provide a comprehensive understanding of environmental emissions and leaching from recycled-plastic bricks/pavers across their life cycle (from production, to use and weathering). The first approach will investigate the physiochemical nature of both gas-phase and particulate emissions released during brick production and the effects of recycled plastic weathering on the emission profiles. The second approach will investigate the capacity for grinding/cutting of these bricks, common techniques employed during construction, to produce inhalable microplastics/nanoplastics (MPs/NPs) and promote the release of encapsulated toxins/additives. In our final approach, a ventilated artificial lung exposure system will assess intrapulmonary exposure conditions and the impact of repeated exposure to these aerosolized pollutants on primary human airway epithelium grown under air-liquid-interface (ALI) conditions. Assays will assess acute toxicity, impact on inflammatory and growth factors, and detailed alterations to the transcriptome by differential mRNA-Seq and gene functional pathway analyses. Specialized techniques previously developed for analyzing engineered nanomaterials (ENMs) and the toxicology of inhaled tobacco products will be applied in novel ways to the study of recycled plastic products. Our multidisciplinary team includes an environmental health and aerosol scientist, an environmental engineer, and a pulmonologist with expertise in environmental and molecular toxicology. Working together, we will determine the exposure potential from plastic recycling and construction brick production in Aim 1, the impact of construction practices (such as grinding) on aerosol release in Aim 2, and intrapulmonary exposure conditions and biologic effects from recycled plastic exposures in Aim 3. This will allow us to carefully investigate emissions, exposures and potential health effects across the life cycle of these recycled-plastic construction bricks/paver. We will focus on hydrophobic polyethylene terephthalate (PET) and high-density polyethylene (HDPE) plastics; the principle recycled plastics in the U.S. Emissions of particulate matter (PM) containing MPs and NPs, volatile organic compounds (VOCs), heavy metal, and metal oxides will be measured.

NSF Awards · FY 2026 · 2026-05

Microprocessors have advanced to a point where they are no longer entirely reliable, being affected by silent computation errors (SCEs) that can corrupt the validity of application results without the user being able to notice. These errors compound for large scale high performance computing (HPC) applications that run in deployments with hundreds or even thousands of nodes and while there exist techniques and research on using runtime monitoring to detect such errors, they suffer from high-overhead, they are limited in the errors they detect, and they are all best-effort, without any guarantees that the errors will be detected. This project aims to address this problem by developing novel, end-to-end, modular, efficient, and verifiable SCE detection runtime monitoring systems for HPC applications. The project’s novelties are formal foundations for reasoning about SCEs, abstractions for decomposing HPC applications in easy to monitor fragments, and proof techniques to formally verify the correctness of the SCE detection mechanisms. The project’s impacts are helping scientists and other HPC practitioners to trust the results of their applications and draw robust conclusions, powering scientific discovery. The goal of this project is to improve SCE detection for HPC applications in two ways: (1) reduce the overhead, and (2) provide formal guarantees that SCE detection is correct. A key insight that enables both is that HPC applications can be decomposed into fragments with special properties that can be used to modularly detect SCEs in each fragment. The project can be separated into four research threads. First, developing formal foundations for reasoning about CPU SCEs together with proof techniques and mechanized proofs that existing SCE detection mechanisms are correct. Second, developing control-path abstractions for HPC applications and use them to develop a verifiable control-path aware SCE detection mechanism. Third, developing a verified library of HPC computation kernels and their validation formulae; using them to develop a verifiable validation-aware SCE detection mechanism. Finally, developing foundations for reasoning about GPU SCEs, together with GPU specific abstractions and proof techniques for GPU SCE detection mechanisms. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NIH Research Projects · FY 2026 · 2026-05

PROJECT SUMMARY There are over 1 million people in the U.S. and more than 40 million people in the world living with HIV (human immunodeficiency virus). The Palm Springs Symposia on HIV/AIDS brings together prominent researchers, clinicians, and policymakers to address the latest advancements and challenges in HIV/AIDS prevention, treatment, and eradication strategies. It serves as a crucial platform for fostering collaborations, disseminating cutting-edge research findings, and translating scientific discoveries into actionable strategies to combat the global HIV/AIDS epidemic.

NSF Awards · FY 2026 · 2026-05

Understanding the structure and function of the tissues that transport water and sugars in plants—xylem and phloem—is essential for predicting and managing the future of both agricultural and natural ecosystems and how they respond to stress. Yet, there are large gaps in current knowledge about how these tissues are organized, how they interact, and how they respond during drought. This project will test hypotheses for how the coordinated anatomy and physiology of leaf carbon and water transport determines the growth, drought resilience, and geographic distribution of plant species, for a wide range of species of herbs, shrubs, and trees from across the US. By combining measurements of xylem and phloem function with state-of-the-art mechanistic models at different scales (leaf, whole plant and ecosystem), the project team will generate fundamental discoveries and resolve how the leaf carbon and water transport systems contribute to whole plant and ecosystem function. This project will benefit the American public more broadly by creating unprecedented databases for leaf structure and function and plant responses to drought, by training undergraduate students in methods of research, data analysis, and writing, and—in collaboration with artists—by developing workshops to transform scientific research into creative public engagement, combining lectures, demonstrations, and hands-on activities, including creation of visual pieces and augmented- and virtual-reality experiences. Further, the project will include outreach to the grape and wine industry, highlighting new discoveries, as the interaction between sugar and water transport in grapevine leaves strongly influences grapevine stress responses and wine quality. The goal of this research is a mechanistic understanding of the variation in leaf xylem and phloem traits and their coordination and dynamics during drought, and implications at tissue, organ, plant and ecosystem levels. First, the project will break new ground in establishing how leaf sugar and water transport are integrated physiologically, and how this integration influences growth at leaf, plant, and ecosystem scales and adaptation across climatic niches. In particular, the project will resolve how leaf carbon and water transport anatomy and flow rates are coordinated within and across species, how they determine maximum rates of gas exchange and growth, how they vary with other functional traits, and how they adapt to environmental conditions. Second, the project will provide new resolution of drought impacts on leaf sugar and water transport across scales, including on ecosystem carbon and water fluxes. The project will clarify drought responses—how, and in what sequence, the sensitivities of the leaf xylem-phloem complex influence the responses and resilience of leaf gas exchange, leaf expansion, plant growth (and, if unrelieved, plant mortality), and ecosystem functions. The project team will generate physiological and functional trait data and model products that will be of value to a wide range of scientists from physiologists to ecologists, the training of many undergraduate and graduate students, innovative art/science workshops, and an unprecedented understanding of leaf xylem and phloem structure, dynamic transport, and implications for drought tolerance, adaptation and ecosystem function. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NIH Research Projects · FY 2026 · 2026-05

PROJECT SUMMARY Uveitis is the fifth leading cause of blindness in the developed world. Intermediate, posterior, and panuveitis are nearly always chronic diseases which account for the highest rates of visual impairment and the development of ocular complications among patients with uveitis. Successful management of these diseases requires long-term care, careful examination, ophthalmic imaging evaluation, and monitoring to preserve vision. A significant challenge in the evaluation of uveitis imaging is the lack of objective biomarkers. Uveitic macular edema (UME) is one of the most common complications in intermediate, posterior, and panuveitis, occurring in approximately 40% of these patients, and is the most common cause of visual impairment and blindness in uveitis. Importantly, UME can be present in successfully treated eyes with inactive uveitis, suggesting that there are risk factors that are independently associated with uveitic inflammatory activity and the persistence of UME. Optical coherence tomography (OCT) is a widely utilized diagnostic tool in the evaluation of patients with uveitis. Most clinical OCT interpretations focus on macular thickness, cystoid spaces, subretinal fluid, and epiretinal membrane formation. However, other findings on OCT, such as ellipsoid zone integrity, photoreceptor layer thickness, intraretinal hyperreflective foci, choroidal thickness, and disorganization of retinal inner layers, have been identified as potential prognostic biomarkers. Investigation of OCT biomarkers is particularly compelling, since OCT imaging is non-invasive, widely available, routinely used in clinical practice, making it an optimal tool for the quantitative evaluation of inflammation and UME. Building on our expertise in image analysis and clinical trials, we will perform a secondary analysis of a combined OCT imaging and clinical dataset from four NEI-funded uveitis randomized clinical trials including the Periocular vs. Intravitreal Corticosteroids for Uveitic Macular Edema (POINT) Trial, Macular Edema -Ranibizumab vs Intravitreal Anti-inflammatory Therapy (MERIT) Trial, Adalimumab vs. Conventional Immunosuppression for Uveitis (ADVISE) Trial, and the First-line Antimetabolite as Steroid-sparing Treatment (FAST) Uveitis Trial. We will pursue the following specific aims: 1) to identify OCT biomarkers that are predictive of response to therapy for uveitic macular edema, 2) to determine which OCT biomarkers correlate with baseline visual acuity and are predictive of longitudinal changes in visual acuity in patients with UME, and 3) to evaluate the association of OCT biomarkers with uveitis activity in intermediate, posterior, and panuveitis and in selected specific uveitic diseases. The aims of this study will address the NEI strategic plan for the area of emphasis relating to the “Immune System and Eye Health”. This study will identify imaging biomarkers of UME and uveitis that will help in disease detection and surveillance. Ultimately, earlier detection and improved monitoring of UME and uveitis can prevent permanent vision loss and disability.

NIH Research Projects · FY 2026 · 2026-05

PROJECT SUMMARY The aim of this proposal is to determine the biological underpinnings of canonical computations in the brain. The focus will be on how these computations manifest in primate visual system, which is the classical system for identifying such transformations of information. Canonical computations are fundamental processing patterns that underlie a wide range of neural functions, impacting perception and cognition across hierarchical brain networks. However, there are large families of possible biological circuits that could implement these computations and, likewise, vastly different computations can be implemented with the same or very similar neural circuitry. What is needed to advance our understanding of these computations in the brain is a way to bridge the gap between physiology, computation and circuitry in a tractable, generalizable model living system. Marmoset early visual areas V1 and V2 are the perfect testbed to develop models of cortico-cortical computations and circuits, some of which will generalize to the rest of the visual system and to hierarchical transformations of information throughout the primate neocortex. An exhaustive dataset of simultaneous V1 and V2 neural responses with high density electrophysiology and calcium imaging will be collected in combination with perturbations using virally mediated opto- and chemo-genetic tools to test models of a canonical interareal circuit. In contrast to the mouse model, where these tools have largely been developed and implemented, the marmoset has prototypical primate neural circuits closely related to our own, but in a simpler and more accessible brain than that of larger primates. The training aims of this proposal support the development of the analysis and genetic tools that are required to understand the transformation of information between V1 and V2. These support an independent research phase, to dissect the circuits involved in interareal transformations and extend the analysis to additional stages of the visual hierarchy. The overall goal of the project is to understand the transformation of information between areas in the visual system ultimately to arrive at a canonical model for cortico-cortical computation and circuitry across the brain.

NSF Awards · FY 2026 · 2026-05

This award funds the operation of two ion microprobes at University of California-Los Angeles (UCLA). These machines make many types of geochemical measurements on solid samples, such as pieces of rock, meteorites, and other materials. These ion microprobes can investigate volumes of rock too small for most other methods, making them crucial for studying tiny geological features. These instruments are open to use by outside researchers. The facility will help users to study a wide range of topics and investigate the earliest periods of Earth and Solar System history, date geological events throughout Earth history, and study recent environmental changes recorded in younger rocks. The laboratory will provide data for hundreds of U.S. scientists and contribute to U.S. science education by collecting data for student dissertations and theses. This award provides continuing support for the UCLA ion microprobe laboratory as a national user facility. Use of the facility’s two large radius secondary ion mass spectrometers (SIMS) by members of the U.S. science community are subsidized by this award, providing access to high spatial resolution geochronology, stable isotope, and trace element data for geochemistry and cosmochemistry. During the award period, the laboratory will continue to focus on providing high quality isotopic data to the community while both expanding the range of isotopic analyses offered for users and pursuing fundamental research into the evolution of the early Earth and Solar System, accessory mineral geochemistry, and stable isotopes on a variety of geological and biological materials. The facility plans new technique development activities, enhancing its geochronological capabilities by investigating 40K-40Ca dating in sylvite to characterize the stability of salt deposits and their suitability as nuclear repository sites. Facility scientists will also develop U-Pb dating protocols for accessory minerals they have not previously pursued (e.g., apatite), and will expand their high spatial resolution U-Pb and trace element protocols to ever smaller mineral inclusions in order to better characterize geologic histories in a variety of geologic settings, facilitated by the very high spatial resolution of the ims1290 ion microprobe’s Hyperion-II ion source. Facility researchers will also further develop U series dating for Quaternary volcanic materials. The facility will continue collaborations on samples returned from asteroid Bennu by NASA’s OSIRIS-REx mission, which also benefit from the high spatial resolution of the ims1290. Facility researchers are also pursuing more recent environmental and biological applications, measuring stable isotopes in otoliths from endangered salmon to understand the effects of drought and changing temperatures on their mortality. The laboratory will continue to enhance the scientific infrastructure and science education in the United States, contributing to student thesis and dissertation research in a variety of topics in the Earth and planetary sciences. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NIH Research Projects · FY 2026 · 2026-05

PROJECT SUMMARY Breast cancer is the most prevalent cancer among U.S. women, accounting for nearly one-third of new cancer diagnoses in women annually.2. Accurately predicting recurrence and mortality is critical for prognosis, treatment decisions, and improving patient outcomes. However, current clinical risk models, such as the Nottingham Index and PREDICT Breast,4,5,23,107 have limitations that hinder precision and clinical utility. More comprehensive prognostic tools are needed. Digital pathology imaging offers a promising solution by capturing tumor characteristics beyond human visual discrimination, including nuclear heterogeneity and chromatin complexity. Recent analytic advancements suggest that pathology images may capture nuanced tumor structural data beyond the discriminating capabilities of traditional microscopic evaluation by humans, offering novel parameters for refining risk prediction. This proposal aims to develop a robust Survivor Model (Aim 2) that merges whole slide image (WSI) data with traditional clinical prognostic factors to improve survival estimation. This will be complemented by developing an Explainer Model (Aim 3) to enhance transparency by generating pathologist-interpretable text descriptions of predictive image features. Our specific aims are: AIM 1. Establish benchmarks for predicting recurrence and survival at 5, 10, and 15 years using a clinical epidemiological model and a deep learning image-based model. 1a) Assess the PREDICT prognostic model107 performance using clinical data. 1b) Retrain and evaluate the SlideGraph neural network model24 using image data. AIM 2. Develop a new Survivor Model by expanding QuiltNet,25 our team’s vision-language model, to integrate clinical features and WSI data for recurrence and survival prediction, then compare it against benchmarks from Aim 1. AIM 3. Develop an Explainer Model for WSI-based survival models incorporating pathologist feedback. 3a) Create an Explainer Model that interprets survival predictions from both the Survivor Model and another survival model. 3b) Integrate pathologist feedback to refine predictions. 3c) Validate the Explainer on CALGB and the large, diverse PATHWAYS Study dataset. This work will generate a clinically actionable risk prediction tool that combines deep learning with pathologist- informed reasoning, advancing precision oncology and enhancing breast cancer prognosis. By improving risk stratification and interpretability, this model has the potential to guide treatment decisions, personalize patient care, and ultimately improve outcomes for individuals with breast cancer.

NIH Research Projects · FY 2026 · 2026-04

Project Summary Schizophrenia (SZ) involves distinct changes in brain network organization, in which disrupted oscillatory communication between brain regions is thought to contribute to a breakdown in cognitive and perceptual processes. In addition to widespread changes in central nervous system (CNS) activity, SZ involves distinct alterations in the rhythmic activity of the autonomic nervous system (ANS). A growing body of evidence suggests that physiological cycles such as heart rate, respiration, and heart rate variability (HRV) interact with the rhythms of the brain and may help coordinate oscillatory communication within brain networks. Whether and how ANS dysfunction in SZ mechanistically contributes to disorganized brain activity and cognition remain to be explored. SZ is characterized by prominent changes in the parasympathetic branch of the ANS, which can be indexed by the cyclical fluctuations in heart rate associated with respiration, known as high-frequency (HF) HRV. HF-HRV is robustly associated with psychological health and cognitive functioning and is consistently found to be lower in SZ. Our group recently showed that, rather than simply reflecting shared neural systems supporting physiological and psychological regulation, the associations between HF-HRV and psychological functioning may be due in part to a causal influence of cardiac autonomic rhythms on brain activity. We observed that HF-HRV oscillations modulate EEG oscillations through phase-amplitude coupling (PAC), a well-established mechanism of oscillatory organization in the brain that appears to extend to brain- body interactions. Crucially, directions of effects were stronger from heart-to-brain than brain-to-heart. We also found that HRV-EEG coupling is lower in individuals with SZ and that this deficit is associated with impaired sustained attention. Our findings suggest that dysregulated neural activity and cognitive dysfunction are due in part to disrupted body-to-brain communication in SZ. To further probe the causal mechanisms through which autonomic rhythms influence brain activity, the proposed study will examine whether increasing HF-HRV can lead to changes in oscillatory activity and cognitive functioning in patients with first-episode SZ and healthy comparison (HC) participants. Prior research shows that simply reducing respiratory rate results in immediate and sizeable increases in HF-HRV. In the proposed study, SZ and HC participants will complete a series of tasks measuring cognitive functioning before and after completing a slow-paced breathing exercise, with EEG, EKG, and respiration measured throughout. We hypothesize that increasing HF-HRV through slow-paced breathing will lead to increased HRV-EEG coupling, increased oscillatory connectivity within relevant brain networks, and cognitive improvements. We aim to clarify how autonomic rhythms influence brain activity and cognition and to bridge largely separate literatures on ANS and CNS dysfunction in SZ. Ultimately, understanding how psychological health depends on the integrated functioning of the brain and body may introduce new treatment avenues for SZ and other mental illnesses.

NSF Awards · FY 2026 · 2026-04

This project will advance the understanding of causes and implications of recent extreme sea ice variability in the Antarctic through development of a research and logistical partnership with New Zealand. We focus on the Ross Sea as an area of strategic interest for the US and New Zealand, a major locus of recent variability, and as a key area of significance to global ocean circulation and intact ecosystem food webs, motivating the establishment of the Ross Sea Marine Protected Area (MPA). Understanding drivers of sea ice variability and its implications for this large and remote region requires integration across a range of approaches. This pilot study will integrate deployment and testing of advanced observing technology, modelling, and satellite remote sensing to assess capabilities and strategies for a broader integrated program to understand the drivers and implications of the recent rapid sea ice decline in the Ross Sea. This program seeks to advance capability in key areas, building a strategic collaboration between the United States Antarctic Program and the New Zealand Antarctic Research Program and other international partners, in alignment with the “Antarctica InSync” initiative, supporting coordinated, sustainable research in one of the world’s most logistically challenging environments. This will foster increased collaboration and shared logistics support, and further enhance US leadership in the Antarctic. Insights from this work will help improve predictions of how the Southern Ocean and sea ice both respond to and influence global environmental change. Antarctic sea ice extent has exhibited extreme recent variability, with a modest long term increase culminating in 2015, followed by a dramatic decline in 2016 and record lows in both summer and winter in 2023, although with significant variability over the past decade. These changes in sea ice extent are likely closely related to changes in thickness. The causes of this recent variability and its implications have been identified as a key theme for the international research effort “Antarctica InSync”. This collaborative RAPID project will (1) evaluate advanced and emerging technology that can contribute to an observational network capable of capturing key processes across the Ross Sea, (2) improve and evaluate both satellite and model products with in situ observations, and (3) develop a combined modelling, satellite, and in situ observational strategy to understand these processes. This is centered on capability development through evaluation of techniques in the McMurdo region, leveraging existing programs and logistics. This capability can then be exploited in future projects through widespread deployment of in situ observations, integrated with a refined modelling and satellite observation strategy to address the complex coupled role of various atmosphere-ice-ocean processes in driving sea ice variability. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NIH Research Projects · FY 2026 · 2026-04

Abstract Comorbid anxiety disorders and substance use disorders (SUD) are associated with poor clinical and functional outcomes. Identifying solutions for the treatment of this comorbidity is critical to improving public health. Theoretical models, clinical trials, and policy support the use of treatments that simultaneously address both problems in clinically meaningful ways, as opposed to separate treatments for each problem, which can lead to poorer clinical outcomes and barriers to care. Digital therapeutics specifically designed for those with comorbid anxiety disorders and SUD are lacking and yet have the potential to increase access to evidence-based behavioral treatment that is currently inaccessible. Although digital interventions exist separately for anxiety disorders and for SUD, none have been developed to address the unique needs of the prevalent and high-risk population of those with comorbid anxiety/SUD. This study builds upon Dr. Wolitzky-Taylor’s innovative program of work in developing and evaluating CBT protocols for this comorbidity by adapting her treatment model to a digital platform. This study aims to develop and evaluate the preliminary efficacy of a digital therapeutic for comorbid anxiety/SUD, Anxiety Management Treatment for SUD (AMT/SUD). As a first step, although the intervention is framed transdiagnostically and relevant across the anxiety and substance use disorders, the target population will be those with mild to moderate cannabis and/or alcohol use disorder, as digital therapy is an appropriate primary modality for this SUD population. First, an iterative, human-centered design process will be used to develop the mobile application-based intervention. This will include a series of focus groups to improve upon a prototype of the application, development of the application, and a small open trial (n=8) to assess for usability and to identify and address any issues prior to the randomized clinical trial (RCT). Next, a pilot RCT will be conducted with adults (N=60) with comorbid anxiety disorders and SUD (recruited from the community and several clinics who serve this population but do not provide integrated care for both problems). Participants will be randomized to either (a) “AMT/SUD”, in which they will engage with the digital therapy (which will include the option for on-demand clinical coaching on the digital content) for 12 weeks, or (b) “SUD-track”, an active control condition in which participants will be instructed to engage with Quitzilla, a publicly available substance use (and other behavior) tracking/monitoring app with motivational content, for 12 weeks. Participants will be assessed on treatment acceptability at post-treatment, and on anxiety and substance use outcomes at baseline, and 3- and 6-mo follow-ups. Following the RCT, additional patient focus groups will be conducted to inform additional refinements to the AMT/SUD mobile application-based CBT program. This digital therapeutic has the potential to make a substantial public health impact.

NIH Research Projects · FY 2026 · 2026-04

Project Summary Sensory experience during early postnatal life profoundly influences the development of neural circuits. The primary visual cortex (V1), as part of the neocortex, is a well-established site of developmental plasticity, where visual experience plays a key role in the proper development of its binocular circuitry. However, how vision regulates the organization of individual neurons in V1, the cell types and connections they form, and the molecules they express, remain poorly understood. I address this knowledge gap by combining single-cell transcriptomics, epigenomics, connectomics and computation to link genes, cell types, regulatory networks and circuit structure in layers 2 and 3 (L2/3) glutamatergic neurons in V1. My recent work found that L2/3 glutamatergic neurons in V1 form continuous rather than discrete cell types. These cells differentially express hundreds of molecules known to be important for neuronal cell-type identity in a graded fashion, and are spatially enriched in different sublayers of L2/3. In mice that are deprived of visual experience by dark rearing, this cell-type organization is disrupted in a specific way. Based on these findings, we hypothesis that the continuous and vision-dependent cell types are key structure underlying cortical developmental plasticity. Aim 1 of my research will determine the developmental origin of L2/3 cell-type continuum. I will generate a developmental atlas of the L2/3 neurons using three existing single-cell RNA-seq datasets from mice with and without visual deprivations. I will delineate the vision-dependent developmental programs of L2/3 neurons, and identify gene programs that are temporally-regulated, type-specific and/or vision- dependent, which will serve as candidates for follow-up experiments to examine their causal link in L2/3 wiring. Aim 2 will examine the axonal-projection patterns of L2/3 neurons in V1. These neurons send divergent projections from V1 to many higher visual areas (HVAs), and transcriptomic differences in L2/3 neurons are thought to be associated with differences in projection targets. We will use barcoded connectomics to systematically determine the relationship between L2/3 cell-type continuum and projection targeting specificity to HVAs. Aim 3, to be pursued during the R00 phase, will investigate the gene regulatory networks underlying L2/3 neurons. Using single-cell multiomics data, we have identified tens of thousands of genomic regions with graded differential accessibility along the L2/3 cell-type continuum. To understand the regulatory logic linking gene expression and genomic elements often known as enhancers, we will use both experimental and computational methods. Experimentally, we will perturb the expression levels of key transcription factors and examine changes in L2/3 cell-type organizations and projection patterns. Computationally, we will train a DNA language model to predict the graded chromatin profiles of L2/3 neurons, and use in silico perturbations to screen candidate genes. Ultimately, the two efforts could be combined into a closed-loop iteration where experiments improve the model, and the model prioritizes experiments. My work will investigate the influence of visual experience on genes, cell types and circuits in a subclass of cortical neurons, thereby providing insights into the molecular logic of wiring plasticity in the mammalian neocortex.

NIH Research Projects · FY 2026 · 2026-04

PROJECT SUMMARY Metabolic diseases, such as obesity and type 2 diabetes (T2D), are characterized by perturbations of glucose tolerance, pancreatic beta cell function, energy imbalance, appetite regulation, and other unknown pathways. Clinical and genetic studies in humans and animal experiments have also implicated gut microbiota and products derived from their metabolism of dietary nutrients as important mediators of metabolic risk. In this regard, we have observed protective associations between plasma levels of indole-3-propionic acid (IPA) – a metabolite generated entirely by gut bacteria from dietary tryptophan – and insulin resistance traits in humans and mice. We have also identified 2 loci for IPA levels on chromosomes 2 and 16 in humans, which harbor genes encoding lactase (LCT) and members of the medium-chain fatty acid acyl-CoA synthetases (ACSM1-5), respectively. These observations point to host genetic factors that modulate IPA levels through both its production by gut bacteria (LCT) and endogenous metabolism (ACSMs). This notion is consistent with our gnotobiotic studies in germ-free mice that increasing Bifidobacterium abundance, which is reproducibly associated with the LCT locus in humans, elevated plasma levels of IPA and attenuated high fat diet-induced (HFD) insulin resistance. In parallel studies, IPA supplementation studies in mice also protected against metabolic disturbances, at least in part, through maintenance of intestinal barrier function, activation of arylhydrocarbon receptor (Ahr), suppression of nicotinamide N-methyl transferase (Nnmt), and elevation of tissue nicotinamide adenine dinucleotide (NAD+) levels. Despite these observations, we still only have a poor understanding of the genetic architecture of IPA metabolism in the host, through either main effects or interactions with diet/gut microbes; the interplay between gut bacterial species that metabolize tryptophan to IPA and its precursors; and the mechanisms underlying the tissue-specific protective effects of IPA on T2D-related traits. The goals of this project are use integrative systems genetics, gut bacterial engineering and functional validation studies in humans and mice to address these fundamental gaps in knowledge. In Aim 1, we will validate ACSM2 as one host genetic determinant of IPA levels and further define the interrelationships between IPA levels, gut bacteria, host genetic factors, and metabolic outcomes in humans. In Aim 2, we will use colonize gnotobiotic mice with synthetic bacterial communities to elucidate the interactions between gut bacteria and dietary factors that promote IPA production and beneficial metabolic improvements in the host. Finally, Aim 3 will determine the basis for the protective association of IPA levels with metabolic phenotypes using genetically modified mouse models for genes involved in IPA signaling. Taken together, these complementary approaches will provide important genetic and biological insight into the causal role of gut microbe-derived IPA in promoting metabolic homeostasis in humans and mice.

NIH Research Projects · FY 2026 · 2026-04

ABSTRACT The Los Angeles urban wildfires (LA Fires), which began on January 7, 2025, have become one of the most destructive disasters in U.S. history. Although officially contained by February 7, 2025, emerging evidence sug- gests that exposure risks persist long after active burning due to post-fire degassing and cleanup activities. LA Fires released a complex mix of volatile and semi-volatile organic compounds (VOCs and SVOCs) from burned structures, vehicles, and household products. These emissions can last weeks to months, as damaged materials release pollutants back into the air. Cleanup activities, including debris removal and demolition, may further re- suspend contaminated dust and release VOCs, prolonging exposure risks for returning residents. However, post- fire indoor air quality remains an understudied yet critical issue in wildfire research. Since January 8, 2025, our team has monitored indoor and outdoor air quality in 25 households near both fires. We found outdoor concen- trations of benzene, toluene, ethylbenzene, xylenes (BTEX), and toxic heavy metals were over 100 times higher during active burning. In the post-fire phase, indoor BTEX levels in burn zone homes exceeded outdoor concen- trations, even in the absence of indoor activities, suggesting prolonged off-gassing from building materials. Ad- ditionally, real-time monitoring detected persistently elevated ultrafine and sub-micron particles in the burn zones weeks after the fires were contained. These findings underscore the urgent need to characterize post-fire expo- sure pathways, particularly in indoor environments where people spend most of their time.To address these critical gaps, we propose two aims. Aim 1: Assess indoor and outdoor exposure to fine and ultrafine particles and VOCs post-fire. We will expand sampling to 50 homes (25 per fire) and monitor air quality over one year or until cleanup is complete. Homes will include affluent, predominantly White communities (Palisades) and pre- dominantly Black communities (Altadena). We hypothesize that indoor VOC levels will remain elevated due to prolonged off-gassing, while fine and ultrafine particles will persist outdoors due to dust resuspension and sec- ondary aerosol formation. Aim 2: Evaluate how building characteristics and mitigation measures influence indoor air quality. We hypothesize that older, leakier homes will experience greater infiltration of outdoor fire smoke, leading to higher post-fire indoor VOC levels. We further hypothesize that wealthier residents in the Palisades will implement more effective mitigation measures (e.g., HVAC upgrades, air purifiers) compared to residents in Altadena, leading to lower indoor exposures. With over 16,000 structures destroyed, the LA Fires released highly toxic pollutants, posing persistent exposure risks to affected communities. This study will provide time-sensitive data to guide returning residents, inform evidence-based policies, and improve indoor air quality recommenda- tions for filtration and ventilation. Findings will also lay the groundwork for future research on the long-term health impacts of toxic urban wildfire smoke, a growing concern as wildfires increasingly threaten densely populated areas.

NIH Research Projects · FY 2026 · 2026-04

PROJECT SUMMARY/ABSTRACT Dr. Alvin Chan is a board-certified pediatric gastroenterologist and physician-scientist dedicated to investigating the regulatory role of bile acids in health and disease. His research focuses on how bile acids shape metabolic processes. His long-term carer goal is to establish an independent research program exploring the role of bile acid metabolism in different pathophysiological contexts to improve human health. He is supported by his primary mentor, Dr. Thomas Vallim, a leader in bile acid and lipid metabolism, as well as his co-mentors, Dr. Peter Tontonoz and Dr. Martín Martín, who will provide their expertise in cholesterol metabolism and intestinal physiology. Through UCLA's Clinical and Translational Science Institute, Children's Discovery and Innovation Institute, and Specialty Training and Advanced Research Program, Dr. Chan will have access to a wealth of resources for career development, including seminars and workshops in grant writing, manuscript preparation, and ethical research. He will also receive formal instruction in energy balance, hormone regulation, lipid metabolism, and biostatistics through graduate courses. Dr. Chan has the full support of his institution. The 4-year research and career development plan outlined in this application will prepare Dr. Chan for an independent academic career in biomedical research. This project aims to elucidate the metabolic pathways linking bile acids to systemic lipid homeostasis in time-restricted feeding (TRF), a form of intermittent fasting that has emerged as a promising dietary strategy to combat metabolic disease. Increasing evidence suggests that synchronizing daily food intake within a specific time window restores the diurnal rhythms of bile acids, leading to improvements in body weight, insulin sensitivity, and dyslipidemia. However, the precise mechanisms by which bile acids mediate TRF's metabolic benefits remain unclear. This research will test the central hypothesis that bile acids are important mediators of TRF's effects by exploring key metabolic pathways in Western diet-fed mice under TRF conditions. In Aim 1, Dr. Chan will determine whether TRF promotes bile acid synthesis to prevent systemic cholesterol accumulation. To determine whether increased bile acid synthesis is required for this protection, he will use a liver-specific AAV-CRISPR strategy to disrupt bile acid synthesis in mice. In Aim 2, he will investigate whether the decrease in food intake during TRF is driven by enhanced bile acid signaling and gut hormone secretion. In Aim 3, he will assess how TRF reduces lipid absorption by testing whether it activates intestinal FXR to alter the bile acid pool composition and/or induces morphological adaptations in the intestine. By addressing the largely unexamined role of bile acids in TRF, this research may uncover key metabolic pathways that could inform novel therapeutic strategies for metabolic disease.

NIH Research Projects · FY 2026 · 2026-04

This education project is a continuation of our current, national class, Training in Advanced Statistical Methods in Neuroimaging and Genetics. Over the past 15 year the National Institutes of Health has greatly increased funding of grants that utilized advanced neuroimaging methods, genetic methods, and advanced statistical methods. While introductory courses are offered, ours is the only advanced course offered in the United States that provides an intensive, hands-on (“doing”) learning opportunity to better prepare biomedical and clinical researchers in advanced statistical methods. In one decade the combined budgets that utilize these advanced analysis techniques from the National Institute of Neurological Disorders and Stroke, National Institute of Mental Health, National Institute on Aging, National Institute on Drug Abuse, and National Institute of Biomedical Imaging and Bioengineering grew 5-fold, and there continues to be a great need to provide an educational opportunity to ensure the workforce is well positioned to carry out important work that has been identified by these and other institutes. Our program will continue to meet this need. We bring together a group of diverse world-class scientists and educators in a two-week intensive format to provide theoretical lectures paired with hands-on computer tutorials. Our course has served 103 students (55 total in 2021-2022 via Zoom due to COVID-19), and in 2023 (our 1st year of in-person) we taught 20 students, and 28 students in 2024 (in-person). We will enroll 26-30 students in April 2025 session. In our competitive renewal we will continue to enroll 26-30 students per year. With this being an advanced course, we ensure that the students accepted are a good education-level match for the content. We also implement mechanisms to maximize diverse perspective in our students and our teaching faculty. These students are accepted from across the United States, with attention to attracting a diverse student cohort. This education program will continue to distribute Tuition Awards based on financial need. We have evolved our course based on feedback from our current course alumni. In our class, over two weeks, students learn and put into practice methods such as: hierarchical statistical models, Bayesian statistics, network science, functional and structural connectomics, disease driven degeneration of the brain, and methods for analysis of genetics data such as polygenic risk scoring and structural equation modeling. The course concludes with lectures and labs on multi-modal analysis (imaging and imaging-genetics), and classification methods for biomarker development. Our course now includes 5 guest lecturers and team building activities outside of the classroom. To ensure students apply the acquired knowledge and skills to their independent research projects back at their home institutes, we supplement the course with our innovative continuing education: zoom-based sessions with the faculty for 8-months post formal course and students having near-real-time access regarding technical implementation questions through the Slack. This continued education portion greatly increases success utilizing their new practical skills in their own research.

NIH Research Projects · FY 2026 · 2026-04

Project Summary Signals that cells receive over time from a small set of pathways (e.g., BMP, Wnt, and TGFβ) shape their fate and phenotype during development, regeneration, and disease. Despite their central importance, signaling histories of individual cells are often inaccessible to direct observation, hindering quantitative analysis and obscuring their connection to eventual cell fate. This challenge is particularly pronounced in mammalian systems, where limited optical access and the constraints of size and timescale often render live imaging impractical. To address this issue, we have developed an approach to reconstruct the history of signaling activity in single cells based on endpoint fluorescence images. This is achieved by regulating CRISPR base editors to generate mutations in engineered target sites at rates proportional to the signal of interest. These mutations create a heritable record of signaling activity in the genome, which can be read out at a later time, together with the gene expression profile of the cells. Using this approach, we demonstrated that cells retain a memory of their past response level to BMP signaling for up to 18 days, providing a mechanism for long-term interactions between signals that can facilitate coordination of developmental processes over time. In this proposal, we will expand the scope and utility of our signal recording approach by extending its dynamic range to capture the broad spectrum of in vivo signal intensities and enabling simultaneous recording of the sequence and timing of two signaling pathways. We will also engineer mouse embryonic stem cells to record three key developmental pathways: BMP, Wnt, and Nodal. This will allow us to generate stem cell-derived embryo models and chimeric embryos to link cell fate and spatial organization at the onset of organogenesis with signaling activity at different time windows earlier in development. Additionally, we will investigate mechanisms that enable long-term changes in BMP responsiveness following an initial stimulation, without requiring differentiation. We will then test whether similar mechanisms exist in Wnt and Nodal pathways and assess their role in mediating long-term crosstalk between pathways. To achieve these goals, we will take an interdisciplinary approach combining gene editing, quantitative imaging, epigenomic assays, computational analysis, and generation of developmental models. The proposed goals build on my prior publications, recent preliminary data from our lab, and collaborations I have established since launching my lab. This research program will substantially advance the state of the art in molecular recording, transforming it into a technology that can be used in vivo, in mammalian systems to drive biological discovery. Our long term vision is to identify how signaling history controls cellular decision making during development, and how instructions that cells receive are coordinated over time to produce tissues with the correct number, types, and spatial arrangement of cells. Ultimately, this knowledge will inform strategies for tissue engineering, and open new avenues for understanding and treating diseases driven by dysregulated signaling.