Stanford University

NIH Research Projects · FY 2025 · 2022-07

PROJECT SUMMARY (See instructions): Learning is a fundamental component of neural systems. It is essential for gaining new knowledge or skills, and impaired learning faculties can have major deleterious effects. Although various forms of associative and perceptual learning have been studied our current understanding of how neural circuits learn remains incomplete. Humans and animals leverage category learning––grouping stimuli together based on shared and often higher order features––to deal with the world’s dazzling complexity. Yet, the neural mechanisms underlying category learning are not known. In this proposal, we focus on auditory category learning leveraging the rich nature and dynamic structure of natural and synthetic soundscapes. Auditory category learning is ubiquitous across the animal kingdom, with vivid examples from invertebrates to humans, and is intimately related to the transformation of sound to percepts. However, mechanistic studies of category learning in audition are not yet mature. In mice, where powerful experimental toolkits exist and new tools are continuously developed, studies of auditory category learning are scarce. Here we will study the multi-regional basis of reshaping of population activity following learning. We will analyze a unique dataset of simultaneous population recordings across brain areas in mice learning an auditory categorization task. We will apply novel computational methods to study how cortical auditory circuits process sounds and how this processing changes following learning. We will explore multiple types of trained categorization as well as responses to categories of natural sounds. We will characterize changes both at the level of single neurons and at the level of neuronal populations. Through simultaneous recordings across brain areas we will delineate changes both at the level of individual brain areas and at the level of interactions between brain areas. Finally, we will use perturbations to improve our causal understanding of the circuitry. These experiments and analyses will allow us to explore specific hypotheses regarding the plasticity and circuit computations of cortical circuits in the mammalian brain, and how these support category learning.

NIH Research Projects · FY 2025 · 2022-07

PROJECT SUMMARY/ABSTRACT: Action potentials are temporal changes of the electrical voltage across the cell membrane, which are crucial for the physiological function of excitable cells such as neurons and cardiomyocytes. In the human heart, cardiac action potentials coordinate the synchronous contraction and relaxation of billions of cardiomyocytes. The waveforms of intracellular action potentials reflect the coordination of a multitude of ion channels, some of which are affected by pharmaceutical drugs to collectively contribute toward proarrhythmic risks. The waveforms of intracellular action potentials also reflect the subtype such as atrial-, ventricular-, or nodal-like cardiomyocytes, or their maturation status. Measurements of intracellular action potentials are mostly performed by the patch clamp technique, which is accurate but invasive, one cell at a time, laborious, and requires specialized expertise. Due to its low throughput and invasive nature, patch clamp is not suitable for drug screening or functional characterization of human pluripotent stem cell derived cardiomyocytes. In the last decade, vertically-aligned and solid-state nanoelectrode arrays (NEAs) have emerged as promising tools with the potential of achieving parallelizable and minimally invasive cardiac AP recording from monolayers of stem-cell-derived cardiomyocytes. However, despite the significant progress and the strong interest, the NEA technology has largely been confined to research groups that develop the technologies, instead of being broadly adopted by the research community. We identified several critical challenges that have hindered such effort. In this proposal, through the partnership between an academic lab and a startup company, we aim to overcome these challenges and develop a robust electrophysiological tool that enables reliable, scalable, and long-term intracellular recording of cardiomyocytes. The goal of this proposal aims to transition the NEA technology from a demonstration of possibility to a status useful to end-users.

NIH Research Projects · FY 2025 · 2022-07

Summary. Prostate cancer (PCa) treatment management is currently heavily reliant upon slide-based histology of prostate biopsies and surgical specimens (prostatectomies). In particular, Gleason grading of histology sections provides a basis for stratifying patients for clinical management, and can result in dramatically different treatment paths. However, prognostication via Gleason grading suffers from several shortcomings, including subjective visual interpretation of complex 3D glandular morphologies based on 2D images, and analysis of a limited amount of tissue (~1% of the biopsy). These shortcomings contribute to poor inter-observer concordance amongst pathologists and poor stratification of patients with indolent vs. lethal disease. For the clinical management of PCa, two major challenges faced by urologists and oncologists, respectively, are: (1) correctly identifying men with low-risk PCa for active surveillance and (2) identifying men who are likely to have disease recurrence and metastasis after curative therapy (surgery or radiation), and hence would benefit from adjuvant therapy. With our open-top light-sheet (OTLS) microscope technologies, our team at the University of Washington (Liu group) has demonstrated the technical feasibility of achieving high-throughput slide-free 3D histology of biopsy and surgical specimens in a nondestructive and reversible manner that does not interfere with current histology methods. Potential benefits over traditional pathology include: (1) comprehensive imaging of specimens (biopsies and surgical bread loafs) rather than sparse sampling of thin sections on glass slides; (2) volumetric imaging of 3D structures that are prognostic; and (3) non-destructive imaging, which allows valuable biopsy specimens to be used for downstream assays. Our team at Case Western Reserve University (Madabhushi group) has also developed computational pathology classifiers, based on intuitive and interpretable “hand-crafted features,” for characterization of PCa aggressiveness based on 2D whole-slide imaging (WSI). In this R01 project, we seek to combine nondestructive 3D pathology with 3D computational pathology approaches to develop a novel prognostic assay, Prostate cancer Image Risk Score via 3D pathology (ProsIRiS3D), for discriminating between indolent and aggressive PCa. In Aim 1, we will develop the core technologies (hardware and software) for ProsIRiS3D. In particular, the goal of Aim 1a is to develop a “4th-generation” OTLS microscopy system capable of achieving sub-nuclear-resolution to explore the added prognostic benefit provided by such high-resolution features. In Aim 1b, computational imaging tools will be developed for extraction of novel 3D quantitative histomorphometric features for PCa prognostication. Our clinical validation studies will show that ProsIRiS3D is superior to analogous 2D approaches for urologists (Aim 2), to determine which newly biopsied patients should be placed on active surveillance vs. curative therapy, as well as for oncologists (Aim 3), to determine which prostatectomy patients have aggressive disease that may warrant adjuvant therapies.

NIH Research Projects · FY 2024 · 2022-07

Project Abstract The effect of analytic flexibility on brain-behavior relationships and predictive models of adolescent socioemotional processing is not well understood. The Maturational Imbalance (or Dual System) Model often lacks reliability and generalizability. Existing work has predominately focused on single task-designs and small samples (median < 50) concentrating on brain-behavior associations using disparate operationalizations of reward and affective processing. The proposed research will integrate three developmental functional magnetic resonance imaging (fMRI) samples (N ~ 105; N ~ 180; N ~ 7,000), with analogous reward and affective paradigms, to investigate key issues related to reproducibility and generalizability: (a) the influence of analytic flexibility on brain-behavior associations and convergence and predictive validity in contrasts within/between task domains; and (b) uncovering task-based fMRI (t-fMRI) brain features (latent neural characteristics) that can serve as the basis for robust brain-behavior prediction models across multiple samples. It is hypothesized that t-fMRI contrasts can be separated across a multidimensional plane of attention and valence, which elicits neural responses leading to approach or avoidance. However, how researchers operationalize positive and negative valence in t-fMRI often varies, and this variability in the decision-making process may influence the underlying neural effects. Aim 1a will examine how brain-behavior associations in a given task change based on analytic decisions relating to fitting general linear models (GLM), contrasts and neural regions. Then, Aim 1b will consider whether changes in brain-behavior associations (as a functional of analytic flexibility) are reflected in changes in construct validity of approach and avoidance within- and between-task domains, such as reward and affective processing. Conversely, traditional univariate GLM approaches show mounting issues in test-retest reliability and express associations that may not support generalizable prediction of behavioral phenotypes. However, the neurodevelopmental literature has proposed that multivariate analyses that leverage dimensionality reduction and machine learning can provide informative brain-behavior prediction models. To test this hypothesis, in Aim 2, dimensionality reduction will be used in a large adolescent t-fMRI sample to generate brain-behavior prediction models and compared across a reward and affective task to consider the influence of constructs. Aim 3 will focus on the dissemination of code and fMRI statistical maps. The fellowship will support the applicant's growth in becoming an independent researcher and leader in the neurodevelopmental neuroscience by providing training in: combining t-fMRI datasets, evaluating the effect of analytic flexibility in fMRI and impact on construct validity, applying dimensionality reduction in neurodevelopmental samples to produce brain-behavior prediction models. This training will support the applicant's long-term goals of understanding of neural mechanisms in adolescent substance use and improving our understanding of traditional and non-traditional measurement models.

NIH Research Projects · FY 2026 · 2022-06

PROJECT SUMMARY / ABSTRACT The purpose of this award is to provide Dr. Brian Rice, Assistant Professor of Emergency Medicine at Stanford University, the support necessary for his transition from a junior investigator into an independent clinician- scientist using applied biomedical informatics to address health disparities. Dr. Rice is an emergency medicine physician with an advanced degree in epidemiology and global health, and a background in computer programming and artificial intelligence. His long-term goal is to utilize his interdisciplinary training to develop and implement machine learning tools to empower precise, high-value clinical decision-making surrounding emergency care and transport in historically disadvantaged populations. His training activities focus on advancing his ability to apply biomedical informatics to address health disparities via these training objectives: 1) expanding his skills in data management and computational statistics 2) learning methods for community- engaged and participatory approaches to health disparities research, and 3) acquiring new skills machine learning and classification model building. The candidate has convened a mentorship team that includes Dr. Tina Hernandez-Boussard, a biomedical artificial intelligence expert with a focus on improving transparency and minimizing bias in machine learning models to make them more equitable and generalizable, and Dr. Stacy Rasmus, a leading Alaska Native behavioral scientist with extensive experience successfully conducting community-engaged qualitative research in rural Alaska. The research proposal builds off the candidate’s prior work with air medical evacuation (medevacs) in rural Alaska which established the central hypothesis that medevacs can be classified as appropriate or inappropriate by machine learning models built on outcome data and enriched by qualitative methods. This central hypothesis will be tested by the following specific aims: 1) define the burden and outcomes of medevacs in rural Alaska; 2) identify key context-specific contributors to medevac utilization in rural Alaska; and 3) develop machine learning models to classify appropriateness of medevac utilization in rural Alaska. The research proposed in this application is innovative because it employs accepted methods of machine learning classification modelling and applies them to novel fields of medevac and Alaska Native health disparities. The significance of the proposed training grant is it will provide the data and the skills required for Dr. Rice to subsequently study the implementation of these models as a decision tool in a future R01-level application. Ultimately, this continuum of research has the potential to decrease expenses and improve safety by redirecting medevac resources towards patients whose time-sensitive conditions benefit from medevacs and away from patients that incur risk and cost without benefit, both in Alaska Native communities in rural Alaska and for all Americans living in rural regions nationwide.

NIH Research Projects · FY 2025 · 2022-06

The cancer research community is on the verge of a major leap in our understanding of the factors that contribute to human cancer risk. While it is clear that mutations in DNA, either spontaneous or environmentally induced, are essential for cancer development, recent advances have highlighted the importance of non-mutagenic factors as rate-limiting determinants of cancer risk in human populations and in mouse cancer models. The root causes of human cancer have been widely debated, but most of the emphasis has been on the origins of the “driver” mutations that are ubiquitous in human tumours. Although epidemiology studies have highlighted the possible roles of lifestyle factors such as obesity, alcohol consumption, inflammation and poor diet in cancer risk, it has generally been assumed that these factors act directly or indirectly to cause mutations in DNA, thus contributing to tumour mutational burden and resulting in increased cancer risk. In contrast, recent sequencing studies have uncovered abundant mutations in normal human tissues, suggesting that even strong cancer driver mutations are not sufficient for cancer formation. These results were presaged by studies of mouse tumour models, some carried out more than 50 years ago, showing that promotion is the rate-limiting step in tumour development. To identify the mechanisms that control mutated normal cells, and to elucidate the precise mechanisms by which promoting factors stimulate the conversion of these cells to neoplastic growth, we have assembled a multidisciplinary team of investigators with wide-ranging experience in epidemiology, genetics, computational network analysis and machine learning, tissue imaging of gene expression, single cell transcriptomics, and genome-wide CRISPR functional screens. We will focus human analysis on a unique collection of several thousand human normal and matched tumour samples from >20 countries, including regions of both high and low cancer risk. Detailed risk factor information and whole genome sequence data is available from all these samples as part of the Grand Challenge Mutographs study. Analysis of these samples, together with detailed intervention studies in human populations, mouse models and human organoids, will allow us to develop a roadmap of tumour promotion from single normal cells carrying driver mutations, through to malignant progression. Our findings will facilitate identification of the causative environmental factors that promote cancer and provide routes to new methods and approaches to cancer prevention based on a deeper understanding of the process of initiated cell selection by tumour promoting agents.

NIH Research Projects · FY 2026 · 2022-06

Advances in neuroscience depend on robust in vivo and in vitro models with innovative technologies to carry out functional and mechanistic studies accompanied by advanced imaging techniques. The Human Brain Organogenesis Program (HBOP), Behavioral and Functional Neuroscience Laboratory (BFNL), Gene Vector and Virus Core (GVVC), and Neuroscience Microscopy Services (NMS) make up a platform, the Stanford Neuroscience Research Center (SNRC), for centralization and dissemination of innovative neuroscience models, reagents and methods. The vision of SNRC is to provide an integrated platform in which users can expand their research to areas outside their expertise or engage multiple modalities in their research, such as applying viral vector approaches and neuroimaging approaches to behavioral models of disease or human organoid cultures. SNRC outreach will approach Neuroscience departments nationally with a call for applications for 6 fully-funded merit-based pilot studies designed to engage different SNRC resources. We will also offer comprehensive workshops on techniques and teach participants how to apply and integrate novel approaches into their current research programs. SNRC is strategically equipped with resources to provide critical support to a range of national research projects and has supported over 500 labs nationwide with over 200 peer-reviewed publications in the last decade. SNRC has a growing national user base from institutions including Yale, Harvard, University of Missouri, Cornell, Princeton, Columbia, University of Pennsylvania, University of Texas, MIT, and many more. Investigators anywhere in the world can request a viral vector, phenotype rodent lines, or have an in vivo stroke study or an efficacy study in a model of neurodegenerative disease run remotely. Anyone can attend a workshop for training in behavioral models, 3D imaging of whole brains, or methods for 3D human cellular models (organoids and assembloids). SNRC supports many small and large biotech companies in proof of concept efficacy studies of clinical drug candidates. This contribution has supported the advancement of these projects to human clinical studies. Through SNRC, academic users will have access to these same industry-standard efficacy studies. All SNRC activities will be supervised by a steering committee consisting of external, internal, and NIH members. Under this U24 grant, we will disseminate essential and cutting-edge resources. We will expand our external user network to share emerging technologies with the Pilot Study program and Annual Workshops. BFNL will expand its automated testing and data processing capabilities, including the Digilab cloud-based automated behavioral phenotyping system. GVVC will set up large-scale viral production as well as higher-level purification technology. NMS will include training classes in STARmap genomic imaging and array tomography proteomic imaging. Under this program, SNRC will engage with the national neuroscience community via newly improved resource sharing websites, hands-on instruction, and annual in-person or online workshops to facilitate networks for collaboration and acceleration of discoveries in brain function and pathology.

NIH Research Projects · FY 2026 · 2022-06

PROJECT SUMMARY/ABSTRACT This proposal for a Midcareer Investigator Award in Patient-Oriented Research (K24) will support the research program of Dr. Manjula Kurella Tamura, a nephrologist at Stanford University and Director of the Veterans Affairs Palo Alto Geriatric Research and Education Clinical Center. The candidate leads a multi-disciplinary research program which is focused on patient-centered outcomes of dialysis treatment in older adults. Her research program, comprised of a health services component and an interventions component, has been supported by five federally funded awards during the past five years, and has produced an extensive portfolio of work to support hypothesis driven mentee research. During this time, the candidate’s research program has provided training opportunities for 13 junior investigators who have successfully obtained funding, published research in high-impact journals, and transitioned into academic positions. In this K24 application, her overarching goal is to grow and sustain this program by: (1) enhancing her skills as a research mentor by obtaining training in key areas, and (2) using her research as a platform to mentor trainees from a range of disciplines, and (3) extending her research to evaluate treatment trade-offs earlier in the course of kidney disease. Recent clinical trials demonstrate that intensive versus standard blood pressure targets reduce mortality and cardiovascular events, but at the expense of kidney function. The scientific goal of this application is to evaluate the comparative harms and benefits of intensive versus standard hypertension treatment and hypertension deprescribing on kidney end-points in two real world older adult cohorts. The secondary goal is to demonstrate the application of novel analytical approaches that extend causal effects from randomized trials to older and sicker populations. The candidate’s mentoring program will integrate resources from the breadth of training programs at Stanford and VA Palo Alto, with unique opportunities tailored to the career development of scientists in aging research.

NIH Research Projects · FY 2025 · 2022-06

The American healthcare system and care economy face growing demands from an aging population, raising important questions regarding the organization, delivery, and funding for services in these two sectors. Long-term services and supports (LTSS) include medical and personal care services for individuals requiring assistance with daily activities. Over the last two decades, Medicaid—which pays for more than half of all LTSS delivery—has shifted away from traditional fee-for-service (FFS) payment models toward managed care systems in which private insurers cover LTSS in exchange for capitated payments from the government. However, empirical evidence on the effects of Medicaid managed care on costs and patient health outcomes is mixed and focuses on relatively young and healthy populations. This project will advance knowledge on by measuring the impacts of the transition from FFS to managed care in LTSS among individuals who are dual-eligible for Medicaid and Medicare and aged 65 and above in two states: New York and Florida. For these beneficiaries, Medicaid pays for LTSS, while Medicare is the primary payer for other types of healthcare services, including hospitalizations, office visits with primary care providers (PCPs) and specialists, and emergency department (ED) visits. The analysis will use several administrative claims datasets covering years 2008-2019 to compare changes in outcomes of beneficiaries from before to after MLTSS was implemented in New York and Florida counties to those among beneficiaries in never-treated counties in two control states—Pennsylvania and California—over the same period. As outcomes, the project will study care in outpatient, inpatient, and ED settings, as well as mortality. Since this care is not covered by Medicaid, any changes in them can be understood as spillovers of the managed care model in Medicaid LTSS on other types of healthcare not included under that model. The project will also identify subgroups who are most impacted by the shift to MLTSS in Medicaid and examine the role of managed care plan features in health care utilization and outcomes. Results will help policymakers, healthcare organizations, providers, and patients to understand the implications of the MLTSS model in Medicaid on patient care and health.

NIH Research Projects · FY 2026 · 2022-06

Project Summary / Abstract Dengue, a potentially life-threatening disease, has increased 30-fold in the last 50 years. Predicting and mitigating arbovirus transmission in the highest risk regions is critical to addressing the increasing risk of arboviruses in the United States. Local transmission of dengue has been steadily increasing in Florida, Texas, and California in recent years. In the next several decades, half the United States may have habitat suitable for Aedes aegypti and Ae. albopictus, mosquitos which spread dengue, chikungunya, Zika, and yellow fever. The RISE Study is a separately funded cluster randomized control trial evaluating the benefits of upgrading local water infrastructure in urban settings. The RISE intervention is a prototype for future infrastructure upgrading. Although permanent infrastructure modifications have been recommended as an arbovirus control strategy, this type of intervention has never before been rigorously tested. RISE provides an important opportunity to evaluate whether this model decreases or inadvertently increases arbovirus transmission. In addition to evaluating a new paradigm for mitigating arbovirus transmission, RISE is an ideal platform to assess gaps in knowledge about risk factors for arbovirus transmission. My hypothesis is that modifiable risk factors drive arbovirus transmission in these communities. To test this hypothesis, I will leverage the RISE platform to study arbovirus risk factors and evaluate the impact of permanent infrastructure modifications on dengue transmission in urban settings. I will also create a mathematical model to simulate dengue transmission under a range of intervention scenarios. I have developed a customized career development plan that aligns with my proposed research. It incorporates both formal and informal training under the mentorship of Drs. LaBeaud and Luby. This training plan draws upon my existing expertise in public health, clinical medicine, and epidemiology; it will enhance my expertise in laboratory diagnostics, geospatial analysis, and mathematical modeling. The planned didactics and technical training included here will provide the foundation necessary to achieve my goal of becoming an academic physician focused on mitigating the spread of arboviruses.

NIH Research Projects · FY 2026 · 2022-06

PROJECT SUMMARY (30 lines) Translation is the endpoint of the central dogma and point of temporal and spatial regulation in gene expression. Biochemical, biophysical and structural methods have outlined the general steps of translation, providing a menu of key factors, structures of ribosomes and complexes, and kinetics for the essential steps of initiation, elongation and termination/recycling. Nonetheless, the mechanisms of key steps such as initiation, elongation and termination, and how they are regulated by RNA structures, modification or regulatory proteins remains unclear. A key challenge is that translation is highly dynamic, involving conformational and compositional changes throughout and following heterogeneous mechanistic pathways. During prior funding periods supported by the grants that we will merge in this MIRA, we have developed single- molecule approaches and reagents that observe translation in real time. We combine these dynamic methods with cryoEM structures to gain a temporal and detailed mechanistic view of the process. Our proposed research focuses on key areas translational control: how initiation is achieved in higher organisms—here the pathway by which a small (40S) ribosomal subunit is bound to a mRNA and recognizes a start—will be determined in both yeast and humans, and we will explore how mRNA structure, protein binding and modified nucleotides change the process. We will investigate how long-range RNA interaction between 5’ and 3’ ends of mRNAs may be critical for basal translation initiation and its control. In elongation, we will continue to explore recoding events and co-translational protein folding and develop methods to watch translation elongation in eukaryotic organisms. We will explore the role of ribosomal stalling/pausing and eventual shunting into ribosomal quality control pathways. Finally, we will understand the pathways by which correct stop codons are recognized and ribosomes recycled and determine how correct vs premature stop codons are distinguished in the nonsense mediated decay pathway. Our research leverages decades of reagent and methods development, and a wonderful group of collaborators to explore translational control, and its central linkage to human health and disease.

NIH Research Projects · FY 2026 · 2022-06

PROJECT SUMMARY Among the known risk factors for late-onset AD, age is considered the greatest. After age of 65, the risk of developing AD doubles every five years. While there is a consensus that late-onset AD mainly impacts the aging brain, the direct effects of aging on development and progression of AD have been mostly overlooked. In fact, the majority of human neuroimaging studies of AD consider age as a confounding factor when reporting the AD outcomes. Several age-related processes including inflammation, mitochondrial dysfunction, synaptic loss and vascular dysfunction may contribute to AD. These processes impact microstructural properties of gray and white matter such as neurite morphology years before they can be reliably detected using conventional MRI measures. They also impact network-level computations as brain reorganizes to compensate for these changes. A gap in knowledge is that brain regions that show most age-related changes in their microstructural organization may be more vulnerable to AD pathology. Advances in MRI techniques have provided us with the ability to probe microstructural organization of cortical and white matter such as neurite morphology in human in vivo. To bridge this gap and in response to the high-priority research topic PAR-19-070 (NOT-AG-18-051: understanding AD in the context of aging brain), we propose a multi-level study to examine microstructural (e.g., cortical neurite morphology) and connectome-level organizational properties of brain networks that are most affected in aging and may contribute to AD. We will pursue three Aims: (1) To examine microstructural properties of gray matter and white matter that are most vulnerable in aging and are most impacted by AD pathology. We will leverage Stanford ADRC PET-MR and deep phenotyping resources and will collect novel, quantitative MRI markers of brain microstructure including measures of neurite morphology and macromolecular tissue volume (MTV) in 120 older adults who have a clinical consensus diagnosis of either cognitively normal controls (HC) or mild cognitive impairment (MCI), and will be confirmed to be Aβ- or Aβ+ with PET; (2) To examine the interaction of aging and AD on organizational properties of human connectome. We will leverage ADNI neuroimaging data to achieve this goal and will validate the findings using an independent dataset, namely the Stanford ADRC dataset; (3) To characterize the trajectory of changes in organizational properties of brain networks in normal aging and during transition to AD phenotypes. Leveraging ADNI longitudinal data, we will apply connectomic analysis, accelerated longitudinal design with mixed effect modelling to model the trajectory of organizational changes of brain networks in normal aging and test the alterations of trajectories at different stages of AD. Successful completion of this study will significantly improve our understanding of AD in the context of aging and will inform development of novel therapeutics of AD targeting aging mechanisms.

NIH Research Projects · FY 2026 · 2022-06

PROJECT SUMMARY/ABSTRACT The innate immunity is well-controlled to respond to pathogenic infection in a timely and sensitive manner, while tolerating “self” molecules in the cell. Defects in the regulation of innate immunity result in various disorders, such as autoimmune diseases or heightened vulnerability to infections. Previous studies by us and others re- vealed ADAR1, an RNA editing enzyme that catalyzes Adenosine to Inosine (A-to-I) editing on dsRNAs, as a key player in the regulation of innate immune response to double-stranded RNAs (dsRNAs). ADAR1 RNA editing and binding activities have been shown to prevent endogenous (“self”) dsRNAs from activating the cytosolic dsRNA sensors MDA5 and PKR, but the underlying molecular mechanisms are not well understood. In addition, the cytoplasmic editing of at least some dsRNAs by the ADAR1 p150 isoform is crucial to suppress the dsRNA- mediated autoimmunity, although the ADAR1 p110 isoform in the nucleus is generally a lot more abundant. How are these dsRNAs edited in the cytoplasm but not in the nucleus? In this MIRA application, we focus on two projects to address these knowledge gaps. First, we will elucidate the interplay between ADAR1 and other players in the dsRNA innate immunity pathways. Specifically, we will inves- tigate the mechanisms by which ADAR1 regulates the MDA5 and PKR pathways of dsRNA sensing. We propose that ADAR1 regulates dsRNA-mediated innate immunity in both RNA editing-dependent and -independent fash- ion. We will study how these two modes of action operate in vitro and test their in vivo implications in mouse models. Second, we will uncover the regulatory mechanisms for cytoplasmic vs. nuclear editing. Specifically, we will perform genetic screens and biochemical assays to identify and characterize the factors responsible for spatial differences in editing. Taken together, these innovative studies will provide a deep understanding of the molecular mechanisms operating at the interface of dsRNA editing and dsRNA sensing in innate immunity.

NIH Research Projects · FY 2025 · 2022-06

The overarching goal of this work is to improve treatments of medication-resistant neuropsychiatric diseases with repetitive transcranial stimulation (rTMS) by tailoring the target to an individual's brain networks. We are indeed in critical need of these individualized treatments for mental health disorders, which affect nearly 50% of Americans during our lifetimes, and brain stimulation treatments, including rTMS represent innovative approaches for these patients. To alleviate depression, rTMS attempts to target a region of the prefrontal cortex generally located within the central executive network (CEN), which drives decision making, cognitive control, and is critically impaired in depression. However, rTMS is delivered without targeting an individual's CEN, and as such may inadvertently deliver stimulation outside the CEN. This application is motivated by recent developments in the field, including a large-scale whole-brain connectivity database derived from invasive recordings and the demonstration that rTMS in depressed patients induces brain changes that predict clinical improvement. In this proposal, we combine non- invasive TMS studies in healthy subjects and depressed patients with invasive direct stimulation studies from surgical patients. We test the hypothesis that the CEN connectivity is weakened in depression and can be maximally modulated by individualizing localization. The project consists of three aims: (1) investigate the excitability, connectivity, and neuronal properties within the CEN using direct brain recordings in surgical patients with epilepsy; (2) derive accurate TMS tools to measure CEN connectivity non-invasively in healthy and depressed populations; and (3) in a depressed population characterize inter-individual variability within the CEN and prospectively test if localization with TMS at the individual level more effectively modulates this brain network. This approach, which can be generalized to any brain region and disorder, utilizes a large database of direct brain recordings to map a brain network at an unparalleled level of detail, develops a link to direct brain recordings in order to yield validated non-invasive brain measures, and applies these insights to individually localize the network and improve targeted brain stimulation. Scientific outcomes include: (1) the first causal, functional map of the human CEN from direct brain recordings; (2) novel non-invasive brain measures of connectivity grounded in electrophysiology; (3) causal brain signatures of depression in the CEN; (4) a methodology to target an individual's CEN in the clinic; and (5) improved modulation of the CEN using this methodology. In summary, a successful outcome of the proposed work would yield an algorithm and guidelines for personalized TMS targeting based on fully validated brain signatures in depression. RELEVANCE (See instructions): Brain stimulation for depression targets the central executive network (CEN), involved in decision making and cognitive control, core in depression, and difficult to target in the clinic. Here we propose to study the connectivity of the CEN using a combination of invasive and non-invasive brain recordings; we will 1) investigate CEN connectivity from direct brain recordings, 2) derive accurate and causal tools to measure CEN connectivity non- invasively in healthy and depressed populations, and 3) test if CEN localization at the individual level can more effectively modulate this network. A successful outcome of the proposed work would yield an algorithm and guidelines for personalized TMS targeting based on fully validated brain signatures in depression.

NIH Research Projects · FY 2026 · 2022-06

PROJECT SUMMARY Accumulating neuropathological and animal studies suggest that AD pathology impacts brain microstructure years before clinical manifestation of the disease. Various processes involved including alterations in dendritic arborization and spines, neurite morphology, synaptic density, and axonal transport and packing. Until recently, the evaluation of these microstructural properties and their association with AD pathology has been mainly limited to postmortem tissue. Recent advances in MRI techniques have provided us with the ability to measure cortical and white matter microstructural properties such as neurite morphology and macromolecular tissue content in human in vivo. In the proposed study, we will employ a set of advanced quantitative MRI sequences and analytical approaches to measure changes in cortical and white matter neurite morphology and macromolecular content in preclinical AD and will examine their association with cognitive outcomes, and amyloid and tau pathology measured by PET. We have recently demonstrated the utility of these measures in detecting alterations in cortical and white matter neurite and macromolecular content in a sample of healthy older adults and patients with amnestic mild cognitive impairment. We have also tested the association between these measures and AD pathology in a small sample of older adults with confirmed AD pathology. Teaming up with experts in early AD characterization and AD pathology and leveraging Stanford ADRC PET- MR and deep phenotyping resources, we will study the following aims on a sample of 120 older adults who have a clinical consensus diagnosis of either cognitively normal controls (HC) or mild cognitive impairment (MCI), and will be confirmed to be Aβ- or Aβ+ based on ADRC amyloid PET data. We will examine cross- sectional and longitudinal changes in cortical microstructural properties including neurite density (NDI) and orientation dispersion index (ODI) (Aim 1), and in white matter microstructural and macromolecular tissue properties including NDI, ODI and macromolecular tissue volume (MTV) (Aim 2), along with their association with cognitive outcomes and AD pathology identified by PET. Taking a network-neuroscience approach, we will also examine connectome-level microstructural changes in preclinical AD and will test the utility of a multi-layer network framework for integrating measures across modalities (microstructural, molecular, PET, cognition) to capture the heterogeneity of AD. The proposed systematic investigation of microstructural and molecular changes in cortical and white matter in preclinical AD and their association with AD pathology and cognitive outcomes in a well-characterized preclinical AD sample can provide unique insight regarding AD development in early stages of the disease and can significantly improve our mechanistic understanding of AD. The outcomes also have the potential to inform development of experimental treatments, monitoring their effectiveness, and predicting cognitive and clinical trajectories of preclinical AD patients.

NIH Research Projects · FY 2026 · 2022-06

ABSTRACT The larynx requires protection from the ~25 million inhaled insults encountered daily during fulfillment of its normal functions including breathing, coughing, swallowing, and in humans, voice production. An epithelium forms a critical first protective barrier on the surface of the larynx. Under normal conditions, the epithelium relies on homeostatic regenerative mechanisms. The basal cell (BC) layer of the epithelium is believed to represent a reservoir of progenitor cells for the formation and regeneration of differentiated epithelium. However, pathological changes, or remodeling, occurs in the composition and organization of the laryngeal epithelium in response to inhaled insults, notably cigarette smoke (CS). Remodeling affects the ability of the epithelium to function as an effective barrier and predisposes the tissue to disease development. Despite the prevalence and likely importance of epithelial remodeling in CS-induced laryngeal disease, its etiology is poorly understood. This is due to a lack of basic knowledge of the mechanisms which dictate laryngeal epithelial homeostatic regeneration and permanent tissue remodeling linked to CS. Specifically, little is known about the biology of the BC population in normal epithelial homeostasis, injured, or diseased conditions. A paucity of research on laryngeal BC biology serves as a major barrier in the development of therapies to prevent and treat CS-diseased vocal folds. To address this unmet need, we propose to test the central hypothesis that BC are critical to the formation and maintenance of normal laryngeal epithelium and CS-induced alterations in BC biology are associated with epithelial remodeling and human disease development. We will test this hypothesis using a normal mouse model (AIM 1) and in vivo and in vitro models of CS exposure (AIM 2) to study laryngeal BC properties in differentiated epithelium, primary culture, and physiologically relevant three-dimensional epithelial cell culture systems. We also propose to evaluate how our in vivo and in vitro findings in mice relate to the human condition by evaluating the biology of BC in human laryngeal specimens from patients with Reinke’s edema, a common CS-induced laryngeal disease (AIM 3). Completion of these aims will demonstrate that BC have a central and irreplaceable role in laryngeal epithelial biology- they function as progenitor cells for normal epithelium and alterations in BC biology are implicated in disease development. Findings will have significant theoretical and clinical impact and will provide novel new insights into the mechanism underlying laryngeal and vocal fold epithelial regeneration. Targeting specific biologic pathways that mediate CS-induced derangements in BC biology may represent innovative therapeutic targets to prevent development and progression of CS- and other smoke-mediated voice disorders.

NIH Research Projects · FY 2025 · 2022-05

Project Summary Despite a great deal of research, we have discovered surprisingly little about the genetic basis of uniquely human traits—largely due to the ethical and practical considerations that severely limit comparisons between humans and other primates. To advance this field, we have integrated two effective approaches for studying evolution: induced pluripotent stem (iPS) cells, and interspecific hybrids. iPS cells can be differentiated into a wide range of cell types in vitro, circumventing many limitations of primate research, while measurement of allele-specific gene expression in hybrids allows cis-regulatory divergence and gene expression adaptations to be mapped genome-wide. To combine these approaches, we have recently generated human/chimpanzee hybrid iPS cells. We propose to characterize this powerful resource with RNA-seq and cellular phenotyping in diverse cell types, including cardiomyocytes, motor neurons, hepatocytes, pancreatic progenitors, skeletal muscle, retinal pigmented epithelium, and skin organoids that include dermis/epidermis, adipose, cartilage, hair follicles, and more. Our goal is to discover and experimentally validate genes and genetic variants that have contributed to the evolutionary origin of our species.

NIH Research Projects · FY 2025 · 2022-05

PROJECT ABSTRACT Unhealthy diet and obesity are major causes of cardiovascular disease (CVD). Emerging adults (ages 18-25) are a crucial group to target with CVD prevention interventions because they have lower dietary quality and experience more rapid weight gain than adults in middle and older adulthood. Moreover, emerging adulthood is distinct developmental period during which lifelong eating behaviors and CVD risk trajectories are largely established. Communication interventions, particularly those appealing to emerging adults’ strong interest in both environmental sustainability and personal health, are a promising but understudied strategy for addressing unhealthy diet in this age group. The goal of the proposed research is to design and rigorously evaluate a communication intervention to reduce dietary risk factors for CVD among emerging adults. The first aim is to identify specific dietary substitutions that emerging adults can readily make to reduce their CVD risk and dietary environmental harms. To identify these substitutions, I will analyze dietary intake data from the National Health and Nutrition Examination Surveys linked to a comprehensive database of foods’ greenhouse gas emissions. The second aim is to develop and optimize health and environmental messages about these dietary substitutions. I will develop candidate messages, pre-test them in qualitative focus groups, then use a randomized factorial experiment with 800 emerging adults to identify the most effective message strategies. The third aim is to evaluate the impact of the messaging interventions on healthfulness of food purchases. In a longitudinal randomized controlled trial, I will assign 500 emerging adults to 1 of 4 conditions: control (no messages), health, environmental, or health + environmental messages. Participants will simulate five weekly shopping trips in an online grocery store with their assigned messages prominently displayed. I will evaluate each messaging interventions’ initial, sustained, and overall impacts on purchase healthfulness and identify the most effective type of message. This research will further NHLBI’s strategic goal of preventing CVD and NIH Nutrition Research Objective 2-6 to leverage behavioral science to initiate and sustain healthy eating. Further, this award will help me achieve my long-term career goal of becoming an independent investigator focused on effective, scalable CVD prevention interventions for emerging adults. With support from this K01, I will build on my expertise in nutrition policy to fill critical training gaps in: 1) the CVD and environmental impacts of food, 2) communication interventions for emerging adults, 3) mixed methods, and 4) advanced analytic techniques for longitudinal studies. My detailed training plan includes tutorials with my interdisciplinary mentorship team at the Harvard TH Chan School of Public Health, formal coursework, hands-on research activities, and participation in conferences, workshops, and seminars. The K01 will provide me with the expertise and preliminary data needed to become an independent researcher successfully competing for R01 funding in this area.

NIH Research Projects · FY 2026 · 2022-05

A central function of the brain is to create internal representations of stimuli and experiences from the outside world to guide behavior. Here, we examine the circuit mechanisms underlying the neural representation of external space, a representation essential to spatial memory and navigation, and impacted by neurodegenerative and psychiatric diseases. The neural basis for the representation of space depends, in part, on circuits in the medial entorhinal cortex (MEC), which contains neurons that encode the spatial position, orientation and running speed of an animal. Between distinct environments, the firing fields of position and orientation cells can change their firing rate and rotate or move to a new spatial location – phenomenon known as ‘remapping’. Together with other structures in the parahippocampal region, MEC neurons can generate unique neural representations for distinct environments, potentially contributing to the encoding of different contexts or episodes. While remapping in MEC has often been studied between environments that differ in sensory features (i.e. visual or odor cues), we have found in recent and preliminary data that behavioral variables (i.e. running speed, expectation of reward) can evoke internal transitions between neural population states (i.e. remapping) in MEC. Here, we aim to test the hypotheses that a change in behavioral variables can drive transitions in MEC neural population states via key nodes in entorhinal circuitry (Aim 1) and that behaviorally driven MEC spatial maps are optimized to represent features relevant to the navigational behavior executed in the environment (Aim 3). Moreover, we aim to establish causality between changes in behavioral variables and transitions in MEC neural population states (Aim 2). To address these aims, we propose to combine electrophysiology using silicon probes with spatial and memory tasks in behaving mice. Until now, electrophysiological approaches had to contend with limited recording channel counts, contributing to a lack of studies that considered MEC neural coding at the population level or as a function of behavioral variables. However, new versions of silicon probes have allowed us to record hundreds of MEC neurons simultaneously along nearly the entire length of mouse entorhinal cortex. This, combined with virtual reality tasks that can provide dense sampling of sensory and behavioral variables, as well as optogenetic perturbations to establish causality between changes in behavioral variables and transitions in MEC neural population states, will enable us to achieve significant new insight into the mechanisms underlying transitions in MEC neural population states and the of such transitions in supporting memory and navigation.

NIH Research Projects · FY 2026 · 2022-05

PROJECT SUMMARY: Mammalian tissues engage in specialized physiology that is regulated through reversible modification of protein cysteine residues by reactive oxygen species (ROS). Despite the longstanding links between ROS dysregulation and aging, technological limitations have resulted in a persistent absence of information on the exact protein cysteines are modified by ROS that explain the molecular basis for this dysfunction in vivo. Using the cysteine-phospho tag (CPT) proteomics technology that I developed, I have determined that a fundamental remodeling of protein cysteine oxidation networks occurs with caloric restriction (CR) in aging. Building on this, I will determine the functional role of redox regulation of newfound protein networks that are linked to the lifespan and healthspan benefits of CR in aging. I have also extended Oximouse to diversity outbred (DO) mouse populations to recapitulate the genetic diversity of human population, in search for redox signaling targets that have high translational potential. Preliminary data from this effort has identified conserved redox signaling targets on proteins that may have critical implications in age-dependent decline of thermogenesis leading to age-related obesity. I will study metabolic redox signaling nodes underlying longevity- modifying interventions and delineate the mechanisms through which these targets are redox-regulated with age that lead to a decline in thermogenic activity. The proteomics data will provide a rich resource for the community to explore ROS and aging. The mechanistic studies will validate redox signaling nodes that can potentially be manipulated to extend lifespan and healthspan, in line with the mission of the National Institute of Aging. Objectives: (1) Defining mitochondrial cysteine oxidation mechanisms underlying the health benefits of CR. (2) Determining adipose metabolic redox signaling nodes underlying longevity-modifying interventions. (3) Investigating the mechanisms of redox control in age-related obesity. The first two objectives will be completed during the K99 phase, and the last objective will be carried out during the R00 phase. This work builds on a redox proteomics technology that I developed, which quantifies absolute cysteine redox modification stoichiometry at orders of magnitude deeper proteome coverage than previous methods. From this big data, I will mechanistically validate individual redox signaling nodes that have important roles in metabolism and longevity. I will be mentored by Drs. Chouchani and Gygi, who are experts in the fields of ROS biology, metabolism, animal physiology, and mass spectrometry (MS)-based proteomics. I will additionally learn from my collaborators/consultants, Drs. Mair, Gladyshev, Banks, Gupta, and Spiegelman, who have extensive expertise in aging, animal physiology, and metabolism. The rich scientific environment at DFCI and HMS adds fuel to my enthusiasm to establish myself as an independent investigator. My unique skillset will allow me to develop novel technologies to study the biology of aging in a “big-data” driven manner, then select targets for mechanistic validation to provide insights for future translational therapeutic development.

NIH Research Projects · FY 2025 · 2022-05

Project Summary Extracellular matrix (ECM) is the most abundant biomaterial in the body. During cardiac development, the ECM plays critical roles in the formation of shapes and patterns of the heart such as chambers and trabeculae through elaborate interactions with differentiating cells. Although problems in ECM-cell interactions can lead to heart diseases, signaling pathways activated by the specific ECM components are still poorly understood. We recently succeeded in developing human induced pluripotent stem cell-derived cardiac organoids (iPSC-COs) that can recapitulate cardiogenesis. In this multi-PI R01 proposal, our team will further elucidate the mechanisms of ECM- cell interactions that influence cardiac differentiation and morphogenesis. We will apply machine learning and novel iPSC double reporter lines (Tbx5-Clover2-Nkx2.5-TagRFP) to elucidate the effect of cell composition on morphogenesis of iPSC-COs (Aim 1). Afterwards, we will screen 36 different combinations of ECM compositions that can reliably induce iPSC-CO formation using 8 additional iPSC lines for validation (Aim 2). By rigorously analyzing iPSC-COs made with optimized ECM using elastic property measurement and single-cell multiomics, we will elucidate the biological and physical effects associated with ECM signaling and mechanotransduction at single-cell resolution (Aim 3). In summary, understanding the exact role and mechanism of ECM-cell interactions may contribute to finding new biomaterials or therapeutic modalities for treatment of heart diseases.

NIH Research Projects · FY 2025 · 2022-05

Project Summary/Abstract We propose the clinical translation and validation of an innovative “radiofrequency (RF) penetrable” dedicated positron emission tomography (PET) insert technology that can be placed within any stand- alone magnetic resonance imaging (MRI) system for acquiring simultaneous PET/MRI data. For this proposal the Stanford team will work with industry partner “PETcoil” to address technical developments required for translational studies, ensure industry level standardization of end user software and technology, and acquire first in-patient simultaneous PET/MRI data using this novel PET insert. PET/MRI exhibits some attractive features. First, combined PET/MRI is uniquely capable of providing excellent anatomical soft tissue contrast and multi-parameter information in a single a scan and, as a result, PET/MR is now commonly used for characterizing disease in regions such as the brain, head and neck, breast, liver and pelvis. Second, MRI does not introduce ionization radiation in a PET/MR study. This significant reduction of radiation dose makes PET/MRI an attractive modality for pediatric patients and those requiring recurring PET studies. Third, PET/MR imaging can occur simultaneously, unlike sequential PET/CT, resulting in temporal in addition to spatial correlation of PET with MR data. Despite these attractive features, the adoption of PET/MRI has been slow since its introduction in 2011. One main reason for this slow adoption is the high cost of procuring an integrated PET/MRI system, which is about $5M for the machine and another $1.5–2M for required room renovations to host the machine. The resulting cost (~$6-7M) is simply not affordable for most institutions. Furthermore, the permanently integrated PET/MR system designs offered by vendors such as GE and Siemens yield sub-optimal spatial resolution and sensitivity performance for the PET system component, especially for neurological imaging applications. The proposed brain-dedicated PET ring offers higher photon sensitivity and spatial resolution, and can be inserted into any existing MR system; thus a user only needs to procure the insert, and MR system modifications or room renovations are not required, reducing the entry costs roughly 10- fold. We have realized a 1st generation brain dedicated PET insert for simultaneous PET/MR and are completing a 2nd generation version, both with a spatial resolution of 2.7x2.7x2.7 mm3 and the latter achieving a photon sensitivity of >6%. In addition, this insert approach is “RF penetrable,” an important and novel concept enabling collection of PET/MR data using the MR system’s built-in body coil for RF transmission through the PET ring insert into the patient, and only a RF receiver coil resides inside the insert, thus facilitating the lower cost insert concept for achieving PET/MR. We will translate and validate the 2nd generation brain PET insert and work with our industry partner to standardize our data processing workflow. If successful, this project will enable more widespread dissemination/accessibility of PET/MRI.

NIH Research Projects · FY 2025 · 2022-05

During alveolarization, the final stage of lung development, angiogenesis drives the exponential, postnatal increase in gas-exchange surface area. Pericytes play a dual role in angiogenesis. Initially, pericytes stimulate and guide endothelial cells (EC) during early microvascular growth and subsequently constrain EC proliferation and migration during vessel stabilization. However, the molecular mechanisms that regulate pericyte phenotype to drive these distinct roles in vascular growth and stability remain poorly defined. Addressing this gap may motivate the development of therapies to treat neonatal lung diseases marked by compromised angiogenesis, including bronchopulmonary dysplasia. O2-sensitive transcription factors, termed hypoxia-inducible factors (HIF) are central regulators of angiogenesis. Our preliminary data suggest that HIF activity in select subsets of lung mesenchymal cells (MC) is required for postnatal angiogenesis and alveolarization. Genetic gain- and loss-of- function studies using Tagln promoter driven Cre-recombinase (a gene expressed by multiple MC including pericytes), demonstrated that Tagln-specific HIF stabilization preserved pulmonary vascular and alveolar growth in hyperoxia. Conversely, Tagln-specific Hif-1a deletion impaired pulmonary angiogenesis and alveolarization even in normoxia. However, the specific Tagln-expressing MC responsible was not identified. Our single cell transcriptomic studies point to a unique, hyperoxia-sensitive, developmental role for pericytes and HIF signaling in pericytes during postnatal lung development. These studies identified: (i) marked changes in the transcriptome of early (P7) versus late (P21) pericytes with blood vessel morphogenesis as the most enriched biologic pathway; (ii) a peak in both proliferating pericytes and microvascular EC at P7; (iii) persistent Hif-1a, -2a, and HIF downstream target expression in pericytes, including Rgs5, a gene that marks activated, angiogenic pericytes, and Lgals1, a gene encoding a secreted, pro-angiogenic, carbohydrate-binding protein; and (iv) hyperoxia-induced loss of ~90% of pericytes, all proliferating pericytes, and suppressed HIF-dependent, pericyte-EC interactions. These observations suggest the overall working hypothesis that HIF-mediated alterations in pericyte phenotype during postnatal development modulate the pulmonary angiogenesis that drives alveolarization. that will be tested in 3 specific aims. Aim 1 will use genetic mouse models, primary pericyte cultures, and ChIP-Seq to define the developmental role of HIF in pericytes on lung vascular growth. Aim 2 will use primary pericyte and EC co-cultures and loss of function strategies to determine if developmental regulation of select HIF-regulated targets in lung pericytes modulate pericyte phenotype and EC angiogenic function. Aim 3 will use HIF reporter mice, deep scRNA-Seq and genetic lineage tracing to determine if hyperoxia suppresses pericyte HIF-signaling, and disrupts pericytes fate and ontogeny during late lung development. By focusing on the lung pericyte, at single cell resolution, these studies will provide insight into pulmonary vascular development and identify strategies to promote lung growth and regeneration.

NIH Research Projects · FY 2026 · 2022-05

Project summary Iron enzymes play major roles in O2 activation in biology. These divide into four classes based on their active site structures that reflect their mode of O2 activation: the non-cofactor dependent mononuclear non-heme iron (MNHFe) enzymes, the cofactor (α-ketoglutarate (α-KG) and pterin) dependent MNHFe enzymes, the binuclear NHFe enzymes and the O2/H2O2 activating heme enzymes. Crystal structures and oxygen reaction intermediates exist for metalloenzymes in all four classes. Over the years, we have developed new spectroscopic methods enabling the detailed study of the NHFeII active sites, and the geometric and electronic structures of their O2 intermediates and have now developed a method to quantitatively study the iron center in the highly covalent and chromophoric heme environment. Among our accomplishments in the past 5 years are: 1) determined that FeIII-O2- species are the reactive intermediates in all the subclasses of non-cofactor dependent MNHFe enzymes; 2) defined the O2 reaction coordinates to generate the FeIV=O intermediates in both the α-KG and pterin dependent enzymes; 3) for the α-KG dependent subclass, defined the geometric and electronic structures of their FeIV=O enzyme intermediates and how these direct halogenation over the thermodynamically favored hydroxylation in the halogenases; 4) showed that in contrast to the MNHFe enzymes, hydroperoxide intermediates are active in the binuclear NHFe enzymes for direct reaction with substrates; 5) for methane monooxygenase, where the peroxo-biferric intermediate rapidly converts to a high-valent 2FeIV-oxo intermediate Q, we have determined the structure of Q (a topic of current debate) and provided insight into its high reactivity with methane; 6) used the spectroscopic method we have now developed for iron in heme environments to determine experimentally the computationally controversial electronic structure of oxyhemoglobin; 7) and extended this method to analyze active sites with strong Fe-oxo bonds. Our studies are now directed toward completing the reaction coordinates of the four classes and their subclasses, understanding O2 activation at the superoxo, peroxo and FeIV-oxo levels, determining the role of the second iron in the enhanced reactivity of the binuclear NHFe enzymes, and understanding the differences in the activation and selectivity of high-valent iron-oxo intermediates in mononuclear NH, binuclear NH and heme enzyme active sites.

NIH Research Projects · FY 2025 · 2022-05

PROJECT SUMMARY While chimeric antigen receptor T cells (CAR-Ts) have provided impressive responses in hematologic malignancies, children and young adults with metastatic or relapsed solid tumors have not yet benefited from CAR-Ts and continue to suffer dismal outcomes. A major barrier to CAR-T efficacy in solid tumors is inadequate CAR-T expansion, driven in part by CAR-T exhaustion and poor memory potential. Preclinically, CAR-T exhaustion results from excessive CAR signaling, and can be rescued by eliminating the CD28 T cell costimulatory domain from CAR design. Clinically, in samples from general pediatric oncology patients, poor memory potential in T cells is associated with chemotherapy exposure. Preclinical models further suggest that CAR-T exhaustion can be reduced by overexpressing a transcription factor, cJun, and that memory potential can be enhanced by exposing T cells to a drug, Ibrutinib. Based on these observations, Dr. Ramakrishna will apply novel single-cell and multi-dimensional technologies to CAR-T patient samples to assess the impact of CAR costimulatory domain or pre-apheresis chemotherapy exposure on CAR-T exhaustion and memory potential and ultimately on patient CAR-T fitness, defined as CAR-T molecular signature paired with functionality. To accomplish her aims, Dr. Ramakrishna will innovatively compare CAR-T samples across three GD2 CAR-T clinical trials. In Aim 1, with training in multi-dimensional data analysis, Dr. Ramakrishna will integrate phenotypic (CyTOF), epigenetic (ATACseq), and transcriptomic (RNAseq) molecular signature with CAR-T functional assessments to determine whether GD2.Ox40.CD28.z CAR-Ts (NCT02107963) confer exhaustion, thereby affecting CAR-T fitness, as compared to GD2.41BB.z CAR-Ts (NCT04539366) in osteosarcoma patients. In Aim 2, with training on cancer immune biology, Dr. Ramakrishna will use CyTOF, ATACseq, and in vitro cytokine production, to test the hypothesis that apheresis and CAR-T products from chemotherapy-naïve patients (diffuse midline glioma; NCT04196413) have improved CAR-T fitness as compared to those from chemotherapy-treated patients (osteosarcoma; NCT04539366), followed by single-cell RNAseq to track persistent CAR-T transcriptional profiles in patients. In Aim 3, with training in immune regulation, Dr. Ramakrishna will evaluate whether CAR-T fitness in chemotherapy-treated patient aphereses can be enhanced through modulating molecular pathways by cJun or Ibrutinib. To build upon her substantial prior CAR-T research and clinical experience, Dr. Ramakrishna has developed a strong training plan and mentorship team, including her primary mentor, Dr. Crystal Mackall, a pioneer in translational immunotherapy research; co-mentor, Dr. Sean Bendall, an innovator in multi-dimensional immune assays; advisory committee, Dr. David Miklos, Dr. Holden Maecker, and Dr. Michelle Monje; and collaborators, Dr. Rosie Kaplan and Dr. Steven Feldman. In completing her proposed plan with this team, Dr. Ramakrishna will be prepared to compete for R01 funding and to launch a translational research program identifying and overcoming CAR-T limitations for pediatric solid tumors patients.