Stanford University

NIH Research Projects · FY 2025 · 2024-08

PROJECT SUMMARY: Cardiovascular disease is a leading cause of death, and mitochondrial dysfunction is implicated in the pathogenesis of cardiomyopathy. Cardiac troponin I (cTnI) is a regulator of myocyte contraction, and mutations in cTnI lead to hypertrophic, dilated, and restrictive cardiomyopathies and sudden death. It is not known why cTnI mutations have such heterogeneous phenotypes, and there are no targeted therapies for cardiomyopathies caused by cTnI mutations. cTnI is regulated by phosphorylation and proteolytic truncation. We recently showed that selectively inhibiting phosphorylation of cTnI by delta protein kinase C (δPKC) during myocardial infarction using a lab-designed peptide inhibitor attenuates cardiac injury and prevents mitochondrial dysfunction. My preliminary data show a novel role of cTnI in inhibiting mitochondrial function, and a therapeutic benefit of preventing cTnI’s binding to mitochondrial ATP synthase using a peptide inhibitor in ischemic injury. The objective of this application is to identify the mechanisms by which cTnI inhibits mitochondrial function and to define the interplay between cTnI mutations and mitochondrial dysfunction in genetic cardiomyopathies. My central hypothesis is that cTnI phosphorylation and truncation directly inhibit mitochondrial function, and mutations in cTnI impair mitochondrial function to cause cardiomyopathy. This hypothesis will be tested in two specific aims: 1) Determine the effect of cTnI phosphorylation and truncation on mitochondrial function and 2) determine the effect of pathogenic cTnI mutations on mitochondrial function. In Aim 1, I will test the effect of recombinant cTnI with phospho-mimetic amino acid substitutions and N-terminal truncation on ATP synthase binding/activity and mitochondrial respiration. I will also express phospho-mimetic cTnI and N-terminal truncated cTnI in human induced pluripotent stem cell-derived cardiomyocytes (hiPSC-CM) to examine their effects on mitochondrial structure/function and myocyte contractility/relaxation kinetics. In Aim 2, I will use hiPSC-CM and transgenic mice with cTnI mutations to establish the effect of pathogenic mutations (causing hypertrophic, dilated and restrictive cardiomyopathy) on mitochondrial function and test the effect of lab-designed peptide inhibitors of cTnI phosphorylation and mitochondrial binding on mitochondrial function and contractility/relaxation in vivo. This research is expected to identify a novel and therapeutically targetable role of cTnI in inhibiting mitochondrial function and exacerbating myocardial remodeling in genetic cardiomyopathies. To successfully complete this project, Dr. Elezaby’s educational goals include training in 1) rational drug design; 2) hiPSC-CM biology; 3) genotype-specific mechanisms in genetic cardiomyopathies; 4) scientific communication; and 5) professional development. His mentorship team includes world-renowned experts in mitochondrial and stem cell biology, drug development, myocyte physiology, and cardiovascular genetics. His career development plan has been designed to ultimately achieve his long-term goal of becoming a leading clinician-scientist investigating the mechanistic underpinnings, therapeutic targets, and interplay between cardiac metabolism and cardiomyopathy.

NSF Awards · FY 2024 · 2024-08

Is there a way to reconcile gravity with quantum mechanics? It is well-known that quantum mechanics, the science of the very small, and gravitation do not integrate properly. Since the time of Newton, we have known that the force of gravity between two massive objects scales with the inverse of their distance squared. This law works well at planetary scales and for human scales. But we generally assume this "inverse-square law" to apply to much smaller distances, down to molecule scale, where quantum mechanics and gravity may work together. But, of course, this is a tremendous extrapolation that should be tested, at least in part, empirically. Indeed, many theories predict that gravity could deviate from the familiar inverse square law already at sub-millimeter distances. Such deviations are extremely difficult to measure experimentally due to the small strength of gravitation and the presence of residual electromagnetic interactions. This award funds the continuation of an experimental program in this area using an entirely novel technique. The team will train students in STEM research. The traditional technique to explore gravity at the meter to 0.1-millimeter scales relies on ever-improving versions of the classic Cavendish experiment, where the force of gravity is compared to the restoring force of a torsion fiber. More recent measurements have used devices obtained by photolithography but are still based on mechanical springs. This award supports an effort based on optical springs, taking advantage of the substantial progress in quantum optics and optomechanics in the last few decades. This is entirely new and holds the promise to revolutionize the field. Indeed, in addition to the primary goal, this new technique has already found applications in other fields of fundamental physics, and in technological areas as disparate as inertial guidance and vacuum measurement. 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 · 2024-08

Project Abstract Motivation: This is a successor application of our successful project, Rapid Robust Pediatric MRI, R01 EB009690. MRI offers superb soft tissue contrast for children, without the ionizing radiation and cancer risk of CT. However, MRI use has been limited due to long exams, low spatial resolution, and motion-artifacts. Thus, MRI often requires prolonged anesthesia with breath-holds and attendant risk; hence, children often are denied the benefits of cross-sectional imaging altogether or are exposed to ionizing radiation. The previous project addressed these concerns by creating a dedicated pediatric imaging system. Highly parallel, high-SNR 3T receive coil arrays were developed specifically for pediatric body imaging. The high SNR was used to accelerate scans reconstructed with parallel imaging, new motion correction algorithms, Compressed Sensing (CS), and higher-dimensional non-Cartesian scanning. This system is now being used extensively in clinical practice, significantly reducing anesthesia depth and duration, and has markedly increased our MRI utilization. Key technologies have been or are now being commercialized with GE Healthcare, including the pediatric receive array, CS, dynamic contrast enhancement, 4D flow, full-Fourier single-shot T2-weighted scanning, coil compres- sion, and Deep Learning (DL) based image reconstruction. Siemens has licensed 21 of our patents, implemented some of them in work-in-progress packages, and productized our coil compression and our ESPIRiT coil sensi- tivity estimation. Philips has licensed six of our patents. This ensures broad impact. Despite this significant progress a substantial number of exams still require anesthesia due to patient discomfort. This proposal focuses on one such common study, diagnosing Inflammatory Bowel Disease (IBD). Current MRI techniques require glucagon to stop bowel motion, and this produces pain, nausea, and vomiting. Intravenous gadolinium contrast is also required. Our goal in this project is to develop advanced MRI techniques which obviate the need for glucagon and IV gadolinium. This will allow more patients to be studied, eliminate anesthesia, and dramatically improve their MRI experience. The developed core technologies will impact other MRI exams as well. Approach: The project has three development aims, validated by a fourth aim of clinical studies. Aim 1 will enable fast dynamic 2D imaging at higher spatial and temporal resolutions. Aim 2 will develop free-breathing 3D contrast-enhanced imaging that can resolve moving bowel, eliminating the need for intravenous glucagon. Aim 3 will enable high resolution motion-robust non-contrast characterization of the bowel wall, eliminating the need for intravenous gadolinium. The impact of all of these developments will be assessed in children with IBD. Significance: This work will lead to fast, robust, broadly-applicable pediatric MRI protocols with less anesthe- sia, making MRI safer, cheaper, and more available to children. MRI will be transformed into a workhorse modality for IBD, improving their care and reducing CT radiation burden. The techniques will also facilitate wide application of MRI to new applications, for both pediatric and adult diseases.

NIH Research Projects · FY 2025 · 2024-08

Transcriptional elongation and mRNA processing occur simultaneously and are highly coupled to increase the efficiency and accuracy of mRNA maturation. Splicing is a step of mRNA processing where intronic regions are removed by spliceosome complexes that bind pre-mRNA. Most human genes with multiple exons are alternatively spliced generating numerous proteins with diverse functions derived from a single gene. Defects in RNA polymerase that alter the transcription elongation rate cause pervasive changes in alternative splicing. Mutations in transcriptional processing cause a variety of human diseases including retina degeneration, which is characterized by photoreceptor cell loss and visual dysfunction that can lead to blindness. Notably, the human retina harbors an astonishing splicing diversity and several retina-specific mRNA isoforms and ubiquitously expressed splicing factors are associated with retinal disease. Retinal photoreceptors, cones and rod cells, constitute over 70% of cells in the retina and initiate the transmission of visual stimuli to the brain by detecting light photons through a molecular pathway known as phototransduction. Many retinal mutations occur in phototransduction genes including rhodopsin, the only photopigment and highest expressed gene in rods. To date, the mechanisms that regulate the precise temporal and quantitative expression of rhodopsin and other phototransduction genes are poorly understood. My preliminary data suggest that the rod-specific transcription factor NRL physically interacts with splicing proteins. I hypothesize that qualitatively and quantitatively precise expression of phototransduction genes are controlled stringently by molecular interactions between the splicing and transcriptional machineries. In this proposal, genetic, biochemical and genomic approaches in combination with high throughput technologies, will be used to identify protein interactions between the transcriptional and splicing machineries. In addition, the role of these interactions will be studied in vitro and in vivo. Furthermore, genomic regions of phototransduction genes associated with RNA polymerase regulation and splicing factor binding will be identified. This grant will expose me to new technologies and computational analysis that will allow me to comprehensively study mechanisms of gene regulation and retinal homeostasis. Overall, this funding opportunity will help me become a well-rounded scientist and achieve research independence in the area of molecular genetics and vision research.

NSF Awards · FY 2024 · 2024-08

Thank you! This CAREER project advances the state-of-the-art in causal artificial intelligence (AI) methods (the blending of causal inference with machine learning and AI methods). Building causal AI systems is a complex pipeline of activities that requires eliciting assumptions from domain experts, developing estimation strategies, constructing uncertainty estimates, performing analysis to understand how robust the conclusions are, and conducting real-world experiments for validation. By automating key components of this causal analysis pipeline and developing robust data-driven estimation procedures, this project will enable more decision-makers to leverage causal AI systems. Integrating education and research, this CAREER project will develop open-source software tools, foster collaborations between academia and industry, and create educational materials, including coding tutorials, lecture notes, and textbooks. This research should also facilitate adoption by practitioners, educates young researchers in the field, and exposes students in K-12 education to foundations of the field. The project explores the following key research directions: i) precise finite sample analysis of estimation procedures for complex causal quantities, such as heterogeneous treatment effects and dose-response curves, in complex scenarios, ii) automated construction of confidence intervals for arbitrary causal quantities in high-dimensional settings, iii) model selection and hyperparameter tuning with rigorous guarantees for both estimation accuracy and uncertainty quantification in the causal setting, iv) aiding users in providing domain assumptions through the use of Large Language Models, v) developing algorithmic approaches for the automated identification of causal effects under parametric or semi-parametric restrictions on the data-generating process, vi) providing approaches for finite-sample sensitivity analysis that provide sharp bounds on parameters of interest, vii) addressing statistical problems related to adaptive data collection either to enhance accuracy or to correct uncertainty estimates. The ultimate goal is to provide accessible tools and educational resources that reduce the barriers to entry to applying causal AI in various domains. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NIH Research Projects · FY 2025 · 2024-08

PROJECT SUMMARY/ABSTRACT Immune checkpoint inhibitors (ICIs) are monoclonal antibodies used as novel cancer therapeutics to release intrinsic brakes on T-cell cytotoxicity against tumor cells. While effective to treat many advanced cancers, ICIs have been reported to cause fulminant myocarditis, pathologic inflammation of the heart—a life-threatening side effect which can lead to severe arrhythmias, heart failure and death. Although our group and others have previously found effector CD8+ T-cell clonal expansion and activation in the heart in ICI myocarditis, the contribution of macrophages with respect to their effect on T-cells has yet to be fully characterized. Using single- cell RNA-seq data collected as part of my funded K08, I have found an enrichment of CXCL9/10+ macrophages and CXCR3+ effector CD8+ T-cells in the hearts of MRL/Pdcd-1/- mice with myocarditis. Furthermore, depletion of macrophages in MRL-Pdcd1-/- mice reduces cardiac CD8+ T-cell infiltration and improves mice survival. Thus, I hypothesize that recruitment of CXCR3+ T-cells to the heart by CXCL9/CXCL10 expressing macrophages plays a pathogenic role in ICI myocarditis. To test this, I will utilize a novel pharmacologically treated mouse model of ICI myocarditis developed in my laboratory, along with high throughput immunophenotyping techniques and in vitro phenotyping. Aim 1 will investigate the effects of CXCR3+ blockade in our mouse model of ICI myocarditis, while Aim 2 will investigate the mechanistic effects of blocking CXCR3 and its ligands, CXCL9/10, on macrophage-mediated T-cell migration and function in an in vitro transwell system. This proposal has been carefully designed to be fully achievable within the timespan of two years of this proposal, while also having critical and high impact in the fields of ICI myocarditis and cardiac inflammation. By completing this project, I will define key pathogenic interactions between adaptive and innate immunity which drive ICI myocarditis, bridging a major knowledge gap in the role of macrophage effects on T-cell trafficking to the heart in myocarditis. In doing so, I hope to pave the way for the development of adjuvant therapies for treatment and prevention of ICI myocarditis. This grant will be instrumental in launching the next phase of my career and prepare me to successfully compete for R01 funding in the field of cardio-immunology and cardiac inflammation.

NIH Research Projects · FY 2025 · 2024-08

Modified Project Summary/Abstract Section Antiretroviral treatment (ART) for HIV infection effectively blocks viral replication, but fails to eradicate the virus, which can be a source of persistent inflammation. The pathways by which chronic, treated HIV infection drives inflammation are poorly defined, particularly in children and adolescents who acquire HIV perinatally. Perinatal HIV infection occurs in the context of a developing immune system, requires life-long treatment, and even with effective ART, treatment is associated with increased risks of metabolic, neurocognitive and cardiovascular complications that result from this HIV-induced inflammation. Thus, to understand the mechanisms driving inflammation in this vulnerable population that faces decades-long infection and treatment, we will study HIV- induced inflammation in samples previously biobanked (and stored in the US) from a unique cohort of perinatally infected adolescents who were maintained on ART and followed clinically from their first year of life. To complement these valuable clinical samples, we have developed organoids of human secondary lymphoid tissues, a major HIV reservoir site. The lymphoid organoids we are using are highly relevant to pediatric and adolescent infections as they are derived from pediatric/adolescent tissue, contain all major immune cell types, infectable with HIV, and are manipulable via gene editing, siRNA transfection, and antibody/small molecule inhibitors to probe mechanisms driving HIV-induced inflammation. Our goal is to use these unique resources to identify HIV-induced inflammatory networks in perinatally-infected adolescents on long-term ART and to define the viral factors that drive HIV-induced inflammation. We will make use of single cell techniques, which to date have only been applied to adult cohorts, to map the cell-intrinsic inflammatory networks induced during chronic treated HIV infection and define the viral genes that initiate these cascades. In addition, to fill a gap that has been missing in prior studies, we seek to understand how these rare infected cells initiate downstream cascades of inflammation that drive pathology by studying communication networks using methods we recently developed to infer cell-cell communication at the single cell level. This powerful combination of a long-term pediatric treatment cohort coupled with mechanistic studies in a robust ex vivo lymphoid culture system will provide a unique window into HIV-induced inflammation. Successful completion of this project will define mechanisms by which residual HIV RNA expression during treated infection drives inflammation in perinatally infected adolescents and establish models to test therapeutics.

NIH Research Projects · FY 2024 · 2024-08

PROJECT SUMMARY Stroke is the third leading cause of disability globally, and the number of incident strokes is expected to increase substantially as the size of the population aged 65 and older grows. After a stroke, some patients experience an accelerated decline in cognitive and functional ability, while disability stabilizes for other patients. However, little is known about why cognitive trajectories vary widely after stroke. One theory of cognitive aging is that a more complex living environment is potentially protective against cognitive decline by allowing for opportunities for exercise, recreation, and social activities. One way to measure individuals’ living environments is through studying their life-space, which is the size and pattern of the physical area in which they spend their time. Studies have found that life-space is associated with better cognitive function in older adults. However, there is a lack of research in identifying the mechanisms by which life-space is protective against cognitive decline post-stroke. We will leverage two studies to evaluate the relationship between life- space and long-term cognitive decline after stroke. Here, we propose a study that aims to (1) estimate the effects of components of life-space on cognitive decline in the years following stroke in a large observational cohort from the Cardiovascular Health Study (n=5,888), (2) characterize the life-space of stroke survivors using geolocation data in the StrokeCog cohort (n=270) and (3) prospectively evaluate the effect of components of life-space on cognitive change after stroke. Our findings will advance our understanding of factors that affect the long-term cognitive trajectory after ischemic stroke. This award will also support the career development of Sylvie Dobrota Lai, a doctoral student in the Department of Epidemiology and Population Health at the Stanford School of Medicine. Through completing the proposed research, the applicant will pursue training in (1) the epidemiology of aging, (2) clinical issues in stroke patients, (3) geospatial data collection and analysis, and (4) career development. The applicant will be supported by a mentorship team comprising of experts in aging epidemiology, statistics, and neurology. Through this fellowship, the applicant will develop strong methodological skills, gain subject expertise, and become a more independent epidemiologic researcher. The proposed study will provide a strong foundation for the applicant’s future academic research career and position her to become a leader in aging research.

NIH Research Projects · FY 2025 · 2024-08

Multiple sclerosis (MS) is a debilitating disorder that affects 2.8 million people worldwide. MS is characterized by loss of myelin, the structure surrounding nerves necessary for efficient communication between neurons and critical to neurodevelopment, maintenance, and plasticity. The severe symptoms that arise as MS progresses are exacerbated by the loss of oligodendrocytes—the myelin-producing cells—and impaired differentiation of their precursor, oligodendrocyte precursor cells (OPCs). To understand why remyelination fails in MS, we first need to comprehend the mechanisms driving the proliferation and differentiation of myelin-forming precursors. OPCs are the most abundantly mitotic cells in the brain and maintain strict, homeostatic boundaries, indicative of a precision in cell cycle control but also an ability to maintain elaborate tiling throughout the brain despite an ever-changing microenvironment. Oligodendroglia dynamics require the precise timing of transcription factors (TFs) expression, that is essential for efficiently remyelinating lesions. This suggests a large range in dynamic plasticity, a characteristic afforded to cells by the circadian (~24 hour) clock system, a transcriptional-translational negative feedback loop driven by the transcription factors BMAL1 and CLOCK that regulates up to 50% of the mammalian transcriptome. While much is known about the vital role of circadian rhythms in neurons, comparatively little is known about their role in oligodendroglial cells. There is still a significant gap in our knowledge of the genetic mechanisms through which BMAL1 and other TFs control OPC differentiation during myelination. My central hypothesis is that the dynamic nature of myelin-forming glia fostered by BMAL1 and other master transcriptional regulators can be used to enhance myelination. This is based on my data in which Bmal1 loss in OPCs results in transcriptional dysregulation, aberrant OPC dynamics and myelination. These data strongly suggest the necessity of BMAL1 in OPC differentiation and myelination. To test this hypothesis, my approach will be to: 1) Characterize the role of BMAL1—the only single clock factor necessary for circadian rhythmicity—in OPC transcriptional regulation during neurodevelopment through single-cell RNAseq and CUT&Tag using our established conditional clock knockout that lacks Bmal1 in OPCs; 2) Evaluate the recovery of the differentiation potential of OPCs that lack Bmal1 by modifying signaling pathways that act downstream of BMAL1; 3) Study the transcriptional control of regulators of human OPC differentiation through a CRISPR screen in human OPCs to discover enhancers. My goal is to identify new regulatory mechanisms of OPC differentiation into myelin-forming cells, starting with the role of BMAL1 in OPC dynamics, and continuing with genomic elements that control OPC differentiation. With the K99/R00 Award, I will obtain the training to prepare me for a lifelong independent research career in genetic regulation of myelin-forming precursors. Understanding the mechanisms that regulate myelin-forming precursors will impart unique insights into normal and aberrant myelination and have a positive impact on developing new therapeutics to restructure myelin in MS.

NIH Research Projects · FY 2025 · 2024-08

Learning and memory is profoundly impaired in patients with Temporal Lobe Epilepsy (TLE) and Alzheimer’s Disease (AD), with devastating consequences on everyday actions such as the ability to safely navigate back home. Temporal lobe structures such as the medial entorhinal cortex (MEC) and hippocampus are critical for the brain’s ability to create, update, and use internal representations of a dynamic external world. While decades of research have revealed how MEC neurons—whose firing rate and patterns encode an animal’s position, orientation, and speed in the environment—can build a static, reliable “map” of the physical environment, less is known about how these maps can be flexibly updated to meet changing behavioral demands. Specifically, how are abstract cognitive features, such as having to avoid an accident-prone traffic intersection or pick up groceries on the way home, integrated into neural maps of the environment to guide behavior? Better understanding the neural circuits and computations which govern flexible spatial processing in MEC is a crucial step towards identifying vulnerabilities in the entorhinal-hippocampal network which may be targeted to alleviate cognitive impairments. Recent advances in high-density electrophysiological recording techniques have generated critical insights about the organization and diversity of information encoded by MEC neurons. In parallel, advances in 3D video recordings techniques and machine-learning algorithms have unlocked access to the rich dynamics of rodent behavior. In this proposal, we combine these state-of-the-art techniques to densely sample single-unit neural activity and behavioral dynamics at high resolution in freely-moving mice performing tasks associated with different cognitive demands, while deploying optogenetic perturbations and an unbiased statistical model of neural encoding. This strategy will allow us to rigorously assess how diverse physical and abstract features of the environment are encoded by hundreds of simultaneously recorded neurons across brain regions. Our overarching hypothesis is that flexible transformations of MEC maps are shaped by distinct neural circuits conveying physical versus abstract features of the environment. In Aim 1, we will test the hypothesis that changes in cognitive demands transform neural maps by recruiting a diverse repertoire of spatial and behavioral variables to be flexibly encoded by MEC neurons. In Aim 2, we will examine if changes in physical features of the environment drive coordinated transformations of spatial representations across MEC and upstream regions such as the anterior thalamic nucleus. In Aim 3, we will determine if cognitive signals conveyed by the thalamic nucleus reuniens enable transformations of MEC spatial representations. This proposal will identify circuit-level substrates that influence which, when, and how transformations of MEC representations occur. By revealing how flexible MEC spatial processing is orchestrated by two thalamic regions which, alongside MEC and hippocampus exhibit pathological hallmarks in TLE and AD, this work will advance our understanding of entorhinal- hippocampal network function in health and disease.

NIH Research Projects · FY 2025 · 2024-08

In ribosomopathies, perturbed expression of ribosome components leads to tissue-specific phenotypes, such as limb and craniofacial defects as well as bone marrow failure. A key example of a ribosomopathy is Diamond Blackfan Anemia (DBA) which results in an erythroid-specific disease manifestation. What accounts for such tissue-selective manifestations as a result of mutations in the ribosome, a ubiquitous cellular machine, has remained a mystery. Our preliminary data strongly support that translational dysfunction may contribute to disease pathogenesis. In particular, our findings show that translational specificity to gene expression upon ribosomal protein (RP) haploinsufficiency may arise from an intermediary pathway, the p53-4E-BP1-eIF4E axis, which becomes activated and links RP haploinsufficiency to selective changes in cap-dependent translation, namely mRNAs with structured 5’UTRs that require eIF4A helicase activity or that have a specific sequence element. This preliminary data strongly supports the rationale to examine translational control and protein synthesis within the hematopoietic compartment, which has been previously unattainable to resolve and has limited our understanding of DBA pathogenesis. Strikingly, while it has been known for over 20 years that RP mutations lead to bone marrow failure associated with ribosomopathies, there has not been any genome-wide studies to pinpoint specific translation impairments underlying hematological abnormalities in- vivo. This is at least in part due to a technical limitation in being able to employ technologies such as ribosome profiling analysis for small numbers of cells. In Aim 1, we will utilize a new technology optimized for small cell numbers to characterize the translational landscape of gene expression for the first time within the early erythroid lineage of the hematopoietic compartment of a faithful DBA mouse model. This will enable characterization of the global translation landscape of gene expression underlying hematopoietic dysfunction in vivo in DBA for the first time. In Aim 2, we will test the hypothesis that the translation factor 4EBP1 play a causative role in alterations in transcript-specific translational control underlying DBA disease pathogenesis and address the fundamental question of whether shared structural features are present in the 5’UTRs of selective mRNAs that account for specificity to gene expression changes underlying ribosomopathies. In Aim 3, we will undertake a state-of-the-art chemical screen to, for the first time, identify translational activators that have the potential to transform the treatment of DBA. In particular, by leveraging over 130,000 diverse compounds available at the High Throughput Screening Knowledge Center (HTSKC), the chemical space will allow for mechanistically novel hits to emerge, including those that directly target the protein synthesis machinery. Together, this proposal holds the potential to transform our understanding and treatment of an entire class of human diseases.

NIH Research Projects · FY 2025 · 2024-08

PROJECT SUMMARY/ABSTRACT: Michael Binkley, MD, MS is an Assistant Professor of Radiation Oncology at Stanford University School of Medicine. His long-term career goal is to combine his expertise in managing patients with hematologic malignancies with his research expertise in statistics, genomics, and cancer biology to develop improved treatment approaches for patients. He aims to develop a translational research program analyzing human tumor and blood samples to identify genomic and microenvironmental factors predictive of clinical outcomes to optimize therapy. This career development award will provide Dr. Binkley with the necessary training, support, and mentorship to develop his research program and gain independence. The proposal will be completed under the primary mentorship of Maximilian Diehn, MD, PhD, and Ash Alizadeh, MD, PhD who are both experts in identifying genomic biomarkers and clinically meaningful microenvironmental factors. The career development plan includes formal coursework, seminars, conferences, and hands-on approaches to allow Dr. Binkley to acquire critical knowledge and expertise in (1) cancer biology and immunology, (2) biostatistics, data management, and predictive modeling, and (3) design of prospective clinical protocols and grantsmanship. Nodular lymphocyte-predominant Hodgkin lymphoma (NLPHL) is a rare subtype of Hodgkin lymphoma that is most commonly treated with intensive chemotherapy with or without radiotherapy. The majority of patients have excellent outcomes but their survival can be threatened by secondary toxicities including cardiotoxicities. To reduce therapy associated morbidity and mortality through de-escalation of therapy by identifying low risk patients and those at high risk of cardiotoxicity, this proposal seeks to (1) describe cell state ecosystems predictive of outcome, (2) use circulating tumor DNA to genotype NLPHL and establish its utility as a surveillance tool for those with advanced stage disease, and (3) establish noninvasive testing of inherited coronary artery disease risk. This proposal will lay the foundation for future prospective clinical trials employing microenvironmental factors to select patients suitable for therapy de-escalation.

NSF Awards · FY 2024 · 2024-08

Among the leading platforms for quantum information processing are systems of cold atoms, which marry exquisite control down to the single-atom level with scalability to large numbers of identical particles. Epitomizing these features are myriad successes in engineering entanglement – nonlocal correlations that form the backbone of quantum technologies – by controlling atoms with laser light. A particularly scalable approach is to couple many atoms to light in an optical resonator, which allows the light to convey information between arbitrary atom pairs. The PI proposes to enhance this approach with programmable connectivity and single-qubit control, by trapping an array of individual atoms in an optical resonator and employing local optical addressing to control the interactions. This new paradigm opens a path to implementing quantum algorithms for chemistry problems and simulations addressing problems in materials science that are intractable to classical computers. The project will also expand the STEM workforce by direct training of graduate students who will conduct the research. The scientific goals of the project are organized into thrusts of (1) exploring frustration and topology in programmable spin models; (2) measurement-based computation and state preparation; and (3) accessing non-Gaussianity as a resource for computation. These efforts will be enabled by the combination of non-local, light-mediated interactions with local addressing to control the graph of interactions in an atomic array. Initial experiments will operate with each array site containing an atomic spin ensemble in a regime of strong collective atom-light coupling, which provides access to Gaussian multimode entangled states. In parallel, the research team will develop a next-generation optical resonator with enhanced atom-photon coupling, in which they will trap an array of individual atoms in optical tweezers. Here, leveraging techniques of single-atom control and detection will allow for approaching a regime of quantum advantage. The project offers a unique opportunity for cross-fertilization between atomic and photonic approaches to quantum information processing, where the former offers the benefit of single-qubit nonlinearities while the latter enables programmable nonlocal connectivity. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NIH Research Projects · FY 2025 · 2024-08

Project Summary / Abstract The development of vaccines is one of the greatest success stories of biomedical research. Vaccines exploit the remarkable capability of the immune system to recognize pathogens, develop memory and upon re-exposure quickly mount an immune response that culminates with elimination of the pathogen. Vaccines are typically injected intramuscularly and provide long-term systemic immunity. However, they are less efficient at generating immunity at the site of infection: mucosal surfaces. With poor mucosal immunity, vaccinated individuals can still become infected and transmit disease, thereby reducing the herd immunity benefits of a vaccine program. The microbial communities that inhabit our mucosal surfaces elicit precise immune responses upon colonization – without inflammation, and across an intact tissue barrier. I propose to develop a novel and unconventional mucosal vaccine strategy that leverages the extraordinary capability of the commensal microbiota to induce precise and long-term immunity at mucosal surfaces. In addition to their efficacy, commensal vaccines promise to be inexpensive and lend themselves to needle-free and cold-chain-free formulations that enable deployment in low- and middle-income countries. Overall, this project will uncover the molecular mechanisms underpinning the intimate relationship established between commensal microbes and their host over millions of years of coevolution and harness this knowledge to develop new vaccine strategies against pathogens. To achieve this goal, I will exploit commensal microbes that colonize the skin, where microbiome intervention is much more accessible. To gain a broad understanding of the immune responses elicited by the microbiota in the skin, I will study the B cell response to prevalent skin commensal microbes (Aim 1). I will profile the B cell response to a newly identified B cell antigen derived from a ubiquitous skin commensal and generate a new monoclonal mouse model to study the molecular interplay between the skin microbiota and B cells (Aim 2). I will engineer skin commensal microbes to elicit potent B cell responses against pathogens (Aim 3). Overall, this project will 1) uncover the B cell response to skin commensal microbes, 2) generate new technologies to probe commensal-specific immunity at the skin barrier and 3) develop a new mucosal vaccination strategy. To achieve my long-term career goal of developing novel technologies to study commensal-immune interactions and creating commensal-based therapies, I have assembled an outstanding group of mentors who complement my training in mucosal immunology and biochemistry: Dr. Michael Fischbach (primary mentor, microbiology and bacterial genetics), Dr. Yasmine Belkaid (co-mentor, skin immunology and bacterial models of infection), Dr. Gabriel Victora (advisor/collaborator, B cell biology and viral models of infection) and Dr. Christopher Barnes (advisor/collaborator, vaccinology). The training I will receive during the K99/R00 award will accelerate my transition into an independent position and allow me to establish a cutting-edge research group of my own.

NSF Awards · FY 2024 · 2024-08

Working with complex data requires a good data structure in order to efficiently organize these data in a computer. The research project will show that a certain popular data structure also has surprising and advantageous statistical properties. It will be shown how these properties can be used to give performance guarantees for a number of statistical procedures and that these guarantees lead to optimal statistical inference. In particular, the project will show how these properties can be used to overcome a problem that affects many multivariate statistical analyses and which is known as the `curse of dimensionality' or `empty space phenomenon'. The research project will also involve mentoring undergraduate students in the context of summer research projects and provide research training opportunities for graduate students. k-d trees are space-partitioning binary trees that are popular in computer science because of their computational efficiency. This project will show that k-d trees also have advantageous stochastic properties that can be used to effectively address a number of challenging statistical problems. In particular, the research will show how the data-adaptive multiresolution partitions generated by a k-d tree can be used to avoid the `curse of dimensionality' or `empty space phenomenon' that afflicts many multivariate statistical procedures. It will also show that the resulting inference comes with finite sample guarantees and that it satisfies certain optimality properties. The to-be-developed methodology will be used to address a number of important problems, such as inference about a multivariate log-concave distribution. Finding the maximum likelihood estimator for such a distribution is computationally very expensive, even for low-dimensional observations. The research will show how the data-adaptive partition can be used to compute a confidence band for a log-concave density in a fast way, and it will establish statistical optimality properties for these bands. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NIH Research Projects · FY 2025 · 2024-08

Project Summary. Depression and anxiety are 2-4 times as likely prevalent among cardiovascular disease (CVD) or diabetes mellitus (DM) patients than among those without CVD or DM. Co-morbid depression and anxiety have a detrimental impact on CVD or DM patients, including exacerbating chronic symptoms and increasing mortality. However, co-morbid depression and anxiety are often underdiagnosed due to the multi- layer barriers at the patient, clinician, and health system levels. Particularly, symptomatic issues and care needs for depression and anxiety might not be easily shared during cardiology or endocrinology visits while clinicians focus on chronic physiological symptoms. The patient portal allows patients to communicate with providers to share their symptoms and concerns, which may signal the early signs of depression and anxiety. Recently introduced Large Language Model (LLM) algorithms have created a robust environment for extracting meaningful topics from large text data. Moreover, machine learning (ML)-based risk models have been designed to predict the risk of CVD or DM, yet, modeling to predict the risk of co-morbid depression and anxiety has been remarkably rare. Thus, in Aim 1, Dr. Kim will identify symptomatic issues and care needs for depression and anxiety among CVD or DM patients using patient portal messages. More than 46 million messages from Stanford Health Center (SHC) will be analyzed by LLM algorithms. It will transform the raw text data into groups of words, then weight them to generate salient topics which represent the primary symptoms and care needs. The generative AI algorithm will enhance interpretability of the topics. In Aim 2, Dr. Kim will develop co-morbid depression and anxiety risk prediction models and specify risk factors among CVD or DM patients. She will leverage the Least Absolute Shrinkage and Selection Operator algorithm, using the electronic health records of more than half a million patients at SHC to calculate the area under the curve to present the accuracy of prediction and odds ratios with 95% confidence intervals to indicate the strength of risk factors. The long-term goal is to apply this patient portal-based symptom detection and risk prediction approach to other at-risk populations to prepare tailored interventions to ultimately improve depression and anxiety outcomes, aligning with the mission of NIMH, "to transform the understanding and treatment of mental illnesses, paving the way for prevention, recovery, and cure." The Career Development Plan will enable Dr. Kim to gain hands-on skillsets to use the newest LLM packages and construct LASSO-based prediction models independently, with an advanced understanding of the clinical context of mental disorders under the guidance of mentors (Dr. Linos in Digital Health, Dr. Rodriguez in Psychiatry, Dr. Hernandez-Boussard in Medical Informatics) and advisors in Biostatistics, Cardiology, Endocrinology, Bioethics. All in all, the strong mentor team and solid training plans along with an excellent institutional support, will fully prepare Dr. Kim to be a well-disciplined independent investigator in computational epidemiology and mental health.

NIH Research Projects · FY 2025 · 2024-08

This mentored F31 Award will provide the trainee, a PhD student in epidemiology at Stanford University, with the training necessary to launch an independent research career in computational epidemiology with a focus on neurological disorders. Under the guidance of a multidisciplinary team of expert mentors, his training goals are to: (1) develop advanced expertise constructing mobile digital tools to monitor neurological function, (2) obtain proficiency integrating heterogenous data sources (digital app, electronic health record [EHR] and imaging data), (3) use advanced statistical techniques (data mining, machine learning) to examine the value of high-dimensional data in predicting clinical outcomes, and (4) gain additional proficiency in preparing manuscripts for publication. Multiple sclerosis (MS) impacts nearly 1 million young adults in the United States, characterized by acute demyelinating brain and spinal cord lesions that cause accumulation of serious neurologic disability over time. The disease course is extremely variable and relapsing remitting MS (RRMS) is the most common subtype, affecting 85% of new onset patients. Treatment decisions are often made using limited cross-sectional data, and even prospectively acquired MRI imaging and clinical assessments in the context of randomized trials are too infrequent to capture the evolution of both clinical and subclinical disability as the disease course evolves. To address these gaps, the candidate will use data collected from 143 patients from the Stanford MS Center to (Aim 1) develop and assess a mobile app paradigm that uses high-resolution passively collected data to retrospectively characterize mobility impairment outside of the clinic, and (Aim 2) improve prospective monitoring of patient function using a trimodal paradigm that includes background collection of mobility metrics, active Apple ResearchKit performance tasks, mobile app-administered surveys regarding patient- reported outcomes (PROs). For both aims, the goal is to predict three outcomes (clinical relapses, Expanded Disability Status Scale [EDSS], MRI measures) that will be collected from objective clinical and imaging data. The proposal builds on extensive prior work of the trainee and his sponsors developing clinical research grade digital tools. If successful, the paradigm will improve upon existing methods by being less costly and less burdensome to patients, ultimately resulting in improved assessment of patients in both clinical and clinical research settings.

NIH Research Projects · FY 2024 · 2024-08

PROJECT SUMMARY Victims of mild traumatic brain injury (mTBI) commonly experience chronic pain, including headaches, spine and limb pain, and are at high risk of developing long-term disability and opioid misuse. Despite this recognized link between mTBI and chronic pain, the neurocircuitry underlying how mTBI increases pain is not known. Emerging preclinical data suggest that the function of a major brainstem pain-modulating circuit, rostral ventromedial medullar (RVM), is disrupted after mTBI - although the precise mechanism is still elusive. The RVM can either enhance or suppress pain. Its pain-facilitating function is mediated by a distinct cell class, ON-cells, which can increase noxious signal transmission through their projections to the spinal dorsal horns. The central hypothesis of this project is that mTBI contributes to chronic pain by sensitizing RVM ON-cell activity, which increases the body’s sensitivity to both noxious and normally innocuous stimuli. In a mouse model of mTBI, my preliminary results suggest that 1) mTBI leads to increased sensitivity in periorbital allodynia (a model for headache) and hindpaw allodynia (a model for distal pain), and 2) an intact ON-cell circuit is required for the development of persistent post-mTBI pain. In two Specific Aims, this study will test the hypothesis by characterizing the functional and electrophysiological changes in descending ON-cells (e.g., spinal/trigeminal dorsal horn-projecting) following mTBI. First, the functional role of descending ON-cells in mTBI-induced hypersensitivity to postsurgical pain (Aim 1a) and headache (Aim 1b) will be explored through the use of chemogenetics. Second, the progressive changes in ON-cell activity in animals with mTBI, and subsequent postsurgical pain (Aim 2a) and headache (Aim 2b) will be studied using in vivo calcium fiber photometry. Finally, the synaptic characteristics of these descending ON-cells in post-mTBI animals with persistent postsurgical pain and headache will be investigated using ex vivo patch clamp recording in RVM brain slices (Aim 2c). This project will provide foundational information to establish the relationship between brainstem pain modulation and brain injury. By defining the longitudinal changes in a highly important pain-facilitating circuit underlying TBI-related pain, the proposed studies address a critical knowledge gap in how TBI leads to chronic pain. Successful completion of this work could also more broadly facilitate our understanding of other centralized pain conditions. Dr. Chen is a physician-scientist with a diverse training background in anesthesiology, pain medicine, and basic neuroscience research. In addition to its scientific significance, this project will enhance his expertise in animal genetics, neural circuit manipulation, in vivo photometry and ex vivo neurophysiological recording, as well as lay the foundation for his future work in pain research and inform clinical practice. The detailed career development presented in this application will provide the required resources and mentorship for Dr. Chen to become an independent R01-funded investigator studying the pathophysiology of brainstem pain modulation neural networks affected by brain injuries.

NIH Research Projects · FY 2024 · 2024-08

PROJECT SUMMARY Immune checkpoint inhibitors (ICIs) have revolutionized cancer therapy, providing lifesaving treatments for an increasing number of malignancies. However, ICIs have also been associated with off-target multi-organ immune-related adverse events, including an increasing incidence of cardiovascular toxicities. After early reports of acute fulminant ICI-myocarditis, active surveillance of ICI cardiotoxicity using cardiac biomarkers such as troponin-I has been recommended. This has resulted in the increased detection of asymptomatic, low- grade cases of unknown natural history and clinical significance. This study will address critical knowledge gaps by investigating risk stratification and outcomes across the entire spectrum of ICI cardiotoxicity subtypes. The applicant’s central hypothesis is that a subset of patients with abnormal troponin-I levels who are asymptomatic have lower risks of adverse cardiac outcomes compared to those with symptomatic disease, and peripheral biomarkers like troponin-I and novel immune markers can help distinguish between “higher” and “lower” risk patients who may tolerate safe continuation of ICIs. To test this hypothesis, the applicant will (1) retrospectively examine cardiac and oncologic outcomes associated with ICI cardiotoxicity stratified by patient symptoms and troponin-I measurements; (2) retrospectively examine the risks of ICI continuation after asymptomatic troponin-I elevation during ICI therapy; and (3) prospectively investigate the role of cardiac, established inflammatory, and novel immune biomarkers in predicting cardiac risks after ICI continuation. These aims will leverage comprehensive data from the Stanford Troponin Monitoring Cohort, consisting of > 1591 consecutive cancer patients with prospectively collected serial troponin-I measurements during each cycle of ICIs, and the International ICI- Myocarditis Registry of > 700 patients with confirmed ICI-myocarditis. The results of this study will lead to critical advances in the field of cardio-oncology by enhancing cardiac risk assessment for ICIs and establishing, for the first time, the role of biomarkers in evaluating the risks of ICI continuation after troponin-I elevation. This will have serious implications for the safe continuation of potentially lifesaving cancer therapies in affected patients. Through this fellowship training, the applicant will also gain important competencies to advance in her long-term goal of becoming a leading physician-scientist in the clinical phenotyping of cardiotoxicity from cancer therapies and forging evidence- based practices in cardio-oncology.

NIH Research Projects · FY 2025 · 2024-08

PROJECT SUMMARY/ABSTRACT Sarcoidosis, characterized by non-caseating granulomas, is a multi-organ inflammatory disease disproportionately affecting black patients in the United States. Although cardiac sarcoidosis occurs in 20-30% of all patients with sarcoidosis, it contributes to 85% of deaths by causing heart failure, ventricular arrhythmias, and sudden cardiac death. The lack of therapeutic targets for cardiac sarcoidosis remains a significant gap in clinical care. My prior work has focused on utilizing single-cell multi-omics and mass cytometry (CyTOF) to identify pathogenic antigen-specific T-cell subsets in myocarditis due to cancer immunotherapy. Now, I am excited to pivot my research direction and extend these innovative methods to investigate cardiac sarcoidosis, with the goal of bringing my prior experience with deep immunophenotyping tools to help bridge the translational gap in cardiac inflammatory diseases. Dysregulation in CD4 T-helper cell (Th) subsets, particularly Th17.1 expressing C-X-C Motif Chemokine Receptor 3 (CXCR3), has been associated with a number of inflammatory diseases, including sarcoidosis. I hypothesize that cardiac sarcoidosis is associated with recruitment of CXCR3+ Th17.1 cells to the heart, which can be therapeutically targeted with CXCR3 blockade. To test this, I will utilize a mouse model of cardiac sarcoidosis and biobank samples from patients with cardiac and non-cardiac pulmonary-only sarcoidosis compared to healthy controls. In Aim 1, I will perform single-cell RNA-seq, TCR-seq, and CITE-seq on tissue (heart, blood, lymphoid organs, lungs) isolated from Tsc2fl/fl CD11c Cre+ mice with cardiac sarcoidosis. In Aim 2, I will conduct single-cell multi-omics and deep T-cell phenotyping on specimens biobanked from patients with cardiac sarcoidosis compared to pulmonary-only sarcoidosis and healthy control patients. In Aim 3, I will explore the therapeutic effects of CXCR3+ blockade on T-cell migration. Specifically, Aim 3a, I will investigate the mechanistic effects of blocking CXCR3 and its ligands, CXCL9/10, on macrophage- mediated Th17.1 cell migration and function in an in vitro transwell system, while in Aim 3b I will treat Tsc2fl/fl CD11c Cre+ mice with CXCR3 blockade to assess for reduced cardiac granuloma formation and Th17.1 cell migration to the heart assessed by single-cell multi-omics. By completing this project, I will define key pathogenic T-cell subsets and interactions between adaptive and innate immunity that drive cardiac sarcoidosis, and test a potential therapeutic pathway for precision medicine. In doing so, I hope to pave the way for the development of adjuvant therapies for treatment and prevention of cardiac sarcoidosis. This Katz R01 will be instrumental in launching my change in research direction within cardio-immunology.

NSF Awards · FY 2024 · 2024-08

Many U.S. cities experience combined sewer overflows (CSOs) during wet weather. The resulting release of sewage and stormwater can have negative environmental and health consequences. Of particular concern are marginalized communities residing historically in flood-prone zones, which face heightened susceptibility to CSO impacts. Current urban wastewater systems were designed to withstand peak flows derived from outdated precipitation records. With climate change producing more frequent and intense rainfall, cities face urgent challenges to manage and mitigate CSOs in an equitable manner. This project will directly address these challenges by developing a model of the Des Moines, IA combined sewer system using real-world data. This system is similar to that of many other major U.S. cities, and therefore provides a framework for researchers to study the resilience of wastewater systems. By prioritizing equity in the scientific approach and proactively integrating future climate conditions, this research bridges the gap in system-level resilience assessment for wastewater systems, and will provide insights into the vulnerability of marginalized communities to CSOs amid climate change. This research aims to analyze the resilience of combined sewer systems in response to climate change and assess potential CSO exposures and impacts on marginalized communities. An integrated modeling framework will be created enabled by cutting-edge development in below-ground drainage modeling and it will be coupled with a qualitative-quantitative survey method to perform relevant, local phenomena-based research. The project is expected to 1) advance data analytics and modeling methodologies for urban wastewater systems; 2) assess system-level resilience of the test-bed system (i.e., Des Moines, IA) to wet weather conditions under the influence of climate change; and 3) uncover the vulnerability of marginalized communities to future likely CSO incidents. This research aims to catalyze equitable solutions in the management and mitigation of CSOs, fostering enduring benefits for marginalized communities. In addition, it will provide unique opportunities for graduate and undergraduate students to work collaboratively across universities and directly with industry collaborators, enabling a pipeline for both personnel and research to move more rapidly in and out of academia. This project is funded jointly by the CBET Environmental Sustainability program and the CBET Environmental Engineering program. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NIH Research Projects · FY 2026 · 2024-08

PROJECT SUMMARY. Acute pancreatitis (AP) is an exquisitely painful, life-threatening, public health problem that has substantial morbidity and limited treatment modalities. Our long-term goal is to develop focused therapies to treat AP and mitigate disease severity. The premise is based on our discovery (1) that the calcium-activated phosphatase calcineurin (CN) is a potent mediator of AP in the primary parenchymal cell of the pancreas, the acinar cell, and (2) that the distinct molecular signatures underlying this potent effect can be leveraged to develop targeted therapies for AP. The two major objectives of the current proposal are (1) to elucidate the CN-modulated signaling pathways in AP and (2) to identify novel and potentially therapeutically targetable, direct CN substrates within these pathways. The three Specific Aims are to: (1) Define the phosphosignaling networks, including signatures regulated by CN activity in AP through phosphoproteomics coupled with powerful bioinformatics; (2) characterize the role of CN in the identified pathways of mTOR and autophagy during AP; and (3) evaluate novel CN substrate candidates that are integral to the identified pathways. Our hypothesis, which was generated from compelling preliminary phosphoproteomic data, is that CN mediates AP by impairing autophagy, and the mechanism for the impairment is through both (1) activation of the upstream autophagy inhibitor mTOR and (2) direct inhibition of CN substrates in the autophagy pathway itself. The design of the approach is that Aim 1 is an unbiased phosphoproteomic screen, using clinically and biologically relevant AP conditions, for phosphosignals that will provide clues to CN-modulated pathways in AP. Aim 2 is to conduct independent, empirical testing of CN modulation in AP of the identified pathways of autophagy and mTOR, by examining canonical components and phosphosites, including the ones that were not necessarily detected in the unbiased phosphoproteomic data. Aim 3 is a systematic identification, followed by biochemical validation, of novel CN substrates that are integral to the identified pathways in AP. Here, we will also probe the molecular mechanisms by which CN modulates novel substrate activity and function. Incorporating a highly multidisciplinary team of investigators and an ideally suited environment, the proposed studies are technologically and conceptually innovative since they utilize (1) advanced computational methods to identify CN-regulated pathways and substrates, (2) human pancreas specimens for ex vivo culture, (3) an innovative in vivo pressure-induced pancreatitis (PIP) model, and (4) cutting edge phosphoproteomic and biochemical tools including BioID, which captures in cell transient low-affinity interactions between CN and its substrate candidates. The significance of the proposal is that it creates a discovery pipeline to identify novel CN-modulated phosphosignaling networks in AP and will provide a valuable resource to the pancreas community that will aid in devising targeted AP therapies.

NIH Research Projects · FY 2025 · 2024-08

Project Summary/Abstract: T2* mapping and quantitative susceptibility mapping (QSM) are vital for in vivo iron quantification. They can track the subtle changes in tissue compositions during early brain development; they can provide valuable characteristics of lesions in Multiple Sclerosis (MS) for structural, pathological, and dynamic information. T2* and QSM are commonly estimated using multi-echo gradient echo (GRE), which suffers from long scan time (5-10 minutes) and sensitivity to motion and B0 perturbations, significantly limiting its clinical accessibility and impeding its potential for fine tissue characterization towards submillimeter resolution. This project aims to develop and validate a rapid, distortion- and blurring-free, and motion- and B0-robust technique for submillimeter-resolution T2* and QSM quantification, and translate it to applications on challenging populations, including infants and MS patients, demonstrating its potential for wide neuroscientific and clinical applications. The goal is fulfilled through three Specific Aims: In Aim 1, we will develop and optimize a highly efficient spherical-coverage echo-planar time-resolved imaging (sEPTI) framework for whole-brain distortion- and blurring-free T2* and QSM quantification. We will leverage a subspace-based unrolled deep-learning network for SNR-boosting reconstruction to achieve a 4x reduction in scan time on top of the already-fast state-of-the-art EPTI techniques. In Aim 2, we will develop a 3.5-ms multi-channel SPINS-trajectory navigator and combine it with the sEPTI technique as nasEPTI to achieve accurate motion and δB! estimation per TR with 70 ms latency. A supervised deep learning network will be developed to achieve fast and accurate estimation of motion and δB! in <5ms. Taken together, we will develop a synergistic per-TR prospective motion correction and retrospective B0 correction pipeline based on the rapid deep learning inference to accomplish a robust nasEPTI technique for artifact-minimized T2* weighted images, and T2* and QSM quantification. In Aim 3, nasEPTI will first be validated on 20 motion-prone infant subjects on 3-Tesla scanners with 0.7mm3 isotropic resolution and 1-minute scan time to demonstrate its robustness to motion and B0 perturbations. In parallel, this technique will be translated to 7-Tesla systems for a protocol of 0.35 mm isotropic resolution and 6- minute scan time. Finally, we will validate the 7T nasEPTI protocol on clinically suspected MS patients with cortical lesions, where T2* and QSM provide critical pathological information about the lesions. The expected outcome is that the proposed techniques achieve distortion- and blurring-free, motion- and B0-robust high-resolution T2* and QSM quantification. They are consistent with conventional multi-echo GRE in terms of T2* and QSM values, but provide enhanced image quality with significantly reduced artifacts. This will enable mesoscale iron characterization within a scientifically and clinically feasible time, facilitating its access to general populations, including motion-prone pediatric and geriatric groups.

NIH Research Projects · FY 2026 · 2024-07

Persons with end-stage kidney disease are 16 times more likely to undergo surgery and have significantly increased perioperative risk of mortality, myocardial infarction, and stroke compared to surgical patients with normal or near normal kidney function. Despite this elevated surgical volume and risk profile, little is known about how to best perform preoperative hemodialysis when these patients undergo surgical procedures. The goal of this project is to improve perioperative health for this high-risk surgical population through optimizing preoperative hemodialysis treatment. In Aims 1 and 2, we will evaluate the link between modifiable preoperative dialysis parameters and postoperative complications underlying adverse outcomes. In Aim 3, we will conduct a pilot randomized trial of a novel intervention to control preoperative hemodialysis timing. Accomplishing these goals will help clinicians and policy makers identify optimal dialysis practices for patients with end-stage kidney disease who need surgery. It will also lay the groundwork for future prospective randomized clinical trials of interventions to reduce perioperative mortality and morbidity for these patients. It is innovative in its use of a unique database linking Medicare claims to electronic health records of a major dialysis provider, application of sophisticated statistical methods, and the creation of a multidisciplinary team with clinicians and researchers from multiple disciplines. In addition to the research objectives outlined above, this K23 proposal aims to provide Dr. Vikram Fielding-Singh, MD, JD, with the protected time, training, and research experience to enable him to become an independent clinical investigator focused on perioperative optimization of persons with end-stage kidney disease. Specifically, the proposal will aid Dr. Fielding-Singh’s development through providing support for completion of a Master of Science in Epidemiology and Clinical Research at Stanford University and mentorship by an experienced team of nephrologists, surgeons, and health services researchers. With this training and experience, the candidate will be uniquely positioned to seek further funding to evaluate additional approaches to improve the perioperative health of patients with end-stage kidney disease.

NIH Research Projects · FY 2025 · 2024-07

Project Summary Radiation-Induced Cardiotoxicity (RIC) remains a concerning health issue, particularly in accidental radiation exposure scenarios as evident in the Life Span Study of Japanese atomic bomb survivors. However, the complex interplay of factors contributing to the diverse presentations of RIC remains elusive. This project aims to shed light on the critical roles of sex hormone “estrogen” and genetic variations in estrogen receptor (ER) signaling in modulating RIC susceptibility and response. The research takes an innovative approach by combining state-of- the-art techniques and multidisciplinary expertise. Firstly, a "cell village" strategy will be employed which leverage pooling human induced pluripotent stem cell (iPSC) derivatives from a diverse cohort of 200 individuals. Pooled iPSCs will be differentiated into 3D cardiac organoids (iPSC-COs) and treated with varying doses of estrogen and radiation to simulate different physiological conditions and radiation exposure, respectively. Cutting-edge single-cell genomics and computational technologies will be employed to scrutinize the resulting transcriptomic and epigenomic changes in each individual. This will help us identify inter-individual variations and underlying genetic mutations that contribute to differential molecular responses upon irradiation. Additionally, animal models will be employed to simulate radiological incidences and corroborate multi-omics data to functional outcomes in whole organisms. Collectively, these experiments will elucidate the genes responsible for sexual disparity in RIC and its relation to estrogen signaling which can provide insights into personalized risk prediction and intervention strategies, addressing a critical knowledge gap in the field of radiation biology and cardiovascular health.