Stanford University

NIH Research Projects · FY 2026 · 2025-04

PROJECT SUMMARY/ABSTRACT Cancer and cardiovascular disease remain the world’s two leading killers. Historically considered distinct entities, emerging data have identified numerous shared risk factors, and demonstrated that cancer patients are at increased risk for cardiovascular events. However, these studies have several limitations. For example, most of this work was unable to control for confounding related to traditional risk factors (such as smoking) and cardiotoxic treatments (such as chemotherapy and radiation). Also, causal relationships have not been proven, and potential mechanistic links between the diseases remain obscure. As a result, it is unknown if cancer directly promotes cardiovascular disease, nor whether there are therapies that could potentially treat patients with co-prevalent disease. Given these critical barriers, the broad, long-term goal of this proposal is to precisely determine if cancer promotes cardiovascular disease, and how it can be treated. To answer these questions, we have assembled a team of leading interdisciplinary investigators who are committed to rigorous and reproducible research across the fields of population genetics, cardio-oncology, and translational medicine. We have established an innovative program that is broad and ambitious, but has been extensively de-risked via our access to unique transgenic animals, highly specialized human biorepositories, and emerging machine learning-based computational methods.

NIH Research Projects · FY 2026 · 2025-04

SUMMARY / ABSTRACT Over 150,000 ICDs are implanted annually in the U.S. at a cost exceeding $5 billion. Despite documented life-extending benefits, patterns of ICD use for primary prevention of sudden cardiac death (SCD) are often misaligned with patient clinical needs and personal values. While ICDs are underused, particularly in lower income, and younger heart failure patients, overuse among older patients often stems from biased decision-making and lack of frank discussion of harms and benefits. Such issues are common among other costly and complex healthcare procedures and technologies. Many older patients have ICDs implanted without receiving personalized data indicating the extent of lifespan extension, which is often limited. Sensitive and empathic discussions do not often occur about ICD acceptability, desired mode of death, and personal values/beliefs. For patients 70+ years (accounting for 40% of ICDs), ICD therapy may not align with patient preferences. ICD benefits do not always offset adverse effects and/or the high risks of dying from non-arrhythmia causes. Enhanced shared decision-making using digital technology can improve ICD decisions for SCD primary prevention. Developed via patient-centered design guided by our team at 3 diverse clinical sites, our new digital ICD tool can efficiently improve patient-physician dialogue, while reducing gaps in quality care and inefficient use of ICDs. Our tool grew out of a successful digital tool covering blood thinners and stroke prevention in atrial fibrillation (AFibGuide). The ICD tool follows a similar design and includes both a patient component and a concise clinician component. It follows a 7-step pathway: a) introduction/data input, b) animated video with key messages, c) frequent questions, d) check-in quiz, e) patient-specific display of risk data, f) values exploration about interventions and death, and g) wrap-up creating a patient-clinician worksheet. Our three Aims are: Aim 1) Refining the tool. Key objectives will be enhancing user experience, developing specific visual displays for numeric information, and app programming for tablets and laptops in Spanish, Mandarin, and English. Aim 2): Rigorous Testing of Tool Effectiveness. A randomized controlled trial (RCT) of our ICD tool will test effectiveness at three diverse clinical sites. We will enroll a total of 600 participants who are 70+ with heart failure randomized to: A) Digital tool with risk displaying, B) Digital tool without risk display, and C) Usual care. Our hypothesis: Satisfaction with decisions will increase in a stepwise manner from Arm C < Arm B < Arm A. Likewise, we expect stepwise increases in patient knowledge, engagement, quality of life, and physical activity. Aim 3: Dissemination Research. This Aim will first delineate barriers to dissemination through serial interviews with a broad range of key stakeholders. Second, we will examine more specific barriers among RCT participants from Aim 2 using focus groups and a questionnaire survey. These strategies will lead to Tool enhancement and a plan for successful public dissemination of the digital ICD Tool.

NIH Research Projects · FY 2026 · 2025-04

Neural organoids represent a powerful tool for modeling the brain and neurodevelopmental disorders (NDDs), but they are unable to capture the interactions between distinct brain regions, which are critical for later brain development. To capture these important interactions, our team established a novel modular brain organoid system, termed brain assembloids, in which organoids of separate brain regions are combined in a single culture. Using these assembloids, we demonstrated that Timothy syndrome, a rare genetic condition affecting cognitive function, is associated with defects in GABAergic interneuron migration. A key limitation of this new technology is that current assembloid protocols require manual positioning of organoids within liquid media, resulting in poor reproducibility and lack of physiologically-relevant brain geometries and connectivities, while making more complex assembloids (i.e., of 3 or more organoid types) prohibitively laborious. Additionally, individual organoid building blocks are commonly cultured in either Matrigel, a poorly defined, highly variable derivative of mouse sarcoma cells, or as free-floating suspensions, which commonly result in unwanted organoid fusion. This results in high variability of organoid size and quality within and between batches. Here, we propose a novel bioengineering platform to enhance the quality, reproducibility, and complexity of neural assembloids to strengthen their use as physiologically- and spatially-relevant in vitro models of interneuron migration in neurodevelopment and NDDs. We leverage a novel magnetic 3D-bioprinting technology (termed SPOT) to generate assembloids of precisely-controlled spatial orientation, constructing physiologically relevant neural connections, and using well-defined biocompatible polymers to enhance reproducibility in organoid and assembloid size and quality. In Aim 1, we begin by evaluating the hypothesis that increasing the viscosity of the surrounding medium will improve the size and organizational reproducibility of brain organoids from several distinct regions that resemble a mid-gestation developmental stage: cerebral cortex (hCO), medial ganglionic eminence (MGE)-like subpallium (hSO), and lateral ganglionic eminence (LGE)-like striatum (hStrO). We will use SPOT to print two-part assembloids of various combinations and evaluate interneuron migration and cortical neuron projections. In Aim 2, we will use SPOT to print three-part assembloids with precise spatial positioning between the MGE-, LGE-, and cortex-like organoids. We hypothesize that reproducible control over geometric positioning of the individual organoids will significantly improve the reliability of interneuron path-finding, allowing this human microphysiological system to be used for NDD studies. In Aim 3, we leverage our three-part assembloids to study the effects of several NDD-related genes on interneuron migration and validate the utility of our bioengineered platform. This transformational work will provide an advanced platform for the controlled construction of complex assembloids, enabling unprecedented molecular and functional studies into human brain development and diseases.

NIH Research Projects · FY 2026 · 2025-04

Chimeric antigen receptor (CAR) T cell therapy has emerged as a transformative immunotherapy for cancer, autoimmune diseases, and transplantation. In this treatment, a patient’s immune cells are isolated and engineered to express a synthetic CAR on their surface to direct T cell reactivity towards diseased cells. Patient CAR T cell quantity throughout the therapeutic process is a contributing indicator of the efficacy of immune response as well as an immediate sign of toxicity through complications such as cytokine release syndrome and immune effector cell-associated neurotoxicity syndrome. However, current methods for quantification are costly in both time and money, precluding point-of-care clinical support. There is a critical need for real-time, low-cost CAR T cell quantification. We propose a rapid, label-free, and cost-effective technique for CAR T cell counting in patient blood using surface enhanced Raman spectroscopy (SERS) and machine learning (ML). Aim 1 entails optimizing a SERS approach to collect Raman spectra from immune cells. This includes the development of methods in Raman spectroscopy and sample preparation, and plasmonic gold nanorod fabrication and surface modification. In Aim 2 we will develop and optimize ML infrastructure to classify and quantify engineered T cell spectra from that of other cells. Finally, in Aim 3 we will digitize patient blood samples mixed with nanorods into single T cell droplets, from which we extract optical signals for each cell using Raman spectroscopy and use ML to quantify CAR T cells. By conducting this procedure on patient blood over the course of CAR treatment, we will generate efficient cell quantification data that can be correlated to therapeutic impact with significant time and financial advantage over previous methods. Our proposal combines innovations in cancer biology, immunology, nanophotonics, and machine learning to develop a technique that will benefit researchers, clinicians, and patients for safer, more effective CAR-therapies. The successful completion of this project will lead to further efficient label-free methodologies, for example in cell receptor expression level quantification, strengthening the addition of this technique to the immunologist’s toolbox. Both the specific aims of this project as well as its future potential strongly align with the agency’s mission. This research will allow for the advancement of fundamental knowledge of CAR T cells and the downstream impacts of CAR expression on immune cells. Additionally, its application in patient care has the critical potential to benefit CAR therapy development and minimize fatal complications, aiding in enhancing health and reducing illness.

NIH Research Projects · FY 2025 · 2025-04

PROJECT SUMMARY/ABSTRACT South Asian heritage and breast cancer are intersecting vulnerabilities for breast cancer survivors and their family caregivers due to cancer-related stigma and fears, taboos around reproductive organs, and rigid gender roles. These cultural factors could amplify the stress, social isolation, and loneliness known to affect survivors and caregivers, and can inhibit breast cancer self-management. Yet, there are no dyadic behavioral interventions to address these psychosocial needs in the South Asian cultural context. The long-term goal of this research is to develop a culturally adapted, behavioral intervention to support self-management among South Asian survivors and their caregivers. The objective here is to develop South Asian Family Approaches to Disease (SAFAD), a theoretically grounded, behavioral intervention to improve self-management by mitigating the stress, loneliness, and social isolation among South Asian survivor-caregiver dyads. We will develop SAFAD by culturally adapting our existing dyadic self-management intervention, web-SUCCEED (web-based Self-care Using Collaborative Coping EnhancEment in Diseases) which is currently being tested in a clinical trial with dyads managing chronic and serious illnesses. We propose the following specific aims: Aim 1: Using generative co-design, develop a prototype of a dyadic self-management intervention for South Asian breast cancer survivors and caregivers by culturally adapting web-SUCCEED. Aim 2: Conduct a pilot randomized trial to assess the feasibility of recruitment, retention, randomization, and measures, and assess the acceptability of randomization and intervention with 30 South Asian survivor-caregiver dyads. We will pursue these aims using an innovative co-design framework that combines the strengths of community-based participatory research and design thinking. Our multistep cultural adaptation process will include engagement with South Asian survivors and caregivers with lived experiences, and community leaders. All activities will be guided by a community advisory board comprising diverse, multilingual South Asians. The proposed research is significant because it tackles the underrepresentation of South Asians in cancer survivorship research; the lack of culturally adapted interventions for South Asians; and the need for evidence-based interventions to combat cancer-related social isolation and loneliness. The proximal expected outcome is the development of a theory-based, culturally adapted, dyadic self-management intervention for further testing. The results will have an immediate positive impact by laying the groundwork for further intervention development, and for prospective, observational studies to understand the experience of South Asians managing breast cancer, an understudied group that is at high risk for healthcare disparities.

NIH Research Projects · FY 2026 · 2025-04

PROJECT SUMMARY/ABSTRACT Delirium occurs in 10-40% of surgical hospitalizations and has been associated with post-discharge declines in cognition and function, including Alzheimer’s Disease (AD). After hospital discharge, the incidence of neurocognitive dysfunction is estimated to be up to 10-25% in the year after surgery. However, pathways leading to postoperative delirium and neurocognitive dysfunction are not understood. Biomarkers obtained during and after surgery may provide important insights, similar to how biomarkers are used in AD research. In AD research, the use of biomarkers has transformed the conceptualization of AD from a syndrome to a pathologic entity. The AT(N) framework has provided researchers with a clear approach for staging, diagnosis, and monitoring disease, with several cerebrospinal fluid (CSF) biomarkers, such as β-amyloid, tau, and phosphorylated tau isoforms, having utility in this framework. The goal of this proposal is to pursue a parallel strategy of examining CSF and blood biomarkers to understand pathways leading to postoperative delirium and neurocognitive dysfunction. One hypothesized pathway is blood brain barrier (BBB) injury, followed by neuroinflammation, and neuron/astrocyte injury or astrocytosis, all layered over heterogeneity in baseline patient vulnerability. Both animal and human studies support aspects of this hypothesis. However, few human studies have collected serial measurements of CSF, which is important for brain-specificity. Relevant domains (and associated markers) that support conceptual models of postoperative neurocognitive dysfunction include baseline risk (AD- related biomarkers; e.g. β-amyloid and phosphorylated tau isoforms), BBB injury (CSF/blood albumin, platelet derived growth factor receptorβ), neuroinflammation (cytokines/chemokines, microglial activation), neuronal injury (neurofilament light, tau), and astrocyte injury/astrocytosis (glial fibrillary acidic protein). The potential of using biomarkers to understand postoperative brain dysfunction is profound, but there are important limitations, including (a) most studies have not collected CSF (b) studies reporting associations of biomarkers and delirium or neurocognitive dysfunction have been suggestive but inconsistent, and (c) most studies have few postoperative samples (particularly for CSF), a small number of biomarkers, and limited cognitive follow-up. To address these gaps, we propose a 3-center study of 180 patients undergoing open or endovascular aortic surgery, who have a CSF drain placed as standard of care. We will obtain serial CSF and blood samples for 2- 3 days. We will then determine whether CSF biomarkers of baseline risk, BBB injury, inflammation, neuronal injury, and astrocyte injury/astrocytosis are associated with delirium (Aim 1) and neurocognitive dysfunction (Aim 2). We will also examine the associations of blood biomarkers with delirium and neurocognitive dysfunction and the correlations of serial blood and CSF biomarkers (Aim 3). This study will provide a unique resource of serial CSF and blood samples to explore how BBB injury, inflammation, and brain injury contribute to delirium and neurocognitive dysfunction. The results will also provide insight into the utility of blood-based biomarkers.

NIH Research Projects · FY 2026 · 2025-04

ABSTRACT The proliferation, survival, invasion, and metastasis of human cancers are driven by oncogenic gene expression networks specific to a malignant cell. Exploiting cancer-specific vulnerabilities in gene expression offers an attractive opportunity for precision medicine. I propose to develop novel pharmacological approaches to rewire oncogenic gene expression and kill a cancer cell, that could yield unprecedented precision and potency and offer a new paradigm for precision cancer therapy. In past work, I have shown that small molecule chemical inducers of proximity (CIPs) can rewire transcription factors to potently activate the expression of pro-apoptotic genes, apoptosis, and killing of a cancer cell. My overall objective is to systematically explore the potential of CIP to rewire fusion transcriptional regulators and produce cancer cell death. Fusion oncogenes are highly relevant target for precision cancer therapies because of their specific expression in tumor tissue and driving role in the progression of the malignancy. Aim 1 will develop CIPs that kill aggressive leukemias driven by translocations of the mixed- lineage-leukemia (MLL) gene. Methods used to achieve this goal will include organic synthesis, pharmacological assays, measurements of chromatin mechanisms, functional studies in cellular models of leukemia, and assessments of effects on primary human hematopoiesis. Aim 2 will discover the core molecular principles that underlie how CIPs can rewire transcription factors, using structural biology, biophysical measurements, protein biochemistry, and computational modeling. The expected outcomes include (Aim 1) a new class of molecules that target the MLL fusion oncoprotein for treatment of MLL-r leukemias and (Aim 2) a comprehensive structural and biophysical analysis of activating pro-apoptotic genes using CIP. Combined, the proposed research will develop novel pharmacology to target a cancer-driving fusion oncogenes. It also will develop important structural insights to inform the rational design of small molecules to rewire oncogenic gene expression. Each of the proposed directions has the potential to yield fundamentally new approaches to targeting gene expression in cancer. The Aims proposed will take place under the mentorship of world-recognized experts in medicinal chemistry, cancer pharmacology, hematologic malignancies, and structural biology who will provide the mentorship needed to acquire skills enabling success. The proposed research will allow me to apply my background in chromatin and chemical biology to make an impact on malignancies with high unmet need, while receiving additional training in synthesis and structural biology. It will prepare me for a successful independent career developing novel pharmacology to target dysregulated transcription in cancer.

NIH Research Projects · FY 2025 · 2025-04

PROJECT SUMMARY/ABSTRACT Today, functional MRI (fMRI) is the most widely-used method for measuring activity across the entire human brain. FMRI is used to infer ‘functional connectivity’, and most studies utilize coarse spatial resolution (~2 mm isotropic) with which it is possible to detect interactions between brain areas at the centimeter scale. However, this approach lacks the ability to estimate the directionality of neuronal communication flowing from one brain area to another, and thus cannot decipher the underlying circuitry needed to investigate brain computation. Meanwhile, the emerging field of laminar fMRI seeks to resolve activation patterns across cerebral cortical layers, and has shown the potential to interrogate the directionality of these connections by probing correlations between input and output layers of cortical areas. Yet even with the highest spatial resolutions available at 7 Tesla (0.8 mm isotropic), laminar fMRI data are marginally capable of isolating the activity of individual cortical layers and are incapable of covering the entire brain with adequate temporal resolution. Here we propose to supplement conventional whole-brain functional connectivity with an ultra-high spatial resolution (0.125 mm) interrogation of cortical laminar connectivity. Our technology automatically places multiple independent 1D “linescan” fMRI acquisitions normal to the cortical surface within functional ‘hubs’ identified in a prior conventional fMRI scan. Linescan MRI is a classic method that acquires a “1D image”—i.e., a single line—enabling ultra-high spatial resolution in the “in-line” direction down to ~100 μm. Since only one line is encoded, it also enables short readouts and ultra-fast temporal resolution. Linescan MRI is well-suited to cortical layers, provided that the line intersects the cortex exactly perpendicularly. Accurate manual prescription of one linescan at a given location in human cerebral cortex is difficult with the MRI console’s user interface; prescribing several linescans across a brain network is prohibitive. Also, linescans cannot be retrospectively corrected for motion. We will overcome these challenges to enable concurrent linescan fMRI at multiple cortical locations to study communication along feedforward and feedback pathways between cortical areas. We will also develop novel radiofrequency pulses to sharpen the ‘line profiles’ to increase resolution and boost SNR. We will develop both novel gradient-echo linescan fMRI to provide ultra-fast temporal resolution and spin-echo linescan fMRI to provide pure T2 contrast— difficult to attain with conventional fMRI—for microvascular weighting and increased neuronal specificity. We will apply our linescan fMRI in experiments designed to showcase its unique capabilities and advantages. We will extend previous findings by measuring layer-specific interactions between left and right motor cortex, then demonstrate, for the first time, how input layers and the cascade of information across visual cortex can be inferred from the onset time of the layer-specific activation, and test a novel hypothesis about directed communication within the Default Mode Network. The outcomes will be dissemination of data acquisition/analysis technologies that expand the scope of what is possible with fMRI, and novel insights into human brain circuitry.

NIH Research Projects · FY 2026 · 2025-04

Project Summary Combined immune checkpoint inhibitor therapy with nivolumab plus ipilimumab has become a standard first-line treatment for metastatic renal cell carcinoma (RCC). Unfortunately, information regarding whether patients are responding to this treatment regimen is not known until tumor diameters are measured on a computed tomography (CT) scan 2-3 months after starting therapy. This is because changes in tumor size typically cannot be reliably measured before this time frame. Patients for whom therapy is ineffective endure treatment side effects without benefit. Therefore, early biomarkers for therapeutic response are needed so that effective and ineffective treatment can be distinguished earlier than current standard of care and patients who do not derive benefit from this combination therapy can move on quicker to a potentially more effective treatment. Blood and urine exosomes are a prime candidate for serving as such a biomarker. The complex mechanisms of action of these drugs involve tumor cells, epithelial cells, immune cells, and other host factors. All these cells release exosomes into the blood stream, which contain protein and RNA derived from these cell types. Therefore, we hypothesize that early molecular effects in these cell types that lead to changes in tumor size on a 3-month CT scan can be measured in plasma proteins and/or exosomal proteins and RNA, specifically changes in KIM- 1, PD-L1, and exosomal micro-RNAs. Thus, exosomes may carry an early biomarker for therapeutic response that can be measured by protein analysis and transcriptomic profiling of exosomes isolated from blood and urine. In this pilot study, we will sequence exosomal RNA from the blood and urine of 50 patients with RCC at 3 time points: at treatment baseline and 3 and 6 weeks after initiating therapy with nivolumab and ipilimumab. We will 1) define for each analyte an exosome signature of response by determining the subset of exosomal transcripts that is differentially expressed on therapy compared to baseline and that correlates with the relative change in tumor burden; and 2) determine how early on treatment such a predictive signature can be feasibly detected (week 3 vs. week 6); and 3) whether blood exosomes alone, urine exosomes alone, or both in combination allow for the most accurate prediction of response. We will use this information to select the on-therapy time point and sampling strategy for validating this candidate predictive biomarker for response in a follow-up study.

NIH Research Projects · FY 2026 · 2025-04

Project Summary/Abstract: T cells, natural killer (NK) cells, and macrophages engineered to express chimeric antigen receptors (CARs) have shown promise as therapies for cancers, autoimmune diseases, heart disease, aging, and chronic viral infections. Current therapies use these CAR immune cells in isolation from one another. This contrasts the natural immune system, which deploys multiple cell types and coordinates their activities to mount immune responses against pathogens and cancers. A major challenge is to extend our engineering of immune cells to include co-engineering distinct cell types to function as a synthetic immune system. Such a synthetic immune system may overcome limitations of the individual CAR immune cell types, provided the cells are engineered to act synergistically rather than antagonistically. We reason that we can design a three-cell (T-NK- macrophage) immunotherapy by treating each cell type as a modular part, creating and testing many combinations of engineered cells. The functions and phenotypes of CAR immune cells can be modulated by changing the signaling domains of CARs or other receptors such as synthetic cytokine receptors (SCRs). In this work, we propose to screen CARs and SCR libraries in three-cell immunotherapy systems against cancer models and to use the screen data to fit dynamical models that describe the time-dependent behavior of such systems. Using this approach, we will identify CAR-SCR pairs with signaling domains that tune three-cell immunotherapy function, and create quantitative models to aid in development of new receptors. In Aim 1, we will construct libraries of CAR-SCR pairs and screen them to engineer a CAR T-NK-macrophage synthetic immune system with synergistic anti-tumor activity against a leukemia model. In Aim 2, we will engineer a tri-specific CAR-T-NK-macrophage synthetic immune system to overcome tumor heterogeneity and antigen escape in the context of a glioblastoma model. To carry out these aims, we will combine CAR T cells, NK cells, and macrophages and perform in vitro arrayed screens using live-cell imaging, flow cytometry, and RNAseq to measure immune cell function (proliferation, killing, cell state) and anti-tumor activity. Dynamical models fit to these data will help us quantify the time evolution of these systems, the activity of each cell type, and their combined synergy. This work will identify receptors that optimize key anti-tumor phenotypes of CAR immune cells. This approach will also give us valuable insights into how multiple cell types synergize or antagonize in the context of a multi-cell therapy. A framework to engineer three-cell synthetic immune system with receptors that tune the therapeutic functions will facilitate improved therapies for cancers and autoimmune diseases.

NIH Research Projects · FY 2023 · 2025-04

PROJECT SUMMARY/ABSTRACT Sexual minority (SM, i.e., people who are not heterosexual) and gender minority (GM, i.e., people who have a gender that is discordant from the sex they were assigned at birth, as opposed to cisgender people who have a gender that is concordant with the sex they were assigned at birth) people (collectively abbreviated as SGM) are at greater risk for health disparities including very high rates of substance use. Some subgroups of GM people evidence greater risk for cannabis use. The primary explanation for the higher rates of cannabis use among SGM people is minority stress (for example mistreatment related to one’s SGM status), but there may also be hormonal contributors to cannabis use. Epigenetic modifications (e.g., DNA methylation) are one way to track molecular modifications in response to cannabis use and may serve as biomarkers for cannabis use. Understanding the epigenetics of cannabis use may help us to develop better ways to identify and treat substance use disorders and to understand the downstream health outcomes of SGM people. This study will leverage The PRIDE Study, a national longitudinal cohort study of SGM people to identify changes in trajectories of cannabis use among SGM people over 9 years of annual data collection (N>14,000 aged 18+), examine differences in these trajectories based on hormonal exposures and examine how minority stress changes these relationships (Aim 1). This study will then identify the relationships between cannabis use trajectories and DNA methylation among SGM people assigned female at birth (N=600), identify differences in the relationships between cannabis use and DNA methylation based on hormonal exposures, and identify which of these relationships between DNA methylation and cannabis use persist even after accounting for minority stress (Aim 2). This study will help us to understand longitudinal trajectories of cannabis use among SGM people to inform targeted prevention and intervention development. This study will also inform the development of biomarkers for cannabis use to improve substance use treatment and prevention.

NIH Research Projects · FY 2026 · 2025-04

Modified Project Summary/Abstract Section Despite decades of average national reductions in mortality among children and adults living in the world’s poorest countries, some regions have been left out of this broad reductions in mortality. This project aims to identify the location of and characterize these “mortality hotspots,” where child or adult mortality are exceptionally high and on track to remain the among the world’s highest reach as the Sustainable Development Goals target year of 2030 approaches. To address this gap and identify paths for improving health among those living in mortality hotspots, this proposal includes three aims. First, we will obtain spatially granular estimates of mortality among infants, children, and adults in low- and middle-income countries using existing and novel spatial interpolation approaches. Second, we will identify mortality hotspots by integrating different mortality estimates, projecting them to 2030, and identifying those locations at the high end of the mortality distribution as hotspots. Finally, we will classify and characterize hotspots based on their proximity to armed conflicts and ease of access for public health interventions. Identifying those hotspots that relatively safe and easier to reach is a step enabling targeting of public health interventions for near-term improvements. The results will inform targeted programs to reduce mortality and disease burden among the world's most vulnerable populations, ultimately advancing global public health efforts.

NIH Research Projects · FY 2026 · 2025-04

PROJECT SUMMARY/ABSTRACT Noninfectious uveitis is often managed using systemic medications or steroids. Both have undesirable side effects. Local steroid side effects include elevated intraocular pressure, potentially requiring surgery, and cataract formation. Systemic immune suppression has side effects that include end organ damage, certain malignancies, and susceptibility to opportunistic infections. The long term research goal of this proposal is to develop viable long term treatments for ocular inflammation using extended intraocular delivery of biologics and immune modulating peptides. This aligns with the NEI priority to develop steroid therapy alternatives for ocular inflammation without side effects such as cataracts or glaucoma. The objective of this proposal is to develop a refillable micromachined lens capsule based drug reservoir for delivery of adalimumab via diffusion and a novel immune modulating peptide using an encapsulated cell-based therapy. The central hypothesis is that a lens capsule based drug reservoir will be able to safely allow extended pharmaceutical delivery to the anterior and posterior segment of the eye. The rationale underlying this proposal is that completion will identify a new technique of locally delivering non-steroidal based therapies for noninfectious uveitis, allowing localized long term immune modulation with a more favorable side effect profile than current therapies. The central hypothesis will be tested by pursuing two specific aims: 1) characterize and control the release of adalimumab from an engineered lens capsule delivery device in vitro and in vivo; 2) characterize and control cell-based production and release of an immune modulating peptide biopharmaceutical from within an engineered lens capsule delivery device in vitro and in vivo. These two aims will be evaluated using an innovative approach using a microfabricated, collapsible, and refillable intraocular drug delivery device implanted into the lens capsule capable of delivering biologics via diffusion and peptide molecules through cell-based production. Characterization will occur on the benchtop and after implantation into a rabbit model. The proposed research is significant because it has the potential to provide new therapies for ocular inflammation in noninfectious uveitis and may open new avenues for managing other chronic ocular diseases. The expected outcome of this work is an improved understanding of how intraocular cell-based and diffusion based therapies can deliver pharmaceuticals in ocular inflammation. These results will have an important and immediate positive impact because they will establish a new way of treating ocular inflammation locally with extended biologic and peptide delivery without the side effect profile of steroids. The findings of this study will provide the framework for an R01 grant with long term animal implantation testing and will prepare for human clinical testing. This work will help to ultimately determine whether localized continuous biologic and peptide drug delivery can provide improved clinical outcomes.

NIH Research Projects · FY 2025 · 2025-04

Abstract Emerging data indicate that up to 50% of Chronic Obstructive Pulmonary Disease (COPD) results from failure to attain maximal lung function in early adulthood, rather than accelerated decline in lung function later in life. Because lung function trajectories are established soon after birth, deficits in lung function in infancy may persist and predispose to COPD in adulthood. Many preterm infants are born with lungs in the saccular stage of development. Lung inflammation in these infants can lead to bronchopulmonary dysplasia (BPD), a complication of prematurity characterized by altered development with dilated and fewer airspaces in the distal lung. Along with respiratory morbidity during childhood, patients with BPD are at risk for reduced peak lung function in their adult years and may develop COPD. To understand mechanisms connecting aberrant early lung development to long-term abnormalities in lung growth and function, we developed a transgenic model in which IKKβ, an upstream activator of NF-κB, can be expressed in the lungs in a developmental-stage specific manner. Using this model, we found that transient inflammation in the saccular stage (but not the alveolar stage) reduced expression of fibulin-5, a critical elastin assembly component, and resulted in altered elastic fiber organization and dilated terminal airspaces. Remarkably, mice with saccular stage inflammation demonstrated persistent abnormalities in lung elastic fiber organization and developed a COPD-like phenotype with emphysema and loss of alveolar attachments that progressed from 2 to 24 months of age. Neutrophil depletion during the saccular stage rescued the lung phenotype in these mice. Further, we found that neutrophil elastase downregulates fibulin-5 expression by mouse lung fibroblasts and alters saccular stage elastin assembly ex vivo, potentially through activation of epidermal growth factor receptor signaling. These findings support the hypothesis that neutrophil elastase downregulates fibulin-5 expression and alters elastic fiber assembly in the saccular stage lung, thereby predisposing to COPD in adulthood. Specific aims are designed to: 1) delineate the mechanisms by which neutrophils impair elastic fiber assembly in the saccular stage, 2) determine the role and regulation of mesenchymal-derived fibulin-5 in elastic fiber assembly during lung development, and 3) investigate the long-term effects of impaired elastic fiber assembly in the lung. Collectively, proposed studies will determine the impact of inflammation during a critical developmental window on both neonatal and adult lung disease. A mechanistic understanding of the developmental origins of COPD will empower future investigations to prevent and/or treat this debilitating disease.

NIH Research Projects · FY 2026 · 2025-03

Combinatorial Perturbation with Multi-Omics Readout to Dissect Etiology of Alzheimer's Disease Using Stem Cell and In Vivo Models Abstract Alzheimer's disease (AD) is a prevalent age-related neurodegenerative disorder. While early-onset AD is driven by well-characterized genes, the mechanistic links between aging and late-onset AD remain elusive. Human genetic studies have revealed numerous risk alleles that modulate AD susceptibility, but their complex interactions are challenging to study using current tools. We propose to develop Combo-Seq/Tag, a powerful toolkit combining precisely installing multiple risk alleles (Combo-Seq) with a multiplex protein tagging tool (Combo-Tag) for studying endogenous protein interactions. These tools will enable efficient perturbation of AD risk genes and multi-omics readouts in human stem cell models. We will also generate a Combo-Seq/Tag mouse strain compatible with the 5xFAD AD model for in vivo study. Our project will yield innovative products, including multiplex, optimized gene-editing vectors, and rich multi-omics datasets, amplifying the impact of AD human genetics studies. By providing a toolkit to dissect the complex genetic interactions underlying AD pathogenesis, our work will contribute to understanding the mechanistic links between aging and neurodegeneration, potentially revealing novel targets for AD diagnosis and therapy.

NIH Research Projects · FY 2026 · 2025-03

Cleft Lip and Palate (CLP) is one of the most frequent birth anomalies, currently treated with autografts from the iliac crest. This approach involves multiple invasive surgeries and suffers from graft failures and high donor site complications. Currently, the only other viable treatment option is Bone Morphogenetic Protein-2 (BMP-2) based bone regeneration, which offers a less invasive alternative by eliminating the need for autografts. Yet, FDA approval of BMP-2 is currently limitted by two issues: variability in its bone regenerative effectiveness— particularly, clinical meta-analyses indicate a lower efficacy in palatal bone compared to mandibular bone—and its propensity to induce significant tissue inflammation via interaction with immune cells. Thus, there is a critical need to solve significant knowledge gaps on (1) the mechanism behind the varied success of BMP-2 in palatal versus mandibular bone repair and (2) the dynamics between BMP-2 and immune cells to improve the BMP-2 based palate bone repair. As BMP-2 is known to enhance bone repair by activating endogenous skeletal stem cell (SSCs), investigating the palatal bone regeneration from SSC point of view is critical. Dr. Takematsu’s preliminary data suggest that differences in the subpopulations and BMP receptor (BMPR) usage between palatal and mandibular SSCs contribute to variations in bone regeneration. Thus, she will identify how BMP-2 based palatal and mandibular bone regeneration is regulated by SSCs at the cellular and receptor level (Aim1). She will employ single-cell RNA sequencing (scRNAseq) to identify if the differences in SSC subpopulations are responsible for the varied regenerative capacities. To understand how different BMPR utilizations by SSCs lead to diverse regenerative results, she has engineered a surrogate BMP-2 made of a bispecific nanobody. This innovative tool will pair the specific BMPRs, allowing the investigation of their interactions and bone regenerative capacity of SSCs. Building on her preliminary data that indicate neutrophils (NPs) contribute to inflammation, she will identify the interactions between NPs and SSCs in the palatal bone regenerative interface and develop safe bone regeneration strategies using the surrogate BMP-2 (Aim2). She will examine the genetic interplay between NPs and SSCs in palatal bone defects repaired by BMP-2 using scRNAseq and will develop strategies to mitigate NP-induced inflammation. By leveraging the differential BMPR expression between NPs and SSCs, she can also create the surrogate BMP-2 to selectively activate SSCs and avoid NP- induced inflammation. This project will advance Dr. Takematsu’s career goal of becoming an investigator specializing in craniofacial SSC biology with an emphasis on osteoimmunology, aiming to control the complex immune interactions and improve the protein therapeutics for craniofacial bone repair. With the mentorship and a research-enriching environment at Stanford University, she will be well-equipped for applying to an independent faculty position. The K99/R00 research will yield robust data to support a R01 proposal, focused on developing safe and effective bone regeneration strategies to repair various craniofacial bone defects.

NIH Research Projects · FY 2024 · 2025-03

Project Summary The ability of an infant to distinguish caregivers from strangers is a fundamental behavior for survival early in life. Across many taxa, infants use olfactory cues to recognize caregivers. Although the survival of neonates depends on this behavior, we do not fully understand the neural mechanisms behind the olfactory encoding of social identity. This is partly because there is a lack of robustly identifiable and ethologically relevant behaviors in well-established animal models. Since all altricial animals rely on parental care for survival and children with developmental disorders (e.g., fragile X syndrome and autism) often have altered olfactory perception, it is essential to understand the mechanisms for linking caregiver odors with affiliative behavior. This proposal seeks to illuminate the neural circuitry underlying olfactory recognition of caregivers in neonatal vertebrate brains using in vivo imaging and molecular tools in social and translucent tadpoles, Ranitomeya imitator. R. imitator tadpoles recognize their caregivers using olfactory cues and display a distinct begging behavior to them, allowing us to decode parental recognition. The combination of in vivo brain imaging and complex behavior in R. imitator makes them uniquely suited for decoding neural circuitry of the developing vertebrate brain. This proposal will test the hypothesis that exposure to social olfactory cues during development modifies the catecholaminergic circuitry in the brain to encode caregiver identity and facilitate behavioral output to receive care from caregivers. The applicant, Dr. Akbari, will use a combination of techniques in behavioral and molecular neuroscience to identify the neurons responsible for caregiver recognition. To test the functional role of distinct neuronal populations in enabling caregiver recognition, pharmacological manipulations will be applied to each brain region. Dr. Akbari will identify cell types involved in social bond formation using single nucleus RNA sequencing. Additionally, the combination of neural tracing and two-photon in vivo imaging will allow the dissection of the circuitry underlying this vital social behavior. This training plan will enhance Dr. Akbari’s background as an optical scientist by adding new experimental techniques in neuroscience to her skill set to prepare for a career in research. Dr. Akbari will learn behavioral and molecular neuroscience techniques from Dr. O’Connell and expand on her computational techniques to analyze calcium activity data with guidance from Dr. Schnitzer. The unique combination of expertise of the mentorship team, Drs. O’Connell and Schnitzer, as well as the fostering environment and excellent resources of Stanford University, will prepare this candidate for leading an independent research program in experimental neuroscience, focused on understanding how the developing vertebrate brain encodes social identity in healthy and disease states.

NSF Awards · FY 2025 · 2025-02

Much can be learned about how an organism functions by understanding how its cells and tissues are organized. Cells are very small and so they can best be observed with specialized techniques like electron microscopy. Samples must be preserved carefully for study by electron microscopy and care must be taken not to introduce changes that could mislead interpretation of observations. The best method for preparing tissue for electron microscopy is to rapidly freeze samples and observe them under very low temperatures, a process called cryogenic preservation. Cryopreservation is challenging in plants, and the goal of the proposed research is to develop procedures that overcome these challenges. If successful, this proposal will allow plant cells and tissues to be observed after cryopreservation and give unprecedented information about how parts of plant cells and tissue work together. Understanding how plant cells work will help develop plants that are better able to meet human needs and ensure food security. The methods developed will be shared with others through public databases to allow other scientists to use the methods in their own studies. The research will include several early career scientists, and they will receive training in techniques and develop skills which are in high demand in science labs and in industry. Cryogenic preservation is the gold standard for determining cell ultrastructure in its “native state” by virtue of physical fixation (freezing) to immobilize cell constituents in milliseconds. Volume electron microscopy (vEM) has gained significant traction as a tool for discovering the structure and spatial organization of cell and tissue components. In combination with cryo-electron tomography (cryoET), cryo-vEM has the potential to yield a paradigm shift in multi-scale in situ structural biology. However, due to their physical and chemical properties, plant cells are uniquely recalcitrant to fixation. Thus, plant science is strikingly lagging other fields in the revolution of understanding of how macromolecular complexes and cell compartments coordinate to create life. Determining the structure of cells and organelles in fully frozen hydrated chemically untreated and unstained would allow, for the first time, the observation of these entities in their native states. This proposal will develop cryopreservation and nanoscale imaging procedures for vEM of plant tissues in a focused effort to address this challenge efficiently for the plant community. Whole cell structures will be elucidated in 3D using cryo-vEM, while nanoscale cellular structure and organelles will be determined using cryo-vEM and cryo-ET. The datasets, protocols, and analytical pipelines generated through this research will be made available to the scientific community and the public through public databases. The proposed work will also provide unique training opportunities for several students and postdocs, training them in state-of-the plant structural biology, much desired expertise in the scientific workforce. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NSF Awards · FY 2025 · 2025-02

From self-driving vehicles to autonomous drones, machine learning-driven perception components constitute a core part of modern autonomous systems and robots. Autonomous system capabilities are primarily enabled by the ability of modern machine learning methods to elegantly process rich perceptual inputs and outputs so as to produce useful information for control, ultimately enabling robots to make intelligent decisions in novel situations based on what they see. However, perception failures can cascade to catastrophic robot failures and compromise human safety, as exemplified by recent self-driving car accidents. Therefore, ensuring safe robot operation under learning-driven, perception-based controllers is paramount to enable their adoption in high-integrity and safety-critical applications. This project will establish a foundational framework for providing continual safety assurances for closed-loop systems under a perception-based controller, wherein assurances are provided provisionally at training time, and continually monitored, updated, and improved during operation-time (or runtime). In particular, this project will: (a) develop novel techniques for learning robust-by-construction perception policies; (b) construct safety monitors for perception policies to ensure their safe operation during runtime; and (c) develop a principled approach to mine closed-loop perception failures at scale and use them to improve robot safety over time. These results will be grounded through a thorough evaluation on a heterogeneous physical robotic testbed, as well as photorealistic simulators, with a focus on autonomous inspection and autonomous aircraft landing tasks. The ability to develop safe perception-driven systems will have a direct, positive impact on a broad range of robotics applications where safety and reliability are of high importance, such as surveillance of critical infrastructure, service or delivery robots, and autonomous cars. This impact will be enhanced through: (a) an integrated education and outreach plan designed to facilitate robot safety discussions and educate faculty and students at all levels: K-12, undergraduate and graduate students, and the broader robotics research community; (b) close collaborations with industry and regulatory bodies; and (c) focusing on disseminating codebases and implementations, and open-sourcing curriculum materials for a new robotics course including hands-on labs with wheeled robots. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NIH Research Projects · FY 2026 · 2025-02

The advent of endovascular therapy (EVT) has revolutionized the treatment of acute ischemic strokes (AIS) caused by large vessel occlusions, affecting up to 700,000 Americans annually. However, despite this significant advance, the current approach to EVT patient selection, primarily based on neuroimaging, inadequately addresses the full spectrum of stroke pathophysiology and patient-centered aspects of care, especially long-term functional outcomes. This shortfall is evident in the lack of integration of essential data from clinical notes, which include detailed patient medical history, symptomatology, and lifestyle factors pre-stroke. Notably, there has been limited research on how a more comprehensive approach to patient data could enhance EVT patient selection. Addressing this gap would significantly advance our ability to predict long-term outcomes in AIS patients, with and without treatment, improving EVT patient selection and ultimately clinical outcomes. This proposal aims to address a vital gap in stroke patient care by moving beyond traditional imaging-centric methods to develop a Fused Imaging and Large Language Foundational Model (FILLM). Leveraging advancements in deep learning and large language models, FILLM is a significant innovation that integrates unstructured clinical notes, imaging, and structured tabular clinical data, revolutionizing the prediction of long- term outcomes for stroke patients. The project's three primary objectives include developing and testing FILLM to predict 90-day outcomes in AIS patients, assessing its generalizability and bias reduction capabilities, and enabling optimal collaboration between the FILLM model and clinicians. The training and testing of the FILLM model will use retrospective data from multiple previous clinical trials, as well as registry data from Lausanne, Johns Hopkins, Stanford University hospitals. A key component of this project is the comprehensive career development plan during the K99 phase, which includes mentorship from experts in radiology, neurology, and computer science. This plan involves hands-on training in multi-modal deep learning AI, active engagement in the clinical application of FILLM, and immersive learning experiences through clinical shadowing and academic coursework. These activities, designed to foster essential skills for independent research in the R00 phase, align closely with the research goals, ensuring a holistic approach to both scientific inquiry and career development. Upon successful completion, this project will significantly better our ability to triage EVT patients using data- driven approaches, promoting a more personalized approach to patient care. The NIH's investment in this project will not only bridge a critical gap in stroke treatment but also facilitate my progression to an independent researcher, ready to spearhead future innovations in stroke research.

NIH Research Projects · FY 2026 · 2025-02

PROJECT SUMMARY The human sense of touch plays a crucial role in our perceptual experiences and enabling motor tasks. Amputation, diabetes, stroke, and a host of other diseases result in loss of touch sensation, affecting modalities including vibration, skin deformation, proprioception, temperature, and pain. When haptic sensory loss is localized to a part of the body, or only certain components of touch sensation are missing, haptic stimulation through wearable actuators at an alternative body part or using an alternative haptic modality has been proposed to replace it. The goal of this project is to develop the specifications for wearable devices that act as haptic sensory prostheses, laying the groundwork for later disease-specific implementation and testing. We propose to (1) exploit attributes from both cutaneous and deep tissue sensation to communicate levels of intensity of a signal, and (2) use new methods integrating 3D printed soft actuators with patterned knit enclosures to enable wearable devices that can provide this stimulation. We will invoke spatial summation with larger pressures resulting in deep tissue stimulation to increase the range of applied. A range of pressures and multiple contacts on arm will act as a sensory substitute for missing, low-dimensional haptic sensation elsewhere in the body. We will determine the feasibility and potential of this approach in two aims in both younger and older adults: Aim 1: Identify appropriate pressure intensity range and resolution for multipoint contact pressure. We will measure human perception of single and multipoint contact stimuli. The outcome of this aim will be a characterization of the extent of spatial summation occurring for a range of pressure stimuli and a public dataset for human perception of single and multipoint contact pressures at the stated locations. Aim 2: Characterize the ability of humans to interpret two-degree-of-freedom information from a multipoint contact pressure haptic sensory prosthesis. The outcome of this aim will be a measure of the effectiveness of the deep pressure stimulation devices for improving the control of the arm position. We intentionally scope this R21 proposal to test the highest-risk aspects of this methodology and develop data that leads to future research and implementation to address diseases involving haptic sensory loss by our team and others. Such future research includes the development of wearable haptic devices that meet the identified specifications, characterizing the best type and location of haptic feedback to act as a sensory prosthesis, and understanding and exploiting human adaptation to high-degree-of-freedom mappings between missing and substituted haptic feedback.

NSF Awards · FY 2025 · 2025-02

Grant Rotskoff of Stanford University is supported by an award from the Chemical Theory, Models and Computational Methods program in the Division of Chemistry to develop machine learning models to predict and analyze the fluctuations of biomolecules, such as proteins. Understanding both the biological function and material properties of biomolecules requires information about their different “shapes” or conformations alongside energetic information, but traditional computational methods based on molecular dynamics simulation are often prohibitively computationally expensive. This project aims to make studying complex biological molecules faster and more efficient using generative models conceptually similar to the AI models used in image or text generation. The PI’s approach combines these generative AI techniques with physics-based, simplified molecular models to ensure that predictions remain robust even far from the training data. The PI will also develop tools to verify the accuracy of these predictions and will assess the model across many different proteins. The tools developed in this project will enable studies of proteins that lack a stable folded structure, which remain poorly understood despite their relevance for human disease. Dr. Rotskoff plans to create educational materials about these new computational methods, including a new undergraduate course at Stanford University and online resources for high school students and teachers. In the proposed project, Grant Rotskoff seeks to develop scalable and transferable models for sampling conformational ensembles of biomolecules by integrating neural networks developed for density estimation with coarse-grained models. The overarching goal of this project is to construct quantitatively accurate configurational ensembles of a diverse array of molecular systems at a substantively lower computational cost than classical molecular dynamics by “back-mapping” coarse-grained configurations to atomistic resolution. The PI will build a theoretical framework for evaluating and optimizing both the parameterization of coarse-grained models and the generative neural networks, which will help guide model development and evaluation. In addition, the PI will develop and evaluate transferable generative modeling strategies with the goal of improving generalization when data is limited. Parameterizing these models from peptide fragments will enable transferability across a large range of proteins, further reducing data cost. Finally, the PI will develop a rigorous toolkit for computing dynamical quantities, such as isomerization rates, from back-mapped coarse-grained simulation data. Rotskoff’s educational plan includes i) development and refinement of a new undergraduate course at Stanford University, ii) development of interactive, online tutorials about generative models for chemical systems targeting high-school level students, and iii) open-source teaching modules for high-school chemistry teachers. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NIH Research Projects · FY 2026 · 2025-02

Patient and family groups (PFGs) have long supported rare disease research as fundraisers and advisers. But today, they increasingly drive the research agenda, working in partnership with academic institutions, drug developers, and regulators to shepherd new therapies from basic research to commercialization. While patient engagement has become common in many areas of biomedical research, this model of PFG-led, therapy-focused, collaborative research— known as “patient-focused drug development” (PFDD)—is especially prominent in the rare disease space, where small patient populations, dispersed expertise, and limited financial incentives for drug discovery necessitate active engagement of PFGs across the drug development pipeline. When collaborations are successful, PFDD can fuel scientific advancement and accelerate cures for rare diseases with limited therapeutic options. However, this emerging model has also created new ethical challenges, as PFGs and their partners navigate competing values, interests, and expectations throughout the PFDD process. These ethical challenges have the potential to disrupt PFDD, erode trust and consume scarce resources, but they remain poorly understood. The objective of this proposal is to gain a multi-perspective account of ethical challenges raised by PFDD in rare diseases and to use collaborative methods to develop tools to manage these challenges. Our proposal includes three specific aims. Aim 1: To explore stakeholder perspectives on the ethical challenges arising in PFDD, as well as ways in which they currently manage these challenges, through semi-structured interviews with representatives of key stakeholder groups including PFGs representing a variety of rare diseases, academic institutions, industry partners, government agencies and rare disease umbrella organizations. Aim 2: To characterize the values, interests, resources, roles, and relationships of stakeholder groups, and to identify nodes of conflict and alignment of values and interests within and across groups, suggesting additional ethical challenges and management strategies, using the framework of stakeholder analysis. Aim 3: To evaluate the tradeoffs and downstream implications of potential strategies for managing ethical challenges identified in Aims 1 and 2, to seek multi-stakeholder consensus regarding recommended strategies, and to develop an implementation strategy. We will engage representatives of key stakeholder groups in a conventional Delphi panel consisting of three rounds of iterative surveys and an in-person consensus meeting. Our study will culminate in an “ethics roadmap” outlining the ethical challenges stakeholders may encounter in PFDD and recommended approaches to managing or resolving these challenges. The roadmap will have a positive impact by helping stakeholders anticipate, understand, and respond to the ethical challenges they may encounter at each stage of PFDD. Future work will evaluate the impact of the roadmap on the process and outcomes of PFDD for rare diseases and will seek to adapt it for other types of research.

NSF Awards · FY 2025 · 2025-02

This project focuses primarily on three different problems in number theory, combinatorics, and ergodic theory. This includes work in additive combinatorics concerning generalizations of Szemerédi's theorem on arithmetic progressions (sequences of numbers that are all equally spaced, like 4, 6, 8, and 10), which, informally, says that any sufficiently large collection of whole numbers contains a long arithmetic progression. It is a central problem in additive combinatorics to determine how large "sufficiently large" is. The investigator will study versions of this question involving more complicated patterns than arithmetic progressions, and then use the results and techniques developed to make progress on a related problem in ergodic theory. The investigator will also study the size and structure of integer distance sets, which are sets of points whose pairwise distances are all whole numbers. This award will support undergraduate summer research on representation theory and additive combinatorics, and also support the training of graduate students. More specifically, the investigator will build on her previous work on quantitative bounds for subsets of the integers lacking polynomial progressions of distinct degrees and for subsets of vector spaces over finite fields lacking a certain four-point configuration to tackle more general polynomial, multidimensional, and multidimensional polynomial configurations. The results for multidimensional polynomial configurations of distinct degree will then be used to make progress on the Furstenberg--Bergelson--Leibman conjecture in ergodic theory, which concerns the pointwise almost everywhere convergence of certain nonconventional ergodic averages. She will also investigate the size and structure of integer distance sets, in both the Euclidean plane and in higher dimensions, by encoding them as subsets of rational points on certain families of varieties and then studying these varieties. With her undergraduate students, the investigator will study the distribution of entries in the character tables of symmetric groups and some algorithmic problems in higher-order Fourier analysis. 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 · 2025-02

OVERALL ABSTRACT The VAST (Viromes Across Spaces and Time) Center proposes to comprehensively identify the human- associated virome and characterize the viral constituents through a unique set of longitudinal samples collected from healthy individuals. To advance our understanding of the human virome, we will employ innovative approaches by accessing unique, well-phenotyped cohorts, exploring diverse lifestyles, engaging with underrepresented communities, utilizing cutting-edge methods for virome-focused microbiome profiling, and emphasizing absolute quantification of viruses rather than relying solely on relative abundance measurements, while also using spatial imaging technology to delineate viral tropism at the subcellular level. The participating laboratories have collected longitudinal samples from a number unique cohorts including: a) densely profiled samples from ~171 extensively characterized individuals who have been tracked for up to 13.5 years. Subsets have performed dietary interventions (e.g. fiber supplementation) and lifestyle changes have been tracked; b) individuals who have been to low earth orbit or Antarctica; c) members of underserved groups such as Native Americans, Hispanics and African Americans, d) children from underserved groups who have undergone an exercise intervention; e) individuals who have had their associated airborne samples (exposome) collected; f) many others. We propose to characterize the virome in depth from these individuals and correlate virus presence, abundance and changes with features of the cohort: location, ethnicity, diet, and perturbations including location (space) and lifestyle (diet, exercise).