Stanford University

NIH Research Projects · FY 2026 · 2025-06

Myocardial infarction (MI) is a leading cause of death in the United States, affecting over 800,000 people annually. Numerous strategies have been developed to treat MI, but effective delivery of protein therapeutics to the heart remains a formidable challenge. Systemic, intravenous (IV) delivery results in low tissue specificity and rapid loss of bioactivity, necessitating high dosing, repeated administration, and/or long treatment periods. On the other hand, direct injection of therapeutics into the myocardium commonly results in rapid clearance due to the heart’s contractility. To address this critical need for a technology that provides (i) sustained bioactivity and (ii) tissue-localization of protein therapies, we propose a new type of injectable, biodegradable hydrogel. This novel biomaterial has a unique molecular structure, with hyaluronic acid (HA) biopolymers bridging between self- assembled lipids to form a liposome network crosslinked hydrogel (HA-LINC). The reversibility of lipid self- assembly into multilamellar liposomes allows the covalently crosslinked gel to be easily injectable and self- healing, while also providing a means for sustained delivery of bioactive protein. As a proof-of-concept test case, we will develop the HA-LINC hydrogel to deliver neuregulin-1β (NRG1), a promising recombinant protein therapy that currently requires 10-hour intravenous delivery for clinical efficacy. In Aim 1, we will evaluate the hypothesis that our unique strategy of crosslinking a hydrogel through lipid self-assembly will result in the formulation of stiff yet injectable hydrogels, resulting in tissue-localization of protein therapies. We will synthesize a library of HA- LINC hydrogels by tuning liposome functionalization, HA functionalization, and HA concentration. Viscoelastic mechanics, in vitro catheter injectability, and in vivo cardiac retention in a rat MI model will be quantitatively evaluated. In parallel, in Aim 2, we will evaluate the hypothesis that chemically stabilized, multilamellar liposomes can achieve sustained bioactivity of encapsulated protein drugs by preventing protein degradation and providing controlled release. Liposomes with varying degree of internal stabilization will be quantified for size, shape, and cargo release rate. Bioactivity of released NRG1 will be quantified using human cardiomyocytes and cardiac fibroblasts. In vivo NRG1 will be quantitatively evaluated using a 2-compartment pharmacokinetic model. In Aim 3, the biopolymer network chemistry with the best tissue-localization (Aim 1) and the engineered liposomes with the optimal NRG1 sustained bioactivity (Aim 2) will be evaluated in vivo for therapeutic functionality. Following induction of MI through ligation of the left anterior descending (LAD) artery, animals will be randomly assigned into one of 5 treatment groups: sham, HA-LINC hydrogel with NRG1 encapsulated into stabilized liposomes, HA-LINC hydrogel only, free NRG1 in HA-LINC hydrogel, and NRG1 encapsulated into stabilized liposomes without gel. We will evaluate treatment effects on cardiac function, immune response, tissue remodeling, gel retention, cardiomyocyte survival, angiogenesis, and expression of proinflammatory and reparative factors.

NSF Awards · FY 2025 · 2025-06

Non-Technical Abstract Modern materials must be both adaptive and multifunctional, yet most synthetic surfaces lack the ability to dynamically change in response to external forces. This research will investigate two-dimensional (2D) materials that combine viscous and elastic properties, allowing them to reorganize, self-heal, and transform under mechanical stress. By coupling soft polymer networks with thin membranes, this project will develop a new class of 2D materials with tunable mechanical and material properties. These materials could enable self-repairing coatings, smart membranes for filtration, and responsive biomedical interfaces. Beyond research, this project will integrate education through public speaking workshops, helping students communicate complex scientific ideas to broad audiences. The project will also provide research and communication training for undergraduate students who will become future leaders in the STEM workforce. By advancing both fundamental materials science and STEM workforce, this work will support the National Science Foundation’s mission to promote scientific progress and national prosperity. Technical Abstract This research program will investigate the mechanics and phase behavior of 2D materials that combine viscous and elastic properties under nonequilibrium forces. Specifically, it will study how active forces reshape multiphase lipid membranes coupled to driven polymer networks, forming dynamic composite materials with tunable properties. While the behavior of bulk active materials is well-studied, the interplay between viscoelasticity and active flows in confined 2D surfaces remains largely unexplored. To address this gap, this research will integrate experimental and theoretical approaches to uncover how local stresses drive structural transformations in phase-separating 2D surfaces. Experimental efforts will focus on engineering lipid-polymer membranes, generating active forces using actin-myosin networks, and analyzing microstructure evolution through advanced microscopy techniques. Theoretical work will develop phase-field models and numerical simulations to predict the effects of actin network elasticity, interfacial tension, and active stresses on material properties. Our theory will elucidate the coarsening mechanisms of viscous 2D droplets embedded within a viscoelastic heterogeneous network. By establishing new design principles for adaptive 2D materials, this project will advance soft matter physics, materials science, and biomaterials engineering. This project will also integrate education and research through structured science communication workshops that train students to effectively convey technical ideas to broad audiences. Additionally, outreach efforts will increase participation of students who will become future leaders of the STEM workforce. This work supports the National Science Foundation’s mission by advancing fundamental research, promoting technological innovation, and strengthening the future STEM workforce through interdisciplinary training at the interface of physics, materials science, and engineering 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 · 2025-06

Climate change, water resources, and human activities are coherently interconnected. Increased temperature due to greenhouse gases likely exacerbates the severity, frequency, and duration of hydrological extremes, such as droughts, flooding, and convective storms. Moreover, atmospheric aerosols from various sources also regulate precipitation intensity and efficiency via interactions with convective clouds and large-scale circulations, while those effects have not yet been fully accounted for in the present climate models. The overachieving scientific objective of this project is to advance the process-level understanding of anthropogenic aerosol on precipitation extremes. A series of critical science questions will be addressed in the project: to what extent extreme precipitation is sensitive to cloud and aerosol physics in a new-generation global weather/climate model; whether local precipitation extremes are linked to local and remote aerosol variations; what type of aerosol effect exerts larger impacts on convective precipitation. Results from the project will provide scientific evidence for policymakers to frame effective actions to address the potential flooding and drought issues in the future climate. This five-year project plans to first improve the extreme precipitation simulation by enhancing the representations of aerosol and cloud microphysics in a fully compressible non-hydrostatic global climate model with regional refinement capability, Model for Prediction Across Scales (MPAS), to convection-permitting scale. The complex impacts of anthropogenic aerosols on cloud and precipitation will be untangled under this modeling framework. The aerosol-aware MPAS will be evaluated against a suite of available ground-based and spaceborne observations. It will be further employed to assess the responses of crucial weather systems that regulate the variability of the water supply and the incidence of extreme precipitation events over East and South Asia as well as the western US, such as the Asian summer monsoons, the mid-latitude storms, and Atmospheric Rivers. The program will also train students through project-based learning by integrating extreme weather and air pollution research into graduate/undergraduate curricula. Outreach activities of the program will directly engage high school students in the research program and raise environmental and climate awareness among students and the public via student mentoring programs and a summer workshop. 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 · 2025-06

Project Summary Many neurodegenerative diseases share neuropathological and clinical features. If this overlap is any indication of shared pathogenic mechanism, therapeutic targeting of such mechanism may have the potential to alleviate a broad spectrum of diseases. Hyperphosphorylation and aggregation of tau is a pathological hallmark of primary tauopathies such as Frontotemporal Dementia (FTD) and Progressive Supranuclear Palsy (PSP) and secondary tauopathies that include some of the most common neurodegenerative diseases such as Alzheimer's disease (AD), and possibly Parkinson's disease (PD) and Huntington's disease (HD). Tau abnormality and beneficial effects of tau reduction have also been observed in experimental models of autism, depression, epilepsy, stroke, and traumatic brain injury, even though these models may not develop prominent intraneuronal accumulations of tau aggregates as in primary or secondary tauopathies. Dysfunctional mitochondria is also a prominent feature of the above diseases. Whether tau abnormality and mitochondrial dysfunction are mechanistically connected and can be targeted together to treat common neurodegenerative diseases is a key question this project aims to address. To effectively target tau, a deeper understanding of its normal physiological function as well as its pathogenic role in disease is needed. Previous studies revealed extensive tau interaction with mitochondrial proteins, and studies in animal models and humans have revealed a specific link between tau and mitochondrial complex-I (C-I) dysfunction, although the exact mechanism is unclear. C-I is the largest multisubunit complex of the respiratory chain, containing 45 subunits in humans. Despite the essential role of C-I in mitochondrial function and bioenergetics, partial but not complete inhibition of its specific subunits offered beneficial effects on lifespan or age-related neurodegenerative disease across species. The molecular mechanism underlying this phenomenon is not well understood. Our recent studies on C-I mediated reverse electron transfer (RET) have offered some clues. Under certain thermodynamic conditions, for example when forward electron transport (FET) is blocked while membrane potential (MMP) is still high, RET will prevail, moving electrons from CoQH2 back to the NAD+/NADH binding site of C-I, producing a significant amount of ROS (RET-ROS) and lowering NAD+/NADH ratio. RET is considered a major source of mitochondrial ROS production, and our recent studies indicate that it is also a main determinant of mitochondrial and cellular NAD+/NADH ratio. In Preliminary Studies, we find that RET is activated during aging and in age-related neurodegenerative diseases such as FTD, AD, PD, and HD, and that genetic reduction of select C-I proteins involved in RET or pharmacological inhibition of RET is beneficial in these conditions. The goal of this study is to use in vivo animal models and human iPSC-derived cell culture models to investigate the mechanism of RET regulation by tau and how tau-induced RET deregulation contributes to a broad spectrum of age-related neurodegenerative diseases including AD and AD related dementias (AD/ADRD).

NIH Research Projects · FY 2026 · 2025-06

Project Summary/Abstract Cannabis is the most widely used illicit drug among adolescents ages 14 -18 in the United States. Research demonstrates cannabis use is not harmless, especially given that the adolescent brain is particularly susceptible to dependence, and due to cannabis-related risks to the lungs, increased risk for depression, and decreased academic performance. Despite these health risks, since the mid-2000s, adolescents’ perceived risk of cannabis use has declined, and adolescents’ approval of cannabis use has increased. To date, very few comprehensive programs addressing adolescents’ misperceptions and knowledge about cannabis and preventing and reducing the use of all cannabis products have been developed, evaluated, or widely disseminated throughout the U.S. To address this gap, using a community-based participatory research approach in which we included a large group of adolescents and young adults, parents, educators, and healthcare providers with expertise in addiction medicine, we developed the “Smart Talk: Cannabis Prevention & Awareness” (Smart Talk) curriculum, which includes 5 lessons focused on health and environmental affects of cannabis, marketing, stress and coping, and refusal skills. Aligning with the NIH Stage Model for Behavioral Intervention Development, and through an NIH R34 grant in which we conducted a pilot randomized control trial with six schools, we have addressed 3 of the 6 stages needed to adequately develop, evaluate, refine, and fully implement and disseminate our Smart Talk curriculum. Our next step is to conduct a full evaluation to determine the real-world efficacy and effectiveness of the Curriculum (Stages III-IV), to determine for whom the Curriculum is most and least effective, and to further implement and disseminate the Curriculum (Stage V). As such, using a cluster-randomized trial, stepped-wedge design, with 30 middle and 30 high schools in California and New York (n=10,800 students), the Specific Aims of this proposed project are to: (1) Determine whether the Smart Talk Curriculum is effective in increasing adolescents’ knowledge of the different forms of cannabis and resistance to using and decreasing their positive attitudes towards and intentions to use cannabis products; (2) Determine whether the Smart Talk Curriculum is effective in changing adolescents’ actual use of different forms of cannabis (including preventing initiation, continuation, escalation; encouraging decreased use and cessation; and reducing co-use of cannabis and tobacco use); and (3) Examine the heterogenous treatment effects (HTE) of the intervention, identifying both those who benefit the most and those who do not benefit from the curriculum. The timing of this proposed research is extremely important given the rates of cannabis use in adolescence, legalization of cannabis across the country, and need for comprehensive cannabis education and prevention programs. Already we have hundreds of schools implementing Smart Talk, so determining the real-world effects of the curriculum and revising the curriculum as needed will further address the needs of schools and adolescents.

NSF Awards · FY 2025 · 2025-06

The space between the stars is not empty: interstellar space is filled with diffuse gas and dust, and threaded by invisible magnetic fields. This material is the interstellar medium (ISM), the stuff out of which new stars are born. The ISM is a wonderful physics laboratory. It is sculpted by a rich array of physical processes, and so observations of the ISM can be used to decipher the poorly understood physics that governs the formation of stars and the evolution of gas in galaxies. Astronomers observe the ISM in many wavelengths of light. This proposal will develop novel tools to unlock the physical information encoded in those observations. This work will generate a new understanding of the gas, dust, and magnetic fields in our Milky Way galaxy. Because the ISM obscures our view of light from the very early universe, this work will also help clear the way for cosmological discovery. This proposal will also build tight links between cutting-edge research and education, impacting students from high school through graduate school. This project will 1) develop a suite of pedagogical Jupyter notebooks to enable active learning in graduate ISM education, 2) host a workshop on integrating computational tools into the classroom, and 3) develop a new dual-enrollment astrophysics course focused on modern approaches to data-driven inference, serving low-income high school students. This proposal will develop cutting-edge methodologies for physical inference with complex data. The researchers will pursue a new approach to determining the phase structure of interstellar gas, and therefore to understanding the evolution of gas in galaxies. This work will open new avenues of inquiry by building computational tools to compare data and numerical simulations in high-dimensional spaces, and will reveal new insights into the magnetic structure of the ISM. This work will also build a new approach to modeling the structure of polarized dust emission from our Galaxy. This project also aims to realize the promise of the ISM for teaching and learning the universe. 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 · 2025-06

PROJECT SUMMARY/ABSTRACT Schizophrenia affects 0.5-1% of people worldwide and features a loss of properly-structured relational knowledge, manifested as dramatic disorganization of thought, delusions, hallucinations, and profound deficits in core cognitive functions. The hippocampus – the seat of relational information processing – plays a key role in the pathogenesis of schizophrenia, with evidence suggesting a loss of normal inhibitory tone, disrupted neural oscillations, and reduced connectivity with a distributed network of neocortical regions. A breakdown in the or- ganization of hippocampal oscillations and hippocampal-cortical interactions may therefore underlie schizophre- nia symptoms, but we do not know whether these signatures are responsive to neuromodulation. Intriguingly, theta burst-stimulation (TBS) mimics the endogenous hippocampal 3-8 Hz theta rhythm and has been used to alter hippocampal function in healthy humans by targeting the posterior parietal node of the hippocampal-cortical network. The overarching goal of this research and training plan is to ask whether connectivity-guided TBS to this parietal node can affect hippocampal neural activity and cognitive function in the context of schizophrenia. I propose a combination of invasive and non-invasive brain stimulation experiments that will bridge core hippo- campal electrophysiology with approaches that can be readily deployed in the schizophrenia population. I will first ask how direct electrical TBS influences hippocampal oscillations via intracranial recordings from neurosur- gical patients (Aim 1), and then use non-invasive TBS delivered via transcranial magnetic stimulation (TMS) to explore effects in schizophrenia patients via scalp electroencephalography (EEG; Aim 2). Finally, I will ask whether TMS-delivered TBS can enhance hippocampal cognitive function in schizophrenia, by stimulating pa- tients between sessions of an associative inference task (Aim 3). This research will advance our understanding of how the hippocampus responds to theta burst stimulation, and whether we can use this form of stimulation to alter hippocampal physiology and cognitive function in patients with schizophrenia. My extensive background in human intracranial electrophysiology and hippocampal memory function – as well as my clinical training – makes me uniquely qualified to pursue this clinically-relevant research that stays grounded in basic neuroscience. I will rely on a mentoring team of world-class experts in invasive and non-invasive brain stimulation and schizophrenia: Drs. Corey Keller, Josef Parvizi, and Jacob Ballon, with Drs. Karl Deisseroth and Fabio Ferrarelli as advisors. In completing this work, I will deepen my understanding of connectivity-guided intracranial stimulation, develop expertise in the use of combined TMS and scalp EEG, and learn how to design, recruit, and execute a study in a unique clinical population. Stanford University and Medical Center provide the ideal multidisciplinary environ- ment to carry out this deeply translational work. When complete, this proposal will address a major gap in our understanding of hippocampal pathophysiology while preparing me to launch an independent research career that leverages invasive and non-invasive neuromodulation in psychiatric populations.

NIH Research Projects · FY 2025 · 2025-05

Summary: Multiple sclerosis (MS), a chronic, demyelinating, neuroinflammatory disease typically affecting young adults, often results in neurological deficits as disease progresses. Although multiple disease-modifying immunomodulatory therapies are available for MS, disease manifestations and treatment response are highly variable and difficult to predict in patients. Current standard of care imaging techniques used to diagnose and monitor MS unfortunately cannot provide early and specific molecular information regarding an individual’s immune signature in the central nervous system (CNS), thus limiting our ability to select the most appropriate therapy and obtain early predictors of response for any given patient. As such, there is a need for non-invasive molecular imaging strategies that provide real-time information about specific immune cells and their functional phenotypes in MS patients. Activated macrophages and microglia are the predominant immune cells associated with acute and chronic-active CNS lesions, suggesting that the combined presence, extent, location, and temporal dynamics of reactive macrophages/microglia have the potential to serve as clinically meaningful biomarkers of active MS. Unfortunately, existing imaging strategies for detecting activated macrophages and microglia lack specificity and cannot distinguish between beneficial (anti-inflammatory) and toxic (pro- inflammatory) immune responses. To address this limitation, we recently developed a novel 4th generation hydroxyl dendrimer PET radiotracer, [18F]OP-801, that is known to be selectively taken up (>95%) by reactive microglia and macrophages. This radiotracer, recently approved for clinical use, has shown tremendous promise in a murine model of sepsis, and we have generated encouraging preliminary data in a mouse model of chronic MS. Here, we propose to utilize [18F]OP-801 in two mouse models of MS (chronic and relapsing-remitting) across multiple disease stages, to assess the relationship with disease severity and central/peripheral inflammation, as well as monitoring responses to an FDA-approved immunomodulatory therapeutic. We hypothesize that [18F]OP- 801 can be used to detect and quantify in vivo macrophage- and microglia-driven immune responses in rodent models of MS, and that [18F]OP-801-PET can accurately predict disease progression and response to therapies. We will test our hypothesis with the following specific aims: 1) Characterize the relationship between [18F]OP- 801-PET signal, disease severity, and markers of central and peripheral inflammation in two mouse models of MS, and 2) Assess the ability of [18F]OP-801-PET versus TSPO-PET to predict and monitor responses to an FDA-approved immunomodulatory therapeutic. We therefore aim to establish the sensitivity and potential utility of [18F]OP-801 prior to use in MS patients. This research promises to provide critical in vivo information about the role and time course of macrophage- and microglia-driven immune responses in EAE and MS. Our proposed strategy using [18F]OP-801-PET could have far-reaching and significant impact as a clinically useful molecular imaging technique for mapping harmful innate immune activation in a range of neurological diseases.

NIH Research Projects · FY 2026 · 2025-05

Alzheimer’s disease (AD) is the most common cause of dementia among people over the age of 65, affecting an estimated 5.5 million Americans. It is now well-established that drug trials based on evidence with a genetic basis are more likely to succeed. However, known genetic markers identified by current genome-wide association studies (GWAS) only explain a small fraction of heritability for late-onset AD (8-17% out of 56-79%). Among them, the causal variants and their effect are only known for a minority of cases. To date, over 400 million genetic variants in the human genome have been sequenced. The causal variants tend to be sparsely spread across the genome with multiplex nonlinear effects on AD. This is far more than the current analytical and experimental approaches can analyze with adequate power. Machine learning (ML) approaches, including deep learning/neural networks, can efficiently learn linear and nonlinear relationships and have been used successfully in many scientific problems. Meanwhile, recent advances in genome sequencing provide an exciting opportunity to apply ML methods to genetic data analysis of AD. However, for application of ML to genetic studies, it is generally difficult to quantify how changes to the genetic variants influence the disease outcome. Although explainable artificial intelligence (XAI) methods have been developed to improve the interpretability of ML and to quantify the relative importance of input features (e.g. genetic variants), there is little to no development for rigorous control of the error rate of selected features - a property critical for reproducible science but less studied in existing XAI methods. The objective of this proposal is to develop rigorous feature selection in ML methods and pair them with causal inference to discover causal genetic variants of AD that could lead to novel targets for the development of new AD therapies. At the Stanford Alzheimer's Disease Research Center, we have curated a database that combines large-scale genetic and multi-omics datasets. The proposed methods will be applied to genetic data from a total of roughly 500,000 samples harmonized across ADGC, ADSP and UKBB. The findings will be validated using real functional experiments, single-cell RNAseq data and proteomics data. We expect that the application of the proposed methods will significantly improve our understanding of the multiplex nature of AD and, critically, provide a credible set of well-defined, novel targets for the development of genomic-driven therapies.

NIH Research Projects · FY 2026 · 2025-05

In 2023, California suffered the greatest number of cases of coccidioidomycosis (Valley fever) in its history. Although outdoor workers are at higher risk of coccidioidomycosis than other individuals, agricultural soil is less likely than non-agricultural soil to harbor the pathogen, raising the possibility that pesticides alter environmental colonization. Fungicides could directly kill Coccidioides, resulting in reduced colonization of soil where pesticides are applied; loss of the pathogen would potentially lead to fewer local cases of disease. Alternatively, fallow land that had previously been treated with pesticides may be permissive of recolonization with Coccidioides endospores through the pesticides’ disruption of competing microbial communities; this could lead to more cases of disease after the fallowing. We propose an exploratory study to evaluate whether pesticides are geographically and temporally linked to human coccidioidomycosis cases or environmental Coccidioides. We hypothesize that environmental pesticides, particularly fungicides and rodenticides, alter local coccidioidomycosis risk and seasonality by perturbing pathogen density within environmental reservoirs. We will take advantage of three data sets including: detailed, aggregated, publicly available pesticide use information to identify monthly applications of pesticides at the level of both the census tract and the individual residence from 2000 to 2023; monthly data previously obtained from the California Department of Public Health over the same time period on incident coccidioidomycosis cases; and data from our group on Coccidioides in 1500-2000 soil samples collected from the Central Valley. We will then use a variety of sophisticated statistical methods to address two aims: Aim 1) Evaluate environmental pesticide use, particularly fungicides and rodenticides, as a risk factor for coccidiomycosis in California over a period of 20 years; and Aim 2) Evaluate environmental pesticide use, particularly fungicides and rodenticides, as a risk factor for Coccidioides detection in soil samples. Analyses will adjust for weather and for specifics of land use, and will assess pesticides in general as well as rodenticides and fungicides. Understanding whether and how soil applications of antimicrobial agents like pesticides and fungicides affect coccidiomycosis incidence and Coccidioides distribution will provide insights into primary prevention of this infection in humans and animals. Future studies that may stem from this work include direct assessments of pesticide concentrations in soils with and without Coccidioides, as well as veterinary surveillance of animals in pesticide exposed areas.

NIH Research Projects · FY 2026 · 2025-05

Abstract One central goal of human genetics is to determine the key genes and molecular pathways that drive disease. By doing so, we can hope to gain deeper insight into the molecular basis of disease, as well as to identify potential targets for therapeutic intervention. While GWAS has identified tens of thousands of significant, robust associations, the results do not provide a straightforward assessment of the potential importance of each gene. As an alternative, we propose to develop new techniques for using rare protein-coding variants including loss- of-function mutations, deletions, and duplications in burden tests. We will use these to estimate the magnitude and direction of effect of each gene on a phenotype of interest, across the full range of expression encompassed by natural variation. In order to improve accuracy, since tests at single genes are often underpowered, we will extend a machine learning approach we developed previously called GeneBayes to share information among similar genes within a hierarchical Bayesian framework. We will release open access software and summary statistics to maximize the value of our work to the scientific community.

NIH Research Projects · FY 2025 · 2025-05

Project Summary Cardiac fibrosis, the excessive buildup of fibrous connective tissue in the heart resulting in impaired function and structure, is a prominent hallmark of dilated cardiomyopathy (DCM), and significantly contributes to the pathogenesis of this inherited heart disease. DCM is characterized by systolic dysfunction and the enlargement of ventricular chambers, often linked to mutations in myocyte-specific genes that impair contractile function. However, beyond myocyte dysfunction, non-myocyte elements play a crucial role, particularly in the form of cardiac fibrosis and endotheliopathy. Notably, the extent of fibrosis correlates with the progression of DCM and serves as a critical predictor of adverse patient outcomes, including the development of heart failure. This strong association suggests a possible causal relationship between cardiomyocyte (CM), and endothelial cell (EC) dysfunction which results in the dysfunctional activation of fibroblasts (Fb) from a quiescent state turning into ECM-secreting myofibroblasts. To discover a way to combat fibroblast activation, we will take two hits from a screen of 5,000 FDA-approved compounds that was previously performed in the lab, with the goal of validating them in a complex human 3D iPSC cardiac organoid (iPSC-CO) initially, followed by further validation in a mouse model of LMNA DCM. iPSC-CO will be generated from 20 sex and racially diverse iPSC lines (10 healthy, 10 DCM) currently available to our lab, and pooled into 2 cell villages before differentiation into CM, EC, and Fb. Using whole genome sequencing in tandem with single nucleus RNAseq and ATACseq, we will profile the transcriptome and the chromatin state of each cell within the organoid, enabling us to assign a cell line identity to the exact cell line origin. In addition, these organoids will be physiologically profiled using measurements of fibrosis and stiffness through AFM contraction kinematics. These two hits will also be tested in an animal model of DCM, the LMNAH222P mouse. The cardiac tissue of these mice naturally becomes excessively fibrotic by 20 weeks of age, so treatments will begin 1 month before, and will be monitored using echocardiography and tail pressure cuff. At the end of the experiment these animals will be used for 10x multiomics analysis as well as histological and immunological analysis of fibrosis. Here, our research aims to uncover effective strategies to mitigate the detrimental effects of cardiac fibrosis in diseases like DCM. By validating and describing the anti- fibrotic mechanism of two hits from prior compound screen, CGS15943 an adenosine receptor antagonist and AM404 a TRPV1 agonist, and correlating their efficacy in the LMNA DCM mouse model, we aim to provide a therapeutic for those affected by DCM. Using advanced techniques like whole genome sequencing, single nucleus RNAseq and ATACseq, and pairing it with physiological profiling, our study will reveal the interplay between three cardiac cell types, CM, EC, and Fb potentially leading to new treatments and knowledge to better combat excessive cardiac fibrosis.

NIH Research Projects · FY 2026 · 2025-05

PROJECT ABSTRACT Cancer immunotherapy, when effective, is lifesaving. Unfortunately, 15-50% of individuals will not respond to therapy; therefore, efforts to ‘flip the switch’ and turn these ‘non-responders’ into ‘responders’ are critical and urgent. Encouragingly, phenomenological studies in humans and preclinical studies in mice have demonstrated that the gut microbiome is associated with cancer immunotherapy response. However, the exact mechanisms that drive microbiome-based changes in immunotherapy response are not known. This project will elucidate how microbial microproteins modulate macrophage function, a critical coordinator of tumor immune response. The central hypothesis of this proposal is that specific gut microbes express microproteins that directly modulate macrophages, thus leading to immunomodulation of cancer. Previous work seeking to deconvolute the signaling interface between microbes and immune cells has done so by: (i) carrying out limited- throughput, arrayed screens, (ii) focusing on microbial small molecule metabolites and (iii) focusing on T-cells. Here, we propose to address many gaps left by these approaches. Namely, we will (i) carry out two orthogonal high-throughput screens (peptide-display polarization assay, Perturb-seq) of 1,000s-10,000s of microbial macromolecules in pooled screens (technical innovation), (ii) focus on proteins, especially an understudied class of microproteins we recently discovered and have now annotated in microbial genomes (conceptual innovation), and (iii) moving one step up in the immunological ‘cascade’ by focusing on macrophages (conceptual innovation). Our strong preliminary data have identified two novel macrophage-modulating microbial proteins that we will mechanistically study in Aim 1, and we have also developed and validated a powerful peptide display system that will be expanded in Aim 2. Building upon these preliminary data, we will: (Aim 1) determine the detailed molecular mechanisms, including target receptors and downstream signaling pathways, that two microproteins (from Klebsiella pneumonia and a Leptotrichia spp.) use to modulate macrophage polarization; (Aim 2) screen a large, data-derived library of candidate microbial microproteins to identify those with immunomodulatory properties; and, (Aim 3) apply scRNAseq to define the dynamic changes in macrophage state induced by these immunomodulating microproteins. Our core team has collaborated for >5 years, and has expertise in microproteins, the human microbiome and translational research (Bhatt – a practicing oncologist) and cancer- focused high-throughput functional genomics and macrophage biology (Bassik). Our preliminary data demonstrates the strength of our environment for this research, and we are supported by experts in multi-omics (Snyder), chemical biology (Bertozzi), immunotherapy/microbiome (Wargo), scRNAseq and tumor immunology (Jerby), and functional assays of microproteins (de la Fuente). Taken together, we are optimally positioned to identify macrophage-modulating microbial factors, which will then be used to develop new, mechanism-based strategies to enhance cancer immunotherapy efficacy.

NIH Research Projects · FY 2026 · 2025-05

PROJECT SUMMARY Repetitive transcranial magnetic stimulation (rTMS) is an effective treatment for depression, but clinical responses are highly variable. This is because the underlying neural mechanisms, as well as the optimal treatment parameters, remain unclear. Treatment targeting the dorsolateral prefrontal cortex (dlPFC) aims to improve symptoms by restoring impaired prefrontal excitability. However, evidence of impaired excitability in depression and subsequent neural change after rTMS is limited due to the lack of reliable markers of prefrontal excitability that can be measured and tracked during rTMS. There is an urgent need for reliable markers of prefrontal excitability to direct personalized treatment and guide systematic screening of novel protocols. Our long-term goal is to improve depression treatment by establishing reliable markers of prefrontal excitability. We hypothesize that biologically-grounded TMS parameter adjustments can optimize prefrontal excitability measurements to effectively capture alterations in depression and modulation following rTMS. The early local TMS-evoked potential (EL-TEP) is a short-latency response recorded over the dlPFC stimulation site that has been shown to be altered in depression and correlate with treatment outcome, but has suffered from low signal-to-noise and reliability issues. We recently developed TARGET (Targeting with Automated Real-time Guidance for Enhancing TEPs) to enhance EL-TEPs by dynamically adjusting TMS parameters, increasing EL- TEP signal-to-noise three-fold and reliability two-fold. However, TARGET's lengthy optimization time, lack of full automation, unclear neural impact, and uncharacterized alteration in depression limit its current utility. We will 1) investigate how adjusting TMS parameters affects neural activity measured with intracranial EEG, 2) optimize TARGET and study EL-TEPs in depression, and 3) test how optimized EL-TEPs detect changes in prefrontal excitability induced by cognitive tasks and rTMS. Impact: This research will characterize TMS parameter effects on neural responses and develop efficient methods for cortical excitability assessment. Success will enhance brain-based monitoring and facilitate novel personalized treatments guided by cortical excitability. Future work will apply this approach to obtain reliable noninvasive measures of cortical excitability across various brain regions and disorders. This work will lay the foundation for clinical trials using TARGET-optimized EL-TEPs as surrogate endpoints for rapid evaluation of treatment effects.

NIH Research Projects · FY 2026 · 2025-05

PROJECT SUMMARY New avenues of therapy for atherosclerotic diseases are needed as they remain the leading killers worldwide. Therapies that target each of the different cell types that influence the formation of atherosclerotic plaque have translated into lifesaving therapies. Characterizing a novel key cell population that plays a pathogenic role in atherosclerosis will open entirely new avenues for therapies. Our preliminary single cell transcriptomic data and histology of human and murine atherosclerotic plaque have identified an understudied population of cells that we define as Adventitial Fibroblasts (AdvFib). Enabled by an innovative genetic tool, our preliminary data has unveiled a previously unrecognized non-cell-autonomous role of AdvFib in plaque biology. AdvFib ablation or modification of AdvFib through GWAS gene TCF21 significantly influences atherosclerotic plaque formation and calcification. Identification and validation of previously unrecognized outside-in signals affecting atherosclerotic plaque using state-of-the-art techniques form the central focus of this proposal and will lead to novel therapies. Our study is highly innovative by focusing on an overlooked population of vascular cells. No current therapeutic targets these cells. Previous studies of adventitial cells were limited by the inability to deconvolute the causal cell type and relevant disease-related pathology due to cellular heterogeneity of the adventitia and lack of a specific tool to track the fibroblast lineage. Our innovative approach overcomes the shortcomings of previous adventitial studies by using single cell genomics tools, a new and unique murine model that we designed specifically to study vascular adventitial fibroblasts, and complementary in vitro human primary cell models. Aim 1 will determine the mechanism behind the observation that even though AdvFib do not contribute to the intimal lesion, targeted genetic ablation of AdvFib significantly decreases plaque formation. We will use our novel AdvFib-specific inducible CreERT2 murine model, inducible diphtheria toxin receptor, and single cell transcriptomics with mechanistic validation using human AdvFib co-culture experiments. Aim 2 will determine why conditional AdvFib deletion of Tcf21, a GWAS gene for coronary disease, alters plaque calcification. We will accomplish this through a combination of single cell transcriptomic, epigenetics and in vitro human AdvFib functional epigenetic mapping and detailed mechanistic validations. Aim 3 will test the potential therapeutic potential of AdvFib-specific Tcf21 overexpression on plaque composition and vascular calcification. We will use a combination of single cell transcriptomics using a novel murine model and in vitro human AdvFib studies. Our rigorous team science approach synergizes expertise from diverse disciplines, including coronary artery development, human genetics, epigenomics, and the innate/adaptive immune system. Completion of this project will define the role of AdvFib in atherosclerosis, solidify AdvFib as a new target for therapy, and identify new AdvFib disease-related pathways and genes that may also play a role in other vascular diseases.

NIH Research Projects · FY 2026 · 2025-05

PROJECT SUMMARY / ABSTRACT Medications for opioid use disorder (MOUD) decrease risk of relapse, overdose, and death in individuals with opioid use disorder (OUD) and have been studied extensively in non-surgical patients. However, even once patients initiate MOUD—which is meant to be used on a long-term or even lifelong basis—a large proportion discontinue it, often following stressful or painful events. In surgical patients with OUD, there is still a critical gap in understanding how exposure to acute pain via surgery affects postoperative MOUD discontinuation vs treatment retention and sequelae including longer-term, comprehensive addiction-related, pain-related, and all- cause outcomes. The central hypothesis for this study is that risk of postoperative MOUD discontinuation varies by both fixed and modifiable clinical factors and that postoperative MOUD discontinuation is a risk factor for OUD-related adverse events. The rationale for the proposed research program is that it is expected to inform the development of interventions aimed at safely guiding patients with OUD through the perioperative period while helping to establish my independence as a physician-scientist. The central hypothesis will be tested through two specific aims: 1) Identify risk factors for discontinuation of MOUD after surgery and develop a risk calculator to predict MOUD discontinuation, and 2) Estimate the association between postoperative MOUD discontinuation and adverse outcomes in surgical patients. These aims will be achieved via a retrospective cohort study and state-of-the-art statistical methods for causal inference in observational studies. The proposed research is innovative because it will leverage three large, nationally representative claims databases and apply sophisticated statistical methods to estimate postoperative MOUD discontinuation and its association with longer-term adverse postoperative outcomes. The research project is significant because it is expected to provide real-world, actionable guidance on the perioperative management of OUD, benefiting the growing population of patients who live with OUD as a chronic condition and will require surgery in their lifetimes. This work will be critically informative for future research led by the candidate on perioperative practices that decrease risk of adverse postoperative events in patients with OUD. The proposed integrated research and training will be accomplished at Stanford University with the support of an exceptional mentorship team. The candidate will build on a solid background in anesthesiology, public health, and health services research to gain relevant expertise in pain and addiction medicine, advanced statistical methods for health services research, usage of Medicaid claims data, and scientific communication. Together, the research and training will advance the candidate’s long-term goal to develop an independent research program as a physician-scientist aimed at improving prevention and treatment of substance use disorders in patients with acute or chronic pain. Ultimately, the continuum of research will have a positive impact by providing a strong evidence base for targeted specialty care of the growing and vulnerable population of patients with OUD.

NSF Awards · FY 2025 · 2025-05

Polar bears have numerous traits that not only give them their iconic appearance but are also adaptations to living in the Arctic environment. These include their large body size with thick fat layer, streamlined head to help dive after prey, and most-noticeable their white fur. While other species of bears live in tropical or temperate environments, polar bears adapted to the extreme low temperatures of the Arctic with novel ways to absorb solar radiation or retain internal body heat. Three of these thermoregulatory adaptations within the skin or hair include: light hair color, dark skin color, and insulating hollow hair. To identify the genes responsible for these traits, DNA, RNA, proteins, and tissue structure of polar bears will be compared to both the brown/grizzly bear and American black bear. Further, the rate of hair heating and cooling, and energy transfer at the hair-skin boundary will be measured and modeled with the aim of developing novel nanoscale materials. Thus, the project will yield new insights into how mammals remain warm in extreme cold environments. Similar pigmentation and hair structural variation have evolved in other Arctic mammals; thus, understanding the molecular and cellular mechanisms of these traits will provide a starting point to investigate convergence. Research results will be translated into educational materials appropriate for K-12 students and distributed to zoos with polar bears, as zoos are often the only opportunity people have to observe these animals. Finally, the project will train scientists in effective science communication and reach non-expert audiences through public outreach. Arctic species must adapt to the extreme temperatures of their environment. This research focuses on skin and hair traits associated with thermoregulatory adaptation. Comparative genomics, transcriptomics, and histological staining of skin tissue between polar bears and two temperate species, brown and American black bears, will determine the cellular basis for light hair and dark skin. Specifically, the abundance and location of melanocytes will be characterized, then changes in gene expression among bear species that can account for differences in cellular location will be identified. Beyond pigmentation differences, polar bear hair has a hollow center thought to increase the insulating capacity of the fur. To identify the genes that underly this trait, protein abundance within hair will be compared among species. Ancestral recombination graphs will be constructed to quantify when during the evolutionary history of polar bears this adaptation arose. As the hollow hair has distinct applications in creating novel heat retaining nanomaterials, this research will quantify and model thermodynamic properties of the hair and hair-skin interface over a range of environmentally relevant temperatures. 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 · 2025-05

PROJECT SUMMARY Developmentally wired programs of social interactions in animals enhance reproductive success, yet these underlying neural circuits also allow for flexibility in behavior, such as modulating behavior in response to past experiences. The mechanisms enabling such flexibility in innate social behaviors remain poorly understood. This project aims to define the experience-driven neural mechanisms that enhance behavioral performance in male mating. We hypothesize that experiential changes in male mating are governed by neural plasticity within the circuits controlling this behavior, focusing specifically on preoptic hypothalamus neurons (POA) expressing tachykinin receptor 1 (POATacr1), a critical population that regulates male mating. To achieve our objectives, we will first delineate the afferent inputs onto POATacr1 neurons. We will employ retrograde tracing and optogenetic manipulations to identify and characterize cell populations projecting to POATacr1 and their role in mating. Second, we aim to elucidate the cellular and electrophysiological mechanisms underlying mating experience-driven plasticity. This includes measuring synaptic transmission onto POATacr1 neurons and characterizing mating experience-regulated cellular dynamics using in vivo 2-photon imaging. Furthermore, we will identify molecular pathways underlying mating experience-driven plasticity through deep sequencing to identify and functionally interrogate candidate genes regulated by mating experience. If successful, our project will reveal novel mechanisms underlying circuit plasticity during experientially driven changes in mating behavior, with potential implications for understanding reproductive behavior in health and disease. The interdisciplinary approach employed will provide insights into the interplay among genes, circuit plasticity, and innate behaviors, establishing a platform for future independent research.

NIH Research Projects · FY 2022 · 2025-05

Project Summary Recent advances in technology driven by the BRAIN Initiative have yielded new methods for characterizing the ac- tivity, transcriptome, and microscale anatomy of neurons throughout the brain, and have increased the throughput of these techniques by orders of magnitude. It is currently possible to record the simultaneous activity of popu- lations of neurons on the order of tens of thousands of neurons in awake behaving animals in vivo using large field of view multiphoton imaging or high density silicon probes, and new machine learning methods are enabling more comprehensive functional characterization than ever before. Transcriptomic profiling can be accomplished at scales of tens or hundreds of thousands of neurons in vitro. Finally the microscale anatomy of axonal pro- jections and connections across the brain can also be assessed in tens of thousands of neurons in the same animal using dense electron microscopy reconstruction for local circuits, or (as we propose here) RNA barcoding methods for local and long-range axonal projections. Each of these techniques on their own can provide im- portant clues about the diversity of neurons and their organization into canonical circuits with specific functional, transcriptomic, or axonal projection profiles. While these techniques are all being pushed forward independently, they remain effectively siloed from each other, precluding multi-modal characterization of the same neurons in the same animal. Developing a comprehensive pipeline to characterize transcriptomic, axonal projections and in vivo functional fingerprints as we propose to do here would enable synergistic analyses of cell-type composition across these multiple dimensions. Finally, because of the low cost and high throughput of this approach, experi- ments using this novel pipeline could be repeated many times in different animals to answer pressing questions about how the relationship between the function, structure, and transcriptome of neurons changes across devel- opmental or disease states. In this proposal, we will leverage our team's combined expertise in in vivo functional imaging and Machine Learning to characterize the complex functional properties of neurons in primary visual cortex of the mouse, and novel sequencing techniques developed by PI Zador to combine transcriptomic profiling with RNA barcoding to measure single-neuron projection patterns throughout the brain at axonal resolution.

NIH Research Projects · FY 2026 · 2025-05

Summary The incidence of esophageal adenocarcinoma (EAC) has been rising dramatically in Western populations over the last several decades. EAC arises from Barrett’s esophagus (BE), a specialized intestinal metaplasia of the esophagus associated with chronic acid reflux. Patients with BE are recommended to undergo periodic endoscopic screening, in which biopsies are obtained along the BE-lined esophagus to detect progression to EAC. Here, the goal is to detect the presence of neoplasia, and if present, to categorize the lesion as low-grade dysplasia (LGD), high-grade dysplasia (HGD) or cancer (EAC), all of which have unique treatment implications. Unfortunately, there is high inter-pathologist disagreement in distinguishing between LGD and HGD. In particular, LGD is notoriously difficult to diagnose by histopathology, and has variable progression rates to HGD and/or EAC. Therefore, there is a need to improve our methods for obtaining a definitive diagnosis and treatment recommendation based on endoscopic biopsies. A significant contributing factor to this problem is that pathological grading (risk assessment) of esophageal biopsies currently relies upon the subjective interpretation of 2D sections that only represent ~1% of the total volume of the biopsies. Our team at the Univ. of Washington (UW), the Fred Hutch Cancer Center (FHCC), and the Brigham and Women’s Hospital (BWH) is pioneering the development of non-destructive 3D pathology and associated computational methods (2D and 3D) for clinical decision support. Non-destructive 3D pathology has the potential to greatly improve diagnostic determinations by enabling: (1) orders-of-magnitude greater sampling of tissue specimens, (2) volumetric imaging of cell distributions, tissue structures, and other novel 3D spatial biomarkers that are prognostic/predictive, and (3) non- destructive imaging, which preserves valuable tissues (e.g. whole biopsies) for downstream molecular assays. Over the past few years, we have conducted a series of studies to evaluate our nondestructive 3D pathology methods for the diagnosis and grading of BE-related lesions (LGD, HGD, and EAC). We have demonstrated the ability of 3D pathology to elucidate esophageal lesions that are ambiguous with conventional 2D histology. We have also developed deep-learning-assisted pipelines to analyze massive 3D pathology datasets for prognostication of cancer outcomes. Here, we will continue to refine these collective technologies to improve the treatment and outcomes for patients with BE. Our project goals include: Aim 1 (standardization and quality control) – to develop a 3D pathology pipeline to enable reproducible (>95% yield) generation of clinical-grade 3D datasets; Aim 2 (AI triage to assist pathologists) – to develop weakly supervised deep-learning triage methods, based on annotated 2D image levels within 3D pathology datasets, for time-efficient pathologist interpretation of 3D pathology datasets; and Aim 3 (AI decision support) – to develop weakly supervised deep learning, based on patient outcomes, for fully computational risk stratification of putative low-grade patients.

NIH Research Projects · FY 2026 · 2025-05

Project Summary Lack of transparency and trustworthiness of deep neural networks (DNNs) has long been recognized as a major drawback of the technology, hindering its widespread acceptance in many practical applications. The objective of this project is to establish a novel contrastive feature analysis (CFA) framework for reliable visualization of the high dimensional feature space and effective design of high-performance DNNs for medical image analysis. We hypothesize that CFA-based feature visualization will enable us to quantify the quality of the feature space at different layers during training/testing of a DNN and empower us with an effective tool to prune the network architecture for enhanced performance. Specifically, we will (1) develop an efficient visualization technique CFA for high dimensional feature data, 2) apply the CFA visualization framework to automatically refine DNN architecture for improved performance, and 3) demonstrate the potential of CFA in solving clinical problems. Successful completion of the project will enable us to analyze the feature data reliably and quantify the quality of the feature space at different layers of a DNN. The study also promises to provide high-performance DNNs for medical image analysis to substantially improve the AI-based diagnosis, prognosis and treatment planning of different diseases.

NIH Research Projects · FY 2026 · 2025-05

Encapsulated cell therapies (ECT) are attractive therapeutic platforms that involve the housing of collections of transplanted cells capable of secreting therapeutic proteins within polymeric frames. These technologies represent the potential to eliminate patient dependence on complex drug-dosing regimens while maintaining circulating drug levels within healthy, nontoxic therapeutic ranges for diseases ranging from autoimmune disorders to cancer. Transplanted cells are isolated from host immune systems via encapsulation materials and semipermeable, porous polymeric membranes (immunisolation membranes) via size exclusion effects. Despite attracting significant interest, ECT devices have not found widespread clinical translation owing to transplant failure, with low oxygen tension within the transplanted cell microenvironment and fibrosis representing major causes. Size considerations related to cellular packing density represent a further translational challenge. This challenge is particularly acute in subcutaneous (SC) implants owing to the region’s low vascularization and high rates of fibrotic capsule formation. Despite these hurdles, SC implants have attracted considerable attention owing to the minimally invasive surgery requirements and potential for easy device monitoring and retrieval. In this proposal, I will use approaches in microfabrication and bioelectronic device design to improve oxygen tension within the transplanted cell microenvironment in SC-ECT devices. In Aim 1 I will develop advanced multiphysics models to predict and address oxygen need in implanted SC devices. In Aim 2, I will use surface chemical modifications to suppress fibrosis and ensure long-term transplant survival in oxygen-generating bioelectronic ECT implants. In Aim 3, I will pursue system level integration using design principles in flexible bioelectronics, biosensor development and resonant inductive wireless power transfer approaches. If successful, the resulting platform technology will support SC transplanted cell survival long term, with potential applications across cell types and disease models. The work is highly interdisciplinary, incorporating materials science, cell therapies, drug delivery and electronic/electrical engineering. If successful, the work will create a platform technology capable of addressing a wide range of unmet therapeutic needs in minimally invasive implantation sites to de-risk clinical translation. My background is primarily in the physical sciences: through this Fellowship, I will work closely with my co-mentors, Profs. Daniel Anderson and Robert Langer at MIT to develop skills that will allow me to work at the interface between engineering and the life sciences, with a focus on clinical translation.

NIH Research Projects · FY 2025 · 2025-05

ABSTRACT: The acquisition of episodic memories (EM) relies on attention mechanisms, which are affected by aging with consequences for everyday functioning. Attention can operate on nonspatial features, via feature- based attention (FA), which has been recently shown to wax and wane at a consistent temporal frequency (behavioral rhythm), likely reflecting an intrinsic rhythmicity of the underlying neural computations. Notably, while a similar behavioral rhythm has been recently observed in EM, this memory-related rhythm has been interpreted to reflect distinct mechanisms from those underlying attentional rhythms despite their overlapping frequency and the likelihood that the memory behavior depends, in part, on attention. The magnitude of EM and FA rhythms may also interact with fluctuations of states of arousal, which are known to relate to variability in attention and memory. These observations raise fundamental questions about the neurocognitive mechanisms underlying behavioral rhythms of FA and EM, and how they are altered in human aging independent of Alzheimer’s disease (AD). This project will examine attention and memory performance concurrent with simultaneous scalp electroencephalography (EEG) and pupillometry with a well-powered sample of 75 young and 75 AD-biomarker negative, cognitively unimpaired older adults. Older adults will be screened with an extensive neuropsychological battery and blood plasma-based assays of AD pathology (Aβ42:40 and p-tau217), enabling more specific conclusions about AD-independent age-related changes in behavioral and neural expressions of FA and EM. In the main experiment, participants will perform a novel, integrated attention-memory task that combines FA and EM, with a design that will sample different phases of rhythms of feature-based attention and episodic memory encoding. Neural rhythms will be characterized using a cutting-edge state-space modeling approach applied to the EEG data to maximize sensitivity and specificity to detect genuine rhythmic neural activity. Pupillometry metrics of pupil size and EEG posterior alpha power will serve as moment-to-moment and individual-difference measures of arousal/sustained attention. Our specific aims are to examine the relations between behavioral rhythms of EM and FA and their alteration in aging (Aim 1); to elucidate the neural mechanisms underlying behavioral rhythms of EM and FA and their changes in aging (Aim 2); and to investigate how FA and EM rhythms relate to changes in arousal and how these relationships are altered in aging (Aim 3). Collectively, this Exploratory / Development Research project will provide novel insights into the dynamic interactions between attention, memory, and arousal, and will elucidate pathways through which AD-independent changes with age result in memory decline and between-person memory variability. The resulting data may ultimately reveal candidate biobehavioral markers for more effective diagnostics, along with potential avenues of intervention that can be developed and explored in future research.

NIH Research Projects · FY 2026 · 2025-04

PROJECT SUMMARY/ABSTRACT Atherosclerotic cardiovascular disease is the leading cause of death worldwide and its rates are rapidly rising, especially in the developing world. Despite decades of research, many questions remain about the disease’s cellular and molecular processes. Chimpanzees, the closest living relative of humans, are not as susceptible to atherosclerosis, despite having higher serum cholesterol levels. This divergence in disease susceptibility between closely related species provides a novel approach to study atherosclerosis. To study these species-specific changes, I will utilize recently published human-chimpanzee hybrid cell lines, a system that allows for the precise detection of species-specific gene expression changes. These cells will be used in conjunction with a protocol that allows for the creation of pure populations of arterial endothelial cells (aECs) from induced pluripotent stem cells. Using the hybrid cells, I have already identified several candidate pathways which exhibit species-specific gene expression changes in aECs. In aim 1, I will assay the function of aECs from both species and identify novel phenotypic differences between human and chimpanzee arterial endothelial cells. These disparities could provide insights into developmental differences as well as provide clues to atherosclerotic mechanisms. Inflammatory signals are thought to drive atherosclerosis and my preliminary data shows differences in gene expression between species following exposure to inflammatory cues. In aim 2, I will identify gene expression divergence between species by subjecting hybrid cells to stimuli that mimic an atherosclerotic environment. By measuring species-specific expression changes in various conditions, I can catalog the genes that are differentially regulated upon exposure to atherosclerotic stimuli, to provide clues about disease pathology. These changes in gene expression will need to be functionally validated to demonstrate that they can influence atherosclerosis susceptibility or progression. In aim 3, I will use pharmacological and genetic methods to interrogate the results from aim 2 to discover novel pathways and genes that influence atherosclerosis. By forming aECs with human, chimpanzee, and hybrid cell lines and dissecting their phenotypes, new insights will be gained into the pathways and genes that are atheroprotective in chimpanzee. Furthermore, my findings will provide a new framework to model the development of atherosclerosis, which may one day be leveraged into novel therapeutic strategies.

NIH Research Projects · FY 2026 · 2025-04

PROJECT SUMMARY The development of inhibitors (i.e., neutralizing antibodies) against infused coagulation protein factor VIII (FVIII) is the most significant treatment-related complication in modern hemophilia A care. Administration of frequent and high doses of FVIII over months-years, referred to as immune tolerance induction, remains the primary strategy for inhibitor eradication for the last 40 years. There is a critical need for novel, innovative, and less burdensome approaches to immune tolerance induction to restore FVIII hemostatic efficacy in the management of acute bleeds or surgeries in persons with hemophilia A (PwHA) and inhibitors. Despite numerous novel treatments recently approved or in the pipeline for hemophilia A treatment, the lack of therapeutic strategies for inhibitor prevention or universally successful inhibitor eradication methods are persistent barriers within the field that warrant continued research focus. Moreover, a poor understanding of the underlying immunologic processes that mediate FVIII immunity further contribute to the limited advancements in therapies for peripheral tolerance induction. The long-term goal of this work is to define the key cellular components and early immunologic events that mediate FVIII immunity to ultimately develop and test targeted immunomodulatory therapies that prevent inhibitor formation and induce peripheral FVIII tolerance. The rationale for this R00 proposal stems from preliminary data demonstrating that type 2 conventional dendritic cells (cDC2) are key mediators in anti-FVIII antibody development in a murine model of hemophilia A. Additionally, single cell RNA sequencing (scRNAseq) analysis show upregulation of phagocytic and interferon genes by cDC2 following FVIII injections in hemophilia A mice signifying their contribution in FVIII recognition and presentation. The central hypothesis is that with early FVIII exposure conventional DC (cDC), specifically cDC2, mediate CD4+ T cell activation in a proinflammatory cytokine microenvironment that induces B cell activation and production of inhibitory anti-FVIII antibodies. The central hypothesis will be tested through the following 2 aims: 1) Define the cytokine microenvironment of cDC2 activation and CD4+ T cell differentiation in FVIII inhibitor development, and 2) Determine the innate immune profile across the lifespan of PwHA with and without inhibitors. Aim 1 will examine the cDC2-activated cytokine microenvironment, focusing of interferon gamma (IFN-γ) and IL-12 production and cellular source, that dictates antibody production in FVIII knockout mice with and without cDC2 depletion. Aim 2 will investigate and compare the innate immune transcriptomic profile of peripheral blood mononuclear cells isolated from PwHA based on age groupings, inhibitor status, and treatment regimen utilizing 10X Genomics scRNAseq and flow cytometry. This research is significant because it will advance understanding of the innate immune response to FVIII and help illuminate therapeutic strategies that can be administered during early FVIII exposure to prevent inhibitor development and induce peripheral immune tolerance.