University Of California, San Diego

NIH Research Projects · FY 2026 · 2025-03

Project Summary: What if we could engineer our own cells to become potent cancer fighters? Here, we will utilize a novel targeted gene therapy approach to specifically engineer distinct immune cell populations (T cells, NK cells and macrophages) to express chimeric antigen receptors (CARs) to enable these immune cells to mediate killing of otherwise refractory cancers. This approach builds off the remarkable success in use of autologous CAR- expressing T cells to better treat and cure B cell malignancies. However, the autologous CAR-T cell strategy requires the cells to be manufactured on a patient-specific basis, making this approach inefficient, expensive, time consuming, and still prone to disease relapse. CAR-expressing NK cells and allogeneic CAR-T cells to provide an "off-the-shelf" strategy that broadens the range of patients who may be treated and makes this process more efficient, standardized, and affordable. However, there are also concerns about immune responses against the allogeneic cells, and the efficacy of this approach against more common solid tumor malignancies remains unclear. Here, we will engineer endogenous immune cells using a novel virus-like particle (VLP) vector that combines the best aspects of the ease and targeting of lentiviral vectors with use of mRNA expression that is more controlled and regulated compared to genome-integrating lentivirus. Cell lineage-specific DARPins or scFvs expressed by the VLPs will be utilized to separately target T cells, NK cells or macrophages. The immune cells will be engineered to express an anti-mesothelin CAR with signaling domains optimized for either T cells, NK cells or macrophages. We hypothesize these engineered therapeutic vehicles capable of performing guided in vivo cellular engineering of specific immune cells will enable endogenous immune cells to now mediate potent killing of ovarian cancer cells. This approach will first be tested in vitro to determine the efficiency and specificity of DARPin-mediated gene expression in T cell, NK cell and macrophage cell lines and then primary immune cells to express CARs that lead to recognition and killing of ovarian cancer cells. Additional transcriptomic and metabolomic profiling will be done of the VLP- engineered immune cells. Next, we will evaluate and optimize this approach using two different in vivo models. The first in vivo studies will use tumor-bearing immune competent mice that will allow us to test both specificity and efficacy of this approach, as well as safety, persistence, and ability to stimulate a broader immune response against ovarian cancer. Subsequent in vivo studies will use immunodeficient mice engrafted with human immune cells to provide a relevant pre-clinical model of engineering endogenous immune cells to effectively target and kill ovarian cancer cells. Our strategy to not only target T cells, but to separately test efficacy of in vivo engineering of innate immune effector cells (NK cells and macrophages) will enable us to efficiently test a diversity of options for this in vivo approach to ensure success in subsequent clinical translation to better treat and cure otherwise lethal malignancies.

NIH Research Projects · FY 2026 · 2025-03

PROJECT SUMMARY Learning is a fundamental process in the brain that enables flexible action—output can be adapted to develop novel behaviors or modify existing ones. This adaptation is necessary to survive in an ever-changing, dynamic environment. The process of learning is thought to be mediated by changes in circuit activity that are driven by experience-dependent modifications at relevant synaptic connections. However, the mechanisms by which learning-induced changes arise at the synaptic and circuit level remain unclear. In order to understand how neural activity is modified with experience in order to shape behavior, one must be able to measure each of these components over the process of learning. This type of measurement has yet to be performed due to technical limitations for measuring these features simultaneously. The research proposed here will use cutting- edge imaging methods combined with newly developed genetically-encoded sensors for monitoring neural activity to monitor changes in the brain during learning of a skilled motor task. Specifically, Aim 1 of this project will simultaneously measure synaptic and spiking activity in corticospinal projection neurons in primary motor cortex. These neurons project directly to spinal cord circuits that control muscle activation; thus, understanding the role of synaptic plasticity at this node in the movement pathway can directly link activity at multiple levels, ranging from synaptic activity to behavioral output. Aim 2 of this project will develop a new behavioral task to specifically test the hypothesis that the function of plasticity in corticospinal neurons is primarily to improve the precision of during dexterous movements. Population activity measured over many days of training on this task will be used to determine how different movement patterns are represented in these neurons over the course of learning. Altogether, these experiments will provide deeper mechanistic understanding of the processes involved in transforming neural activity during learning. Additionally, the insights from the proposed study have broader implications for understanding the brain during natural behavior, since motor learning is required to perform many ethological behaviors (e.g. hunting, foraging, escaping from predators), as well as disease, since deficits in motor learning present as primary or secondary symptoms in many neurological diseases. Lastly, the findings here will have high relevance to understanding capacity for plasticity in the corticospinal circuit to alter motor output, which can inspire new opportunities for the development of therapeutic treatments for patients with spinal cord injuries.

NIH Research Projects · FY 2026 · 2025-02

Abstract Disabling pansclerotic morphea (DPM) is a severe, systemic disorder of childhood with debilitating skin, joint, and mucosal symptoms, immune dysregulation and malignancy. DPM is known to be severely recalcitrant to therapy, leading to death within 10 years of diagnosis. Our investigation of the specific contribution of STAT4 to the immunodysregulatory phenotype seen in DPM patients revealed the following key observations: 1) The STAT4 variant is a gain-of-function mutation that leads to impaired wound healing; 2) STAT4 variation leads to an enhanced immunodysregulatory phenotype; 3) persistent phosphorylation of STAT4 results in IL-6 mediated autoinflammation; 4) JAK inhibition upstream can reduce IL-6 and improve wound healing in vitro and in vivo. Based on our preliminary data we propose the CENTRAL HYPOTHESIS that gain-of-function mutations in STAT4 lead to persistent JAK-STAT signaling due to steady STAT4 phosphorylation, erroneous gene transcription, increased cytokine production, persistent systemic inflammation, and subsequently the failure to regulate normal wound healing. To investigate our hypothesis, our proposal has the following SPECIFIC AIMS. FIRST, we will determine the mechanism of STAT4 gain-of-function mediated immune dysregulation in DPM. We will test the hypothesis that enhanced STAT4 activity leads to a failure of normal NK and T cell development and cellular activation due to intrinsic defects in hematopoietic precursors leading to altered differentiation and subsequent lymphocyte exhaustion from systemic inflammation using novel patient- derived induced pluripotent stem cells (iPSCs) to examine development, transcriptomics, proteomics and immune cell function. Human studies will be complemented by in vivo assays using knockin murine progenitor cells, bone marrow cells, and peripheral cells at progressive stages of disease. SECOND, we will dissect the role of enhanced STAT4 signaling in neovascularization and immune cell crosstalk. We will test the hypothesis that gain-of-function mutations in STAT4 lead to upregulation of angiogenic factors that drive neovascularization, life-threatening bleeds, and contribute to poor wound healing. We will characterize the role of STAT4 signaling in endothelial cells and vessel formation by differentiation of patient-derived iPSCs to endothelial cells. We will assess the competency of vessels in vitro, and the role of oxidative stress in perpetuating poor wound healing. We will investigate translational mechanisms targeting JAK/STAT and angiogenic pathways in DPM disease using transcriptomics of iPSC generated vessels. Finally, we will investigate translational mechanisms targeting the JAK/STAT pathway in DPM.

NIH Research Projects · FY 2026 · 2025-02

Genetically-encoded tools that provide researchers with a means to control neural activity in genetically-defined cell types are widely used to establish causal relationships between neural activity and behavior. Current tools for silencing synaptic output in a way that is restricted to anatomically-defined target nuclei in the brain suffer from technical drawbacks that limit their widespread use by the neuroscience community. Optogenetic silencing tools are either prone to artifacts or demonstrate limited efficacy. Although chemogenetic tools such as the hM4Di Designer Receptors Exclusively Activated by Designer Drug (DREADD) appear to be highly effective in multiple cell classes, anatomically-restricted silencing requires local infusion through guide-cannulas, which lacks temporal precision and perturbs ongoing behavior. To address these limitations, we are developing optochemogenetic tools in the form of “photo-caged” DREADD agonists that can be applied systemically in an inactive form and subsequently released in the brain with light to achieve site-specific synaptic silencing with high temporal precision using sub-second flashes of light. These reagents are designed to either be compatible with optical measurements of neural function involving fluorescent probes, or sensitive to sources of blue light that are commonly used by many labs for optogenetics experiments, which should allow for rapid and broad diffusion in the neuroscience community. We will rigorously validate new caged DREADD agonists using in vitro, ex vivo, and in vivo experimental paradigms, culminating in fiber photometry recordings and optochemogenetic modulation of behavioral responses to aversive and rewarding stimuli. This work builds on our recent advances using related photopharmacological probes that target opioid receptors. To maximize end-user uptake, performance criteria are determined through extensive consultation with the scientific community.

NIH Research Projects · FY 2026 · 2025-02

Project Summary The overarching goal of our research is to understand the regulatory mechanisms that ensure accurate transmission of the genome during cell division. Macromolecular machines including the DNA replisomes and kinetochores execute chromosome replication and segregation, respectively; and they scaffold many post-translational modification enzymes to control their assembly and function. Mutations of these enzymes cause errors in chromosome replication and segregation, leading to gross chromosomal rearrangements and aneuploidy, respectively. In the next five years, we will investigate two areas, focusing on how post-translational modification enzymes regulate the assembly and function of DNA replication complexes and kinetochores. In the first area, we will study how cells prevent incomplete DNA replication, which is a major cause of gross chromosomal rearrangements. Specifically, we will investigate how cells regulate the loading of the Mini-Chromosome Maintenance (MCM) complex to ensure a timely completion of DNA replication, and how cells remove excess MCM at the end of DNA replication, both are required to prevent incomplete DNA replication. In the second area, we will study how cells promote kinetochore assembly in the M phase via protein phosphorylation and control kinetochore disassembly after chromosome segregation through protein sumoylation and ubiquitination pathways. Using a quantitative proteomics technology and an array of genetic, biochemical and cell biological assays, we will dissect the signals that control reversible kinetochore assembly to accommodate centromere replication and chromosome segregation. Together, these studies will illuminate the still enigmatic regulatory processes that are disrupted in the genome instability mutants and in diseases.

NIH Research Projects · FY 2026 · 2025-02

New therapeutics often fail to reach the clinic due to poor efficacy and severe adverse toxicity, primarily arising from inadequate drug delivery mechanisms. This inefficiency costs the pharmaceutical industry billions annually, underscoring the urgent need for targeted drug delivery systems that can accurately target diseased tissues while minimizing off-target toxicity. In recent years, innovative delivery strategies—such as nanoparticles, exosomes, whole cells, and red blood cells— have been developed to deliver therapeutic agents. However, despite these advancements, no fully developed and clinically viable intravenous drug delivery system currently exists. Thus, the development of precise delivery mechanisms to diseased tissues offers a significant opportunity to treat a broad spectrum of conditions safely. Our laboratory has pioneered a novel therapeutic delivery system, "Cargocytes," designed to transport therapeutic cargo directly to inflamed and damaged tissues with precision. These transporters are derived from mesenchymal stem cells (MSCs) genetically engineered with chemoattractant receptors (CCR2 and CXCR4) and the endothelial adhesion molecule (PSGL-1). This GPS-like guidance system allows Cargocytes to respond to P- and E-selectins on inflamed endothelial cells and chemoattractants (CCL2 and CXCL12) secreted by diseased tissues. The MSCs are then enucleated via gentle density gradient centrifugation and transfected with mRNAs encoding the therapeutic payload before intravenous administration. Our work shows that enucleation bestows the Cargocyte with unique functional and biophysical properties while providing significant safety advantages for therapeutic delivery. This application aims to: Aim 1: Optimize the in vitro production, cryopreservation, and biobanking of Cargocytes for subsequent studies. Aim 2: Conduct comprehensive immunogenicity and organ toxicity tests in vitro and in vivo using established immunocompetent mouse models. Aim 3: Evaluate the ability of optimized Cargocytes carrying an IL-10 payload to treat inflammatory pancreatitis effectively and safely in a preclinical mouse model of caerulein-induced chronic pancreatitis. Through these objectives, we aim to establish Cargocytes as a groundbreaking therapeutic delivery platform capable of addressing the unmet need for precise, targeted drug delivery in clinical applications.

NIH Research Projects · FY 2026 · 2025-02

Abstract: The PI’s lab focuses on developing effective and scalable machine learning (including deep learning) methodologies to address pressing challenges in healthcare. We have developed foundation models, self-supervised learning methods, multi-level optimization methods, interpretable machine learning (ML) methods, large-scale distributed ML systems, etc. to analyze multi-modal, high-dimensional, and dynamic clinical data, including medical images, electronic health records (EHRs), clinical notes, etc. for medical decision support in diagnosis and treatment. In the next five years, we will develop accurate, efficient, and interpretable multi-modal foundation models for the early detection of sepsis. Sepsis is a life-threatening condition that leads to widespread inflammation, multiple organ failure, and eventually death. Early detection and intervention of sepsis are critical to reducing the risk of death and minimizing the extent of organ damage. A foundation model (FM) is a large-scale ML model, like GPT-4, that is pre-trained on a vast dataset and can be fine-tuned for a wide range of specific tasks and applications. Possessing advanced capabilities for identifying nuanced clinical patterns and signals from large-scale patient datasets, FMs hold immense potential in the early detection of sepsis. Nevertheless, developing FMs for this task presents significant challenges, including scarcity of large-scale EHR data for pre-training, heterogeneity across various data modalities, prevalence of missing values and anomalies in patient records, substantial risk of overfitting during fine-tuning, and lack of interpretability, among other factors. We aim to develop transformative ML methods to address these challenges. First, we will curate large-scale high-quality EHR data for pre-training the FMs, by developing self-supervised learning (SSL) methods, bi-level optimization based methods, and multi-modal diffusion based generative models for imputing missing values, detecting outliers, and synthesizing large-scale pre-training data. Second, we will learn effective representations for EHRs by developing multi-modal Transformer models to handle heterogeneous data modalities, capture long-range dependencies among clinical variables, and incorporate medical knowledge. Third, we will pre- train the multi-modal Transformer model on curated large-scale EHR data by developing novel self-supervised pre- training methods, including a multi-modal masked data prediction method, a hierarchical SSL method, and an automated SSL approach. Fourth, we will fine-tune the pre-trained FM for sepsis early detection, by developing new fine-tuning methods based on meta learning, multi-level optimization, and neural architecture search. Fifth, we will develop interpretable FMs to improve the trustworthiness of detection outcomes. The proposed studies will be conducted on about 29 million patient records, which represent the largest efforts to date to study multi-modal FMs for sepsis. Our proposed research will democratize the early detection of sepsis by making pre-trained FMs accessible to a broader range of clinicians. Smaller medical institutions, which may not have extensive computational infrastructure, can leverage pre-trained FMs to jumpstart their development of in-house, specialized detection models. Besides, the developed technologies can go beyond sepsis and be applied for a broad range of clinical applications.

NIH Research Projects · FY 2026 · 2025-02

PROJECT SUMMARY This K01 award will support the career development of Dr. Alexandra Heaney, a climate epidemiologist in the Herbert Wertheim School of Public Health at UC San Diego. The candidate’s goal is to become a leader in interdisciplinary research that combines cutting-edge causal inference and statistical modeling with community- based mixed methods research to characterize the health impacts of climate-related environmental hazards and to build community resilience to these hazards. This application proposes linked career development and research activities to fill important gaps in knowledge surrounding the impacts of ambient dust and extreme heat exposure on adverse birth outcomes. Extreme heat is an established risk factor for preterm birth (PTB) and low birth weight (LBW), but knowledge of the impacts of mineral dust—a pollutant becoming more prevalent in the Western US due to climate change—remains limited. Clarification of these environmental factors' individual and combined effects on neonatal outcomes is needed. Further, local-level adaptive capacity is integral to climate resilience, yet little work has investigated the lived experience of adapting to extreme heat or dust exposures, especially among pregnant individuals. This project aims to advance the candidate’s expertise and skills in environmental and perinatal epidemiological methods, dust exposure science, and community engaged research to address these knowledge gaps. The candidate will leverage new modeled concentrations of dust and a cohort of ~6.5 million mother-child pairs from the Study of Outcomes in Mothers and Infants (SOMI) cohort to estimate the effects of dust exposure during pregnancy on PTB and LBW (Aim 1) and quantify the interactive effects of dust and extreme heat exposures on adverse birth outcomes (Aim 2). The candidate will then engage with community partners in Imperial Valley, CA where exposures to dust and heat are particularly high, to examine the perceptions of risk, adaptive behaviors, and adaptation resources used by members of the communities to mitigate the adverse impacts of these environmental hazards. The 3- year plan includes mentorship from four experienced and committed faculty at UCSD with expertise in community engaged and mixed-method research, perinatal epidemiology, and dust science. Two additional mentors—leaders in environmental epidemiology and environmental health policy—will support the candidate. Leadership of the proposed research, along with a training plan involving coursework, and mentored grant writing, will advance the candidate’s training objectives to: 1); build expertise in dust exposure science 2); build expertise in birth outcome research and perinatal and environmental epidemiological methods; 3) train in mixed-method and community engaged research approaches; and 4) strengthen collaborative partnerships and build leadership skills for directing transdisciplinary research projects. UCSD’s commitment to early career scientists; leadership in implementation science, epidemiology, and climate science; and close community partnerships will provide the candidate an outstanding environment to advance her career goals.

NIH Research Projects · FY 2026 · 2025-02

PROJECT SUMMARY Goal-directed perception and cognition rest on the ability to keep target information activated in mind, through periods when it is unavailable in the sensory environment. This working memory can serve to track occluded objects, wield goal templates for visual search, and retain a coherent representation of the visual world as the eyes move around. Working memory is considered an endogenous internal maintenance function, but successful behavior must also adjust goals in reaction to external conditions. Likewise, failure to integrate relevant sensory content into working memory, or to shield internal goal content from interfering input, are both uniquely characteristic of several neurological and psychiatric disorders. Yet the mechanisms that adaptively promote or prevent interactions between perception and working memory have been perplexing to isolate, and it is broadly contested how and where working memory information is stored. In addition to known fronto- parietal substrates, recent findings show that working memory engages distributed activations throughout subcortical and sensorimotor regions, and may further recruit the peripheral nervous system and sensorimotor apparatus. For instance, during a blank working memory delay, gaze and involuntary eye movements veer toward the location where a working memory item was encoded, and changes in pupil size track its remembered brightness. Such oculomotor and peripheral measurements have become widely adopted as indices of neuro-cognitive processing, but it is unknown what underlying activity they reflect and if they serve any functional role. This proposal tests the possibility that peripheral modulation, and pupil control in particular, may be a sensitive instrument to align internal goals and perceptual processing. Although the eyes are considered windows to underlying states, they do more than pass data through—they also modulate and filter what we extract from the environment. Rather than recapitulate neural activity, pupillary responses may subtly mold cortical working memory traces, hold the eyes in a goal-ready configuration, or bias visual perception in line with working memory features. The proposed studies will systematically test these possibilities in humans. The project will combine physiological measurements (fMRI and eye-tracking) with transcranial stimulation (TMS), to test the causal relationships between peripheral modulation, neural working memory signatures, and behavior. Specific Aims will test whether pupillary working memory signals convey behavioral relevance and decisional quality (Aim 1), configure to the predictive task context (Aim 2), or shape and interact with ongoing perception (Aim 3). This work will test the boundaries of cognitive influence on pupillary function, revealing new working memory mechanisms and unboxing potential for pupil states to be volitionally controlled. Every Aim will perturb activity at critical visuo-oculomotor loci, to dissect the underlying circuitry and define the information contained within cognitive pupillary inflections. This clarity will be essential in order to harness these integrative signals toward better methods for gauging and treating sources of visual and cognitive dysfunction.

NIH Research Projects · FY 2026 · 2025-02

The last decades have witnessed substantial progress in optical technologies revolutionizing our ability to record and manipulate neural activity. However, current cellular-resolution optical recording techniques have several limitations such as low temporal resolution due to slow kinetics of indicators and low frame acquisition rates of imaging setups. Furthermore, measures more common in human studies, such as local field potentials (LFPs) and electrocorticography (ECoG), cannot be inferred from optical recordings, leading to a gap between our understanding of the dynamics of microscale populations and brain-scale neural activity. Here we propose ultra-high density neuro-clear as a unique and innovative transparent probe technology to synergistically combine high-resolution optical imaging, electrophysiological recordings, and optogenetics for large-scale recording and modulation of neural activity. Neuro-clear will consist of planar and laminar probes based on two key technology innovations: (i) Transparent graphene electrodes and wires allowing for efficient light delivery without blocking the field-of-view of the microscope, and elimination of light-induced artifacts in the recordings, (ii) Adaptation of multi-layer silicon CMOS fabrication techniques for developing high-density flexible probes with a very small form factor, and (iii) Integration of data acquisition chips on polymer substrates to achieve minimalist SWaP (size, weight, and power) form factors suitable for head-mounted operation over extended recording sessions. Graphene electrodes will be nano-engineered to achieve ultra-low impedance and stable single-unit recordings. Neuro-clear will inherit the advantages of silicon neural probes and flexible polymer microelectrode arrays to probe the activities of neuronal microcircuits at multiple spatial and temporal scales through crosstalk-free integration of optical imaging, electrical recording, and optogenetics. Such a capability will enable in vivo studies of neural mechanisms responsible for complex behaviors that cannot be understood with existing technologies. Neuro-clear technology will be broadly applicable to problems in neuroscience and will transform neuroscientists' ability to study neural circuits.

NIH Research Projects · FY 2026 · 2025-02

PROJECT SUMMARY/ABSTRACT Eating Disorders (EDs) are bound together by their severe health consequences and often intractable course for affected individuals, which can only be ameliorated through a better understanding of ED etiology. Studies have typically focused on separate diagnostic categories (e.g., anorexia/bulimia nervosa, binge eating disorder), despite evidence for genetic and symptom overlap across diagnoses. Further, there is a need to examine EDs before and during their peak onset in adolescence, given the dynamic neurodevelopmental changes characterizing this period. This project uses a transdiagnostic and multimodal approach, leveraging large-scale longitudinal data collection from the Adolescent Brain Cognitive Development (ABCD) Study to prospectively identify genetic, neuroimaging, and behavioral measures that may be predictive of an ED in adolescence. A sample of adolescent girls being treated for an ED will also be included for clinical generalizability. Aim 1 (K99 phase) will identify behavioral and neuroimaging-derived correlates of EDs across both ABCD (ages 11-14) and clinical (ages 13-18) datasets, using sophisticated neuroimaging methods to parse through potential morphological and microstructural predictors of adolescent EDs. Aim 2 (R00 phase) will expand its study design to include genomic (polygenic risk for EDs and related conditions) and longitudinal behavioral and brain imaging data (ages 9 to 17) to inform a predictive model of the emergence of an ED in adolescence, and the impact of these discovered predictors in a clinical setting (ages 14-19). This project’s strategic utilization of ABCD Study data holds an unparalleled opportunity to uncover the etiological factors of an ED across both males and females using prospective longitudinal multi-site data, a research endeavour that otherwise would be extremely difficult and costly to initiate from scratch. Moreover, the inclusion of a clinical dataset allows for a rare but much-needed investigation of the generalizability of results from a sub-clinical to more severely ill patient sample. This project will also apply innovative methodologies, including the integration of polygenic risk scoring across diverse participants, alongside sophisticated neuroimaging techniques allowing for quantification of whole-brain microstructural features that may provide additional sensitivity in detecting predictive factors of an adolescent ED. Dr. Makowski’s proposed training plan, including training in ED research and machine learning methods, will enhance her existing skillset in psychiatric neuroimaging and genomics. The chosen mentorship team will add the necessary expertise and support that will facilitate Dr. Makowski’s transition to an independent research position, including additional training in ED research (mentor: Dr. Wierenga; collaborators: Dr’s Bischoff-Grethe, Fennema-Notestine), neuroimaging and genomics integration (co-mentor: Dr. Dale), neurodevelopment (collaborators: Dr’s Jernigan, Rhee) and machine learning (consultant: Dr. Zou). This award will position Dr. Makowski to successfully complete the aims of this project and work towards a more complete etiological model of EDs that can help inform future treatment.

NIH Research Projects · FY 2026 · 2025-01

PROJECT SUMMARY The complement system is a complex cascade of proteins that bridges innate and adaptive immunity by circulating in the bloodstream and rapidly initiating and amplifying an immune response when pathogenic material is identified. Discrimination between pathogenic material and host tissue is a vital function for maintaining a healthy immune system. Tissue-specific damage that is driven by complement activation and subsequent protein deposition at the tissue surface is characteristic of complement-mediated diseases. One of the key protectors of complement activation on host tissue is the Factor H protein (FH). FH can bind both heparan sulfate and sialic acid in the glycocalyx of glycoproteins and proteoglycans that covers most cells. FH inactivates complement component C3, a central protein that drives complement activity. FH is a member of a protein family composed of an additional five FH-related proteins (FHRs). Although these FHR proteins carry highly similar heparan sulfate-binding domains, FHR proteins counteract the regulatory mechanisms of FH and promote C3 activation and amplification of the complement response. Heparan sulfate and sialic acid have been appreciated as key drivers of host recognition, but their specific interactions and their relative importance is not well-defined. Heparan sulfate is a highly diverse polysaccharide that varies in composition across tissues. Sialic acid is a single sugar molecule that is often found on terminal residue(s) of larger asparagine- or serine/threonine-linked glycans on glycoproteins and gangliosides. The central focus of this project is to define the contribution of heparan sulfate to the tissue-specific regulation of complement, using a combination of biochemical, cell biological and genetic models in mice. We will (i) use in vitro biochemical and cellular models to define binding affinities of FH and FHR proteins for heparan sulfate and to quantify complement activation on the cell surface when heparan sulfate or sialic acid biosynthesis is disrupted, (ii) examine the impact of heparan sulfate on complement activation in a murine model of FH deficiency, which in humans results in complement activation and chronic inflammatory diseases, such as C3 Glomerulopathy and Age-Related Macular Degeneration; and (iii) determine the effect of recombinant heparan sulfate oligosaccharides as agents for sequestering FH or FHR proteins and altering tissue-specific complement regulation both in vitro and in vivo. These studies address the central theme of this request for applications focused on tissue-specific regulation of complement activation and host recognition. Defining the role of heparan sulfate in complement regulation could open the door to a new class of therapeutics that would significantly impact a number of human diseases.

NSF Awards · FY 2025 · 2025-01

Research Activity Identifier (RAiD) is a new digital persistent identifier (PID) specifically for research projects and activities, developed by the Australian Research Data Commons (ARDC). RAiD provides unique, digital persistent identifiers with corresponding metadata for research projects. This is especially helpful for long-term discovery, resolution, access, sharing, reporting and tracking of the researchers, resources, funding, and associated outputs of projects with multiple stakeholders over time. Based on international standards and guidelines, RAiD provides a transparent, visible, and reliable collection point for often overlooked or lost project information, even after closure, and helps to alleviate the administrative burden of risk-prone and repetitive manual entry of extensive data by multiple researchers when preparing research applications, submissions, funding requests, subproject allocations, project collaborations, and research reports. Currently there is no way for institutions in the United States to use RAiD, although interest has been expressed by stakeholders across the research ecosystem, including the Center for Open Science, health research funders, universities, cyberinfrastructure providers, multi-institution research projects, and individual researchers. This effort facilitates development of cyberinfrastructure for a hosted cloud service for a US Research Activity Identifier registration agency, a web application and API for minting RAiDs, and a business model and process for providing a RAiD service point for US-based entities. It builds upon and leverages existing expertise and resources at an NSF-funded advanced computing center, a national research data organization, and a robust nonprofit already providing PID infrastructure services for institutional members of ORCID and DataCite in the US. This award is jointly funded by the NSF Office of Advanced Cyberinfrastructure and the Directorate for Social, Behavioral and Economic Sciences (SBE). 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 · 2025-01

PROJECT SUMMARY/ABSTRACT We are in the middle of a global opioid epidemic. In 2020, 9.3 million Americans misused prescription opioid pain medications, with 8-12% going on to develop an opioid use disorder (OUD). OUD is highly heritable, but few of the relevant genes are known . A better understanding of how genetic differences make people susceptible or resistant to OUD will be invaluable for improving prevention, treatment, and the development of new pharmacotherapies. Genome-wide association studies (GWAS) are powerful, unbiased tools for elucidating the genetic basis of psychiatric and somatic disorders. In the past decade, hundreds of associations between specific loci and various substance use and misuse traits have been discovered. However, the greatest progress has been made for commonly used drugs, particularly tobacco and alcohol. In contrast, OUD GWAS have not yet reached the sample sizes needed to produce more than a handful of associations. In addition, current GWAS mostly focus on case:control diagnosis of OUD, missing critical pre- addiction stages, such as initial opioid use, subjective response to opioids, escalation of use, and the transition from problematic opioid use to OUD. Increasing our understanding of these pre-addiction stages will deepen our understanding of the genetic risk for OUD, and is an area that NIDA has identified as priority (e.g., NOT- DA-20-030 and NOT-DA-20-004). In this project, we focus on the genetic basis of pre-addiction. Ascertainment of clinically diagnosed OUD cases and opioid-exposed controls concentrates on extreme ends of the spectrum of risk. Focusing on pre-addiction is complementary and can be inexpensively collected at scale in already genotyped population- based cohorts. Pre-addiction traits confer risk for OUD; however, few large genetic datasets have been collected. We will use pre-addiction phenotypes that are genetically correlated with OUD in a multivariate framework for discovery, to boost power of existing opioid GWAS, and dissect the subcomponents of OUD. To accomplish these goals, we are extending our long-standing relationship with the genetics company 23andme, Inc., to deploy a survey taken from well-validated questionnaires to measure pre-addiction and related traits. Responses will be completed by 500,000 subjects from diverse ancestral populations. The results will be used to perform GWAS for pre-addiction and comorbid traits and combined with existing independent OUD GWAS using multivariate analyses available to us by our independent projects and network of collaborators. We expect that this work will demonstrate the utility of studying pre-addiction in population- based cohorts as a tool to accelerate opioid genetics research, and will provide an invaluable resource for the scientific community.

NSF Awards · FY 2025 · 2025-01

The goal of this project is to empower Artificial Intelligence (AI) researchers to more easily search, discover, and use AI-ready data sets. This will potentially streamline and democratize AI research. The project will investigate and develop data discovery services using innovative techniques that are themselves based on AI methods and can extract data set information from scientific papers. The resulting discovery services will be integrated into the National Data Platform Pilot (NSF award #2333609), providing scientists and students with an end-to-end research environment that connects them to national computing and storage resources. The project will conduct outreach and training efforts that will engage both scientists and students, particularly those at minority-serving institutions, who will help evaluate the technology. This project advances data search and discovery capabilities by using AI techniques to automatically extract and store data citation information, which must frequently be inferred, from research publications. This capability will help scientists and students, particularly those new to AI research, to identify AI-ready data sets that are relevant to their research from related publications. This removes startup impediments to creating new AI pipelines. Integrating these search and discovery services into the National Data Platform Pilot will enable users to more seamlessly conduct AI research on national-scale research resources that can scale beyond their personal computing and storage. The project uses AI-ready datasets from the National Artificial Intelligence Research Resource (NAIRR) to demonstrate and evaluate the effectiveness of the service. It also develops a generalized approach to support the integration of additional AI-ready NAIRR datasets and open corpora. The project democratizes the discovery and use of data in support of AI and other research through outreach and community engagement activities, including integration with hands-on workshops and hackathons within the National Data Platform Pilot. It also supports evaluating and reporting on the use and value of data by automatically producing usage statistics. 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 · 2025-01

PROJECT SUMMARY Human milk is considered the recommended sole source of human nutrition worldwide for at least the first six months of life and is the recommended continued source of human nutrition for at least the first two years of life. Yet, from a scientific perspective this basic human tissue type has been grossly understudied. The UC San Diego Human Milk Research Biorepository (HMB) was established in 2014 as a first-of-its-kind environmental epidemiology cohort (EEC) consisting of indexed human milk samples and associated clinical data that is available to the scientific community to aid our understanding of this critical source of infant nutrition. This open cohort study has accumulated over 110,000 aliquots of human milk samples to date from across the nation along with associated broad-based longitudinal data on infant health and development. Accordingly, it provides unprecedented current and future value to researchers and trainees as well as public health entities to better understand the short, intermediate, and long-term role of human milk in human health and disease. However, the existing cohort is lacking diversity in several critical areas, including racial/ethnic diversity and socioeconomic diversity. This proposal aims to increase the diversity of the HMB EEC by partnering with local lactation groups and academic and/or community partners in targeted diverse settings to enhance the recruitment of diverse populations into the study. Namely, we will recruit 300 new participants who represent low or low-middle income households and/or who self-identify as Black or Hispanic/LatinX. We further aim to improve the accessibility of the HMB EEC data to the scientific community through key enhancements to the study website and resource infrastructure. Finally, we will engage in efforts to raise awareness of the HMB EEC as a research resource that is available to lactation scientists who themselves represent populations that are underrepresented in medicine or who focus their research on questions pertaining to minority health and health disparities. This will be accomplished via the establishment of partnerships with historically Black colleges and universities and other minority-serving institutions to explore opportunities to enhance the diversity of the workforce involved in breast milk research. The HMB EEC provides unmatched value to the research community and public health entities to better understand the role of breast milk in child health and development across the lifespan. By enhancing the diversity of the cohort and improving the accessibility of the data to the scientific community at-large and specifically to diverse groups of human milk researchers, this EEC will provide greater benefit not only in the area of minority health and health disparities-related breast milk research but will also provide a unique cross-sectional snapshot of the “health” of the breast milk supply across the nation that can be monitored over time, by location, and by specific demographic groups.

NIH Research Projects · FY 2026 · 2025-01

Human milk is considered the recommended sole source of human nutrition worldwide for at least the first six months of life and is the recommended continued source of human nutrition for at least the first two years of life. Yet, from a scientific perspective this basic human tissue type has been grossly understudied. The UC San Diego Human Milk Research Biorepository (HMB) was established in 2014 as a first-of-its-kind environmental epidemiology cohort (EEC) consisting of indexed human milk samples and associated clinical data that is available to the scientific community to aid our understanding of this critical source of infant nutrition. This open cohort study has accumulated over 110,000 aliquots of human milk samples to date from across the nation along with associated broad-based longitudinal data on infant health and development. Accordingly, it provides unprecedented current and future value to researchers and trainees as well as public health entities to better understand the short, intermediate, and long-term role of human milk in human health and disease. However, the existing cohort is lacking diversity in several critical areas, including racial/ethnic diversity and socioeconomic diversity. This proposal aims to increase the broader representation of participants in the HMB EEC by partnering with regional and local lactation groups and academic and/or community partners in selected U.S. metropolitan settings to enhance enrollment in the study of women who are currently underrepresented in the HMB EEC. Namely, we will recruit 300 new participants who reside in three targeted metropolitan areas and we will test the value of providing monetary incentives to improve recruitment of participants who provide improved representation of the population in the HMB EEC cohort. We further aim to improve the accessibility of the HMB EEC data to the scientific community through key enhancements to the study website and resource infrastructure. Finally, we will engage in efforts to raise awareness of the HMB EEC as a research resource that is available to lactation scientists who themselves represent populations that are underrepresented in medicine or who focus their research on questions pertaining to minority health and health disparities. This will be accomplished via the establishment of partnerships with historically Black colleges and universities and other minority-serving institutions to explore opportunities to enhance the diversity of the workforce involved in breast milk research. The HMB EEC provides unmatched value to the research community and public health entities to better understand the role of breast milk in child health and development across the lifespan. By enhancing the diversity of the cohort and improving the accessibility of the data to the scientific community at-large and specifically to diverse groups of human milk researchers, this EEC will provide greater benefit not only in the area of minority health and health disparitiesrelated breast milk research but will also provide a unique cross-sectional snapshot of the “health” of the breast milk supply across the nation that can be monitored over time, by location, and by specific demographic groups.

NIH Research Projects · FY 2025 · 2025-01

PROJECT SUMMARY Amyotrophic Lateral Sclerosis (ALS) is a fatal neurodegenerative disease that was previously considered mainly a disorder of protein mislocalization. However, recent findings have unveiled a significant association of ALS with RNA misregulation. Among the 53 genes linked to ALS, the gene KIF5A has recently garnered attention. KIF5A, a kinesin motor protein known for its role in organelle transport, has been implicated in ALS through mutations that purportedly lead to a gain-of-function, resulting in a hyperactive state of the protein. My research has utilized machine learning predictions alongside experimental approaches to demonstrate that KIF5A functions as an RNA-binding protein. Moreover, I found ALS-related mutations in KIF5A modify its RNA-binding profile, uncovering a novel aspect of KIF5A's involvement in ALS. My preliminary findings indicate that KIF5A with ALS mutations exhibits a preference for binding to mRNA of heat shock proteins and several other genes associated with ALS. I propose that mutations in KIF5A contribute to motor neuron degeneration by disrupting RNA processing. The proposed research encompasses three objectives: (1) to investigate the impact of KIF5A ALS mutations on the proteotoxic pathway, (2) to explore the interactions between KIF5A and ALS-associated genes and RNA targets, and (3) to evaluate the effects of KIF5A mutations on transcription, RNA localization, and RNA-binding protein (RBP)-RNA interactions using spinal organoid models. Success in this project will lay the groundwork for innovative methods and insights into the misregulation of RNA processing in ALS. My expertise in quantitative, single-molecule imaging, combined with the Yeo lab's profound knowledge in RNA processing, stem cell models and neurodegeneration, positions me uniquely to lead the proposed research. These objectives will establish a foundation for my career as an independent researcher, focusing on the mechanisms of RNA transport in neurodegenerative disorders.

NIH Research Projects · FY 2026 · 2025-01

PROJECT SUMMARY Cerebral blood vessels are critical to deliver blood, containing oxygen and nutrients, to every neuron and glial cell in the brain. In addition, the endothelial cells comprising central nervous system blood vessels possess unique properties, termed the blood-brain barrier (BBB), that allow them to tightly regulate the movement of ions, molecules, and cells between the blood and the brain, thus, tightly regulating the extracellular environment of the brain. Studies have indicated that neurovascular dysfunction, including hypoperfusion and BBB dysfunction, may be an important component of Alzheimer’s disease pathogenesis. This vascular dysfunction could lead to accumulation waste products such as amyloid, leakage of serum components to the brain, and increased neuroinflammation, all of which could have important impacts on the neurodegeneration that is observed in patients with Alzheimer’s disease. Despite the potential importance of neurovascular dysfunction, very little is known about the molecular changes to cerebral blood vessels in patients with Alzheimer’s disease, and how these changes may affect neurovascular function and the progression of Alzheimer’s disease pathology. We have performed proteomics on blood vessels isolated from human patients with Alzheimer’s disease and from age and sex matched controls. Interestingly, we found downregulation of pathways involved in angiogenesis and barrier formation, which may account for the hypoperfusion and BBB dysfunction, respectively, observed in Alzheimer’s disease patients. The proteomic data also showed robust downregulation of the transcription factor SOX18 in the blood vessels of patients with Alzheimer’s disease. We further used mice models to downregulate Sox18 expression in brain endothelial cells and found very similar changes to those found in Alzheimer’s disease patients, including a downregulation of angiogenesis and barrier formation pathways. Therefore, we hypothesize that downregulation of SOX18 in brain endothelial cells is key to the neurovascular dysfunction observed in patients with Alzheimer’s disease. In this grant we will first examine the role of Sox18 in modulating neurovascular function in mice, including angiogenesis and barrier formation. We will then use human induced pluripotent stem cell models of the BBB to identify the molecular mechanisms by which SOX18 regulates neurovascular function. We will then determine whether modulating Sox18 expression can alter the disease course in multiple mouse models of Alzheimer’s disease. These experiments will allow us to understand the role of SOX18 in neurovascular function, and determine whether targeting SOX18 could limit the pathogenesis of Alzheimer’s disease.

NIH Research Projects · FY 2026 · 2025-01

4Summary3 Cardiovascular disease (CVD) is the number one cause of death worldwide. The underlying cause is athero- sclerosis, which progresses to thrombosis and leads to myocardial infarction, stroke, and pulmonary embolism. The main drugs used for CVD management are statins and anti-coagulants, but they have side effects, must be taken as a lifelong therapy, and there is a lack of patient compliance in primary prevention. Immunothera- peutic approaches with atheroprotective antibodies are promising; however, the need for lifelong treatment means that passive immunotherapy is unsuitable for most patients due to the high costs per dose. To over- come these challenges, we propose a CVD vaccine that targets S100A9 or S100A9 and PCSK9 to sim- ultaneously target inflammation or cholesterol metabolism. S100A9 and its heterodimer S100A8/9 regu- late myeloid cell function and control inflammation. We have shown that knockout of S100A9 attenuates ather- osclerosis in mouse models. S100A9 deficiency is protective but has no effect on hemostasis. Given the role of S100A8/9 in CVD pathogenesis, we propose a vaccine that targets S100A9. Plant virus like particles (VLPs) derived from cowpea mosaic virus (CPMV) will display S100A9 and/or PCSK9 epitopes and deliver them to innate immune cells, activating the latter by binding to pattern recognition receptors (PRRs). Our proposal builds on extensive supporting data validating S100A9 as a target, and demonstrating the efficacy of plant vi- rus-based vaccines. We will develop S100A9-CPMV vaccine candidates and assay whether anti-S100A9 anti- bodies reduce S100A9 serum levels, inflammatory cytokines, and cholesterol, ultimately to achieve atheropro- tective effects in a mouse model of atherosclerosis. We will test efficacy in this model, as well as safety and mechanism of action (Aim 1). Because CVD is a multifactorial disease, we will develop a multi-target vaccine that targets S100A9 and cholesterol checkpoints such as PCKS9 – this is expected to increase efficacy of the approach through combined attenuation of inflammation and reduction of cholesterol (Aim 2). Finally, S100A9 is linked to cancer as well as CVD. We will therefore test the efficacy, safety, and mechanism of action of our approach in high-risk models: mice undergoing chemotherapy using healthy mice and tumor-bearing athero- sclerosis models. Synergistic effects of the S100A9 vaccine candidate will be assessed. We will also investi- gate the effects of aging and the circadian cycle on the efficacy and safety of the vaccine (Aim 3).

NIH Research Projects · FY 2026 · 2025-01

PROJECT SUMMARY/ABSTRACT The transition from a fully differentiated oocyte to a totipotent embryo is one of the most dynamic transitions in biology. Remarkably, this transition occurs in the absence of new transcription. In the mouse, transcription is globally silenced in the oocyte before ovulation and is not fully reactivated until the late 2 cell embryo stage. This period of transcriptional quiescence is highly conserved from worms to humans, and oocytes that fail to undergo transcriptional silencing are not fully competent to support further development. Without new transcription, the oocyte and early embryo depend upon post-transcriptional mechanisms to regulate gene expression to drive development through this window of transcriptional silence. However, the mechanisms required to silence transcription in the oocyte and orchestrate gene expression in the absence of transcription during development remain poorly understood, particularly in mammals. A better understanding of these mechanisms is critical both to improve our understanding of the earliest stages of mammalian development and the diagnosis and treatment of infertility, as only ~50% of in vitro fertilized human embryos successfully traverse this period of transcriptional silence. The overarching goal of this project is to uncover molecular mechanisms required for successful developmental progression from oocyte to embryo during this window of transcriptional silence. One post-transcriptional mechanism known to play a critical role during this period is regulation of mRNA polyadenosine (poly(A)) tail length in the cytoplasm to control translation, where cytoplasmic polyadenylation activates translation and deadenylation leads to translational repression and/or decay. In recent findings from our laboratory, we have profiled poly(A) tail lengths transcriptome-wide across the entire transition from oocyte to embryo. Integrating these data with recently published ribosome profiling data, we have produced the first transcriptome- wide analysis of poly(A) tail and translation dynamics across the entire oocyte-to-embryo transition in a mammalian system. Building on these data, we plan to use the mouse model to investigate (i) the mechanisms that drive global transcriptional silencing in the oocyte; (ii) the post- transcriptional mechanisms regulating poly(A) tail length and gene expression during transcriptional silence; and (iii) regulation of maternal factors required to mediate reprogramming to totipotency. These studies will advance our understanding of the mechanisms that drive gene expression and development during transcriptional silence from oocyte to embryo in mammals, with the long-term potential to improve the diagnosis and treatment of infertility.

NIH Research Projects · FY 2026 · 2025-01

Animals efficiently collect sensory information from the environment and adapt their behavior accordingly. This process predominantly involves active movement of the body and sensory appendages to sample space through purposeful actions. Mammals explore their olfactory environment through intermittent sniffs, they see using smooth pursuit of the eyes to track moving objects, they touch with digits, and, for rodents, through the rhythmic sweep of their vibrissae. Here we propose experiments, models, and theory to address how object position is robustly computed from vibrissa touch. Whisking is an ideal system to study the coding, circuitry, and dynamics of active sensing. The underlying circuit for rhythmic motor control of the vibrissae is part of the greater orofacial sensory system that is coordinated by the oscillator for breathing. The whisking rhythm per se is sufficiently precise so that under behaviorally relevant conditions the representations of whisking and touch are well described in terms of phase in the whisk cycle, as opposed to by kinetic parameters. We focus on a computation in the input layer, L4, to cortex. Our data is at the level of fields of single spines and boutons as well as single neurons, all in behaving mice. Preliminary results show that a major fraction of thalamocortical (TC) boutons encode phase in the whisk cycle so that the TC input to cortex has the geometry of a torus, with phase and neuron identity as the dimensions. L4 excitatory neurons inherit a phase preference for touch in the whisk cycle through the mapping of this input, across a cortical column. The wiring pattern of these projections and its degree of order will constrain the computation performed at the TC stage. Aim 1 involves the construction of a theoretical model that is motivated by past and preliminary data. The model accounts for phase sensitivity in neurons that are subthreshold but poised to invariantly represent a touch input. The model network has a ring architecture, with a thalamic excitatory rhythmic drive balanced by local inhibition, extending continuous attractor models into the realm active sensing. Aim 2 focuses on measurements of the phase tuning of the thalamocortical input, of the activity of L4 inhibitory neurons, and of the predominantly subthreshold response of L4 excitatory neurons during rhythmic whisking. This Aim establishes the balance between an excitatory TC input and the recurrent inhibition. Aim 3 focuses on the transformation of touch into a ‘bump’ of activity, in the space of phase in the whisk cycle, by L4 excitatory neurons. Here we establish the nature of intracellular dynamics and excitatory synaptic architecture and dynamics. We investigate and characterize invariant properties of the bump in L4 activity. Aim 4 completes our theory with the addition of excitatory synapses that are transiently active during the bump. We conjecture that the local excitation is asymmetric in the phase dimension and operates with time-lags; our preliminary data supports this conjecture. The local excitation leads to a bump that exists only for a fraction of the whisking cycle but is invariant in amplitude and lifetime to signify touch. Our project addresses three neuronal computations essential in active sensing. One is the inherence of order in maps of sensory features between two layers, here phase from thalamus to cortex. A second is the interplay between excitatory inputs and inhibitory interactions to maintain a network at the threshold of activation. The third, and major effort, concerns transient recurrent activity to stabilize a touch response tied to rhythmic self-motion. Our work thus provides a solution to a basic problem in active sensing, i.e., the separation of ex-afferent from self-motion sensory signals. Our study will provide new fundamental knowledge that highlights the role of subcortical mechanisms in the neural computations of sensory invariance. Dysfunction in these computations can lead to sensory "overload", in which individuals no longer reject irrelevant details of the sensory stream. This is reminiscent of conditions that induce meltdowns and shutdown in autism spectrum disorders. An outcome of our research will thus be a new model experimental system to potentially address the root cause of this dysfunction. As such, the proposed fundamental research will contribute to reducing the burden of a major neurological disease.

NIH Research Projects · FY 2025 · 2025-01

PROJECT SUMMARY/ABSTRACT In the central nervous system (CNS), blood vessels have specialized functions that are critical for maintenance of CNS homeostasis. These include the blood-brain barrier (BBB), which tightly controls the access of ions, molecules, and cells to the CNS, and neurovascular coupling, a process by which blood flow is transiently increased to regions of elevated neural activity. Further, vascular cells regulate development and function of neurons and glia, and perivascular spaces serve as conduits for cerebrospinal fluid circulation, which may be important for waste clearance. These processes rely on the coordinated function of many cell types, including endothelial cells, pericytes, vascular smooth muscle cells, perivascular fibroblasts, astrocyte endfeet, and immune cells, which together constitute a neurovascular unit (NVU). Emerging evidence suggests that many NVU properties are dynamically regulated by physiological cues, including circadian rhythms and neural activity. This suggests that the CNS vasculature achieves a balance between the stability required to achieve continuous, highly tuned oxygen and nutrient delivery, and the plasticity required to dynamically modulate function. Importantly, NVU dysfunction is observed in aging and neurological diseases, including Alzheimer's disease, and such dysfunction contributes to the associated CNS pathology. A better understanding of the molecular mechanisms underlying neurovascular stability and plasticity in health, and age- and Alzheimer’s disease- associated dysfunction, may reveal new molecular targets for treating this dysfunction. This project will address this knowledge gap by quantifying the lifetimes of neurovascular proteins in health, aging, and Alzheimer’s disease. Protein lifetime is a fundamental parameter that profoundly influences protein function, and thereby influences cell and tissue function: long-lived proteins can stabilize cellular structures, but are also susceptible to accumulated damage; short-lived proteins are amenable to rapid modulation by physiological cues, but have high energetic burden. Changes to protein lifetimes are potential mechanisms of aging- and disease-associated cellular dysfunction. Although protein lifetimes have been measured in the CNS, the vast majority of neurovascular protein lifetimes have not been quantified due to the low vascular fraction in whole brain tissue. This project will generate a comprehensive atlas of neurovascular protein lifetimes in health, aging, and a tauopathy-based model of Alzheimer’s disease. Aim 1 will employ stable isotope labeling in mammals (SILAM), nonenzymatic vessel isolation, and mass spectrometry-based proteomics to quantify protein lifetimes, and identify changes in aging and Alzheimer’s disease. In Aim 2, single nucleus RNA-seq will be used to define the cellular and transcriptomic composition of isolated microvessels, and allow inference of cell type(s) of origin of proteins detected in Aim 1. Together, this work will advance understanding of the molecular bases of neurovascular function and yield new hypotheses for molecular mechanisms underlying age- and Alzheimer’s disease-associated neurovascular dysfunction.

NIH Research Projects · FY 2026 · 2025-01

PROJECT SUMMARY The advent of anti-A immunotherapies is transforming the treatment of Alzheimer's disease (AD), demanding novel precision medicine approaches to inform prescribing guidelines and risk-benefit assessment. Critically, this emerging class of AD therapeutics carries significant risks, including amyloid-related imaging abnormalities (ARIA) associated with brain edema and microhemorrhages, and brain atrophy, for which the mechanisms and long-term consequences remain undetermined. Risk for ARIA increases dose-dependently with APOE4, the strongest single genetic risk factor for AD that is also associated with elevated blood-brain barrier (BBB) permeability and cerebral amyloid angiopathy. Evidence implicating cerebrovascular fragility in ARIA development, attributed to immunotherapy-triggered A clearance from blood vessels, suggests that BBB dysfunction may be a critical mechanism underlying ARIA, and perhaps serve as a valuable biomarker for predicting and monitoring ARIA. Consistent reports of brain atrophy following anti-A immunotherapies raise concern for drug-induced acceleration of neurodegeneration, yet the cellular changes contributing to volume loss on structural MRI have not been investigated. Distinguishing benign alterations in fluid dynamics or inflammation from neuronal loss will be essential for ensuring safe and effective widespread roll-out of these novel agents. The proposed investigation will address these pressing outstanding issues by integrating advanced MRI techniques into real-world clinical settings to evaluate BBB permeability and brain microstructure as biomarkers for ARIA risk and treatment response. A-positive individuals prescribed anti-A immunotherapy will undergo cognitive assessment, amyloid PET, and plasma AD biomarker measurement at screening and 12-months, as well as routine MRIs to screen for ARIA. Participants will complete research MRIs, including restriction spectrum imaging to measure brain microstructure and dynamic contrast-enhanced MRI to quantify BBB permeability, prior to treatment, upon detection of ARIA, and at 12-months. This project will test the hypotheses that pre-treatment BBB permeability and abnormal microstructure predict ARIA incidence and colocalize with regions of ARIA, and will characterize trajectories of dynamics in BBB permeability and brain microstructure over the treatment course (Aim 1). BBB leakage and microstructure are expected to predict and correlate with treatment response, as quantified by change in cognition and AD biomarkers (Aim 2). Associations of BBB permeability and microstructure with ARIA and treatment outcomes are expected to differ by factors previously suggested to modify anti-A immunotherapy response, including sex, age, APOE4, and race/ethnicity (Aim 3). As the first study to directly evaluate BBB breakdown and brain microstructure along the time-course of anti-A immunotherapy, this project is anticipated to inform the development of critically-needed screening and monitoring biomarkers and guide clinical recommendations that enhance safety, efficacy, and patient access.

NSF Awards · FY 2025 · 2025-01

A prominent paradigm used in both mathematics and computer science is the “structure vs randomness'' paradigm. At one end, it aims to identify structure in mathematical objects that is useful for their mathematical analysis and for the design of efficient algorithms for their manipulation. At the other end, it aims to use randomness and random-like properties for the analysis of objects that lack structure. Randomness is a common mathematical tool used throughout mathematics and computer science. One can sometimes identify “random like'' properties of mathematical objects that are as useful as true randomness for their study and analysis. In the best-case scenario, randomness can be identified as the absence of structure, and the two notions of structure and randomness can be seen as complementary. The project will expand the bridge between mathematics and computer science and may have a practical impact on widely adopted algorithms. Integration of research and education is a key component of the project. This project focuses on a novel approach towards this “structure vs randomness'' paradigm, whose main goal is to obtain significantly improved quantitative bounds for many important problems in mathematics and computer science. At the core of this new paradigm are two new concepts: spreadness and mixing. Spreadness is a quantification that there are not too many elements in any structured subset of the ambient universe and mixing is a measure for how two objects behave jointly via some common operation. The project aims to develop both the theory and applications of this new approach. On the theory side, we aim to build a versatile framework that can both connect existing applications and extend them to new ones. On the applications side, the proposal highlights exciting potential applications across several fields - additive combinatorics, communication complexity, graph theory, and fast combinatorial algorithms. 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.