University Of California, San Diego

NSF Awards · FY 2025 · 2025-09

Dark matter is a mysterious substance that makes up most of the matter in the Universe, but it has never been seen directly. To uncover this cosmic enigma, scientists are conducting the XENONnT experiment. This experiment uses a detector filled with nearly nine tons of ultra-pure liquid xenon to search for extremely rare interactions that could help us understand what dark matter is composed of. XENONnT is the last experiment in the international XENON Dark Matter project, which has received support from the National Science Foundation since it began. This project creates a rich environment for educating students and researchers in the U.S. and around the world, with more than twenty institutions collaborating globally. The scientists working on this project are trained in advanced science and technology that cover multiple disciplines. The specialized tools and techniques they use, along with advanced data analysis and statistical methods, are not only important for understanding dark matter but also have significant applications in fields like medicine, nuclear safety, and data science. Candidates for the dark matter which dominates the matter content of the Universe span decades in mass and interaction cross-section with normal matter. The class of Weakly Interacting Massive Particles (WIMPs) has been the most studied theoretically and experimentally with indirect and direct searches as well as at the Large Hadron Collider. The sensitivity for WIMPs direct detection has increased by many orders of magnitude in the past twenty years thanks to experiments using liquid xenon in dual-phase time projection chambers with increasing target mass and decreasing background. The phased XENON Dark Matter project has led the direct detection field with its XENON10, XENON100 and XENON1T experiments and has paved the way to the current generation of multi-tonne scale liquid xenon detectors, including the largest of the XENON detectors, XENONnT with 6 tonnes of active target. The unprecedented ultra-low background achieved by XENONnT, the lowest among all direct searches, has enabled a sensitive search not just for WIMPs but also other rare interactions, such as the recent first observation of coherent elastic neutrino-nucleus scattering from solar B-8 neutrinos. This award will enable the XENON US groups to continue to contribute to the operation of the experiment at the Italian Gran Sasso Underground Laboratory (LNGS) and to continue to lead several science analyses using the data acquired to-date with the XENONnT detector. 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 · 2025-09

Children learn about numbers through their senses and by learning to count before starting school. Learning about numbers is critically important as a foundation for future achievement in the mathematics classroom. Most research on early number learning focuses on visual learning, even though children interact with objects and numbers through vision, touch, and sound. In this project, researchers will investigate how children learn about numbers through different senses, including in situations when they cannot use visual cues. The research team will work with children who have differing amounts of visual experience (e.g., blindness or visual impairments) and use research methods that focus on other senses including touch. Research aims include (a) investigating non-visual strategies for learning how to count and (b) exploring how children learn to perceive and compare different amounts of things. This work will help deepen and broaden current scholarship on early number learning. In addition, research outcomes will benefit those who can and cannot see. The results from this study may inform mathematics instructional practices for young children. Researchers in this project will work with children having differing levels of visual acuity. Mathematics skills are correlated in development with a range of visual abilities; however, numerical information can also be accessed through non-visual senses like hearing and touch. Some children are born unable to see, yet they learn about numbers. The broad purpose of this project is to understand the precise role that vision plays in numerical development. One research aim is to learn how those children discriminate and estimate perceptual arrays. A second aim is to explore how they learn counting skills. The research team will explore whether children, who learn haptically, pass through the same stages as children who learn to count visually. In study one, over 100 children ages 2 to 12 will be presented with haptic stimuli (e.g., small groups of raised bumps on a flat surface), and asked to estimate how many bumps they perceive. They will complete various validated tasks such as Give-N, highest count, and haptic working memory. In addition, researchers will administer a version of the Test of Early Mathematics Ability 3. In a second study, the research team will investigate the role of vision in the development of counting skills using set matching tasks for which validity has been gathered from prior studies. For study two, data from over 100 children ages 3-12 will be collected. Fifty additional children ages 3-12 will be added to study two with an intent to explore their counting abilities with large sets as part of the Give-N task. Only those children who show proficiency with small sets will be eligible for the large set study. In study three, 100 children ages 2-7 will be administered four tasks from study one in addition to the Non-Verbal, Same-Different task. Finally, in study four, 60 children ages 2-7 will complete the Give-N and Highest Count tasks. Children from the United States and India will participate. Tasks will be adapted to focus on counting violations as well as anticipating their outcomes on the tasks. Data from the studies will be analyzed quantitatively using multiple regression techniques that involve multiple covariates. One benefit from this project is a deeper understanding of how young children learn to count with senses besides vision. There is potential for research results to translate to mathematics instruction and learning contexts for all learners. This project is supported by NSF's EDU Core Research (ECR) program. The ECR program emphasizes fundamental STEM education research that generates foundational knowledge in the field. Investments are made in critical areas that are essential, broad and enduring: STEM learning and STEM learning environments, broadening participation in STEM, and STEM workforce development. 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 · 2025-09

Project Summary The heart consists of a broad spectrum of cardiac cell types that form distinct cardiac structures critical for maintaining heart function. These cell populations include not only cardiomyocytes, cardiac fibroblasts, epicardial cells, endothelial/endocardial cells and smooth muscle cells, but also more specialized cell types comprising the cardiac valves, cardiac conduction system, etc. Thus, maintaining the function and homeostasis of these cell types is crucial for optimal heart performance, and disrupting their overall maintenance can result in distinct heart diseases including mitral valve prolapse (MVP), one of the most frequent valvular heart diseases (VHD) that has a 2-3% prevalence in the general population. However, despite recent genetic studies identifying potential genetic loci associated with MVP, what are the specific cell lineages affected during MVP and how do gene regulatory networks (GRNs) control genetic programs that direct their pathologic outcomes are key biomedical questions that remain to be elucidated. Thus, to examine specific cell-types participating in VHDs, particularly MVP, we propose to implement joint single cell/nuclear (sc/sn) RNA-seq and ATAC-seq technologies (i.e. single cell multi-omics) on normal and MVP/diseased human mitral valves. In addition to identifying distinct CV cell-types and their related transcriptional profiles and chromatin landscape, we seek to elucidate the interactions between cell-type specific cis-regulatory elements/CREs (e.g. enhancer-promoter connections), which mediate the GRNs that control how CREs direct gene expression of these cell types in normal and MVP mitral valves. Furthermore, because structural form is critical for maintaining cardiac valve function, we propose to further investigate the spatial organization of identified cell types in the mitral valves of human hearts with and without MVP. Through these multi- disciplinary integrative efforts and analyses, we plan to examine the hypothesis that CREs and their enhancer- promoter interactions dynamically function and coordinate in a cell-type specific manner to direct lineage- specific gene expression during mitral valve homeostasis and MVP defects/disease, and altering these highly- regulated cell-type specific CREs and GRNs, especially in cardiac valve specific cell types, can lead to MVP and possibly other VHDs. Specifically, we propose to 1) identify human cardiac valvular cell-types and their gene regulatory programs in normal and MVP defective/diseased mitral valves; 2) investigate the spatial organization of the diverse cardiovascular cell types of normal and MVP defective/diseased mitral valves; and 3) examine how perturbations of cell-type specific CREs and GRNs during MVP impact cell function and gene expression.

NIH Research Projects · FY 2025 · 2025-09

PROJECT SUMMARY Mechanisms of gene regulation in bacterial defense islands Advancements in bioinformatics and the availability of tens of thousands of bacterial genome sequences have enabled the discovery of diverse pathways in bacteria that defend against environmental stress and bacteriophage (phage) infection. Over 100 different antiphage immune systems have been identified, and each bacterial genome encodes a different combination of ~5-20 such systems. Over the past five years, the molecular mechanisms of many antiphage immune systems have been deciphered, but because immune systems are typically studied one-by-one in model organisms, how these systems are regulated in their native hosts is not well understood. Our lab previously identified the transcriptional regulators CapH+CapP and CapW, which are each associated with diverse antiphage immune systems and control their expression in response to phage infection and/or DNA damage. Our fortuitous discovery of CapH+CapP and CapW implies that many similar regulators remain to be discovered. The aim of my research is to identify and characterize novel transcriptional regulators associated with antiphage immune systems in clinically-important bacterial pathogens. While studying ubiquitination-related BilABCD and BubABCD systems, I identified the novel transcriptional regulators CapK and CapS, and further found that these proteins co-occur with a variety of antiphage immune systems. I will define the upstream signal(s) and molecular mechanisms of CapK+CapS, thereby expanding our knowledge of how bacteria respond to phage infection. Building off my work on CapK+CapS, I will perform comprehensive bioinformatics searches of bacterial genomes to identify new immune system-associated transcriptional regulators, then use my established experimental workflow to validate their activity and define their molecular mechanisms. Complementing this work, I will perform gene expression profiling (RNA-Seq) on a large panel of clinical Enterobacter isolates with distinct sets of antiphage immune systems, to determine whether and how these systems are regulated in response to phage infection, DNA damage, and other stress. This work will define the global transcriptional control networks that regulate expression of antiphage immune systems and coordinate the bacterial response to infection. Together, the work proposed here will comprehensively define the mechanisms of transcriptional regulation in antiphage immune systems, and establish gene expression regulation as a widespread means of bacterial immune system control.

NSF Awards · FY 2025 · 2025-09

The National Science Foundation (NSF) Graduate Research Fellowship Program (GRFP) is a highly competitive federal fellowship program. GRFP helps ensure the quality, vitality, and strength of the scientific and engineering workforce of the United States. The program recognizes and supports outstanding graduate students who are pursuing research-based master's and doctoral degrees in science, technology, engineering, and mathematics (STEM), including STEM education. GRFP provides three years of financial support for the graduate education of individuals who have demonstrated their potential for significant achievements in STEM. This award supports the NSF Graduate Fellows pursuing graduate education at this awardee institution. 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 · 2025-09

PROJECT SUMMARY The continuous influx and prioritization of particular aspects of sensory information into the nervous system is fundamental for interaction with the environment. The brain must dynamically modulate neural representations of and behavioral responses to relevant sensory stimuli depending on an organism’s internal state. This flexibility can drive important changes in behavior, subsequently conferring evolutionary advantages and balances to homeostatic needs (e.g., a small fish might benefit from heightened sensitivity to food-relevant sensory cues when hungry, enhancing its ability to detect small prey-like organisms). Collective behavior, such as the coordinated movement of a school of fish, is thought to confer a selective advantage, helping the group perform behaviors such as food-seeking more effectively. How does an animal group synchronize its behavior based on the internal states of individual members? Relatively little is known about the neural circuits processing the social motion of conspecifics and how they may be modulated by an internal state, such as hunger. To better understand how internal states influence complex natural sensorimotor behaviors, this project will investigate the neural circuits involved in hunger-dependent perception of social motion in schooling fish. To accomplish this, the small and transparent micro glassfish (Danionella cerebrum) will be used, a new model system in neuroscience with genetic amenability, lifelong optical transparency, and innate engagement in coordinated schooling behavior. Previous work in the Lovett-Barron lab has indicated that adult D. cerebrum engage in schooling using vision alone, providing a unique opportunity to investigate the brain-wide networks that underlie hunger-dependent social motion perception using a visual virtual reality system and simultaneous brain-wide, cellular-resolution two-photon calcium imaging in behaving adult fish. In addition, multi-animal posture tracking and pharmacological perturbation will be used to quantify complex group behavior and probe the involvement of specific brain areas to state-dependent behavior. This project will identify the neural populations involved with the perception of and response to group social motion across the brain and investigate how those circuits are modulated by hunger. Then, targeted pharmacological perturbation of hunger-producing neurons will be used to reveal how this population influences the sensory representation of social motion. Understanding how the brain responds to hunger cues and regulates sensory processing is critical for comprehending the complex interplay between appetite regulation and sensory perception. By leveraging insights from evolutionary conserved neural circuits, this research has the potential to uncover fundamental principles applicable to diverse vertebrate species, including humans, paving the way for novel strategies to address obesity and malnutrition on a broader scale.

NSF Awards · FY 2025 · 2025-09

Wildfire is happening more often near cities and towns, putting people, homes, and communities at greater risk. Since wildfires are growing larger and more intense it is even more important to take steps to protect these communities. One helpful way to prepare and respond to wildfires is by using computer modeling and simulation. This powerful tool helps predict how fires might spread in areas where forests and natural areas meet cities and towns. These areas are called the wildland-urban interface (WUI). However, creating accurate models is challenging because how a fire spreads in an urban area is affected by many complex processes that occur in both small areas (like a building) and large areas (like a whole neighborhood). This project aims to understand these processes better and build more reliable models that can predict how fires will act in WUI areas, whether at small or large scales. The team also plans to create an easy-to-use computer program that will help emergency planners and local leaders use these tools to make better decisions about evacuations, managing fires, and keeping communities safer. The technical aspects of the proposed research are organized around four primary objectives identified as: (i) to develop a fundamental physical understanding of how fire interacts with individual structures and materials in urban environments at the local scale; (ii) to investigate how these localized interactions influence fire dynamics at intermediate scales—such as neighborhoods and communities—thereby bridging the gap between structure-level physics and community-scale outcomes; (iii) use insights from items (i) and (ii) to construct a computationally efficient, large-scale reduced-order model that accurately predicts fire spread in wildland-urban interface (WUI) scenarios, while capturing the essential underlying physics; (iv) to integrate models developed into a user-friendly, operational platform designed to enable real-time prediction and support decision-making for fire preparedness, response, and mitigation in WUI regions. The project outcome is expected to have a significant societal impact, addressing the increasing wildfire risks driven by shifting hydro-meteorological patterns, drought, and urban sprawl. It will produce predictive tools and decision-support platforms to aid real-time evacuation and firefighting strategies. Additionally, it will inform land-use planning, building codes, and zoning regulations to reduce future risk. Notably, the project promotes broad applicability by guiding policies that ensure all populations receive adequate support during disaster preparedness and recovery efforts. 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 · 2025-09

PROJECT SUMMARY Glioblastoma multiforme (GBM) is the most common malignant primary brain tumor and, despite incremental advances over the past few decades, has a five-year survival rate less than 10%. The failure of targeted drug therapies and this stagnation in therapeutic development is due, in part, to its characteristic heterogeneity and plasticity––“multiforme”––highlighting a critical need to understand the biological processes underlying these GBM hallmarks. Extrachromosomal DNA (ecDNA), large circular DNA elements that harbor oncogenes and enhancers, are a class of amplifications with oncogenic properties due to their unique structure. Without centromeres, ecDNA segregate randomly into daughter cells, which promotes genetic heterogeneity and exceptionally high copy number. ecDNA is present in over 50% of GBM tumors, the most of any cancer type, and the most prevalent genes found on ecDNA are well characterized cellular state drivers such as EGFR and PDGFRA. Despite the well-documented individual relationships between glioblastoma, extrachromosomal DNA, and intratumoral heterogeneity, the interplay between the three is not well understood. The overall goal of this proposal is to characterize the role of ecDNA in GBM transcriptional heterogeneity––diverse distributions of GBM cellular states––and plasticity––frequent cell state interconversions––during tumor initiation and upon drug treatment. Given its nonequal inheritance and intra-tumoral copy number variation, the central hypothesis of this proposal is that ecDNA enable cellular state heterogeneity and plasticity. By comparing engineered models that differ only in how EGFRvIII and PDGFRAΔ8–9 are inherited, Aim 1 will determine how ecDNA shapes the distribution of GBM cellular states during tumor initiation. Aim 2 will characterize the heritability and plasticity of cellular states during and after targeted drug therapy with an EGFR inhibitor in barcoded isogenic patient derived xenograft models that differ in how they amplify EGFRvIII: on ecDNA vs. chromosomes. In addition to determining whether cellular state transitions occur more frequently (i.e., high plasticity) in ecDNA+ models, this aim will also directly establish whether ecDNA enables drug resistance to targeted therapy in vivo. Heterogeneity and plasticity are thought to enlarge the total fitness landscape promoting adaptation during evolution and drug treatment, and as such, clarifying the mechanisms underlying these GBM hallmarks, as expected with this proposal, is essential. The expertise in glioma modeling present within the Furnari lab will come together with the expertise in genomics of the Ren lab to form an ideal environment to execute this research plan at UC San Diego. Through graduate coursework, a diverse mentorship team, and hands-on research, this proposal will provide the training to become a successful independent physician-scientist and domain expert in cancer genomics.

NIH Research Projects · FY 2025 · 2025-09

Project Summary/Abstract Alzheimer’s disease (AD) is an age-related neurodegenerative disease affecting millions of people worldwide. Its pathological hallmarks include extracellular plaques formed from amyloid beta (Aβ) peptide, dystrophic neurites containing hyperphosphorylated tau protein, oxidative and nitrosative stress, microglial activation, severe synapse loss, and neuronal death; the consequence of these changes is progressive dementia. Attempts to treat AD by targeting Aβ have so far fallen short of addressing the entire pathology, and more diverse strategies are critical to the pursuit of disease-altering therapies. A promising area of study is the cellular changes caused by redox processes that affect protein function; one such change is protein S- nitrosylation, a redox-mediated posttranslational modification whereby nitric oxide (NO)-related species react with a thiol group (or more properly thiolate anion) on a cysteine residue, a reaction discovered in our laboratory. S-Nitrosylated proteins (SNO-proteins) undergo structural and functional changes which can be disease-relevant, although the full import of these changes throughout the proteome is only now beginning to be explored. In a recent unbiased mass spectrometry study, our group found that S-nitrosylated phospholipase D3 (SNO-PLD3) is associated with AD in human brain samples compared to controls. This proposal seeks to elucidate mechanistically the pathological importance of this result to AD. PLD3, a lysosomal 5’ exonuclease found in many cell types, is involved in regulation of toll-like receptor (TLR)9 innate immune signaling in macrophages; it is also known to colocalize with Aβ plaque-associated inclusions within dystrophic neurites in AD mouse models and human AD patients, and single nucleotide polymorphisms in PLD3 confer genetic risk for AD. My preliminary data show that S-nitrosylation of PLD3 increases its enzymatic activity. In light of these results, recently-published crystal structure data, and the fact that S-nitrosylation of a cysteine residue can facilitate disulfide bond formation between vincinal cysteines, I propose to test the hypothesis that S- nitrosylation of PLD3 facilitates a reversible “signaling” disulfide bond that serves to increase PLD3 stability and enzymatic activity, thus downregulating TLR9 signaling—which has recently been linked to memory formation. I will elucidate the effect of S-nitrosylation on PLD3 structure, and then examine the cellular consequences, including TLR9 dysregulation, in human induced pluripotent stem cell (hiPSC)-derived models of microglia and neurons. Accordingly, my Specific Aims are to: 1. Determine the effect of S-nitrosylation on PLD3 structure and stability, and 2. Determine the impact of redox-mediated modulation of PLD3 exonuclease function on TLR9 signaling in microglia and neurons. Understanding the role of SNO-PLD3 in cellular pathologies may provide a new therapeutic target for AD involving redox modulation of protein function.

NIH Research Projects · FY 2025 · 2025-09

PROJECT SUMMARY Carbohydrates present an important class among the natural building blocks of biopolymers as glycan-protein interactions participate in many essential biological processes including immune function, cell-signaling, the recognition of pathogens, among others. Understanding the nature of these interactions has sparked a growing interest in building synthetic glycan assemblies that can probe and mimic these natural recognition events and inform the design of effective antiviral and therapeutic agents. Despite ongoing interest, however, existing glycoassembly platforms such as dendrimers, nanoparticles, and polymers often face fundamental limitations including non-uniform composition and size, lack of atomic precision, and limited architectural tunability. These challenges hinder precise control over their molecular recognition behavior and limit our understanding of the structure-activity paradigms essential to their function. The proposed research seeks to address these limitations by employing a coordination-driven self-assembly approach of synthesizing multivalent glycomolecules with atomic precision. This new supramolecular synthetic strategy advances the state-of-the-art abiotic systems by introducing a modular and programmable method of designing key structural parameters including architectural size, shape, charge, rigidity, and morphology, which are essential factors for probing and understanding structure-activity relationships involved in biomacromolecular recognition. By employing a platform that offers the topological surface density and complexity characteristic of nanoparticles with the synthetic control afforded by small molecule systems, the proposed work aims to provide the ability to optimize glyconanoassemblies for enhanced protein recognition and selectivity. Through this unique synthetic approach, we aim to establish a new paradigm for studying glycan-protein recognition that provides fundamental insights into the design of therapeutic strategies to treat conditions where multivalent interactions play a pivotal role. Because our work is positioned at the interface of molecular synthesis, inorganic chemistry, chemical biology and materials science, we are equipped with a vast array of tools to advance and develop this interdisciplinary program.

NIH Research Projects · FY 2025 · 2025-09

SUMMARY/ABSTRACT Despite the lungs’ crucial role in health and disease, significant gaps remain in our understanding of the mechanisms that govern the development of the normal, healthy lung. Adressing these knowledge gaps will inform therapeutic options for disease and is vital for ensuring long-term respiratory health in both children and adults. As a Pediatric Pulmonologist and physician-scientist, my long-term goal is to identify and validate new therapeutic targets to improve the care of children with respiratory diseases. Toward this effort, our group recently uncovered a novel regulator of lung development, Krüppel-like factor-6 (KLF6). In mice, my preliminary data show that inactivation of Klf6 in the developing lung epithelium leads to a lethal lung growth defect, and inactivation of Klf6 in alveolar epithelial type 1 (AT1) cells just after birth leads to a reduction in lineage traced AT1s. Taken together, this suggests that KLF6 is required in distinct biological processes in prenatal lung growth versus postnatal alveolar formation. By leveraging single-cell profiling, multimodal data analysis and integration, and mouse genetic approaches, my overall objective is to 1) define the roles of KLF6 in branching morphogenesis and postnatal alveolar formation, and 2) define the KLF6-regulated target genes and signaling pathways. My central hypothesis is that KLF6 is a critical promoter of lung growth, airway branching, and alveolar epithelial cell formation. By delineating the role and mechanism of a novel transcriptional regulator in lung development, my findings will contribute to new strategies to address childhood lung diseases such as bronchopulmonary dysplasia – a chronic lung disease in premature infants with lifelong impacts on lung health. The central hypothesis will be tested by pursuing two specific aims: 1) Delineate the mechanism of KLF6 function in lung growth during prenatal branching morphogenesis; and 2) Determine the mechanism of KLF6 function in alveolar epithelium formation during postnatal alveologenesis. Mouse Cre lines will be used to define the cellular mechanisms underlying the phenotypes observed, and sequencing-based omics including state of the art 10X Multiome – simultaneous profiling of gene expression and chromatin accessibility from the same nucleus – will be used to precisely define cellular states and their regulation. The research proposed in this application is innovative, in the applicant’s opinion, because it will determine the role of a poorly studied transcription factor regulator, KLF6, in lung development. The proposed research is significant because it will provide the scientific premise for my future R01 proposals to advance our understanding of both normal lung development and disease pathogenesis.

NIH Research Projects · FY 2025 · 2025-09

PROJECT SUMMARY/ABSTRACT. Nearly 87% of adolescents consume caffeine in some form, and both rates and quantities of caffeine consumption increase as adolescents transition into young adulthood. Although investigations into adult caffeine use are well studied, there is a paucity of research on the effects of early adolescent caffeine initiation and chronic use. Of further concern, these increases in caffeine consumption coincide with increases in other substance use including cannabis use, with 37% of high school seniors reporting past year cannabis use. Preclinical models have shown that even after caffeine cessation, adolescent caffeine exposure can lead to increased susceptibility of future substance use. Additionally, some preclinical models have demonstrated that concurrent caffeine and cannabis use exposure may lead to decreases in cognitive performance mediated through hippocampal dysfunction. Despite this early evidence, there have been limited longitudinal investigations into adolescent caffeine consumption and concurrent cannabis use and no studies examining their interactive effect on cognition in human adolescents. The primary aim of the current K08 proposal is to address this gap in the literature by examining longitudinal trends in caffeine consumption; measure the impact of caffeine exposure on future cannabis use; and investigate how the combined effect of caffeine and alcohol use impacts neurocognitive trajectories through random intercept cross-lagged panel models. By leveraging data from the Adolescent Brain Cognitive Development (ABCD) study, long-term consist trends in caffeine consumption and substance use can be assessed throughout adolescence. Additionally, harmonized studies such as the Protracted Understanding of Fluctuating Substance use and Severity Study (PUFFS) can be employed to gain an understanding of how these trajectories may change as adolescents transition into young adulthood. As both studies incorporate detailed clinical interviews of substance use, including caffeine use, aggregates of total self-reported caffeine use across multiple caffeine modalities are collected, which provides a novel opportunity to calculate estimates of overall caffeine consumption. The proposed project offers Dr. Wallace an opportunity to gain additional training in adolescent caffeine research, which is largely missing from the adolescent addiction field, as well as mentorship in complex longitudinal statistical modeling across multiple datasets. A mentorship team of experts will bridge these unique fields to improve our understanding of the effects of caffeine exposure and concurrent cannabis use on adolescent cognitive development. These experiences would build off of Dr. Wallace’s previous experiences with cross- sectional cannabis use research on the developing brain. At the conclusion of this award, Dr. Wallace will meet his goal of career independence as a clinical research scientist with expertise in adolescent caffeine consumption in the context of addiction and longitudinal analyses, which will be exemplified by submission of an R01.

NSF Awards · FY 2025 · 2025-09

Scientific research often relies on open collaboration across borders, institutions, and disciplines. But in today’s competitive global environment, there is growing concern that valuable discoveries funded by U.S. taxpayers may be subject to malign foreign interference or misappropriation. This project develops new tools and techniques to help universities and research agencies better understand when and how such transfers of knowledge might occur. By analyzing how people, publications, and ideas are connected, the system will flag unusual patterns—such as researchers moving abroad and using U.S. research without attribution or foreign patents that closely resemble federally funded work. The long-term goal is to help institutions protect research integrity while continuing to support open and collaborative science. Technically, the project constructs a knowledge graph that connects data from grants, publications, patents, and institutional affiliations over time. Within this graph, it defines and detects “leakage paths”—chains of connections that suggest research may have moved outside authorized channels. The system uses a combination of human-defined templates and machine learning techniques, such as temporal graph neural networks, to score and explain these patterns. Simulated scenarios of potential misuse are also used to improve the models and discover new risk indicators. The final output, a proof-of-concept system, will be shared as an open-source toolkit, including a searchable API, interactive interface, and reproducible simulation environment. If successful, the project will provide a new kind of research security infrastructure—one that is proactive, explainable, and aligned with evolving national priorities. 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 · 2025-09

PROJECT SUMMARY A major obstacle in studying retinal degenerative disorders lies in accurately modeling their pathophysiology from the cellular to the systems level in a benchtop lab setting. Although animal models provide valuable insight into disease processes in vivo, ethical and technical limitations often prevent the full translation of experimental findings into the clinical context. Recent advances in tissue engineering – particularly in 3D bioprinting and human induced pluripotent stem cell (hiPSC)-derived neural populations – provide new approaches for investigating neuropathology in vitro. Emerging evidence suggests that when compared to 2D substrates, biocompatible 3D hydrogel microenvironments more accurately portray normal physiologic and pathologic neural states. However, patterning 3D tissues and probing their electrical activity are not trivial and pose challenges for elucidating the relationships between cell physiology, emergent electrochemical signaling behavior, and higher- level computation and cognition. While multi-electrode arrays (MEAs), optogenetic stimulation, and voltage- sensitive fluorescent imaging are well-established techniques for interrogating native in vivo neural activity, their application towards in vitro 3D systems has been limited. This R21 project aims to develop a novel, high-throughput optical projection platform to create “visual-circuit-on- a-chip” by integrating 3D bioprinting, optogenetic stimulation, MEA recording, and real-time fluorescence imaging. In Specific Aim 1, we will develop an integrated platform for bioprinting, electrophysiology, and multiwavelength optogenetic stimulation. The bioprinting method allows for projection printing into conventional cell culture plates as well as single-well and multi-well MEA substrates. Using photopolymerizable extracellular matrix mimics, we will encapsulate hiPSC-derived neural progenitor cells and induced neurons to direct cell proliferation, neurite outgrowth, and functional connectivity. In Specific Aim 2, we will implement hiPSC technology to enable spatiotemporal control of induced multicellular differentiation and optogenetic stimulation. We will build simplified neural circuits first, then extend into a more comprehensive visual circuit platform utilizing hiPSCs engineered to produce specific populations of induced retinal neurons. Our combined technical capabilities will allow us to integrate these experimental methods into a novel all-in-one platform to yield high- throughput fabrication and interrogation of systematically patterned and stimulated biological neural networks.

NIH Research Projects · FY 2025 · 2025-09

PROJECT SUMMARY ABSTRACT Head and neck cancer is a major cause of morbidity and mortality worldwide. My clinical research program focuses on novel alternative therapeutic strategies for head and neck cancer patients who are medically unfit for standard treatment, which differentially affects older populations with comorbidities and medically underserved populations. Historically, these patients have been poorly represented in clinical trials. I have dedicated my career to advancing care of head and neck cancer patients through clinical research, and have served as national PI, national co-chair, and co-author for multiple NCTN trials, as well as contact PI for NRG Oncology at UCSD. I have also led multiple funded IITs, previously holding numerous NIH grants including KL2, R21, and R01 grants supporting my clinical trials work. Recently, our field has seen a consistent string of failures of experimental arms in high-profile trials, highlighting the need for continued work to define the standard of care and develop new therapeutic strategies through NCI-sponsored trials. This project will advance science in this arena through my activities as a national leader in NRG Oncology and as Co-Chair of the NCI Head and Neck Steering Committee (HNSC), including the active development of the NRG HN2437 Phase II Randomized Trial concept. In addition, through my roles as NRG Contact PI and MCC Head and Neck Disease Team Co-Leader at my institution, I will continue to support accrual to NCI-sponsored trials, and as a scientific collaborator and co-investigator, will actively support accrual to NCI-sponsored institutional IITs that are advancing novel treatment paradigms. This grant will additionally enable me to fulfill my ambition of proposing a Clinical Trials Planning Meeting addressing older patient populations and engage in mentorship of emerging investigators. Lastly, it will enable me to continue implementing novel risk-assessment methods that I have developed, using competing event models to define subpopulations who selectively benefit from intensive treatment. For over 16 years, I have served as a research leader at UCSD's Moores Cancer Center (MCC), where I have been Head and Neck and Radiation Disease Team Leader and have led its NRG program since 2008 from affiliate to full voting member status. MCC is the only NCI-designated Comprehensive Cancer Center serving San Diego and Imperial Counties in Southern California. Its clinical trials program is the principal locus of clinical cancer research in the region, which serves a large, ethnically diverse population, with a high prevalence of underrepresented minorities and non-English speaking patients. This grant will also enable me to support innovative collaborations at UCSD, resulting in novel therapeutic strategies. Ultimately, this project will promote novel clinical trials that will improve outcomes for head and neck cancer patients with contraindications to standard therapy, defining new standards of care for future generations.

NIH Research Projects · FY 2025 · 2025-09

PROJECT SUMMARY How fast can populations adapt to inhabit a different ecological niche or to keep track with a changing environment? Recent studies in systems as diverse as Galapagos finches, Drosophila melanogaster, and sticklebacks suggest that adaptation can be very fast if adaptive genetic variation is available and the genomic architectures of adaptative traits facilitate a coordinated response to selection – especially if adaptive alleles are grouped together in compact architectures or kept in linkage disequilibrium within chromosomal inversions. But it has been very difficult to link fitness in natural systems, spatial and temporal patterns of allele frequency change, and an understanding of the genomic basis of specific adaptive traits. Aedes aegypti provides a remarkably tractable system in which to answer these questions. In this species, a human-specialist form evolved from a generalist ancestor within the last 5000 years, likely in West Africa. This transition was accompanied by several well-characterized changes in important traits across their lifecycle, from behavior, to life history, to physiology. This species is easy to collect and study in the field, easy to work with in the lab, and has a high quality genome assembly and tractable genetic manipulation with CRISPR-Cas9. In the proposed work, we build on recent work showing that this species shows evidence of several shifts in ecology across sharp spatial clines, and across decades and even seasons in its native range in Africa to characterize the genomic basis of these rapid and repeated shifts in ecology. We will use field study of rapid fluctuations in genome-wide allele frequencies across the starkly different dry and wet seasons of the southern edge of the Sahel in Senegal to characterize the genome-wide distribution of adaptive variation and patterns of selection across the genome. We will couple this with high-resolution mapping of genes involved in key putatively adaptive traits in the lab, and functional characterization of these genes using reciprocal hemizygosity tests in hybrids between human-specialist and generalist lab strains. We will take advantage of this species’ short generation time to carry out experimental evolution studies of the role of genomic architecture in rapid evolution – in particular, we will examine the role of a recently characterized large chromosomal inversion in mediating rapid ecological transitions in space and time. The proposed work will synthesize direct observations of allele frequency change in nature and focused laboratory study to come to a new and deeper understanding of the genomic mechanisms that can enable rapid evolution.

NIH Research Projects · FY 2025 · 2025-09

Summary Arrhythmogenic right ventricular dysplasia/cardiomyopathy (ARVD/C) is an incurable genetic based cardiac disease that causes sudden death in young people, including pediatric populations. ARVD/C is termed a “disease of the desmosome” as majority of mutations are found in desmosomal (junctional anchor) genes. Cardiac inflammation, manifested as myocarditis, is an early component of ARVD/C, especially in pediatric patients and patients with mutations in the desmosomal gene, desmoplakin (DSP). However, no models and limited mechanistic insights exist of a direct causal relationship between inflammation and episodic myocardial injuries that drive DSP cardiomyopathy and what therapeutics would be impactful. We provide evidence for preclinical mouse models of DSP cardiomyopathy harboring inflammation, one of which is provoked by acute inflammatory stress to drive chronic myocarditis in DSP cardiomyopathy, providing platforms to dissect immune cell mediators. We show significant focal cardiac T cell infiltration in mice with DSP cardiomyopathy and that early use of CD4+T cell neutralizing antibodies can attenuate ensuing cardiac enlargement and pathology in these mice suggestive of T cells as mediators of DSP cardiomyopathy. We report the presence of human DSP peptides in a human immunopeptidome database suggesting DSP’s potential direct involvement as an antigens, which may explain T cell responses. We show T cell infiltration in explanted human heart tissue from a pediatric patient harboring two pathogenic DSP mutations, suggesting a T cell response that may be driven by DSP antigenic functions in the human heart. Early T cell involvement and as mediators of ARVD/C helps explain our report of asymptomatic patients with pathogenic DSP heterozygous mutations presenting early with recurrent myocarditis prior to the diagnosis of ARVD/C. Thus, understanding the immune response that underlies DSP cardiomyopathy can identify vulnerabilities in immune cell and antigen recognition that may drive disease and optimize immunotherapies for this subgroup. Loss of the gap junction protein, connexin43 (a primary target of DSP protein loss) is a key molecular alteration in DSP cardiomyopathy and we show that connexin43 upregulation via gene therapy is therapeutic and prevents myocarditis driven DSP cardiomyopathy. We hypothesize that DSP gene mutations/loss impact connexin43 loss, which disrupts cardiomyocyte junctional integrity and primes pathogenic T cells (via DSP antigen exposure) to drive chronic inflammation/myocarditis in ARVD/C. Connexin43 targeted strategies can therapeutically intervene with myocarditis driven DSP cardiomyopathy. We aim to define: (i) the immune cell mediators, (ii) triggers, and (iii) therapeutics that intervene with myocarditis in DSP cardiomyopathy.

NSF Awards · FY 2025 · 2025-09

Mammals evolved from a reptile-like ancestor that used its limbs and tail together for walking and running. In early mammals, however, the limbs moved independently from the tail. This allowed mammal tails to evolve entirely new functions or to disappear in species like humans and other apes. Mammal tails play essential roles in movement, social interaction, energy storage, and protection. These many functions are enabled by variation in the shape, size, and number of individual vertebrae. Yet, little is known about how such variety arose during mammal evolution, how different tails develop from embryo to adult, or how different bone-tendon-muscle connections determine how a tail is used. This interdisciplinary research program will answer these questions and provide training for students and postdoctoral fellows across three laboratories. The research will also inspire an interactive exhibit in collaboration with the University of Michigan Natural History Museum. This exhibit will include 3-D printed mammal tails, representing both real and imaginary forms, strung with cables that will allow visitors to explore how tails function. In doing so, visitors will gain an intuitive understanding of how changes in tail anatomy favor specific uses. This collaborative proposal leverages over ten years of synergy among the research team members, combining insights from phylogenetic comparative models, evolutionary developmental biology, and biomechanics. In Aim 1, a broad survey of tail morphology in extant and extinct mammals will determine how the modularity of tail shape evolved. The evolution of tail morphology across mammals will be modeled to test whether speciation rates and ecological adaptation influenced tail variations. These insights will pinpoint specific evolutionary and ecological factors that shaped tail differences. In Aim 2, studies address a gap in our understanding of the genetic mechanisms that drive this variation. Laboratory mice and bipedal jerboas will be used to elucidate the genetic controls of vertebral elongation, which will shed light on the broader evolutionary influences on tail morphology across mammals. Finally, in Aim 3, robotic models will be used to understand how inter- and intraspecific variation in vertebral proportion affect tail function. This approach seeks to understand the functional implications of varying tail designs, linking physical attributes directly to their ecological, evolutionary, and genetic origins. The work has potential for the development of new biotechnology particularly in the field of robotics. This project was co-funded by the Physiological Mechanisms and Biomechanics Program and the Developmental Systems Cluster in the Division of Integrative Organismal Systems, the Systematics and Biodiversity Science Cluster in the Division of Environmental Biology, and by the Division of Emerging Frontiers, all in the Directorate for Biological Sciences. 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 · 2025-09

Project Summary/Abstract Stillbirth, defined as intrauterine fetal demise (IUFD) at or above 20 weeks gestational age, is a devastating pregnancy outcome, with rates that have remained steady over the last decade and are higher in under-resourced communities. Fetal growth restriction (FGR) is a significant risk factor for stillbirth, and is defined as a fetus that fails to reach its growth potential. However, “true” (pathologic) FGR is difficult to distinguish from a constitutionally-small fetus, and is hard to diagnose, particularly in the antenatal period. A major underlying cause of FGR is placental dysfunction, where the placenta fails to meet the energy demands of a growing fetus. However, placental dysfunction is not a uniform condition, and is difficult to diagnose in an ongoing pregnancy. Post delivery, placental dysfunction can be identified following a complete pathologic evaluation, categorized as either vascular (maternal vascular malperfusion/MVM or fetal vascular malperfusion/FVM), and/or inflammatory (villitis of unknown etiology/VUE or acute chorioamnionitis/ACA) patterns of injury. At the UC San Diego Center for Perinatal Discovery (CPD), our group specializes in placenta-based diseases of pregnancy, including preeclampsia, preterm birth, FGR, and stillbirth. Over the past five years, through study of pregnant patients within our ongoing CPD cohort, all of whom have detailed clinical and pathologic annotation, we have identified molecular pathways underlying multiple placental patterns of injury, which are associated with placental dysfunction and FGR. Most recently, through limited proteomic profiling, we have identified maternal serum biomarkers associated with MVM. We now propose to develop a maternal serum-based test for antepartum identification of placental dysfunction and FGR, and hence those at risk for stillbirth (Project 1). In addition to validation of this test using retrospectively- collected biosamples, we propose a prospective cohort, which can be replicated across all Stillbirth Research Centers, in which we will follow pregnant patients suspected of having FGR in the third trimester. We will collect detailed information on this cohort, including data and biological measurements of psychosocial determinants of health, in addition to maternal biosamples and placental pathology. Using these data, we propose to construct a high-dimensional bio-psycho-social prediction model for FGR and stillbirth (Project 2). As in the past, we will engage the local community, especially those who have experienced stillbirth, throughout development of the prediction model and dissemination plan as we seek to make the greatest impact on stillbirth prevention. Successful completion of this proposal will establish a prediction model, through integration of maternal serum biomarkers and bio-psycho-social determinants, for placental dysfunction and FGR, and enable identification of pregnant patients at high risk of stillbirth.

NIH Research Projects · FY 2025 · 2025-09

SUMMARY/ABSTRACT Aging is a major contributing factor to the development of heart failure (HF). Inflammation is now considered to be an important driver of the adverse cardiac remodeling and chronic low-grade inflammation is a hallmark of aging (inflammaging). NIMA-related kinase-7 (NEK7) is a serine/threonine kinase that was originally discovered to play a critical role in cell-cycle progression. The functional role of NEK7 in the heart has not been determined although NEK7 is abundantly expressed in cardiomyocytes. Our preliminary results demonstrated that NEK7 activity is decreased in ventricular lysates from old mouse hearts and that NEK7 has an ability to suppress inflammatory gene expression. Our data further suggests a possibility that the anti-inflammatory effect of NEK7 is due to enhanced mRNA degradation. RNA-binding proteins (RBPs) regulate RNA metabolism including mRNA stability and play a key role in inflammatory disease. However, how RBPs are regulated in the heart and how such regulation alters the process of inflammaging are elusive. Aim 1 determines whether NEK7 inhibits inflammation and adverse cardiac remodeling induced by aging. Aim 1A examines if NEK7 activity is decreased in purified adult mouse ventricular myocytes isolated from young and old mouse hearts. Aim 1B determines whether NEK7 activity suppresses inflammaging, using AAV9 vectors encoding constitutively active (CA) and kinase-dead (KD) dominant negative NEK7. Inflammation will be assessed by cytokines and chemokines qPCR, protein arrays, immunohistochemistry and flow cytometry. NLRP3 inflammasome priming and activation will also be examined. Aim 1C determines if NEK7 activity provides salutary effects against aging in the heart using AAV9-CA-NEK7 and AAV9-KD-NEK7. Cardiac dimensions, systolic and diastolic function, hypertrophy, fibrosis and cell death will be assessed during the course of aging. Aim 2 seeks to identify the RBPs that are phosphorylated and regulated by NEK7 to suppress inflammatory gene expression in the aging heart. Aim 2A determines if NEK7 phosphorylates and regulates the RBPs that have been established to regulate inflammatory responses. Phosphorylation of the RBPs by NEK7, effects of NEK7 on their protein stability, subcellular localization and affinity for RNA, and their contributions to the NEK7-mediated suppression of inflammatory gene expression will be examined. In Aim 2B, to systematically identify the RBPs that are phosphorylated by NEK7 in the aging heart, we will employ phosphoproteomic analysis in control, CA-NEK7 and KD-NEK7 mice at the age of 24 months. Phosphorylation of the RBPs by NEK7 will be confirmed by in vitro experiments and their contributions to the NEK7-mediated anti-inflammatory responses will be examined in cardiomyocytes. Successful completion of this R21 exploratory/developmental grant will provide evidence that NEK7 provides salutary effects against aging in the heart and identify RBPs that are phosphorylated by NEK7 to suppress inflammatory responses. Our long-term goal is to understand how the NEK7/RBPs signaling network negatively regulates inflammatory responses and adverse remodeling in the aging heart.

NIH Research Projects · FY 2025 · 2025-09

Project summary. Inflammation underlies majority of human diseases including diabetes, atherosclerosis, and cancer. These diseases are responsible for majority of deaths and represent substantial global health burden. Macrophages and T-cells, subsets of immune cells, have emerged as key mediators of inflammation. The role of biochemical cues in shaping the transcriptional response of these cells have been investigated. However, accumulating evidence has shown that physical factors also tune their phenotype and effector functions. Recent two-dimensional studies have shown that mechanical confinement directs the nuclear translocation of transcription factors in macrophages. Another study found enhanced T-cell killing of cancer cells stiffened through cholesterol depletion. These studies have contributed to the field of mechano-immunology that seeks to understand how physical factors direct immune cell fate. Recent mechano-immunology findings have laid the groundwork for my proposal aimed at determining how biophysical cues shape macrophage and T-cell cell behavior. We have developed a three-dimensional culture that allows us to interrogate how biophysical cues regulate immune cell trafficking and macrophage-T- cell interaction in the tumor microenvironment. We have already identified that naïve macrophages are more efficient at trafficking to tumors than polarized macrophages. Furthermore, macrophages adopt different shapes depending on their activation state and their local microenvironment. Our preliminary results show that T-cells have longer-lived interactions with rounded macrophages, compared to elongated ones. This implicates macrophage shape, a biophysical property, in regulating its interaction with T-cells. We will extend these findings by elucidating the role of matrix viscoelasticity on immune cells behavior and performing a rigorous immunophenotyping of these cells. In addition, the proposal will implement machine learning algorithms to high resolution spatiotemporal information obtained from live confocal imaging. This will unlock the potential to identify heterogenous phenotypic states and quantify their evolution over time. Further, the proposal will integrate confocal live imaging with the single-cell RNA sequencing data. Such detailed, single cell analysis will identify genetic programs that are responsible for heterogenous morphometric states. The proposed research will be significant because it is expected to yield mechanistic insights that have broad translational impact for a myriad of diseases where inflammation is the underlying cause. These include Alzheimer’s, atherosclerosis, arthritis, diabetes, and cancer, which represent a growing global burden. The pathology of these diseases is orchestrated by macrophages and T-cells. Insight into the mechanobiology of macrophages, T-cells, and associated intracellular, transcriptional, and epigenetic modifications will deliver novel therapeutic options. Analysis of morphological heterogeneity using machine learning algorithms will provide a useful clinical and research tool to monitor disease progression.

NIH Research Projects · FY 2025 · 2025-09

Diabetic foot ulcers (DFUs) are a common manifestation of uncontrolled diabetes mellitus, and DFU treatment accounts for approximately one-third of the total cost of diabetic care. Sadly, tools that determine response to therapy or predict relapse are largely limited to visual inspection despite the known utility of tissue perfusion and tissue hypoxia in monitoring therapy/relapse. The current generation of tools to quantify perfusion and hypoxia are surface-weighted and ensemble approaches with no ability to understand the DFU in three dimensions. Thus, imaging tools that predict and monitor DFU response to therapy and identify at-risk tissue before DFUs relapse would have a major impact on DFUs. To address this major limitation, we recently used photoacoustic imaging to map and measure tissue perfusion and hypoxia in chronic wounds. We then identified imaging biomarkers that suggest a response to therapy in a pilot human cohort leading to a receiver-operator curve (ROC) area under the curve (AUC) of 0.92. Our proposed work will now validate these imaging biomarkers in longitudinal cohorts via three aims: Aim 1 will use the biomarkers to monitor DFU standard care that fails in up to 70% of patients after 24 weeks. Our goal is to quickly (<30 days) escalate those needing advanced treatment (e.g., skin grafts). Aim 2 will use photoacoustic imaging to guide DFU hyperbaric oxygen therapy (HBOT). The role of HBOT in DFU treatment remains controversial—perhaps because there is no way to quickly stratify responders from non- responders. We hypothesize that DFUs with a greater increase in perfusion and oxygenation due to HBOT as detected by photoacoustic imaging will heal more quickly. Aim 3 will evaluate DFU relapse. The DFU recurrence rate is 66% and even higher in dialysis patients. We will perform longitudinal imaging of dialysis patients with a DFU in remission and hypothesize that subjects with lower foot perfusion and/or oxygenation will have the highest risk of relapse. The significance of this work is underscored by the major and negative impacts that DFUs have on quality of life, and the innovation lies in patient cohorts not yet studied with photoacoustic imaging. This work is feasible because of our large body of preliminary data (five published manuscripts with 116 patients imaged) as well as the inclusion of experts in wound care, imaging, dialysis, and biostatistics. The imaging will offer direct assessment of microvascular disease in 3D and change clinical practice by enabling clinicians to: 1) Escalate those needing advanced care at baseline visit leading to earlier, quicker treatments (Aim 1); 2) Discontinue HBOT non-responders within the first ~ 5 treatments while continuing to treat known responders, which will stop futile treatments and lower costs (Aim 2); and 3) Start therapy early for DFU relapse, which will target limb salvage earlier, decrease morbidity, and lower costs (Aim 3). Importantly, the work will likely have value beyond DFUs (e.g., decubitus ulcers, burns).

NSF Awards · FY 2025 · 2025-09

The distribution and circulation of fluids in the Earth’s interior are connected to volcanic activity, earthquakes, and plate tectonics in general. In this project, the chemical elements (termed “volatiles”) hydrogen (H) and carbon (C) at depths of several hundreds of kilometers below the Earth’s surface (i.e., in the upper mantle) are of particular interest. These light elements provide key information to understand the temperature and chemical composition of the Earth’s mantle, as well as the processes that have shaped the interior of our planet. This team will focus on H,C-bearing mantle rocks using a combination of techniques that are carefully selected to reveal the rock chemistry and the electrical response at high pressures and temperatures. This project is at the frontier of high-pressure research because of the high degree of synergy between two primary techniques (Raman spectroscopy and impedance spectroscopy), and the plan to make these measurements simultaneously at high pressures and temperatures. Electrical measurements (in situ) and vibrational spectroscopy (in & ex situ) are a powerful combination that is anticipated to significantly advance our understanding of transport, dehydration, and decarbonation in volatile-bearing minerals. This work will help develop an advanced model of the transport of volatiles in subduction zones, and presents an opportunity to foster multi-disciplinary collaborations between mineral physics, chemistry, and geophysics. These PIs will train and mentor a postdoctoral researcher, graduate student and several undergraduate students. This project features simultaneous, in situ electrical and Raman spectroscopic measurements on minerals that transport volatiles in subduction zones. Specifically, seven hydrous silicates and carbonates will be probed at pressures up to 8 GPa and temperatures up to 1300 C in presses at Carnegie Institution for Science-EPL. Ex situ vibrational spectroscopy measurements performed at UC San Diego, and electron microprobe analyses conducted at EPL will complement the dataset to probe the sample composition and texture, with particular emphasis on the chemical speciation of volatiles (H, C) and other species (particularly Fe2+ and Fe3+) that are most relevant to charge transport. Advances in the quantification of H and C using Raman spectroscopy will contribute to calibration standards that will be useful to the community. Simultaneous in situ impedance and vibrational spectroscopy are a powerful combination that have the potential to significantly advance our understanding of transport, dehydration, and decarbonation in volatile-bearing minerals. The laboratory-derived measurements will form the foundation for the development of an advanced model for volatile transport in subduction zones. The lab-based model will in turn allow predictions of the electrical response of volatile-carrying materials at depth that are testable using field electromagnetic surveys. 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 · 2025-09

Advances in sensing, artificial intelligence, computation and communication are enabling the deployment of large networks of autonomous systems, such as drones, ground robots, and other mobile agents, across diverse applications including search and rescue, environmental monitoring, precision agriculture, and transportation. The research funded by this grant aims to create new mathematical tools and algorithms that allow large groups of autonomous agents to operate safely, efficiently, and collaboratively, even under physical constraints, communication limitations, and local decision-making. The central idea of this research is to model large groups of autonomous agents not individually, but as evolving spatial distributions like densities or concentrations over a region. This macroscopic perspective looks to enable the design of scalable, tractable algorithms that guide the collective behavior of many agents, while still accounting for each agent’s physical limitations, local interactions, asynchronous timing, and safety constraints. By linking these global objectives with local decision-making through new optimization techniques, the project seeks to create algorithms that are both theoretically grounded and practically applicable. The research will be complemented by educational and outreach activities that include the development of new curriculum for undergraduate and graduate education, research experiences for students through high-fidelity simulations, and opportunities to engage in algorithm development and visualization at the multiagent robotics (MURO) Lab at the University of California, San Diego. Findings will be disseminated through academic publications, conference sessions, and public engagement efforts. This project aims to develop new tractable, robust, safe and distributed transport algorithms for large-scale multi-agent (autonomous) systems modeled by probability distributions. The theoretical foundation relies on the design of new macroscopic proximal gradient algorithms that account for individual agent limitations as well as approximation errors arising from the use of a finite number of agents. The research is organized around three main thrusts: (i) the development of robust transport algorithms for large-scale homogeneous populations, with robustness characterized via Input-to-State (ISS) stability properties; (ii) the design of safe-proximal gradient algorithms for homogeneous agents incorporating feedback control for macroscopic proximal gradient optimizations; and (iii) the formulation of distributed safe proximal gradients for heterogeneous populations, coordinated by a higher-level network of operators. 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 · 2025-09

Abstract Identification and validation of biomarkers of aging, which predict the lifespan and risk of disease better than chronological age and can help identify factors that accelerate aging and interventions that promote resilience, is the major goal of the Predictive Biomarkers Initiative of the NIA. DNA methylation (DNAm) clocks, which provide assessments of chronological and biological age, have attracted a lot of attention and have been incorporated into multiple commercial products. Nevertheless, the DNAm clocks are usually based on averages over large pools of cells of different types and extract age-related trends from noisy data. Recently, the Co-PI lab pioneered the analysis of cellular states, identities, and perturbations based on high-resolution confocal imaging of epigenetic marks in nuclei of individual immuno-labeled cells and applied this approach to aging. The imaging-based chromatin and epigenetic age (ImAge) analysis captures the principal changes in the spatial organization of chromatin and epigenetic marks that correlate with biological age. The cell-to-cell variability of the ImAge readouts increases with age, making it a separate metric of the process of aging and highlighting the value of obtaining the quantitative epigenetic signatures from single cells. ImAge measurements require only small amounts of Peripheral Blood Mononuclear Cells (PBMCs) that can potentially be obtained from fingerstick blood samples. To effectively implement ImAge for assessing the human biological age, PBMCs obtained from a fingerstick must be immuno-labeled and presented for high- resolution imaging with minimal cell loss. To meet this challenge, we propose a platform for single-cell capture, immuno-labeling, and high-resolution imaging of PBMCs in arrays of bottomless microscopic conical wells with picoliter volumes. When captured in a conical picowell, a round cell rests on the tilted sidewalls and remains motionless under moderate mechanical perturbations, including medium exchanges during the immuno- labeling. The major advantage of the proposed bottomless conical picowells is that the cell loading is by vertical flow through the picowells, thus minimizing the cell loss, increasing the proportion of picowells with single cells, and filtering out cell debris. We will develop and validate an ImAge platform based on arrays of bottomless picowells and fluidic perfusion devices. We will apply it to obtain the first ImAge dataset of human PBMCs from healthy donors of different ages. When fully developed and tested, the proposed bottomless picowell-based platform will enable cost-effective longitudinal tracking of biological age of individual patients to facilitate personalized medicine and to achieve a better understanding of how aging is affected by different life events, environmental changes, and medical interventions.