University Of California Los Angeles

NSF Awards · FY 2025 · 2025-05

All languages have clausal embedding, which is the ability to embed one sentence inside of another (e.g. 'Katie thinks that Kayla said that Alex is smart'). Languages differ with respect to the precise mechanics involved in accomplishing clausal embedding and the inventories of embedding strategies. Furthermore, recent research has shown that the particular linguistic elements involved (e.g. the word 'that') have important effects on the functioning and interpretations of clausal embeddings. This project approaches this crucial aspect of natural language through careful investigation of the variation observed across languages and in-depth examination of clausal embedding within several related languages. The project implements these investigative aims through naturalistic data collection. This leads to the second goal of this project, which is to train students to work with language speakers to elicit language data, and work on data processing, thereby increasing the number of specialists focusing on field linguistics. This project investigates clausal embedding through traditional linguistic fieldwork through the documentation and description of the clausal embedding strategies present in a variety of languages. The team accomplishes this by collecting texts and stories and eliciting linguistic data from native speakers. These data help reveal the grammatical properties associated with clausal embedding, from which a deeper understanding of human language is gleaned. An archived collection of data from the project serves as a large corpus of natural speech, which helps investigators pinpoint the relevant grammatical properties of human languages and serves as a permanent record of the languages and history. The results from this project have broad applicability across fields and serve as the basis for future crosslinguistic work on human language in general. 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 · 2025-05

Project Summary/Abstract A unique state-of-the-art hybrid high-resolution tandem mass spectrometer equipped with electrospray ionization (ESI) and a variety of activation/dissociation methods for structural characterization of a broad range of large biological and synthetic molecules is requested. This instrument will be a vital component to advance the research aims of over 11 NIH-supported projects. The studies involve a variety of biomolecule structure related research, including the characterization of protein-protein and protein-ligand (metals, lipids, inhibitors, co-factors) interactions, membrane proteins and their interactions with lipids, protein aggregates, therapeutics, RNA- inhibitor complexes, and protein-bioconjugated molecules. The research projects impact a range of human health issues, including neurodegenerative diseases, such as Alzheimer’s and Parkinson’s diseases, bacterial infectious diseases, hypertrophic cardiomyopathy, cancer, oral cavity infections, and viral infections. The high- resolution mass spectrometer will be capable of low-parts-per-million mass measurement accuracy for intact biomolecules and product ions derived from tandem mass spectrometry (MS/MS) experiments. It will have capabilities for multistage MS-n experiments (where n is greater than 2), thus permitting advanced top-down MS analysis using collision-, electron-, and photon-based fragmentation methods for efficient ion activation and dissociation. Access to multiple fragmentation methods on the same instrument greatly improves the ability to dissociate large intact biomolecules to derive complete sequence/structure information, as well as the direct detection of posttranslational modifications and proteoforms. The proposed high-resolution tandem mass spectrometry system will be supported and administered by the UCLA Molecular Instrumentation Center (MIC), a campus-wide, integrated facility formed to enhance the accessibility of existing shared, sophisticated instrumentation facilities to the broader research community at the institution.

NIH Research Projects · FY 2026 · 2025-05

Project Summary Natural killer (NK) cells have the innate capacity to identify and eliminate virally infected cells. Human cytomegalovirus (HCMV) infection increases the risk of severe health issues in newborns and patients with immune deficiencies (such as AIDS patients or solid organ transplant recipients). Previous work in mice and humans has demonstrated that NK cells are essential for host protection against herpesviruses such as HCMV, and that mouse cytomegalovirus (MCMV) infection can be utilized to model and study HCMV infection in vivo. While the transcriptional and epigenetic regulators associated with mouse NK cell activation and persistence during viral infection have been well studied, they are still not well understood in human NK cells. Our long-term goals seek to identify the relevant transcriptional regulators of human NK cell function following viral infection. To address this, we performed a targeted CRISPR screen in primary PBMC-derived human NK cells concentrated on transcription factors differentially expressed during human NK cell development. Of these candidates, MEF2C was the sole transcription factor broadly required for human NK cell cytotoxicity, proliferation, and antiviral cytokine production ex vivo. Analysis of PBMCs from patients with MEF2C haploinsufficiency syndrome (MCHS) further demonstrated defects in NK cell proliferation and effector function ex vivo, and Mef2c haploinsufficient mice displayed increased mortality during viral infection associated with defective NK cell function. MEF2C was required to promote SREBP-dependent lipid import in response to cytokine activation, and oleate supplementation restored intracellular lipid levels and the cytotoxicity of MCHS patient NK cells. CRISPR-mediated knockout of individual SREBP isoforms in human NK cells revealed that SREBP2, but not SREBP1, is required for NK cell effector functions. These results suggest that MCHS patients with increased susceptibility to viral infections may be caused by an NK cell-intrinsic functional defect, and oleate supplementation may represent an effective strategy to enhance immunity in these patients. While these preliminary results implicate MEF2C as a critical regulator of human NK cells through regulation of the SREBP2 pathway, the precise mechanisms by which MEF2C is induced, and controls human NK cell functionality are unknown. In Aim 1, we will determine the transcriptional and post-translational mechanisms of MEF2C regulation in human NK cells. In Aim 2, we will determine the mechanism of action and in vivo therapeutic efficacy of oleate supplementation on NK cell cytotoxicity. In Aim 3, we will investigate how the SREBP2 pathway promotes antiviral cytokine production in human NK cells. In summary, the studies included in this proposal will contribute to the fundamental understanding of how human NK cell effector functions are regulated by cell-intrinsic metabolism, while also contributing to novel strategies to enhance the clinical use of NK cells during viral infection and in immunocompromised patients.

NSF Awards · FY 2025 · 2025-05

Understanding how to predict changes in the Arctic environment, especially sea ice variations, is crucial because these changes have big impacts on economies and societies both locally and globally. This project focuses on developing new ways to forecast Arctic sea ice during summer when sea ice is melting and reaches its minimum, looking at time periods from a few weeks to an entire season. It also aims to determine how far into the future these predictions can be made. The amount of summer sea ice in the Arctic is influenced by many factors, ranging from daily weather changes to long-term shifts in global wind patterns, affected by slowly changing ocean temperatures around the world. However, the understanding of how these factors interact is still limited. This limitation comes from the short duration of reliable satellite data monitoring and the complexity of the connections between these elements, which are challenging for traditional climate models or simple statistics to interpret. This project will use advanced and sophisticated machine learning methods to potentially improve predictions of Arctic summer sea ice. Additionally, the project will provide college students with opportunities to learn across different science topics, leveraging the resources and expertise of the participating institutions. Preconditioning of sea ice before the summer months has long been recognized as a vital predictor of September's Arctic sea ice extent. The dynamic interactions between ice, ocean, and atmosphere are also major contributors to the changes observed in summer sea ice. The researchers will examine the impacts from external climate components and how they interact with the persistent local conditions before the summer season, which has not been fully considered in previous studies. This project will develop models of regional Arctic sea ice coverage based on a diverse array of observational data at a global scale, integrated by an advanced machine learning method. This approach aims to capture the complex, non-linear variations in both local and remote influences across timescales in a global context. The investigators will conduct a series of meticulously designed reforecast experiments to isolate and quantify the influence of various physical drivers on summertime Arctic ice within the predictive framework. 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 · 2025-05

Nontechnical Abstract Semiconductors are used in many types of devices, including computer chips, displays, solar cells, and thermoelectric devices that directly convert heat to electricity. Most semiconductors are made of hard materials, such as silicon, that are expensive to process and manufacture. This project explores the properties of plastic semiconductors that are lightweight, flexible and inexpensive to process into devices. The main challenge facing the development of plastic semiconductors is that it is not as easy to control their electrical properties by doping (the addition or removal of electrons to the semiconductor) as with inorganic semiconductors. This is because the structure of the plastic materials changes upon doping. This project aims to understand how those structure changes control electrical conductivity, and to use that understanding to controllably produce plastic semiconductors with improved conductivity. The efforts will include using new processing methods to allow dopant molecules to be precisely added to the plastic semiconductors at desired molecular locations, and using the structure of the polymer to drive the doping process. The project is a collaboration between researchers who have complimentary expertise in understanding the structure and physical properties of plastic semiconductors and the electronic and device properties of the materials. In addition to scientific advances, this multidisciplinary project trains undergraduate and graduate students in areas of national need and helps bring experiments on related topics (harvesting energy from sunlight and nanoscale materials) to Los Angeles area high schools. Technical Abstract Conjugated polymers have numerous potential uses because they combine the mechanical properties of plastics with the electrical properties of semiconductors. When doped by strong oxidizing agents, their conductivity can be changed by orders of magnitude, but interactions with the dopant counterion and dopant-induced changes in morphology can limit the final carrier mobility. This project aims to understand how the choice of dopant counterion size and shape, along with changes to the degree of polymer crystallinity and crystal structure in the doped state, all work together to determine the electrical properties of doped conjugated polymer films. The project will accomplish this using both chemical and electrochemical doping with a variety of counterions and dopants. Structural aspects of the doped films will be determined using synchrotron-based grazing-incidence wide-angle X-ray diffraction experiments. Electrical properties will be determined via temperature-dependent four-point probe electrical conductivity, Hall effect, and ultrafast transient absorption spectroscopy experiments. The project will also take advantage of rub-aligned films in which the polymer chains all point in the same direction, creating anisotropic conductivity. The first specific question to be addressed by the project is the connection between counterion size and shape, and electrical properties. This will be accomplished by doping the same series of polymers using a series of counterions whose sizes vary by nearly an order of magnitude, directly elucidating correlations between the ion size, local structural change, and carrier mobility. Another specific question to be answered is how the energetics of crystallization (either the crystal-to-crystal phase transformations or the gain or loss of crystallinity upon doping) alter the propensity of conjugated polymers to be doped. This will be accomplished by using blends of polymers that show different propensity for dopant-induced ordering or disordering. A third main question that will be targeted by the project is the role of the local dielectric environment in doping. This will be accomplished by adding electrolytes to the solutions used for doping, with the aim of altering the propensity for doping. 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 · 2025-05

This I-Corps project is based on the development of a system that uses advanced artificial intelligence (AI) to improve quality control in medical device manufacturing. Traditional inspection methods frequently fail to identify small or subtle defects in medical devices, resulting in increased costs from product returns, repairs, and operational inefficiencies. This technology uses a more accurate and efficient defect detection system that is designed to minimize waste, lower rework costs, and optimize production processes. Ultimately, the goal is to improve reliability of medical devices, which may directly enhance patient safety, reduce the risk of recalls, and support better healthcare outcomes. In addition, this technology may decrease production costs, increase competitiveness, and help to ensure compliance with industry standards. This I-Corps project utilizes experimental learning coupled with a first-hand investigation of the industry ecosystem to assess the translation potential of a technology to identify, localize, and categorize visual anomalies in the medical manufacturing process. This technology is based on deep-learning and machine vision techniques using a semi-supervised, multi-scale, hierarchical convolutional neural network paired with traditional computer vision engineering to produce a low-latency, highly accurate machine vision system capable of anomaly detection. The system relies on an orchestrated set of vision and image morphology passes to construct a consistent, highly accurate classification and identification mask. The primary goal is to make a substantive improvement to visual anomaly detection for highly consistent objects without requiring an overly large dataset. Adoption of this technology may allow for improved defect detection in the manufacture of critical medical devices in a more streamlined fashion than is possible with human operators alone. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NIH Research Projects · FY 2026 · 2025-05

Project Summary/Abstract Many patients with retinal degeneration lose vision slowly and retain some visual perception well into middle age. Photoreceptors in degenerating retina must therefore be able to continue to function for a prolonged period, and the rest of the retina must be able to adapt to the loss of some cells to preserve visual processing. Recent research has shown that cones in degenerating retina even without outer segments still respond to light and form new synapses, showing that degenerating cones can continue to produce signals much as in healthy animals. For rods, we have little information about how physiology and connectivity are altered as degeneration proceeds. This knowledge is crucial since most forms of genetically inherited disease are caused by mutations in rod proteins and proceed first with rod degeneration; and since some proposed therapies envisage introduction of new rods into the retina. We propose to address this gap in our knowledge by using single-cell recording from photoreceptors and bipolar cells, first to describe changes in rod function as disease progresses, and then to understand how the retina maintains visual processing during cell loss. The first Aim of our proposal is to document changes in rod membrane potential, input resistance, voltage and current light responses, and amplitude and voltage dependence of Ca2+ currents in mouse models of autosomal dominant retinitis pigmentosa, where rod degeneration occurs rapidly or slowly over a prolonged period. We propose also to make contemporaneous recordings from rod bipolar cells to monitor light sensitivity, maximum response amplitude, and response nonlinearity, with electrodes filled with fluorescent dye to document cell morphology. We hope to discover whether rods can maintain responsiveness as cells are dying, and to understand how rod connections to bipolar cells are preserved. The second Aim of our proposal seeks to investigate plasticity in the propagation of photoreceptor responses in degenerating retina and to establish its mechanism. We have long known that synapses within the retina can break and reform in degenerative disease, but this remodeling has been thought to be deleterious and to limit the ability of degenerating retina to respond to photoreceptor replacement or other forms of therapy. More recent experiments have indicated that remodeling can be adaptive: new synapses formed during degeneration can mediate visual detection and produce nearly normal retinal output provided degeneration has not proceeded too far. We will use physiological recordings to investigate previous anatomical evidence that rod bipolar cells can synapse with cones after rods have degenerated, or cone bipolar cells with rods in cone disease. We will explore the function and pharmacology of these connections and investigate the influence of light responsiveness, glutamate release, and synaptic adhesion proteins on synapse formation. Our aim is to provide new information about the mechanisms the degenerating retina uses to accommodate photoreceptor loss with the ultimate goal to help design new therapies for vision restoration.

NSF Awards · FY 2025 · 2025-05

This project will conduct basic scientific research toward a new wearable technology that can capture images through human skin using advanced optical layers. Current imaging devices used in research to see through the skin are relatively large, expensive, and not practical for everyday use. This new technology will be lightweight, cost-effective, and wearable. Such compact and power-efficient wearable computational imagers and sensors will be transformative for various applications, including counting of blood cells, implantable optical sensing, and the detection of infections and bacteria through the skin. The research team will also engage in outreach, offering research opportunities for high school and college students and spreading awareness about the potential impact of this innovation through media and public platforms. This project will demonstrate proof of concept of a novel wearable technology platform to image and sense through the skin using diffractive optical networks formed by successive transmissive layers spatially engineered at the sub-wavelength scale. Diffractive optical networks consist of multiple spatially engineered layers designed using deep learning to optimize light propagation for inference. These passive diffractive processors do not need electrical power to run, and they complete their image reconstruction or sensing task at the speed of light propagation through structured diffractive layers, filtering out the optical distortions created by random tissue scattering and absorption while passing the rest of the desired information beneath the tissue onto an imager chip. The system will be designed to operate in the near-infrared (NIR) spectrum, ideal for tissue imaging, and fabricated using high-precision nanofabrication techniques like two-photon polymerization. Testing will involve skin-phantom models integrated with microfluidics to simulate biological conditions, including blood flow. This proposal aims for transformative advancements in wearable tissue imaging technology to democratize wearable diagnostics devices, sensors and in vivo imaging cytometers that operate through the skin. The results of the project will lead to subsequent in vivo animal testing and performance quantification through superficial blood vessels for target cell counting/detection and to miniaturization of the developed technology into a wearable form factor. 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 · 2025-05

This I-Corps project is based on the development of software technology to help physicians avoid unnecessary escalation of patients to higher levels of care. Currently, hospital beds are often occupied by patients who could be cared for at a lower-level facility, causing these hospitals to turn away patients who truly need beds. Other patients have extended stays, sometimes multiple days, in an area of the hospital that is not ideal for them, such as in the emergency department. This incompatibility between needs and available space is causing significant revenue loss and harming patients. This solution is designed to provide decision support on where and when each potential patient could receive care and to make limited hospital capacity available for patients who need it most. In addition, the technology identifies space in highly specialized hospitals for patients who require specialized care. This technology may also enable more efficient use of limited resources in hospitals and healthcare systems encompassing multiple hospitals, improving patient outcomes. This I-Corps project utilizes experiential learning coupled with a first-hand investigation of the industry ecosystem to assess the translation potential of a software technology that uses artificial intelligence (AI) to enable decision support and learning for placement of patients in hospitals. Current clinical decision support and prediction technology focuses on acuity or first-come, first-served bed placement, and lacks a learning system and outcomes considerations. This technology uses generative AI and natural language methods to quantify systems where the parameters are multidimensional and continuously changing, such as network flow models. The software uses surfacing and quantifying variation in agent decisions allocating constrained resources for inflow demand. The technology continually updates a surfacing algorithm using feedback from top performing agents. In addition, decision support is designed to customize to a specific healthcare system for admissions and other key flow decision points. Initial technical results from small scale testing of a partly manual model have demonstrated a reduction in the number of unnecessary patient escalations. The goal is to enable effective use of bed capacity, providing value by reducing time and resources, and improving patient outcomes. 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 · 2025-05

This project will investigate the decay mechanisms of the internal tide across the equatorial Pacific and quantify how much of the vertical mixing and advection associated with the internal tide impact the regional heat budget. The investigators will use high-resolution numerical simulations of the ocean to examine the internal tides in the equatorial Pacific Ocean. The project is motivated by observations that internal tide energy is reduced in the equatorial zone. They aim to determine if this is because of dynamics of the tides themselves as a function of latitude, or whether ocean dynamics specific to the equatorial zone are responsible for interacting with the tides. This project will examine the relative importance of internal tide steepening and wave-mean flow interactions for internal tide decay. The investigators will use a set of realistically-forced, nested, high-resolution Regional Ocean Model Simulations (ROMS) of 6 km, 2 km, and 500 m during both an El Nino and a La Nina year, each with and without tidal forcing. Coarse-graining will be used to quantify energy losses out of the internal tide to the subtidal and supertidal bands. This technique will also be applied in combination with temporal and spatial filters to identify processes such as scattering and energy transfers. The same simulations will also be used to quantify how much internal tide-driven mixing and advection contribute to the regional heat budget. The proposed work will leverage both historic and current observational data in the region. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NIH Research Projects · FY 2026 · 2025-05

PROJECT SUMMARY/ABSTRACT Heart failure with preserved ejection fraction (HFpEF) affects ~3 million Americans and is driven by obesity and hypertension. HFpEF is characterized by diastolic dysfunction of the heart, lung edema, impaired skeletal muscle work, elevated circulating liver enzymes, and fluid retention by the kidneys. As a systemic disease, new treatments for HFpEF are likely to arise from investigations across multiple organs. Indeed, emergent HFpEF therapies in humans, including SGLT2 inhibition and GLP1 agonism, both independently have effects on multiple organ systems including decreasing appetite, glucose levels, and body weight, in addition to improving cardiac HFpEF phenotypes like ventricular stiffening and diastolic function. In unpublished data for this proposal, we have shown these therapies to be effective in the ZSF1 rat, providing strong premise to use this model system to develop a greater basic and translational understanding of HFpEF. While previous work has implicated chromatin alterations in other forms of heart disease, epigenomic and transcriptomic reprogramming in HFpEF is not understood. We hypothesize that chromatin remodeling and transcriptome regulatory pathways are mobilized across different organs in response to metabolic and hemodynamic stress, setting into motion the pathologic phenotypes of HFpEF. Our goal is to reveal the molecular insights into the actions of widely used drugs such as empagliflozin (SGLT2 inhibitor) and semaglutide (GLP1 agonist) across multiple organs and to identify novel therapeutic targets in HFpEF. We will measure transcription, chromatin accessibility and histone modifications in heart, kidney and liver, to map the regulatory landscape during the development of HFpEF in a well-established rat model. These studies will provide the first detailed, multi-organ epigenomic atlases of HFpEF, while simultaneously biobanking adipose, blood, aorta and skeletal muscle for future analyses. This proposal will also enable identification of transcription factors and chromatin remodelers operative in heart, liver or kidney, to determine the temporal and causal relationships of multi-organ dysfunction in HFpEF. We will leverage PharmOmics to interrogate these networks for the purposes of re-positioning existing drugs and prioritizing molecular targets. Finally, we will test a newly identified molecular target, histone H1.0, which we have recently shown is necessary for fibroblast activation and fibrosis in vivo. We will modulate histone H1.0 levels in the ZSF1 rat model using AAV9, with readouts including cardiac, lung, liver, kidney physiology and exercise capacity. We hypothesize that greater levels of histone H1.0 promote fibrosis and tissue stiffening—exacerbating the phenotypes of HFpEF—and that targeted depletion of histone H1.0 can counteract these effects. This proposal will provide the first heart, liver and kidney analyses of the epigenomic and transcriptomic underpinning of HFpEF pathogenesis, examining the molecular basis for the beneficially effects of emergent HFpEF therapies across organ systems.

NIH Research Projects · FY 2025 · 2025-05

Abstract: Overall Component Leptospirosis is a widespread and frequently fatal human health problem that disproportionately impacts low resource settings. Research on host-pathogen dynamics in leptospirosis are significant because little is known about leptospiral virulence factors or host response to leptospirosis. The proposed studies will involve highly synergistic collaborations between program project investigators who are leaders in studies of leptospiral virulence genes (Haake and Picardeau), endothelial interactions (Coburn), inflammasome pathways (Sutterwala), and field studies of acute febrile illness (Reller and Woods). With the description of many new leptospiral genomes, a striking pattern of massive species diversity has emerged leading to central hypothesis #1, which is that a core set of leptospiral virulence factors have evolved with roles in survival in mammalian host phagocytes, translocation, and dissemination, which are upregulated in response to the host microenvironment. Central hypothesis #1 will be tested by correlating genome-scale leptospiral evolutionary changes with virulence phenotypes, examining the roles of transcriptional regulators and non-coding small RNAs in adaptation to and survival within host phagocytes, and translocation across endothelial barriers. The correlation of inflammatory markers such as IL-1β levels with disease severity leads to central hypothesis #2, which is that human inflammatory response pathways drive disease outcomes. Central hypothesis #2 will be tested in vitro (interactions with macrophages and endothelial cells), in animal models (infections in hamsters and mice), and in human field studies in Tanzania, Nicaragua, and Sri Lanka. Specifically, we will follow up on our innovative discovery of a striking dichotomy between the high level of inflammasome activation in human macrophages and the low level in macrophages from mice, which are reservoir hosts and do not exhibit disease. We will also follow up on our innovative discovery of dramatic disruption of endothelial VE-cadherins by pathogenic leptospires in terms of the role of intercellular invasion in dissemination. Animal model studies will provide longitudinal host response data in support of human studies that will have a positive impact through development and validation of rapid biomarker diagnostic and triage tools to identify serious infections at an early stage when antibiotics and other interventions can prevent and/or treat critical illness including fatal hepatorenal failure.

NIH Research Projects · FY 2025 · 2025-05

Perfluorination imparts unique, abiotic properties to molecules and materials. The unifying goal of our work is exploiting these properties to enhance therapeutics, diagnostics, and create new chemical tools. In one approach, we capitalize on the inverse quadrapole moment imparted by perfluorination of aromatics. We design cyclophane host molecules that can recognize perfluorinated aromatic compounds in living systems through arene-perfluoroarene interactions as well as secondary non-covalent or covalent interactions. Ultimately, we aim to apply these novel host–guest complexes to the detection and/or treatment of diseases with a metabolic signature, such as cancer, inflammation, and drug-resistant infection. A different area employs perfluoroalkyl compounds, more commonly referred to as perfluorocarbons, which phase separate from aqueous and organic solution. The perfluorocarbons can be stabilized as droplets in water by using surfactant to create perfluorocarbon nanoemulsions. We view perfluorocarbon nanoemulsions as bioorthogonal, nano, reaction vessels and develop methods to load an array of payloads, control their biodistribution, and trigger their disassembly. The major goal of this work is to create a versatile nanomaterial scaffold that can be tailored toward many different diseases in a personalized manner. Additionally, we continue our fruitful collaboration with the Camp às group who have developed the first methods to measure mechanical forces in tissue by capitalizing on the orthogonality of perfluorocarbons. This method involves the microinjection of a droplet of perfluorocarbon containing a surfactant and fluorophore. The surfactant controls the interfacial tension of the droplet and the fluorophore allows for visualization by confocal microscopy. As the cells exert forces on the droplet, the droplet deforms. The deformation can be observed by microscopy and, if the interfacial tension is known, correlated back to forces. We employ our expertise in fluorous fluorophore and amphiphile synthesis to create custom components for the droplet measurements, expanding the range of forces and scope of animals in which these measurements can be performed.

NIH Research Projects · FY 2026 · 2025-04

PROJECT SUMMARY Repeat and prolonged treatment interruption (TI) (>28 days out of care) is common and the major threat to HIV epidemic control in eastern and southern Africa. Current services do not work for TI clients in the long-term. interventions for TI clients are limited in duration and services offered. Yet recent evidence shows that TI clients need long-term services tailored to their unique needs. TI clients experience varying and changing barriers to care that require tailored and responsive interventions. There are no one-size fits all intervention. Long-term and dynamic choice of DSD may be the best practical strategy to provide long-term, responsive TI interventions. We will implement a cluster randomized control trial (cRCT) to test the impact of a long-term, dynamic CHOICE intervention on 12-month viral suppression (<50copies/mL) among TI clients in Malawi. TI clients will receive person-centered counseling + ongoing, dynamic choice of how ART services are delivered over 24-months. Clients can combine multiple choices for service delivery at any given time to create personalized intervention packages. Choice of service delivery are informed by preliminary research and the building blocks of differentiated services and include: 1) ART dispensing intervals (1, 3, 6months), location of ART distribution (facility, home, or community), and if they want peer mentorship (if yes – frequency, when, where). Clients can adjust their choice at each ART visit or via hotline throughout study period. We will compare CHOICE to SOC (1-3 counseling sessions + routine facility-based services). Specific Aims are: Aim 1. Test the effectiveness of CHOICE versus SOC on 12-month viral suppression among TI clients in Malawi. We will conduct an individually randomized trial at 12 health facilities (n=800 individuals). Primary outcome is viral suppression (<50copies/mL) at 12-months (study collected sample). Secondary outcomes are: repeat TI and ART coverage (days with ART in possession) at 6, 12 and 24 months. Aim 2: Systematically evaluate the implementation of CHOICE. We will use mixed-methods to understand barriers, facilitators and needed improvements to HCW implementation of CHOICE, clients’ ability to choose DSDs, and equity in intervention implementation and outcomes. Aim 3. Estimate cost and cost-effectiveness of CHOICE. We will use a micro-costing approach to estimate the distribution of care costs by study arm, differences between arms, and incremental cost effectiveness. The trial will set the stage for how to best provide long-term, dynamic choice interventions to TI clients throughout the region. It is timely, feasible, and of high impact.

NSF Awards · FY 2025 · 2025-04

With the support of the Chemical Structure, Dynamics & Mechanisms-B (CSDM-B) and the Chemical Catalysis (CAT) programs, Osvaldo Gutierrez of the Department of Chemistry at Texas A&M University will use a mechanistic-driven, multi-technique approach to design and develop asymmetric multicomponent Fe-catalyzed cross-coupling reactions involving stabilized carbon-centered radicals. The long-term goal of this work is to develop iron-catalyzed multicomponent cross-couplings to the level of palladium and nickel-based systems in terms of synthetic applications and mechanistic understanding. The project lies at the interface of organic synthesis and computational chemistry and is well-suited to train the next generation of organic chemists at all levels. In parallel to this research activities, Dr. Gutierrez will continue to evolve initiatives aimed at increasing the number of underrepresented minorities in science, technology, engineering and mathematics (STEM) fields by integrating education, research, and outreach through partnerships with the Alliance for Diversity in Science and Engineering (ADSE), TED-style talks, and expansion of on-going collaborative research and educational programs with the community colleges. The development of inexpensive, sustainable, and selective catalysts that can directly convert simple chemical “building blocks” to high-value chiral compounds remains a grand challenge in chemical synthesis. In this vein, there has been surge in the development of new iron-catalyzed cross-coupling reactions due to iron’s higher abundance in the earth’s crust, lower cost, and less toxic properties in comparison to most transition metal counterparts. However, in contrast to nickel- and palladium-based systems, the use of iron complexes capable of controlling enantioselectivity in catalytic carbon-carbon bond formation remains extremely rare. In this project, the Gutierrez research group will use a mechanistic-driven, multi-technique approach to design and develop asymmetric multicomponent Fe-catalyzed cross-coupling reactions involving allyl-and alpha-heteroatom bearing radicals. Efforts will include continuing to perform both high-level quantum mechanical calculations and experiments to accelerate reaction and catalyst design. There are potentially significant long term scientific broader impacts related to sustainable chemistry, particularly through the development of earth abundant transition metal catalysis. 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 · 2025-04

PROJECT SUMMARY/ABSTRACT Freezing of gait (FOG) is a disabling symptom in advanced Parkinson’s disease (PD) with inadequate treatment options. The pathophysiology of FOG is poorly understood, likely contributing to disappointing results of novel neuromodulation strategies. The goal of this proposal is to identify electrophysiological mechanisms of FOG that can serve as biomarkers for novel neuromodulation strategies. Activity in the globus pallidus internus (GPi), the major output nucleus of the basal ganglia, is central to understanding basal ganglia contributions to gait impairment, as it provides insights into activity that downstream locomotor circuits read out from the basal ganglia. The project leverages a state-of-the-art multimodal brain/behavior recording platform and recent advances in sensing deep brain stimulation devices to record neural activity from the human GPi simultaneously with electroencephalography (EEG), motion capture and eye gaze during over-ground walking and FOG episodes in PD patients with and without FOG. To reliably elicit FOG episodes and improve external validity, we implement a novel immersive virtual reality environment to recapitulate real-world scenarios that commonly trigger FOG. With these tools, the proposed studies will determine how gait-related neural oscillations in the beta (12-30 Hz) and theta/alpha (4-12 Hz) bands in the GPi and cortex relates to abnormal gait during continuous walking (Aim 1); the onset and recovery from FOG episodes (Aim 2); and the therapeutic benefits from external cues (Aim 3). This paves the way for multiple innovative neuromodulation strategies that (1) prevent FOG episodes by promoting normal or compensatory gait control during continuous walking and (2) ameliorate severity of FOG episodes by targeting signals associated with FOG onset and recovery. Additionally, it establishes a novel VR paradigm for future precision-medicine approaches to FOG therapeutic development.

NIH Research Projects · FY 2026 · 2025-04

PROJECT SUMMARY/ABSTRACT Prostate cancer is the second most common cancer in men in the United States. The first line of treatment for men with aggressive prostate cancer is hormone therapy or androgen ablation therapy. Although initial responses are observed, unfortunately, the disease commonly recurs in its aggressive hormone therapy- resistant form also known as castration resistant prostate cancer (CRPC). Current therapies for hormone therapy resistant prostate cancer or CRPC prolong the patients’ lifespan by only a few months. Thus, there is an urgent need to identify the molecular mechanisms underlying the development of CRPC in order to define new strategies to overcome aggressive prostate cancer. Trop2 is a cell surface protein that is found altered in multiple types of human cancers. Our recent studies demonstrate that Trop2 is a novel promising therapeutic target for aggressive prostate cancer due to its high expression in advanced prostate cancer and its oncogenic role in the disease. The goals of the proposed research are to: 1) Establish Trop2 activation as a driver of advanced prostate cancer. 2) Investigate the molecular mechanisms through which Trop2 contributes to the development of the aggressive disease. The completion of the proposed project will lead to defining new molecular mechanisms underlying the development of aggressive prostate cancer. The proposed project will evaluate the oncogenic role of Trop2 receptor and its activation and cleavage in aggressive prostate cancer in pre-clinical models of prostate cancer creating an important translational link between the proposed research and treatment of patients with aggressive disease in the near future. Due to the high expression of Trop2 in many epithelial cancers, we believe that our findings will be applicable to a broad range of cancers.

NSF Awards · FY 2025 · 2025-04

This I-Corps project is based on the development of a mental health smart neurodiagnostic and neurointervention tool. Current diagnostic tools used to assess serious psychiatric disorders face challenges including the clinician's experience, the patient's willingness to disclose symptoms, the time and labor required, behavioral heterogeneity, and expense. This technology is a digital diagnostic and intervention platform that targets neurovascular dysfunction and its related neuromuscular dysfunction, sleep disturbances, impaired autonomous nervous system, and inflammation, which are the main factors in the development and progression of serious psychiatric disorders. The goal is to provide a digital set of quantitative physiological, neural, movement, psychological, and environmental measures of serious mental illness as well as to enhance access for early identification, treatment, and early preventive intervention of serious psychiatric disorders. This technology may reduce the delay in diagnosis of mental illness and improve patient outcomes by treating core psychiatric symptoms, improving neurovascular function and its related conditions. This I-Corps project utilizes experiential learning coupled with a first-hand investigation of the industry ecosystem to assess the translation potential of a mental health smart neurodiagnostic and neurointervention platform. The platform targets the main neurophysiologic factors in the development and progression of serious mental illness including neurovascular dysfunction and its related neuromuscular dysfunction, sleep disturbances, impaired autonomous nervous system, and inflammation. The solution is based on a model for body-mind biology in development and progression of serious psychiatric disorders. It uses multi-faceted hardware, firmware, and software developed for active and passive data including audio-video of the face; video electroencephalogram (EEG); neurovascular functions; clinical phenotypes of psychiatric disorder; and a custom developed, web-based cloud for body-mind machine learning. In addition, the technology includes a digital reminder intervention and multi-faceted hardware, firmware, and software for augmented reality and neurostimulation intervention for serious mental illness. The digital machine learning algorithms for the identification of serious mental illness, their related psychosomatic disorders, and self-regulation flexibility with neurointerventions may reduce core psychiatric symptoms and treat underlying neurovascular dysfunction and associated psychosomatic disorders at the earliest stages. 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 · 2025-04

This I-Corps project is based on the development of a biomonitoring device to track wellness and disease management. The device measures key metabolites, which are small molecules such as glucose (the body’s main source of energy) and ketones (metabolites from the breakdown of fat in the body seen during fasting or ketogenic diets) that can be measured in saliva and are important for providing information on physiological systems. Monitoring metabolites is crucial for understanding the body’s complex physiological processes and advancing both diagnostics and therapeutics. This noninvasive method allows individuals and clinicians to make informed decisions about daily nutrition and physical activity, supporting weight management and mitigating risks associated with metabolic disorders like diabetes. This device may have the potential to reduce healthcare costs, improve patient adherence, and enhance overall health outcomes. This I-Corps project utilizes experiential learning coupled with a first-hand investigation of the industry ecosystem to assess the translation potential of a device to measure metabolites in saliva. Currently, saliva is not used for biomonitoring as dilution can cause metabolite levels to fall below the detection limits of traditional sensors and/or increase susceptibility to interference, reducing the accuracy and reliability of measurements. This device is based on a single-walled carbon nanotube electrode architecture that leverages tandem metabolic pathway-like reactions for electrochemical analysis, enabling broad-spectrum metabolite detection. This technology integrates cofactors, self-mediates reactions at maximum enzyme capacity, and employs multifunctional enzymes to facilitate accurate metabolite sensing while mitigating interference. Proof-of-concept studies on a set of 12 key metabolites and nutrients have demonstrated a 100-fold enhancement in signal-to-noise ratio with multi-day operational stability. This technology demonstrated precise and non-invasive monitoring of highly diluted endogenous metabolites and nutrients in saliva, and robust in-vivo continuous monitoring of metabolites in the blood and brain environments. This solution may allow the use of saliva to monitor metabolites that are key indicators of physiological systems, reducing healthcare costs, improving patient adherence, and enhancing overall health outcomes. 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 · 2025-04

Collective Intelligence offers profound insights into how groups, whether they be cells, animals, or even machines, can work together to accomplish tasks more effectively than individuals alone. Originating in biology and now influencing fields as varied as management science, artificial intelligence, and robotics, this concept underscores the potential of collaborative efforts in solving complex challenges. On the other hand, the quest for finding global minimizers of nonconvex optimization problems arises in physics and chemistry, as well as in machine learning due to the widespread adoption of deep learning. Building the bridge between these two seemingly disparate realms, this project will utilize Collective Intelligence to leverage the interacting particle systems as a means to address the formidable challenge of finding global minimizers in nonconvex optimization problems. Graduate students will also be integrated within the research team as part of their professional training. This project will focus on a gradient-free optimization method inspired by a consensus-based interacting particle system to solve different types of nonconvex optimization problems. Effective communication and cooperation among particles within the system play pivotal roles in efficiently exploring the landscape and converging to the global minimizer. Aim 1 targets nonconvex optimization with equality constraints; and Aim 2 addresses nonconvex optimization on convex sets; while Aim 3 applies to Clustered Federated Learning. Additionally, convergence guarantees will be provided for nonconvex and nonsmooth objective functions. Theoretical analyses, alongside practical implementations, will provide valuable insights and tools for addressing different types of nonconvex optimization challenges. 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 · 2025-04

PROJECT SUMMARY Cancer monitoring is essential for the early detection and timely intervention of various adverse outcomes, such as minimal residual disease (MRD), recurrence, and side effects. Plasma cell-free DNA (cfDNA) has shown great promise for cancer monitoring due to its unique advantages: (1) noninvasiveness, which enables repeated collection; (2) comprehensiveness, as cfDNA contains DNA from different tumor clones; and (3) capability to inform side effects, as cfDNA comes from various organs, and damage to a specific organ can lead to increased DNA release from that organ. These advantages make cfDNA ideal to monitor various adverse outcomes. Yet a gap exists between the potential of cfDNA applications and method development. Current usage of cfDNA is limited to MRD/recurrence detection with small mutation panels. The proposed project aims to develop a computational system, TreatMonitor, for ultrasensitive, comprehensive, broadly applicable, and affordable cancer monitoring using multi-omics profiling of cfDNA. Dr. Li will improve MRD/recurrence monitoring by integrating exome- and methylome-wide tumor signals (Aim 1, K99). She aims to enable sensitive monitoring of side effects by accurately and comprehensively quantifying tissue contribution in cfDNA using deep learning (Aim 2a, K99), and identifying tissue damage from abnormally altered tissue contributions in patients’ cfDNA samples (Aim 2b, R00). Throughout the K99 and R00 phases, the method will be validated technically and clinically. TreatMonitor will be the first to achieve several milestones: the first approach to integrate cfDNA exome and methylome for monitoring, and the first cfDNA-based method for monitoring side effects during cancer treatment. TreatMonitor thus offers a comprehensive solution to monitor various adverse outcomes, informing early intervention, facilitating cfDNA-based cancer research, and ultimately improving the quality of life of cancer patients. Dr. Li’s’ long-term goals are to understand genetic and epigenetic influences on cancer treatment outcomes and to develop prognostic and predictive models that guide treatment selection. The overall training objective is to provide Dr. Li with additional years of mentorship to become a highly qualified independent investigator at the intersection of precision oncology, computational biology, and statistics. Training goals include the development of competencies in (1) the clinical and biological characteristics of cancer and its treatment, (2) advanced statistical methods in deep learning and longitudinal data analysis, and (3) professional development skills. Through this training, her background in statistics, computational biology, and liquid biopsy will be integrated to solidify her expertise in precision oncology as she transitions to an independent tenure-track faculty position. During the K99 phase, Dr. Li will be under the primary mentorship of Dr. Steven Dubinett, with a strong co-mentoring team (Drs. Wing Hung Wong and Samuel French). UCLA has a vibrant interdisciplinary community for cancer research with active collaboration, and all of the required equipment and facilities.

NSF Awards · FY 2025 · 2025-04

The Earth’s upper atmosphere includes a region of partially ionized gas known as the ionosphere. The magnetosphere, created by Earth’s magnetic field, acts as an obstacle to the solar wind, the stream of charged particles from the Sun. This project seeks to understand the processes heating electrons at polar latitudes using a combination of theory, numerical modeling, and analysis of radar and satellite observations. The processes coupling energy from the solar wind and magnetosphere into the ionosphere are highly complex. Accurately describing electron energetics in ionospheric models remains challenging due to the complex kinetic electron physics involved. A key parameter for understanding the ionosphere and ion escape from the ionosphere is the temperature of electrons. This research program will be combined with educational and public outreach efforts related to teaching about the physics of high-energy electrons in space, including those electrons that create the colors of the northern lights. The energetic electron transport phenomena studied in this project are very closely related to auroral electron transport phenomena. The project will create a “Make Your Own Aurora” website where users can learn about heliophysics by digitally simulating auroral emissions. Students of graduate and undergraduate levels will be involved in this project. This project seeks to understand the physical mechanisms controlling electron energetics in the polar cap ionosphere. The ability to predict ionospheric electron temperatures is of fundamental importance to aeronomy since they affect chemical reaction rates, ambipolar electric fields, plasma scale heights, and ion upflows. Science questions to be addressed are 1) Which physical processes explain the electron temperatures observed in the polar cap ionosphere? 2) How do polar cap electron temperatures vary with solar, geomagnetic, and background plasma conditions? And 3) How do electron temperature variations relate to ion upflow variations? They will perform statistical studies of temperature measurements from the Resolute Bay Incoherent Scatter Radar (RISR), measurements from the Defense Meteorological Satellite Program (DMSP) spacecraft, and energetic electron distributions from the Fast Auroral Snapshot (FAST) spacecraft. The theory and modeling activities will integrate kinetic models of energetic electrons previously developed into the High-latitude Ionospheric Dynamics for Research Applications (HIDRA) model. A computationally efficient version of HIDRA that can reproduce these measured quantities will be a major advance for high latitude modeling. 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 · 2025-04

Wildfires, including the 2025 Palisades and Eaton fires in Los Angeles, California, have devastating effects on communities, ecosystems, and infrastructure. The severity of these impacts is driven, in part, by how wildfire alters the soil properties that drive flooding and landslides. Yet, the impact of wildfire on soil health and hydrology remains underexplored. Understanding these impacts is crucial for informing disaster preparedness, land management, and restoration strategies, particularly in regions increasingly prone to wildfires. This project will investigate how fire altered soil properties and hydrological processes in regions impacted by the Palisades and Eaton fires in Los Angeles, as well as the resilience of these systems over time. This project will produce essential information to enhance early warning systems for hydrological disasters, such as flooding and landslides, which are exacerbated by fire-induced soil degradation. Additionally, the study will provide valuable insights for policymakers, conservation agencies, and local communities on effective post-fire recovery measures. The project also fosters educational advancement by offering graduate and undergraduate students hands-on experience in field research and laboratory analysis. This research will assess wildfire-induced changes in soil properties and hydrological functions across different burn severities, vegetation types, and landscape positions. Specifically, the project will characterize the spatial patterns of soil degradation and hydrologic change following wildfires. The project will also determine how rates of recovery in soil health and hydrology vary across severely burnt, moderately burnt, and unburnt areas. The project team will compare spatial field measurements in areas affected by the recent (Palisades and Eaton) fires to those impacted by older fires. Measurements through time will be made in representative sites under severe, moderate, and unburnt conditions. Data collection will include soil physical and chemical properties, infiltration capacity, saturated hydraulic conductivity, nutrient availability, soil moisture profiles, plant community composition, and soil microfauna. The findings will advance scientific understanding of wildfire impacts on soil health and hydrological resilience, contributing to the fields of hydrology, soil science, and fire ecology. 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 · 2025-04

This I-Corps project is based on the development of a tool to assess mental health conditions using wearable sensors to monitor stress. Currently, insurance companies and clinicians rely on patient self-reports, psychological assessments, and limited physiological monitoring such as pulse, heart and respiratory rate, and the electrical activity of the brain to assess mental health conditions. However, these methods are often inconsistent and prone to error. This technology is based on the use of a sensor to measure cortisol levels in the body, which is the primary stress hormone. Alterations in cortisol levels have been shown to correspond to stress and mental state. This technology may fill the critical gap in how mental health is measured and treated. The goal is to improve outcomes for patients with mental health conditions. This I-Corps project utilizes experiential learning coupled with a first-hand investigation of the industry ecosystem to assess the translation potential of a quantitative cortisol measurement tool based on acoustic wave sensors and molecularly imprinted polymers (MIPs). This solution is a wearable technology that aims to provide a continuous assessment of the mental state of a patient based on cortisol levels in the body. This sensor technology combines MIPs with acoustic wave devices to provide continuous cortisol monitoring. Cortisol is targeted using a MIPs bioreceptor that is capable of operating in situ continuously. The binding of cortisol in the MIP leads to a shift in the resonant frequency of the acoustic wave devices made of piezoelectric materials. The frequency shift can be electrically read by applying voltages to the acoustic wave devices. This innovation may enable better assessment of mental health conditions, better treatment decisions, and improved patient outcomes. 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 · 2025-04

Project Summary Autism spectrum disorder (ASD) is associated with marked heterogeneity with respect to the development of executive function (EF) abilities. In the United States, 12 million children primarily speak a language other than English in the home, suggesting that 1 in 4 children with ASD are being raised in a bilingual environment. Individuals who speak two languages fluently sometimes perform better on tasks of EF than monolingual individuals. Despite the potential advantages that bilingualism may confer, clinical practitioners commonly advise against providing a bilingual environment for children with developmental disabilities. The rationale for this recommendation is that concentrating on one language should better support a child’s language development. Yet, a growing body of work suggests there are no negative effects of being raised in a bilingual environment for children with neurodevelopmental disorders. Preliminary evidence even suggests possible associations between bilingualism and enhanced EF in some children with ASD. Still, there is little research specific to bilingualism in children with ASD, leaving clinicians struggling to develop informed recommendations for families of children with the disorder. Currently, there is no developmental cognitive neuroscience research specific to bilingualism in ASD during the critical period of early adolescence, when EF abilities and the brain networks supporting them are rapidly maturing. This project will capitalize on data collected as part of an ongoing project (R21HD111805) to determine longitudinal associations between bilingualism, EF, and brain organization in ASD using behavioral and informant-report assessments combined with state-of-the-art multimodal neuroimaging approaches. We will collect two additional time points of data from 150 age-, IQ-, sex-, SES-, pubertal stage-, and ASD-severity matched monolingual and bilingual children with ASD who were between the ages of 8-12 at initial study enrollment and will be between 12-16 at study completion. The project aims to 1) determine longitudinal associations between bilingualism and EF abilities in children with ASD using an informant-report indicator of EF, a performance-based laboratory task developed by our lab, and NIH Toolbox Tasks of EF, 2) to determine the longitudinal impact of bilingualism on brain functional organization underlying EF abilities in children with ASD using both task-based functional magnetic resonance imaging and resting-state functional connectivity dynamics, and 3) to determine the longitudinal impact of bilingualism on brain structural organization underlying EF abilities in children with ASD using diffusion weighted imaging. The project will be conducted in Los Angeles, where nearly 60% of the population is bilingual. This research addresses the strategic plan from the Interagency Autism Coordinating Committee that aspires to understand alterations in brain function in ASD to better enable the development of targeted interventions and societal accommodations that improve quality of life for individuals on the spectrum.