University Of California Los Angeles

NIH Research Projects · FY 2025 · 2025-09

PROJECT SUMMARY Vascular grafts, which are used to replace, bypass, or repair diseased blood vessels in approximately 3 million surgeries each year, play a crucial role in various medical procedures. However, stenosis remains a significant issue of post-implantation, with nearly 40% of grafts experiencing reduced patency within 2 years. This high incidence of stenosis and its life-threatening complications highlight the urgent need for continuous monitoring of vascular graft patency. However, existing imaging methods for assessing vascular graft stenosis, including X- ray angiography, magnetic resonance imaging, and Doppler ultrasound, are unsuitable for continuous monitoring due to their dependence on operator-controlled equipment, invasive contrast agents, and/or exposure to ionizing radiation. Vascular graft stenosis often goes undetected until it progresses to complete occlusion, necessitating repeat surgeries. To address this grand challenge, we propose a magnetoelastic vascular graft (MVG) as a transformative platform technology that not only restores blood flow but also enables wireless, real-time, and continuous stenosis diagnosis. Our proposed MVG directly translates hemodynamics into high-fidelity electrical signals, which can be wirelessly transmitted outside the human body. As stenosis changes the hemodynamics by restricting blood flow, further analyzing these received signals by using artificial intelligence (AI) can enable continuous and accurate patency monitoring and timely postoperative complication management. Moreover, the MVG’s hemodynamics-driven working mechanism eliminates the need for external power or frequent interventions, enabling continuous, real-time stenosis monitoring anywhere, anytime. This innovative platform technology stems from PI’s recent discovery of the giant magnetoelastic effect in soft matter (Nat. Mater. 2021; Highlighted by Nature). In our preliminary studies, we successfully fabricated MVGs with scalability and customizability and validated their biocompatibility and stenosis diagnosis capability in both rat and swine models in vivo. To further test our hypothesis, three specific aims are proposed for this R01 Research Project: Aim 1) To optimize the MVG and determine how the degree of stenosis affects sensing signals. Aim 2) To investigate the long-term biosafety and sensing durability of the MVG in rat models. Aim 3) To investigate the long-term stenosis monitoring in swine models. To achieve these proposed aims, we have assembled a multidisciplinary team with complementary expertise, including PI Prof. Jun Chen (Ph.D., leading expert in soft magnetoelastic bioelectronics), Co-Is Prof. Song Li (Ph.D., expert in vascular tissue engineering), and Prof. Geoffrey Colby (M.D., Ph.D.,16 years of expertise in open microsurgical and endovascular treatments), and Prof. Wei Wang (Ph.D., Fellow of ACM, IEEE, clinical big data analysis), and Consultant Prof. Murray H. Kwon (M.D., MBA, expert cardiothoracic surgeon). Successful deliverables are expected to drive a transformative shift in vascular disease management, enhancing both quality of life and human longevity.

NIH Research Projects · FY 2025 · 2025-09

Project Summary Learning to predict the time of salient environmental stimuli, such as rewards, is essential for survival. During classical conditioning, animals learn when to expect a rewarding stimulus (e.g., food) following a predictive cue (e.g., odor). The striatum is implicated in associative reward learning, movement, and timing. Furthermore, the predominant striatal neuron types, medium spiny projection neurons (MSNs) expressing dopamine receptor type 1 (D1) or 2 (D2), both contribute to these diverse behavioral functions. However, the specific roles of D1 and D2 MSNs in learning to represent time are unknown. The research goal of my training grant is to elucidate how temporal coding by ventral striatal D1 and D2 MSNs evolves during learning and the extent to which these distinct cell types contribute to the learning of timed motor behavior. My central hypothesis is that (1) learning improves D1 and D2 MSN temporal coding in response to a reward-predictive cue, and (2) D1 and D2 MSNs exhibit opposing, complementary roles for learning to initiate precisely timed movements. To test this hypothesis, I will utilize a classical conditioning behavioral paradigm in which mice learn to lick in anticipation following a reward- predictive cue. In either the early or late stages of learning, I will use in vivo electrophysiological recordings from optogenetically identified D1 and D2 MSNs, behavioral assessment of the effect of perturbing these cell types, and computational methods to decode time from neural population activity. In Aim 1, I will record D1 and D2 MSN dynamics in different stages of learning and decode time using a machine learning-based pattern classifier. Aim 1 analyses will make comparisons of temporal decoding performance between D1 and D2 MSNs, early and late stages of learning, and distinct temporal intervals. In Aim 2, I will elucidate the causal roles of D1 and D2 MSN activity for learning to produce precisely timed, reward-conditioned licking movements. I will optogenetically inhibit the activity of D1 or D2 MSNs throughout classical conditioning, and I will determine the extent to which these perturbations impact the execution of conditioned licking behavior (e.g., lick initiation time and lick probability). The expected outcomes are that perturbing D1 and D2 MSN activity throughout learning will impair both the temporal precision and mean time of cue-evoked lick initiation. Specifically, I expect that there will be differential effects of D1 and D2 MSN perturbations, such that inhibition of D1 and D2 MSNs increases and decreases mean lick onset time, respectively. These outcomes would suggest that a precise balance of D1 and D2 MSN activity underlies behavioral timing during associative learning. Overall, this project will provide insights on the temporal nature of how the brain processes reward during experience-dependent learning.

NIH Research Projects · FY 2025 · 2025-09

A crucial problem in various areas of life science is to determine which known small molecules are present/absent in a specific sample. As an example, physicians might be interested in characterizing the molecules in oral/urinal/fecal samples collected from a patient. Ecologists are interested in characterizing the molecules produced by microbes in various environmental / host- oriented microbial communities. Natural product scientist focusing on discovery of novel antimicrobial or antitumor molecules are interested in determining all the known molecules in their sample, in order to focus their effort on the novel ones. In next five years, the goal of Mohimanilab is to develop efficient algorithms for identification of known and novel small molecules in complex samples. Efficient search of a spectrum against a large number of mass spectra/predicted spectra is a fundamental task arising in various problems including mass spectral library search and identification of small molecules by database search of mass spectra in metabolomics. Given a database of millions/billions of reference spectra and a query spectrum, our goal is to find the (predicted) spectrum that generates the query spectrum. Modern search engines usually form a probabilistic model between the spectra and the reference molecules. Then a probabilistic score can be calculated between each query spectrum and each reference molecule. The main problem with this approach is that the runtime of the search grows linearly with the size of the database. For example, searching a single query spectrum against all the reference spectra available at the Global Natural Product Social molecular networking infrastructure dataset (~1 billion spectra) takes more than two weeks on a single CPU. In the case of unrestricted search allowing for a modification of the query spectrum in relation to the reference, the runtime increases to multiple years per query spectrum. Therefore, faster approaches are needed to search mass spectra against large reference databases. In this proposal, we develop indexing strategies to speed up these queries. In this proposal, we will develop new algorithmic approaches for identifying known/novel small molecules from complex samples, based on mass spectrometry data. Tools developed during this proposal will be provided to the scientific community through the Global Natural Product Social molecular networking webserver.

NSF Awards · FY 2025 · 2025-09

Understanding how quarks and gluons—the fundamental building blocks of matter—combine to form protons and other hadrons is essential to uncovering the structure of the visible universe. This research investigates how these elementary particles are distributed inside hadrons and how they interact through the strong nuclear force, as described by quantum chromodynamics (QCD). This project combines modern machine learning tools—especially transformer-based deep learning architectures—with advanced theoretical approaches to extract detailed physical information from high-energy particle collision data. Another central focus is on energy-energy correlators (EECs), observables that provide sharp insight into the dynamics of quarks and gluons in hadronic final states. This work contributes to fullfilling the scientific mission of U.S. nuclear physics facilities and supports future discoveries at the Electron-Ion Collider, while also advancing techniques relevant to particle physics research at the Large Hadron Collider. By integrating theory, computation, and data-driven analysis, the project promotes a deeper understanding of matter at its most fundamental level. This project develops new theoretical frameworks and global QCD analysis strategies that combine novel observables with machine learning to reveal the internal dynamics of strongly interacting particles. It incorporates hadron-in-jet observables to extract nonperturbative fragmentation functions within a QCD-based framework, enabling detailed insights into the dynamics of quarks and gluons as they fragment into observable hadrons. A major focus is the energy-energy correlator, where new theoretical developments extend its application to spin phenomena and the small‑x regime relevant for probing gluon saturation. By bridging lepton and hadron collision data through unified theoretical treatments, the project improves constraints on nonperturbative QCD effects across broad kinematic regimes. The resulting framework will enable robust comparisons with experimental data across a wide range of momentum scales. To overcome computational bottlenecks in global fits, transformer-based machine learning models are employed to emulate expensive calculations and enhance the precision of extracted information about quark and gluon dynamics. These methods directly support data interpretation at the Jefferson Lab, the Relativistic Heavy Ion Collider, and the Large Hadron Collider, and provide essential theoretical tools for the future Electron-Ion Collider and broader efforts in high-energy nuclear and particle physics. 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 Interstitial lung disease (ILD) is a leading cause of systemic sclerosis (SSc)-related death in the United States and the World. ILD occurs in the majority of patients with SSc and progresses the most rapidly early in the disease course. We have demonstrated that patients who experience SSc-ILD progression within the first two years of their disease have an increased risk of premature mortality. Therefore, modifying the course of SSc- ILD at this early disease stage through therapeutic intervention can improve outcomes for patients. However, no reliable treatment response biomarkers exist for SSc-ILD to personalize therapy. Clinicians struggle to determine whether a patient is responding to a specific therapy using existing response tools that rely on clinical, physiologic and radiologic assessments, which are imperfect in their ability to categorize patients who are and are not benefiting from therapy. Further, measurable changes in the existing response tools only occur after a substantial amount of time (1 year or more) and lung damage has occurred from ILD. Response biomarkers that signal therapeutic efficacy early in the course of treatment are greatly needed. With the expansion of treatment options for SSc-ILD, reliable response biomarkers could guide clinicians to stop administering an ineffective agent and start an alternative agent before the patient experiences irreversible lung damage. Our group has demonstrated that specific circulating biomarkers, such as C-reactive protein, interleukin-6, and chemokine (C-X-C motif) ligand 4, chemokine ligand 18 and Krebs von den Lungen 6, decrease in response to treatment with mycophenolate mofetil (MMF) in the context of a clinical trial. A greater decline in these biomarkers at 1 year was associated with future improvement in lung function at 2 years. We herein propose to validate the aforementioned response biomarkers in an observational cohort of patients with SSc-ILD and determine whether early changes (at 3, 6 months) in these and other circulating biomarkers predict progressive pulmonary fibrosis (PPF) at 1 year. We also propose to study a novel response biomarker for SSc-ILD: Positron emission tomography (PET) with a tracer that targets fibroblast activation protein (FAP). Through measuring the change in pulmonary 68Ga-FAPi-46 uptake, we aim to track the evolution of fibrotic remodeling activity in the lungs and link these changes to changes in circulating biomarkers. We hypothesize that a panel of circulating biomarkers will predict changes in 68Ga-FAPi-46 uptake, as well as PPF at 1 year. To test this hypothesis, we will perform biochemical and functional imaging biomarker assessments early in the treatment course and evaluate patients for PPF at 1 year. This work will: (1) Identify circulating response biomarkers for SSc-ILD; (2) Determine whether functional imaging plays a role in monitoring treatment response in SSc-ILD; (3) Understand how 68Ga-FAPi-46 uptake correlates with radiologic features of ILD (e.g., fibrosis, ground glass, honeycombing); (4) Reveal biological pathways linked to fibrotic remodeling activity on PET imaging. This work is not only relevant for SSc, but also for other rheumatic diseases associated with ILD.

NIH Research Projects · FY 2025 · 2025-09

PROJECT SUMMARY/ABSTRACT (Limit: 30 lines of text) Chromatinopathies, defined as developmental disorders caused by germline mutations in epigenetic genes, present a significant challenge for millions of Americans affected by these 179 rare diseases since ~94% of all rare diseases do not have treatments available -- highlighting a huge patient population with unmet needs. Our lab found heterozygous nonsense mutations (i.e. truncating) in the KAT6A gene cause a Chromatinopathy called Arboleda-Tham Syndrome (ARTHS) that is also referred to as a rare neurodevelopmental disorder. Although neurological deficits are always observed in ARTHS, the pathogenic mechanisms underlying these phenotypes are not understood and nothing is known about KAT6A’s functions in human neurodevelopment (ND). KAT6A is the catalytic subunit of a histone acetyltransferase (HAT) complex that acetylates histones. My preprint study of ARTHS Cerebral Organoids (COs) describes the consequences of KAT6A deficiency during in vitro human ND. We show ARTHS COs are delayed in repressing the expression of pluripotency/cell cycle transcription factors (TFs) during neural differentiation compared to controls -- leading to an overabundance of cycling neural progenitor cell (NPC) markers in genes upregulated in ARTHS COs. My preliminary data also shows ARTHS neurons suffer from phenotypic defects like aberrant synapse morphology and metabolic dysfunction compared to controls. We propose a research strategy to uncover the mechanisms underpinning our observations in neural models derived from ARTHS patients to elucidate the functional consequences of KAT6A deficiency during human in vitro ND. I hypothesize during neuronal differentiation, truncating KAT6A mutations cause reduced KAT6A protein or HAT activity -- leading to altered gene regulation at cell cycle and ND-related genes via remodeling of histone acetylation and TF binding. I also hypothesize, independent of these gene regulatory consequences, the loss of KAT6A function negatively affects NPC cell fate & neuron health through altered proliferation and mitochondrial dynamics, respectively. I will differentiate rare induced pluripotent stem cells harboring truncating KAT6A mutations and matched controls into NPCs and neurons. In Aim 1, I will apply complementary functional genomics assays to these cells & perform vertical data integration to identify the precise mechanisms by which KAT6A deficiency causes aberrant changes in transcription and chromatin remodeling via perturbations to the histone acetylation and TF landscape. In Aim 2, using these cells and KAT6A inhibitors, I will quantify changes in select cellular phenotypes using high throughput methods to deconvolute the negative phenotypic consequences of losing KAT6A function during neuronal differentiation. Together, these aims utilize orthogonal approaches in human stem cells to identify the molecular and cellular mechanisms underpinning KAT6A’s function in human in vitro ND and ARTHS neuropathology.

NIH Research Projects · FY 2025 · 2025-09

PROJECT SUMMARY/ABSTRACT Social dysfunction is a core feature of schizophrenia, and individuals with a schizophrenia diagnosis often lack strong social ties to friends and family. This type of social disconnection is detrimental to health and associated with reduced quality of life. However, current treatments have little to no effect on social functioning and connectedness in schizophrenia, and new treatment approaches are urgently needed. Yet, poor understanding of the neural mechanisms that underlie the formation and maintenance of social connections in schizophrenia has hindered the development of novel interventions. Recent social neuroscience research has identified inter- brain synchrony as an important neural mechanism that promotes the formation of social ties by facilitating successful social interactions in healthy samples. Converging evidence suggests that this mechanism may be disrupted in schizophrenia, yet it has never been investigated directly in a schizophrenia sample. This project will investigate inter-brain synchrony and its relevance to social connection in schizophrenia for the first time, using methods adapted from non-clinical research. In this study, participants who have a schizophrenia diagnosis and healthy control participants will each take part in structured social interactions with two different laboratory confederates while electroencephalographic (EEG) recordings are collected simultaneously from both the participant and the confederate. The interaction with one confederate will include a conversation structured to induce a feeling of interpersonal closeness (experimental condition), while the interaction with the other confederate will include a conversation structured to include only superficial small-talk (control condition). The amount of inter-brain synchrony between participants and confederates will be assessed based on EEG activity from just before and after each conversation, during a brief collaborative task. This study has two major goals. First, the project will investigate inter-brain synchrony as a neural mechanism of social dysfunction in schizophrenia by comparing synchrony between the schizophrenia and control samples as well as investigating relationships between levels of inter-brain synchrony and participants’ social connectedness. Second, the project will test the malleability of inter-brain synchrony measures by comparing synchrony between the two experimental conditions and the pre- vs. post-conversation measures. As an additional goal, the project will investigate relationships between inter-brain synchrony and interpersonal synchrony of behavior measured during the social interactions, and with clinical variables (e.g., symptoms). Achieving these goals has the potential to transform the understanding and treatment of social dysfunction and disconnectedness in schizophrenia by elucidating the role of a novel neural mechanism. This study could offer new treatment targets for interventions to improve social functioning, and it could provide a basis for the development of novel biomarkers to assess social functioning in schizophrenia and other mental health conditions.

NSF Awards · FY 2025 · 2025-09

The interactions between plants and fungi, both beneficial and deleterious, significantly affect agricultural output, food safety, and bioeconomy. Beneficial fungal-plant interactions can lead to increases in plant robustness and crop yield, while deleterious interactions can lead to devastating plant diseases and tremendous economic loss. Many aspects of these interactions are mediated by small organic molecules known as secondary metabolites produced by the fungi. These molecules can direct impact plant health, effect the symbiotic plant-fungi relationships and control the soil microorganism composition. Despite the importance of these metabolites in mediating plant-fungi interactions, only a limited number of compounds are known. Therefore, a complete understanding of the chemical identities and functions of these molecules is critical to our ability to control the fungal-plant interactions, and to benefit agriculture and plant-based bioeconomy. To do so, the researchers will apply synthetic biology approaches to genetically and chemically catalog the secondary metabolites that can be biosynthesized by different plant-associated fungi. They will then test the biological activities of these compounds directly on model plants grown in the laboratory to assess their functions. If beneficial or deleterious effects on plant are observed, they will perform plant genetic studies to understand the target of the compounds. Successful completion of this project will unveil the multitude of interactions between fungi and plants, provide access to chemicals that can be used to improve plant growth and crop yield, and develop new strategies to overcome the devastating plant diseases caused by pathogenic fungi. It is widely accepted that secondary metabolites are highly important in fungal-plant interactions. However, a very limited number of compounds from fungi has been isolated and characterized. Genome sequences of biocontrol and phytopathogenic fungi have revealed each fungus can encode 50~80 biosynthetic gene clusters (BGCs) that are associated with secondary metabolite biosynthesis, with an overwhelming majority of these (> 90%) remain uncharacterized with unknown metabolites in laboratory conditions. Transcriptomics data with pathogenic fungi showed numerous BGCs are upregulated during different phases of plant colonization and virulence, yet the metabolites have remained completely unknown. The objectives of this project are to expand the inventory of secondary metabolites from these plant-associated fungi, and to understand their biological roles. Towards these goals, this project will use systems and synthetic biology tools to perform genome mining of the BGCs, and genetic and biochemical approaches to identify the molecular targets of bioactive metabolites. In Objective 1, the researchers will refactor BGCs from the genomes of beneficial fungi such as Trichoderma afroharzianum t-22 and Gliocladium roseum, and produce the compounds in heterologous hosts. Objective 2 will focus on the devastating wheat pathogen Zymoseptoria tritici. We will use bioinformatics and heterologous expression to identify metabolites from BGCs that are elevated during the biotrophic and necrotrophic phases of fungal growth in wheat. In Objective 3, the researchers will analyze the small molecules that exhibit functions on plants for their modes of action using forward genetics in Arabidopsis thaliana. This project represents an important step towards fully mapping the small molecule interactome. 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 Successfully navigating one’s environment requires simultaneous processing of reward seeking and risk aversion. For example, driving to work or walking through a crowded city center includes reaching spatial targets in a timely manner while avoiding collisions with stationary and/or moving objects. Spatial processing and decisions involving avoidance and pursuit are both linked to medial temporal lobe (MTL) structures including the hippocampus and amygdala, and pathologies within these networks cause altered decision-making patterns. While the physiological aspects of MTL engagement during avoidance and pursuit have been explored in rodents and stationary humans, the parallel neuronal mechanisms in freely-moving humans remain entirely unknown. The proposed study will leverage a unique cross-institutional collaboration, recruiting human participants from a database of epilepsy patients with acute or chronic implants to record single-unit and local field potential activity from key regions such as the hippocampus, amygdala, nucleus accumbens, and prefrontal cortex. The project will also harness cutting-edge wearable technologies, including eye tracking, augmented reality (AR), and motion capture. Participants will engage in a naturalistic navigation task requiring the pursuit of spatial targets to earn monetary rewards, all while maintaining a specified distance from an experimenter who is in constant motion within the environment. The proposed research will identify MTL population oscillatory (Aim 1) and single- neuron (Aim 2) mechanisms supporting avoidance and pursuit in freely-moving humans. This will allow for a comprehensive understanding of naturalistic navigation, including aversion to penalties, pursuit of rewards, tracking the movements of another individual, and the manifestation of behaviors such as freezing. The insights gained from this research have the potential to guide the development of stimulation-based therapeutic interventions targeting emotional regulation disorders and other conditions rooted in MTL-related pathologies. Additionally, the proposed study will pave the way towards understanding the intricacies of human cognitive and neural processes in complex real-world scenarios, fostering a bridge between fundamental neuroscience and practical clinical applications. This project will be conducted under the supervision of Dr. Nanthia Suthana and Dr. Ausaf Bari as part of the UCLA-Caltech Medical Scientist Training Program.

NSF Awards · FY 2025 · 2025-09

This award is made in response to Dear Colleague Letter 24-130, as part of the ECosystem for Leading Innovation in Plasma Science and Engineering (ECLIPSE) interdisciplinary program. The award supports a joint Grant Opportunities for Academic Liaison with Industry (GOALI) effort by the University of California - Los Angeles and Lam Research Corporation that includes a collaboration with Sandia National Laboratories. Each year the worldwide industry produces over a trillion computer chips, or about 150 chips per person, with semiconductor sales amounting to hundreds of billions of dollars. Some are simple transistor circuits and others are extremely complicated AI circuits. Memory chips with up to 50 billion transistors on a chip are now being produced, and all these chips are made in machines containing plasmas. The plasma-based manufacturing is responsible for production of much of the modern electronics, yet improvements in the future generations of chips rely on better understanding of the plasma behavior. This award supports a research collaboration between the chip making industry and UCLA to do just that. The intricate construction of chips occurs in highly specialized fabrication facilities, where components from capacitors and wires to transistors are meticulously assembled on an atomic level. Central to this sophisticated manufacturing process is the use of plasma etch technology, an indispensable tool in the creation of these fundamental building blocks of modern electronics. This research effort will use lasers to measure the motion of positively charged ions and the electric fields inside an actual chip making tool donated by the LAM Research Corporation. One technique uses Laser Induced Fluorescence to track ions. This technique makes ions moving at a certain velocity glow when a laser beam of exactly the right wavelength strikes them. Motion maps are generated for all velocities. The second technique, Raman Dip Spectroscopy, uses two carefully tuned lasers to excite electrons in outer atomic orbits of the neutral atoms. The result is a map of the electric field in the device with 10 nanosecond temporal resolution and spatial resolution of 10’s of microns. These measurements have never been done in a modern plasma etch tool. 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 Autistic individuals, who represent 1 in 36 individuals in the United States, are disproportionately likely to experience obesity relative to the general population. Obesity rates among this group increase during adolescence and emerging adulthood (age 15–30). Chronic stressors, defined as persistent and cumulative stressful experiences over the life course, are key mechanisms underlying obesity in the general population because they elicit chronic stress responses leading to obesity, including chronically elevated concentration of the stress hormone cortisol that increases food consumption and fat storage. Autistic individuals experience severe chronic stressors in the forms of lifelong stigma, discrimination, victimization, and rejection. Three-fourths engage in camouflaging: utilizing behavioral and cognitive strategies to mask autistic traits to appear more “typical.” Camouflaging—found to coincide with periods of developmental changes and transitions—is a potentially highly impactful chronic stressor for autistic individuals. Camouflaging leads to low well-being, self-esteem, and quality of life; high distress, anxiety, depression, and suicidality; and delayed diagnosis and compromised healthcare, which are linked to obesity in the general population. Despite this, research has yet to investigate camouflaging as a potentially impactful chronic stressor leading to obesity in autistic populations. I will address this gap through my proposed research. In collaboration with my mentorship team of R01-funded investigators and community collaborators, I will collect a multi-modal suite of pilot data—including validated survey data and assessment of cortisol through mail-in hair sampling—from 250 autistic adolescents and emerging adults. I will test associations between chronic stressors—including camouflaging—and obesity; assess whether the association between camouflaging and obesity is strongest for those with chronically elevated cortisol; and test sub-group differences based on autism severity. This research addresses NIDDK's mission to address disproportionate obesity in minority populations by informing efforts to make obesity interventions more effective for a large and at-risk population. The combination of my proposed K01 training and unparalleled access to an expansive recruitment and data collection network makes me uniquely positioned to carry out this research. I will gain knowledge and skills in obesity and biomedical research as well as cultivate leadership skills and develop and submit an R03 application in preparation for an eventual R01. This project supports my long-term goal of becoming an independent investigator in obesity at the intersection of developmental and biomedical health.

NSF Awards · FY 2025 · 2025-09

The interactions between plants and fungi, both beneficial and deleterious, significantly affect agricultural output, food safety, and bioeconomy. Beneficial fungal-plant interactions can lead to increases in plant robustness and crop yield, while deleterious interactions can lead to devastating plant diseases and tremendous economic loss. Many aspects of these interactions are mediated by small organic molecules known as secondary metabolites produced by the fungi. These molecules can direct impact plant health, effect the symbiotic plant-fungi relationships and control the soil microorganism composition. Despite the importance of these metabolites in mediating plant-fungi interactions, only a limited number of compounds are known. Therefore, a complete understanding of the chemical identities and functions of these molecules is critical to our ability to control the fungal-plant interactions, and to benefit agriculture and plant-based bioeconomy. To do so, the researchers will apply synthetic biology approaches to genetically and chemically catalog the secondary metabolites that can be biosynthesized by different plant-associated fungi. They will then test the biological activities of these compounds directly on model plants grown in the laboratory to assess their functions. If beneficial or deleterious effects on plant are observed, they will perform plant genetic studies to understand the target of the compounds. Successful completion of this project will unveil the multitude of interactions between fungi and plants, provide access to chemicals that can be used to improve plant growth and crop yield, and develop new strategies to overcome the devastating plant diseases caused by pathogenic fungi. It is widely accepted that secondary metabolites are highly important in fungal-plant interactions. However, a very limited number of compounds from fungi has been isolated and characterized. Genome sequences of biocontrol and phytopathogenic fungi have revealed each fungus can encode 50~80 biosynthetic gene clusters (BGCs) that are associated with secondary metabolite biosynthesis, with an overwhelming majority of these (> 90%) remaining uncharacterized with unknown metabolites in laboratory conditions. Transcriptomics data with pathogenic fungi showed numerous BGCs are upregulated during different phases of plant colonization and virulence, yet the metabolites have remained completely unknown. The objectives of this project are to expand the inventory of secondary metabolites from these plant-associated fungi, and to understand their biological roles. Towards these goals, this project will use systems and synthetic biology tools to perform genome mining of the BGCs, and genetic and biochemical approaches to identify the molecular targets of bioactive metabolites. In Objective 1, the researchers will refactor BGCs from the genomes of beneficial fungi such as Trichoderma afroharzianum t-22 and Gliocladium roseum, and produce the compounds in heterologous hosts. Objective 2 will focus on the devastating wheat pathogen Zymoseptoria tritici. The researchers will use bioinformatics and heterologous expression to identify metabolites from BGCs that are elevated during the biotrophic and necrotrophic phases of fungal growth in wheat. In Objective 3, the researchers will analyze the small molecules that exhibit functions on plants for their modes of action using forward genetics in Arabidopsis thaliana. This project represents an important step towards fully mapping the small molecule interactome. 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

The discovery of new pharmaceutical compounds relies on the ability to synthesize increasingly complex scaffolds with desirable biological and pharmacokinetic properties. To foster continued growth in this area, new transformations to access small organic molecules are required. Methods which form new C–N bonds are highly valuable, as over 50% of the top two hundred drug compounds contain at least one N-atom. Recently, the Doyle group has demonstrated that sulfonamides can be activated for hydroamination reactions using photoredox/phosphine catalysis through α-scission of an intermediate phosphoranyl radical. While phosphoranyl radicals have been used to enable a variety of transformations through β-scission, transformations proceeding through α-scission are underdeveloped despite providing an approach to form C–N or C–heteroatom bonds. To promote the development of new transformations relying on phosphoranyl radicals, a better understanding of the factors controlling α- versus β-scission is required. We propose leveraging data science to build a comprehensive, predictive model explaining phosphoranyl radical α- versus β-scission selectivity. This model will employ data collected from a model reaction to train predictive machine learning algorithms, overcoming limitations in our current mechanistic understanding of this process. In addition, we will leverage phosphine activation of N-nucleophiles for a novel alkene carboamination reaction based on a photoredox, phosphine, and nickel tandem catalysis. This unique approach relies on the ability of phosphine catalysis to form N-centered radicals and the established reactivity of nickel catalysis towards C-centered radicals to enable a desirable carboamination reaction without the requirement of pre-functionalized amines or stoichiometric reagents. In addition, this approach is amenable to carboamination with N-heterocycles. Overall, the proposed research is comprised of two aims: (1) develop predictive machine learning algorithms to determine factors influencing the selectivity of α- and β-scission of phosphoranyl radicals, and (2) develop a photoredox, phosphine, and nickel catalysis mediated carboamination reaction. These aims will be explored concomitantly with data collected in aim 1 being applicable to, but not necessary for, the completion of aim 2. Aim 1 will contribute significantly to our understanding of phosphoranyl radical reactivity, promoting the design and development of new transformations relying on this powerful mechanistic step. The transformation developed in aim 2 will address challenges in currently available carboamination reactions to generate desirable C–N and C–C bonds and will provide a framework for future reactions combining photoredox, phosphine and nickel catalysis. Overall, this work represents a significant advance in the field of phosphoranyl radical reactivity and is expected to have longstanding impacts on future applications of these approaches to pharmaceutically relevant transformations.

NIH Research Projects · FY 2025 · 2025-09

Project Summary Social affiliation is critical to the physical and emotional health of a wide variety of species. Disruptions in social functioning - a key feature of conditions like autism, social anxiety, and schizophrenia - can severely limit one's capacity to cultivate healthy social relationships and bonds. The neural circuit mechanisms governing affiliative social behaviors are not well understood, which is an important part of the social processes domain of the Research Domain Criteria (RDoC) and relevant to several psychiatric disorders. Allogrooming (grooming behavior directed toward another individual) is a major form of affiliative social contact through which animals may form, maintain, and strengthen social relationships and is conserved in a wide range of social species, such as birds, bats, rodents, canids, cats, equids, and primates. This project aims to understand the neural mechanisms regulating allogrooming in mice by examining the oxytocin receptor (OXTR) system, a critical modulator within the brain's `social behavior network'. The sponsor has previously identified a pathway from the medial amygdala (MeA) to the medial preoptic area (MPOA) as essential for allogrooming in mice. However, the specific neural encoding of oxytocin-responsive neurons in this circuit remains unknown. I will gain exceptional training in powerful genetic approaches that allow us to target oxytocin receptor cells specifically. The outlined proposal will 1) utilize in vivo optogenetics to manipulate oxytocin-sensitive MeA neurons and their projections to the MPOA and BNST, 2) assess the role of OXTR specifically in the MeA on prosocial behavior, and 3) utilize in vivo freely moving calcium imaging to optically record MeA OXTR neurons during allogrooming behavior. The proposed study will provide an excellent training experience for the applicant, and it will reveal how discrete, anatomically defined pathways descending from the MeA are engaged during allogrooming. These results will set the foundation for a more incisive analysis of how OXTR circuits shape social function in both health and disease.

NIH Research Projects · FY 2025 · 2025-09

New methodologies to construct C–C, C–N, C–O, and other C–heteroatom bonds are crucial for the continued development of new pharmaceutical candidates. Photoredox catalysis has emerged as a powerful field of organic chemistry for this purpose; however, while many organic functional groups are within the oxidation and reduction potentials of the growing library of photocatalysts, several important groups remain inaccessible either due to their redox potentials or chemoselectivity challenges. In-situ phosphoranyl radical generation by photoredox catalysis has emerged as a promising alternative to activate such desirable functional groups. There are two major scission pathways from the phosphoranyl radical: 𝛼- and 𝛽-scisson. The reversibility of phosphoranyl radical 𝛼-scission has precluded its application toward generation of highly desirable oxygen- centered radicals from alcohols. This proposal details the application of phosphoranyl radical 𝛼-scisson on sulfonamide and alcohol substrates able to undergo a rapid intramolecular 1,5-hydrogen atom transfer (HAT) step after the 𝛼-scisson event. In the first aim, the catalytic phosphine/photoredox system will be evaluated with secondary sulfonamide substrates, which were unable to engage in productive reactivity in the previous hydroamination work. Distal functionalization, pyrrolidine synthesis, and distal multifunctionalizations will be accomplished under similar sets of reaction conditions. The second aim focuses on engaging a more challenging class of substrates in phosphoranyl radical 𝛼-scisson: alcohols. Through the use of conformationally-strained phosphetanes and by again coupling 𝛼-scisson to 1,5-HAT, we will activate aliphatic alcohols through phosphine/photoredox catalysis in a net-oxidative reaction to form substituted tetrahydrofurans. This catalyst design will then be applied to the first catalytic in phosphine 𝛽-scisson of alcohols for deoxygenation, a valuable medicinal reaction that has remained inaccessible through phosphoranyl radical scission because it results in P(V). Through redox-cycling the strained phosphetane, complex scaffolds such as steroids and carbohydrates can be deoxygenated under catalytic conditions. In both aims, DFT calculations will be utilized to calculate the potential energy surfaces of the key scission events of the phosphoranyl radical, as well as the 1,5-HAT step and possible back-electron transfer of the heteroatom radical with the photocatalyst. In aim 2, a free-energy relationship between the computed conformational strain of synthesized phosphetanes and the scission events will be established. Development of these strategies provide new applications of photoredox-enabled phosphoranyl radical 𝛼- scisson, allowing access to valuable, medicinally-relevant scaffolds including complex sulfonamides, pyrrolidines, tetrahydrofurans, and deuterated compounds. By understanding the factors that influence the energetics of the key mechanistic steps, this work will enable future reaction development in this area.

NIH Research Projects · FY 2025 · 2025-09

PROJECT SUMMARY While conventionally known as contrast agents for diagnostic ultrasound, gas-encapsulated microbubbles can also be functionalized with targeting antibodies and therapeutic payloads. This unique delivery mechanism allows for improved therapeutic index in difficult-to-reach locations, minimizing the risk for off-target effects. However, the potential of microbubble theranostic agents has not yet been fully realized because of current limitations in conjugating antibodies and therapeutic agents to the microbubble itself. These limitations include difficulties in conjugating the antibodies in the right alignment on the microbubble while preserving microbubble integrity. It is also unclear what the pharmacokinetic characteristics of the theranostic microbubbles will be in a clinically-relevant large animal model. We plan to overcome these limitations using a novel site-specific labeling technique known as Light Activated Site-Specific Conjugation (LASIC) technology. Leveraging LASIC to attach both targeting antibodies and therapeutic payloads will streamline the theranostic microbubble manufacturing process, facilitating its translation into the clinical population. With successful LASIC-optimization of microbubbles, the biodistribution of these microbubbles will be further improved via image-guided catheter delivery. This project will be conducted via 3 aims: 1) Creating targeted microbubbles using LASIC technology: We will test the feasibility of LASIC on commercially available avidin-coated, and then the less immunogenic azido-lipid-based microbubbles. Efficacy of microbubble-cell binding will be evaluated using in vitro assays and ultrasound phantoms. We will then 2) Generate theranostic microbubbles using LASIC to attach therapeutic payloads to the microbubbles. In this aim we will also augment microbubble payload release via non-invasive sonoporation, using in vitro techniques to optimize drug delivery. Lastly, we will 3) validate the safety and pharmacokinetic profile of the LASIC-optimized microbubbles large animal tumor model, also known as the Oncopig. The microbubbles will be delivered via a clinically relevant image-guided catheter, allowing for maximum therapeutic index in the target tumor. The results of this project will have significant implications for the translatability of microbubble platforms for theranostic purposes. By minimizing disruption of the phospholipid shell, LASIC can potentially revolutionize the way microbubbles are currently conjugated. The potential implications of this research extend well beyond the immediate impact of microbubble conjugation chemistry, paving the way for future advancement in theranostic agents, image-guided interventions, and large animal validation modeling.

NIH Research Projects · FY 2025 · 2025-09

Project Summary Genetic association studies have become the de facto standard study design for identifying genetic variants associated with complex traits. Thousands of such studies, enrolling tens of millions of people worldwide, have been conducted to date. Their results have been used for myriad purposes ranging from basic science to clinical translation and including studies of trait genetic architectures. However, recent work from our groups and others have shown that a widely held belief about genetic association study results is frequently incorrect. Specifically, the assumption that underlying the loci associated with the trait of interest are causal variants directly impacting the trait. We and others have established that these associations also contain substantial contributions from confounding factors: gene-environment correlation due to indirect genetic effects (effects of relatives’ genotypes mediated through the environment) and population stratification, as well as correlations with other genetic variants due to assortative mating and population structure. Here we aim to develop methods to quantify and resolve this issue, dissecting these often-overlooked components of intergenerational dynamics when studying trait genetic architectures. In Specific Aim 1, we are set to develop a comprehensive simulation framework. This framework will efficiently model realistic intergenerational dynamics on a large scale, crucial for understanding the nuances of genetic transmission across generations. It will serve to quantify and correct the biases inherent in current methodologies used for studying genetic architecture, providing a more accurate lens through which to view the genetic underpinnings of traits. In Specific Aim 2, we develop a theoretical framework for understanding the joint impact of indirect genetic effects and assortative mating. This then enables us to develop methods that separate these statistically confounded factors that are key to explaining intergenerational transmission of traits. By leveraging the unique properties of family data, we will be able to build an accurate picture of the different factors that contribute to both genetic associations and to intergenerational health and social inequalities. Central to the success of this project is our team of diverse collaborators. Comprising experts from various geographical locations and spanning junior to senior investigators, our team brings together a wealth of experience in this niche area. The multidisciplinary expertise of our faculty members, encompassing genetics, computational biology, psychology, social sciences, and other relevant fields, ensures a comprehensive approach to tackling these complex genetic issues. By addressing the intricate intergenerational dynamics and refining the analysis of genetic architectures, we are not only enhancing the scientific understanding of genetics but also paving the way for more precise and meaningful applications in health and medicine.

NIH Research Projects · FY 2025 · 2025-09

PROJECT SUMMARY/ABSTRACT Social determinants of health (SDOH) exert a powerful influence on the everyday management of type 1 diabetes (T1D) and short and long term outcomes of T1D. Experts agree that identifying and addressing negative SDOH may help accomplish numerous T1D care goals and promote health equity in treatment. However, fundamental research gaps in achieving these goals remain, including optimal screening and management processes for identification of negative SDOH, and how to develop robust partnerships with community-based organizations (CBOs) that address SDOH with high potential for sustainability and scalability. This project will generate new knowledge regarding how to implement a social work-led SDOH screening and referral program designed to aid families of youth with T1D who face several vulnerabilities, including food insecurity. We will implement a single arm, pragmatic clinical trial with contemporaneous, non- randomized controls; whereby all families with a child enrolled in the California Children’s Services (CCS) program (which provides specialized medical care for low-income families of youth with a qualifying chronic medical condition) will receive access to a novel social work-led SDOH screening and referral program. Outcomes will be compared against youth with T1D who are also seen in our Westwood Pediatric Endocrinology clinic but who are not enrolled in the CCS program and will not receive access to the SDOH intervention. We have partnered with several community-based organizations (CBOs) across Los Angeles County who provide social services, including food-related services, to receive referrals for CCS families who screen positive for having a social need. We will assess the feasibility and acceptability of this screening and referral protocol among families, CBOs, and providers (Aim 1) by measuring key implementation outcomes (comprehensive documentation of SDOH screening, result, and referral in the patients’ medical record) and acceptability outcomes (self-reported satisfaction with the program by families and barriers and facilitators by CBOs and providers). We will additionally estimate the effect of this intervention (Aim 2) by measuring changes (pre/post intervention) in families reported social needs, diabetes-related quality of life, and in the child’s glycemic control (measured by HbA1c). Results from this work can provide a roadmap for sustainable and scalable SDOH interventions with potential to improve outcomes for youth with T1D in an equity-informed manner.

NIH Research Projects · FY 2025 · 2025-09

ABSTRACT Our long-term objective is to define mechanism that regulate lipid flux in cells and animals and to elucidate their impact on metabolic disease. Crosstalk with resident immune cells of the lamina propria of the gut has been shown to influence the function of the absorptive epithelium, but molecular mechanisms whereby cellular lipid levels in immune cells regulate this communication are largely undefined. We have discovered that accessible PM cholesterol abundance in gut T cells is a potent modulator of dietary lipid absorption. Our preliminary data show that inactivation of Aster-A induces changes in TH17 cell signaling, including production of the cytokine IL-22, that alter systemic metabolism and energy balance. Here we propose a complementary series of cellular, animal and pharmacological studies to define the underlying molecular mechanisms and physiological implications of this discovery. Specific Aim 1 is to understand the mechanism(s) whereby gut T cells modulate dietary lipid absorption. We will define signaling components that mediate the suppression of fatty acid uptake by IL-22, taking advantage of genetic models, chemical inhibitors and intestinal enteroids. Specific Aim 2 is to elucidate the role of IL-22/IL-22R signaling in intestinal and systemic lipid homeostasis. We will further define the importance of the IL-22/IL-22R axis for whole-body physiology and energy balance. We will utilize a novel AlpiCreER; Il22ra1F/F mouse model to dissect the function of the IL-22/IL-22R axis specifically in mature enterocytes. Specific Aim 3 is to define intrinsic and environmental cues that regulate fatty acid absorption. Diet composition has long been known to impact systemic metabolism. We hypothesize that environmental factors that perturb IL-22/IL-22R axis may serve to modulate intestinal metabolism. We will now examine the effects of dietary AHR ligands such as indole-3-acetate and tryptamine that are produced by gut microflora from ingested tryptophan. To define specific gut immune cell populations responsive to these environmental cues, we will delete IL-22 in T cells or type-3 innate lymphoid cells and characterize their function importance in intestinal metabolic responses including the response to AHR agonists.

NIH Research Projects · FY 2025 · 2025-09

Modified Project Summary/Abstract Section The project will conduct a follow-up study of an NIH-funded randomized control trial (RCT) that made contraception more affordable for U.S. women seeking care at Title X providers--a federal program that has offered subsidized, patient-centered reproductive health services since 1970. From 2018-23, the Michigan Contraceptive Access, Research, and Evaluation Study (M-CARES) randomly assigned vouchers making any method of contraception highly discounted or free and has followed participants for two years in administrative and survey data. The proposed project extends the scope of M-CARES to consider a comprehensive set of health and well-being outcomes measured three to five years after study enrollment. The project's specific aims are to: (1) Link M-CARES participants to administrative records three to five years after enrollment, including (a) birth records, (b) credit reports, (c) IRS tax and Census data, and (d) health care records to be used for research. We have executed data use agreements (DUAs) with relevant agencies, and our preliminary studies project almost universal link rates with these records. (2) Develop and field a year-five follow-up survey (Y5FU), which will focus on information missing or incomplete in administrative records, including (a) contraceptive use; (b) retrospective pregnancy outcomes and desire/intendedness; (c) physical and mental health; (d) relationship stability and quality; (e) education and labor-market outcomes; (f) financial stability; (g) parenting; and (h) overall well-being. (3) Quantify the cumulative causal effects of reducing the costs of contraception on outcomes measured three to five years later, using the trial’s random assignment and outcomes from data in Aims 1 and 2. Achieving these aims will contribute novel and rigorous evidence regarding how the affordability of contraception affects a comprehensive set of health and well-being outcomes at three to five years. The combination of administrative and survey data maximizes the information collected per dollar spent and minimizes attrition and measurement error. Achieving this study's aims would provide a more complete cost-benefit accounting of public programs subsidizing contraceptives, such as Title X and Medicaid.

NIH Research Projects · FY 2025 · 2025-09

PROJECT SUMMARY Proteases, particularly matrix metalloproteinases (MMPs), are pivotal in the malignant progression of solid tumors, mediating invasion, migration, and metastasis via remodeling of extracellular matrix (ECM). Recent studies have shifted focus from the abundance of MMPs to their functional roles, especially in profiling proteolytic activities. However, detecting MMP activities within tumor tissue pose challenges, necessitating complicated procedures involving invasive acquisition of tumor tissues and labor-intensive purification of MMPs. This is especially more challenging for bone cancer tissues, as bone tissue biopsies typically undergo decalcification, which can severely damage the proteins in the tissue. Tumor extracellular vesicles (EVs) transport MMPs from tumor cells while preserving their functional activities, making them ideal surrogates for the parent tumor tissue for noninvasive profiling of MMP activities. Osteosarcoma (OS), the most common pediatric bone cancer is in pressing need of a quantitative liquid biopsy assay for assessing treatment responses for both localized OS and metastatic OS. Therefore, assessing OS EV MMP activities holds significant promise to serve as a liquid biopsy assay that can supplement radiographic imaging for assessment of treatment responses. Over the past decade, our UCLA team has pioneered click chemistry-mediated tumor EV enrichment technologies, i.e., Click Beads and Click Chips, enabling diverse downstream molecular analyses, such as mRNA profiling and protein quantification. Recently, we demonstrated the feasibility of coupling functional analysis, i.e., MMP activity assay using the enriched tumor EVs, offering a strong potential to deepen our understanding of MMPs’ pathological roles and to develop new cancer diagnostic solutions. The long-term goal of this TTNCI R01 proposal is to further refine, validate, and translate a streamlined OS EV MMP Activity Assay for monitoring treatment responses in OS patients who receive treatment interventions, e.g., a combination of neoadjuvant chemotherapy, surgery, and adjuvant chemotherapy. This two-step assay involves: i) click chemistry-mediated enrichment of subpopulations of OS EVs using EV Click MagBeads, in the presence of trans-cyclooctene-grafted antibodies targeting the respective OS EV surface markers, and ii) FRET peptide probes for assessing the activities of OS- associated MMPs in the enriched OS EVs. The innovation of this proposal lies in i) innovative use of nanotechnology-enabled OS EV MMP Activity Assay to address an unmet clinical need in noninvasive assessment of treatment responses in an aggressive pediatric tumor, and ii) a rigorously developed design of experiments (DOE) plan to identify optimal parameters for the assay. The successful development of the proposed OS EV MMP Activity Assay is expected to achieve translational readiness for eventual GLP manufacturing and a Phase-2 biomarker study.

NIH Research Projects · FY 2025 · 2025-08

ABSTRACT Nutrient availability affects many cellular processes that are important for health and disease, including metabolic diseases such as diabetes, obesity, fatty liver and cardiovascular disease. The liver is the central hub of metabolism and is intricately involved in coordinating and maintaining metabolic health. The liver coordinates systemic metabolism is via secreted peptides, or hepatokines, which enter the circulation and can trigger responses in a number of distal tissues. There are well established transcriptional mechanisms that control hepatokine production, such as the PPAR-dependent transcriptional regulation of FGF21, a hepatokine that controls energy balance. Here we describe a novel mechanism by which the liver controls maintains homeostasis in the fasted state, via post-transcriptional control of mRNA stability by a family of RNA binding proteins (RBPs). Using global unbiased RNA-Seq analysis, we have identified a key hepatokine as a specific target of the RBP family. We then show that hepatic loss of these RBPs results in pronounced increases in the levels of mRNA as well as increased circulating levels of the hepatokine. We have generated extensive metabolic analysis showing that loss of all three members of the RBP family in the liver dramatically impacts body weight and energy balance. We also generated an inducible knockout mouse model where the RBPs and the hepatokine are deleted in hepatocytes, demonstrating that the hepatokine plays a significant role in the metabolic regulation of the RBPs. In Specific Aim 1, we will test the hypothesis that the RBPs regulate the hepatokine in the context of fasting, where they limit the surge in expression for the hepatokine in the fasted state. Then, using a complementary gain-of-function model for one of the redundant RBPs, we will use an inducible RBP overexpression model to identify direct RBP targets in the liver. In Specific Aim 2, we have identified a second hepatokine that is also regulated by our family of RBPs. We will determine the relative contribution of this hepatokine to the systemic changes in metabolism we observe following liver-specific loss of RBPs. Lastly, we have identified human variants in the 3’UTRs of both hepatokines, and will test whether these variants affect mRNA stability and contribute to human GWA loci for metabolic traits. Our studies will provide a novel layer of control for hepatokines and aid our understanding for how the liver regulates systemic metabolism, which may open up novel therapeutic avenues to modulate and treat metabolic disease.

NIH Research Projects · FY 2025 · 2025-08

PROJECT SUMMARY/ABSTRACT There has been a dramatic resurgence in the number of congenital syphilis cases globally, including a very steep rise in the number of cases in the U.S. In Brazil, congenital syphilis is an extremely serious health problem despite numerous campaigns aimed at targeting eradication of syphilis during pregnancy. In the last 10 years, the number of cases of syphilis in pregnancy in Rio de Janeiro has skyrocketed, with 1 to 2 of every 10 pregnant patients who receive prenatal care in disenfranchised areas of the city testing positive for syphilis. This is 2 logs higher than the already dramatic number of cases observed in the U.S. Rio de Janeiro currently has the highest number of syphilis pregnancy cases in the country. Our group of researchers has a longstanding collaboration in the field of infectious diseases, particularly vertical transmission of infections, which spans 3 decades, with landmark clinical trials conducted such as NICHD HPTN 040 for prevention of intrapartum transmission of HIV. The site in Brazil is a seasoned NICHD site with participation in many NIH-sponsored network studies since 1999, while the UCLA PI is a licensed physician in both the U.S. and Brazil, and a native of Rio de Janeiro. We propose to conduct a randomized clinical trial for prevention of maternal syphilis during pregnancy, utilizing the existing local health infrastructure and scientific methods developed in our prior studies, with the support of the Brazilian Ministry of Health and local health departments which welcome this partnership given the urgent need to address the ongoing syphilis crisis. The main goal of the proposed research is to prevent the development of syphilis in pregnancy and congenital syphilis through enhanced serologic screening for syphilis during prenatal care with point of care treponemal testing at 6, 7 and 8 months of pregnancy and monthly shots of benzathine penicillin as syphilis prophylaxis to negative participants in the intervention arm as compared to standard of care in pregnant patients randomized to the control arm (point of care testing three times during pregnancy). The study will assess the number of patients screening positive for syphilis and the number of infants requiring treatment for congenital syphilis in a study population comprised of 500 pregnant participants. Patients identified with syphilis will be managed according to Brazilian standard of care guidelines which mirror CDC recommendations. The study will assess tolerability, acceptability, and safety of benzathine penicillin while evaluating maternal/ obstetrical and infant health parameters during pregnancy and at the time of birth. The data rendered will be crucial for development of prevention efforts to curtail the syphilis epidemic.

NIH Research Projects · FY 2025 · 2025-08

This proposed rapid R21 study will take place in the South Bay region of Los Angeles, where operators recently announced plans to retire two petroleum refineries at the end of 2025. Refineries are among the largest stationary sources of hazardous air pollutants in the country and tend to be located in low-income communities and urban centers near highways and other industrial facilities, where they contribute to cumulative air pollution bur dens. Many components of refinery emissions including volatile organic compounds (VOCs), polycyclic aromatic hydrocarbons (PAHs), and sulfur dioxide (SO2) are known respiratory irritants. Several studies have shown living near refineries is associated with poorer respiratory health including declines in lung function, increased bronchial inflammation and asthma exacerbations, but prior work has primarily been cross-sectional in nature, limiting causal inference. The objective of the Community Health and Air Quality Implications of Refinery Retirements in Los Angeles (CHAIRS-LA) study is to take advantage of the unique time sensitivity opportunity (‘natural experiment’) afforded by the refineries’ closure and accompanying abrupt change in air pollutant emissions to determine whether the retirement of two petroleum refineries amid an urban community results in changes in exposure to air pollutants and respiratory health. This project is in response to the concerns of community-based organizations and builds upon longstanding partnerships between the research team and community partners. N=150 adult community residents will be enrolled for a longitudinal study with measurements taken at three time points: prior to refinery closure (this proposal), and one and two years later (future work). Participants will provide information on acute respiratory, dermal, gastrointestinal, and neurological symptoms via questionnaire, lung function will be measured via spirometry, and airway inflammation via a non-invasive fractional exhaled nitric oxide (FeNO) biomarker test. Participants will wear a personal passive sampler (Fresh Air wristband) for seven consecutive days to measure personal exposures to VOCs and PAHs including acetaldehyde, 1,3-butadiene, formaldehyde, naphthalene, and BTEX compounds (benzene, toluene, ethylbenzene and xylene). Passive samplers will also be installed outside homes for a subset of N=30 participants. The quasi-experimental design will allow us to compare changes in these measures before and after the refinery closure, which eliminates confounding by both observed and unobserved time-invariant factors. Results will enable future work to collect post-closure measurements in order to identify the effect of the refineries’ retirement on health among neighboring residents. Outcomes will include new knowledge about the impacts of petroleum refinery retirements on exposure to ambient air pollutants and respiratory health collected through participatory research.

NIH Research Projects · FY 2025 · 2025-08

PROJECT SUMMARY/ABSTRACT Human Papillomavirus (HPV) is the major cause of head and neck squamous cell carcinomas; most oropharyngeal (75%) and other head and neck cancers are caused by chronic HPV infection. Metastatic HPV- associated cancers are minimally responsive to current treatments and uniformly fatal. The most recent American Cancer Society annual statistics for oral/oropharyngeal cancers in the U.S. indicate 54,540 new diagnoses and 11,540 deaths. Novel therapies are therefore sorely needed. HPV-associated cancer cells require direct dysregulation of cells through viral E6 and E7 oncoproteins, which are indispensable for tumorigenesis. These proteins are essential for ongoing tumor cell survival, and therefore serve as ideal therapeutic targets. Knockdown of E6 or E7 using siRNA in HPV-transformed cells results in apoptosis. This pilot R21 project describes plans to screen for druggable small molecule antagonists of HPV E6 or E7 oncoproteins. The overall strategy will be to screen small molecule libraries for compounds that cause specific death of tongue cancer squamous cell lines with HPV, but not those without HPV: o Aim 1: To create tongue carcinoma cell clones differing in HPV status and fluorescence color. o Aim 2: To screen small molecule libraries for drug candidates causing HPV-specific cell death. o Aim 3: To test the function of drug candidates to induce death of other HPV-transformed cells. Successful completion of this project would identify drug candidates that induce apoptosis of HPV-transformed oral cancer cells through interference with E6 or E7.