University Of Florida

NIH Research Projects · FY 2025 · 2024-01

PROJECT SUMMARY The development and function of hair cell stereocilia in the cochlea are essential for our sense of hearing, as they play a pivotal role in detecting sound through their mechanosensory capabilities. Stereocilia, organized into rows of graded height on the hair cell surface, are susceptible to damage caused by loud sounds and the aging process, leading to irreversible hearing loss. The architecture of stereocilia is critical for detecting sound and is regulated by a structural protein called actin that forms a rigid scaffold of filaments within these structures. My overarching goal is to understand the regulatory mechanisms that govern actin filament growth and ensure the correct development of stereocilia. In this proposal, I explore the function of the molecular motor protein myosin 15 (MYO15A) that controls actin filament assembly and stereocilia size. Mutations in MYO15A cause human hereditary hearing loss, DFNB3, underlying the essential activity of this protein in the cochlea. The central focus of my proposal is to discover how MYO15A and its associated proteins, known as the 'elongation complex' (EC), can control actin polymerization and stimulate stereocilia growth. My preliminary data along with the published work of others, have revealed a unique ability of MYO15A and EC proteins to form biomolecular condensate that are hypothesized to form the stereocilia tip density that controls actin filament elongation. The properties of these MYO15A-EC condensates are poorly understood, but highly relevant to stereocilia biology. In this proposal, I will conduct a comprehensive characterization of the biophysical properties of MYO15A-EC tip density condensates and explore their potential as reaction compartments optimized for actin filament growth. In Aim 1, I will measure the material properties and microrheology of purified MYO15A-EC tip density condensates, revealing their structural makeup. In Aim 2, I will test the hypothesis that MYO15A-EC tip-density condensates can potentiate actin filament growth. This work will utilize cutting-edge experimental approaches including optical trapping force spectroscopy and single-molecule microscopy techniques. The results from these experiments will reveal the fundamental properties of MYO15A-EC tip density condensates and advance our understanding of how stereocilia are built and maintained. Completion of this project will advance my long-term goal of manipulating stereocilia biology therapeutically to treat hearing loss in patients.

NIH Research Projects · FY 2023 · 2024-01

ABSTRACT Nociceptive pain is a protective response to harmful stimuli that is necessary to survival while nociplastic pain represents altered nociception arising from a sensitization of peripheral nociceptor neurons leading to subthreshold inputs eliciting a pain response. While studying a potential role for SARS-CoV-2 spike ^protein in pain, we identified Neuropilin 1 (NRP1) as a key receptor mediating the transduction of vascular endothelial growth factor-A (VEGFA) signaling to sensitize sensory neurons in models of nociplastic pain. In models of nerve injury pain, vascular endothelial growth factor-A (VEGFA) – an angiogenic factor – binds NRP1 and induces mechanical allodynia and thermal hyperalgesia. Pharmacological antagonism of NRP1 blocked VEGFA induced pain-like behaviors. This work demonstrated that NRP1 could be a novel therapeutic target with the potential to reverse chronic pain. Mechanistically, NRP1 sits upstream of a cytosolic protein – the collapsin response mediator protein 2 (CRMP2), a dual trafficking regulator of N-type voltage-gated calcium (CaV2.2) as well as voltage-gated sodium channels. We hypothesized that activation of the VEGFA/NRP1/CRMP2/ion channel pathway elicits sensitization of dorsal horn neurons, consequently contributing to neuropathic pain states by enhancing excitatory synaptic input to dorsal spinal cord neurons. In this proposal, we test the hypothesis that interfering with VEGFA binding to NRP1 initiates an intracellular signaling cascade that, through CRMP2, leads to a decrease in sodium and calcium channel functional activity to decrease nociceptor activity culminating in reduced pain-like behaviors. We plan to test our hypothesis by using two chronic pain models to answer the following questions: 1. Does NRP1 signaling induce nociceptor sensitization and chronic hypersensitivity via CRMP2? 2. How does NRP1 signaling affect acute and chronic pain? 3. Are the behavioral effects of NRP1 mediated by neurons or microglia in the DRG? Completion of the proposed studies will allow: (i) validation of a novel target of chronic pain, (ii) use two chronic pain models to explore the breadth of applicability, and (iii) provide important information for development of a next generation of mechanism-based chronic pain medications. Overall, completion of these experiments will validate the role of NRP1 in nociceptive processing and will open opportunities for future therapeutic targeting of NRP1 for chronic pain treatment.

NIH Research Projects · FY 2025 · 2024-01

PROJECT SUMMARY Lung cancer is a leading cause of cancer death in the United States, with non-small cell lung cancer (NSCLC) being the major subtype accounting for approximately 85% of cases. Effective treatments for NSCLC are currently lacking due to the complexity of its molecular subtypes and the incomplete understanding of its underlying mechanisms. RNA N6-methyladenosine (m6A) modification is increasingly recognized as being deregulated in human cancers, however, specific m6A events in NSCLC are yet to be identified. We found elevated m6A modification on 7SK small nuclear RNA in NSCLC cells and a NSCLC mouse model. Targeted reduction of m6A-7SK inhibits NSCLC cell growth in soft agar colony formation assays. 7SK regulates RNA Polymerase II (Pol II) transcription and is a central player in controlling Pol II transcriptional pausing and elongation. Therefore, m6A modification of 7SK may underlie NSCLC formation and phenotype. The goal of this study is to dissect the molecular pathways that regulate m6A-7SK and decipher the mechanisms by which m6A-7SK affects gene regulatory networks in NSCLC. The first aim is to identify the m6A sites using real-time PCR-based m6A detection assay, and to identify writer and eraser enzymes of 7SK by short hairpin RNA knockdown. The second aim is to determine how m6A-7SK influences gene expression and NSCLC formation. CRISPR dCasRx-ALKBH5 fusion protein will be used to modulate m6A-7SK in NSCLC cells, and cell proliferation and migration assays will be employed. To determine the molecular details of m6A-7SK-mediated gene regulation, SHAPE-MaP sequencing will probe the structure of m6A-7SK; nascent RNA-seq, ChIP-seq of Pol II, and ChIRP-seq of 7SK will be performed to survey transcriptional program in NSCLC cells with different levels of m6A-7SK. The results of this study will reveal novel molecular details of m6A modifications on 7SK and how they regulate cancer gene expression. This information will provide the basis for future research to develop novel NSCLC therapeutics by altering RNA m6A levels.

NIH Research Projects · FY 2025 · 2024-01

PROJECT SUMMARY/ABSTRACT Cognitive deficit is prevalent in people living with HIV. Mounting evidence has implicated systemic inflammation and neuroinflammation in cognitive deficit via HIV-specific mechanisms; however, the cognitive effects of longitudinal change in inflammation are poorly understood. Preliminary findings from a non-intervention cohort of adults living with HIV show unexplained cognitive decline across domains over a 2-year period. I hypothesize that this cognitive decline is associated with an increase in systemic inflammation in people living with HIV. Thus, to address Aim 1, I will conduct a secondary analysis examining blood plasma IL-6, CRP, sCD14, and sCD163 as predictors of NIH Toolbox Cognitive Battery change in this cohort. This aim will provide valuable information on the longitudinal relationship between inflammation and cognition in the absence of intervention, which may be used as a comparison point for interventional research. Critically, interventions to reduce systemic inflammation in people living with HIV are in their infancy. Heavy alcohol use is prevalent among people living with HIV. Alcohol use exacerbates systemic inflammation and may contribute to increased neuroinflammation, operationalized as disruptions in brain myo-inositol and choline, in people living with HIV; relatedly, alcohol use is associated with increased cognitive deficit in people living with HIV. Alcohol reduction is known to partially remediate brain myo-inositol and choline disruptions and cognitive deficit in seronegative populations. However, the added physiological burden of HIV may reduce the beneficial impact of alcohol reduction. Having described inflammatory and cognitive change in the absence of intervention, I will turn to secondary analyses of an interventional study of alcohol reduction to assess its effectiveness in remediating alcohol-related cognitive deficit in this population. I hypothesize that alcohol reduction will associate longitudinally with reduced magnetic resonance spectroscopy (MRS) markers of neuroinflammation and that reduced neuroinflammation will associate longitudinally with improved cognition in people living with HIV. In Aim 2, I will examine Timeline Follow-Back drinks/month before and after intervention and HIV serostatus as predictors of brain MRS myo-inositol, choline, and N-acetylaspartate over 4 time points. In Aim 3, I will assess change in brain MRS myo-inositol, choline, and N-acetylaspartate in relation to NIH Toolbox Cognitive Battery change over 4 time points. This project, building on the baseline established by Aim 1, will provide critical insight into the effectiveness of alcohol reduction as an intervention in this vulnerable population.

NIH Research Projects · FY 2025 · 2024-01

Project Summary/Abstract Recent initiatives from the National Institute on Alcohol Abuse and Alcoholism have focused on the prevention of child and adolescent alcohol use. To address this, the proposed project focuses on identifying salient, prospective predictors and inferred causes of early alcohol initiation (EAI) or the consumption of a full drink containing alcohol before the age of 16. The aims of the proposed project will test current assumptions of predictors of alcohol initiation (Aim 1a), compare a priori risk factors with novel, data-driven risk factors (Aim 1b), infer causal relationships between factors and EAI (Aim 2), and, as an exploratory aim, isolate individual measures as predictors using machine learning techniques (Aim 3). To accomplish these aims, we will be leveraging the Adolescent Brain Cognitive Development (ABCD) study consisting of over 11,000 youth participants. ABCD provides multiple time points of neuroimaging, neurocognitive, and environmental measures starting when youth are 9-to-10-years-old allowing for the incorporation of high-dimensional data into a single framework. Thus, the resulting sample provides a unique opportunity to use advanced quantitative methods including structural equation modeling, exploratory factor analysis, and random forest machine learning to highlight what drives youth to initiate alcohol use during this risky developmental period. The outcomes of this project aim to inform research on prevention and intervention of EAI to ultimately delay alcohol initiation to more developmentally appropriate ages.

NSF Awards · FY 2024 · 2024-01

This project aims to serve the national interest by understanding how critical thinking and empathetic science, technology, engineering, and mathematics (STEM) professionals can be developed through a humanities-driven curricular and problem-solving approach. The need for empathetic and critical thinking skills for STEM professionals is becoming readily evident due to the increased complexities of our society. Continued globalization through technologies means that the work of scientists and engineers has a greater impact on how we interact and communicate than ever before and presents a new set of grand challenges for our society. Traditionally, the humanities have played little to no role in STEM education even though critical thinking and empathy skills are hallmarks of a humanities education. There are, however, natural links that may enrich STEM students' educational experience and better prepare them to meet these grand challenges. This project will present science and engineering problem-solving within a humanities setting, an approach called humanities-driven STEM (HDSTEM). This approach will engage an interdisciplinary collaboration between humanities and engineering situated at two universities, Texas Tech University (TTU) and Rochester Institute of Technology (RIT). With this collaboration, students will develop problem-solving skills that require them to empathize and think critically. Through the NSF IUSE:EHR Engaged Student Learning track, this work will meet the program's goal to seek transformative approaches to generating and using new knowledge about STEM teaching and learning to improve STEM education for undergraduate students. This project will examine the effectiveness of two problem-solving assignments: typical problem-solving and empathy-embedded problem-solving within two-course designs: a HDSTEM design with team-taught Humanities and STEM faculty, and instruction by STEM faculty in an introductory engineering curriculum. Curriculum treatments will be compared across two universities, TTU and RIT. While considering different faculty and instructors for this curriculum at the two institutions, the curriculum will be tied together through shared typical and empathy-embedded problem-solving assignments. The purpose of these treatments is to deepen STEM students' ability to empathize and think critically. At the same time, the project will examine which of the two implementation processes (i.e., HDSTEM curriculum and introductory engineering curriculum) performs better. This study will use a mixed-methods approach to analyze data and results. Multiple sources of data will be collected, analyzed, and compared for triangulation. Comparisons will be made between the data collected at the beginning and end of the courses. Discourse and content analysis in conjunction with commonly used rubrics for critical thinking and empathy will measure and assess differences from the curriculum treatments. Results will show benefits in critical thinking and empathy from the HDSTEM environment. The NSF IUSE: EHR Program supports research and development projects to improve the effectiveness of STEM education for all students. Through the Engaged Student Learning track, the program supports the creation, exploration, and implementation of promising practices and tools. 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 · 2024-01

PROJECT SUMMARY/ABSTRACT Chronic limb threatening ischemia (CLTI) is the most severe manifestation of peripheral artery disease (PAD) and is characterized by the presence of ischemic rest pain, with or without gangrene, and often requires limb amputation. Analysis of CLTI patient muscle specimens has identified fatty fibrosis, the replacement of muscle with intramuscular fat and fibrotic scar tissue, as a prominent feature. Recent evidence points to ciliary Hedgehog signaling as a potent anti-adipogenic signal that suppresses the differentiation of fibro-adipogenic progenitors (FAPs), the cellular origin of fatty fibrosis, into adipocytes. Using pre-clinical rodent studies and translational experiments in patient tissues and cells, we have uncovered mis-regulated Hedgehog signaling within the CLTI limb. Preliminary experiments indicate that genetically or pharmacologically altering the Hedgehog pathway in the ischemic limb modulates fatty fibrosis, perfusion recovery/angiogenesis, and muscle function – indicating therapeutic potential of this pathway. This proposal will use innovative and powerful mouse models involving cell-specific gain- and loss-of-function approaches to identify and define the cellular and molecular mechanisms by which intramuscular fat forms within the CLTI microenvironment, and the functional consequences of intramuscular fat and fibrosis on CLTI limb hemodynamics and function. Success in these studies will provide mechanistic insight into the impact of fatty fibrosis on PAD/CLTI pathobiology, and would aide in the search for novel targets for therapeutic development aimed to treat a patient population that currently has few available options.

NIH Research Projects · FY 2026 · 2024-01

SUMMARY/ABSTRACT There are currently more than 280 genes in which defects are known to cause retinal degeneration. Thus, there is a critical need to develop broad spectrum approaches to treating these diseases. The hypothesis of this proposal is that if we can selectively increase glycolysis in rod and cone photoreceptors, then this increase in metabolic potential should slow retinal degeneration across a broad spectrum of etiologies. Our findings strongly support the idea that we can specifically modify arrestin1 such that the catalytic rate of enolase1 in glycolysis is selectively increased in rods and cones. Significantly, this increase in glycolysis slows the loss of photoreceptors and improves photoreceptor function in at least one animal model of retinal degeneration. Accordingly, the specific aims of this proposal are to determine the mechanistic properties of ArrGG’s effect, examining metabolites and gene expression profiles of treated animals (Aim1). We will then establish ArrGG as a gene-agnostic approach to slowing retinal degeneration, testing the therapeutic benefit of ArrGG in diverse models of inherited retinal degeneration (Aim 2).

NIH Research Projects · FY 2026 · 2023-12

PROJECT SUMMARY Hypertension (HTN) is the most prevalent modifiable risk for cardiovascular disease (CVD) and disorders directly influencing CVD (i.e., diabetes, chronic kidney disease, obstructive sleep apnea, etc.). Despite lifestyle changes and drug therapy advances, ~20-30% of patients with treated HTN are “resistant” to (require ≥3) antihypertensive drugs. TRH is generally thought to originate through volume overload and autonomic nervous system (ANS) dysfunction that impairs immune function and inflammatory response. However, few treatment options are available for patients with TRH and promising procedures (e.g., renal artery sympathetic denervation) remain inaccessible to most. Thus, a mechanism-based breakthrough is imperative to foster development of novel medical-based strategies to better control blood pressure (BP) and potentially cure and/or prevent TRH. Our prior funding period provides strong evidence for an altered gut microbiota-gut leakiness- neuroinflammation interaction hypothesis in which gut dysbiosis and gut leakiness, combined with neuroinflammation, perpetuate neurogenic HTN and contribute to TRH and possibly to racial disparities in TRH. We also showed that minocycline, an antibiotic with anti-inflammatory properties, appears to reduce BP in animal HTN models as well as among patients with TRH. In this renewal application, we propose to elucidate mechanisms that underlie the effects of minocycline on BP-lowering in White and African American individuals with TRH. Our overarching objective is to test the hypothesis that minocycline rebalances gut dysbiosis, namely by increasing butyrate-producing functional capacity, attenuating gut-mediated inflammatory response and gut leakiness, and that these effects explain BP-lowering effects in TRH. Four specific aims are proposed to support/refute this altered gut microbiota-gut leakiness- neuroinflammation interaction hypothesis in TRH: Aim 1 will investigate the hypothesis that minocycline alters gut microbiota (primarily butyrate-producing capacity) that mediates minocycline-induced BP lowering in TRH. Aim 2 will assess the extent to which minocycline alters gut-associated inflammation and gut leakiness, and their response with BP changes after minocycline treatment. Aim 3 will evaluate the hypothesis that minocycline reduces neuroinflammation in TRH. Aim 4 will evaluate the hypothesis that these effects of minocycline differ in White versus African American individuals. Together, these studies will elucidate ANS-based mechanisms of host-microbiota interactions in TRH, evaluate potential of minocycline to reduce TRH, and serve as proof of concept for other therapeutic options that rebalance microbiota or mitigate TRH-associated inflammation, to improve BP control in patients with TRH, who remain at high risk.

NIH Research Projects · FY 2025 · 2023-12

Project Summary/Abstract Niemann-Pick disease type C1 (NPC1 disease) is a hereditary disorder characterized by the lysosomal storage of cholesterol and sphingolipids, and clinical signs of progressive cerebellar ataxia, dementia, vertical supranuclear gaze palsy, dysphagia, and early death. There are no FDA-approved therapies for NPC1 disease. Repeated intracisterna magna (IC) administration of 2-hydroxypropyl-beta-cyclodextrin (HPßCD) in cats with NPC1 disease prevented the onset of cerebellar ataxia, prevented Purkinje cell death, normalized cerebellocortical and cerebrocortical cholesterol and gangliosides concentrations, and increased survival time. These preclinical data advanced IC HPßCD into clinical trials where efficacy has been demonstrated. However, HPßCD must be administered IC every two weeks for the duration of the patient’s life and results in progressive dose-limiting ototoxicity, highlighting a clear need for less invasive and safer therapies for these patients. We hypothesize that optimization of IC gene therapy using an AAV9 vector to deliver NPC1 to the brain will effectively prevent NPC1 disease-associated cerebellar ataxia and Purkinje cell pathology without repeated lifelong injections and without ototoxicity. We also hypothesize that intracarotid (IV) administration of a novel AAV serotype to cats can deliver NPC1 to the basal ganglia and brainstem, regions which are untreated by IC administration of HPßCD or AAV9, and are responsible for dystonia, vertical supranuclear gaze palsy, and dysphagia. Therefore, in the proposed studies we will assess methods to optimize AAV9-mediated transduction of the greatest number of Purkinje cells (Aim 1), evaluate the efficacy of AAV9-NPC1 administration to treat clinical, biochemical, and histologic aspects of NPC1-associated cerebellar disease (Aim 2), and evaluate the efficacy of intracarotid AAV-NPC1 administration to treat extracerebellar regions responsible for dementia (cerebral cortex), dystonia (basal ganglia), and vertical supranuclear gaze palsy and dysphagia (brainstem) (Aim 3). These proof-of-concept studies will be the first to optimize the delivery of a non-diffusible membrane-bound protein to Purkinje cells, thereby advancing gene therapy for many other genetic diseases affecting Purkinje cells including spinocerebellar ataxias. Moreover, these studies will be the first to develop a one-time therapy for NPC1 disease that treats both cerebellar and extracerebellar disease and results in no ototoxicity.

NIH Research Projects · FY 2026 · 2023-12

PROJECT SUMMARY Essential voice tremor (EVT) affects over 40% of individuals with essential tremor (ET), one of the most common movement disorders. While ET is characterized primarily by upper limb tremor, EVT is a significant problem because it profoundly disturbs communication and quality of life. Unfortunately, EVT remains poorly treated and the few available treatments, such as propranolol and botulinum toxin injections, have limited efficacy. Deep brain stimulation (DBS) of the ventral intermedius nucleus (VIM) of the thalamus is the treatment of choice for severe upper limb tremor no longer responding to medication. There is evidence that patients undergoing successful DBS therapy for upper limb tremor, can also exhibit some suppression of voice tremor. However, the effectiveness of DBS remains unclear because the few available supportive studies used perceptual ratings or acoustic analysis with a limited number of subjects. EVT suppression with DBS is likely as few case studies show that the placement of a DBS lead in specific thalamic locations could affect both hand and head regions and consequently suppress EVT and upper limb tremor. To establish VIM DBS as a treatment for EVT, there is a critical need to determine the optimal thalamic location for neurostimulation that will mediate upper limb and voice tremor suppression. This requires precise quantification of voice tremor changes in a large and well- established cohort. Here, our multidisciplinary group, proposes to address the current knowledge gaps and determine how VIM DBS leads to effective EVT suppression. We propose to leverage our ability to recruit 140 ET patients undergoing thalamic DBS for upper limb tremor suppression. We expect that 56 of these patients will exhibit EVT and will be matched to ET patients that do not exhibit EVT (ETNVT).We will test the central hypothesis that neurostimulation applied onto specific thalamic neurocircuitry will suppress EVT and limb tremor. In Aim 1, we will use sensitive acoustic analyses to precisely quantify the effectiveness of DBS on EVT. We will test the hypothesis (H1) that bilateral thalamic DBS will significantly suppress voice tremor in patients with EVT, reducing voice tremor to the ETNVT level. In Aim 2, based on our strong preliminary data, we propose to examine the association between voice tremor and axial tremor/fall risk. We will test the hypothesis (H2) that DBS-induced voice tremor suppression will be associated with reduced axial tremor and reduced fall risk. In Aim 3, we will use cutting-edge neuroimaging techniques to determine the effect of the volume of tissue activated (VTA) locations and related neurocircuitry on EVT suppression. This proposition is based on our preliminary data that stimulation of the non-decussating dentato-rubral-thalamo-tract (nDRTT) associated with reduced EVT. We will test the hypotheses that neurostimulation of the nDRTT will suppress EVT (H3.a) and EVT suppression will be greater when the VTAs are located in medial thalamic areas that affect both the hand and head (H3b). The outcomes will be clinically impactful and improve current treatment of ET as they will identify thalamic targets that optimize EVT suppression and determine if this EVT suppression is a marker for reduced fall risk in ET.

NIH Research Projects · FY 2026 · 2023-12

AAV-mediated gene replacement is a powerful approach to treat genetically defined disease. It is often believed that there is a straightforward path to the clinic once gene replacement efficacy is shown in preclinical models. However, major obstacles limit safe and effective gene therapy for many diseases, particularly in systemically delivered contexts. Some diseases are not yet tractable because therapeutic gene expression in one tissue might be toxic in another, or because the therapeutic window of cargo expression is too narrow to safely administer. Toxicity in liver and dorsal root ganglia have been observed in several gene therapies, regardless of capsid or cargo. More versatile, fined-tuned, and self-regulated gene expression cassettes are required for safer and more effective gene therapies. Many approaches exist to regulate gene therapy cargoes, including synthetic promoters and tissue-specific microRNA binding sites. However, despite the ubiquity of RNA processing in the genome, few efforts have incorporated alternative splicing into gene therapies. In Aim 1, we will leverage tissue- specific splicing patterns to generate cargoes facilitating expression in certain tissues but not others. In a first example, we will use develop methods to restrict cargo expression to skeletal muscle and de-target the heart. We have already incorporated muscle-specific exons not expressed in heart into AAV and tested their activity in vivo; we will further optimize these cassettes by testing hundreds of splice site and cis-element motif variations. In a second example, we will identify and test exons that de-target liver and dorsal root ganglion but preserve expression in muscle, heart and/or central nervous system tissues. We will individually validate “winner” cassettes for both examples. We term this approach Tissue-specific Alternative splicing to Restrict Globally Expressed Therapeutic-AAV (TARGET-AAV). In Aim 2, we will re-purpose naturally occurring auto-regulatory cassettes to design and test gene therapies that can sense and regulate their own expression levels. We will use RNA binding proteins mutated in motor neuron disease as test cases, given that RNA binding proteins are well established to regulate their own expression. We will incorporate intronic miRNAs knocking down the corresponding endogenous proteins in the same cassette as an auto-regulated, healthy version of the same RNA binding protein. Similar to Aim 1, we will optimize auto-regulatory behavior by making alterations to intronic and exonic sequences. We will establish proof-of-concept for this approach in cell culture and in iPSC-based models of these disease. We call this approach Biologically Regulated Interchangeable Tuneable Elements (BRITE). Completion of this work will provide guiding principles for the field of gene therapy to incorporate alternative splicing into gene therapy cargoes.

NIH Research Projects · FY 2026 · 2023-12

PROJECT SUMMARY Invasive aspergillosis is one of the most common fungal infections in immunocompromised patients. With the increasing number of susceptible patients and the threat of antifungal-resistance, the development of host- centric interventions is of paramount importance. Complement, a potent component of the innate immune system, is protective against many infections. On the other hand, complement overactivation has been shown to drive lung injury and inflammation. Pulmonary hemorrhage is a characteristic feature of invasive aspergillosis, and the interactions between pulmonary hemorrhage and complement activation are poorly understood. Intervening in the interactions between hemorrhage and complement may prove beneficial as a novel therapeutic intervention to manage pulmonary aspergillosis, and a number of complement inhibitors are either FDA- approved or in late-phase development. The overarching hypothesis in this project is that pulmonary hemorrhage in invasive aspergillosis leads to complement overactivation, leading to tissue injury and further hemorrhage. The dynamics of complement activation are complex and span multiple sites, making it difficult to predict how and when to intervene. We propose that mathematical modeling-based design of effective therapies in pulmonary aspergillosis can help in the discovery phase of understanding mechanisms of complement-mediated injury in pulmonary aspergillosis, and possible interventions of such mechanisms. As such we will leverage the power of mathematical modeling, closely coupled with in vivo models of pulmonary aspergillosis, to unravel the interactions of hemorrhage and complement in the lung and to systematically interrogate the model to determine possible points of intervention. In Aim 1, we will mechanistically explore the effects of the terminal component of the complement cascade in pulmonary aspergillosis. In Aim 2, we will build a multiscale mathematical model of pulmonary aspergillosis to capture the mechanisms that connect hemorrhage and complement activity, validating these mechanisms in vivo. We will then use the model to derive a prioritized set of interventions that will be validated in mouse models of pulmonary aspergillosis. This research is intended to train a PhD mathematician with a background in mathematical modeling in experimental biology and facilitate his transition to an independent investigator. He will be mentored by a physician-scientist with expertise in lung host defense and a complement biologist and overseen by an advisory committee composed of experts in computational modeling, lung biology, and mycology. This training will be enhanced by the rich scientific environment at the University of Florida, together with rigorous coursework in advanced immunology, mycology, and microbiology, and training in grant writing and scientific rigor. Taken together, this project will train a transdisciplinary scientist for an independent investigative career.

NIH Research Projects · FY 2025 · 2023-12

PROJECT SUMMARY In this R21 exploratory/developmental grant application, we propose to develop and validate methodologies for in vivo analysis of RNA targeting in specific circuits, as well as investigating the regulation of these RNAs during long-term memory storage (LTM). The significance of RNAs localized to dendrites for local translation is well known. However, current methodologies do not provide accurate identification of RNAs targeted to distinct subcellular compartments. For example, several studies utilizing molecular analysis of microdissected dendrites or neuronal processes have identified RNAs in the distally localized neurons of diverse organisms, including sea slugs and mice. A major caveat of this approach is that the microdissected regions contain dendrites/neuronal processes from several different neurons as well as segments of interneurons and localized non-neuronal cells. Thus, this approach yields RNAs from dendrites of multiple neurons and non- neuronal cells, preventing our ability to identify the neuron-specific, distally targeted RNAs necessary to generate a more profound understanding of RNA localization and LTM. Since, learning and memory involves changes that are circuit-specific, the lack of robust and reliable methodologies to identify circuit-specific, targeted RNAs acts as a critical barrier to our understanding of RNA targeting in vivo, as well as the role that these RNAs play in both in LTM and disorders of memory. To address this critical knowledge gap, we here propose a strategy that starts with the expression of a tagged kinesin that mediates the transport of RNAs in specific neurons followed by immunoprecipitation of kinesin complexes from distinct neuronal projections and identification and rigorous characterization of associated RNAs. We anticipate that our kinesin-based strategy will yield deep insights into in vivo RNA targeting and their modulation by LTM.

NIH Research Projects · FY 2021 · 2023-12

PROJECT SUMMARY Acute Kidney Injury (AKI) is a heterogeneous syndrome that has multiple etiologies, variable pathogenesis, and diverse outcomes. For example, congestive heart failure and dehydration can produce identical changes in serum creatinine level and urine output (i.e. parameters used to define AKI); however, they differ vastly in their physiological contexts and demand completely opposite treatments. AKI is common in hospitalized patients, affecting 10% to 15% inpatients in the general units and >50% in the intensive care units. Regardless of the underlying cause, even mild forms of AKI are associated with 6.5-fold increase in mortality. The current clinical management guideline for AKI is based on minimizing the risk of developing AKI and providing supportive care. However, the sheer number of known and potentially unknown risk factors of AKI and the complex interactions among them make it impossible for physicians to analyze and forecast AKI risk for a single patient in real time. Machine learning has demonstrated its success in modeling complex electronic health record (EHR) data for disease risk predictions, including AKI. Overwhelming majority of the clinical risk prediction models are trained on data from a predefined patient cohort, also known as a global prediction model, optimized for the supposedly “average” patient. However, the one-size-fits-all prediction model may not work for all patients. Findings from our work in current funding cycle revealed that a global model can make completely wrong predictions for patients in high-risk and heterogeneous (variable pathogenesis) subgroups because it only captures knowledge generalizable to a study population but miss subtle risk drivers specific to an individual patient. Personalized modeling is a promising approach in which a model is trained on-demand for each patient by identifying an individualized retrospective cohort of similar patients. In the current funding cycle, we developed and validated a novel personalized AKI prediction framework and demonstrated its ability to capture patient heterogeneity with an improved AKI risk prediction for individuals. Building on the success of our current project, in this renewal application, we propose to focus the development of new machine learning methods within the personalized modeling framework to gain deeper understanding of the personalized AKI risk and its predictors from individualized cohorts. We designed three specific aims within the personalized modeling framework to answer three important clinical questions: (1) what is an individual patient’s risk for developing AKI during hospital stay? (2) why is an individual patient at risk for developing AKI during hospital stay? (3) when will an individual patient’s kidney function recover after AKI onset? The proposed research has the potential to advance personalized decision support, inform personalized intervention, and facilitate shared decision making for providers, AKI patients, and their families.

NIH Research Projects · FY 2026 · 2023-12

Summary Dysfunctional perception and attention often accompanies and predates the onset of psychiatric illnesses including obsessive-compulsive and anxiety disorders. Many of these dysfunctional responses appear in the context of perceived threat and danger. The neurobiology of visual and attention systems has been extensively characterized in animal models, resulting in extensive mechanistic knowledge ranging from the molecular to the systems and behavioral levels. The proposed research aims to provide new empirically-based, quantitative, and objective markers of specific perceptual and attention processes associated with obsessive-compulsive and anxiety psychopathology. We aim to establish a dimension spanning from hypervigilance to perceptual avoidance, hypothesized to discriminate between diagnostic categories but also predictive of transdiagnostic variables such as severity and comorbidity. We will measure well-validated markers of sensory processing (visual evoked potentials) and competition/attention (frequency-tagged steady state potentials). These data will then be related to clinical data collected in a large sample of individuals presenting with symptoms on the obsessive-compulsive and anxiety spectrum. A mechanistic computational model of perception and attention will be used to aid in data reduction and to heighten reliability. Finding reliable and valid biomarkers of visuocortical reactivity has the potential of transforming diagnostic assessment by providing continuous indices of specific dysfunction. If the goals of this application are met, then reliable and valid indices of dysfunctional perception and attention may help to significantly shift clinical practice. In assessment, objective measures of fear conditioning could be used, for example, to objectively identify patients with hypervigilance, versus those with avoidant dispositions. These inter-individual differences may also be relevant in the context of exposure-based treatments and may represent novel means of assigning patients to individualized treatment protocols as well as predicting treatment outcome.

NIH Research Projects · FY 2026 · 2023-11

Project Summary. New anti-inflammatory therapies are needed to help the millions of Americans that are afflicted by one or more chronic inflammatory conditions. Conventional anti-inflammatory drugs are ineffective and limited by deleterious side-effects that result from administering drugs systemically and at high doses. Many chronic inflammatory conditions manifest locally, not systemically. Localized delivery of natural immunoregulatory molecules is an attractive strategy to treat chronic local inflammation. The proposed research will develop a new anti-inflammatory therapy based on synthetic multivalent assemblies of galectin-1 (“G1”) and galectin-3 (“G3”). G1 and G3 are natural regulators of inflammation that signal changes in immune cell behavior via membrane glycan recognition. Despite some reported successes of wild-type G1 and G3 as anti- inflammatory therapies, their potency is ultimately limited by their low carbohydrate-binding affinity and their unstable active quaternary structures. To address these limitations, our approach joins G1 and G3 into synthetic multivalent nanoassemblies. We make these nanoassemblies through recombinant fusion of G1 and G3 onto the N- and C-termini of peptide linkers that form a-helical coiled-coils. Using this approach, we created G1/G3 Zipper, a heterotetramer with two G1 and two G3 domains (i.e., a dimer-of-dimers). G1/G3 Zipper was shown to have significantly greater signal potency than wild-type G1 and G3 in vitro, and acts through different receptors and different pathways than the wild-type proteins. Preliminary data demonstrate that G1/G3 Zipper can suppress sterile inflammation induced by l-Carrageenan, whereas an engineered G1 homodimer is ineffective. G1/G3 Zipper can also resolve imiquimod-induced psoriasis. Using a similar coiled-coil scaffold approach, we recently demonstrated that the signaling activity of G3 increases as the number of G3 domains increases from two to six. Informed by these data, the guiding hypothesis of the proposed research is that the anti- inflammatory potency of G1/G3 Zipper constructs can be maximized by increasing the number of G1 and G3 domains. To test this hypothesis, Specific Aim 1 is to measure the signaling activity of G1/G3 Zipper constructs with four or six G1 and G3 domains using various cell models of G1 and G3 signaling. Specific Aim 2 is to evaluate the effectiveness of G1/G3 Zipper constructs to suppress local inflammation using the l-Carrageenan and imiquimod-induced psoriasis models. We will use ELISA, bulk RNAseq, and in vivo imaging to identify the mechanisms of action of G1/G3 Zipper. We will use in vivo imaging and histology to establish G1/G3 Zipper pharmacokinetics. We will use humoral immunity models to assess G1/G3 Zipper safety. Completion of the proposed studies will establish our innovative G1/G3 Zipper construct as a new class of anti-inflammatory therapy. Harnessing the immunomodulatory activity of G1 and G3 to treat chronic local inflammation has the potential to impact nearly all aspects of human health. Establishing valency-function relationships of G1/G3 Zipper in two inflammation models will be valuable for translation of galectin therapies.

NSF Awards · FY 2023 · 2023-10

Federated learning enables hospitals to collaboratively learn a shared global model while ensuring patient privacy; however, there is a big statistical challenge for our application owing to EHR heterogeneities, i.e. difference in patient characteristics and clinical observations made or feature space. Thus, real-world EHR data from different hospitals are never independently and identically distributed (IID). The proposed research is to overcome this statistical challenge while improving security for federated learning by leveraging a large integrated EHR dataset with medical records for more than 21 million patients from 12 healthcare systems spanning across 9 US states. A novel privacy-preserving federated transfer learning framework is proposed for building a robust and accurate AKI prediction model that require learning on real-world EHR data from siloed healthcare systems. This project will (1) develop novel transfer learning solutions to address three distinct non-IID EHR data analytic scenarios, (2) develop a novel federated learning framework with a dynamic weighting aggregation mechanism to build a robust and accurate Acute kidney injury (AKI) prediction model; and (3) develop a comprehensive privacy-preserving federated transfer learning framework with novel privacy-preserving solutions to address the unique privacy challenges in the proposed transfer learning applications. The project proposes new transfer learning solutions to combat the non-IID challenge in federated learning and new security building blocks tailored for homogeneous and heterogeneous transfer learning tasks. Together the project will develop a privacy-preserving federated transfer learning framework to provide a first practical solution for non-IID clinical data scenarios. Our research methods and findings will provide promising new directions to machine learning for healthcare and will contribute to both academic research and potential commercialized products. More importantly, the interpretable nature of the base gradient boosting machine model in the proposed federated transfer learning framework will provide better understanding of the predictors from which clinicians can use to design prevention and management strategies for high-risk patients. This project is jointly funded by Smart and Connected Health and the Established Program to Stimulate Competitive Research (EPSCoR). 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 2023 · 2023-09

PROJECT SUMMARY Chronic pain is a pathological state where sensory neurons become hyperexcitable leading to nociceptive neurotransmission in the absence of a painful stimulus. Genetic and functional studies have established the voltage-gated sodium channel NaV1.7 as a major contributor to human pain signaling. Although the regulation of NaV1.7 is poorly understood, it is thought to involve mechanisms related to surface trafficking and regulation via protein-protein interactions. For instance, upregulation of SUMOylation of cytosolic collapsin response mediator protein 2 (CRMP2) and VGSC β-subunits, and downregulation of Nedd4-2 (a cytosolic E3 ubiquitin ligase) in a model of spared nerve injury induced chronic pain result in functional upregulation of NaV1.7 channels. My studies have identified lymphocyte antigen 6 (Ly6) proteins as a novel class of NaV1.7 channel modulators. Ly6 proteins are extracellular glycoproteins that are a hallmark of different types of cancer and have a role in cell proliferation, cell migration, cell–cell interactions, immune cell maturation, macrophage activation, and cytokine production. Ly6 proteins show structural resemblance to the three-fingered snake venom toxins that are known to modulate nicotinic acetylcholine receptors and voltage-gated sodium channels. Of these group of proteins, Ly6e and Lynx1 are common between humans and rodents. RNA-sequencing databases showed that both Ly6e and Lyn1 expression increases in different populations of dorsal root ganglia (DRG) neurons after nerve injury. Moreover, my preliminary findings show that: (i) there are higher Ly6e signal levels in DRGs after spared nerve injury (SNI); (ii) overexpression of Ly6e is associated with increased sodium currents in DRGs, and NaV1.7 currents in HEK cells; and (iii) intrathecal injection of Ly6e plasmid induces pain- like behaviors in naïve rats. These data led me to hypothesize that: (i) modulation of NaV1.7 channels by Ly6e and Lynx1 may lead to altered expression and activity of these channels during chronic pain, and that (ii) interfering with NaV1.7-Ly6e/Lynx1 interactions may relieve pain. Thus, the goals of this proposal are to investigate the role of Ly6 proteins (i) in sensory neurons and (ii) as molecular determinants of the altered functional activity of NaV1.7 channels in pain states. My Specific Aims are: (1) Investigate the physiological function(s) of Ly6e and Lynx1 in primary sensory neurons from rodents with and without nerve injury; (2) Identify and characterize Ly6e and Lynx1 as modulators of NaV1.7 channels in rodent and human dorsal root ganglia neurons; and (3) Identify specific interaction domain(s) in NaV1.7, Ly6e and Lynx1 and validation of in vivo target engagement. These studies are anticipated to advance our understanding of the role of Ly6e and Lynx1 in the sensory system, and their role as modulators of a key pain-associated voltage-gated sodium channel, NaV1.7.

NIH Research Projects · FY 2025 · 2023-09

SUMMARY OF OVERALL COMPONENT Enhanced Echinobase: A Community Genomics Research Resource for the Future Echinobase (Echinobase.org) is the central repository and web-accessible resource for all of the diverse genomic data types produced by biologists working with echinoderms. Echinobase was cloned from Xenbase to enhance database functionality, web application capabilities, and performance, all at a fraction of the cost of doing this independently. A key added feature developed through this work are database modules that support curation and searches of gene expression data. The look and feel of Echinobase is unique, and is tailored to its user base including the creation of a multi-species viewer. The website provides rapid integrated capabilities for search, view and download of a range of datatypes to empower their own research. Echinoderms are one of only three major phyla within the deuterostomes, and therefore the species within this clade encompass a large taxonomic diversity of body plans. Species of echinoderms are powerful model systems for understanding the processes by which the genome controls development. The strengths of this experimental model will continue to make it a preeminent system for the analysis of the genomic control of embryogenesis and for analyses of developmental gene regulatory networks (GRNs) to reveal the mechanistic links between the genome and development and consequently the genomic basis of congenital diseases.

NIH Research Projects · FY 2025 · 2023-09

PROJECT SUMMARY/ABSTRACT Triple-negative breast cancer (TNBC) is a highly heterogeneous and aggressive subtype of breast cancer characterized by the highest potential for metastasis and thus the worst clinical outcomes of all breast cancer subtypes. The outcome in metastatic TNBC (mTNBC) is particularly poor with a median overall survival time of < 16 months. Chemoimmunotherapeutic treatment strategies employing chemotherapeutics, including both conventional compounds and targeted therapies, and PD-1 blockade have proven efficacious for a variety of solid tumor malignancies, however, the efficacy of anti-PD-1 chemoimmunotherapy is limited in the context of mTNBC with an estimated overall progression-free survival of < 10 months and overall survival < 2 years for the best-case scenarios. While the outcomes observed thus far represent a minor improvement for mTNBC, anti- PD-1 chemoimmunotherapy has achieved > 40% 5-year overall survival with greater improvements in response rate and progression-free survival in other solid tumor malignancies. Thus, further studies are needed to optimize anti-PD-1 chemoimmunotherapeutic strategies in mTNBC. Despite the essential synergistic role that chemotherapy plays in anti-PD-1 chemoimmunotherapeutic treatment strategies, the identification and selection of the optimal chemotherapeutic agent(s) that best synergize with PD-1 blockade for an individual patient remain a critically unmet need. Previous studies have identified that the immunomodulatory effects of chemotherapy (chemo-immunomodulation) are imperative for anti-PD-1 chemoimmunotherapeutic efficacy, thus, understanding the factors that influence chemo-immunomodulation may be critical for optimizing anti-PD-1 chemoimmunotherapeutic treatment strategies. Nevertheless, while studies have sought to understand genomic and transcriptomic features that influence chemoresistance, few studies have focused on factors that influence chemo-immunomodulation. The objectives of this proposal are to identify, characterize, and establish the clinical relevance of genomic and transcriptomic features that influence chemo-immunomodulation and utilize the data generated from the studies herein to develop a machine-learning- based model predictive of chemo-immunomodulation by select agents. Aim 1, 2A, and 2B of this proposal will identify and characterize genomic and transcriptomic factors that influence chemo-immunomodulation using bulk and single-cell RNA-sequencing approaches in in vitro, in vivo, and ex vivo models of mTNBC. Aim 2C will establish the clinical relevance of these findings for selected chemotherapeutics using preclinical mTNBC murine models. Aim 3 seeks to utilize the abundance of data generated through single-cell RNA-sequencing to generate preliminary machine learning models that are predictive of chemo-immunomodulation for selected chemotherapeutic agents. The results of this study may provide information that guides novel approaches in designing, optimizing, and maximizing the efficacy of anti-PD-1 chemoimmunotherapeutic strategies based on patient-specific genomic and transcriptomic characteristics and their influence on chemo-immunomodulation.

NIH Research Projects · FY 2024 · 2023-09

PROJECT ABSTRACT This NIDCR Dual Dentist Scientist Pathway to Independence Award (K99/R00) for Tumader Khouja BDS MPH PhD, will establish Dr. Khouja as an independent oral health services researcher developing and implementing evidence-based interventions that integrate dental care into medical settings utilizing both qualitative and quantitative research methods. This long-term goal will be achieved via a 5-year training and research plan that will launch Dr. Khouja’s independent program of research and academic career and support the NIDCR’s mission to increase and maintain a strong cohort of new and talented independent dual degree dentist scientists. The career goals of this program are: (1) training in intervention sciences [and biomedical informatics]; (2) gain expertise in qualitative methods to inform, design, and evaluate theoretically based behavioral interventions, and (3) professional development as an independent researcher. These career goals will be achieved via formal coursework, trainings, national conferences, mentorship, and research experience. The overall objective of this proposal is to understand the barriers and facilitators to non-traumatic dental condition (NTDC) management in the emergency department (ED) through quantitative and qualitative methods. The first aim will determine the national variation in NTDC prescribing in the ED and subsequent ED/urgent care revisits and hospitalizations within 30-days of an index ED visit. Using national electronic health records and integrated claims datasets and a random effects model, we will identify factors associated with prescribing for NTDC and variation at the patient, provider, hospital and state levels. The second aim identifies ED providers’ perceived barriers and facilitators to the management of NTDC in the ED. Using individual in depth interviews, ED providers (physicians, advanced practice providers) will identify the facilitators and barriers to management and prescribing for NTDC in the ED. The third aim will pilot and refine a multifaceted approach for NTDC prescribing in the ED and assess the acceptability and feasibility of the implementation of this strategy in ED settings. We will develop a 2-level interventional strategy [using human centered design methods] that will aid ED providers in NTDC prescribing and refine it based on our findings from the previous aims and field experience. As we test the intervention in an ED, we will use [EHR data from the University of Pittsburgh Medical Center (UPMC) to] evaluate appropriate treatment and clinician experience with ED use for NTDC before and during the intervention. Further trials will test the effectiveness of the intervention in U- and/or R-level proposals. An outstanding interprofessional team comprised of a public health dentist, pharmacist, ED physician, behavioral psychologist, biostatistician [and biomedical infromatician] will provide mentorship to ensure the success of this project. The long-term goal of this program of research is to develop a generalizable and sustainable intervention to improve NTDC management in ED and other medical settings. [This work supports priorities of the U.S. Surgeon General, NIH Director, and NIDCR to integrate oral health and general health through collaborative alliances and creating a diverse pipeline of clinician oral health researchers.]

NIH Research Projects · FY 2025 · 2023-09

PROJECT SUMMARY This R34 application aims to develop and test an innovative mobile application (app) to reduce college student drinking and sexual assault risk in real time. Over 75% of campus sexual assaults involve alcohol, yet existing campus alcohol and SA prevention efforts designed for universal delivery are often siloed and limited in their ability to provide students with in-the-moment assistance to reduce risk. Smartphone apps are an integral part of college student life and are increasingly used to engage students in real-time alcohol prevention; however, none have integrated alcohol and sexual assault prevention into a single cross-cutting tool. This study addresses this gap by expanding a promising campus sexual assault prevention and response app (uSafeUS®) to include evidence-based alcohol harm reduction tools and real-time messaging to support students’ use of protective behavioral strategies (PBS) in the moments when they most need them. The uSafeUS app, currently in use on 24 US college campuses, utilizes sexual assault PBS (e.g., sharing current locations and an expected return home time with trusted peers) as the primary risk reduction mechanism for students to use in social contexts where alcohol is present, yet none of the existing features directly address alcohol consumption. This project will leverage the existing uSafeUS infrastructure and a proven user-centered development process to expand app features to include an interactive drink tracker and personalized feedback messaging to reduce alcohol consumption and increase PBS use. The expanded app (uSafeUS+) will be beta tested in an open trial to gather end-user (student) and campus administrator feedback about the app’s practical utility in the field and feasibility of the proposed implementation and evaluation plans. This will be followed by a pilot 3-arm randomized controlled trial (N = 90, 30/arm) to examine the acceptability, feasibility, and initial efficacy of uSafeUS+, relative to active (uSafeUS) and assessment-only control groups. In the short term, results from the current study will optimize the planned app and inform a fully powered multi-site hybrid effectiveness-implementation trial. Longer term, findings have the potential to inform the use of mHealth approaches for integrating prevention tools to universally deliver personalized real time prevention on college campuses where heavy drinking and sexual assault often co-occur.

NIH Research Projects · FY 2025 · 2023-09

PROJECT SUMMARY/ABSTRACT The overall goal of our research program is to develop new multi-purpose similarity-based tools to extract and analyze information from very large datasets in the biomedical sciences. A central aspect of our work will be the determination of the distance (or similarity) between different objects, a fundamental notion that pervades many aspects of modern data science. Similarity searches are at the core of high-throughput virtual screening, an essential task in medicinal chemistry and drug design. Comparisons also play a key role in rationalizing the results of Molecular Dynamics (MD) simulations by helping us to identify the most important conformations of a system, and how they contribute to its dynamic behavior. Similarity-based techniques are also essential in spectral studies, being the foundation behind the post-processing machinery in Imaging Mass Spectrometry (IMS). However, these applications are currently based on metrics that can only compare two objects at a time, so comparing N objects scales quadratically, which makes them fundamentally ill-equipped to handle the amount of data generated by state-of-the-art simulations and experiments. We recently generalized the pair-wise comparisons, proposing extended similarity indices that allow us to compare an arbitrary number of objects simultaneously. Our indices offer unprecedented efficiency, while also outperforming their binary counterparts in diversity picking, feature selection, and clustering. We will leverage these advantages in three main research directions. (1) We will develop protocols to improve the drug design process via careful exploration of the chemical space. The extended indices will allow us to study the relations among various very large molecular libraries, which will be key in polypharmacology and drug repurposing. They will also lead to better measures of chemical diversity and a deeper understanding of structure-activity relations. This will serve as a guide in generative molecular models, resulting in more robust identification of new drug leads. (2) We will present new workflows to efficiently analyze biological ensembles. Our medoid algorithm will identify conformations close to the folded state of a protein, while our clustering will classify the structures corresponding to other metastable states. Alternatively, we will implement sampling techniques that will allow us to analyze very long MD simulations. These tools can then be combined to gain a deeper understanding of various dynamical processes, including the detailed exploration of protein folding landscapes. (3) We will develop new post-processing techniques to aid with the interpretation of IMS data. Our similarity indices can be used to identify spatially- and molecularly-correlated domains in tissues, without the unphysical artifacts present in other techniques. This will allow us to track the spatial heterogeneity of metabolic processes, which is critical to the validation of IMS data and to establishing new diagnosis tools. The application of our framework to the study of lipid expression in pancreatic tissue will lead to a better understanding of type 1 diabetes metabolism and pathophysiology.

NIH Research Projects · FY 2025 · 2023-09

Project Summary How does an animal decide when to help another individual? This question is fundamental to understanding how an individual modifies pro-social behaviors based on the context of a social situation, a feature often disrupted in neuropsychiatric disease. Past rodent research has investigated the mechanisms behind pro-social behavior; however, they focused on paradigms where animals do emotional state-matching or help an individual in distress. Therefore, our fundamental understanding of the mechanisms promoting pro-social behavior is biased towards negative affective states leaving a gap in our understanding of these decisions in positive affective states (e.g. helping others obtain rewards). The amygdala encodes valence, the goodness or badness of a stimuli, and is known to be involved in social decision making in negative affective states. Recent evidence points to amygdala activity being necessary for learning to help a conspecific gain a reward, but how amygdala neurons encode these prosocial decisions is unknown. Furthermore, which amygdala circuits may control these pro-social decisions in a changing social context also remains unknown. Using mice as a model and an established assay for pro-social decision making, this proposal will investigate the hypothesis that functional connectivity of the amygdala and prefrontal cortex flexibly modulates both pro-social helping behavior and individualistic behavior depending on the social context (e.g. conspecifics present). Thus, this study fills an important gap in our knowledge about the neural mechanisms mediating pro-social decision making across social contexts, and how necessary and sufficient functional connectivity between the amygdala and prefrontal cortex is to pro social or individualistic behavior.