University Of Florida

NIH Research Projects · FY 2025 · 2024-09

Not only is skeletal muscle a target in sepsis that contributes to worse patient health outcomes, including problems weaning from mechanical ventilation and a greater risk of death, but through release of mtDNA there is strong potential for skeletal muscle to play an amplifying role in driving the systemic inflammation by activating damage associated molecular patterns (DAMPs). Therefore, identifying treatments to attenuate adverse muscle impact with sepsis is one key to improving patient outcomes. This high risk-high reward R21 application explores the role of an event known as mitochondrial permeability transition (mPT) in skeletal muscle as a mechanism for both muscle dysfunction and mtDNA-mediated escalation of systemic inflammation in sepsis. mPT is triggered by Ca2+ to cause formation of a non-specific pore across the mitochondrial inner membrane, where phosphorylation and/or acetylation of the mitochondrial peptidyl-prolyl cis-trans isomerase protein cyclophilin D (CypD) reduces the amount of Ca2+ needed to trigger mPT, whereas knockout of CypD increases the amount of Ca2+ needed to trigger mPT. Notably, mPT has been demonstrated to occur in various tissues with sepsis but has so far not been considered in skeletal muscle, despite several studies noting an accumulation in skeletal muscle of mitochondria with morphological features that are established consequences of mPT. In addressing the outcomes of mPT in skeletal muscle, we have shown that mPT causes atrophy and dismantling of the acetylcholine receptor cluster at the neuromuscular junction, and other impacts are likely to be revealed with further study. Furthermore, mtDNA is released from mitochondria during mPT and higher mtDNA levels in the circulation predict poor outcomes in septic patients. Considering that skeletal muscle constitutes up to 40% of body mass, mPT occurring in skeletal muscle has strong potential to play a major role in driving the increase in circulating mtDNA in sepsis. In addressing this issue, we will test the central hypothesis that knockout of the mPT-promoting protein CypD in skeletal muscle will attenuate both muscle dysfunction and systemic inflammation in sepsis to yield improved outcomes in septic mice. We expect that our studies will demonstrate that in the context of experimental sepsis skeletal muscle-specific CypD knockout will confer protection to skeletal muscle, attenuate the increase in circulating mtDNA to limit systemic inflammation, and thereby promote better outcomes in sepsis.

NSF Awards · FY 2024 · 2024-09

Astronomers are just beginning to understand when and how planets form around young stars, with deep implications on the prospects for life in the Universe. While rocky planets similar to Earth are located close to their stars, these innermost regions are typically too close-in to study with conventional telescopes. This project will combine light from multiple telescopes operating as an interferometer – the CHARA array - to measure the temperature and map the surface density of the inner disk surrounding solar-mass and intermediate-mass young stars. Repeated observations will track moving clumps of dust that could be indicating accretion/wind physics or local planet formation. Outreach programs at rural community colleges will draw local high school students into higher education. An inspiring educational experience is planned for middle-schoolers in “Wolverine Pathways,” a University of Michigan program offered to communities in the Detroit-metro area who are historically under-represented in state colleges. The CHARA Array is the longest-baseline optical/infrared interferometer in the world. Researchers at the University of Michigan developed the MIRC-X and MYSTIC instruments which combine all six CHARA telescopes with broad 1.1-2.5μm wavelength coverage simultaneously, while also supporting access by the broader astronomical community through open time administered by NOIRLAB. In commissioning data, the team has discovered hot, time-variable emission inside the expected dust destruction radius. In this project, they make a modest upgrade to the telescopic instrumentation; measure multiwavelength data to assess the disks temperature; expand the target sample to stars of diverse masses, luminosities, ages, and accretion rates; and measure time-domain follow-up data. This project improves research infrastructure by providing new software tools, such as the first MYSTIC-ABCD pipeline, written in Python and C, and it makes the source code publicly available. Regarding broader impact, an outreach program with St. Clair County Community College develops authentic research modules with an internet-enabled telescope, supporting STEM students transferring to 4-year colleges. 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 2024 · 2024-09

Abstract Walking recovery is a top rehabilitation goal for many individuals with incomplete spinal cord injury (ISCI). Accordingly, there are extensive resources invested into understanding ISCI-induced walking impairments and developing interventions to advance recovery. While these efforts target lower extremity control, functional walking is a full-body activity requiring rhythmic, coordinated movements of the limbs and trunk. After ISCI, individuals often demonstrate trunk control deficits: aberrant trunk movements during stepping, impaired posture, and consequently, reliance on assistive devices and ongoing walking impairment. Despite the importance of the trunk in walking control, it is rarely an intervention target and clinical assessments of walking do not consider trunk control. Instead, trunk control is assessed in sitting or static standing, which provides limited insight into control during walking. Understanding of trunk control is critical to address the severe and persistent impairments that limit walking function. Our long-term objective is to quantify trunk control during walking to inform critical next steps in clinical assessment and future walking research. This initial study will quantify coordination of trunk movements and underlying muscle activation. We will address following aims: Aim 1: To test the hypothesis that individuals with ISCI demonstrate impaired coordination of trunk movements during walking. We predict individuals with ISCI will demonstrate reduced counter-rotational trunk movement across the gait cycle. The primary outcome will be the phase relationship between movements of the thorax and lower extremities, quantified by continuous relative Fourier phase, an established approach to quantify phase relationships during cyclic activities. Additionally, trunk kinematics (i.e., range of motion, accelerations) in all planes will be quantified and differences between those with ISCI and controls will be calculated. Aim 2: To test the hypothesis that individuals with ISCI demonstrate impaired intermuscular coordination of trunk and lower extremity muscles during walking. We predict that individuals with ISCI will demonstrate a reduced number of co-active muscle patterns to achieve the biomechanical sub-tasks of walking (i.e., limb loading, swing initiation). The primary outcome will be the number of motor modules (i.e., groups of consistently co-activated muscles) required to account for activation of 32 trunk and lower extremity muscles during walking. Additionally, timing of module activation and relative muscle contributions will be quantified. Achievement of these aims will address a critical gap in understanding walking control after ISCI. This 2-year study will provide initial evidence to develop larger, more definitive investigations of trunk control during walking, a critical step for advancement of research and care for people with ISCI.

NSF Awards · FY 2024 · 2024-09

Throughout history, infectious diseases have shaped human societies in profound ways. The Black Death pandemic of the 14th century was one of the deadliest in human history, killing an estimated 30 to 60 percent of Europe’s population. This project aims to unravel the complex relationships between climate, agriculture, human behavior, and disease outbreaks during the Black Death and subsequent centuries-long plague pandemic. By integrating mathematical models with archaeological and historical data, the researchers will reconstruct how environmental and social factors combined to create conditions ripe for catastrophic pandemics. Broader impacts will arise from the integrated datasets and modeling tools that will be made freely available and support infectious disease research. The crucial insights will aid management of modern outbreaks and may improve public health in the future. The project will develop computer simulations that integrate models of disease transmission, human demographics, land use, and climate. These models will be combined with diverse sources including human skeletal remains, tree-ring data, pollen records, and historical documents using a technique called data assimilation. This approach allows researchers to fill in gaps in the fragmentary historical record and test hypotheses about how factors like climate-driven food shortages, urbanization, and trade routes affected plague outbreaks. The researchers will collect new bio-archaeological data on age, health status, and migration patterns from skeletal remains at plague burial sites across Europe. By reconstructing the environmental and social conditions surrounding major outbreaks over several centuries, the project aims to identify recurring patterns that cannot be revealed from contemporary pandemics alone. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NSF Awards · FY 2024 · 2024-09

The increasing use of reusable hardware intellectual property (IP) in modern semiconductor design faces significant confidentiality threats, including reverse engineering (RE), IP theft, and piracy throughout its lifecycle. Various active IP protection techniques have been investigated to secure hardware IPs against these threats. With the emergence of a broad range of attacks on these techniques, there is a need for a principled approach to enable robust protection against possible attacks, while achieving low hardware overhead and scalability to large designs. The key novelty of this project is the use of diverse Artificial Intelligence (AI) techniques, such as reinforcement learning and explainable algorithms for automated discovery of new hardware security attacks and deriving commensurate design transformations to effectively protect against these attacks. The research outcomes from this project are used to develop new cybersecurity courses, increase the participation of undergraduate/high-school students in research, and release of open-source tools/datasets for the broader research community. This project also contributes to enhancing the security and trustworthiness of electronic hardware and greatly benefits the semiconductor industry, as well as making a positive impact on national security. This project is developing a new framework for microelectronic security and trust. The approach utilizes a fundamentally different, knowledge-guided systematic design transformation approach for securing IP against RE attacks. This framework mimics the way security researchers and engineers gather knowledge from existing attacks to discover novel attack vectors and their root causes. Furthermore, the method can devise strong defense strategies to mitigate the newly discovered attacks and apply these defense strategies in a scalable manner to create a protected design with minimal design overhead. This project comprises of three parts: (1) the reinforcement learning techniques discover novel attack vectors against logic locking and identify root causes behind the success of these attacks, (2) explainable diverse Artificial Intelligence (AI) is used to extract design transformation rules that can defend against diverse attack vectors, (3) the discovered design rules are applied to successfully meet design and security requirements while also ensuring correctness. The research team is also developing novel security metrics and integrating all the components into a comprehensive IP protection platform for rapid evaluations. Moreover, the research team also extends the framework to other Design-for-Security techniques, such as fault, side-channel, and Trojan attack countermeasures. 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 2024 · 2024-09

Project Summary Deoxyribonucleic acid (DNA), carrying genetic instructions for the growth, functioning, and reproduction of most living organism, presents a critical avenue for exploring evolutionary history, disease etiology, personalized medical interventions, and beyond. However, our grasp of the role played by DNA sequences, especially non-coding DNA, remains limited. Unraveling this mystery proves challenging due to the labor-intensive and resource-demanding nature of experiments required for its decoding. Although computational techniques have arisen, they grapple with obstacles such as insufficient training data to unlock the secretes within DNA sequences. Inspired by recent advancements in natural language processing, we recognize significant prospects for employing a similar approach to study DNA sequences as a form of biological language. Our central concept revolves around developing an advanced DNA language model. Aligning with the trajectories of its linguistic and protein structural counterparts, our model holds the potential to reinvigorate the research of DNA structure and functionality. This model serves as a versatile tool, enabling the exploration of various functions residing within DNA sequences using an innovative multi-task learning architecture. Our initial exploration focuses on unveiling the fundamental mechanisms driving DNA regulation. The model is adaptable to various DNA functions under the multi-task learning framework. Additionally, the model facilitates the understanding of the functional impacts of non-coding variants, which has profound implications for genetic testing. Our innovative framework could significantly expand the scope of variants that can be reported in genetic testing, thereby enhancing our ability to identify genetic contributions to health and disease and guiding personalized medical interventions.

NSF Awards · FY 2024 · 2024-09

People make many decisions in life (e.g., what job to take, whether to have kids) based on how they expect those decisions to make them feel. Ultimately, people want to make choices that contribute to leading a meaningful life, and doing so results in greater well-being, giving back to their communities through service, and pursuing careers that benefit society such as nursing and teaching. However, people can underestimate how meaningful an experience will be (e.g., that attending medical school would enhance their sense of purpose deeply), leading them to pursue suboptimal paths. This project studies the conditions that impact people's underestimations of the meaningfulness of future experiences, why they are errant in these assessments, and how to make better life decisions. This project examines errors people make in underestimating the meaning of future experiences by identifying the boundary conditions and mechanisms underlying how people anticipate meaningfulness in life decisions. In field and lab experiments, the work tests the hypotheses that people routinely underestimate the meaning of life experiences, and whether these errors extend equally to positive and negative experiences and to both milestone and mundane life events. Finally, the project examines when and why people are most likely to underestimate meaning to help improve meaningfulness forecasting accuracy. Many meaningful growth experiences involve discomfort, and if people underestimate the meaning of such experiences, they may pursue relatively meaningless but comfortable experiences over meaningful and challenging ones. Correctly anticipating that life experiences may be more meaningful than anticipated may improve people's ability to make more informed choices and can encourage them to pursue meaningful activities (e.g., volunteering, prosocial careers) that enhance society. 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 2024 · 2024-09

(PLEASE KEEP IN WORD, DO NOT PDF) Heparanase, an endo-β-D-glucuronidase, is the only known enzyme to cleave the heparan sulfate (HS) side chains of heparan sulfate proteoglycans (HSPGs), which are key components in the extracellular matrix (ECM) of all tissue types. In the glomerular basement membrane (GBM), these HSPGs play a crucial role in the glomerular filtration barrier. Alterations in HS has been associated with glomerular barrier dysfunction in nephropathy. Under diabetic milieu, the release of heparanase is significantly increased, and heparanase has been identified as a key contributor in the development of diabetic nephropathy, which is marked by a decline in glomerular filtration rate (GFR) and the presence of albuminuria. Prior investigations using existing HS-based heparanase inhibitors have shown promising therapeutic effects, such as restored glomerular filtration barrier and reduced albuminuria, in animal models or patients with diabetic nephropathy, suggesting an emerging therapeutic option for the disease. However, HS-based structures are heterogenous, suffering from batch-to-batch variation, and the existence of other HS binding proteins has led to undesired off-target effects, limiting their therapeutic application. We therefore hypothesize that heparanase inhibitors with defined chemical structures, high selectivity, and drug-like features can yield successful outcomes for the prevention and treatment of diabetic nephropathy. Currently, no orally available heparanase inhibitor has been developed. In this project, we will develop innovative artificial intelligence (AI)-based methods, aiming to support the development of potent orally available small-molecule heparanase inhibitors, which will be evaluate in murine models in the next phase.

NSF Awards · FY 2024 · 2024-09

With the support of the Macromolecular, Supramolecular and Nanochemistry Program in the Division of Chemistry, Professor Stephen A. Miller of the University of Florida will convert post-consumer waste plastic and bio-based feedstocks into a novel family of sustainable polymers with properties suitable for replacing incumbent packaging plastics. Despite what is taught in most textbooks, the ester functional group is generally more stable than the amide functional group, as proof of concept experiments and computations indicate. This relative stability will be exploited to synthesize exemplary polymers via Amide to Ester Polymerization (ATEP), an unexplored polymerization pathway particularly suited for the chemical recycling/upcycling of post-consumer polyesters (e.g., water bottles and polyester clothing) and nylons (e.g., backpacks and fishing nets), yielding polyesteramides. Convergent chemical recycling will transform mixed waste streams of polyesteramides and polyesters into a single monomer suitable for repolymerization. Alternatively, the polyesteramides will be degraded via hydrolysis under environmentally relevant conditions (e.g., seawater). Long-term studies will establish polyesteramide degradation rates, while computational studies will explain how they can degrade in water over relatively short timescales—necessary to combat the plague of plastics accumulating in the environment. The U.S. plastics industry directly employs over one million people and generates $550 billion in annual shipments. More sustainable polymers—whether from post-consumer materials or bio-based feedstocks—are expected to exceed a 40% market share by 2030. Inclusion of the proposed ATEP polymers could further accelerate this amazing growth and expand the variety of materials applications. While polyester aminolysis is much more facile than hydrolysis or alcoholysis, the formed bis-amides have minimal demand because of their presumed stability. ATEP creates an application for these bis-amides and is a novel kinetic pathway for their polymerization, generally yielding polyesteramides with properties excelling those of the original polyester. Key polymer properties include melting temperature and glass transition temperature, and these measured properties will be correlated to polymer structure. For example, aminolysis of post-consumer PET (polyethylene terephthalate) followed by ATEP will yield polyesteramides with a tunable glass transition temperature that depends on the nature of the amine originally employed for aminolysis. Polymer upcycling will be achieved when the glass transition temperature substantially excels that of the precursor PET (72 °C). The complexities of ATEP will be unraveled by pursuing specific project goals: (1) optimizing PET aminolytic depolymerization conditions and applying them to a variety of commodity polymers, including polyesters, nylons, and others; (2) optimizing ATEP and comparing polyesteramide properties to those of extant polymers; (3) further developing the thermodynamic and kinetic rationale of ATEP via computational methods; (4) applying ATEP to a variety of bio-based diacids; (5) establishing polyesteramide structure/property relationships; and (6) investigating practical depolymerization conditions, including environmental degradation and chemical recycling. Exploring the many facets of ATEP will greatly expand the fundamental understanding of polymerization/depolymerization chemistry. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NSF Awards · FY 2024 · 2024-09

The USA National Phenology Network (USA-NPN) is the premier source of information regarding plant and animal phenology, the timing of life-cycle events such as leaf budburst, flowering, and fruiting or insect adult emergence, in the United States. Phenology observations maintained by USA-NPN are contributed by professional and volunteer observers at tens of thousands of locations across the country, and these data are used widely in science, science communication, and management. However, critical limitations in the USA-NPN’s data collection and access infrastructure currently limit public engagement and research use from reaching their fullest potential. This work will result in major improvements to the USA-NPN’s data collection mobile app and to data access tools. These enhancements are expected to lead to substantial growth in volunteer participation, especially from locations and communities of people that do not yet participate. Engaging a larger and more diverse community in data collection will result in a more robust, balanced, and representative phenology dataset, which will contribute to societal well-being through the provision of better ecological data to inform decision-making. The full set of activities directly links to our ability to understand planetary resilience. The USA National Phenology Network is a national-scale program focused on the collection, provisioning and use of plant and animal phenology data. In this study, the researchers will make major improvements to the USA-NPN’s technical infrastructure in order to lower barriers to entry for new and continuing public participants who collect phenology data and increase engagement and connections among participants. In particular, we will develop observing challenges, in-app badges, enhanced, tailored user notifications and multilingual support for the USA-NPN mobile app. This work will also support science and management use by ensuring data quality through the addition of photo storage, computer-aided identifications, and enhanced discoverability. In particular, the researchers will improve tools to access data, and periodically publish the dataset to the Global Biodiversity Information Facility. These participation and user-focused improvements will lead to a redesigned, easier-to-use set of access points for the research community, and integration into global ecological data-sharing initiatives with a focus on FAIR (Findable, Accessible, Interoperable, Reusable) data. Finally, this work will support training and new opportunities for graduate and undergraduate students interested in the public participation in science. 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 2024 · 2024-09

Frontotemporal dementia (FTD) represents 10 to 20% of all dementia cases. GRN mutations account for up to 20 percent of familial and 5 percent of sporadic FTD. Homozygous GRN mutations cause the rare lysosomal storage disease ceroid lipofuscinosis. Dysfunctional lysosomal degradation pathways due to reduced granulin function can lead to TDP-43 proteinopathy. TDP-43 has been implicated in regulating transcription, alternative splicing, and mRNA stability. GRN-FTD manifests as the behavioral variant (bvFTD), primary progressive aphasia, and movement disorders with extrapyramidal features such as parkinsonism and corticobasal syndrome. It is unknown what brain circuits cause motor symptoms and aphasia in GRN-FTD patients. Basal ganglia are involved in both motor and language functions. It is unknown whether and how GRN mutation affects basal ganglia, leading to motor symptoms and aphasia. We obtained a line of Grn (mouse homolog of human GRN) knockin (KI) mice with the most common GRN-FTD mutation found in human patients. Preliminary studies of Grn KI mice showed earlier onset motor coordination and balance deficits, accompanied by altered firing patterns of striatal neurons. Our long-term goal is to use mouse models to elucidate the pathophysiology of motor symptoms and language deficits associated with FTD. The specific objective of this proposal is to determine the effect of Grn knockout restricted to the striatum on motor and non-motor symptoms in mice. We hypothesize that heterozygous striatum-specific loss of function of the progranulin protein leads to TDP-43 proteinopathy and reduced hyperpolarization-activated cyclic nucleotide-gated (HCN) mRNA and protein expression, in turn results in motor and communication deficits accompanied by anatomical and functional deficits in the basal ganglia, especially in the striatal cholinergic interneurons (ChIs) and medium spiny neurons (MSNs). The rationale for the proposed research is that once the mechanisms of the altered striatal neurons and motor and aphasia symptoms in FTD are clarified, novel therapeutics can be developed to treat motor and non-motor symptoms in FTD patients. We plan to test our hypothesis with the following Specific Aims: Aim 1: To test the hypothesis that the heterozygous striatum-specific Grn knockout mice have deficits both in motor and non-motor behaviors, we will examine the mutant mice with a behavioral test battery. Aim 2: To test the hypothesis that altered striatal neurons in the heterozygous striatum-specific Grn knockout mice contribute to motor and non-motor symptoms in FTD, we will a) quantify the number of striatal ChIs by immunohistochemistry, b) analyze the in vitro activity and morphology of striatal neurons, and c) quantify proteins involved in striatal cholinergic metabolism and HCN expression. The successful completion of the above aims will allow us to determine how the altered properties of striatal neurons can lead to motor dysfunction and aphasia in FTD. Characterizing these neurons will provide novel targets for treatment and offer great promise for developing targeted therapies for motor dysfunction and aphasia associated with FTD.

NIH Research Projects · FY 2025 · 2024-09

The objective of the proposed State of the Science Meeting Series: Health and Safety of Gulf Coast and U.S. Caribbean Fishers reflects an integrated, multi-disciplinary collaboration focused on evidence informed education bridging the gap between research and practice to improve fishing industry sector worker safety and health. In 2018 the Southeastern Coastal Center for Agricultural Health and Safety (SCCAHS) launched the annual State of the Science (SOS) Meeting to better understand and enhance the uptake of evidence-based practices that improve the health and safety of agricultural, forestry, and fisher populations and spotlight emerging issues. The SCCAHS has convened a total of six meetings 2018 – 2023, with the annual theme driven by community feedback reflecting their priorities, values, and experiences. The focus of this proposal is to use the sound SCCAHS framework to create a forum that addresses cross-sector topics (musculoskeletal health, injury prevention, surveillance, climate adaptation and mental health) and the effectiveness of practices and policies on U.S. Gulf and Caribbean fisher communities. The meeting outcomes will contribute to stronger collaboration between regional researchers and serve as a vehicle to disseminate research findings more broadly to community stakeholders related to NIOSH strategic and intermediate goals on musculoskeletal disorders, workplace safety, and healthy work design and well-being. The leadership team seeks to convene two SOS meetings in partnership with the Gulf and Caribbean Fisheries Institute (GCFI) in November 2024 and 2025. The SOS meetings will be convened pre-GCFI Annual Conference specialty workshops in collaboration with the NIOSH Office of Agricultural Safety and Health and an Organizing Committee. These groups understand the burden and needs of commercial and artisanal fishing workers – climate change impacts, governance, and adherence to safety interventions. These meetings will be driven by the long-term goal to cultivate partnerships and interdisciplinary collaboration, share national and regional research findings, engage the community as leaders in the research process and mobilize responsive programming to serve real- time conditions and challenges. The conference plan will be directed by NIOSH strategic goals and corresponding specific aims: 1) to provide oversight in aligning speakers/discussion leaders in addressing knowledge gaps and emerging issues impacting Gulf Coast and U.S. Caribbean fisher populations, 2) to embed hallmark community led meeting track – Community Voices: The impact of climate variability on fisheries productivity and fisher livelihoods, 3) to implement networking opportunities to advance collaborations among Gulf Coast and U.S. Caribbean stakeholders, and 4) to evaluate, translate, and disseminate research to practice findings into public information products. The proposed work is important because Gulf South, Puerto Rico, Saint Croix, Saint John and Saint Thomas coastal areas and island territories must join the discussion to support capacity building and promoting fisheries research, assessment, and management.

NIH Research Projects · FY 2025 · 2024-09

Project Summary Disruptions of epigenetic mechanisms that regulate gene expression are frequently found in cancer and collaborate with genetic alterations to drive cancer phenotypes such as therapy resistance and immune escape. Since 2016, Dr. Bennett, the research specialist for this R50 award application, has supervised teams of researchers and performed key experiments for the NCI-funded research program of the unit director, Dr. Jonathan Licht, at the University of Florida Health Cancer Center to study how epigenetic mechanisms are disrupted in cancer. Dr. Bennett has strong track record of important contributions to cancer research, and his work has been instrumental to the success of CA195732, U54CA193419 and U01CA225566. He has demonstrated that a glutamate to lysine mutation at amino acid 76 of histone H2B fundamentally alters chromatin dynamics and accessibility, causing changes in gene expression and cell growth properties that favor tumorigenesis. Dr. Bennett showed that treatment of acute lymphoblastic leukemia cells harboring mutant histone methyltransferase NSD2 with PRC2 inhibitors can reactivate glucocorticoid (GC) receptor expression and restore sensitivity of these cells to GC therapy. In addition, he has determined genetic dependencies for growth and therapy resistance in uveal melanoma as well as identified an HDAC8-driven permanent lineage switch maintained after drug withdrawal in melanoma. This R50 award will provide career stability for Dr. Bennett to continue making important contributions to cancer research and advancing the unit director’s larger NCI- funded research program. Dr. Bennett will lead research teams and perform key experiments to accomplish the aims of the Dr. Licht’s three NCI-funded R01 awards: R01CA266078 (Histone fold Mutations in Cancer Pathogenesis), multi-PI R01CA256193 (Characterization and targeting of the epigenetic state underlying uveal melanoma liver metastasis) and multi-PI R01CA262483 (Defining and targeting epigenetic plasticity-driven drug resistance and immune escape in melanoma). In addition, funding of this award will allow Dr. Bennett to pioneer new directions for each project especially by applying cutting-edge technologies and building collaborations with other NCI-funded investigators. Dr. Bennett is an expert in a wide spectrum of epigenomics techniques such as biochemical assays, gene expression analysis, chromatin profiling and CRISPR screens that are essential for the success of these awards and advancing the unit director’s NCI-funded cancer research program. These studies will reveal new epigenetic mechanisms of oncogenesis that contribute to tumor progression, heterogeneity, and therapy resistance, with the aim of finding new targets and pathways of intervention for cancer patients that will ultimately lead to better patient outcomes.

NSF Awards · FY 2024 · 2024-09

NON-TECHNICAL SUMMARY Solids with internal structure composed of chemically bonded layers separated by weaker interactions form the basis of important technologies, especially in areas of energy storage. Modern batteries use layered materials as the chemically active components that store and release ions during operation. Layered solids are also being developed by materials scientists and engineers for next-generation semiconductor devices. For many of these applications, smaller particles improve performance, but as particle size decreases, surfaces contribute more and more to material properties. Supported by the Solid State and Materials Chemistry program in the Division of Materials Research at NSF, this project explores how the surface contribution to solid-state properties changes when the layered solids operate in different chemical environments, specifically when used in different solvents. Combining experimental and computational approaches, the fundamental studies will directly inform applications that rely on chemical reactions of layered solids, including applications in critical energy-related and information technologies. Through research tasks designed to be platforms for training and development, the project will provide students with the skills and knowledge needed to be competitive in high-technology professions. TECHNICAL SUMMARY Intercalated layered solids are among the most widely used in current lithium electrode technologies and among the most widely explored for future solutions. Other important applications involving layered host/guest reactions include catalysts, ion exchange and the production of 2D materials. Although it is widely recognized that solvents play crucial roles in liquid phase intercalation processes, the reasons behind much solvent-dependent behavior remain poorly understood and under debate. This NSF SSMC project combines experimental and computational approaches to quantify how the solvent-host interface alters the effective internal pressure of the host as surface energy and surface stress change, leading to differences in chemistry. Using molecular intercalation reactions, research aims include detailed structural analyses of solvent-host interactions alone; structural and kinetic studies of solvent influences on intercalation products and mechanism; and theoretical studies to relate the solvent-host effects to key mechanistic steps in the intercalation process. Findings will directly inform applications that rely on solid-state host-guest reactions, including applications in critical energy-related and information technologies, and the project includes significant human resources development, providing training and knowledge needed to be competitive in high-technology professions. A new public outreach exhibit, entitled The Materials in Your Battery, will highlight fundamental questions related to battery technology. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NSF Awards · FY 2024 · 2024-09

This project concerns the development of efficient and reliable algorithms for detection of anomalies in data. This topic is of current in interest in many industries such as computer systems management, healthcare, and power systems. For these three examples, anomalies may represent a serious threat, such as a data breach, a medical emergency, or collapse of the power grid. Research will focus primarily on online settings for which speed of response is critical, such as early detection of events that may lead to disaster. The goal is not only to identify a sudden change but also anticipate the onset of undesirable behavior. Dissemination will be strengthened through local workshops, for which the PI has been active since 2012. In particular, the annual “workshop on cognition and control” organized by the PI has attracted speakers from all over the globe. There is a long history of research on algorithms for threat detection, with most of the research focused on algorithm design based on statistical models of threatening behavior. While such approaches may bring both complexity and fragility, the large literature on quickest change detection offers enormous insights on appropriate architectures for change detection algorithms in a model-free setting. Several approaches will be explored based on recent advances in machine learning, notably reinforcement learning and gradient free optimization. In addition, it is believed that development of these approaches within the domain of threat detection will help advance these general approaches to machine learning. 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 · 2024-09

PROJECT SUMMARY Opioids exert a plethora of behavioral effects that include clinically beneficial analgesia and untoward euphoria that leads to their abuse. Furthermore, prolonged exposure to opioids is associated with the development of dependence and tolerance that drive relapse and contribute to overdose and grave side- effects. All of these effects are mediated by the μ-opioid receptor (MOR), strategically positioned in neurons that form reward and nociceptive circuits. Furthermore, MOR signaling is involved in development of addiction to a wide range of drugs of abuse. The overarching goal of our efforts is to dissociate the behavioral effects associated with activation MOR signaling in neural circuits to curb the development of dependence. Our strategy to achieve this goal is to use large scale, unbiased approaches to identify novel modulators of MOR signaling and then apply high throughput chemical biology strategies to target these components with small molecule compounds. By conducting an unbiased forward genetic screen we have recently identified several novel receptor-like components that exert “anti-opioid” activity by modifying MOR signaling. Proof-of-principle experiments with knockout mice show that elimination of these elements profoundly alters behavioral responses to opioids diminishing the dependence and tolerance while increasing analgesia. Based on these observations we propose to use high throughput approach to develop pharmacological tools for redirecting MOR signals to specifically manipulate with opioid responses modifying addictive behaviors. Specifically, we plan to follow up on the discovery of the diverse set of compounds identified in high- throughput screening campaign, optimizing them using medicinal chemistry for achieving selective and specific alterations of MOR signaling. We will characterize the compounds and undertake their development efforts culminating in studying the effects on modifying opioid responses with circuit specific resolution using innovative optical strategies for recording neuromodulation in brain slices. Finally, we will investigate in vivo actions of the developed tool compounds testing their activity in rodent models of pain and addiction using a comprehensive battery of behavioral assays. These efforts will be paralleled by conducting in vivo pharmacokinetics, pharmacodynamics and toxicology studies. It is expected that this effort should result in a development of precision tools for understanding opioid receptor signaling and dissociating opioid effects with circuits and molecular specificity.

NIH Research Projects · FY 2024 · 2024-08

PROJECT SUMMARY Transplantation of solid organs (liver, pancreas, spleen, adrenal glands, heart, lungs) can save the lives of many patients with irreversible organ disease or injury. In the U.S., more than 40,000 transplants were performed in 2021 alone. After a solid organ transplant, lifelong immunosuppressant therapy must be used to prevent and treat organ rejection. The calcineurin inhibitor tacrolimus is a major therapeutic in such cases. Due to the risk of organ rejection, infection, and drug toxicity, therapeutic drug monitoring is advised to ensure pharmacokinetic (PK) targets. Typically, the need for precise dosing has been linked to genetic differences, particularly those affecting drug PK. Despite the important role of pharmacogenomics in precision dosing, large expression variability occurs within each genotype, which can be captured by expression data. Moreover, no known genetic signatures define the wide expression variations for certain key enzymes, such as CYP3A4. Hence, assessing variability in expression of gut and hepatic CYP3A4 is a promising alternative to inform drug development and precision medicine. This promising approach may capture transcriptional regulation effects, such as the downregulation of CYP3A4 by proinflammatory cytokines. Recent exploratory studies showed the application of plasma-derived extracellular vesicles (EV) and omics technologies deployed as a liquid biopsy to assess the expression of drug-metabolizing enzymes and transporters. Hence, EV are gaining traction as new phenotyping biomarkers. Various EVs are shed into the blood and contain cargo representing their tissue of origin. Building upon earlier findings, we will answer the following research question: Can we use liver-derived EV as in vivo CYP3A4/5 expression biomarkers to inform tacrolimus dosing in liver transplant patients? A prospective clinical study will be conducted in patients undergoing liver transplants to explore whether liver and gut-derived EV expression data can be used to predict the variability in tacrolimus pharmacokinetics and ultimately to propose an optimal dosing regimen. In summary, we will integrate PK, transcriptomic data, and modeling and simulation to establish an innovative strategy to individualize tacrolimus dosing. The use of expression data to support precision dosing can potentially overcome the exclusion of under-represented population subgroups (e.g. rare genetic variants of CYP3A4/5 and P- glycoprotein (P-gp). Thus, this proposal will promote diversity in immunosuppression therapy by enhancing the number of subjects responding to tacrolimus efficacy and reducing the risk of adverse reactions. Our research will develop an integrated package of highly predictive mathematical models and dosing optimization strategies for tacrolimus. By tracking different sources of variability in tacrolimus pharmacokinetics, we will inform precision public health interventions in solid organ transplant patients. Importantly, our liquid biopsy approach can be further evaluated and applied in other solid organ transplant patients such as heart, lung, and kidneys.

NIH Research Projects · FY 2024 · 2024-08

PROJECT SUMMARY Pancreatic cancer (PC) is a significant public health issue and is the third leading cause of cancer deaths in the U.S. PC is associated with significant neurologic and psychiatric morbidities, which are associated with reduced health-related quality of life (HRQoL). Supportive care medications (SCM) are the foundation to managing PC- related neurologic and psychiatric symptoms and thus improving HRQoL. Multiple PC studies have demonstrated worsened HRQoL in racial/ethnic minorities. Prior research evaluating the impact of race/ethnicity on SCM use in cancer indicated that racial/ethnic minorities were less likely to be prescribed several types of SCM. However, the studies did not assess the contextual-level social determinants of health (SDoH), the quality of SCM used, nor the impact of social or cultural factors on SCM use. Thus, to our knowledge, no research has examined causal paths of racial disparities in SCM use in PC, or assessed their impact on HRQoL, leaving significant knowledge gaps. The long-term goal of our research is to optimize medication use and improve HRQoL in patients with cancer. The overall objectives of this application are to (i) elucidate the relationship between race/ethnicity and other sociodemographic factors and the use of SCM, (ii) evaluate if there are differences in the quality of SCM between racial/ethnic groups, and (iii) describe the sociocultural and psychosocial factors that influence SCM use in racial/ethnic minorities. The central hypothesis motivating this research is that racial/ethnic disparities in SCM use exist in PC, and contribute to HRQoL racial disparities in patients with PC. The rationale for this project is that there is a critical need to understand SCM use disparities across racial/ethnic minorities, and identify potential drivers. The central hypothesis will be tested by pursuing three specific aims: (1) Derive a sociobehavioral phenotype that explains SCM use disparities in racial and ethnic minorities with PC; (2) Determine how SCM sociobehavioral phenotype, SCM use, and race influence HRQoL and (3) Identify facilitators of and barriers to SCM use in patients with PC. For aims 1-2, we will use quantitative methods to determine population-level racial/ethnic health care disparities from analysis of the NCI SEER- Medicare, and SEER-Medicare Health Outcomes Survey linked databases and a contextual-level SDoH database from the social and built environment. Aim 3 uses key informant interviews of PC patients, and providers to evaluate the influence of SDoH, psychosocial, and sociocultural factors on SCM use. This project is highly innovative because it will be the first to derive a sociobehavioral phenotype of SCM use disparities in PC using a novel integrated external exposome database that captures multiple dimensions of SDoH. It is also highly impactful because it will provide new insights into the explanatory causes of SCM disparities, their consequences on HRQoL, and the facilitators and barriers to SCM use from multiple perspectives. Ultimately, such knowledge can lead to new discoveries, including SCM prescribing patterns and influences on utilization, and may be applied to other cancer types with high morbidity, mortality, and disproportionate impact on racial minorities.

NIH Research Projects · FY 2025 · 2024-08

ABSTRACT. The aging process involves a gradual deterioration of physical and physiological functions, ultimately leading to mortality. Frailty and muscle weakness are prevalent conditions in the elderly and are strongly associated with negative health outcomes. Unfortunately, there are no treatments available that can mitigate the potentially reversible age-associate decline in physical function, although such interventions could have tremendous impact on the health care system. Recent studies have revealed a strong correlation between elevated levels of L-kynurenine (L-Kyn) and frailty, muscle weakness, and neuromuscular junction degeneration in humans, however a causal relationship has not been tested. L-Kyn is a product of tryptophan breakdown and has been linked to motor neuron death, skeletal muscle atrophy, mitochondrial dysfunction, all characteristics of aging. Skeletal muscle plays a critical role in detoxifying L-Kyn into neuroprotective kynurenic acid via kynurenine aminotransferases (KATs). Interestingly, KAT4, a mitochondrial isoform, declines with age and distinguishes healthy aging from sarcopenia. L-Kyn also activates the aryl hydrocarbon receptor (AHR), a transcription factor involved in regulating gene expression and functioning as an E3 ubiquitin ligase. Chronic AHR activation has shown toxicity in various cells but has not been explored in the context of frailty and age-related physical decline. Based on supporting data, I hypothesize that elevated kynurenine levels and increased AHR activity play a causal role in the decline of physical function during aging. In this fellowship, I will use novel genetic mouse models to test if elevated L-Kyn, skeletal muscle L-Kyn degradation, and AHR activation in muscle are mechanistic drivers of the decline in muscle and physical function with aging. In addition to advanced training in aging biology, mitochondrial energetics, and muscle physiology, a robust career development program including scientific communication and training for leadership in academia have been developed. This training will prepare the applicant to become an emerging leading in aging research and attain a tenure-track position at a research-intensive academic institution.

NIH Research Projects · FY 2025 · 2024-08

PROJECT SUMMARY/ABSTRACT Autoantibodies initiate inflammation and tissue injury in patients with autoimmune disease. Antibody specificity (for both foreign- and self-antigens) is determined by clonal selection, which is a function of survival and proliferation of B cells at key developmental and peripheral activation bottlenecks. Autoreactive B cell clones are primarily removed by apoptosis-dependent negative selection, and foreign antigen-specific B cells are mainly amplified by proliferation-driven positive selection. The same extracellular ligands (e.g., CD40L and BAFF) that drive positive selection of protective B cells also rescue self-specific B cells from apoptotic negative selection. A key limitation in the field is that we do not currently understand the mechanisms underlying B cell responses to selection ligands that distinguish between foreign-reactive and autoreactive B cells. We have found that the ubiquitin ligase Itch, an essential autoimmune suppressor, specifically promotes apoptosis in negatively selected B cells exposed to survival ligands, but not B cells responding to normal positive selection cues. CD40L and BAFF activate the mammalian target of rapamycin complex 1 (mTORC1) in B cells, inducing an array of metabolic changes to support proliferation and survival, ultimately dictating selection. Mitochondrial oxidative phosphorylation has recently emerged as an essential regulator of apoptosis. We found that Itch regulates a downstream branch of mTORC1-dependent mitochondrial oxidative phosphorylation through a distinct mechanism from its role in limiting upstream mTORC1 activation. This proposal will define Itch-regulated metabolic pathways in B cells that distinguish selection of foreign-antigen specific as compared to autoreactive B cell responses.

NIH Research Projects · FY 2025 · 2024-08

Project Summary Kaposi's sarcoma-associated herpesvirus (KSHV) is an oncogenic gammaherpesvirus with a biphasic lifecycle associated with several diseases such as Kaposi's sarcoma and primary effusion lymphoma (PEL). It is primarily spread through saliva making the oral cavity a critical site for initial infection. KSHV encodes an immediate early virion-associated tegument protein that is vital for efficient lytic reactivation and virus production. Following up on a proteomics study of KSHV factors in uninfected cells, our coimmunoprecipitation and imaging analysis in primary effusion lymphoma (PEL) cells during lytic reactivation of KSHV demonstrated that an immediate early protein of KSHV interacts with host transcription factors, FOXK1 and FOXK2. FOXK1 and FOXK2 belong to the Forkhead family of transcription factors. FOXK1 and FOXK2 are unique as they are the only Forkhead proteins which carry a Forkhead-associated (FHA) domain. FOXK proteins are ubiquitously expressed and play a key role in cellular processes such as cell cycle regulation, cancer development, and autophagy regulation. Their role in KSHV infection is not well understood though. Preliminary data from this proposal supports a pro-viral role for these host transcription factors during KSHV's lytic cycle. The purpose of this project is to dissect the importance of the interaction between the immediate early KSHV tegument protein and FOXK proteins and identify novel targets genome-wide of the immediate early KSHV tegument protein during reactivation and de novo infection. A combination of genome-wide studies coupled with KSHV mutants will be used to analyze how the FOXK and immediate early tegument proteins affects KSHV infection. In summary, I predict that this novel host-pathogen interaction might be engaged by KSHV, in order to promote its lytic cycle in the oral cavity and beyond, thus by understanding the mechanism, we could uncover future therapeutic targets. The completion of this project will provide in-depth training in epigenetics, virology and genomics approaches. These skills will be enhanced in the outstanding research environment provided by the Oral Biology department at the University of Florida College of Dentistry.

NIH Research Projects · FY 2025 · 2024-08

Abstract Dental caries is the most prevalent chronic infectious disease, affecting an estimated 2.5 billion people worldwide. Streptococcus mutans is an important pathogen in dental caries due to its ability to acidify the oral pH, inhibiting the growth of health-associated non-aciduric bacteria and narrowing the diversity of the oral microbiota. Candida albicans has emerged as a synergistic partner to S. mutans in dental caries, with the two organisms being co-isolated from early childhood, root, and dentinal caries. Dual-species S. mutans-C. albicans biofilms demonstrate enhanced matrix formation, cariogenicity, and stress tolerance including chlorhexidine and hydrogen peroxide. Hydrogen peroxide has a more than century-long history of oral use for its anti-microbial effect. Many oral hygiene products including mouthwashes and toothpastes incorporate hydrogen peroxide. While hydrogen peroxide has shown to be efficacious as an adjunct in treating periodontitis, its anti-caries effect is less studied. Interestingly, S. mutans is relatively susceptible to oxidative stress in comparison to health-associated oral streptococci. However, the enhanced oxidative stress tolerance of S. mutans in co-culture with C. albicans may reduce hydrogen peroxide's effectiveness as an anti-caries agent. C. albicans encodes a robust set of oxidative stress tolerance genes. Notably, these include 6 superoxide dismutase (SOD) enzymes (3 of which are extracellular) and a catalase enzyme, which detoxify superoxide to hydrogen peroxide and hydrogen peroxide to water, respectively. S. mutans encodes only a single SOD enzyme. Our working hypothesis is that C. albicans oxidative stress tolerance enzymes, catalase and extracellular SODs, enhance S. mutans oxidative stress tolerance in S. mutans-C. albicans biofilms. The goals of this application are to elucidate the mechanism of C. albicans protection of S. mutans oxidative stress tolerance in vitro and in vivo. To accomplish these goals the PI will utilize biofilm, survival, interruption, and confocal microscopy assays (Aim 1) and rat caries model (Aim 2) to determine the roles of C. albicans catalase and extracellular SOD enzymes on S. mutans oxidative stress tolerance and subsequent cariogenicity Knowledge gained from this study will provide a novel target for disruption of S. mutans-C. albicans synergism and the highly cariogenic biofilms these organisms produce. Additionally, the comprehensive training plan provided will further the PI's development to a well-rounded dental researcher through formal coursework, opportunities to learn new techniques, mentor students, improve scientific presenting and writing skills, balancing dental practice and research, and networking with other dentists and scientists at conferences.

NIH Research Projects · FY 2025 · 2024-08

PROJECT SUMMARY/ABSTRACT The primary goal of this proposal is to provide a framework of methodologically-diverse, and clinically-inclined, investigative training that will prepare the principal investigator for a successful career as a translational physician-scientist. In addition to MD/PhD-specific professional development and expanded clinical/translational training, much of this preparation will come from technical education gained from the execution of this proposal’s research aims. These aims seek to broadly understand the placental correlates of fetal congenital heart defects (CHDs) in pregnancies affected by pregestational maternal diabetes mellitus (DM). It is recognized that the placenta plays a critical role in the development of fetal CHDs in early pregnancy, although this role is poorly understood. DM-affected pregnancies also have a pronounced phenotype of placental dysfunction, although the mediators of this also remain unknown. Additionally, DM-affected pregnancies are at substantially elevated risk of developing fetal CHDs and, for certain subtypes of CHD, carry an RR as high as 13.8. These CHDs represent a large percentage of critical and surgery-necessitating defects and are particularly high-burden, as they come with risk of additional malformations, neonatal hypoglycemia, preterm birth, and other perinatal complications. These complications, many of which are also seen in DM pregnancies, come downstream of cyclical exacerbations of placental dysfunction due to CHD-induced fetal hemodynamic changes. Given this, investigation of the pronounced changes in placental function seen in DM and/or CHD-affected pregnancies could yield extremely impactful information for both diagnostic and prognostic management of CHDs in diabetic pregnancies. The identification of pathway-level molecular changes, and their clinical associations, in pregnancies affected by DM, fetal CHDs, and both (DM+CHD) will produce novel and foundational information that could change the paradigm of perinatal care in these pregnancies. The overarching hypothesis of this project is that similar profiles of angiogenic and inflammatory molecular dysfunction, and resulting clinical pathology, will be observed in both maternal DM-affected and fetal CHD-affected pregnancies, and that this dysfunction will be particularly exacerbated in DM-affected pregnancies that also develop fetal CHD. This hypothesis will be tested via two aims. One aim will use large-scale institutional health data to assess the perinatal risk of common obstetric and neonatal complications in DM+CHD pregnancies relative to those affected by either pathology in isolation. The other will characterize the cell type-specific molecular dysfunction of DM, CHD, and DM+CHD placentas using high-throughput RNA sequencing, western blotting, and immunohistochemistry. In completing this training plan, and the scientific aims it includes, the applicant will receive critical didactic and experiential training necessary to achieve the long-term goal of their career, which is to multimodally improve the prevention and management of CHD- and DM-affected pregnancies, through improved perinatal risk-assessment, targeted prenatal therapy/supplementation, or serum biomarker identification for early diagnosis.

NIH Research Projects · FY 2025 · 2024-08

PROJECT SUMMARY Approximately half of all cancer patients in the United States are treated with external beam radiotherapy (RT), with approximately 40% of all curative treatment being attributed to it. Modern treatment planning systems (TPS) are designed to optimize the target dose distribution such that the dose to the tumor volume is maximized and doses to surrounding organs at risk are minimized. While this approach is successful in reducing the severity of deterministic organ toxicities, there is mounting evidence to suggest that stochastic, radiation-induced second primary cancer (SPC) risks are a serious concern following RT treatment and should be considered in TPS dose engines. This is presently impractical due to the limited anatomical information present in the patient’s planning computed tomography (CT) image studies. Furthermore, TPS that do compute doses to near- and out-of-field organs either grossly underestimate their magnitudes or neglect to compute them entirely. A whole-body computational phantom, with anthropometric parameters based on the patient’s demographic, could supplement the limited geometric information present in the planning image. Implementing this model into a system-specific Monte Carlo radiation transport simulation would then provide a practical means to compute doses to organs distal to the treatment field with a high degree of accuracy. Previous work at the University of Florida has produced the largest adult and pediatric computational phantom libraries to date, representing individuals of both biological sexes over a wide range of heights, weights, and ages. Given this information, I hypothesize that computational phantoms produced by merging CT planning images with patient-matched tetrahedral mesh-type phantoms can be used to compute accurate near- and out-of-field organ doses and concomitant SPC risks following RT, with potential for clinical implementation, medical record supplementation, prospective TPS dose optimization, and future epidemiological studies. The proposed project will achieve this through the completion of the following Specific Aims: Aim 1: Develop a system for generation of whole-body patient-specific mesh phantoms from radiation therapy treatment planning CT images. Aim 2: Construct Monte Carlo radiation transport source terms for external beam radiotherapy systems and assess normal organ doses and concomitant SPC risks following radiotherapy treatment. The development of this system will fulfill an urgent need for RT dosimetry methods which compute dose and SPC risk for all organs in the body post-treatment.

NIH Research Projects · FY 2025 · 2024-08

Project Abstract 1.2M people are living with HIV (PWH) in the US. With advances in antiretroviral therapy, the survival of PWH has increased; half of PWH are over the age of 50. Given the number of older PWH is steadily increasing, this has become a new population of interest in aging research. Older PWH face a 60% increased risk of dementia with different risk profiles for neurological disorders compared to the general population. Specifically, disparities in dementia diagnoses and care are deeply rooted in social determinants of health (SDoH), yet, the dementia risk in PWH has not been well-characterized considering disparities including SDoH—a growing concern in HIV- aging research. Currently, there is no cure for dementia, thus, it is vital to develop strategies for early recognition of dementia and provide interventions on modifiable factors early to delay its onset. Developing an early warning system (EWS) using risk prediction models enables the detection of PWH at a high risk of dementia, supporting timely biobehavioral interventions. However, no such EWS exists for PWH. The proliferation of real-world data (RWD) such as electronic health records (EHRs) and claims data, leveraging artificial intelligence (AI), particularly machine learning (ML), offers unique opportunities to generate real-world evidence (RWE) for HIV- aging research. This proposal creates a cohort of older PWH with all-cause dementia including Alzheimer’s disease (AD) and AD-related dementias (ADRD) using a unique RWD source—OneFlorida+ network (20M patients from Florida, Georgia, and Alabama) integrated with both individual- (e.g., education, social cohesion) and contextual- (e.g., neighborhood characteristics) SDoH. Built upon this unique resource, our study has two objectives: (1) examine disparities in the risk of dementia among PWH≥50 by leveraging large-scale RWD linked with SDoH data and (2) prototype a prediction model for an EWS that identifies PWH at a high risk of dementia. The Specific Aims are: (1) developing computable phenotypes and natural language processing methods and tools to systematically extract key characteristics and relevant outcomes using RWD; (2) developing ML-based prediction models and examining disparities in the risk of dementia among older PWH; and (3) applying a user- centered design approach to prototype an EWS for detecting older PWH with high risk of dementia. Findings will serve as the foundation for R01 submissions focused on the expansion of EWS as an AI-driven clinical decision- support tool optimizing early detection of PWH at a high risk of dementia and the development of biobehavioral interventions supporting the control of ‘realistically modifiable’ SDoH factors for delay of dementia onset that can be used in PWH’s everyday life. Mentors are committed to the candidate’s training, each providing unique expertise to the research and training plan. This K01 application, consistent with the NIA’s mission, will support the candidate’s development as an interdisciplinary scientist with a triple background in AI, data science, and HIV aging research, dedicated to developing data-driven approaches based on RWE for reducing disparities and promoting healthy longevity for older PWH.