University Of Florida

NIH Research Projects · FY 2025 · 2024-08

Autistic people are at increased risk of suicide behaviors (SB), including suicidal ideation and suicide attempts, and have higher rates of suicide death compared to non-autistic people (use of ‘autistic’ reflects community language preferences). Yet there is limited understanding of the mutable factors related to risk of SB for the autistic population. Beyond biological and behavioral traits, research with the general public reveals multiple social determinants of health (e.g., community-level resources, health policies) contribute to risk of SB. However, the impact of individual, community, and policy factors on risk of SB in the autistic population is unknown. Meaningful improvements in policy and practice will require an understanding of (1) how risk of SB clusters for autistic individuals across interdependent individual, community, and policy factors and (2) the current state of mental health service (MHS) provision among autistic people. To contribute to the long-term goal of reducing risk of SB for the autistic population, this project uses a sequential, mixed methods design, in collaboration with an established team of autistic stakeholders and policy and practice experts, to analyze multilevel, socioecological factors associated with risk of SB and receipt of MHS and to generate community-supported recommendations for suicide prevention. Aim 1 will identify clusters of socioecological factors (at individual, community, and policy levels) associated with risk of SB among two national samples of autistic youth and adults. Autistic people (aged 12-64) will be identified in two national healthcare claims databases (MarketScan private, CMS Medicaid) and integrated with public use and proprietary databases to create multilevel, longitudinal datasets containing individual, community, and policy factors. Data reduction, hierarchical clustering, and multilevel analytic techniques will partition individuals into homogeneous groups based on shared characteristics to identify underlying factors associated with risk of SB among autistic people. Next, using the databases developed in Aim 1, Aim 2 will evaluate socioecological factors associated with MHS receipt (psychotherapy, pharmacology, both, neither), dose (visits/year), and delivery modality (face-to-face, telemental health, both) for autistic people with documented SB and/or co- occurring mental health conditions. Informed by critical findings from Aims 1 and 2, through collaboration with autistic stakeholders and focus groups with additional autistic adults, family caregivers, and MHS clinicians, Aim 3 will establish community-supported recommendations to reduce risk of SB and facilitate receipt of MHS. In response to RFA PAR-23-095 and aligned with the NIMH strategic plan, this project will optimize real-world data collection systems to characterize clusters of multilevel risk factors of SB and factors associated with receipt of MHS among autistic people. Study results will produce translatable, community-informed evidence and recommendations aimed at reducing risk of SB and improving MHS delivery for autistic people.

NSF Awards · FY 2024 · 2024-08

This project aims to create an AI-powered framework that helps designers automatically evaluate the environmental impact of their designs and optimize them for sustainability. This research overcomes several key challenges in sustainable design practices, including the scarcity of lifecycle inventory (LCI) data essential for lifecycle assessment (LCA), the lack of accurate tools for including product lifespan uncertainties in LCA prediction, and the absence of an inclusive decision-making framework that integrates environmental and technical considerations. This project develops advanced AI algorithms such as graph attention networks (GATs) and reinforcement learning (RL) to advance design science and national manufacturing prosperity. It augments designers’ abilities to quickly update design alternatives that align with sustainability practices and provides manufacturers with faster and more accurate tools to assess the environmental impacts of their products, aiding in the development of software packages to measure corporate social responsibility. This framework supports sustainable development within engineering design and extends its applications to decision-making throughout the product lifespan and supply chain. Furthermore, this work aligns with national interests by promoting scientific progress, supporting sustainable manufacturing, and advancing STEM education, particularly through undergraduate research experiences and K-12 activities. The objective of this project is to establish a cutting-edge AI-driven framework for sustainable design that cohesively integrates advanced eco-design algorithms with product LCA and sustainability evaluation, setting a new standard in optimizing design alternatives. To achieve this objective, this research will implement several key innovations: (i) develop novel GAT algorithms to extract LCI data by analyzing similarities with existing designs that possess known LCI data, thereby addressing the issue of data scarcity essential for LCA; (ii) create advanced algorithms inspired by Markov process simulations to model the heterogeneity and stochasticity of product lifespans, thereby significantly improving the accuracy of LCA predictions; and (iii) establish a decision-making framework based on a novel non-lexicographic multi-criteria RL algorithm to facilitate the simultaneous evaluation of environmental and technical considerations and produce Pareto-optimal design alternatives. This integrative approach will combine the data extraction capabilities of GAT algorithms and the LCA prediction accuracy provided by Markov process simulations to transform sustainable design practices. This researched framework will be rigorously evaluated through its application in designing consumer electronics, including smartphones, tablets, and laptops. This collaborative project between the University of Florida and Florida International University combines expertise in engineering design, lifecycle assessment, circular economy, optimization, and artificial intelligence. Educational initiatives will include the organization of industry and academic webinars and workshops, provision of timely training for students, and promotion of STEM education with an emphasis on underrepresented groups. 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 · 2024-08

The goal of the proposed project is to test the effectiveness of a primary care-situated intervention focused on motivating and guiding patients to use empirically supported, freely available online tools for weight loss, including a commercial platform for goal setting and self-monitoring of diet, physical activity and weight (MyFitnessPal) and online communities providing support for weight loss. Over 40% of US adults live with obesity and approximately 35% with overweight, increasing their risk for poorer health, lower quality of life, and higher mortality. The primary care setting has significant potential to help connect patients with effective weight loss programs and tools, given evidence that primary care providers (PCPs) can motivate health behaviors. Despite the potential, due to numerous implementation barriers, PCPs rarely connect patients to empirically supported weight loss approaches. To address these challenges, UTOOLS (Understanding and Treating Overweight and Obesity for Weight Loss Success) was developed with primary care implementation as a central focus. The novel approach takes advantage of freely available existing online tools to support weight loss. To support effective and sustained engagement of patients with these online tools, UTOOLS delivers an interactive “Kickoff” (short videos and personalized feedback) prior to a scheduled PCP appointment, followed by 52 weeks of text messages and emails targeting psychosocial constructs that are hypothesized to influence online tool engagement. UTOOLS takes advantage of the influence of PCPs through PCPs’ “virtual endorsement” of UTOOLS, yet does not rely on PCPs to initiate a discussion about weight and maximizes flexibility of the PCP during clinic time. Pilot studies support the potential of UTOOLS for effectiveness, the feasibility of the proposed trial design, and the potential for implementation in a clinical setting. To test the 52-week UTOOLS intervention, a randomized trial will be conducted in primary care clinics. Fifteen to 20 PCPs will be recruited and enrolled, followed by 453 of their patients across clinics with strong representation from groups under-represented in weight loss interventions, including African American/Blacks, Latinos, men, and individuals with lower income. Patients will be randomized to complete either the 52-week UTOOLS intervention or a 52 week educational control. The primary outcome is the proportion of patients achieving >3% weight loss at 52 weeks. At the same time as effectiveness is evaluated, essential data to inform future real-world implementation will be gathered. The evaluation plan includes a focus on testing a model of engagement with the online tools to inform future digital health interventions. If effective and favorably received by stakeholders in the proposed trial, UTOOLS has substantial potential to be implemented broadly, aided by its use of existing online tools, limited PCP and clinic burden, and ability to be largely delivered autonomously.

NSF Awards · FY 2024 · 2024-08

This project aims to serve the national interest by improving the proof-writing abilities of undergraduate students. This Level II IUSE project, part of the Engaged Student Learning track, intends to accomplish this by training an innovative artificial intelligence model to provide feedback on student proofs to support both college students in proof-oriented mathematics courses and the post-secondary faculty who are teaching them. The project will create a website to demonstrate the model: students will be able to use the website to write proofs, receive immediate feedback on their proofs, and revise and resubmit new drafts for feedback. This model is not intended to replace the work of mathematicians as teachers, but to offer an important tool to faculty - one that gives students immediate, iterative, researched-based feedback on their written proofs in ways that exceed what is practical for professors to provide, and also attends to the needs of diverse learners. To reach its goals, the project will take a Constitutional AI approach, convening a group of experts in proofs, equity, and college-level mathematics teaching and learning to build a constitution that will guide the development and training of a Large Language Model (LLM) specifically trained to give feedback on student proofs that is in line with the constitution. Project research will focus on how the LLM serves students and faculty. The constitution will drive the development of the LLM and will be available for use to support future AI interventions and educational technology work. This work will advance understanding of how students learn to write proofs, how artificial intelligence can be used to support student learning, and how constitutional AI approaches can be used to align artificial intelligence with educational values and priorities. The NSF IUSE: EDU 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.

NSF Awards · FY 2024 · 2024-08

Almost all organisms have separate male and female sexes, but this common dynamic holds a contradiction: males and females are physiologically different from each other, sometimes extremely so, but share almost the same set of genes. How do differences between the sexes arise from a shared set of genetic starting points and why do various species show wildly different degrees of sex differences? This research seeks to answer these fundamental questions using a remarkable group of insects, the bagworm moths. Both male and female bagworms start life as caterpillars that carry around a protective silk bag as they feed and grow. Males always mature into winged adult moths, but females can develop very differently depending on the species. In some species, females mature into winged moths whereas in others, females either never develop wings and remain much like a larva and crawl to find a mate, or do not develop legs or eyes and never leave their bag. By studying this diverse group of insects and their relationships, researchers will gain a better understanding of how sex differences are genetically controlled and why they vary across the tree of life. This project will provide training in systematics for two postdoctoral researchers and three graduate students. The researchers will collect bagworm species from around the globe to first construct a phylogeny of bagworms to determine how many independent transitions of sexual dimorphism have occurred. They will also test how larval bag structure, local climate, and other variables influence the evolution of sexual dimorphism. Researchers will generate genomic resources for key species exhibiting different levels of dimorphism to uncover the genetic mechanisms that control sexually dimorphic development in each case. This work will uncover the molecular underpinnings of novelty, discerning whether bagworms employ a common molecular framework or have evolved convergent strategies to achieve similar levels of dimorphism. Finally, researchers will assess the role of adaptation in the evolution of sexual dimorphism by testing for positive selection in genes expressed in males only or females only, especially on the sex chromosomes, which harbor many sex-biased genes. This work will help resolve outstanding questions of evolutionary genetics on the role that sex chromosomes play in adaptation across the genome. Results of this work will be disseminated to the broader community through a number of avenues including peer-reviewed publications, conference talks, a museum exhibit at the Florida Museum of Natural History, and a web comic distributed on social media. 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 · 2024-08

The goal of this research project is to apply new methods to reliably characterize the extent of capital breeding in three sea turtle species and to test whether reproductive strategy is related to environmental conditions. Reproduction is one of the most basic and important aspects of animal life history. Capital and income breeding represent opposite strategies to fuel reproduction, with capital breeders relying on stored energy, and income breeders relying on food intake during the reproductive period. Sea turtles were long thought to be capital breeders and to fast during reproduction because of the long migrations they undergo from their foraging grounds to nesting areas. However, increasing evidence suggests that some individuals feed during this time. Two major challenges in understanding sea turtle reproductive strategies are that the methods to determine whether sea turtles feed between successive nesting events have not been reliable, and the drivers of variability in breeding strategies are not well understood. Thus, the research will fill an important gap in knowledge about sea turtle energetics and reproduction, with implications for conservation and management of these endangered species. Training and learning opportunities will be provided to a diverse audience, including an undergraduate immersion course in sea turtle biology and conservation, with an emphasis on effective science communication methods. In addition, the methods and theories of isotopic analyses will be incorporated into a graduate-level class, contributing to training and workforce development. The sea turtle clade offers the opportunity to explore variation in reproductive strategy in the context of environmental conditions. The proposed study will (1) characterize variability in capital breeding within and among three sea turtle species and determine how nutrients are allocated to the synthesis of egg components and (2) relate breeding strategy to environmental characteristics and reproductive success. Stable isotope analysis has a long history of identifying trophic and movement patterns in animal ecology, but recent advances allow carbon and nitrogen isotopes to be measured in individual amino acids. This project uses that method to provide a biochemical fingerprint of capital breeding by classifying the source of nutrients (endogenous vs. exogenous) used to fuel metabolism and produce eggs. Identifying the source of nutrient allocations to reproduction can illuminate the evolution of basic life-history trade-offs and characterize the links between organismal physiology and the environment across the annual cycle in these migratory marine consumers. This CAREER award provides a lens through which to elucidate mysteries about reproductive strategies for a group of animals of conservation concern, demonstrates application of novel technologies, and delivers educational components that bridge international experience with science communication. A graduate student and post-doctoral fellow will be involved in the research, and the research team will participate in local outreach activities to a non-scientific audience. 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 · 2024-08

Project Summary Substance use disorder (SUD) is characterized by recurrent drug-taking behaviors that often resemble the renewal-induced relapse after a successful extinction-based therapy. This inability of transferring the learned extinction as the subjects are re-exposed to the original drug context (i.e., their homes) is associated with deficits in neural regions such as the nucleus accumbens (NAc), which regulates the extinction of drug-associated memories and its ability to maintain voluntary abstinence. For instance, addicts developing addiction in a particular context “A” may extinguish the responses for drug-associated cues in a clinical context “B”, but when re-exposed to the same cues in context “A”, fail to transfer the learned extinction to suppress the context-induced renewal/relapse. Thus, because the ability to cease drug-seeking relies on overcoming drug-associated memories, extinction represents a preclinical opportunity to characterize and manipulate the molecular substrates underlying drug-seeking behavior to overcome the renewal-associated relapse. While drug self-administration (SA) leads to numerous neuroplasticity changes in the reward circuit, little is known about the impact of extinction training in reprogramming the addiction-relevant behavioral and transcriptomic codes/outcomes of the brain reward circuit. Together, these research questions pose a platform to delineate my current personal and professional training plan, which will be applied as I transition to a faculty position. Under the tutelage of my primary mentors (Drs. Eric Nestler: sponsor and Paul Kenny: co-sponsor) and my mentoring committee (Drs. Mary Kay Lobo, Yavin Shaham, Li Shen and Fabricio Do Monte), I will use RNA-sequencing of NAc subregions (core and shell) of rats receiving cocaine-SA and contextual extinction (AAA vs ABA) or withdrawal (no extinction) procedures, to characterize the drug-associated memories (phenotypes; renewal vs. extinction), at the transcriptional level (Aim 1). Subsequently, to manipulate the resulting behaviors, I will be targeting the transcriptome of NAc subregions and cell types. Specifically, I will design novel viral vectors to perform viral-mediated gene transfer to manipulate a top hub gene (i.e., transcription factor) previously proven or newly deduced as a main driver of renewal-induced relapse (failure of extinction transfer) in a subregion and cell-specific manner in NAc. As for the cell-specific manipulations, I will be utilizing the novel transgenic rat model expressing Cre-recombinase in dopamine D1 or D2 medium spiny neurons (MSNs) (Aim 2). Purposely, because life situations involving conflict between abstaining from or taking a drug due to adverse consequences are a key feature of relapse, I will test the impact of extinction training on restoring adaptive decisions in a conflict-based model (Aim 3), where drug seeking leads to punishable outcomes (i.e., footshocks), to delve deeper into the neurobiology of extinction/renewal that is most relevant to people.

NSF Awards · FY 2024 · 2024-08

Viral agents constantly threaten humans, livestock, and crops. Many viruses have RNA genomes. In the most extreme case, noncoding RNAs alone (i.e., viroids) can infect crops leading to production losses. For instance, consider the cases of oil palm and coconut palm; approximately 40 million palms were killed by viroids between 1980 to 2007 due to the lack of effective treatments. Climate change is projected to increase cross-species viral transmission risks and pose risks of new viroid and virus outbreaks. Thus, it is imperative to explore potential solutions for sustainable agriculture. Unfortunately, there is no effective measure available to combat viral or viroid diseases in crops. Given that RNA structures are often the functional basis for infectious RNAs (i.e., RNA viruses and viroids) to achieve a successful infection, understanding those RNA structures with functional implications will likely provide targets for blocking infection. Based on recent breakthroughs from the research team, this proposal will develop state-of-the-art technologies to outline a comprehensive atlas of viroid RNA structures in plant cells and improve understanding of structure-based viroid infection. The knowledge gained here will ultimately lay the foundation for screening structure-targeting anti-viroid drugs to combat viroid diseases. Moreover, next-generation scientists, including undergraduate, graduate students, and postdoc researchers, will receive high-quality training. It is well-known that RNA structures exhibit dynamic folding patterns in cellular environment for exerting functions. However, current understanding of most RNAs was based on thermodynamic modeling or limited in vitro probing data. The research group will characterize both spatial and temporal landscapes of viroid RNA structures in living plant cells using a comprehensive experimental design. By employing cutting-edge chemical probing techniques and computational algorithms, this project will determine the in vivo RNA structure landscapes of viroids in different subcellular locations and the potential biological significance. The study will span multiple time points to create a comprehensive atlas of viroid structurome dynamics throughout the infection process. In particular, understanding in vivo RNA structure features in regulating the intracellular movement of viroids will be a major goal. Notably, warm temperatures lead to more severe foliage symptoms and significant potato yield loss by viroid infection. The risk of new outbreaks of viroid diseases is projected based on global climate change. Hence, this project will also outline viroid RNA structural alterations in response to high temperatures. The research tools developed in this project will aid the broader RNA biology research community. 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 · 2024-08

Project Summary/Abstract Ankle contractures in muscular dystrophy: mechanisms and tissue adaptations Duchenne muscular dystrophy (DMD) is a genetic disorder that causes progressive muscle degeneration and weakness leading to difficulties walking, using the arms, and breathing. In addition to muscle weakness, individuals with muscular dystrophy often lose flexibility in joints such as their ankles, knees, hips, elbows, and hands. This loss of range of motion, called a contracture, can cause difficulty with function, positioning, and comfort. The loss of ankle joint range of motion and development of plantarflexion contractures affects nearly all children with DMD while they are still able to walk, and contracture prevention and management is a major goal of rehabilitation for ambulatory children with DMD to allow for maximal function and quality of life. However, there is little convincing evidence to demonstrate that currently prescribed contracture interventions are effective or improve function, and this is likely due to a gap in knowledge about the pathophysiology of contracture development in DMD. The goal of this proposal is to prospectively evaluate the potential mechanisms driving loss of ankle range of motion in DMD and the plantarflexor muscle and/or tendon changes that result. Our central hypothesis is that progressive proximal muscle weakness and degeneration drives ankle contracture development in ambulatory children with DMD and that the primary adaptation in the plantarflexor muscle-tendon unit is shortening of the Achilles tendon. In aim 1, we will quantitatively evaluate lower extremity muscle strength and muscle replacement by fat using magnetic resonance imaging (MRI) to evaluate the impact of muscle weakness and degeneration on ankle joint dorsiflexion range of motion in ambulatory individuals with DMD. In aim 2, we will evaluate the tissue adaptations occurring alongside loss of joint range of motion including changes in plantarflexor muscle length, Achilles tendon length, Achilles tendon structure, and muscle-tendon passive stiffness. Data collected from this study will help physical therapists and other rehabilitation professionals better understand the causes of ankle contractures in muscular dystrophy, which will lead to more evidence-based decisions about targeted interventions that may help prevent or slow contracture formation.

NSF Awards · FY 2024 · 2024-08

Talin plays a pivotal role in forming multicellular tissues, governing crucial cellular functions such as adhesion and motility, which are implicated in various human diseases. By coordinating the recruitment of essential regulatory elements at focal adhesions, talin facilitates their formation and influences cytoskeletal dynamics, profoundly impacting cell adhesion mechanisms. This project seeks to discover how the structural properties and post-translational modifications affect the function of talin. This project will determine near-atomic resolution cryogenic electron microscopy structures of talin in its phosphorylated active state and its interaction with F-actin. Biochemical assays and live cell experiments will yield a comprehensive understanding of the function of talin in cellular adhesion processes. The PI is deeply committed to outreach activities to foster scientific curiosity and learning among younger students. This project will strive to inspire the next generation of scientists through workshops, mentorship programs, and involvement in science fairs. Talin occupies a central position in cell adhesion, primarily by activating integrins into high affinity states and facilitating the connection between integrins and the cytoskeleton. This research project will use the first Japan Electron Optics Laboratory (JEOL) 300 kV cryogenic Atomic Resolution Microscope (cryoARM300) installed in the US to determine the near-atomic resolution structures of talin. The actin-bound form of talin and its effects in the regulation of adhesion dynamics in live cells will be determined. This project will also determine near-atomic resolution cryoEM structures of talin in its phosphorylated active state and complement the data with biochemical and in live cell experiments. Thus, significant mechanistic insights into cell adhesion will be obtained on a new cryo-electron microscope in the US that has aided near-atomic resolution insights into many biological processes. This project is supported by the Molecular Biophysics Cluster in the Division of Molecular and Cellular Biosciences. 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 · 2024-08

The research seeks funds to study in detail the enigmatic compact intracloud lightning discharges (CIDs) that are triggered at higher altitudes (e.g., in convective surges penetrating into the stratosphere) by energetic (>1016 eV) cosmic ray showers (CRSs). CIDs are known to be the strongest natural producers of VHF radiation on Earth. Most CIDs are solitary, some serve to initiate ordinary lightning, and some occur in clusters. They were discovered in 1980, but their nature largely remains a mystery, because they are brief, hidden inside the cloud, and usually produce no detectable visible light. One of the objectives of the suggested work is to solve the inverse problem to separately obtain, for the first time, the CID current and CID channel length from calibrated multiple-station electric field measurements. Expected results have important implications for our basic understanding of non-conventional (streamer-based) lightning phenomena and energy coupling between the different layers of Earth’s atmosphere. The project outcomes will be also useful in a number of other disciplines, including atmospheric electricity, high-energy atmospheric physics, meteorology, lightning detection, and plasma physics. The studies will serve to foster international collaboration and involves participation of graduate students. The projects will address new science questions that are relevant to the primary objective of the CEDAR Program, which is “to understand changes in the atmosphere over short- and long-time scales” and are: (a) What are the electric parameters of CIDs, including currents and charge transfers? (b) Can a large, low-conductivity (essentially cold) streamer formation that constitutes the body of CID support traveling waves? (c) What is the largest altitude at which CIDs occur and what is the origin of post-CID activity? This effort will lead to acquisition of a large data set, compare three different methods for estimating CID heights and search for “outliers” to investigate events that occur above the average height. The researchers plan to study the recently discovered secondary pulses that follow the main CID waveform attributed to the so-called blue events (BLUEs) at cloud tops. Success will be primarily gauged by publications, presentations at conferences, graduate degrees awarded, and high-school and undergraduate students involved. 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 · 2024-08

Polymer membranes offer an energy-efficient, cost-competitive solution for separating gas molecules in important industrial applications such as carbon dioxide (CO2) capture and petrochemical separations. For example, conventional processes to purify propylene and ethylene annually consume as much energy as the entire country of Singapore uses in a year. Using membranes to perform these purifications could reduce the energy requirement by up to 90%. Similarly, there is a pressing societal need to develop energy-efficient methods to capture CO2 from various sources. An ideal membrane would contain ultra-thin nanopores that could perfectly separate different gases from each other while remaining extremely permeable to minimize operating costs. However, achieving such ideal structures in practice has proven difficult. This project will develop a new strategy for forming two-dimensional (2D) polymer membranes with gas-selective nanocavities built from aligned molecular rings called macrocycles. The macrocycles will be tailored for high gas permeability and selectivity. This project will create new knowledge of how membrane features like nanopore size, chemistry, and shape affect gas transport through the macrocycle membranes, enabling the design of better membranes for clean energy and sustainability applications. The research will be tightly integrated with new interdisciplinary STEM curricula for K-12 through graduate-level education, emphasizing how polymer engineering is enabling strides toward clean energy and sustainability in the United States. This research project aims to design 2D polymer gas separation membranes with homogeneous size-sieving nanostructures and ultra-thin (<20 nm) selective layers. Rigid, small-molecule calixarene macrocycles with well-defined nanocavities will be crosslinked at an interface to yield thin films with aligned nanopores. Tuning nanopore chemistry will enable control over nanopore dimensions between approximately 0 and 1.5 nm. The central hypothesis is that macrocycle pore size, functionality, and dynamics will affect single and mixed gas transport in nanoporous membranes. This project will experimentally investigate the structure and dynamics of nanoporous macrocycle membranes and reveal how nanopore dimensions and polymer dynamics impact gas sorption and diffusion mechanisms. These studies will then be extended to gas mixtures to reveal the roles of competitive sorption and plasticization on separation performance, with the ultimate goal of upscaling the most promising structures to form composite membranes. Interdisciplinary chemistry and chemical engineering course modules will be developed to explore transport phenomena in various separation applications. A hands-on outreach module on membrane separations will also be designed and targeted to K-12 students. This module will be used for demonstrations in the annual Halloween Molecular Mania event and bi-annual chemical engineering workshop for high school teachers at the University of Florida and hosted online for broader distribution. Successfully achieving this project's research and education goals could result in significantly reduced carbon emissions and chemical and petrochemical separation costs in the United States, as well as growing public awareness of energy and sustainability challenges and engineering solutions. 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 · 2024-08

The planned Center for Science, Technology, and Advanced Research in Space (C-STARS) seeks to form a multidisciplinary hub that supports and serves the rapidly growing sector of space manufacturing. C-STARS brings academic researchers together led by University of Florida and three partner universities (Florida Institute of Technology, Embry-Riddle Aeronautical University and Florida Agricultural and Mechanical University) with spaceflight providers to help industries transition to the space manufacturing sector and improve the production of unique medicines, therapeutics, electronics, and materials that can benefit the people of Earth. The rapid increase in private sector investment and competition has increased the demand for in-space manufacturing technologies and products critical to a new space-based industry. Despite the advantages and expanding access, conducting research and manufacturing in space is limited by experience, data reproducibility, and standardized hardware technologies. C-STARS brings together broad expertise and experience in space research across the State of Florida, including the Florida Spaceport, which is the busiest spaceport in the U.S. to ensure an efficient and effective transition to commercial space research and operations for its industry partners. Additionally, C-STARS will develop new corporate mentoring programs, curriculums, certifications, and internship programs to train the future workforce in this dynamic and rapidly changing field thereby ensuring that the US achieves and sustains global space manufacturing preeminence.   The planned Center for Science, Technology, and Advanced Research in Space (C-STARS) serves as a critical nexus to advance technologies, processes and operation protocols associated with in-space manufacturing to benefit life on Earth and sustain life during deep space missions. Manufacturing in the microgravity environment provides unique physical advantages that cannot be replicated on Earth enabling the production of novel and potentially higher quality products. C-STARS combines the unique experiences, resources, and perspectives of its academic partners to help support industry transition their products and operations to the space environment in areas such as regenerative medicine, diagnostics, artificial intelligence, biomonitoring, bioenergy systems, additive manufacturing of electronics, and materials recycling. Products arising from these thrust areas have the potential to advance cell therapies, mitigate human diseases, recycle space electronics, and improve the overall sustainability of space manufacturing. In proximity to the nation’s busiest spaceport and through partnerships with manufacturing companies, launch providers, and STEM-focused education centers, C-STARS is uniquely positioned to assist companies’ de-risk, high value manufacturing needs, promote large-scale company portfolio growth, and support diverse workforce training. Together, C-STARS creates a sustainable, efficient, and effective collaboration with industrial partners to ensure U.S. maintains its leadership in the field of space manufacturing. 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 · 2024-08

PROJECT SUMMARY Opioids exert their addictive effects by altering signal processing in the reward circuit of the basal ganglia. This action involves multiple adaptations, including changes in neuronal wiring and synaptic transmission. Recent evidence suggests that the glutamatergic system plays a critical role in reward. Particularly, group III metabotropic glutamate receptors (mGluRs) have been recognized for their role in shaping opioid effects Located at presynaptic terminals of neurons, group III mGluRs control the strength of glutamatergic actions and synaptic plasticity of the reward circuit. The overall goal of this research is to understand molecular mechanisms by which opioids alter glutamatergic signaling and wiring of the reward circuit. The focus of this proposal is on ELFN1, a recently discovered cell-adhesion molecule which interacts with group III mGluRs, modulates their function and plays a key role in establishing synaptic connectivity. ELFN1 is selectively expressed in cholinergic interneurons (CIN) in the reward circuit hub – nucleus accumbens (NAc) and its ablation in mice prominently influences opioid effects. Based on accumulated preliminary data, we hypothesize that the trans-synaptic interaction of ELFN1 in CIN with group III mGluRs on glutamatergic afferents in the NAc plays a critical role in the structural and functional plasticity of synaptic communication in the reward circuit to shape opioid effects. This hypothesis will be tested by pursuing three complementary Specific Aims that seek to (1) elucidate the physiological role of ELFN1 in specifying synaptic properties of NAc neurons, (2) determine molecular mechanisms of ELFN1 action and (3) characterize the contribution of ELFN1-mGluR complexes to rewarding effects of opioids. The strategy proposed to address these Aims will entail a synergistic combination of behavioral, genetic, cell-biological, and physiological approaches, exploiting a powerful array of reagents, animal models, and innovative assays to examine role and mechanisms of ELFN1 in the endogenous setting of a nervous system. Such studies are expected to provide critical insights into the role of synaptic cell adhesion molecules in configuring neural circuitry and neuromodulatory receptors involved in reward processing and opioid use disorder.

NSF Awards · FY 2024 · 2024-08

Data science is evolving rapidly and places a new perspective on realizing state-space dynamical systems. Predicting time-advanced states of dynamical systems is a challenging problem in STEM disciplines due to their nonlinear and complex nature. This project will utilize data-driven methods and analyze state-space dynamical systems to predict and understand future states, surpassing classical techniques. In addition, the PI team will (i) guide students to obtain cross-discipline PhD/Master's degrees, (ii) guide students to work in a peer-learning environment, and (iii) educate a diverse group of undergraduates. In more detail, this project will utilize state-of-the-art machine learning (ML) algorithms to efficiently analyze and predict information within data matrices and tensor computations with low-complexity algorithms. Single-dimensional ML models are not efficient at extracting hidden semantic information in the time and space domains. As a result, it becomes challenging to simultaneously capture multi-dimensional spatiotemporal data in state-space dynamical systems. Using efficient ML algorithms to recover multi-dimensional spatiotemporal data simultaneously offers a breakthrough in understanding the chaotic behavior of dynamical systems. This project will (i) utilize ML to predict future states of dynamical systems based on high-dimensional data matrices captured at different time stamps, (ii) realize state-space controllable and observable systems via low-complexity algorithms to simultaneously analyze multiple states of the systems, (iii) analyze noise in state-space systems for uncertainty quantification, predict patterns in real-time states, generate counter-resonance states to suppress them, and optimize performance and stability, (iv) study system resilience via multiple state predictors and perturbations to assess performance and adaptation to disturbances and anomalies, and finally (v) optimize spacecraft trajectories, avoid impact, and use low-complexity algorithms to understand spacecraft launch dynamics on the space coast and support ERAU's mission in aeronautical research. 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 · 2024-07

PROJECT SUMMARY Myocarditis is a leading cause of sudden death in children and young adults but is understudied, especially in children. Viral myocarditis, inflammation of the heart muscle, has been found to involve both the innate and adaptive immune response in adult myocarditis models, but before this study, there were no mouse models for pediatric viral myocarditis; therefore, this is unstudied in the pediatric population. Our long-term goal is to evaluate the development and progression of myocarditis, dilated cardiomyopathy, and heart failure across the lifespan. Our overall objective of this application is to determine how the immune mechanisms differ between pediatric and adult mice and patients leading to and during myocarditis. Our central hypothesis is that younger pediatric mice and patients, before the onset of puberty, will develop a stronger innate and adaptive immune response, leading to severe disease during myocarditis. This hypothesis will be tested with the following two specific aims: 1) Identify the differences in immune biomarkers between pediatric and adult myocarditis patients by sex and age. 2) Determine how age and hormone status alter the immune response, leading to altered viral myocarditis severity in a translational mouse model by sex. Under the first aim, we will utilize 550 adult and pediatric patient blood samples/clinical data to investigate if patient age alters immune biomarkers predicting disease severity based on cardiac function and/or standard laboratory values in myocarditis patients by sex. For the second aim, we will first examine innate and adaptive immune mechanism differences between pediatric and adult mice in myocarditis utilizing female and male 3-week, 4-week, and 8-week-old mice. We will assess differences in the inflammasome, complement, and antibody response at 48, 5 days, and 10 days post-infection. Next, we will investigate the role of sex hormones in pediatric and adult mice to determine if age differences are due to estrogen and testosterone changes during puberty and aging. We will utilize gonadectomy at various ages to study the influence of hormones on innate and adaptive immune responses in male and female mice. Additionally, we will utilize aged male mice and a VCD-induced ovarian failure model in female mice to study the effect of menopause/andropause on myocarditis mechanisms. The research proposed in this application is innovative because it departs from the status quo and studies the differences between pediatric and adult mouse populations using the first pediatric viral myocarditis mouse model. The proposed research is significant because it is expected to identify how the age of patients/mice could influence the innate and adaptive immune response leading to myocarditis severity or progression. This will have a positive impact as it is expected to significantly impact the myocarditis field by providing a mechanistic understanding of how sex, age, and hormone status interplay in response to viral infection during acute myocarditis and will lead to targeted treatments in an individualized manner and provide a better understanding of pediatric disease.

NIH Research Projects · FY 2025 · 2024-07

PROJECT SUMMARY This application aims to use existing data within the All of Us Researcher Workbench to improve our ability to identify cardiovascular disease (CVD) patients treated with statins or antiplatelet therapy (i.e. P2Y12 inhibitors) at increased risk for adverse drug responses and adverse outcomes. In order to manage CVD and prevent adverse outcomes, CVD patients can be treated with multiple medications including lipid-lowering agents or statins and antiplatelet agents such as clopidogrel. There are well known clinical and genetic factors that impact the risk of statin-associated musculoskeletal symptoms (SAMS) with numerous statins and the risk of adverse cardiovascular outcomes with the P2Y12 inhibitor clopidogrel. Despite guidance from expert consensus groups, and regulatory agencies, the implementation of pharmacogenetic testing for statins, and P2Y12 inhibitors has been limited, occurring mostly at large, academic medical centers. Additionally, almost all of the studies conducted to date have been in populations of largely European and Asian ancestry. In order to provide equitable care and fulfill precision medicine for the over 53 million Americans estimated to be treated with statins or P2Y12 inhibitors annually, we need to better understand their usage and associated outcomes in diverse, real-world populations. Our central hypothesis is that precision medicine models derived from diverse, real-world data for SAMS, and adverse outcomes after treatment with an antiplatelet agent, will be more precise and accurate than existing models To test our central hypothesis we will complete the following Specific Aims: 1) Evaluate statin prescribing patterns, adverse drug responses, and adverse outcomes in patients with CVD by SLCO1B1, ABCG2, and CYP2C9 genotypes using electronic-health record (EHR)-based data, genomic data, and data from surveys and wearables, and 2) Characterize antiplatelet prescribing patterns, adverse drug responses, and adverse outcomes in patients with CVD by CYP2C19 genotype using EHR-based data, genomic data, and data from surveys and wearables. To achieve these aims, we will utilize existing data from the All of Us Researcher Workbench. The All of Us Research Program is enrolling a diverse group of persons in the United States, and including multiple types of real-world data (e.g. EHR, demographic, wearables, patient surveys, genomic). We will deploy validated CVD algorithms and determine observed rates of CVD, statin prescribing, and antiplatelet prescribing. We will identify characteristics of SAMS in patients with CVD treated with statins and characteristics of adverse outcomes in patients with CVD treated with a P2Y12 inhibitor. We will also use multivariable regression analyses and machine-learning methods to model adverse drug responses and adverse cardiovascular outcomes. We will examine characteristics and models of CVD patients treated with statins by SLCO1B1, ABCG2, and CYP2C9 genotypes, and of CVD patients treated with a P2Y12 inhibitor by CYP2C19 genotypes. Analyses will be conducted overall, by race and ethnicity, urban versus rural areas, across geographic regions, and by sex as a biological variable.

NIH Research Projects · FY 2026 · 2024-07

Lewy body dementia (LBD) is the second most common form of neurodegenerative dementia, behind only Alzheimer’s disease (AD). LBD is clinically defined as a dementia that arises prior to or within one year of a Parkinson’s disease (PD) diagnosis or PD with subsequent dementia. Post-mortem examination of LBD brains commonly reveals a combined pathology of intraneuronal Lewy bodies along with amyloid plaques and neurofibrillary tangles consistent with AD. As such, LBD is considered one of the Alzheimer’s disease and related dementias (ADRDs). A small subset of genes implicated in other neurologic diseases influence risk for LBD (e.g. GBA1, APOE), while many genes determinant for familial forms of AD or PD do not. These data suggest a meaningful partial overlap of neurodegenerative disease genes with regards to LBD. While APOE has recently received attention regarding its influence on both amyloid and alpha-synuclein pathology, GBA1 has not been as thoroughly examined. Autosomal recessive missense mutations in the GBA1 gene cause the lysosomal storage disorder, Gaucher’s disease. Intriguingly, recent work demonstrates that GBA1 is also the greatest risk factor for LBD. The molecular mechanisms through which GBA1 mutations may evoke this unique clinical presentation and complex neuropathology are not known. Our data demonstrate novel Golgi-related dysfunction in GBA1 mutant cells, upstream to the lysosomal and late endosomal events important to alpha- synuclein and APP processing, respectively. Here, we will use wildtype induced pluripotent stem cell-derived neurons, as well as matched isogenic neurons harboring multiple pathogenic GBA1 mutations, to examine the influence of GBA1 on the regulation, trafficking, and maturation of key lysosomal proteins thought to be involved in the metabolism of alpha-synuclein. We will also examine the resulting changes in alpha-synuclein degradation and neuronal release, and the accumulation of alpha-synuclein species recently discovered in human LBD brain tissue. In addition, the effect of pathogenic mutation in GBA1 linked to LBD on gamma- secretase and APP biology will be mechanistically and pathologically interrogated here both in vitro and in vivo. Lastly, emerging clinical and biochemical data demonstrate that GBA1 and LRRK2 interact in both physiological and disease-relevant ways. LRRK2 mutations causal for PD appear to decrease risk of dementia in GBA1 patients. Thus, to model these dual-mutation carriers, we will examine neurons with GBA1 mutation alone or those also expressing pathogenic LRRK2 mutations and assess pathways relevant to synucleinopathy and amyloidogenesis described above. This work will directly investigate novel pathways with the potential to understand the novel clinical phenotypes and mixed AD/PD pathology in LBD. Our approach exploits the genetic and molecular intersections of multiple neurodegenerative diseases with the goal of understanding both the similarities and differences in their etiologies.

NIH Research Projects · FY 2025 · 2024-07

Abstract This is a supplemental application under NOT-OD-25-015 to conduct bioethics research and advance capacity building related to bias in AI algorithms. This project is specific to both bioethics research and capacity building in bioethics. Bias in AI algorithms can lead to inaccurate predictions, delaying diagnoses, misguiding treatments, and worsening patient outcomes. Furthermore, biases in AI algorithms can disproportionately affect certain demographic groups, amplifying existing healthcare disparities and leading to inequitable outcomes. How to reduce bias, particularly due to insufficient or unrepresentative datasets, is a major concern in healthcare. Transfer learning offers a promising solution to mitigate data bias when datasets are small or unrepresentative. This is especially relevant for PET imaging, such as Gallium 68 PET scans, for which datasets are limited. With support from the parent R01 project, the team has developed a novel transfer learning framework for PET image quality enhancement. The proposed framework aims to perform pre-training using large-scale high-quality 18F- FDG PET datasets and then fine-tune on limited Gallium 68 datasets. In this supplement project, we will comprehensively evaluate the bias-reduction effect of this proposed framework, explore additional bias mitigation strategies, and investigate potential biases that may rise from transfer learning. Furthermore, we will actively disseminate our findings to research, educational and clinical communities. Bias in AI algorithms is a pressing and emerging bioethical issue when adopting AI to clinics. In the era of rapid AI advancements, this study will provide a robust evidence base to inform and guide future bioethical policies for AI/ML practices, particularly as pre-training and transfer learning become foundational in developing large healthcare AI models. Furthermore, this study will also advance AI-bioethics capacity building by: developing transferable frameworks and methodologies applicable to various biomedical applications, and creating educational resources to address bioethical challenges stemming from biases in AI algorithms.

NIH Research Projects · FY 2025 · 2024-07

PROJECT SUMMARY/ABSTRACT Pulmonary hypertension (PH) is a progressive disease leading to right heart failure and an unacceptably high mortality rate. Despite major milestones in our understanding of predisposing factors to PH, to date, we still have limited mechanistic insight into its development and progression. Thus, despite advances in current therapies, there is no available cure and treatment has limited improvement in outcome. Therefore, development of drug treatments with alternate targets may benefit patients. To this end, our published and preliminary studies demon- strate increased activated microglia, specifically TREM2-expressing disease-associated microglia, contribute to neuroinflammation in autonomic brain regions, particularly the paraventricular nucleus (PVN) of the hypothala- mus. These data informed our central hypothesis that activation of resident microglia, especially TREM2+ microglia subtype and infiltrated myeloid precursors, promotes aberrant preautonomic neuronal signal- ing in the paraventricular nucleus of the hypothalamus leading to sustained sympathetic activation, which is critical to PH. We plan to test this hypothesis via the following three aims: Aim 1 will evaluate the microglia-dependent mechanisms that contribute to increased preautonomic neuron activity within the PVN; Aim 2 will evaluate the mechanism by which TREM2 contributes to PH pathophysiology, exploring the working hy- pothesis that TREM2 expression within microglia is necessary and sufficient for augmented sympathetic activity and thus, a potential therapeutic targeted. Finally, Aim 3 will test the hypothesis that chronic microglia activation leads to dysautonomia and enhanced systemic inflammation, with consequently increase in circulating myeloid cells infiltration to autonomic brain regions such as PVN, contributing to neuroinflammation in a feedforward loop, worsening PH outcomes. Experiments will combine 2-photon microscopy in brain slices, flow cytometry, sympa- thetic ablation, and several cutting-edge genetic models. Ultimately, we expect results of these studies to con- tribute to better understanding of the mechanism whereby microglia and infiltrated myeloid precursors contribute to the pathophysiology of PH. Collectively, the proposed studies will lead to novel information regarding the brain’s pathogenic contribution to pulmonary hypertension, which may represent an entirely novel target for PH therapeutics. In addition, strong mentorship by Drs. Andrew Bryant and Eric Krause, as well as a Mentoring Committee comprised of established professors, who are experts in the proposed techniques and have extensive mentoring experience; will provide conceptual and methodological training, to achieve the research goals and prepare me to establish an independent research program.

NSF Awards · FY 2024 · 2024-07

With support from the Chemical Measurement and Imaging Program in the Division of Chemistry, Professor Boone Prentice's group at the University of Florida is working to devise means of identifying subtle differences in the chemical structures of lipids and metabolites - biomolecules that play vital roles in cellular functions. Changes in the structures of these molecules can signal changes in health and biology, but these differences can be difficult to characterize. The Prentice group is developing experimental and computational methods that are better able than existing approaches to identify chemical changes in these biomolecules, potentially enabling new biological discoveries and benefiting societal health. As part of this project, the team is developing a 2-day, hands-on, laboratory-based Gainesville Emerging Scientist Training (GEST) workshop for high school students in the local community. These outreach efforts are designed to promote careers in STEM disciplines, increase public scientific literacy and engagement, improve educator development at the graduate and undergraduate student levels, and develop a more competitive scientific workforce. Tandem mass spectrometry (MS/MS) has become an important resource in biological research (e.g., in proteomics, lipidomics, and metabolomics) due to the high level of specificity afforded by fragmenting compounds of interest and then analyzing the product masses. However, severe deficiencies remain in the ability to identify and differentiate small molecules and their isomers. Work in the Prentice laboratory aims to develop gas-phase reactions to enable rapid differentiation of metabolic isomers in complex biological samples. The approach entails novel use of gas-phase kinetics to determine and exploit the unique thermochemical properties of each isomer. Dissociation kinetics of analyte/reagent ion complexes generated using either ion/ion or ion/molecule gas-phase reaction chemistries are probed using infrared multiphoton dissociation (IRMPD) to measure isomer activation energies (Ea). These workflows are being tested for applicability to multiple analyte classes, including isomers of sugars, glycolipids, gangliosides, and glycerophospholipids. The experimental data is complemented with computational experiments to improve understanding of the fundamental energy surfaces, chemical structures, and dissociation kinetics responsible for the observed gas-phase behaviors. 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 · 2024-07

Over the years, geoscientists and physicians have developed domain-specific knowledge, tools, and protocols designed for human well-being. However, siloed pathways of information-generating knowledge within geosciences and medicine disciplines have created a bottleneck for effective translation of public health responses to environmentally sensitive, clinically relevant, and climate/weather-modulated pathogens that are transmitted through bioaerosols. This resaerch coordination network breaksdown that barrier by employing novel systems-thinking frameworks of prediction (when, where, and how) and prevention (what) for such transmission vectors. The network, which has a national reach, involves large numbers of geoscience and health professionals who interact to form understandings and share reserach avenues that are needed to tackle medical conditions resulting from bioaerosol transmission by bring together the two fields in directed conversations and partnership building. The network involves understanding, from the environmental and human physiological view, conceptual relationships among infectious pathogens, associated sbioaerosols, and geophysico chemical and environmental transport processes. Broader impacts of the work include integration of fields that fosters collaborations and new, systems knowledge that results in scientific insights that catalyze transformative thinking regarding the environmental impacts and transport of pathogent leading to better healthcare delivery, management, and outcomes, particularly in response to changing climatic conditions. The outcome establishes a platform for collaboration and interdisciplinary, joint problem-defining mechanisms between geoscientists and the medicine/healthcare community. This Research Coodination Network demonstrates that a holistic environmental and human health approach to climate-driven health issues and synthesis of data from both fields is necessary to develop prediction and prevention frameworks of when, where, and how societally relevant and environmentally sensitive infectious pathogens and associated bioaerosols pose a risk to human health. The network will develop knowledge pathways that enhance public health response through improved healthcare delivery systems by exploring the validity of the three propositions. First, mechanisms for exposure of infectious pathogens (through water, sea-sprays, or both) and bioaerosols and their association with climate and weather processes remain unknown or otherwise limited. What is the feasibility of developing methodological (modeling-based), technological (sensor-based), and theoretical (physical/heuristic) frameworks? Second, effective decision-making within healthcare delivery systems necessitates a spatial and temporal understanding of geophysical processes, thereby requiring the establishment of feedback mechanisms bridging disciplinary boundaries. Third, the environmental boundaries in which humans work and live create variability, uncertainty, and nonlinearity from and within the healthcare system and geophysical processes. Hence, such boundaries are not exogenous and remain a function of human activities, and behaviors. These three propositions will be examined by: [1] engaging scholars, practitioners, and professionals from geosciences and healthcare management domains to closely examine and develop a predict and prevent case study workshop and [2] developing the Predict Prevent Data Exchange—a technological platform designed to facilitate dynamic web-based community engagement, digital knowledge repositories, and educational solutions. This initiative aims to foster joint problem definition and scenario development of solutions to complex geosciences-derived pathogen-aerosol systems. The ambition here is to develop scientific curiosity and capacity that will likely lead to a nationwide appreciation of climate and weather-informed healthcare delivery systems for vulnerable coastal human populations. 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 · 2024-07

Project summary/abstract Cocaine addiction is a multidimensional psychiatric disorder with pathophysiology that seems to involve abnormally strong learned associations. These types of learned associations are thought to be encoding within patterns of sparsely distributed neurons, called neuronal ensembles. Relatively little is known about how neuronal ensembles controlling cocaine-seeking differ from those underlying natural reward seeking. We have recently found that a small molecule, Rac1, is differentially expressed in cocaine-paired neuronal ensembles compared to food-paired ensembles. This molecule may represent a unique molecular adaptation that defines the cocaine-seeking ensemble. There is, therefore, a critical need to determine the role or Rac1 in cocaine- seeking ensembles. The long-term goal is to determine the neural mechanisms underlying drug memories to enable development of clinically useful therapies to alleviate craving and relapse of cocaine use disorder. The overall objective in this application is to the role of Rac1 in the behavioral, structural, and activity of cocaine- ensemble neurons. Our central hypothesis is that Rac1 signaling is integral to cocaine-induced neuroadaptations, driving neuroadaptations that increase the cue-reactivity of cocaine ensemble neurons and drive cocaine-seeking behavior. The rationale for the proposed research is that understanding how Rac1 expression effects the neuronal ensembles governing cocaine-seeking behavior will provide new opportunities for developing experimental therapeutics to treating cocaine use disorder. To attain the overall objectives, the following specific aims will be pursued: 1) Determine the impact of IL ensemble Rac1 activity on cocaine-seeking behavior; 2) Identify changes in cellular structure within cocaine-associated neuronal ensembles; and 3) Determine the role of Rac1 activity on cue reactivity of cocaine ensemble neurons. The research proposed in this application is innovative because it dissects the role of Rac1 within neuronal ensembles in cocaine self- administration compared to food-seeking ensembles using several cutting-edge methods. These contributions will have significant impact because they are expected to have determined how Rac1 drives adaptations within the neuronal ensembles mediating cocaine-seeking.

NSF Awards · FY 2024 · 2024-07

This project addresses two critical needs of the nation: 1) a significant talent shortage in the field of microelectronics and semiconductors, and 2) a high unemployment rate among individuals with disabilities and neurodiversity in the STEM workforce. There are over 2 million autistic adults holding post-secondary degrees in the United States. Empirical studies have shown that autistic individuals possess unique strengths that can excel in many STEM fields, such as strong attention to detail, visual pattern recognition, high integrity, and adherence to rules, which are essential in the field of semiconductor quality assurance and data analysis. Despite autistic individuals' strong STEM backgrounds compared to their neurotypical peers, they remain one of the most underrepresented groups in the STEM workforce due to multiple challenges they face in the competitive job market, including networking, finding mentors, and limited opportunities to receive hands-on training. Meanwhile, the semiconductor industry is struggling to recruit talented domestic engineers in microelectronic quality assurance after years of reliance on foreign outsourcing. Expensive training costs and equipment, often costing multimillion dollars, are cited as primary obstacles to expanding hands-on training experiences. This project aims to bridge this gap by designing and providing an 8-week intensive program leveraging virtual reality (VR) technology, called PATH. The outcome of this project will contribute to addressing the nation's urgent need to rebuild a strong and diverse workforce in the semiconductor industry. This is a collaborative effort between the University of Florida (UF), the Center for Autism and Related Disability (CARD), and industry partners including Skywater Foundry in Kissimmee, FL, and ZEISS in Jupiter, FL. During the project period, a total of 50 autistic adults will receive training. The specific target demographic is autistic adults with associate or bachelor's degrees in electronic engineering, material science, computer science, industrial engineering, or other relevant areas. The training aims to prepare them for entry-level jobs as quality assurance engineers and process engineers in semiconductor foundries. Over the 8-week training period, students will not only learn fundamental concepts of Integrated Circuit (IC) packaging and quality inspection methods through lectures but will also have the opportunity to gain hands-on experience through VR simulation. VR simulations have been recognized as effective tools for autistic individuals, as they can provide a tailored learning experience without the concern of making mistakes in an individualized space, as compared to the conventional group-based observation method. Additionally, PATH participants will receive one-on-one mentorship from industry experts. Among the 50 participants, selected individuals will have the opportunity to work as summer interns at Skywater Technology. The developed learning contents, including lecture recordings, VR simulations, and quizzes, will be made available to the public through an online learning platform to enhance its broad impact on the larger community beyond the project period. 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 · 2024-07

Abstract Several recurrent, relatively common copy number variants (CNVs) have been shown to confer significant risk for neuropsychiatric disorders (NPD). These CNVs are under-identified in the general population and under- characterized with respect to the broad range of possible phenotypic manifestation and penetrance. The 15q13.3 BP4-5 recurrent deletion (15q13.3DS) confers risk for early onset NPDs such as autism spectrum disorder (ASD) and intellectual developmental disorder (IDD), What is less clear is the impact of this CNV on NPDs with later onset, such as major depressive disorder(MDD), bipolar disorder, and schizophrenia, as well as numerous other later-onset medical and neurological conditions such as epilepsy, and neurodegenerative disorders. Similarly, little is known about the relationship between ASD-associated CNVs and potentially clinically relevant dimensional neurobehavioral traits among carriers who do not meet full clinical criteria for an early onset NPD. There is a need to characterize a wider population base to better understand the penetrance of these CNVs, along with other potentially associated medical, psychiatric, and neurological phenotypes. There are likely additional factors (such as underlying polygenic risk) that may impact the phenotypic expression of these variants that already exist in the information already collected. We will identify a cohort of 200 individuals with 15q13.3DS with access to their electronic heath records(EHR). We will recruit 75 individuals for deeper quantitative phenotyping. We will identify additional clinical characteristics in addition to confirming the currently known phenotypes associated with 15q13.3DS by leveraging available longitudinal EHRs. We will then combine the EHR data with the quantitative phenotypic data that we have collected using well-referenced and validated tools to create a deep dataset. This dataset will then be used to train and systematically test a predictive algorithm of 15q13.3DS diagnosis and risk prediction for penetrance of its various manifestations. To complete these series of studies as part of a K23 Mentored Career Development Award Dr. Soda will work with a team of mentors with complementary skillsets, complete relevant coursework towards a biomedical informatics certificate, and participate in related practicum experiences. This will help Dr. Soda meet his training aims; 1. Learn to operate in, manage, harmonize complex health-related data through biomedical informatics. 2. Learn the skills needed to conduct genomic analysis on the effect of rare as well as common variants found in the genome and its relation to symptom penetrance. 3. Learn advanced analysis of biomedical data with machine learning techniques. The completion of this proposal will uncover previously unknown syndrome presentations, identify factors related to psychiatric disorder penetrance in individuals with 15q13.3DS and will lay the groundwork for Dr. Soda to achieve independence towards R01 funding to assess the sensitivity/ specificity of such developed tools in identifying individuals with rare genetic syndromes.