University Of Florida

NIH Research Projects · FY 2025 · 2025-07

PROJECT SUMMARY/ABSTRACT Cancer Cachexia (CC) presents a profound challenge to cancer survival, affecting roughly 80% of cancer patients and contributing to a substantial proportion of cancer-related fatalities. Among its manifestations, skeletal muscle weakness and wasting stand as a pivotal concern, impacting both the quality of life and survival rates of afflicted individuals. The goal of this F32 application is to pursue research training in the newly emerging area of muscle circadian clock disruption in cancer The circadian clock mechanism in skeletal muscle regulates a rhythmic daily program of gene expression (i.e. clock output genes) contributing to muscle homeostasis, while muscle clock disarrangements are implicated in several models of muscle atrophy. My preliminary investigations unveiled transcriptomic shifts in core clock genes within skeletal muscle in various pre-clinical CC models, suggesting a potential role for the clock in cancer-induced muscle detriments. These observations are supported by compelling unpublished data from collaborative research between the Esser and Judge laboratories, showing disruptive alterations in the muscle circadian clock and clock output genes in pancreatic cancer-bearing mice. These combined findings provide the rationale for this F32 proposal. This proposal stands out for its scientific novelty, being the first to delineate the muscle clock profile and assess its impact as a modifier in the development and progression of CC. My overarching hypothesis is that the muscle clock serves as a CC modifier and loss of clock function will lead to accelerated and aggravate CC-induced muscle impairments. The outcomes of this proposal will 1) define the cachexia stage at which the muscle clock is disrupted, interrogate clock disruptions and its relationship with cachexia manifestations in a muscle type-specific fashion, and 2) provide an extensive assessment of both behavioral and muscle-specific changes in CC modulated by the muscle clock mechanism.

NIH Research Projects · FY 2025 · 2025-06

ABSTRACT One of every five deaths in the United States is due to cancer. In both men and women, it is the second leading cause of death, exceeded only by heart disease. However, it is the leading cause of death among women aged 40 to 79 years and men aged 60 to 79 years. Furthermore, cancer is primarily a disease of the aged and the nation’s population is aging. By 2050, about one in five Americans will be age 65 or older, up from about one in eight in 2000, and the number of Americans aged 65 and older will more than double over the 40-year period, reaching more than 80 million in 2050. It is therefore imperative that we ensure a continuous workforce of highly trained cancer researchers who will discover, through research, new therapies and preventative strategies that improve treatment outcomes and reduce cancer-related mortality and morbidity. We believe that this goal will be achieved through educating and training the next generation of cancer research scientists. Experiential research internships have been shown to be effective in encouraging students to matriculate to graduate schools and to consider research careers. R1 institutions, classified as doctoral universities with very high research activity, offer abundant opportunities for undergraduate research. However, students completing their Baccalaureate degrees at non-R1 institutions may be disadvantaged due to lack of access to equivalent research experiences. Furthermore, since R1 institutions comprise only a small fraction of degree-granting institutions, it is becoming increasingly clear that in order to meet the expanding need for a highly trained cancer research workforce, it is essential to strengthen the pipeline of potential future researchers. We believe the strategy to achieve this goal, while simultaneously providing career and skills development to enhance future career aspirations, is to offer undergraduates from non-R1 universities the opportunity for hands-on, immersive research experiences that will enhance their graduate portfolios, strengthen their academic competitiveness and aid their preparation for competitive PhD program acceptance. We are requesting support for 8 baccalaureate trainees (rising juniors, seniors, and postbaccalaureates) annually from non-R1 institutions, including Historical Black Colleges and Universities, Hispanic-Serving Institutions, and rurally located colleges to participate in our Summer Training in Research and Oncology for the Next Generation of Researchers (STRONGER) Program. The program will directly link the interns with graduate students in the laboratories of a cadre of outstanding cancer research faculty, with broad research expertise, to provide the interns with a near-peer mentoring experience in a team-based cancer research setting. Coupled with the University of Florida’s unique scientific resources and infrastructure, the STRONGER program will expose students to a broad range of cancer research disciplines and provide a path to future careers in cancer research.

NIH Research Projects · FY 2025 · 2025-06

Abstract Mosquito-borne diseases impose significant burdens on global public health, with anthropogenic changes in landscape, socio-economy, and climate further accelerating transmission. However, our ability to quantify the effects of these socio-environmental changes on disease transmission remains limited, impairing our predictions of disease spread and the development of effective intervention strategies. Current field studies primarily rely on vector abundance to assess transmission risk, overlooking the critical role of human-mosquito contact. Mosquito biting rates, a key determinant of pathogen transmission, are difficult to measure accurately in natural settings due to the lack of reliable methods. Thus, despite its importance, field-derived data on mosquito biting rates are scarce, hampering our understanding of how socio- environmental factors influence disease transmission. This study seeks to fill this gap by developing a novel methodology using X-ray micro-computed tomography (micro-CT) to assess key tissue characteristics for quantifying mosquito blood- feeding rates. Building upon a labor-intensive traditional histologic technique, our proof-of-concept study supported that micro-CT imaging offers a non-destructive, high-resolution alternative capable of visualizing bloodmeal separation and ovarian development in Aedes aegypti, a primary vector of many mosquito-borne diseases. By applying this innovative technology, we aim to provide an efficient and scalable approach to quantifying mosquito biting rates more accurately. In Specific Aim 1, we will optimize protocols for sample preparation, micro-CT scanning, and post-imaging processes to balance image clarity and throughput, ensuring cost-effective application. In Specific Aim 2, we will develop image standards and diagnostic keys to assess relevant mosquito midgut and ovarian tissue characteristics important for determining blood-feeding rate, and validate their reliability through blinded validation studies. The adoption of micro-CT imaging technology represents a significant advancement in vector-borne disease research. While micro-CT is well- established for imaging insect morphology, its application to quantify mosquito blood-feeding rates is novel. This project provides a much-needed improvement over traditional histology, simplifying sample preparation and enhancing imaging precision, and will revolutionize how mosquito blood-feeding rates are measured across diverse environments. The 3D imaging technology will also offer deeper insights into mosquito anatomy and physiology, including in blood-engorged midguts—the critical juncture where pathogen infection occurs. The expected outputs include shared protocols, image data, and diagnostic resources that will enable more accurate estimation of mosquito biting rates in the field. By bridging the gap between field data and predictive models, we will enable more precise assessments of disease risk, particularly in the face of rapid socio-environmental change. The results of this research will have far-reaching implications, enhancing global disease prevention efforts and empowering researchers with the tools needed to combat mosquito-borne diseases more effectively.

NIH Research Projects · FY 2025 · 2025-06

PROJECT SUMMARY The bone marrow (BM) niche is a highly complex microenvironment that houses hematopoietic stem cells (HSCs). These niche cells have been shown to provide instructive cues to HSCs and dysregulation of this signaling due to aging can lead to impaired hematopoietic activity. With our increasingly aging population, understanding and developing therapeutics to combat malignancies associated with an aged blood system is of great importance to both better treat these patients as well as reduce the resulting monetary and healthcare load. This proposal aims to characterize a recent finding in our lab which identifies thrombospondin-1 (Thbs1) as a pro-gerontic factor of HSCs and the BM niche. Thbs1 is a well-studied extracellular matrix protein with notable involvement in age-related changes in other systems, such as the cardiovascular and metabolic systems, but has not been studied within hematopoiesis. Through competitive HSC transplantation assays, we show that HSCs derived from aged global knockout (gKO) Thbs1 murine models have young-like engraftment and lineage potential. Reciprocal transplant assays on these mice also show that intrinsic and extrinsic influence of Thbs1 plays a role in the increased functionality we observe within the global KO. We have since developed a Thbs1- GFP reporter mouse and have identified that endothelial cells (ECs) and megakaryocytes (MKs) produce Thbs1 within the BM niche. My preliminary data suggests that KO of Thbs1 derived from ECs and MKs recapitulates the increased HSC functionality observed in young global KO mice. I hypothesize that age-related dysregulation of cell-specific derived Thbs1 plays a critical role in the aging of HSCs, and, through targeting Thbs1, we can improve HSC functionality. To test this, we will: 1. Identify which cell-specific KOs of Thbs1 recapitulate the global KO phenotype whilst assessing possible alterations in hallmarks of HSC aging, including DNA damage, polarity, and changes in cell cycle, to obtain mechanistic insights. 2. Determine if deletion or inhibition of Thbs1 can enhance the functional capacity of HSCs expanded within a polyvinyl alcohol-based platform to be used within BM transplants. 3. Assess the possible effects Thbs1 has during myelosuppressive insult and determine if targeting Thbs1 can lead to better recovery and preservation of the BM microenvironment and HSC functionality. Results stemming from this proposal will lead to not only a better understanding of the basic biology of Thbs1 within hematopoiesis, but also identify the therapeutic potential of targeting cell-specific Thbs1 to alleviate aged HSC phenotypes.

NSF Awards · FY 2025 · 2025-06

This Faculty Early Career Development (CAREER) award will support research aimed to address critical needs for designing safer high-voltage transmission tower-line (TTL) systems that sustain power delivery during extreme wind events, such as hurricanes and tropical storms. Current industry standards rely on static, averaged wind load assumptions that oversimplify the unpredictable and complex nature of wind loads. This research project will challenge these assumptions by introducing innovative random wind load models that capture distinctive collapse mechanisms of TTL systems. By integrating these wind load models into advanced computational simulations of how tower failures propagate under wind-induced collapse, the research intends to advance the design and risk assessment of TTL systems. The outcomes of this work intend to provide safer, more robust power grid infrastructure, enhancing energy security and reducing blackout risks during hurricanes. Broader impacts will include the development of educational resources that promote hands-on, experiential learning in wind engineering design. By advancing the technical design of transmission towers and integrating the research with educational and outreach activities, this project will promote the national welfare in energy security, infrastructure resilience, and workforce development. This project will contribute to NSF's role in the National Windstorm Impact Reduction Program (NWIRP). The specific goal of the research is to model the progressive collapse of high-voltage TTL systems under extreme wind loads with high accuracy and low computational cost. Since the progressive failure path of TTL systems has been proven to be sensitive to stochastic wind loads, this research will first develop multivariate statistical models to capture stochastic wind load patterns along the height of transmission towers. To support this effort, novel panel-wise high-frequency base balance experiments will be conducted at the NSF-supported Natural Hazards Engineering Research Infrastructure (NHERI) Boundary Layer Wind Tunnel at the University of Florida to calibrate wind load models and validate the feasibility of using nodal force representations for wind loads on individual tower panels. Building on these models, the project will introduce three new progressive collapse modeling procedures for wind engineering: (1) static collapse analysis with normative wind load, (2) static collapse analysis with stochastic wind load, and (3) dynamic collapse analysis with temporal wind loads. These procedures will enable the modeling of cascading failures as forces redistribute in real time after localized damage. By addressing the entire spectrum of collapse pathways, from initial localized element failures to large-scale system collapse, this project will advance the accuracy, robustness, and efficiency of risk assessment methods for power grid infrastructure. The expected outcomes include (1) the development of stochastic wind load models that support performance-based design, (2) the creation of progressive collapse analysis procedures that enable real-time force redistribution modeling under wind loads, (3) the introduction of new damage measures that link tower collapse to power delivery functionality, and (4) the production of systems-level fragility models that quantify regional blackout risk for large-scale power grids. These contributions will challenge the reliance on normative wind load assumptions in transmission tower design, paving the way for performance-based wind engineering practices. The impact of the research will extend to power grid resilience, as the integration of stochastic wind loads and progressive collapse modeling will reduce uncertainty in risk assessments, improve infrastructure safety, and support the development of next-generation transmission towers designed for hurricane resilience. Project data will be archived and made publicly available in the NHERI Data Depot (https://www.DesignSafe-ci.org). This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NIH Research Projects · FY 2025 · 2025-06

Abstract Sepsis is the most common cause (~75%) of acute respiratory distress syndrome (ARDS), a common condition with over 40% mortality. There are no effective pharmacotherapies for ARDS, likely due to patient heterogeneity. We have shown that HDL, which is usually anti-inflammatory/anti-oxidant, becomes dysfunctional (DysHDL) in sepsis, and becomes a negative regulator of inflammation, lipid oxidation, and chemotaxis. DysHDL harbors an altered proteome and lipidome when compared to normal HDL and has not been studied in septic ARDS. We recently developed a panel of fifteen measurements including lipoproteins, inflammatory molecules, and clinical features and established two new sepsis phenotypes, HYPO and NORMO. We applied our sepsis phenotyping pipeline (preliminary data) to septic ARDS patients and found that HYPO septic ARDS patients had ~70% mortality, lower apoA-I, HDL-C, low density lipoprotein (LDL-C), worse endothelial dysfunction (ICAM-1), and higher organ failure severity when compared to NORMO septic ARDS patients (0% mortality). Moreover, HYPO septic ARDS patient plasma contained significantly elevated lipoxygenase (LOX) pathway oxidized lipids (12- HETE/15-HETE) compared to NORMO septic ARDS. We also identified six upregulated lipid metabolism genes in peripheral blood leukocytes of HYPO vs. NORMO septic ARDS patients, critical for HDL/cholesterol biosynthesis, lipid/drug metabolism, and bacterial toxin clearance. Our central hypothesis is that unique phenotypes based on lipid-gene molecular patterns exist in septic ARDS that can be harnessed to reveal patient molecular heterogeneity. We further hypothesize that HDL metabolism and the LOX pathway play critical roles in septic ARDS, specifically in the HYPO phenotype subset. Our MPI team with unique expertise will address major gaps in ARDS research by i) identifying novel septic ARDS phenotypes, ii) systematically discovering repurposed drugs for septic ARDS treatment. Aim 1 will investigate HYPO/NORMO phenotypes in septic ARDS patients, by measuring fifteen markers and DysHDL in 150 ROSE trial participant samples. We will perform targeted lipidomics to quantify the oxidized lipidome of LOX, COX, and P450 pathways and obtain untargeted transcriptomic signatures via whole blood RNAseq. We will localize expression patterns by cell type using single cell RNAseq in a small subset. Aim 2 will determine novel septic ARDS phenotypes utilizing lipidomic and transcriptomic profiles of septic ARDS patients. We will perform multi-omic, molecular phenotyping using an unsupervised machine learning approach to uncover novel lipidomic/transcriptomic phenotypes and link molecular phenotypes to potential drugs via drug-gene interactions.

NIH Research Projects · FY 2026 · 2025-06

Project summary The double-stranded RNA virus rotavirus is one of the leading causes of enteric virus induced deaths worldwide. Upwards of 200,000 people, mostly children, die due to rotavirus infection each year. While several rotavirus vaccines have been developed and efficiently protect children in the developed world, they display poor efficacies in developing countries where they are needed the most; indicating that alternative strategies to combat rotavirus infection are greatly needed. Rotaviruses infect the intestinal epithelial cells lining the surface of the gastrointestinal tract. Upon rotavirus infection these cells upregulate type I and type III interferons to combat rotavirus infection. Recent work from our lab has shown that type I interferons are dispensable for controlling rotavirus infection. We found that type III interferons are the key cytokines which restrict rotavirus replication and spread in human intestinal epithelial cells. Humans express four type III interferons (IFNl1, IFNl2, IFNl3, and IFNl4). How each subtype of type III interferon is produced following virus infection and whether the different subtypes of type III interferon have subtype-specific antiviral properties remain mostly unknown. To unravel how rotaviruses induced type III interferons in human intestinal epithelial cells, we used genetic depletions and pharmacological inhibitors. We could show that intestinal epithelial cells produce type III interferons following rotavirus infection through both the RIG-like receptor (RLR) and STING pathways. These preliminary data report for the first time that rotavirus infection can be sensed by the STING pathway which normally is responsible for sensing DNA virus infection. In addition, we found that RLRs and STING each lead to the upregulation of distinct type III interferons: RLR activation upregulated IFNl1 and IFNl2/3 while STING led to the exclusive upregulation of IFNl2/3. To determine whether IFNl1 and IFNl2/3 were equally important to control rotavirus infection we genetically depleted them in our human intestinal epithelial cells. We found that IFNl1 was dispensable for controlling rotavirus infection while IFNl2/3 was critical for controlling rotavirus infection and spread. In this proposed project we will further investigate how STING is activated following rotavirus infection and determine how distinct type III interferon subtypes (IFNl1 vs IFNl2/3) can be upregulated depending on the pattern recognition receptor which is activated. Together these results will give us insight into tissue specific mechanisms used to combat viral infection and provide novel insight into whether IFNl2/3 could be implemented as anti-rotaviral therapeutic measure in areas of low vaccine efficacy.

NIH Research Projects · FY 2026 · 2025-06

Project Summary Streptococcus mutans resides in the oral cavity where it is known to initiate the development of dental caries. For this pathogen to thrive in the dynamic and variable environment of the mouth, S. mutans must be able to adapt to both short- and long-term ecological pressures. The horizontal acquisition of new DNA, which may encode for new beneficial traits, is a critical aspect of S. mutans adaptability. In addition, regulation of the processes involved in the acquisition of DNA are intertwined with the basic physiology and stress responses of S. mutans. Mobile genetic elements often mediate HGT and include integrative and conjugative elements (ICEs), widespread among oral bacteria. ICEs are mobile elements that are integrated on the genome and possess the ability to excise and subsequently transfer to nearby bacteria via conjugation. Importantly, these elements often contain “cargo” genes that provide some benefit to the host bacterial cells (including antibiotic resistance, metabolism, and virulence). In recent work supported by R03 DE029882 and F32 DE032551, we undertook the first characterization of TnSmu1 as a model of HGT within this critical oral pathogen. We discovered that TnSmu1 is a functional ICE, capable of transfer. Further, we have made significant progress investigating a regulatory system that controls activation of TnSmu1 and showed that TnSmu1 causes a host cell defect in cell division. Further, when TnSmu1 excision is induced, the S. mutans Type I-C CRISPR-Cas system is up-regulated, for reasons that are currently unclear but possibly suggesting an interaction between TnSmu1 and this bacterial defense mechanism. Together, this indicates TnSmu1 shares a complex relationship with its host bacterial cell. Despite the prevalence of ICEs in oral bacteria and the significant impact of TnSmu1 on host cell physiology, detailed studies of their molecular mechanisms and their impact on oral communities are lacking. To address this, we propose to use TnSmu1 as a model of conjugal transfer in the following Specific Aims: Aim 1: Dissect the regulatory mechanisms that control the switch from the integrated to excised state of TnSmu1. Aim 2: Elucidating interactions of TnSmu1, mobile genetic elements, and CRISPR-Cas defense in bacterial hosts. Aim 3: Investigating the fitness cost(s) of TnSmu1 acquisition on recipient strains. Taken together, these studies will provide a wealth of information for an understudied mechanism of gene transfer in the oral microbiome. Elucidating mechanisms of gene transfer is critical for understanding of S. mutans adaptability and the ability to combat oral disease. At the conclusion of these studies, this work will have created a new understanding of HGT, evolution, and pathogenesis of S. mutans within the oral microbiome.

NSF Awards · FY 2025 · 2025-06

Conventional thermal separation processes like absorption and distillation consume over 10% of the total U.S. energy production. Gas separation membranes offer a great opportunity to reduce energy consumption and cost of chemical separations. Developing innovative polymer materials for the membrane layer that controls the separation is key to achieving high separation efficiency and low separation costs. Unfortunately, membrane materials can lose separation performance over time, especially in the chemically harsh conditions commonly found in industry. “Polymers of Intrinsic Microporosity” (PIMs) are unique materials that exhibit high internal surface areas and high rigidity, making them particularly promising for gas separations such as carbon capture and hydrocarbon purification. This project will develop design principles for making more robust and efficient gas separation membranes. These insights will come from investigating how PIM molecular structure and molecular motions can be used to avoid performance losses under industrial conditions. To bridge the skill gap needed for students to transition from academic to industrial research, this proposal will develop a new student safety certificate program at University of Florida to enhance student safety literacy and academic safety culture. New sustainability-focused, hands-on teaching kits and in-person and remote workshop activities will be developed for middle and high school teachers across Florida to incorporate in their classrooms. The combination of research, graduate and undergraduate training, safety education, and outreach activities will help train the next generation of STEM researchers. Polymers of Intrinsic Microporosity (PIMs) are leading materials for energy efficient gas separation membranes but remain susceptible to a tradeoff between permeability and selectivity and detrimental effects of gas- and vapor-induced plasticization and physical aging. Despite observations that polymer dynamics play a crucial role in membrane gas separations, a lack of quantitative investigations of polymer dynamics alongside structure driven design has hindered advancement and commercialization of next-generation membranes. This project aims to experimentally decouple the effects of free volume and specific polymer dynamic modes on fundamental gas and vapor transport properties, plasticization, and physical aging in unique dipole-tagged PIM membranes. New, facile synthetic strategies to post-functionalize PIM-1 to prepare a library of well-controlled PIM derivatives will be developed to facilitate these studies. Experimental tools such as broadband dielectric spectroscopy that are relatively underutilized in the gas separation membrane field will be employed to quantify polymer dynamics. These structure/dynamics/property studies will address key hypotheses regarding how selective control over specific dynamic modes could improve gas permeability while maintaining selectivity and resistance to plasticization and aging. Tightly integrating modular synthetic strategies with multicomponent gas/vapor transport measurements and experimental polymer structure and dynamics characterization will provide transformative insights into how molecularly tailored PIM membranes can enable new improvements in chemical process efficiency. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NIH Research Projects · FY 2025 · 2025-06

Abstract This proposed research is both for statistical methodology development and novel secondary analyses of an important existing national dataset. The overall goal of our proposed research is to assess person-level marginal associations between dental caries and periodontitis. We consider a modeling setup where individual units (e.g., teeth and surfaces) are clustered so that the outcomes in a given cluster (e.g., mouth) are not independent. Due to the nature of the underlying biology, both caries and periodontal outcomes are correlated with the size of the cluster. This phenomenon is referred to as “informative cluster size (ICS).” Additionally, treating a periodontal outcome such as the attachment loss as one of the two variables in this association study, we may face a greater form of informativeness that goes beyond ICS; e.g., many more teeth with smaller values than larger values of attachment loss, even for subjects with comparable numbers for total cluster size (e.g., number of teeth). As a result, a different type of reweighting will be needed to assess the marginal associations. After developing the general statistical methodology for calculating these novel associations by solving a generalized estimation equation, we will apply a regression technique based on jackknife pseudo-values [Andersen et al, 2003] to determine which of the modeling factors (e.g., sex, race, economic status, family income, smoking status, education level, tooth position, and so on) significantly contribute to this association. A motivating dental dataset to which to apply our statistical research is from the National Health and Nutrition Examination Survey (NHANES). Tooth and surface/site level cross-sectional national US data stratified by age (30-49, 50-64, and 65+) will be analyzed using our novel statistical methods. During the proposed research period of two years, we will undertake the following tasks: Aim 1: We will develop statistical tests based on resampling combined with permutation to test for informativeness of number of observed data units (e.g., teeth) for caries outcomes at various levels of attachment losses. Aim 2: We will introduce novel inferential methods for the marginal associations (with different marginalization weights) between caries and periodontal outcomes and those of various covariate effects and use in detailed analyses of the NHANES data set of periodontal and caries outcomes mentioned above. Aim 3: We will create a scalable, computationally-efficient, and user-friendly R-package based on our inferential tools to be developed under Aims 1 and 2. Without this R-package, members of the scientific community may not be able to our novel methods for their data analysis, since the base R software does not have implementations of these methods. The R-package will be tested on the NHANES data set, which will be supplied with this R-package. Finally, the R package will be distributed to the scientific community at large through CRAN (Comprehensive R Archive Network). Our proposed research is important both for gaining new scientific knowledge and for statistical methodology development leading to new tools of data analysis.

NIH Research Projects · FY 2026 · 2025-06

Project summary Alzheimer’s disease (AD), the most common form of dementia, is characterized by cognitive decline and impairment of behavioral and functional abilities. Approximate 6.7 million people in the United States are affected by AD and this number is anticipated to triple by 2060. While mutations in amyloid precursor protein (APP) and presenillin (PSEN1 and PSEN2) are known to cause familial early onset AD and the APOE4 variant is a common disease risk factor, the genetic contributions to the majority of late onset AD cases are not clear. While the accumulation of Aβ plaques and hyperphosphorylated tau (pTau) are the hallmark features of AD, it is not clear if targeting Aβ plaques or pTau is an effective treatment strategy for sporadic AD. Our recent findings strongly support the contribution of microsatellite repeat expansions in AD. Using antibodies targeting polymeric proteins reported in known repeat expansion disorders, we show poly-glycine-arginine (polyGR+) aggregates are frequently found in AD brains with unknown genetic etiologies. Using a repeat expansion pulldown tool, we identified a novel polyGR-encoding GGGAGA repeat expansion in CASP8 (CASP8-GGGAGAEXP). The CASP8- GGGAGAEXP produces polyGR-containing proteins in CASP8-GGGAGAEXP(+) AD brains and in transfected cells. A rare, specific variant of this expansion, CASP8ADR1 containing stretches of (GGGAGA)4CG motifs is associated with increased AD risk in three independent cohorts (odds ratio = 2.2, p<0.0001). We also show CASP8ADR1 produces higher levels of rGGGAGAEXP RNA inclusion and polyGR aggregates, and is more toxic than the common CASP8-GGGAGAEXP variant in cells. Our finding is exciting because it connects AD to a large family of >70 rare neurological disorders caused by repeat expansion mutations including C9orf72 frontotemporal dementia (FTD) (C9-FTD). Molecular mechanisms of these diseases involve protein loss- or gain- of-function (GOF), RNA GOF, and the toxicity of polymeric proteins produced by repeat-associated non-AUG (RAN) translation. PolyGR proteins have been shown to be highly toxic in C9 FTD models. In AD autopsy brains, polyGR+ aggregates are increased with AD pathological hallmarks (e.g. increased pTau in the hippocampus and increased Aβ plaque and pTau deposition). Interestingly, polyGR+ aggregate levels are increased in AD cases that experience brain injuries and high blood pressure that have been shown to induce oxidative stress. We hypothesize that CASP8ADR1 contributes to AD by producing toxic RAN proteins and oxidative stress increases AD risk in CASP8ADR1 carriers by increasing the accumulation of RAN protein aggregates. We will test this hypothesis in three specific aims: Aim 1) To test the hypothesis that expansion RNAs and polyGR-containing proteins expressed from CASP8ADR1 accumulate in regions with AD pathology in CASP8ADR1(+) AD autopsy brains; Aim 2) To test the hypothesis that CASP8ADR1 alleles produce repeat expansion products that are associated with molecular hallmarks of AD in patient derived organoids; and Aim 3) To test the hypothesis that removing or blocking expression of the CASP8ADR1 will mitigate disease phenotypes in patient derived models.

NIH Research Projects · FY 2026 · 2025-06

Women in the United States (US) have not reaped the benefits of the decline in worldwide maternal mortality rates as maternal deaths have increased steadily in the US for the past three decades. Disparities exist in both maternal morbidity and mortality in the US. Low-income women or those covered by Medicaid are more likely to experience increased maternal morbidity when compared to those in higher socioeconomic classes. Effective, sustainable interventions are urgently needed to improve outcomes for all women and to close gaps in maternal health. Doulas have been associated with improved maternal outcomes; however, there are challenges in access to doula services due to cost or lack of third-party reimbursement; rendering these services sometimes inaccessible for low-income communities. This proposal will leverage existing community partnerships and infrastructure to refine and test the Perinatal Wellness Doula Home (PWDH). A unique model of comprehensive doula support for low-income women throughout the prenatal, birth, and postpartum period. Our overarching goal is to demonstrate the utility of PWDH in reducing perinatal mood and anxiety symptoms, maternal morbidity, and close gaps in perinatal health outcomes. This project will be executed utilizing three aims: Aim 1: collection of qualitative data from pregnant/postpartum women, support persons, doulas, medical providers, community partners, and various stakeholders to refine our previously developed intervention prior to testing (n=48). Aim 2: conduct of a pragmatic two-armed Effectiveness-Implementation Hybrid Randomized Controlled Trial of PWDH and standard Medicaid doula care in a socially high-risk population (n=516). Aim 3: integration of qualitative and quantitative data to contextualize findings, develop community-informed messaging for dissemination, and promotion of systems change by informing Medicaid doula policies. This innovative implementation-effectiveness approach will allow us to not only determine effectiveness of PWDH, but also to understand context for implementation. We hypothesize that PWDH will provide multilevel support and address non-medical needs, thereby improving maternal mental wellbeing, and reducing adverse perinatal outcomes. We strive for a comprehensive approach that gathers necessary information from all stakeholders and decision makers to facilitate implementation of PWDH if observed to be effective. Study activities will be guided by two Community Advisory Boards comprised of 1) Service Recipients – low-income pregnant and postpartum women, partners/ support persons, and 2) Service Providers – doulas, medical staff, community representatives, and policy makers. This proposal is critical to developing the community-informed interventions needed to help low-income communities thrive.

NIH Research Projects · FY 2025 · 2025-06

The protein tau (MAPT, tau) aberrantly accumulates in a family of neurodegenerative diseases (collectively termed tauopathies); the most prevalent and notable of these diseases being Alzheimer’s Disease (AD). The modification of tau, through post-translational modifications or mutation, has been associated with the toxic accumulation that occurs in neurodegenerative disorders. However, our group as well as others have investigated if the interaction between tau and normal cellular RNA can play a role in the accumulation and eventual toxicity of tau. We identified RNA motifs enriched as tau-binders in distinct phases of disease progression: from persons presenting no tauopathy markers or clinical manifestations of neurodegeneration, to those without cognitive impairment but some pathological tau detected post mortem, to those diagnosed with AD later confirmed at autopsy. These motifs and the dispersal of these motifs throughout disease stage suggest that some RNA-tau interactions may be protective against or neutral to condensate or pathology development, whereas other motifs may enhance condensates and pathology. If the studies proposed herein that follow these data are successful, we may be able to answer questions about specificity of mRNA motifs for forming condensates with tau, the fate of these mRNA interacting with tau, and (eventually) the impact of these interactions and condensates on pathology. Importantly, if we are able to identify RNA motifs that either enhance or inhibit the formation of biomolecular condensates, this information could then be modified into therapeutic strategies.

NSF Awards · FY 2025 · 2025-06

The integration of mathematical models and ecological experiments presents a unique opportunity to understand, in simplified ways, complex ecological interactions. Parasitism is one of these complex interactions that can impact multiple types of hosts from humans to plants. The process of parasite transmission is complex, and parasites employ various mechanisms to ultimately exploit the host resources. Some parasites even use other organisms, like insects, as vectors to infect their hosts which adds, yet another layer of complexity. Mathematical models have been essential to allow us to study vector-borne parasite transmission. Yet, these simplified relationships ultimately may result in an incomplete picture of the ecological process. Moreover, these simplifications may result in biased understanding of key population-level outcomes such as the proportion of individuals infected or how likely is a parasite to persist. For instance, models assume that every individual host has the same probability of getting infected. However, we know that this may not be always true. This project considers individual differences, host movement, and spatial variations to study their impact on host infection and the transmission of disease in the system. This CAREER project integrates teaching and research to development a graduate course and will provide opportunities to graduate, undergraduate, and high school students in research. This study evaluates how much model complexity is needed to effectively describe and forecast vector-borne disease dynamics. To answer this question this project follows an interdisciplinary approach that integrates hypotheses derived from theoretical mathematical models of increasing complexity with field transmission experiments in a natural lizard-malaria system in Puerto Rico. The investigators will build models that describe vector-borne parasite transmission under a variety of heterogeneous scenarios for the hosts including (1) individual differences, (2) movement, and (3) spatial heterogeneity. Then, the hypotheses will be tested in enclosure experiments in a natural lizard-malaria system. In these experiments, the conditions of the mathematical models on populations of infected and uninfected lizards and mosquito vectors will be recreated to quantify parasite prevalence and persistence under different heterogeneity scenarios. The quantitative interdisciplinary approach that is the cornerstone of this project is also regarded as a key gap in undergraduate and graduate training in ecology. The educational component of this project addresses this issue by developing and testing a novel pedagogical approach providing novel tools to teach mathematical modeling concepts to non-math majors This award was supported by the Mathematical Biology Program in the Division of Mathematical Sciences and the Population and Community Ecology Cluster in the Division of Environmental Sciences. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NSF Awards · FY 2025 · 2025-06

This project will test how savanna ecosystems respond to the removal of invasive species. Invasive species are introduced from outside their natural range that rapidly expand across areas where they were introduced. Invasive species negatively affect the economy and can change ecosystems in undesirable ways. Because of these negative effects, many restoration efforts involve removing invasive species. The project will test if ecosystems are resilient and can return to their original state after invasive species are removed. This project will also examine how long it takes for ecosystems to return to their original state once invasive species are removed. Both questions will be answered by experiments done in central Kenya, where an invasive ant has displaced native ants that defend Acacia trees against elephants and other browsing mammals. In invaded areas, browsing on trees is common, transforming savanna woodlands into open landscapes with few trees. Through targeted removal of the invasive ant, the project will discover whether invaded areas can be returned to their original state. Removal of invasive ants may restore the partnership between trees and native ants and reduce browsing by elephants. Across much of East Africa, Acacia trees are critical to the bioeconomy because they provide food for black rhinoceros, giraffe, and other animals. These trees are also used for fuel by humans. This project provides an opportunity to answer important questions about ecosystem resilience. Research in this system will address conservation issues that are relevant for land managers and restoration planning. This project will test the hypothesis that a foundational ant-Acacia mutualism responsible for giving rise to near monocultures of the whistling-thorn tree is resilient following the removal of the invasive big-headed ant. Invasion fronts occur along a rainfall gradient, providing an opportunity to quantify whether and under what contexts the ant-acacia mutualism is resilient to removal of big-headed ants. Specifically, this project will answer two questions: (1) following big-headed at removal, how faithfully do stability-promoting feedbacks return to approximate those from uninvaded areas (i.e., is the foundational ant-acacia mutualism resilient)? (2) does resilience hinge on time since invasion, rainfall, or both? To answer these questions, the project will employ large-scale removal of big-headed ants, assays of photosynthesis, and demographic modeling to quantify the restoration of feedback loops involving symbiotic ant activity, elephant browsing, and whole tree photosynthesis. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NIH Research Projects · FY 2026 · 2025-06

ABSTRACT Cervical spinal cord injury (SCI) disrupts neural pathways to spinal respiratory motor neurons, causing impaired breathing and even death. New treatment strategies are desperately needed to improve breathing ability after cervical SCI. Since most SCIs are incomplete, meaningful functional recovery can be induced by harnessing the intrinsic capacity for neuroplasticity, strengthening spared neural pathways to respiratory motor neurons. Therapeutic acute intermittent hypoxia (tAIH) is a simple, safe and effective means to induce respiratory motor plasticity and improve breathing ability in rodent models of acute cervical SCI but is considerably less effective with chronic injury. However, tAIH is highly effective in non-respiratory motor systems in chronic SCI, but only when paired with task-specific training. The impact of combined tAIH and task-specific respiratory training is not known. Thus, our fundamental goal is to maximize breathing recovery after chronic, incomplete cervical SCI using a combinatorial approach that pairs tAIH with respiratory training. We propose to study two distinct respiratory training paradigms: physical exercise and exposure to elevated levels of carbon dioxide (CO2; e.g., hypercapnia). Physical exercise increases breathing via a well-known and reproducible phenomenon known as “exercise hyperpnea”, whereby breathing is increased in proportion to metabolic rate and blood gas levels are regulated by a mechanism independent of chemoreceptor feedback. On the other hand, we can elicit robust, automatic increases in breathing via hypercapnia, which may provide an opportunity for task specific training in cases where vigorous exercise is not possible (e.g., those with limited mobility). This unique form of respiratory training involves activation of carotid CO2 chemoreceptors and is well tolerated and easily administered to individuals with impaired mobility. Although the mechanisms differ, both exercise hyperpnea and hypercapnia engage neural pathways involved in automatic (vs. volitional) breathing control, thus represent forms of automatic respiratory training. We will test the hypotheses that maximal therapeutic benefits will be achieved when tAIH is paired with either treadmill- or hypercapnia-based respiratory training. We will test our working cellular model concerning mechanisms of synergy between tAIH and task- specific training, which we hypothesize converges on spinal BDNF/TrkB signaling in phrenic motor neurons. Lastly, we predict lasting changes in the neural circuits innervating phrenic motor neurons, shifting the balance of excitatory vs inhibitory inputs, and ultimately increasing their excitability and overall motor output. These are the first studies to pair tAIH with respiratory training that targets automatic respiratory control, which is critical for restoring independent breathing ability. This research will inform future clinical trials as we seek potent and enduring recovery of breathing ability after chronic SCI. Indeed, our team has a documented history of translation, and we are actively translating highly novel discoveries from preclinical models to persons with SCI. Thus, in a very real sense, our work will help accelerate translation of promising ideas into clinical practice.

NIH Research Projects · FY 2025 · 2025-06

Project Summary / Abstract Alzheimer's disease (AD) is a devastating age-related neurodegenerative disease that can severely curtail life quality and expectancy. Depression and sleep disorders manifest decades before disease onset and may serve as an important early biomarker. Serotonin (5-HT) neurons in the dorsal raphe nucleus (DRN) exhibit neurofibrillary changes in the early stages of AD, which may contribute to some of these early non-cognitive symptoms. The goal of this application is to determine whether tau accumulation in 5-HT DRN neurons induces depressive-like behaviors and disordered sleep, leading to chronic sleep disruption. These sleep deficits, in turn, may promote hyperexcitability of 5-HT neurons and lead to neurodegeneration. The increased activity in 5-HT neurons due to sleep deprivation also facilitates the spread of tau pathology to the entorhinal cortex (EC), another region that is impacted early in the course of AD. Loss of 5-HT inputs from the DRN to the EC will disinhibit neurons that project to the hippocampus, precipitating tau spread and the onset of cognitive and memory problems. In Aim 1, we will use in vivo fiber photometry to measure neural activity in 5-HT neurons during tests of depressive-like behavior in mouse models of tauopathy to see if the normal function of these neurons is negatively impacted. We will also monitor 5-HT activity during sleep to see if that is altered by tau pathology. In Aim 2, we will examine the effect of sleep deprivation on 5-HT neuronal excitability and the progression of tau pathology in the brain using electrophysiology and 3D imaging. The role of increased neural activity in 5-HT neurons on the spread of tau pathology will also be examined using chemogenetic manipulations of neural activity. In Aim 3, we will determine whether tau-induced loss of 5-HT inputs to the EC alters 5-HT signaling in principal neurons that project to the hippocampus. We will also establish a role for 5-HT/5-HT2A receptor signaling in the spread of tau pathology to the hippocampus and the onset of cognitive deficits. In total, the proposed research will provide essential information concerning the impact of tau pathology on early behavioral symptoms of AD and the later development of cognitive and memory deficits.

NSF Awards · FY 2025 · 2025-06

As learning components based on artificial intelligence are becoming commonplace in cyber-physical systems (CPS), our engineering methods are lagging behind. Typically, engineers rely on their knowledge to make assumptions under which the system can guarantee a certain level of performance and safety. However, with black-box learning and increasingly large high-dimensional data, human engineers struggle to understand and formalize these assumptions, which severely limits the effectiveness of validation and monitoring. As a result, CPS systems end up susceptible to rare events, distribution shifts, and other unexpected circumstances — and are not equipped to respond to these intelligently and safely. This project aims to transform the management of assumptions in learning-enabled CPS by making novel fundamental connections between formal methods, machine learning, and decision-making. Improving our society’s ability to construct higher-performing and safer CPS for unforeseen situations, this project will deliver techniques, tools, and a catalog of typical assumptions that are expected to generalize across many CPS application domains. It will also train the workforce for future CPS in rigorous methods. This project represents a major step towards building assumption-aware CPS — ones that behave with an understanding of their own assumptions and limitations. To make these assumptions explicit and actionable, this project will build the mathematical and algorithmic foundation for assumption awareness via specifying, validating, and responding to assumptions behind the closed-loop CPS guarantees. To this end, this project will create an engineering methodology in three sequential thrusts: (1) discovering and representing relevant assumptions of learning-enabled CPS, (2) performing end-to-end validation of these assumptions across offline and online settings, and (3) enhancing decision-making and control to recover from online violations of these assumptions. The developed methodology will be evaluated on small-scale autonomous racing, underwater vehicles, and modeling autonomous street traffic. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NIH Research Projects · FY 2025 · 2025-05

PROJECT SUMMARY / ABSTRACT Opioids are the most widely used and effective agents for treating pain but are highly addictive. In addition, side effects such as nausea and respiratory depression often accompany their use, making opioids undesired by many prescribers and patients. That said, their unmatched ability to manage pain has led to continued administration and use, viewed as a necessary evil. Opioid actions, both good and bad, primarily originate at the µ opioid receptor (MOR), a G protein-coupled receptor (GPCR) found throughout the central nervous system. By activating MOR, opioids initiate various intracellular signaling pathways that mediate distinct responses. The divergence of opioid actions along these pathways are believed to be the source of co-occurring analgesic and adverse effects. In addition, the dynamic balance between pathways has implicated roles in opioid tolerance and addiction. Towards the goal of making opioid treatment safe and effective, it is essential to understand how regulation occurs along these pathways and how dysregulated systems impact signaling biases. Here, my studies will address this by identifying new regulators and determining how they influence MOR biology. Using a set of ~ 80 pre-validated genetic candidates, I will implement a MOR-MAPK platform to identify the most impactful MAPK regulators. My preliminary experiments already validated this approach and revealed several new MOR regulators. In line with these exciting new findings, mechanistic details of how this new element affects MOR signaling will be explored and followed up by studies exploring its impact on processing opioid signals in native neurons. Taken together, this will expand our understanding of the opioid signaling landscape and may provide new genetic targets for tuning signaling biases towards safe and effective opioid treatments.

NIH Research Projects · FY 2026 · 2025-05

Project Summary/Abstract Drug addiction is marked by functional changes to once healthy cell signaling pathways. Drugs of abuse such as morphine, cannabinoids, cocaine, and gamma-hydroxybutyrate (GHB) disrupt inhibitory neurotransmission signaling through G protein-coupled inward rectifying potassium (GIRK) channels. In fact, while some substances like alcohol bind directly to GIRK, the channels are also directly downstream of G protein coupled receptors (GPCRs) which make up the largest class of drug targets for FDA approved pharmaceuticals. GPCRs, heterotrimeric G proteins of the Gi/o family, and GIRK channels are linked by a series of distinct protein-protein interactions, and a substantial proportion of inhibitory neuromodulation is mediated by this pathway. One major inhibitory GPCR found in the hippocampus called GABAB receptor (GABABR) initiates a series of conformational changes that propagates through the signaling cascade resulting in GIRK channel opening. While individual subunit interactions have been studied, no consensus on the comprehensive macromolecular organization of this signaling pathway has been reached. GHB, a drug of abuse, acts as a weak agonist at GABABR and in high doses induces sedation and euphoric effects. Understanding how GABABR and GIRK channel proteins interact and are organized as a signaling cascade will provide valuable insight into how inhibitory signals are sensed, propagated, and transmitted. Significantly, GABABRs and GIRK channels have been shown to co-localize and interact in neurons, and both GABABR and GIRK channels form complexes with inhibitory G protein subunits. Thus, this proposal plans to test the hypothesis that GIRK channel activation consists of a preformed complex that is rearranged upon GPCR/G protein activation. To test this hypothesis, I will use optical biosensors and GIRK signaling assays in Gα null cells to define the functional signalosome. Additionally, I will define the protein-protein binding interfaces within the complex using crosslinking-mass spectrometry. Finally, I will determine how the protein-protein interactions change from the inactive to the fully active signaling state. Taken together, this project will provide a clear understanding of how inhibitory GABAB-G protein-GIRK signaling occurs and more broadly, how drugs such as GHB hijack GPCR- ion channel dynamics.

NIH Research Projects · FY 2026 · 2025-05

There is an urgent unmet need in the clinic to improve response rates to immune checkpoint inhibition (ICI) treatment and extend overall survival in these treatment-refractory non-small cell lung cancer (NSCLC) patients, which is an estimated 68% of all lung cancer patients. We recently showed that microbiota transplantation feces from ICI responder (R) patients into gnotobiotic lung cancer allograft mice decreased tumor growth compared to non-responders (NR) colonized mice following anti-PD-1 therapy, a phenomenon associated with enrichment of the Bacteroides genus. Our preliminary work identified 183 culturable Bacteroides isolates from feces of R mice, with 6 out of these strains able to stimulate IFNγ production from primary CD8+ T cells. A consortium composed of these six stimulatory isolates (6-Consort) decreased tumor growth compared to NR feces-colonized mice following treatment with ICI and increased intratumoral and systemic IFNγ production. A combination of bioassay-guided fractionation with metabolomics performed on the supernatant of these bacteria identified novel small molecule Bac429, which was synthesized and found to induce IFNγ production from primary CD8+ T cells. Moreover, intra-tumor Bac429 injection in xenograft mice augmented anti-PD-1 mediated anti-tumor effect. These exciting findings suggest that some bacteria from ICI-responsive patients produce small molecules that augment immunotherapy responsiveness. Our central hypothesis is that specific bacteria produce small molecules that determine ICI efficacy and toxicity by engaging host immune responses. The rationale for the proposed research is that once we understand the interplay between bacteria and cancer therapy, it would be possible to design selective bacteria-derived drugs to augment responsiveness to immunotherapy. We plan to test our central hypothesis and fulfill the overall objective of this application with the following specific aims. Aim 1: Define the functional impact of Bac429 on experimental NSCLC. Our hypothesis is that Bac429 is a microbially-regulated small molecule with immunostimulatory effect impacting response to anti-PD-1 treatment in lung cancer. Aim 2: Establish the relationship between diet and Bac429 production in 6-consort mediated anti-PD-1 synergistic effect. Our hypothesis is that selective dietary glycan modulation will affect bacterial metabolism and Bac429 production and that this gene-diet interaction can be harnessed to modulate anti-tumor immunity. Aim 3: Design of cis-Bac429 to improve anti-tumor immunity properties. Our hypothesis is that key structural modifications of Bac429 will improve solubility, bioavailability and anti-tumor immune effect. At completion, this project will characterize bacterial-derived metabolite Bac429 and its mechanism of action implicated in the anti-tumor efficacy of anti-PD-1 treatment. This knowledge will serve as a springboard for future studies expanding to other forms of solid tumors.

NIH Research Projects · FY 2025 · 2025-05

ABSTRACT: Chronic rhinosinusitis (CRS) is the leading cause of olfactory dysfunction in the general population. Olfactory dysfunction most commonly occurs in patients with CRS with nasal polyposis (CRSwNP), with up to 80% of patients exhibiting olfactory loss. One anti-inflammatory agent that may have beneficial effects in the treatment of CRSwNP is vitamin D3 (VD3). We and others have reported, that patients with CRSwNP are deficient in 25(OH)D3. Recently we have also observed that 25(OH)D3 deficiency was associated both subjective and objective olfactory loss. Conversely, using a murine model of cigarette smoke (CS)-induced CRS, we observed that IN delivery of 1,25(OH)2D3 was able to improve olfactory function. Therefore, we hypothesize that VD3 metabolites could serve as novel broad spectrum anti-inflammatory capable of reversing CRS-related olfactory loss. While human observational studies have suggested that in the superior turbinate an elevated presence of granulocytes, such as eosinophils and neutrophils, are associated with olfactory dysfunction in CRSwNP, mechanistic studies confirming this observation are lacking. Previously we have shown in mice, that dietary deficiency in VD3 caused significant increases in eosinophils and neutrophils. Therefore, will also test the hypothesis that VD3’s ability to reduce inflammation and improve olfactory outcomes, is through its modulation of granulocyte functions. We will test these novel hypotheses through the execution of the following aims. AIM 1 will dissect role of VD3 metabolites in the regulation of inflammation associated with CRSwNP-olfactory loss. In Aim 1A we will dissect the interplay between olfactory loss, VD3 metabolites, and sinonasal inflammation in patients with CRSwNP. AIM 1B we will dissect mechanisms by which VD3 metabolites can modulate endogenous and irritant-induced inflammation using human sinonasal nasal epithelial cells. Collectively, AIM 2 we will determine the role of VD3 metabolites in modulating granulocyte-induced olfactory loss in vivo. AIM 2A will determine the impact of granulocyte depletion on improving olfaction functions in vivo. We will utilize two murine models of CRS: aspergillus fumigates-extract induced model to generate eosinophilic disease, and a CS-induced mouse model to create neutrophilic disease. We will pair these models with eosinophil or neutrophil depletion protocols to determine whether removal promotes reversal of established disease and restores olfactory loss. AIM 2B will determine the ability of IN VD3 metabolites to improve olfactory loss and disease severity, reduce inflammatory cell infiltrate, and allow for regeneration of olfactory neurons and epithelium. If successful, these studies could provide evidence for the use of IN VD3 as a treatment for CRSwNP-related olfactory loss.

NSF Awards · FY 2025 · 2025-05

With the support of the Chemistry of Life Processes (CLP) program in the Division of Chemistry, Professor Jeffrey Rudolf of the University of Florida is studying a family of oxidative enzymes within the context of organic molecules made by bacteria. Natural products are small organic molecules that are made by organisms in nature. Natural products have profound impacts on society as commercially, agriculturally, and pharmaceutically relevant chemicals; they also serve as important probes for understanding fundamental processes in chemistry and biology. Cytochrome P450 enzymes (P450s), best known for their importance in human health, perform key enzymatic modifications of natural products in a variety of organisms including bacteria. The project aims to discover new natural products through the identification of unique P450s within the genomes of target bacteria and to understand the molecular interactions between P450s and their redox partners, proteins that are required for P450s functionality. This pursuit will allow graduate and undergraduate students to gain valuable training in bioinformatics, molecular biology, bacterial genetics, natural products chemistry, biochemistry, and analytical chemistry techniques. The project will also establish an Undergraduate Mentoring and Career Development Program (UMCDP) for select primarily undergraduate institutions (PUIs) and provide PUI students summer research experience opportunities in the Rudolf Lab. The goals of these programs are to increase awareness of career opportunities in science, provide a route to mentored research opportunities and graduate programs, and educate students in modern research topics and advancements. P450s are one of the most accomplished ‘chemists’ employed by nature and the study of microbial P450s reveals their diverse roles in nature, expands their catalytic repertoire, and exposes their potential for biotechnological applications. With the explosion of bacterial genomes now available, it is evident that our understanding and use of P450 catalysis is limited. This proposal seeks to achieve the following objectives: (i) discover novel natural products with unique P450 functionalities, (ii) build a foundation of sequence-structure-function knowledge through the characterization of P450s, and (iii) identify native redox partners of bacterial P450s. These goals will be accomplished through an interdisciplinary approach including genome mining, metabolomics and transcriptomics of native and genetically engineering bacteria, and functional characterization of P450s using genetic knockouts and a variety of biochemical and biophysical techniques for in vitro reconstitution. This proposal will make fundamental contributions to natural products biosynthesis and to understanding the general principles of P450 enzymology. In addition, synthetic and biosynthetic chemists who aim to functionalize unactivated C–H bonds or use P450s as biocatalysts will benefit from the results generated by this project. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NSF Awards · FY 2025 · 2025-05

Efficient cooling is a major challenge in high-performance computing, power electronics, and renewable energy systems. Microchannel flow boiling, which involves absorbing waste heat by boiling a refrigerant in flow through tiny channels, is a promising solution for removing high heat loads in compact spaces. However, designing these systems relies on trial-and-error methods due to the complexity of the underlying physics. As bubbles form during boiling, they merge into larger bubbles, which affects the rate of heat removal. This project will apply machine learning to predict the transition from flow regimes of small, separated bubbles to longer, stretched-out bubbles in microchannels. Understanding and controlling this transition is critical for improving cooling efficiency, preventing system instabilities, and enhancing the performance of next-generation thermal management systems. The research will make use of high-speed experiments, computational simulations, and machine learning to develop predictive models that can rapidly explore different operating conditions. By combining fundamental thermodynamics with advanced computational techniques, this work will improve the reliability and efficiency of microchannel cooling systems. The project will also support student training in interdisciplinary areas of fluid dynamics, AI, and thermal management. This research will develop a novel machine learning model, known as a Parametrized Hybrid Physics-Informed Neural Network (PH-PINN), to capture the complex multiphase interactions in bubbly flow in microchannel flow boiling. The model will integrate high-fidelity experimental data and interface-resolved simulations to predict how bubbles nucleate, grow, detach, and merge within confined channels. Unlike conventional models that require extensive computing resources, the PH-PINN will allow rapid predictions across a wide range of physical conditions without retraining. The project will also implement a Physics-Constrained Temporal Generative Adversarial Network (PC-Tempo-GAN) to model the evolution of the vapor-liquid interface while ensuring compliance with conservation laws and boundary conditions. This approach represents a major step toward integrating physics-based constraints into AI-driven simulations, enabling more accurate and computationally efficient predictions of phase-change phenomena. The results of this research will contribute to the development of energy-efficient cooling technologies, reducing design time and cost while enhancing the performance of critical systems in computing, electronics, and renewable energy applications. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NSF Awards · FY 2025 · 2025-05

This Faculty Early Career Development Program (CAREER) grant will fund research that looks to advance the field of optimization by providing a new generation of learning-enabled cutting planes that can equip commercial optimization solvers with significant new capabilities. Cutting planes can refine a problem's formulation and certify solution quality, complementing other approaches that primarily seek feasible decisions without guarantees. However, stronger cutting planes incur a higher computational cost and radiate effects through the optimization process. This research project intends to develop novel learning architectures to judiciously deploy cutting plane strategies intending to improve current data-agnostic techniques by exploiting the presence of shared structure in modern optimization settings. The improvements will enable faster solution times and more complex models for challenging operational problems, exhibited in the project by engineering applications in power systems, logistics, and healthcare. The educational plan will extend a current partnership in the non-profit sector to increase accessibility of valuable optimization expertise and provide student engagement through engineering senior design projects. Integer programming solvers currently rely on restricted cuts from a broader disjunction-based family of inequalities, which are derived from tightening the feasible region via subproblems. Incorporating cuts from stronger disjunctions with more terms is hindered by a lack of generalizable understanding of what makes a cut useful and how solver components interact. Towards addressing these obstacles, this project will employ theoretical analysis and computational experiments to create efficient learning-based cut and disjunction selection strategies by: (1) classifying when cuts help; (2) adaptively identifying beneficial disjunctions and subsets of cuts; (3) tailoring models for unit commitment, vehicle routing, and organ exchange market problems; and (4) applying the new methods to optimize logistics at local nonprofits in combination with student capstone and research opportunities. The investigation will yield deeper, transparent, and actionable insights into cuts and disjunctions, informing algorithms for which implementations will be open sourced and whose performance will be evaluated on a curated and publicly-releasable benchmark dataset. 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.