University Of Florida

NIH Research Projects · FY 2025 · 2025-01

ABSTRACT - Substance Use Disorders (SUDs) and the psychiatric comorbidities that accompany them are underserved, vicious disorders that leave individuals, their loved ones and society negatively impacted. Psychoactive substances, such as those containing a tryptamine moiety (i.e. psilocin), show promise in relieving SUD tendencies yet the underlying mechanism responsible is yet to be fully elucidated. Classical approaches aimed at deducing the receptor and mechanism of action involve probing specific receptors, hypothesized to be responsible for downstream processes resulting in symptom relief, with chemical probes possessing affinity for said receptor and observing if symptoms improve. A widely acknowledged weakness with this approach is the lack of specificity a compound can exhibit for a receptor or interest, leading to off-target receptor binding thereby confounding the independent variable. The same specificity issue found in stimulatory experiments holds true in suppressive like experiments, where a blocker is used to block a receptor binding sight leading to suppression of a specific pathway. Therefore, elucidating the exact mechanism is inherently difficult and would require molecular probes which are more specific than what are found currently. In lieu of synthesizing new compounds, we propose the development of rapid analytical methodologies, leveraging tandem mass spectrometry, capable of screening biomass to discover preexisting natural products containing a tryptamine moiety. Ion-activation methods such as Higher-energy Collisional Dissociation (HCD) and Ultra-Violet Photon Dissociation (UVPD) will serve as complimentary methods for both identifying and characterizing compounds containing a tryptamine moiety. HCD gradually imparts internal energy thereby cleaving the lowest energy bonds whereas UVPD imparts internal energy rapidly resulting in more stochastic cleavages. HCD and UVPD are therefore complimentary as HCD in tandem with computational models can identify compounds with a tryptamine or indole moiety, due to the stable heterocyclic ring remaining intact under activation, and UVPD can characterize the candidate structure more extensively. The outcome of this project will result in methodologies capable of screening biomass to rapidly identify and characterize new psychoactive compounds. The new compounds discovered from this method will enable researchers to better study the mechanistic explanation responsible for psychoactive compounds efficacy leading to more effective therapies with reduced off target consequences.

NIH Research Projects · FY 2026 · 2025-01

PROJECT ABSTRACT In neurons, changes in transcription and translation are important processes underlying the process of long-term potentiation at the synaptic level. However, the compartment-specific and cell-specific variations in translation and transcription during the process of long-term memory (LTM) storage, along with the molecular mechanisms responsible for these changes, remains unclear. Previous studies have found that mRNAs differentially localize to different areas of the neuron and serve as the basis for localized translation via the actions of molecular motors, such as kinesin and dynein. The importance of these motor proteins in the process of neuronal function is well- documented, such that disruptions in the functions of these motors are associated with a range of neurodegenerative diseases. Despite the importance of these proteins, the processes of translational control that governs molecular motors during LTM remains poorly understood. This proposal seeks to understand this relationship between local translation, molecular motors, and LTM storage, utilizing the model Aplysia californica. Recent investigations into the role of axonal organelle transport during LTM identified enhanced bidirectional transport of mitochondria associated with synapse maintenance. This enhancement in transport is dependent upon translation and transcription. Building upon this finding, I hypothesize that compartment-specific regulations of translation contributed to this change in transport, and play an important role in synapse formation, maintenance, and plasticity. To test this hypothesis, puro-PLA will be used to examine the localized translation of kinesins and dynein subunits, along with dynactin, using the Aplysia SN-L7 coculture system to reconstitute synapses in vitro. In addition, puro-PLA will also be employed to examine the expression of translation regulators such as eIFs, in order to elucidate the potential direct effects these regulators have on translation. Furthermore, puromycin labelling will be used in conjunction to sensitization, tissue clearing and light-sheet microscopy to assess temporal changes in translation at a cell-specific manner within the entire Aplysia CNS. These studies will shed more light on the role of translational regulation in LTM, in both a simple circuitry and the entire nervous system. The results of these studies will further elucidate the role of translational control in axonal transport dysfunction that contribute to neurodegenerative diseases, and identify potential targets for therapeutic development.

NSF Awards · FY 2025 · 2025-01

This project will support professional development opportunities for computer science (CS) teachers of grades K-8 including general education and special education classes. Focusing on students' first experiences with computing in school contexts, this project seeks to fundamentally improve the level of engagement and learning for all K-8 learners, including those with disabilities, in CS and robotics education. Through a Networked Improvement Community Research-Practice Partnership, this project will work in three school contexts: Broward County Public Schools in Florida, Chicago Public Schools in Illinois, and the Computer Science Teachers Association's nationwide community of practice. The collaborative partnership will (1) bring together cohorts of general and special education teachers in both face-to-face and online professional development focusing on Universal Design for Learning and High Leverage Practices, (2) investigate the needs, barriers, and strategies for general and special education teachers to meet the needs of all students in K-8 CS education, (3) build and disseminate a shared practical knowledge base about ways in which professional development for general and special education teachers can contribute to CS education for all, and (4) share information about what K-8 students can accomplish in STEM education. This project is a Networked Improvement Community Research-Practice Partnership aimed at addressing a shared problem of practice related to the engagement of all learners in CS education. The partnership will leverage improvement science and design-based implementation research to develop improvement goals and utilize a shared set of measures to understand variation and make progress across a variety of contexts. Necessary steps to ensuring quality CS education for all students include: (1) strengthening the partnership through developing a shared theory of improvement, (2) developing and revising shared systems of measures, (3) valuing practitioner expertise and shared leadership, (4) capacity-building through ongoing teacher professional development and professional learning communities, and (5) cycles of design-based implementation improvement cycles. As a networked improvement community, the project will investigate the level of engagement of all learners across different K-8 CS instructional settings, including catalysts and barriers to engagement across the school contexts; and how instructional practices such as Universal Design for Learning, High Leverage Practices and accessibility are enacted by general and special education teachers across multiple K-8 CS settings. Lastly, the project will use a mixed methods approach to understand each partners' unique contexts and large-scale quantitative analysis of the participation of K-8 students across settings. This project is funded through the Computer Science for All: Research and RPPs program. 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 · 2025-01

PROJECT SUMMARY/ABSTRACT Antimicrobial resistance (AMR), particularly in the context of hospital-acquired infections, poses a significant global challenge. It increases morbidity, mortality, healthcare costs, complicates infection control measures, and undermines the effectiveness of existing antimicrobial treatments. This proposal is designed to address the complexity of AMR transmission patterns, which have remained uncertain under traditional outbreak management strategies. Therefore, novel data-driven approaches are urgently needed, leveraging modern genomic and computational methods for a better understanding and control of AMR pathogens. The proposal's overarching objective is to provide a high-resolution characterization of multi-drug resistant (MDR) bacterial transmission patterns and evolution within and beyond hospitals. The project will integrate complex data sources, such as whole-genome sequencing (WGS), electronic health records (EHR) and epidemiologic data from a prospective cohort study, and then apply phylodynamic and causal artificial intelligence methodologies to achieve these goals. It focuses on two specific aims. The first will be to characterize flow of transmission from communities to hospitals in gram-negative MDR bacterial infections. The application of WGS, linked with sociodemographic and economic data, will be used to trace the lineages of these bacterial infections. Based on preliminary work on gram-positive MDR pathogens, we expect the majority of gram-negative hospital-onset infections originate from community ancestral strains rather than within the hospital setting, pointing towards independent introductions of bacterial strains into the hospital setting. The second aim will identify use EHR and causal artificial intelligence to develop a causal model that predicts WGS-confirmed MDR bacterial outbreaks with higher precision than conventional approaches. This aim will identify actionable within-hospital factors that increase the risk of MDR bacterial outbreaks. By addressing a critical gap in the interplay between hospital and community settings in the transmission of MDR bacterial strains, the outcomes of this study are expected to contribute to a potential shift in how infection control teams utilize existing data sources. Ultimately, this project will provide the trainee with the expertise in using complex data to understand the evolution of emerging pathogens and identify mechanism of transmission in hospitals. The skills cultivated from this project will enable the trainee to pursue his long-term career goal in becoming an infectious disease physician-scientist with the unique ability to integrate molecular biology, hospital epidemiology, and modern data science approaches. This research and training directly target the need for innovative data science to inform tailored interventions to combat AMR, especially among gram-negative pathogens.

NSF Awards · FY 2025 · 2025-01

This Boosting Research Ideas for Transformative and Equitable Advances in Engineering (BRITE) Pivot award aims to establish a systematic methodology for bio-inspired design using artificial intelligence (AI) and mathematical sciences. This methodology will be applied to design probabilistic fasteners that facilitate robotic assembly operations. Robots face fundamental limitations in handling complex assembly tasks, a challenge that can be addressed by drawing inspiration from biological attachment mechanisms such as gecko feet, burrs, and bird feathers. Despite the significance of bio-inspired design, no standardized methodology currently exists to help designers adequately learn from nature. This project advances AI and pattern recognition algorithms to systematically assess images of biological systems and detect visual characteristics such as shape, distribution, and density. Also, it utilizes fractal geometries to perform dimensional analysis of biological mechanisms. Fractal geometry is a mathematical framework used to describe complex, irregular, and self-replicating structures, characterized by self-similarity, where smaller parts resemble the whole at varying scales. The resulting bio-inspired probabilistic mechanical fasteners address long-standing challenges in robotic assembly by providing secure, repeatable attachments without requiring expert precision or complex alignment. This project promotes scientific progress through innovation at the intersection of engineering design, mathematics, robotics, and biology. Furthermore, it aligns with national interests by revolutionizing smart manufacturing and various industries reliant on robotic assembly, while advancing STEM education through undergraduate research experiences, webinars, workshops, and K-12 activities. The objective of this project is to develop a bio-inspired design methodology powered by AI and fractal geometries with a focus on the design of probabilistic mechanical fasteners suitable for robotic assembly tasks. The objective is achieved through five main research tasks: (1) advancing pattern recognition algorithms to extract essential patterns within biological mechanisms and facilitate the conceptual design phase by identifying target and fractal-based patterns, (2) advancing dimensional analysis techniques based on fractal geometries to accelerate the detailed design process, (3) developing cutting-edge deep learning models for three dimensional reconstruction of biological attachment mechanisms, which integrates semantic information and employs noise reduction strategies, (4) systematic optimization and conducting of functional analyses to fine-tune mechanical fasteners parameters, and (5) performing simulation analysis for the generation of synthetic data, coupled with the real-world robotic assembly experiments to evaluate the performance of bio-inspired mechanical fastener prototypes. The educational plan includes offering summer research experience for undergraduates, workshops and webinars, and training of K12, undergraduate, and graduate students 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.

NSF Awards · FY 2025 · 2025-01

Saltwater intrusion and sea-level rise (SWISLR) present major challenges for rural and small coastal systems whose residents often need economic and political aid to ameliorate SWISLR issues. Rural and unincorporated areas often do not have the same support as more populated regions due to the lower population densities and constrained planning capacity. Many small coastal communities are economically, culturally, and spiritually connected with their location, making adaptation to SWISLR crucial to maintaining the capacity of these communities to coexist with coastal change. This project works across research institutions, local communities, tribal governments, and municipalities to establish partnerships for understanding local flooding hazards and co-develop science priorities that will directly lead to actionable solutions. The core activity for this planning grant is to conduct a series of surveys, community workshops, and interviews with stakeholders across Florida (FL) and North Carolina (NC). The goal is to identify specific earth system science problems related to coastal flooding that will lead to detailed, local information for coastal communities. Ultimately, this project will increase the ability of small coastal communities to develop and implement adaptation strategies, while also learning from other communities across the Southeast who are facing similar challenges. This grant advances earth systems hazard research through capitalizing on innovations in high resolution data (remote sensing, machine learning, flood modeling). With these data, this project answers localized questions about the variability of flooding and coastal hazards, moving beyond regional projections to inform local flooding hazards and determine the consequences of a changing system. Bringing new knowledge to overlooked systems and communities will allow understanding of the variability of flooding hazards, determine how understudied areas might contribute new insights to our understanding of SWISLR, and include underserved voices (Indigenous and local communities) in the coastal solutions discussion. Through developing a repository of successful coastal projects and initiating a series of workshops, this project will increase the communication and dissemination of information and stories beyond state lines. This project connects to communities through a co-production process to enhance resilience to SWISLR hazards. Collaboration through FL Sea Grant, NC Sea Grant, and SWISLR Research Coordination Network extends the results of this project throughout municipalities in the southeastern coastal plain. The project deliverables will be openly available and archived as open pre-prints or deposited into open repositories using FAIR data practices. 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 · 2025-01

Project Summary Renal cell carcinomas (RCC) are the 7th most common types of cancer in the world with over 400,000 new cases and 170,000 deaths worldwide each year. Clear cell renal cell carcinomas (ccRCC) are the most common (>80%) and most aggressive subtype of RCC. ccRCC are highly vascularized tumors with elevated levels of vascular endothelial growth factor A (VEGFA) due to frequent (>80%) loss of function the Van Hippel Landau gene. As such, the first line of therapy for ccRCC are tyrosine kinase inhibitors (TKIs) which target the VEGF pathway in combination with immune checkpoint inhibitors (ICIs). However, these therapies have shown to be effective in only a subset of patients. This highlights the need to identify which patient cohorts are likely to respond and to develop novel therapies to improve the efficacy of ICIs. Angiopoietin-like 4 (ANGPTL4) is a secreted protein with several functions including regulating angiogenesis and has been shown to promote breast cancer progression and metastasis. We found that ANGPTL4 is highly upregulated in ccRCC compared to normal kidney tissue and blocking ANGPTL4 or knockout of ANGPTL4 reduces tumor growth in a 786O ccRCC xenograft model. Knockout of ANGPTL4 also decreased tumor angiogenesis and increased expression of adhesion molecules on tumor associated endothelial cells – an indicator of vessel normalization which is a key mechanism for combination with ICIs. We also found that a subset of ccRCC patients express low levels of ANGPTL4 and these patients have a shorter overall survival and less frequency of VHL mutations. Correlated with this we found that knockout of ANGPTL4 in ccRCC cells with wild type VHL increased tumor growth while blocking antibodies against secreted ANGPTL4 had no effect. This indicates a cancer cell intrinsic function for ANGPTL4 that is relevant to this subset of ccRCC patient. Based on these findings, we hypothesize that ANGPTL4 has a dichotomous function in ccRCC where secreted ANGPTL4 promotes angiogenesis and tumor progression and cancer cell intrinsic ANGPTL4 suppresses tumor growth possibly through regulation of lipid metabolism. Targeting secreted ANGPTL4 in the tumor microenvironment in combination with ICIs is a rational therapeutic approach for treating ccRCC patients with high levels of ANGPTL4. The objective of specific Aim 1 is to define the role of ANGPTL4 in the tumor microenvironment in ccRCC progression, metastasis and tumor vascularization. The goal of Aim 2 is to use mouse models of ccRCC to preclinically test the efficacy of combining anti ANGPTL4 antibodies with immune checkpoint inhibitors. In Aim 3 we will determine the cancer cell intrinsic function of ANGPTL4 in ccRCC cell lines in regards to regulation of lipid metabolism. This project will establish the mechanistic role of ANGPTL4 in the pathophysiology of ccRCC and its potential as a therapeutic target in combination with immune checkpoint inhibitors.

NIH Research Projects · FY 2025 · 2025-01

The onset of the COVID-19 epidemic in December 2019, caused by the novel SARS-CoV-2 coronavirus, unleashed a catastrophic toll, claiming over 7 million lives and imposing an unparalleled strain over the healthcare, social, and financial systems worldwide. Although COVID-19 is no longer a global emergency, the healthcare burden continues. This is because thousands of people have experienced multiple neurological symptoms for months or even years after the initial infection, which is referred to as Long Covid. These symptoms include “brain fog”, persistent headache, disturbed consciousness, fatigue, and cognitive decline to name a few. Unfortunately, hardly anything is known about the molecular underpinnings of these prolonged neurological manifestations and the potential involvement of SARS-Co-V2 proteins in the onset of degenerative dementias like Alzheimer’s disease (AD). To address this gap, we screened all 29 proteins encoded by the SARS-CoV-2 genome and found one non-structural protein that induces a very aggressive phenotype when expressed in the eye of transgenic flies as well as loss of axonal projections when expressed in the Drosophila brain mushroom body neurons, which are associated with memory functions. Strikingly, we also found that this protein aggravates Abeta42-dependent neurodegeneration and dramatically exacerbates Abeta42 aggregation as evidenced by thioflavin staining. This suggests that the potential presence of this SARS-CoV-2 protein in the brain could trigger a response to influence the development of Alzheimer’s disease. To test this hypothesis, we will perform an age-dependent study of the neurotoxic role of this protein in a Drosophila model of Abeta42 deposition using genetic, molecular and behavioral approaches (Aim1) as well as a comprehensive pathological analysis in mouse models of Alzheimer’s disease (Aim2). This complementary work in flies and mice is highly significant because it may uncover a groundbreaking pathological association between coronavirus proteins and Alzheimer’s disease. In addition, it may also lead to a paradigm shift to guide new research priorities to prevent a potentially devastating public health crisis in the future.

NIH Research Projects · FY 2026 · 2025-01

Colorectal cancer (CRC) incidence has been steadily increasing in subjects younger than 50 years old. A relatively recent body of literature suggests CRC could be the result of interaction between dietary components and specific microorganisms. Identification of carcinogenic diet-bacteria interplay would deliver potentially new insight for CRC prevention and treatment. Previous studies revealed that diet rich in microbially accessible sulfur is associated with relative enrichment of Bilophila wadsworthia in the gut and higher risks of CRC including early onset CRC. Energy drinks, the second most popular dietary supplement of teenagers and young adults, commonly contain high amounts of the sulfur amino acid taurine. Taurine can be metabolized by Bilophila wadsworthia to produce H2S, which exhibits DNA-damaging activity at physiological levels. Our preliminary data show that while taurine supplementation protects against colitis and colonic cancer development in the absence of B. wadsworthia, B. wadsworthia colonization together with taurine supplementation promotes development of neoplastic lesions in DSS/Apcmin/+ mice. Taurine and B. wadsworthia, alone or in combination, significantly alter the microbiota composition along CRC development. Importantly, taurine supplementation favors B. wadsworthia gut colonization in mice, suggesting active taurine-B. wadsworthia interplay. In this application, we propose to test the hypothesis that B. wadsworthia-mediated taurine-H2S biotransformation determines the impact of dietary taurine on individual’s gut homeostasis, inflammation and carcinogenesis. We plan to test this hypothesis with the following specific aims: Aim 1. Determine the interaction between dietary taurine and B. wadsworthia in intestinal inflammation and tumorigenesis. The hypothesis is that taurine favors production of disease-promoting H2S by sulfur- metabolizing bacteria such as B. wadsworthia. We will define the impact of taurine and energy drink supplementation on mouse colonic inflammation and tumorigenesis in relation to B. wadsworthia colonization status and metabolic activity. Aim 2. Determine the mechanism by which H2S exerts neoplastic effect. We will determine host genes regulating responses to H2S genotoxicity using whole genome CRISPR/Cas9 genetic screen, and elucidate the in vitro and in vivo mutational signatures induced by H2S and B. wadsworthia taurine metabolism respectively. Aim 3. Evaluate the impact of energy drink consumption on microbiota function from a healthy young adult cohort. We will leverage an ongoing interventional trial where longitudinal stool samples are collected from healthy young adults before and after energy drink consumption to determine microbiota functional capacity changes. We will perform fecal microbiota transplantation in gnotobiotic DSS/Apcmin/+ mice to compare carcinogenic activities of feces collected pre- and post-energy drink consumption. This project will provide key knowledge to prevent intestinal inflammation and carcinogenesis through modulation of taurine intake or bacterial metabolic activity.

NSF Awards · FY 2025 · 2025-01

In the United States, health policy advocates allege a growing quality crisis, as public health experts consistently report that the US population pays significantly more for healthcare than other nations, with worse outcomes. The rhetoric of quality and its moral mandate to ensure and improve medical services is now a central part of health policies globally. Yet little is known about how the idea of quality itself is conceptualized in clinical care spaces, how these conceptions might differ according to the characteristics of the individuals and organizations who attempt to provide quality care, and how these conceptions frame the types of actions individuals and organizations implement in pursuit of quality improvement. This doctoral dissertation research investigates if and how the rhetoric of quality improvement and assurance impacts the provision of medicine in an isolated rural medical setting. In addition to providing training for a graduate student, this work will be disseminated widely to academic and non-academic audiences. Findings also inform ongoing development of a regional social science and medicine curriculum for family medicine residents. Through an ethnographic study with health administrators, physicians, nurse practitioners, physician assistants, and clinical staff, researchers analyze the process of creating quality health services within the medical center as well as values, perceptions, and organizational dynamics that influence how quality is conceptualized and enacted across multiple care settings. The researchers use participant observation of the daily activities at a medical center and observe administrative and clinical practice across each care setting. Data will be collected using focal follows, observation, interviews, methods from cognitive anthropology, and archival research. The research findings expand understanding of local and national attempts to influence biomedical practice and make significant contributions to the anthropology of policy, medical anthropology, the anthropology of institutions, quality improvement, and implementation science. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NIH Research Projects · FY 2026 · 2025-01

EpiGNOME: Epigenetic Graphical Networks Of Methylation Effectors for COPD Progression ABSTRACT Modern clinical and translational sciences rely on big data to identify drivers of disease progression and develop predictors of disease outcomes. Chronic Obstructive Pulmonary Disease (COPD) is a leading cause of death and likely represents several molecular subtypes, which makes the prognosis and treatment challenging. Genetic variation only explains a fraction of COPD pathogenesis. DNA methylation variability is particularly important since it is more stable than gene expression and captures genetic influences and longitudinal exposures. Despite its likely prominent role in disease and potential for therapeutic targeting, limited investigation has focused on methylation, partly because of the analytic challenges posed by the high-dimensional and collinear data. This project focuses on the investigation of the role of DNA methylation in COPD progression. We will develop novel directed (causal) graph methods for high dimensional collinear data. These methods will provide a foundation for advancing integrative computational systems biology by overcoming challenges inherent in large scale methylation datasets. Through these new methods, applied at a population scale, we will identify potential cause- effect relationships among DNA methylation and genetic and clinical effectors related to COPD subtypes and progression. Our premise is that DNA methylation will reveal molecular mechanisms and drive the development of stable COPD disease subtypes, not previously revealed with genetic and gene expression analyses. NHLBI's Trans-Omics for Precision MEDicine (TOPMED) initiative includes a massive multi-Omic profiling program that promises to break down barriers to understanding lung diseases. We will assemble results of genome-wide DNA methylation analysis from leukocytes (two cohorts: COPDGene, LTRC), and lung tissue biopsies (two cohorts: LTRC, LTCOPD); and longitudinal DNA methylation data from over 11,000 samples. These resources provide the foundation for the development of a novel computational framework for DNA methylation analysis and will enable us to further investigate COPD subtypes and identify effectors of COPD progression. The logic of our approach begins with the identification of methylation marks directly linked to COPD outcomes from cross- sectional leukocyte DNA methylation (Aim 1) and proceeds with similar analyses using repeated measures of DNA methylation and pulmonary phenotypes (Aim 2). Finally, in Aim 3 we will identify COPD progression subtypes and compare lung to blood epigenetic pathways. This project will advance algorithmic development beyond standard methods; it will lead to generalizable insights into features of the epigenome that may drive lung function decline and COPD progression; and identify stable COPD subtypes that will reveal new molecular mechanisms and can be used to design new disease prevention and management strategies. This proposal is a response to NOSI (NOT-HL-23-067), “Integrative Omics Analysis of NHLBI TOPMed Data”, with the bulk of discovery and methods innovation leveraging extant TOPMed data.

NSF Awards · FY 2025 · 2025-01

Synthetic biology has significant potential in plant agriculture, for example, by providing new trait genes to breeding programs, engineering plant-microbe interactions, and developing new crops and products. This Workshop brings together a number of different communities such as established, public- and private-sector plant breeders and metabolic engineers as well as early-career plant synthetic biology researchers such as faculty, postdoctoral researchers, and PhD student trainees to catalyze interactions that will help the field reach its potential positive impact on science and society. The workshop forum provides an opportunity for the participants from these different communities, to learn from and network with each other, and to leave with fresh, down-to-earth, actionable perspectives and contacts. The format of the workshop would include keynote talks, short talks, idea pitches and posters, as well as panel and breakout discussion sessions. After the workshop, a report will be prepared and circulated within the plant synthetic biology community. This Workshop brings together early-career synthetic biology researchers, agricultural synthetic biology and agribusiness professionals as well as postdoctoral researchers and graduate students. The format is a lively mix of talks highlighting realistic opportunities and challenges and showcasing real-world applications. Also included are idea-pitches from early career researchers and live feedback from professionals, posters and breakout sessions. The end point will be a crafting of a report to project the Workshop’s message to the plant synthetic biology community. The aim above all is to give participants from different communities opportunities to learn from and network with each other, and to leave with fresh, down-to-earth, actionable perspectives and contacts. This award is co-funded by the Division of Molecular and Cellular Biosciences, the Systems and Synthetic Biology Program, the Cellular and Biochemical Engineering Program and the Plant Genome Research Program. 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 · 2025-01

The objective of this CiviL Infrastructure research for climate change Mitigation and Adaptation (CLIMA) project is to integrate low-energy mechanisms into the designs of structural components, enabling them to adapt their shapes and configurations with minimal energy input. This project aligns with NSF’s mission of promoting the progress of science and advancing the national health, prosperity and welfare by creating new knowledge in energy-efficient and adaptable structures and design methodologies, and by enabling more resilient infrastructure against environmental challenges. The research will establish a firm analytical foundation that enables: (a) the integration of multi-stable systems in engineering designs; (b) the establishment of integrative design methodologies based on additive manufacturing and generative design; and (c) the combination of architectural and performance-based design that will empower system-level design and deployment of adaptive systems. The theoretical innovations will be realized by creating adaptive building enclosures that can change their shapes as necessary to improve building energy performance. Potential applications include structural systems that can adapt to changes in the environment, mechanical systems that can be rapidly deployed, and medical devices that can be modulated to accelerate healing. This project also includes the development of educational methods to train the next generation of engineers and architects interested in the broad concept of adaptive structural systems. The overarching goal of this CLIMA project is to establish a strong foundation for the design and implementation of multi-stable components in structural and mechanical systems in order to achieve low-energy geometric modulation. The research draws upon architectural and structural design, additive manufacturing, and generative design theory to produce a new realm of adaptive capabilities through multi-stable systems. The research is innovative in its study of (a) snap-through mechanisms that enable adaptive structural functions attuned to various environmental configurations; (b) the integration of additive manufacturing and generative design to empower the efficient fabrication of components capable of high geometric and structural performance; and (c) system-level implementation of adaptive capabilities through design simulations of optimized building enclosure geometry with multi-stable connections and laboratory demonstrations. Results from this research will empower new engineering systems that can be modulated by altering stable states, thus requiring no energy to maintain the system in a given position. The research has broad societal impacts by paving a path to new structural system concepts in both existing and new structures to produce new geometric adaptation capabilities, and by focusing on the climate change mitigation and adaptation theme of reducing raw materials, maximizing utilization of materials, efficient manufacturability, and improving sustainability and resilience of buildings. The comprehensive education plan involves the integration of undergraduate students in research, development of curriculum, and creation of pre-kindergarten through high school educational materials and resources within the area of adaptive structures. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NIH Research Projects · FY 2026 · 2024-12

ABSTRACT While there are several FDA-approved medications for opioid use disorder, they are not effective at reducing opioid intake and preventing relapse in all individuals. Additional treatment options are needed. One compound that has been shown to reduce intake of multiple classes of drugs is the hormone oxytocin. Several clinical trials have found oxytocin to effectively decrease craving, withdrawal symptoms, and intake of several drugs, including heroin. However, there have been negative results in some clinical trials of oxytocin for substance use disorder (SUD), necessitating further evaluation of oxytocin’s strengths and limitations for the treatment of SUD. Oxycodone is a prescription opioid drug that has high rates of non-medical use, and contributes significantly to the number of overdoses in the U.S. SUD is a condition characterized by allocating increased resources (e.g., time, money) to drug acquisition and consumption. Studies done investigating the behavioral economics of drug- seeking in humans find that drug demand (amount of effort or resources people will allocate to obtaining drug) is predictive of future drug use and treatment success. Translational animal models provide insight into neural mechanisms of behavioral economic drug demand and allow for testing of novel treatments. Towards this goal, our preliminary data finds that in a behavioral economics model of demand for intravenous oxycodone, a mid- range dose of oxytocin (1 mg/kg IP) increases elasticity of demand and decreases the “price” (i.e. number of lever presses) at which demand for intravenous oxycodone becomes elastic in male, but not female rats. A large body of research finds no such sex differences in the ability of the same dose of oxytocin to attenuate intake and seeking of other addictive drugs such as cocaine and methamphetamine. Thus, additional research is necessary to characterize the effects of oxytocin on oxycodone seeking. Here we will generate a dose-response curve for the ability of oxytocin to increase the elasticity of demand for intravenous oxycodone in male and female rats. We observe robust spontaneous signs of withdrawal in male and female rats and greater withdrawal is associated with less elasticity of demand for oxycodone. Here we will also examine the ability of oxytocin to attenuate spontaneous withdrawal. We will also investigate the ability of oxytocin to reduce drug-seeking after a period of abstinence. Here will perform the first ever assessment of the ability of oxytocin to attenuate oxycodone seeking in male and female rats after drug abstinence, while assessing baseline blood oxytocin levels. Our hypothesis is that, as we observed for oxycodone demand, the dose-response curve for oxytocin to attenuate drug seeking after abstinence will be shifted to the right in female rats. We also hypothesize that blood oxytocin (in the absence of exogenous oxytocin administration) will be negatively correlated with oxycodone seeking. Upon determining the dose-response curve for oxytocin’s effects on oxycodone-demand and incubated seeking here, future work will interrogate neurobiological substrates and circuits involved in the ability of oxytocin to attenuate demand and incubated seeking of oxycodone in male and female subjects.

NIH Research Projects · FY 2026 · 2024-12

PROJECT SUMMARY/ABSTRACT: Remarkable progress has been made in gene therapy of hemophilia B as well as hemophilia A using recombinant adeno-associated virus (AAV) vectors. The United States Food and Drug Administration (USFDA) granted approval Hemgenix for gene therapy of hemophilia B in November 2022, and Roctavian for gene therapy of hemophilia A in June, 2023. Both Hemgenix and Roctavian are based on recombinant AAV5 serotype vectors. However, AAV5 vectors are less than optimal since they do not transduce human hepatocytes efficiently. Thus, extremely high vector doses are needed to achieve clinical efficacy, which necessitates the use of prophylactic immune-suppression. Of the 10 most commonly used AAV serotype vectors, we have identified AAV3 as the most efficient in transducing primary human hepatocytes. In addition to capsid-modified AAV3 vectors that are ~10-15-fold more efficient than their wild-type counterpart, we have also generated genome-modified AAV vectors in which we have engineered the AAV inverted terminal repeats (ITRs) with which up to ~22-fold improved transgene expression can be achieved. In the current application, we wish to combine both capsid- and genome-modifications to develop optimized AAV3 vectors to pursue the following three Specific Aims: Specific Aim 1: To evaluate the underlying molecular mechanism of enhanced transgene expression from ITR- engineered AAV vectors. Specific Aim 2: To evaluate the efficacy of ITR-engineered AAV3 vectors in primary human hepatocytes using humanized mice in vivo. Specific Aim 3: To evaluate the efficacy of ITR-engineered AAV8 vectors for phenotypic correction of murine hemophilia A and B, and evaluate the immunogenicity of these vectors. The capsid+genome-modified optimized AAV vectors are likely to be more efficacious at lower doses, thus being less immunogenic, thereby further increasing the safety as well as reducing vector production costs, ensuring translation to the clinic with higher probability of success for gene therapy of human liver diseases in general, and hemophilia B and hemophilia A in particular.

NIH Research Projects · FY 2026 · 2024-12

Project Summary/Abstract This K25 proposal is for a five-year mentored training program to launch Dr. Aprinda Indahlastari’s career as an independent aging investigator by leveraging her engineering background to develop personalized cognitive intervention in NIH-relevant research on cognitive aging and dementia. As such, the proposed training will transition Dr. Indahlastari into the field of aging and ADRD, by 1) acquiring knowledge in neurobiological effects of clinical aging and Alzheimer's disease and related dementias (ADRD) in the context of aging interventions, 2) gaining experience in clinical trial design focused on deploying aging interventions, 3) learning skills in advanced neuroimaging analytics with machine learning to probe and analyze intervention effects, and 4) becoming an independent investigator and forming a network of collaborators in clinical ADRD research. The training plan encompasses various components such as formal coursework, didactics, clinical cases shadowing, conferences, direct mentorship, and career development activities to facilitate candidate’s transition towards independence. The overarching research question addressed in this proposal is characterizing the effect of acute (one-time) application of transcranial direct current stimulation (tDCS) with standard fixed dosing on working memory performance and functional connectivity in individuals with mild cognitive impairment (MCI). Fixed dosing strategy refers to prescribing the same stimulation parameters to participants within a single study. To address this question, a human trial study will be conducted at the University of Florida to evaluate working memory gains with tDCS in MCI patients compared to healthy control. The study will employ state-of-the-art methods including person-specific computational models, machine learning, and multi-modal neuroimaging. The research proposal outlines two main aims to unravel the relationship between working memory gains and acute tDCS application in the MCI cohort. Aim 1.) Identify whether acute tDCS application leads to greater behavioral change in working memory and quantify important factors driving these changes in MCI patients compared to cognitively intact cohort. We hypothesize that acute tDCS may increase working memory performance during active tDCS and larger degree of brain atrophy and white matter hyperintensity observed in MCI patients will significantly decrease current intensity in stimulated brain regions. Aim 2.) Determine whether acute tDCS application strengthens functional connectivity within the working memory network. We hypothesize that acute tDCS may significantly increase functional connectivity within the working memory network during active stimulation, but not during sham stimulation, for both healthy and MCI cohorts. Machine learning enhanced models will be employed to identify important tDCS current characteristics that drive working memory gains and strengthen connectivity networks at individual level. The information gathered from this grant will provide a basis for future R01 submission to formulate custom intervention tailored to each individual. These personalized interventions are expected to be more effective than the standard fixed dosing strategy in improving overall cognitive abilities.

NIH Research Projects · FY 2026 · 2024-12

Abstract Cryptococcus neoformans (Cn) is an encapsulated fungus and the causative agent of cryptococcosis. HIV/AIDS patients are significantly susceptible to develop and die of cryptococcal meningoencephalitis (CME) despite of optimal antifungal treatment. The polysaccharide capsule of Cn is abundantly released during infection, causing formidable effects to the host immunity. Its main component, glucuronoxylomannan (GXM), has been implicated in fungal brain invasion and consequent neuropathology. However, there are important knowledge gaps regarding the involved fungal factor(s), regulatory mechanisms, and interaction between Cn and cells of the central nervous system (CNS) that are implicated in CME progression. Therefore, our long-term goal is to fully dissect cellular pathways involved in the neuropathology associated with Cn brain infection. Post-mortem pathological studies in human CME brain tissue samples have demonstrated that there is an intimate relationship between neurons and cryptococcomas. However, the role of GXM on neuronal and cognitive dysfunction observed in CME patients is not well understood. Our preliminary data show that Cn GXM binds to the surface of neurons and causes several cellular changes including morphological alterations, increases in intracellular calcium activity, and altered synaptic transmission. GXM release also leads to an increase in reactive astrocytes and hinders microglial migration, both findings that directly link immune response factors to Cn neuropathology. Hence, the goal of this application is to elucidate the mechanisms by which Cn GXM interfere with neuronal physiology in the basal ganglia, one of the main brain regions associated with cognitive and motor function and significantly colonized by Cn, especially in the setting of CD4 T cell deficiency. Our central hypothesis is that Cn GXM accumulation results in neuroimmune dysregulation and neurotoxicity, contributing to CME pathogenesis and cognitive impairment. To address our hypothesis, we propose the following aims: (1) To determine how Cn GXM affects basal ganglia function in CD4 T cell-deficient mice; (2) To test the hypothesis that exposure to Cn GXM leads to basal ganglia principal neurons death in CD4 T cell- deficient mice; and (3) To investigate how Cn exposure leads to altered synaptic transmission in the basal ganglia and lead to neurobehavioral deficits. Identifying novel mechanisms by which Cn alters neuronal function and behavior in immunocompromised individuals will provide new insights into this neuropathology. In addition, results from our proposal will potentially facilitate future development of new therapeutics and preventive measures for combating CNS cryptococcosis (a disease that kills ~20% of people with AIDS worldwide) and effective management of its potential neuro- sequelae in survivors.

NSF Awards · FY 2024 · 2024-12

Ecosystems and the services they provide are changing. This makes predictions for how systems will change crucial for decision making by land managers and policy makers. However, current capabilities for making ecological forecasts are limited. Making forecasts requires understanding how ecosystems will respond to changing conditions. Because ecosystems are governed by complex interactions among species and their environment, our knowledge from the past may provide limited information about the future as conditions change. Thus, it is critical to develop and assess our ability to make forecasts when novel conditions occur. For over 40 years, the Portal Project has been collecting data on mammals and plants as part of a long-term experiment in southeastern Arizona. Continuing data collection at this site provides a unique opportunity to (1) assess how the occurrence of novel conditions impact the ability to forecast the population sizes of mammals and (2) determine the best methods to forecast changes in ecological systems. This project will support the growing field of ecological forecasting by providing a high-quality, openly available data source for other researchers. The research team will also produce online educational materials to support classes to teach the next generation of ecological forecasters. This research project will use the unique strengths of the Portal Project to improve ecological forecasting under novel conditions. Comparing the performance of forecasting approaches under novel conditions requires long-term data and novel environments. Over the past two decades, the environment at the Portal Project has become warmer and drier. This creates novel environmental conditions for species. Additionally, experiments at the site create novel combinations of species. Ongoing data collection will be used to assess: (1) if models with more ecological complexity perform better, (2) if data from experiments can improve forecasts, and (3) if forecasting models can handle rapid environmental changes. This research will use an automated forecasting system that serves as a model for ecological forecasting. The project requires ongoing data collection to test forecasts and to provide information on ecological changes as species and the environment change. 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 · 2024-12

This project examines the professional development, mentoring, and career retention of early-career engineers, with a focus on how individuals build and use resources to navigate the early stages of their careers. Decisions made in the first years of practice can strongly influence long-term professional pathways and the stability of the engineering workforce. By investigating the experiences and mentoring relationships that shape these formative years, the project seeks to identify strategies that support engineers’ success, resilience, and sustained engagement in the field. Using qualitative methods and narrative inquiry, the research will trace the career stories of early-career engineers and document the strategies they use to navigate entry into the engineering profession. The project aligns with NSF’s mission to strengthen the U.S. STEM workforce by advancing understanding of factors that expand professional development and support productive, long-term participation in engineering across the nation. The study focuses on how early-career engineers develop and apply career navigation skills and how mentoring relationships contribute to their professional integration. The research will employ multiple interviews with participants, followed by systematic analysis and restorying of the data into narrative case profiles that highlight critical decision points, supports, and obstacles. The project will also include interviews with mentors identified by participants to illuminate mentoring practices that foster growth, learning, and retention. The goals are to identify how career navigation resources are cultivated and used; to understand how organizational environments shape early-career development; and to offer new insight into the skills, supports, and forms of capital that enable engineers to remain and advance in the profession. Expected outcomes include a detailed account of early- career professional formation in engineering that can inform mentoring programs, organizational policies, and workforce development initiatives aimed at improving retention and building a resilient STEM workforce capable of addressing complex national and global challenges. 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 · 2024-12

John F. Stanton of the University of Florida is supported by an award from the Chemical Theory, Models and Computational Methods program in the Division of Chemistry to develop and implement quantum-mechanical methods for doing calculations relevant to the fields of molecular spectroscopy and chemical kinetics. The Stanton group has a longstanding presence in an area that can be characterized as “Theoretical Chemical Physics”. In the research supported by this grant, they will continue to develop and refine methods relevant to the areas of molecular spectroscopy (how molecules and electromagnetic radiation interact) and chemical kinetics (how quickly chemical reactions occur). In addition to this, the development of the base quantum-chemical methods will be extended. In particular, the supported research will produce cutting-edge software program packages for doing very accurate calculations for “open-shell’’ molecules (those that contain one or more unpaired electrons). It is expected that the software will be the most efficient available to the community for studying this interesting class of molecules that are relevant to areas such as the environment, energy science, and astronomy. This work will extend a highly efficient coupled-cluster (CC) package (NCC, developed previously by the PI and D.A. Matthews of Texas Methodist University) to open-shell reference functions, for which methods for ground and excited states (CC and EOM-CC) will be implemented for general open-shell references up through the CCSDTQ level of theory. In addition, analytic gradients for all of these methods will become available within the funding period. Beyond this, a method that accounts for quantum tunneling effects in chemical kinetics – semiclassical transition theory – will be studied to assess how far below the barrier this method is able to provide accurate results. Remaining research on electronic spectroscopy will range from a diagrammatic fundamental analysis of the spectroscopic intensity of complicated vibronic interactions and study of the uniquely complex A-state of the nitrate radical. 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 · 2024-12

Project Summary This application requests funding for the 10th International Microsatellites and Human Disease (UMHD10) conference to be held in Guanacaste, Costa Rica from January 14th to 19th, 2025. The UMHD conference series has successful track record of scientific exchange and clinical collaborations that have encouraged breakthrough research. Since their discovery in the early 1990s, research into repeat expansion mutations have led to novel insights into fundamental biological processes, which has produced significant therapeutic progress. Microsatellite repeat expansions are associated for 70+ human diseases, ranging from common neurological disorders, like Alzheimer’s disease (AD), Amyotrophic Lateral Sclerosis (ALS), and autism spectrum disorder (ASD), to rarer disease, like Huntington’s Disease, Myotonic Dystrophy, and spinocerebellar ataxias (SCAs). UMHD10 finds the field sitting on a cusp of transformative change across multiple fronts, but also facing significant barriers. While repetitive sequences have been estimated to make up 75% of the human genome, research into the role of these sequences in biological processes is still ongoing. On the clinical front, the complexity and variability associated with many repeat expansion disorders has limited therapeutic progress. UMHD10 aims to attract the brightest minds in the field with a comprehensive program that provides an inclusive and open environment for the open exchange of ideas, the creation of interdisciplinary collaborative peer networks, and the development of career skills. The three main specific aims/objectives of the meeting are (1) to advance the field’s understanding of the role of microsatellites in human biology and to spur development of therapeutic technologies, analytics, and tools to tackle associated human diseases; (2) to provide an inclusive and open environment for the exchange of ideas, the creation of interdisciplinary collaborative peer networks, and the development of career skills; and (3) to increase participation in the microsatellite field at all stages (research, clinical & advocacy) by individuals typically underrepresented in biomedical research. The meeting’s goal is to advance understanding of microsatellites in human biology and to spur development of therapeutic technologies, analytics and tools to tackle the associated human diseases.

NSF Awards · FY 2024 · 2024-12

The nature of dark matter, which makes up nearly 27% of the mass-energy content of the Universe, is one of the most fundamental questions of modern science. The weakly interacting massive particle, or WIMP, is a favored dark matter candidate sought in searches at the Large Hadron Collider accelerator in Switzerland, indirect detection experiments, and direct detection experiments that look for WIMP interactions with nucleons in ultra-sensitive particle detectors. The SuperCDMS SNOLAB experiment is a direct detection dark matter search that looks for WIMPs of lower mass with world-leading sensitivity, complementing the on-going global efforts. This award supports the base operations of the SuperCDMS SNOLAB experiment as it commences the first science data-taking of the completed detector. The program includes development of accessible analysis resources that will enhance training opportunities for training of undergraduate and graduate students and postdoctoral researchers. In addition, computational skills will be incorporated into a diverse outreach effort through short course modules, research projects, and planned workshops. The goal of the SuperCDMS project is to directly detect galactic dark matter and thus address the particle nature of dark matter, its astrophysical properties, and how it relates to the Standard Model of particle physics. The construction of the SuperCDMS detector is reaching completion in preparation for installation and integration at the deep underground SNOLAB sited in Sudbury, Ontario, Canada. The team will operate advanced cryogenic detectors that have unprecedented sensitivity to dark matter particles with masses at and below the GeV/c-squared mass scale. The advanced cryogenic detectors will provide unprecedented sensitivity to lower mass dark matter particles, with ultimate potential sensitivity to the dark matter-nucleon cross-section where solar neutrino-nucleus scattering becomes significant. Extending beyond the search for dark matter, the experiment’s phonon-mediated detectors have applications in cosmology, astronomy and industry. 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 · 2024-12

The objective of this Grants for Rapid Response Research (RAPID) project is to collect ephemeral data on time use during hurricane preparedness, targeting areas affected by the consecutive hurricanes Helene and Milton in Florida. The back-to-back events underline compounded stress and time demand resulting from ongoing adjustments to daily routines. The primary hypothesis is that time poverty — a significant but often overlooked social vulnerability — limits flexibility and discretionary time necessary for effective disaster preparations. The project seeks to understand how individual characteristics — such as employment and family responsibilities - influence time management and stress levels. The ultimate goal is to enhance disaster management strategies to better meet the needs of diverse populations. The project empirically evaluates the uniform hurricane warning period's effectiveness, particularly for time-poor populations. It conducts a geographically targeted survey through mixed methods and employs a combined cluster and stratified sampling. A set of research questions are formulated and investigated, including, 1) how individuals allocate their time from the initial awareness of hurricane warning to landfall; and 2) how various factors like time poverty, employment role, family responsibilities (e.g. childcare or eldercare), and geographic risk exposure influence the time pressure experienced during hurricane preparations. The new data enrich the American Time Use Survey, which currently lacks specific details on time use during extreme events, and expand empirical knowledge on the impacts of time poverty on disaster preparations. By identifying effective time management strategies, the research informs future improvements to America's Alert & Warning Infrastructure, ensuring the systems and policies are attuned to the varying abilities of populations in response to threats. 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 · 2024-12

The big bend coast of Florida was recently impacted by subsequent storm events including Hurricane Idalia (Cat 3; Sept 2023), Hurricane Debbie (Cat 1: July 2024), Hurricane Helene (Cat 4; Sept 2024), and Hurricane Milton (Cat 3; Oct 2024). These represent a unique series of storms impacting the same region within a short period of time. Hurricane Helene also stood out because of rapid intensification and last moment changes in course that allowed limited time for warnings and evacuation, and storm preparation by residents. The goal of this Grant for Rapid Response Research (RAPID) project is to collect perishable data that will enable to quantify sediment erosion and deposition, debris transport and accumulation, and resulting damages to the built environment from storm surge and wave action during Hurricanes Helene and Milton through comparison of data collected pre-storm, during-storm, and in-between storms. The effort will yield a data set that will improve current predictions of tropical cyclone impacts on coastal communities and will likely serve as a benchmark data set for future research studies. Data will be shared widely through NSF Natural Hazard Engineering Research Infrastructure (NHERI) DesignSafe-CI and with local communities to increase awareness and understanding of risk assessments. The project will collect detailed field data, including measurements in the nearshore and in coastal environments in Cedar Key, Shired Island, and Horseshoe Beach, Florida. The findings may lead to improved understanding, prediction, and mitigation of erosion and scour and impacts thereof during severe tropical storm events from storm surge, inundation, and wave action. Specifically, this data set will be unique in providing information both before and during a Cat 4 storm with a 4m storm surge. These observations, combined with post-storm surveys and with additional measurement during Hurricane Milton and between Hurricanes Helene and Milton will enable researchers to understand the effectiveness (and potential unintended consequences) of different shoreline protection systems. 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 · 2024-11

Biological phenomena are often driven by complex dynamic regulatory networks. In natural or engineered systems, complicated structures can be generated from simpler building blocks, or modules. This notion of complex systems built from modules is also prevalent in modern systems biology. However, a clear theoretical foundation of modularity, including useful definitions of basic concepts and mechanisms, is still missing. This research project will fill this gap by defining modular structures in biological systems in a mathematically rigorous way. The research will determine why modularity can be advantageous to an organism and elucidate how modularity can be leveraged to advance our understanding of molecular systems. Studying the modularity of specific gene regulatory networks underlying salamander limb regeneration as well as hormone regulation in plants harbors the potential to reveal novel biological insights. Through involvement of students in all aspects of the research, this project contributes to the interdisciplinary training of STEM workforce. The dissemination of results through a dedicated project website and webinars enables anyone to analyze biological network models. The foundation of this project is a rigorous, structure-based definition of modularity in the context of Boolean networks, a common modeling framework in systems biology. Through computational, experimental, and theoretical studies, it will be shown that this definition of modularity (i) is biologically meaningful, (ii) implies a decomposition of the dynamics of Boolean networks, which can be employed to efficiently compute their dynamics, and (iii) that modular networks can be controlled effectively. The theoretical results, including theorems and implemented algorithms for practical computation, will advance the body of knowledge in the fields of network analysis, systems biology, and developmental biology. The validity of the project will be demonstrated through (1) in vivo analyses in the model plant Arabidopsis, (2) in silico analyses in an emerging animal model, axolotl. This will yield novel biological insights regarding (1) the interplay between phytohormones during Arabidopsis organogenesis, and (2) gene regulatory networks directing fibroblast reprogramming in axolotls. 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.