University Of Wisconsin-Madison

NIH Research Projects · FY 2025 · 2025-06

Project Summary The potential for animal viruses to spill over into humans represents a persistent, consequential threat to human global health. However, our ability to predict which viruses are most likely to “jump” into humans is currently limited. Computational approaches are a potential solution to this problem, and early results are promising. Nevertheless, most computational approaches are “static” with respect to virus evolution - they endeavor to predict zoonotic potential of viruses at a single point in time (the point at which viruses were identified or sequenced), but they do not account for evolution, which is a hallmark of virus biology. This project will fill this methodological gap by offering a new approach inspired by adversarial machine learning. Adversarial machine learning is a broad area of research that includes methods designed to identify small changes to a learned model’s input that significantly change its output. We will develop and apply adversarial machine learning to the following prediction task: given genomic protein sequences from a non- human animal virus, use a learned model to predict if the virus is likely to be infectious to humans, or how extensively it would have to mutate to become infectious Our proposed approach will notably advance the state of the art by (i) considering not just the human-infection risk for a “static” viral sequence but also the spillover risk attributable to evolutionary variants, (ii) applying and developing methods to characterize and explain the risk prediction for a given virus, and (iii) developing and evaluating predictive models based on state-of-the-art neural networks for protein sequences.

NIH Research Projects · FY 2026 · 2025-06

Project Summary Childhood asthma poses a significant public health burden due to its high prevalence, associated healthcare costs, and long-term impacts on children's health and development. The human microbiome has been associated with asthma phenotypes, endotypes, and disease severity, positioning it as a potential therapeutic target for asthma prevention and control, particularly since the microbiome is inherently modifiable. We recently assembled the largest and most geographically diverse datasets containing infant nasal and gut microbiomes, along with host genetics data, from multiple birth cohorts within the NIH-funded Children’s Allergy and Asthma Data Repository (CADRE). This study presents a unique opportunity for a more thorough investigation into the impact of the microbiome and its interactions with host genetics on asthma risk. Unfortunately, the statistical and computational tools for analyzing the CADRE study are currently lacking, primarily due to the complex compositional structure of microbiome data. This proposal seeks to address critical gaps in the methodological literature by focusing on three major areas. Specifically, we aim to develop a comprehensive suite of statistical methods to: (1) detect host genome-wide associations with the infant microbiome; (2) identify genotype-microbiome interaction effects on childhood asthma; and (3) uncover the causal role of the infant microbiome in childhood asthma. These aims are grounded in rigorous prior research, underscoring the significance of the scientific questions and the limitations or absence of existing methods. We will apply these methods to the CADRE study. These methods have the potential to advance our understanding of the microbiome's role in childhood asthma and facilitate the development of new strategies for asthma treatment and control.

NSF Awards · FY 2025 · 2025-06

This award supports participation at the Macaulay2 software development workshop that will be held from June 30 to July 4, 2025, at the University of Wisconsin-Madison. Macaulay2 is a leading computer algebra system for supporting research in commutative algebra and algebraic geometry. At the workshop, researchers will extend its functionality by working in small groups to develop high-quality software packages that will be made publicly available. The workshop gives new users the opportunity to learn from experienced programmers; it will feature tutorial sessions on Macaulay2, as well as basic training in version control and software development. The workshop will include professional development activities intended for early-career mathematicians. The choice of coding projects is motivated by recent research advances in mathematics. Each project will be led by a leading researcher, and the projects involve a wide variety of active research areas within commutative algebra, algebraic geometry, algebraic topology, representation theory, and algebraic combinatorics. Specific goals include computations related to Galois and monodromy groups, matrix Shubert varieties, Mackey functors, symmetric linear forms, Koszul duality, and positroid varieties. More information can be found on the workshop’s website: https://macaulay2.github.io/Workshop-2025-Madison/ 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

Nitrogen is an essential nutrient for all life on earth. It is also the most abundant element in the atmosphere, but most organisms cannot access it from the air directly. Only certain specialized microbes have the ability to convert nitrogen in the atmosphere into a biologically useful form in a process known as nitrogen fixation. Some of these microbes are free-living, but most live in a close symbiotic association within the roots of plants, exchanging nitrogen for carbon. This nitrogen-fixing symbiosis is a central component of the global nitrogen cycle, and it is central to agricultural systems because nitrogen is often the limiting factor for crop growth. It is therefore imperative to understand how nitrogen-fixing plant-bacterial partnerships form in nature and how they respond to an environment filled with challenges and in constant flux. The purpose of this project is to provide a data-intensive framework to learn how plants and bacteria choose their partners and how this choice influences and responds to surrounding species, soil, and climate. A second purpose of the project is to train students from groups underrepresented in science. Students will be prepared for the data-intensive careers now needed across STEM disciplines using an innovative mentorship program and interdisciplinary research including fieldwork, laboratory work, and computational biology. The project will investigate the diversity of nitrogen-fixing bacteria and other microbes associating with plant roots across the North American continent using NSF-sponsored ecological monitoring resources through NEON (the National Ecological Observatory Network). At each of 45 NEON sites, environmental data will be combined with data on the nitrogen-fixing symbiosis. Specifically, investigators will sample the microbiome in the soil and root nodules, and will assay leaf isotopes to determine the level of function of nitrogen-fixing symbionts. Leveraging data from these different sources, the PIs will be able to determine whether microorganisms and plant partners are each limited by the same environmental factors, such as aridity. They will also be able to determine the extent to which choosiness of plant or microbe partners limit the extent of the association. In addition, by examining patterns in the tree of life, the PIs will be able to infer whether highly specific partnerships have persisted across evolutionary time. Finally, models will be used to address synthetic questions across all data sources. For example, a model can test the prediction that arid environments favor highly specific associations, in which both microbes and plants choose specific partners in those stressful settings. This project is jointly funded by the BIO Emerging Frontiers Program and the Established Program to Stimulate Competitive Research (EPSCoR). This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NIH Research Projects · FY 2025 · 2025-06

ABSTRACT Voice disorders affect approximately one million American children and the associated impacts on quality of life are significant. These disorders often go underdiagnosed and undertreated in children due to subjective, imprecise evaluation methods, and the misconception that children do not experience a change in voice-related quality of life. The ability to perform at school, relate to friends and family, participate in social activities, or engage in everyday activities can be severely affected by voice impairment. A key part of providing voice care is a complete voice assessment, including aerodynamic evaluation of vocal input. The primary goals of this proposal are to develop noninvasive aerodynamic assessments which are reliable in the pediatric population, and to describe differences between healthy and dysphonic pediatric voices between the ages of 4-17 years. Three methods of aerodynamic measurement have been developed in our laboratory: complete airflow interruption; incomplete airflow interruption; and airflow redirection. These methods have been validated and shown to be accurate with adults. We have demonstrated improved measurement reliability for aerodynamic parameters using complete airflow interruption in children. Additional modifications must be made to optimize assessment and address anatomic and physiological differences between adults and children. We will adjust our current protocols with shorter trial times, auditory masking, visual feedback in the form of gamification, and cheek restraints. These modifications will allow for more reliable measurement of aerodynamic parameters in children. Aerodynamic evaluation will be performed in children with normal voice and children with voice disorders related to vocal fold nodules or polyp. Aerodynamic parameters will be correlated with pediatric voice-related quality of life score, lesion characteristics, clinician-based perceptual voice assessment, and acoustic voice assessment. This research will optimize a reliable method of aerodynamic voice assessment in children, determine how aerodynamic input differs in the setting of a voice disorder and how that correlates with other voice measures, and generate normative data ranges for aerodynamic parameters measured by mechanical interruption. Complete assessment of pediatric voice has been limited by patient-controlled methods of aerodynamic measurement, which are not well-suited to children. This research represents a shift in pediatric voice evaluation and provides a foundation for complete, objective, reliable voice assessment in children.

NIH Research Projects · FY 2025 · 2025-06

Project Summary More than half of all children with cerebral palsy (CP) have communication challenges. A subset has impairments that are so severe that they lack functional speech. Many also have intellectual disability. Children with CP and severe speech impairment often have severe gross and fine motor limitations that restrict limb use. Augmentative and alternative communication (AAC) systems, particularly voice output devices that can be accessed with eye gaze, can provide crucial access to language for many children. However, our ability to match language features of AAC systems with language ability profiles of individual children is severely hindered by a lack of tools to accurately assess latent receptive language abilities in children with severe speech and motor impairment. AAC technologies currently require sustained eye-gaze for a specified dwell-time to activate word choices, which can be extremely challenging for children in this population. Innovations in other areas of language development research have led to the widespread use of eye-gaze techniques to measure receptive language and learning in other difficult-to-test populations, including infants and autistic toddlers. However, these techniques have yet to be leveraged to assess receptive language and learning ability in children with CP and severe speech and motor impairment. Data illuminating children's receptive vocabularies and their ability to learn new words would provide critical information for identification of an appropriate place to start when matching language features of AAC systems to underlying language abilities. Our long-term goal is to develop tools to better characterize receptive language and learning potential in children with CP and severe speech and motor impairments that can be used to match latent child language skills with language features of AAC systems. The objective of the proposed research is to begin this process by developing and testing eye gaze paradigms for use with children who have CP and severe speech and motor impairment. The planned studies will allow us to determine whether these methods provide more detailed and sensitive information than the usual behavioral tests. Aims are: 1.) To characterize lexical processing in children with CP and severe speech impairment using eye-gaze measures; 2.) To investigate novel word learning in children with CP and severe speech impairment using eye-gaze measures; and 3.) To characterize the relationships between familiar word processing (Aim 1), novel word learning (Aim 2), and traditional behavioral assessments of child language and cognitive attainment. This work will advance the development of tools for measuring latent language and cognitive skills in children with CP and severe speech and motor impairment. The ability to capture underlying skills at earlier chronological or developmental ages represents a critical advance in the current state of clinical assessment. Results will lead to a more accurate understanding of language development in children with CP and severe speech impairment, to the development of more precise AAC interventions, and to theoretical insights about the relationship between language production and comprehension in children who cannot talk.

NIH Research Projects · FY 2025 · 2025-06

Project Summary Title: Profiling cell type-specific ubiquitome in UBE3A mutant mice Angelman Syndrome (AS) is a rare genetic and severe neurodevelopmental disorder with complex symptoms. It is caused by the failure to inherit a typical maternal allele of the UBE3A gene, which encodes a HECT-type ubiquitin protein ligase. This genetic mutation contributes to 85%–90% of AS cases. While UBE3A expression and function suggest that UBE3A may target different proteins in various cell types, at different ages, and in different brain regions, the detailed molecular mechanisms regulated by UBE3A ubiquitination in the brain remain elusive. No study has yet identified UBE3A substrates in a cell-type and age-specific manner, nor is it known whether UBE3A substrates are differentially ubiquitinated in different brain regions in mammalian animals due to the lack of available tools. Identifying cell-type and age-specific UBE3A substrates is critical for understanding the functions of UBE3A and the mechanisms underlying UBE3A deficiency in AS. This knowledge is essential for developing potential cures for AS. We hypothesize that UBE3A targets distinct proteins in a cell type-specific and developmental stage specific manner in the brain. The goal of this project is to systematically identify differentially ubiquitinated proteins, potentially UBE3A substrates, in UBE3A model mice in different cell types (excitatory and inhibitory neurons) at different developmental stages. Additionally, we aim to investigate the spatial ubiquitination of UBE3A substrates by visualizing their ubiquitination patterns. We have successfully engineered a Cre-dependent Ubiquitin Tagging (CUT) mouse line designed to selectively tag endogenously ubiquitinated proteins within specific cell types in the mouse tissue. This innovative mouse line facilitates spatial visualization of protein ubiquitination within specific cell types at the single-cell level and enables purification of ubiquitinated proteins in specific cell types for cell-type-specific ubiquitome profiling. By combining our specific-Cre::CUT tool with Proximity Ligation Assay (PLA) and confocal microscopy, we will visualize cell type-specific and age-specific ubiquitination of UBE3A substrates at the single-cell level in different brain regions. Focusing on the P7 and P56 cortical brain regions, we will generate triple transgenic mice (Nex1- cre::CUT::Ube3am-/p+ for excitatory neurons and Gad2-cre::CUT::Ube3am-/p+ for inhibitory neurons) to profile ubiquitomes using pulldown experiments and mass spectrometry. This will help identify differentially ubiquitinated proteins and potential UBE3A targets across different cell types and ages, allowing for a comprehensive analysis of UBE3A functions. This study will identify differentially ubiquitinated proteins in UBE3A mutant mice in both excitatory and inhibitory neurons at different ages. This will elucidate UBE3A's varying functions across cell types and ages, enhancing our understanding of its role in AS and advancing towards effective treatments. Our data will also serve as a valuable resource for AS research.

NIH Research Projects · FY 2025 · 2025-06

PROJECT SUMMARY With a steadily increasing number of aged individuals, the number of people suffering from Alzheimer's disease (AD) is also increasing worldwide. Unfortunately, there have been only three FDA approved therapeutics for AD and these have failed to make major clinical impacts. The risk of AD is significantly increased by the development of obesity and type 2 diabetes (T2D) and studies recently performed show that glucose metabolism is disrupted in the brains and neurons of patients with AD with defects in glucose uptake and mitochondrial dysfunction. Interventions known to improve metabolic health like calorie or protein restriction, can extend lifespan while delaying age-related disease and slowing or preventing AD in animal models. However, dietary interventions like these are hard to sustain in the long term. Bariatric surgery (BS) is the most impactful therapy for obesity and metabolic disease. Sleeve gastrectomy (SG), the most performed bariatric surgery, has a profoundly positive impact on obesity, metabolic disease, and end organ health and can extend life by as much as 10 years. In humans, SG and other BS are associated with improved cognition, increased grey and white matter, and reduced circulating amyloid precursor protein. In preclinical studies, we have shown that SG mice are protected from metabolic disease in older age and that female mice prone to AD (3xTG) are protected from age-related frailty, cognitive decline, and AD-specific pathology. Others have shown that alternative forms of BS can similarly improve cognition, reduced Aβ plaque formation, tau phosphorylation, and microglial activation. Thus, there is growing evidence that SG may be able to treat or prevent AD but there has been a lack of preclinical studies aimed at understanding this phenomenon. Thus, there exists a major knowledge gap in our mechanistic understanding of how SG influences AD and if there are sex or strain differences in the response of AD to SG. This proposal, which is responsive to PAR-23-179, we will address these major outstanding questions. We will rigorously test the ability of SG to prevent metabolic disease, age-related frailty, and AD across sexes in two AD-prone mouse strains – APP/PS1(APP overexpressing) and hTau (tau overexpressing) - which will be preconditioned with western diet to induce obesity and T2D. We will perform deep metabolic and cognitive phenotyping and correlate these findings with traditional markers of AD pathology. Lastly, we will use a novel 10X Genomics platform to perform spatial transcriptomics and single nucleus RNAseq in SG and Sham brain specimen to help elucidate the mechanisms by which surgery impacts the pathogenesis of AD. The work proposed holds promise to simultaneously add to our mechanistic understanding of how altering metabolism can alter brain health and reveal novel targets for the future treatment of this devastating disease.

NIH Research Projects · FY 2026 · 2025-06

ABSTRACT Cerebrovascular disease (CVD) is the second most common cause of dementia and the fifth leading cause of death in the US. At least half of clinically diagnosed Alzheimer’s disease (AD) dementia patients also have CVD upon autopsy. Despite this, clinical trial designs and treatments frequently overlook the multi-etiological nature of cognitive decline. For example, significant progress has been made in identifying and treating AD proteinopathy through anti-amyloid therapies; however, these do not treat or consider effects from comorbid CVD pathology. Past and ongoing clinical studies focused on single-etiology disease may thus suffer from insufficient diagnoses and risk estimates, and the effects of treatment may be obscured. This leaves a critical gap in dementia research for accurate diagnoses and effective treatments against vascular contributions to cognitive impairment and dementia (VCID) and AD with comorbid CVD. The knowledge gap is largely due to a lack of non-invasive vascular markers that can inform on specific CVD processes contributing to VCID and their progression. While Magnetic Resonance Imaging (MRI) serves as the gold standard non-invasive imaging modality for evaluation of CVD, commonly employed MRI-based markers in the field, such as white matter hyperintensities measured on T2-FLAIR, only evaluate non-specific sequelae of CVD (downstream tissue injury). Furthermore, structural and static markers fail to provide insight into the dynamic vascular and hemodynamic phenomena that, as observed in animal models, lead to brain tissue injury and cognitive decline. The proposed project aims to address this gap by utilizing a suite of neuroimaging tools developed by the applicant to understand CVD processes contributing to VCID and to assess vascular hypotheses in relation to the presence of any AD proteinopathy in an individual. The PI’s research program has generated novel preliminary data in AD pathology-positive individuals across the cognitive spectrum indicating presence of intracranial vascular stiffness and decreased neurovascular flow tone, which may contribute to brain tissue injury and cognitive decline. Leveraging a unique MRI dataset and newly developed methods, the project will reprocess existing raw data (k- space) to understand interactions between CVD processes, AD proteinopathy, brain tissue injury, and cognitive decline. Existing longitudinal data in more than 2,000 participants from ongoing studies, including the WI Alzheimer’s Disease Research Center (WADRC) and the WI Registry for Alzheimer’s Prevention (WRAP), will be reprocessed from the raw signal MRI data to provide a detailed spatial characterization of intracranial vascular stiffness and neurovascular flow tone dynamics in both the macro- and micro-circulation. Our goal is to determine the impact of vascular disease processes, including vascular stiffness and decreased flow tone, on brain tissue integrity and cognition in the presence and absence of AD pathology. Ultimately, the discoveries from this project will provide new insights into specific CVD pathways leading to VCID and will inform treatment strategies for AD- related cognitive decline, considering the potential confounding effects of underlying comorbid CVD.

NIH Research Projects · FY 2026 · 2025-06

PROJECT SUMMARY Lower urinary tract symptoms (LUTS) pose a significant healthcare and quality of life burden. Therapeutic strategies mainly target symptom improvement, primarily because underlying cause(s) are not well understood. The complex etiology of LUTS may include exposure to environmental chemicals such as polychlorinated biphenyls (PCBs), persistent organic pollutants that are ubiquitous in the environment and still unintentionally produced despite worldwide bans. Since PCBs consist of different structural variants in varying proportions in the environment and in people, we use a human-relevant PCB mixture known as MARBLES PCBs which mirrors the most abundant PCB congeners and their relative concentrations as measured from the blood serum of pregnant women in the Markers of Autism Risk in Babies-Learning Early Signs (MARBLES) cohort. PCBs can be endocrine disruptors, including directly binding to estrogen receptors and inducing estrogen receptor mediated gene transcription, but if and how PCBs influence bladder function is understudied. We previously demonstrated that MARBLES PCBs exposure in mice causes augmented urinary voiding physiology and bladder contractility. Study of PCBs’ mechanism(s) of action to perturb urinary voiding function is still ongoing, but preliminary data suggests that increased big potassium (BK) channel expression in the detrusor smooth muscle cells contributes to the observed voiding changes. Therefore, since literature supports the individual actions that PCBs can bind to and activate ERβ, ERβ agonism can increase BK channel expression, and increased BK channel expression in urinary bladder smooth muscle can impact urinary voiding physiology, I hypothesize that in utero and lactational exposure to human-relevant PCBs directly act upon ERβ which alters urinary voiding function via increased big potassium (BK) channel expression in mice at 6 weeks of age. We will address the hypothesis by characterizing MARBLES PCB’s ability to induced gene transcription of estrogen receptor beta in vitro. Then, in vivo utilizing control genotype and ERβ knockout mice, we will developmentally expose mice to vehicle control or the MARBLES PCB mixture. We will test developmental MARBLES PCB exposure’s effects on BK channel expression, bladder contractility, and urinary voiding physiology, and also elucidate ERβ’s role in affecting PCB adverse outcomes. Our studies will have far-reaching effects on elucidating the molecular mechanism of how human-relevant PCBs impact bladder function and disrupt steroid hormone action. It is of great importance for human health to understand the etiology of these complex pathologies and identify targets for pharmacological interventions. And more broadly, this proposal highlights how the intersection on toxicology, urology, and endocrinology can result in basic research that has wide outcomes for human health benefits.

NSF Awards · FY 2025 · 2025-06

Managing modern power grids involves solving computationally challenging tasks at short intervals. Linearly approximating the governing complex physical laws is standard practice to lighten the computational burden, albeit with some inaccuracies. Traditionally, linearization design is agnostic of the end use. However, increased variations in operating conditions highlight the limitations of this one-size-fits-all approach. This NSF project aims to bridge the modeling and application gap by developing novel use-inspired approaches that yield linear models tailored for specific tasks and anticipated operating conditions. Reaching beyond power systems, the project will transform how scientists and engineers linearize complex physical laws to enable real-world applications. The intellectual merits of the project include the development of application-suited linearizations that enable robust decision-making and accurate simulation studies at scale. The broader impacts of the project include the development of tractable grid operation tools to increase the deployment of distributed energy resources. The fundamental aspects of this project will be used to increase the research participation of undergraduate students. Existing power-flow (PF) linearizations are typically developed and assessed based on their accuracy compared to the AC PF equations. However, when using PF linearizations for downstream applications, focusing on the application output accuracy is crucial. Closing the PF linearization loop around the end-use, this project will span three intertwined thrusts, developing certifiably optimal PF linearizations tailor-made for i) deterministic optimization, ii) stochastic optimization, and iii) dynamic modeling. The targeted canonical problems represent high-impact applications such as bulk system dispatch, distributed energy resource management, voltage control, uncertainty management, power system planning, and time-domain simulations. To tackle such diverse challenges, this project will source ideas from bilevel (stochastic) optimization, systems theory, sensitivity analysis, automatic differentiation, system identification, and neural networks. This project will develop comprehensive, rigorous, and tractable approaches allowing explicit inclusion of input data distributions and end-use application structure into the PF linearization process. Due to the generalizable structure of the proposed research, the project findings are envisaged to contribute towards use-inspired modeling in broader science and engineering disciplines. 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 aims to serve the national interest by improving postsecondary STEM teaching, learning, and institutional environments to support the persistence and success of students beginning their STEM education and careers at community colleges. These institutions play an important role in broadening the nation's STEM talent by offering a range of educational options for diverse student populations, including transfer into a four-year STEM major and pathways to STEM careers such as certificates, diplomas, associate degrees, and industry training credentials, all of which contribute to the STEM and STEM-related workforce. However, there is limited understanding of the full range of factors and contexts that influence various community college STEM pathways from a longitudinal standpoint. To advance knowledge that highlights the collective significance of teaching, learning, and institutional environments, this Improving Undergraduate STEM Education (IUSE) Engaged Student Learning (ESL) Level 3 project plans to adopt an expansive time window to capture students' STEM pathways and outcomes through the community college. Using 12 years' worth of survey and interview data, the project team hopes to unpack a comprehensive set of experiences and outcomes in undergraduate STEM education, as well as the factors that influence them. The findings from this project will be used to further refine and develop a new Community College STEM Educational Pathways and Success model. Overall, this project holds the potential to produce new research-based knowledge and tools to transform teaching, learning, and STEM education through community colleges. To advance theoretical and empirical understanding of the myriad STEM pathways through community colleges, the project intends to explore how beginning community college students experience undergraduate STEM teaching, learning environments, and various contextual factors to illuminate the components and conditions that result in improved STEM teaching and learning spanning community colleges and four-year institutions that serve STEM transfer students. Using a longitudinal mixed methods design and a robust panel cohort of about 1,660 community college students beginning in STEM in Fall 2014, the project plans to continue following this cohort for four additional years to examine how this cohort's undergraduate STEM education impacted their long-term STEM outcomes in the academic, professional, and workforce domains. Data collection begins with one final wave of a 12-year panel survey, followed by two waves of qualitative interviews to dig deeper into these students' perspectives and experiences throughout their undergraduate STEM education journey. To ensure actionable and translatable knowledge to inform research and innovations nationally, the project will disseminate a new theoretical model, survey instrument, and interview protocols that researchers and practitioners can adopt or adapt in their study and practice of similar issues. The NSF IUSE: EDU Program supports research and development projects to improve the effectiveness of STEM education for all students. Through the Engaged Student Learning track, the program supports the creation, exploration, and implementation of promising practices and tools. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NSF Awards · FY 2025 · 2025-06

Artificial intelligence is rapidly expanding across all fields of science, including physics. The 2024 Nobel Prize in Physics was awarded for groundbreaking advancements in artificial intelligence that have led to significant discoveries in various physics applications, including the IceCube's observation of astrophysical neutrinos from the Galactic Plane. Here, we propose to use generative AI to transform the simulation of high-energy particle interactions, enabling faster and more efficient modeling. Traditional simulation methods require immense computational resources, with a single particle collision at high energies involving billions of calculations. By applying AI-driven techniques, we aim to dramatically accelerate these processes, reducing computational costs while preserving accuracy. The expected outcomes include advances in fundamental physics, fostering discoveries in astrophysics, and new applications in medical physics, such as radiation therapy. Beyond research, we will integrate the outcomes of this project into the successful augmented reality (AR) app ICEcuBEAR, using AI-generated particle showers to create interactive holograms. This will enhance physics education by bringing AR experiences into K-12 classrooms and after-school programs, introducing students to the fundamentals of particle physics in an engaging and accessible way. This interdisciplinary research will be carried out through a close collaboration between computer scientists and physicists, combining expertise in artificial intelligence, Monte Carlo simulations, and high-energy particle interactions. To achieve these advancements, we will develop graph-based generative AI models that efficiently simulate particle showers—cascades of secondary particles following high-energy collisions. Particle showers exhibit an inherent tree-like structure, where each parent particle branches into multiple secondary particles, forming a hierarchical pattern. Our approach will use generative models that preserve this structure, capturing complex correlations in particle interactions. Recent breakthroughs in large language models (LLMs) and diffusion-based AI provide a foundation for this work, as these methods are well-suited for learning structured dependencies in sequential data. By incorporating physics-informed constraints, we aim to improve simulation accuracy while dramatically reducing computational costs. This approach will enable faster and more precise event reconstruction—critical for time-domain multi-messenger follow-up and more effective background and signal modeling. Achieving a breakthrough in our simulations will allow these advances to be fully applied to neutrino source analyses, significantly increasing the overall sensitivity and discovery potential of neutrino observatories such as IceCube. Moreover, our refined simulation framework is expected to facilitate rare event searches by overcoming limitations due to insufficient background statistics or the prohibitive computational expense of accurate signal modeling, thereby enhancing discovery potential in both particle astrophysics and high-energy collider experiments. Expected outcomes also include open-source algorithms and software, as well as the application of this framework to high-energy neutrino analyses, such as those targeting neutrino discoveries at the Galactic Center with IceCube data. 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

NONTECHNICAL SUMMARY This award supports theoretical research on charge and heat transport in quantum electronic systems, focusing on novel two-dimensional materials, nanostructures, and superconducting devices. The research addresses both fundamental and applied physics, with potential to bring innovations for quantum technologies. The analytical methods developed in this work will be applicable to a wide range of problems in the quantum physics of low-dimensional systems. Modern technology relies on electronic devices that perform a variety of functions, such as transistors, diodes, and other key components. The central theme of this project is to investigate nonreciprocal transport phenomena. Nonreciprocity in quantum materials refers to the phenomenon where a system’s response to an external stimulus (such as electric current, magnetic field, or light) depends on the direction of the applied stimulus. In other words, the system’s transport or optical properties are asymmetric when the direction of the current or field is reversed, violating conventional reciprocity relations. One of the main goals of this project is to study the superconducting diode effect in materials and junctions, which could lead to new functionalities, since superconductors can support dissipationless currents. Another focus of the research is exploring nonreciprocal thermoelectric effects, where heat can be converted into electricity and vice versa. The research program is closely integrated with education and outreach efforts. These initiatives include training undergraduate and graduate students and mentoring postdoctoral scholars in advanced topics in quantum physics. To inspire the next generation of physicists, the project will also engage students through science Olympiads and summer schools, providing valuable experience and exposure to modern developments in the field. TECHNICAL SUMMARY This project focuses on theoretical research in electron quantum transport and nonreciprocity in correlated systems and devices. The research agenda addresses both the fundamental physics of electronic correlations in complex materials and the practical physics of mesoscopic devices, particularly in the context of quantum science and superconducting nanostructures. The proposed scientific program is partly motivated by recent and ongoing experiments and will be conducted in close collaboration with several research groups. These collaborations are a key pillar of the project’s success. The work is structured around three main thrusts, each comprising interconnected sub-projects: [1] Transport Phenomena in Correlated Electron Systems. This thrust aims to develop a new kinetic theory that accurately accounts for correlations between electron scattering and long-range disorder potentials. These potentials may manifest as scalar or pseudo-vector fields, particularly relevant to multi-valley conductors with spatially varying strain. Applications include transport in topological moiré systems and nonlinear phenomena such as magnetochiral anisotropy and second harmonic generation. [2] Noncentrosymmetric Superconducting Systems. This line of research investigates the microscopic mechanisms underlying the superconducting diode effect, explores spin-galvanic effects, and studies interferometry in multiterminal Josephson junctions. It also aims to uncover transport anomalies at the interface between quantum Hall systems and superconductors. [3] Correlated Electronic Multilayers. This thrust explores electronic crystal phases in two-dimensional materials and investigates anomalous and nonreciprocal Coulomb drag phenomena in 1D and 2D devices, as well as the behavior of odd electron liquids. The project strongly emphasizes training graduate and undergraduate students by integrating them into research within a highly collaborative environment alongside postdoctoral scholars and colleagues from other groups. Additionally, the outreach and engagement component of the program targets a broad audience, including the general public, middle and high school students, and professional physics majors. Key components of this program include: Science Olympiad (preparing and mentoring students for science competitions); Podium Speaker Series (hosting talks to inspire and engage students in STEM fields); Quantum Summer Schools (organizing local summer schools to support students from Midwestern states and coordinating the advanced Boulder Summer School); Scientific Coordination of Events (organizing conferences and workshops to foster scientific collaboration). 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 award provides support for participants of the workshop Canonical Metrics in Differential Geometry, hosted at the University of Wisconsin-Madison in April 2025. Differential geometry is a branch of mathematics that studies the local and global shapes of spaces using various approaches such as analytic methods, metric methods, algebraic methods, and more. The workshop will primarily focus on several active topics in this subject. This event seeks to establish several major scientific goals. First, it will bring leading specialists from different subject areas together and the participants will discuss recent groundbreaking results in the field. Second, the workshop will provide an opportunity for graduate students and junior researchers in neighboring institutions to explore forefront outstanding questions and new technical tools. Third, the proposed expository lecture will help undergraduate students of the hosting institution, local high school students and general audience to understand current status and global pictures of several cutting-edge research fields, sparking interests in overall STEM fields. The workshop will feature long and short research talks at various levels, as well as an expository lecture. The proposed workshop will be incubating new research activities and educating interested personnel of all backgrounds in the Midwest area. The specific emphasis of the workshop will be on the canonical metrics of smooth and non-smooth spaces, which arise in various contexts of geometry. In addition to numerous substantial breakthroughs, the active and intensive study of canonical metrics has been stimulating entirely novel techniques, which have, in turn, opened up new directions for research. The main research topics of the workshop include Einstein metrics, the Ricci flow and Ricci solitons, canonical metrics in complex geometry and conformal geometry. The workshop will also provide an environment and support for interdisciplinary communication in differential geometry. Investigations from different perspectives may inspire significant developments in the subjects and generate interesting open problems. An overall goal of the workshop is to create a welcoming environment for sharing new ideas and tools, highlighting important progress in various fields, building an active network, and inspiring new collaborations. https://geometryworkshop.wiscweb.wisc.edu/ 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

Project Summary Neural stem cells (NSCs) in the brain proliferate and generate newborn neurons throughout life. Dysfunctions in neurogenesis have been associated with neurological diseases such as epilepsy, depression, and Alzheimer’s Disease. A significant rate-limiting step in adult neurogenesis is NSC quiescence exit, when a non-dividing quiescent NSC (qNSC) enters the cell cycle prior to population expansion and differentiation. Further, during aging and disease, extrinsic and intrinsic factors drive NSCs deeper into quiescence, reducing neurogenesis, and contributing to cognitive decline. Therefore, identifying factors controlling NSC quiescence and quiescence exit are critical to improving neurogenesis and enhancing cognitive function. Currently our understanding of NSC quiescence is incomplete due to technical limitations imposed by the bias of markers used to isolate each population of NSCs and the lack of live cell labeling strategies. However, recently we observed distinct optical signatures separating activated NSCs (aNSCs) from qNSCs using fluorescence-lifetime imaging (FLIM) and the relative abundance of two signals: 1) the metabolite NAD(P)H, and 2) autofluorescence within lysosomes (PAF), a technique we refer to as optical cell state imaging (OCSI). OCSI is a non-invasive tool capable of tracking NSC cell state in living cells over time, without exogenous label. OCSI collects 2 types of data from each cell: the relative abundance of NAD(P)H and PAF through fluorescence intensity, and a decay rate of fluorescent photons from NAD(P)H and PAF using FLIM. This decay rate can change based on fluorophore binding to protein partners or chemical state, which is dependent on the metabolic pathways used by a given cell. Importantly, many studies have shown that qNSCs and aNSCs preferentially rely on different types of cellular metabolism for generating energy. Using dimension reduction analyses of the 8 measures collected with OCSI in young mouse NSCs, we have not only identified distinct signatures separating qNSCs and aNSCs and tracked the dynamic changes of these measures through live cell imaging during quiescence exit, but also prospectively sorted NSCs based on this autofluorescent signal to successfully predict their proliferative behavior and identity from in vitro cultures and acutely isolated NSCs. These results reveal OCSI as a novel tool that uses the energetics of a cell to define its cell state, allowing us to unbiasedly address unanswered questions about NSC quiescence and activation to advance our understanding of these processes. We here propose to 1) identify the molecular signal associated with PAF, one of the primary contributors to OCSI’s predictive ability, 2) determine which quiescent populations current methods of NSC identification target, and 3) develop a FLIM-based cell sorter and single cell deposition system to increase the throughput for future studies while maintaining the high-resolution separation of quiescent to activated cell states. Completion of these Aims will provide a novel tool and establish OCSI as a method to answer critical questions regarding the mechanisms and regulators underlying NSC quiescence that can be targeted to drive NSC proliferation.

NSF Awards · FY 2025 · 2025-06

This award provides support for U.S.-based participants of a research conference on dynamics and rigidity, which will take place at the conference center of the Hotel San Michele in Cetraro, Italy. By bringing together experts from various subareas of dynamics, as well as researchers who have applied related methods in groundbreaking ways, the conference aims to foster collaborations across mathematical communities with the ultimate goal of making progress on longstanding problems. An emphasis will be placed on supporting young researchers, with all NSF funds dedicated to providing travel and lodging support for graduate students and postdoctoral scholars. The conference will include professional development panels addressing academic publishing, grant writing, and work-life balance. In addition, organizers will proactively recruiting attendees from a comprehensive range of experts in various stages of their career. Dissemination of knowledge will be ensured through the public availability of resources prepared by the speakers, allowing the broader mathematical community to benefit from the conference's outcomes. The last several years have seen an unprecedented number of breakthroughs in geometry and dynamics, including the resolution of the Zimmer conjecture, the classification of higher rank orbit closures in strata of Abelian differentials, and the classification of hyperbolic manifolds admitting infinitely many totally geodesic hypersurfaces. Many of these results were direct consequences of new discoveries of rigidity phenomenon in dynamical systems, including the classification of stationary measures following work of Benoist-Quint and applications of Margulis functions as in work of Eskin-Mirzakhani-Mohammadi. The goal of this conference is to bring together experts in rigidity phenomenon and dynamics from several communities, including smooth, homogeneous, and Teichmuller dynamics, together with mathematicians who have successfully applied such results to solve longstanding questions with an eye toward jump-starting collaborations between groups of experts with similar interests and bringing about new and exciting developments. The conference website is https://sites.google.com/view/eskin2025. 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

Specific subpopulations of U.S. women, including those with lower education, lower income, rural residence, and the underinsured experience higher breast cancer disease burden and lower survival rates than women without these characteristics, despite recent improvements in screening access and treatments. The majority of efforts to mitigate poor outcomes have focused on screening mammography access, but women must navigate multiple additional steps when cancer is suspected, including more imaging, biopsies, and specialist consultations. Each year, >12 million U.S. women enter this diagnostic care continuum. Failure to receive timely, quality evaluation leads to delayed diagnosis, more invasive procedures, advanced cancer stage at diagnosis, and greater mortality. Compared to screening, surprisingly little is known about drivers of patient outcomes during this diagnostic period. It is estimated that up to 30% of women with abnormalities detected by mammography fail to obtain appropriate or timely follow-up. A clearer understanding of the variable care and outcomes during the diagnostic continuum is hindered by the decentralized nature of breast cancer screening and diagnosis in the U.S., with differences in care likely due to a complex combination of individual, residential, and healthcare delivery factors. We propose to conduct the largest U.S. observational study of diagnostic breast imaging to date. Specifically, we aim to 1) identify specific subpopulations of women with lower access to and use of key diagnostic imaging technologies; 2) determine differences in diagnostic outcomes that can serve as quality of care indicators across different subpopulations; and 3) identify differences in timeliness of diagnostic evaluation across different subpopulations. We will use multi-level statistical modeling and mediation analyses to account for multifactorial interactions that likely influence diagnostic care. Our team, the Breast Cancer Surveillance Consortium, consists of national experts in breast cancer epidemiology, biostatistics, health services research, medicine, and radiology. The BCSC represents the largest longitudinal breast cancer imaging data resource linked to long-term outcomes that is representative of the general U.S. population. We systematically collect woman-, exam-, residential-, practice-, provider- and tumor-level data across seven regional registries and more than 200 individual practices. With data collected for 13 million breast imaging exams, our team is well-positioned to carry out the proposed analyses. Our study will help shift the breast cancer screening research paradigm from focusing on screening access to evaluating the entire episode of care. By identifying novel quality of care metrics and “early warning” indicators of worse outcomes, our results will inform both practice-level interventions aimed at closing local quality gaps and national practice guidelines and policies directed towards more effective breast cancer diagnostic evaluation.

NIH Research Projects · FY 2026 · 2025-06

ABSTRACT Bilingualism is common in many parts of the world and in the United States at least one-third of the population under age five speaks a language other than English at home. While there is motivation for the use of both languages in treatment for bilingual children with Developmental Language Disorder (DLD), it remains unclear how to optimize the integration of two languages for learning. Code-switching, or the use of multiple languages in discourse, is an especially controversial topic within bilingual language development, and the effect of code- switching on language learning is not well understood. We aim to test the effect of code-switching on bilingual children’s ability to learn novel words. Our target population is four- to six-year-old Spanish-English bilingual children across the full range of language ability (from typical to weak skills in both languages, i.e., DLD). We will test learning via an implicit learning task, contrasting learning between single-language and code- switched conditions. Specific Aim 1 is to examine the effect of code-switching on implicit novel word learning in bilingual children with and without DLD across two time points (immediate and delayed). In two studies under this aim, we will test the effect of code-switching on novel word learning, manipulating the placement of the language switch across studies (prior to the novel word in Study 1; after the novel word in Study 2). Both studies will test children immediately after learning and after a 10-minute delay. Specific Aim 2 is to examine the effect of language ability on word learning in bilingual children with and without DLD. Across both studies, children’s language skills will be assessed via an omnibus measure of language ability measuring language skills across English and Spanish. Children with DLD are characterized by processing and learning difficulties; therefore, children with lower levels of language ability might be especially sensitive to an effect of code-switching. At the same time, children with DLD demonstrate more difficulty with initial encoding than with long-term retention of information; therefore, children with lower levels of language ability may show different patterns of sensitivity to code-switching at immediate vs. delayed testing. Specific Aim 3 is to examine the effect of code-switching exposure on word learning in bilingual children. Across both studies, direct measurements of code-switching exposure collected via naturalistic parent-child interactions will be used to test the association between code- switching exposure and word learning in code-switched vs. single-language contexts. The proposed project will contribute to the theoretical understanding of the word learning mechanisms in single- and dual-language contexts, as well as to the broader lines of inquiry into the mechanisms that support code-switching in bilinguals. These studies are the first to empirically test the effect of code-switched input on implicit word learning across time points in bilingual children with DLD. Practically, the results may provide foundational information for clinicians delivering services to bilingual children with DLD and to parents who raise them.

NIH Research Projects · FY 2025 · 2025-06

PROJECT SUMMARY/ABSTRACT Antimicrobial resistance (AMR) is an accelerating pandemic contributing to a huge healthcare burden and hundreds of thousands of deaths annually. A major player in this phenomenon is expression of multidrug efflux pumps. These membrane transporters have the remarkable ability to export structurally and chemically diverse antibiotics while remaining selective for toxins. Despite high clinical relevance, our understanding of polyspecific drug efflux is limited. This is due to the complexity of overall promiscuous transport, which relies on a combination of flexible ligand binding and proton-gated conformational change to move the substrate across the membrane. While many mutational studies evaluating specificity thus far have focused on the binding site, I hypothesize that polyspecificity arises as a combination of these distributed transporter functions, and as such the determinants of substrate range are diffuse. Here, I combine deep mutational scanning with in vivo and in vitro validations to address two Aims. In Aim 1, I measure the function of all 7,760 possible single mutants of NorA in the contexts of ten antibiotic substrates and ten antibiotics not normally transported by NorA, validating select variants with clonal IC50 assays. This will expose the basis of multidrug specificity, both within the binding site and distally. Preliminary data shows that residues driving specificity may be found far from the binding site, including several residues thought to be involved in proton coupling. In Aim 2, I will develop a high-throughput method to measure NorA’s energy efficiency by testing various approaches to stress the proton motive force, which NorA relies on for energy. I hypothesize variants that are highly sensitivity to basic pH, nigericin, or valinomycin will exhibit reduced coupling efficiency. pH-sensitivity screens highlight expected variants in early results. I will validate this using an accepted coupling efficiency assay in which variants are reconstituted into liposomes containing the pH-sensitive fluorophore pyranine, which is currently working in my hands with control mutants. Completion of these Aims will mark the most exhaustive study of a drug efflux pump yet, yielding a wealth of information on how AMR arises and how we may lessen this substantial public health burden. The training planned during this fellowship will develop my skills in design and execution of high-throughput screens, computational analysis of large multidimensional datasets, bacterial cell biology, and advanced biophysical techniques. Training will take place at the University of Wisconsin–Madison under the supervision of Dr. Srivatsan Raman, an expert in high-throughput biology, with additional training and mentorship from co- sponsor Dr. Katherine Henzler-Wildman, a renowned transport biologist also in the UW–Madison Biochemistry department. My graduate program, Cellular and Molecular Biology, will provide training in responsible conduct of research and professional development activities to prepare me for an impactful career in academia.

NIH Research Projects · FY 2026 · 2025-06

PROJECT SUMMARY/ABSTRACT Recurrent respiratory papillomatosis (RRP) is a highly morbid laryngeal disease caused by low-risk human papillomavirus (HPV) types 6 and 11. RRP is characterized by quickly growing epithelial lesions that impair voice function. Hoarseness is the most common symptom, resulting in significant communication impairment in patients with RRP. Available HPV vaccines are preventive only, have low uptakes in the US and globally, and are given well after RRP arises in children. RRP management involves repeated laryngeal surgery, which can scar vocal folds and permanently worsen the voice. Risk factors for RRP onset are poorly understood. Most HPV infections are transient: cleared by the immune system without establishing chronic infection or clinical disease. The goal of this proposal is to better understand how PV establishes vocal fold infections that lead to RRP in immunocompetent individuals. One potential avenue is injury. Vocal folds are subject to injury from multiple mechanical and environmental exposures. PV is thought to enter tissue via a microwound. However, in the novel in vivo laryngeal mouse papillomavirus (MmuPV1) infection model, laryngeal injury is not required for chronic laryngeal PV infection and disease in the absence of an immune system. This means that uninjured vocal fold epithelium permits PV entry. In contrast, in immunocompetent mice, MmuPV1 can only cause vocal fold disease when epithelium is injured, which indicates that there must be other factors in PV-induced vocal fold disease establishment besides initial viral entry into epithelium. This proposal will test the overarching hypothesis that vocal fold injury not only physically facilitates PV entry into epithelium, it also disrupts epithelial homeostasis and immunity and facilitates increased PV gene expression, such that PV overpowers the ability of the immune system to control the infection. Aim 1 will use the MmuPV1 laryngeal infection model to define the extent to which injury enhances PV-induced vocal fold disease in immunocompetent individuals, including the effect of injury on vocal fold disease in a low-risk HPV milieu that better recapitulates RRP. Aim 2 will use novel in vivo and in vitro platforms to define the mechanisms by which injury enhances PV-induced vocal fold disease throughout each phase of the viral life cycle. By better defining how low-risk HPV exploits vocal fold injury to establish infections that lead to RRP in immunocompetent individuals, completion of the specific aims will have a significant and sustained impact on laryngology and PV biology. The career development plan includes advanced virology and molecular biology techniques. Together with clinical training and an extensive background in laryngeal biology, these new skills will place the candidate in a strong position to work independently toward her long-term goal to become a clinician-scientist faculty member in academia with a translational research program that uses well-validated preclinical models to improve mechanistic understanding of RRP. The University of Wisconsin-Madison is an ideal environment for the K99 phase evidenced by long-established and active communities and mentors in virology and laryngeal biology.

NIH Research Projects · FY 2026 · 2025-06

PROJECT SUMMARY Spinal Muscular Atrophy (SMA) is a rare neurodegenerative disorder characterized by progressive muscle weakness and atrophy due to degeneration of lower motor neurons. Historically, SMA was the leading genetic cause of infant mortality, with the majority of those who survived past infancy relying on mechanical ventilation and alternative nutritional support to live beyond age 2 years. Since 2016, however, FDA approved disease-modifying therapies have altered the disease’s trajectory, enabling the acquisition of motor milestones, reducing the need for ventilatory support, and allowing full oral nutrition. Despite these advances, the impact of disease modifying therapies on speech, language, and cognition has yet to be empirically quantified. This proposed project seeks to address this gap by examining speech, language, and cognitive development in children with SMA who have received these therapies. The aims of this study are as follows: Aim 1: To characterize speech motor abilities in children with SMA following disease-modifying therapy. We will collect behavioral speech data from 20 participants with SMA who have received disease-modifying therapy, aged 2 to 21 years, from a regional SMA clinic. From these data we will: (A) quantify performance of individuals with SMA after disease-modifying therapies compared to typically-developing expectations on the following variables: speech intelligibility, articulation rate, standardized articulation scores, maximum mouth opening, profile of speech subsystem involvement, and parent reported intelligibility in context; and (B) identify differences across these same variables among individuals, based on whether treatment was initiated pre- or post-symptomatically, and the age of treatment initiation. Aim 2: To characterize language and cognitive development in children with SMA following disease-modifying therapy. Using the children with SMA from Aim 1, we will: (A) quantify performance compared to typically-developing expectations on the following variables: receptive language, expressive language, and cognitive ability, as measured by standardized test scores and language sample analyses, and (B) identify differences across these same variables among individuals based on age at treatment initiation and symptom onset. This research is a critical first step for developing a comprehensive understanding of communication development, informing targeted speech interventions, and maximizing communicative participation for a new generation of children with SMA. The proposed project is a foundational first step to my long-term goal to advance the development of evidence-based speech and communication treatment for SMA to maximize participation and quality of life. This project, bolstered by extraordinary support from the University of Wisconsin-Madison, will provide extensive training in SMA, bulbar function, research design and analysis, ethical research practices, scientific writing, and professional development. This comprehensive training will position me to make meaningful contributions to the field of communication sciences and disorders and to serve the SMA community as an academic researcher.

NSF Awards · FY 2025 · 2025-06

The research component of this project lies at the intersection of geometry, dynamical systems, and group theory. A dynamical system is concerned with the long-term behavior of evolving physical or geometric objects, such as planets orbiting the sun or water flowing through a pipe. Mathematicians have gained deep insights about geometric shapes by studying the dynamics of their symmetries. This information is naturally recorded in a group, and algebra and geometry become intimately connected. This project will exploit the dynamics of such symmetries to unravel intrinsic properties of low-dimensional geometric objects. The project's goals in both intellectual merit and broader impacts are deeply intertwined, and the proposed research will directly inform and enhance the educational components of the project through the involvement of undergraduates in research and outreach, and graduate students in research, mentoring, and outreach. The project has four main research goals: (1) to prove the singularity conjecture for Cannon-Thurston maps, (2) to study the dynamics of free group automorphisms to obtain rigidity results in free and free-by-cyclic groups, (3) to classify hyperbolic extensions of free groups, and (4) to study dynamics in flat surfaces to reveal exotic number-theoretic behavior and obtain curve counting results. The educational component of this project includes enhancing the infrastructure of the Madison Experimental Mathematics Lab (MXM), expanding MXM through carefully designed outreach initiatives, and creating and implementing a Research Incubator for graduate students and postdocs. Additionally, the PI will continue their engagement in other professional activities through organizing conferences, workshops, and seminars; developing a new graduate course; and mentoring of undergraduates, graduate students, and postdocs. 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 · 2025-05

PROJECT SUMMARY This career development award will allow Dr. Nicholas Burgraff to establish an independent research career dedicated to understanding the neurophysiological control of airway function and its intricate interactions within neural networks that regulate respiration, with a pivotal focus on how various pharmaceuticals, notably opioids, can disrupt these systems. This line of research is crucial as it addresses how drugs may inadvertently contribute to potentially life-threatening complications like respiratory depression. The training plan and research strategy outlined in this proposal, combined with Dr. Burgraff's experience in translational physiology, respiration, and rhythm generation, positions him exceptionally well for success in this endeavor. The primary sites of focus in this research are the Dorsal Motor Nucleus of the Vagus, Nucleus Tractus Solitarius, and Nucleus Ambiguus, areas with significant influences on airway smooth muscle control and the balance of autonomic regulation. We hypothesize that fentanyl disrupts this balance, favoring parasympathetic dominance that leads to airway constriction. Additionally, the study aims to establish dual-action treatments targeting both this constriction and rhythm disruptions without reversing opioid binding, offering a new paradigm in opioid overdose interventions. This project will expand Dr. Burgraff’s prior training in electrophysiology and whole animal physiology by incorporating cutting-edge techniques including retrograde viral tracing, immunohistochemistry, optogenetics, and high-density neural recordings. Merging these methodologies will allow Dr. Burgraff to leverage a multi-level approach to investigate the functional dynamics of fentanyl on neuronal circuits controlling airway constriction and assess counteractive strategies. Building upon Dr. Burgraff's preliminary results, the proposed research will pave the way for developing effective therapeutic strategies that complement or replace conventional opioid reversal strategies. By shedding light on the specific neural circuits and autonomic mechanisms underlying fentanyl-induced airway constriction, this project holds the potential to significantly improve patient safety and outcomes in various medical scenarios where opioids are used, from acute pain to long-term opioid therapy. This investigation thus aligns seamlessly with Dr. Burgraff's career objectives, his pursuit of R01 funding, and his commitment to advancing the understanding and management of complications associated with opioid use. To assist Dr. Burgraff in accomplishing the research and career development objectives of this proposal, he will receive strong mentorship from Dr. Nino Ramirez, a distinguished figure in respiratory rhythm generation with an impressive track record in mentorship. He will also be supported by an advisory committee of established professors and attending physicians, all with expertise in the techniques and translational relevancies that are integral to this proposal. With full institutional support and the additional training, mentorship, and experience that this grant will provide, Dr. Burgraff will be positioned to successfully compete for R01-funding and establish a high-impact independent research program in this critical area of study.

NIH Research Projects · FY 2026 · 2025-05

ABSTRACT__________________________________________________________________ Evidence from our research group and others suggests that the gut microbiome plays a role in Alzheimer’s disease (AD), but few studies have tested the impact of gut microbiome modulation in AD. Here we propose to test the safety and feasibility of a custom probiotic intervention among people with AD dementia and preclinical AD, test secondary outcomes to prepare for a future clinical trial, and explore potential mechanisms by which gut microbiome modulation impacts the brain in AD. We will achieve this by enrolling participants from the Wisconsin Alzheimer’s Disease Research Center to participate in a randomized double-blind trial of a custom probiotic formulation. Half of the participants will be randomized to probiotic supplementation, and half will be randomized to placebo. The study will include participants with mild AD dementia and participants with preclinical AD (cognitively unimpaired and amyloid positive). Participants will undergo the probiotic intervention or placebo for 24 weeks and be evaluated at baseline, week 12, week 24, week 36, and 1 year. In addition to safety and feasibility, we will evaluate secondary outcomes to prepare for a future clinical trial. We will assess cognitive function and plasma biomarkers before, during, and after the intervention, as well as collect stool samples over the course of the study. We will begin to assess leading mechanisms by which the gut may impact the brain to prepare for a future trial, including impacts on gut inflammation and intestinal permeability, and modulation of bile acid metabolism. We hypothesize that the probiotic intervention will be safe and feasible, and will modulate the composition and activity of gut microbiota, impacting bile acid metabolism, intestinal permeability and AD outcomes. Very little is yet known about the utility of probiotic interventions in the context of AD, which is critical for advancing the gut microbiome field toward novel interventions for AD. There is a significant need to ensure that research on gut microbiome and AD benefits individuals with dementia and those at risk for cognitive decline. Successful completion of the proposed aims is expected to inform the participant selection, design, and endpoints of subsequent clinical trials, and inform upon the link between gut and brain in the context of AD.