University Of Iowa

NIH Research Projects · FY 2026 · 2024-12

PROJECT SUMMARY: Amelogenesis imperfecta (AI) is a rare genetic congenital enamel disorder characterized by enamel that is prone to rapid wear and breakage. AI affects approximately 1 in 15,000 children in the United States and poses a significant financial and psychosocial burden for those affected. Moreover, our understanding of the etiology of AI is limited with roughly 50% of cases having no known genetic cause. The long-term goal of this research proposal is to study the function of a novel AI associated gene, Mediator of Cell Motility 1, or MEMO1, to uncover molecular mechanisms of normal and abnormal enamel development—ultimately leveraging these details in regenerating enamel. The applicant previously identified a role for the protein MEMO1 during amelogenesis. Oral ectoderm loss of MEMO1 led to severe enamel hypomineralization and chipping, like that observed in humans afflicted with AI. Despite severe enamel pathology associated with loss of Memo1, several questions remained. For example, what are the spatial and temporal dynamics of MEMO1 during amelogenesis? How does MEMO1 function within the ameloblast? This fellowship aims to tackle these questions with the central hypothesis that MEMO1 is essential within the definitive ameloblast at the earliest onset of enamel mineralization and functions within a network of integrin- based signaling and cytoskeletal dynamics. This hypothesis is based on preliminary data and shared enamel pathology associated with oral epithelial loss of Memo1 and integrins. Two experimental aims will address this central hypothesis. In aim 1, conditional mouse genetics, µCT, nano-indentation, histology, immunofluorescence, and single cell RNA sequencing will assess the spatial and temporal requirements of MEMO1 during amelogenesis. In aim 2, a Memo1 knockout ameloblast cell line will be coupled with immunofluorescence, integrin-activation assays, live-cell imaging, co-immunoprecipitation, proximity-based ligation proteomics, and pull-down assays to assess MEMO1’s ameloblast-specific, cellular function. Insights from the proposed research will enhance our comprehension of MEMO1’s contribution to normal enamel development and mechanisms underlying AI. The resulting insights may pave the way for improved diagnostic and therapeutic strategies for AI. With combined mentorship from Dr. Van Otterloo and Dr. Tootle, the applicant will develop skillsets in single cell bioinformatic analysis, proteomics, live cell imaging, and micro- computed tomography greatly advancing their doctoral training. The comprehensive training plan, cohesive team, and supportive institutional environment outlined in this research proposal will advance treatment of oral and dental disorders and propel the applicant forward along a path of an independent researcher.

NSF Awards · FY 2024 · 2024-11

The broader impact/commercial potential of this I-Corps project is the development of an innovative initiative poised to transform the educational landscape through artificial intelligence. This technology aims to improve learning experiences by providing personalized, efficient, and accessible educational tools for students, educators, institutions, researchers, and publishers. By leveraging advanced artificial intelligence (AI), the proposed tool enhances operational efficiency, accelerates research innovation, and democratizes access to educational resources. Central to its mission is the mitigation of inequality among students, faculty, and researchers by removing prevalent barriers to accessing information and learning resources. This technology is particularly beneficial in improving retention rates among low-income and marginalized groups, who often face disproportionate challenges in educational settings. The commercial potential lies in its wide applicability across various educational settings, including K-12 schools, higher education institutions, professional training programs, and academic publishing. This I-Corps project utilizes experiential learning coupled with a first-hand investigation of the industry ecosystem to assess the translation potential of the technology. This solution is based on the development of intelligent agents designed to cater to the specific needs of users within the academic ecosystem. The artificial intelligence (AI) tools include emotionally aware assistants for students, automated grading systems for educators, and data-driven insights for institutional decision-making. The project builds on a decade of AI research, including advancements in adaptive learning systems, data analytics, and user experience design, integrating these advances into practical, user-focused solutions. The technology incorporates a robust Software-as-a-Service platform with a container architecture for efficient load balancing and resource allocation. It utilizes a dual approach for its AI models, incorporating Application Programming Interface (API) based models for advanced natural language tasks and open-source tools for textual and multimodal analysis. The tool showcases significant intellectual advantages, such as flexibility in model selection, fine-tuned domain-specific models, and comprehensive review capabilities. This approach promises to enhance educational outcomes and operational efficiencies, ultimately contributing to a more educated and technologically adept society. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NIH Research Projects · FY 2026 · 2024-11

Project Summary The COVID-19 pandemic caused by severe acute respiratory syndrome-related coronavirus 2 (SARS-CoV-2) remains a threat to public health, particularly in aging populations. The top priority for COVID-19 research is to improve fundamental knowledge of SARS-CoV-2 and viral pathogenesis, including studies to characterize the virus and to understand the host immunity. Our proposed study aims to better understand the molecular mechanisms underlying SARS-CoV-2 infection and innate immune regulation, which is important for controlling COVID-19 and potential future threats of other emerging coronaviruses. Sterile alpha motif (SAM) and HD-domain containing protein 1 (SAMHD1) is the unique mammalian dNTP hydrolase (dNTPase) that also regulates innate and adaptive immunity in hosts. Importantly, SAMHD1 phosphorylation negatively regulates its dNTPase activity and antiviral function. We found that SAMHD1 negatively regulates antiviral innate immune responses and inflammation through interacting with various key proteins in innate immune signaling in macrophages. SAMHD1 transcript is upregulated in SARS-CoV-2 infected primary human bronchial epithelial cells. Our preliminary data showed that SARS-CoV-2 infection of human lung epithelial cell lines or primary human airway epithelial (HAE) cultures significantly upregulated SAMHD1 phosphorylation. However, the function of SAMHD1 in regulating SARS-CoV-2 replication and innate immunity remains unclear. Our hypothesis is that SARS-CoV-2 infection increases inflammation in lung and airway epithelial cells by upregulating phosphorylation of SAMHD1, thereby reducing SAMHD1-mediated anti- inflammation effects. Our established primary HAE cultures provided a physiologically relevant in vitro model to study SARS-CoV-2 infection and cellular responses. We will also use an established mouse model of SARS-CoV-2 infection as a complementary in vivo approach in our studies. We designed two specific aims to test our hypothesis: Aim 1. To examine the role of SAMHD1 in SARS-CoV-2-induced inflammation of primary HAE cultures and SAMHD1- knockout mice; and Aim 2. To investigate the mechanisms of SARS-CoV-2-upregulated phosphorylation of human SAMHD1. Accomplishing our multidisciplinary studies will help define the mechanisms by which SAMHD1 regulates SARS-CoV-2 replication, inflammation, and antiviral innate immunity.

NSF Awards · FY 2024 · 2024-11

The human respiratory system relies on airway basal cells (BCs), a type of stem cell, to keep lungs healthy. These cells replace damaged cells and help remove debris and pathogens through a process called mucociliary clearance. The extracellular matrix (ECM), a network of proteins that provides structural support for these cells, significantly influences the ability of BCs to replicate and transform into different types of airway cells. Unfortunately, existing laboratory models do not fully mimic lung ECM, particularly factors like composition and stiffness, making it difficult to study how these environmental conditions influence BC behavior. This project aims to create a new material that simulates the composition and stiffness of lung tissue, which will allow researchers to control precisely the environment around BCs so they can explore how these factors affect how the cells grow, replicate, and differentiate into cells necessary for proper lung function. Results from this research may lead to new treatments for lung diseases, especially conditions that damage the airways. Beyond advancing lung disease research, this project will promote interest in science, technology, engineering, and mathematics (STEM) careers among middle school students, particularly in underserved rural communities. Through a partnership with the educational app Couragion, the research findings will be transformed into interactive content, offering students a fun and engaging way to explore scientific careers. This research aims to engineer a biomaterial platform to investigate how the extracellular matrix (ECM) influences airway basal stem cell (BC) self-renewal and differentiation. Current models such as air-liquid interface cultures and 3D organoids do not fully replicate the dynamic mechanical and biochemical environment of the lung ECM. To address these limitations, poly(ethylene glycol)-based hydrogels that can dynamically stiffen to precisely control ECM composition and stiffness will be used. This interdisciplinary approach combines expertise in materials science, stem cell biology, and regenerative medicine to develop an advanced platform for studying cell-matrix interactions. The study will examine how variations in ECM stiffness and protein composition affect BC renewal and differentiation, and harness these environmental cues to reproducibly control cellular function. BC responses to tunable biomaterials will be assessed, focusing on outcomes such as cell proliferation, differentiation capacity, and gene expression. This project addresses significant gaps in understanding how the mechanical and biochemical ECM properties regulate BC function, with wide-reaching implications for tissue regeneration and disease modeling. The ability to separately control ECM stiffness and composition will offer new insights into how lung development and repair are managed at the cellular level. 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

The purpose of this project is to organize the second meeting of NSF's Formal Methods in the Field (FMitF) program. Expected participants are investigators of projects currently funded by the program and a selection of researchers interested in submitting proposals to it in the future. The project's novelties are the participation of potential future applicants and invited talks from people in industries where formal methods are in regular use. The project's impacts are an increased awareness of the FMitF program and a deeper understanding of the variety of research it supports, which will likely lead to a increased participation of the scientific community in the future. Broader impacts include the strong potential for improvements in the approaches being developed by the educational projects supported by the FMitF program, as those approaches could build on the experience accumulated by the transition-to-practice projects and the challenges encountered in training external users. The event, which will be hosted by the University of Iowa, will be one and a half days long and will take place in person in Iowa City, Iowa, on November 12-13, 2024. It will include activities such as short talks and poster presentations by researchers from currently funded projects, invited talks by prominent researchers in formal methods from industry, and breakout discussion sessions. The objectives of the meeting are to give the FMitF program directors an overview on the state of progress in the various funded projects, let all participants learn about the research funded by the program, provide opportunities for cross-fertilization of ideas, and, finally, identify challenges in the broader adoption of formal methods and suggest next steps for addressing them. 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 · 2024-10

This project aims to serve the national interest by implementing evidence-based practices and support structures in engineering courses to improve student learning and performance. A substantial majority of undergraduate students report that they have not been taught how to study or learn effectively, which can lead students to use ineffective strategies that lower academic success. To support effective student learning, educators at the University of Iowa have distilled evidence from brain science into a manageable set of practices based on mindset, metacognition (processes to plan, monitor, and assess one's own learning), and memory (the 3Ms). This project is designed to bring that brain science knowledge into engineering by engaging students in deliberate, continual practice with 3M strategies in their engineering courses in order to cement the practices into students' academic habits. This research seeks to advance the understanding of how engineering students engage with constructs from cognitive science and how incorporation of 3M strategies in second-year engineering courses have the potential to impact student performance, alter students' use of metacognitive learning strategies, and help students become more self-regulated learners. The project team plans to provide professional development to undergraduate faculty members to support the redesign of critical elements of their course materials and class support structures through a series of workshops, a community of practice, and reflective practices. Teaching assistants will engage in 3M training focused on modeling and practicing behavior in scenarios related to student help hours and assignment grading and feedback. A mixed methods approach will be used to assess the impact of the interventions on students' academic performance, use of cognitive and metacognitive learning strategies, and motivation. Student course assignments, reflections and cognitive wrappers, questionnaires, and interaction data will document the students' engagement with the 3Ms. Research findings, training materials, and resources will be disseminated through national workshops, publications, and publicly available education websites. The NSF IUSE: EDU Program supports research and development projects to improve the effectiveness of STEM education for all students. Through its Engaged Student Learning track, the program supports the creation, exploration, and implementation of promising practices and tools. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NSF Awards · FY 2024 · 2024-10

This project aims to serve the national need of mitigating the underrepresentation of women in science, and therefore contributes to scientific progress. Peer mentorship is one of the most effective avenues to increase the status of women in academia. By providing intense peer-mentorship to junior women scholars of international relations, the project will promote high-quality scholarship and contribute to an increased success of mentored women in academia. The project will promote these goals through the hosting of intense peer-mentorship workshops to foster networks, provide feedback and support, disseminate information, and encourage psychological resilience. The project also tracks the success of peer-mentorship programs through survey research and a collection of data on academic success. Studies that have evaluated the status of women in international relations over the past 30 years reveal significant gender gaps on numerous dimensions. The continued under-representation of female scholars at top research institutions and high ranks harms scientific progress. Recent research demonstrates that active mentoring, especially through workshops that foster networks, provide feedback and support, disseminate information, and encourage psychological resilience, are among the most promising avenues for change. The Journeys in World Politics workshop program has mentored young women scholars of International Relations (IR) since 2004. The project hosts annual three-day workshops that support 18-20 participants and includes research presentations by junior scholars, feedback from discussants, oral autobiographies by senior scholars, and career and gender discussion sessions involving topics such as networking, work-life balance, and navigating classroom gender dynamics. Beyond the workshops, the project maintains an active website and other forms of communication, arranges meetings at conferences, and thereby builds a broad network of women in the entire political science discipline. To track the success of mentorship workshops, the project collects more systematic data to evaluate the mechanisms through which mentoring programs increase long-term success rates for female political scientists. 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 · 2024-10

Transition-metal-carbide (TMC) ceramics, such as zirconium carbide (ZrC) or tungsten carbide (WC), are critical high-temperature materials composed of transition metals and carbon atoms. They exhibit superior mechanical, chemical, and thermal properties and have thus attracted vast interest in harsh environment applications, such as cutting tools, engine parts, heat exchanger, and nuclear fuel cladding. Additive manufacturing (AM) offers the potential to fabricate TMC parts with much more complex geometries for their extensive applications but entails substantial carbon emissions and energy consumption. This Future Manufacturing project supports research that will lead to a novel AM process for TMC ceramics, named vacancy-assisted jet fusion (VJF), which can potentially reduce the processing temperatures and carbon emissions associated with existing AM processes for TMCs. The project will engage K-12 and underrepresented minority students through outreach activities such as ceramic art design program and the Science Undergraduate Laboratory Internships (SULI) program to help raise awareness of ceramic AM technologies among young people in Iowa and attract a diverse pipeline of workforce to the manufacturing industries and beyond. The VJF process fabricates intricate TMC parts through the combined use of locally induced crystal vacancies and layerwise triggered electron flow. The objective of this research is to determine the effects of locally induced crystal vacancies and layerwise triggered electron flow on the densification of TMC particles. This project utilizes an integrated approach including high throughput printing, multi-scale material characterizations, and machine learning (ML)-based material simulations to fill the critical knowledge gap in the effects of locally induced crystal vacancies and layerwise trigger electron flow on the densification of TMC particles. Specifically, this project will (1) quantify the effects of layerwise triggered electron flow on the diffusion of locally induced crystal vacancies using high-throughput, multi-nozzle inkjet printing and advanced microscopic techniques, (2) uncover the underlying mechanisms that govern the diffusion of locally induced crystal vacancies using large-scale atomistic simulations via machine learning force field (ML-FF), and (3) determine the effects of vacancy diffusion on densification kinetics of TMC particles utilizing meso-scale characterization tools. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NSF Awards · FY 2024 · 2024-10

Mathematics and computer science are inextricably linked. However, it is well-known among educators and education researchers that undergraduate computer scientists often do not appreciate the relevance of mathematics to their discipline. This disconnect adversely affects students, especially as they progress from concrete, practical introductory courses centered on programming to theoretical upper-level courses rooted in abstract mathematics. Researchers have observed that student performance in the classroom and retention within the major falter when these connections are not established. This project's impact is to address these concerns by developing pedagogy that (a) unites the mathematical foundations and practice of computer science together in a way that all undergraduates can appreciate and directly apply in their future endeavors and (b) is adoptable by as many institutions as possible, especially those with limited room to expand their curriculum. To accomplish these goals, the investigators develop, deploy, and evaluate new pedagogy that integrates formal methods techniques within the existing undergraduate computer science curriculum. Specifically, this pedagogy introduces program reasoning, an activity all computer scientists perform, as the primary vehicle for studying the mathematical foundations of computing in the contexts of introductory programming, discrete mathematics, and algorithms courses. Such pedagogy bridges the gap between mathematics and computer science for all undergraduate computer scientists and makes relevant formal methods for a new generation of programmers. Additionally, the project promotes the relevance of formal methods to undergraduate computer science educators, as exemplified by this pedagogy, through a series of workshops at the regional and national levels. 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 · 2024-10

Black and Latinx people are underrepresented in the STEM workforce. This project examines how curricula and practices in a culturally situated, community-based youth development program nurture and support the STEM engagement of Black and Latinx boys and girls. Often research supporting out-of-school-time (OST) activities in STEM and traditionally underrepresented youth takes place in newly created learning environments. However, this program goes to where the youth are already, the Downtown Boxing Gym. Building knowledge and understandings on the inclusion of arts into gender-based STEM research could have implications for the future of OST research and programming. The project will explore how out of school learning spaces can broaden participation of Black and Latinx youth in STEM focused learning opportunities. Participants in this project are 170-250 youth, ages 8-18, who are involved in the Downtown Boxing Gym in Detroit, Michigan. This project utilizes a mixed methods approach to collecting and analyzing survey data, interview data, and video data using thematic and interaction analyses. The goals of the project are to: (1) examine how youth learn STEM in informal environments; (2) advance the knowledge base of informal STEM learning, and (3) increase belongingness, broaden participation, and support learners' participation in and understanding of STEM practices utilizing a student- and practitioner- driven approach. During the school year, the program is offered twice a day, five days each week, for one hour, and during the summer five days a week, four hours a day. The program curriculum is collaboratively created by staff and students and may include topics and activities such as: 3D modeling, video game coding, environmental analysis of wildlife, chemistry, artificial intelligence/facial scanning, and robotics programing/construction. This Type 4, Integrating Research and Practice, project is funded by the Advancing Informal STEM Learning (AISL) program, which supports projects that: (a) contribute to research and practice that considers informal STEM learning's role in equity and belonging in STEM; (b) promote personal and educational success in STEM; (c) advance public engagement in scientific discovery; (d) foster interest in STEM careers; (e) create and enhance the theoretical and empirical foundations for effective informal STEM learning; (f) improve community vibrancy; and/or (g) enhance science communication and the public's engagement in and understanding of STEM and STEM processes. 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 · 2024-10

Recent advances in machine learning have led to more accurate software-based predictions by leveraging the vast amounts of data that are currently produced, stored, and analyzed by modern computers. Many of these advances are due to deep learning, through which the available data is used to train artificial neural networks in which every input is sequentially analyzed by many layers of artificial neurons to identify more complex relationships. When the prediction task is more challenging or the predictions need to be more accurate, considerably larger networks are trained with dedicated hardware such as general-purpose Graphics Processing Units (GPUs). Nevertheless, individuals and organizations with more constrained resources may not have access to GPUs, and those larger networks may not fit in embedded systems such as Internet of Things (IoT) and mobile devices. On the one hand, there are many inexact pruning methods for reducing the size of a neural network after training. These methods may reduce the accuracy, affect the robustness of the network when applied to slightly modified data, and lead to fairness issues because the effect of pruning is uneven and disproportionally affects groups that are underrepresented in the data. On the other hand, the relationships that trained neural networks represent are often not as complex as they could potentially be. That implies that it is possible to obtain smaller neural networks representing the same relationships, hence avoiding the side effects of conventional pruning methods. This project aims to improve our understanding of what neural networks can represent, and how they can be exactly compressed for a more efficient use. This project aims to develop exact neural network compression algorithms and investigate the relationship between network expressiveness in terms of the number of linear regions and network compressibility by leveraging polyhedral theory and discrete optimization techniques. Our primary goal is to develop faster and more scalable algorithms to identify network modifications having limited or no effect to the model represented by trained neural networks. Secondarily, we aim to identify theoretical connections between representability and compressibility as well as develop more efficient methods for measuring the number of linear regions. 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 · 2024-10

This EArly-concept Grants for Exploratory Research (EAGER) award supports research to address the challenge of integrating unmanned aircraft systems (UAS) into the congested airspace near airports. The research will focus on developing advanced motion planning algorithms to coordinate the navigation and control of multiple manned and unmanned aircraft during landing sequences, specifically targeting the initial approach and holding pattern navigation. A key aspect of this research is to enhance pilot comfort by managing cognitive load during the critical phase of integrating UAS with manned aircraft. This includes ensuring pilots maintain high situational awareness without excessive stress due to UAS proximity. Additionally, the project seeks to increase operational efficiency, which can be measured by the number of aircraft landings per time unit or reduced wait times for landing clearances. The ultimate goal is to develop a landing strategy for mixed traffic that demonstrates higher efficiency than scenarios involving only manned aircraft. To achieve these objectives, the project will focus on three main areas of research: developing a numerical solver for optimal control, mathematical modeling of informal navigation rules, and integrating cognitive state analysis into UAS motion planning. The numerical solver aims to manage complex cost functions and constraints in densely pilot-populated UAS environments near airports. The mathematical modeling will translate the informal rules that guide pilot behavior into algorithms that enable UAS to mimic and anticipate these behaviors. Integrating cognitive state analysis into UAS motion planning involves evaluating pilots’ cognitive states through physiological measures and using this data to refine UAS navigation strategies. The anticipated outcomes include the integration of UAS into airspace near airports, significantly benefiting air traffic management, national security, and smart transportation systems. This project also aims to foster innovation in autonomous systems research and education, providing a multidisciplinary research platform for students and contributing to the broader acceptance and utilization of UAS technologies. 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 · 2024-10

The objective of this project is to support research on multimodal transit services, combining fixed-route public transit with shared mobility services, while accounting for systematic uncertainties, rider preferences, and inherent complexity of different transportation modes. Car-less households face challenges in accessing jobs and services mainly due to difficulty in traveling between transit hubs and origins/destinations. At the same time, uncertainties in travel time, demand, and rider choices significantly impact design and operations of transit services. The research team investigates service planning and network design for fixed-route transit, as well as fleet sizing, routing, and relocation for shared mobility. Successful implementation is expected to (i) advance theories and computations in transportation and network problems under uncertainties, and (ii) enhance the potential of multimodal transit services to reduce private vehicle ownership, lower greenhouse gas emissions, and alleviate urban traffic congestion, while providing affordable transportation services for underserved groups. The team also contributes to curriculum development at the University of Minnesota and the University of Iowa, promote diversity in STEM fields, enhance undergraduate research, and engage in K-12 outreach activities. The research focuses on developing a hierarchical, data-driven optimization framework that incorporates user behaviors for planning and operating multimodal transit systems under systematic uncertainties. Demand response to multimodal transit services is characterized through a hierarchical process to accommodate diverse user adoption preferences. Corresponding decision-making is modeled as sequential resource planning and allocation processes. The models and methodologies are based on stochastic optimization with single- and multi-stage dynamics. The primary outcomes include (1) an integrated hierarchical optimization framework to capture user behaviors; (2) data-driven methods to learn use preferences in transportation systems; (3) distribution-free approaches to accommodate unknown uncertainties in network design; and (4) efficient computational methods to enable practical application. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NIH Research Projects · FY 2025 · 2024-09

Project Summary One in twenty-six individuals will develop epilepsy during their lifetime. A major cause of epilepsy worldwide is viral encephalitis. Infected patients are 16x more likely to develop epilepsy than the general population. Active infection can provoke seizures in the short term, but also increase the risk of spontaneous, recurrent seizures post-viral clearance. However, the mechanisms underlying seizures during the acute phase and the development of chronic epilepsy in the post-viral phase are unknown. The Wilcox lab and collaborators have developed the only mouse model of viral-induced temporal lobe epilepsy (TLE). C57Bl/6 mice injected with Theiler’s murine encephalomyelitis (TMEV) recapitulate features of human viral encephalitis: mice exhibit seizures 3-8 days post- infection (DPI), clear the virus by 14 DPI, and can eventually develop chronic TLE. TMEV infection induces inflammation, reactive gliosis, and cell death in the hippocampal CA1, which may contribute to acute seizure development. However, over half of previously infected animals will develop recurrent, spontaneous seizures long after viral clearance. This suggests differing etiologies between acute and chronically occurring seizures in TMEV. CA3 neurons are spared by TMEV infection and the amplitude distribution of CA3 mEPSCs varies across the acute and chronic phase. It is possible that hippocampal damage and consequential inflammation incite acute seizures, while long-term changes in hippocampal circuitry underlie the chronic seizures. The progression of TMEV-induced hippocampal lesions and underpinnings of acute vs chronic seizures are gaps in our knowledge that this proposal aims to address. We will quantify TMEV-induced cell loss and use targeted recombination in active populations (TRAP) to map the epileptogenic zone and seizure propagation networks during discrete post-infection timepoints. In Aim 1, we will perform immunolabeling-enabled 3-dimensional imaging of solvent cleared organs (iDISCO) in TMEV-infected mice at 5 DPI (seizure peak), 14 DPI (after acute seizures resolve and the virus is cleared), and following the first recorded chronic, spontaneous seizure to determine the extent and progression of lesions in the acute and chronic phase of TMEV infection. In Aim 2, we will determine seizure propagation pathways in TMEV-infected mice following seizures in the acute vs chronic phase by tagging neurons active during seizures at 5 and 14 DPI and the chronic phase with TRAP. Activated circuitry will then be quantified to compare seizures across the course of TMEV infection and the subsequent development of TLE. Participation in the proposed training plan and completion of these experiments will advance my neuroscience training in pursuit of a career as an independent epilepsy researcher. It will also address crucial questions about epileptogenesis across TMEV infection. These experiments are the foundation for a future K99 aimed at manipulating the regions, networks, and cell types identified here. It is our hope that we may discover critical clues to novel treatments for epilepsy patients.

NIH Research Projects · FY 2025 · 2024-09

Project Summary Iowa is currently number 2 in the United States for cancer incidence a ranking that is an action call to accelerate adaptation and adoption of evidence-based interventions (EBIs) aimed at preventing cancer, screening for cancer, treating cancer, and supporting cancer survivors. For a state like Iowa, EBIs need to be innovatively adapted, building on what we understand to be effective in a rural context. The University of Iowa Prevention Research Center for Rural Health (UI PRC-RH) will continue its successful participation in the Cancer Prevention and Control Research Network (CPCRN) as a collaborating center, implementing EBIs to address cancer disparities in rural areas and micropolitan communities. As an active, productive CPCRN participant since 2014, we have drawn on distinctive resources, especially a well-functioning statewide network of partners that includes hospitals, community-based organizations, and the statewide cancer consortium. The success of our center also derives from its team of productive researchers with expertise in cancer prevention and control, specifically HPV vaccination, and extensive experience with rural populations. Over the next five years, our participation in the CPCRN organization and workgroups will strengthen existing CPCRN collaborations and form new ones to support the adoption of evidence-based interventions across the cancer continuum in rural areas. HPV vaccination uptake is one area where we understand which interventions are effective, but they are not always implemented in rural areas. In Iowa we have a disproportionately high incidence of HPV-associated oropharyngeal cancer (OPC). At the same time, our rates of HPV vaccine completion in Iowa are lower than the national average. A “strong provider recommendation” is an effective intervention for many health behaviors, and it has been especially valuable for HPV vaccination. One strategy for adapting this EBI to our state is to expand the number of health-related professionals making a strong recommendation. We propose testing whether dental professionals can be effective recommenders of the HPV vaccine. Dental professionals are uniquely positioned to promote the HPV vaccine, as they perform routine oral cancer screenings and preventive dental care at every patient visit. Based on formative research, we developed an intervention—Educate, Recommend, Refer—that includes skills-based, data- and theory- informed trainings and supporting materials. The central hypothesis is that providing dental professionals with the Educate, Recommend, Refer intervention will result in parents receiving HPV vaccine education, recommendations for the vaccine, and referrals to local vaccine providers. The outcomes of our work will accelerate implementation of evidence-based cancer prevention and control strategies in rural and micropolitan communities, thereby helping to decrease health disparities between rural and urban populations. Building on our prior research in rural areas, we will continue to make our distinctive contribution to the growing body of knowledge on disseminating and implementing EBIs to lessen the burden of cancer.

NIH Research Projects · FY 2025 · 2024-09

Project Summary Multiple forces are undermining US vaccination rates, resulting in the reemergence of previously eliminated diseases. Despite decades of intervention development to improve vaccination outcomes, most interventions generally have little to no impact. This is especially true in rural areas of the United States. One reason why existing vaccination interventions may fail is the underlying assumption that non-vaccination is the result of either not knowing, or having misconceptions, about essential aspects of vaccination. However, the scientific evidence from evaluations of vaccination interventions generally goes against this assumption. Drawing on decades of research from political psychology and “motivated social cognition”, along with preliminary data for this proposal, we argue that people find vaccine confidence or hesitancy more attractive to the extent that they experience motivational factors to manage threats, reduce uncertainty, have cooperation-based social goals, and prefer objective information. For example, in one of our prior studies we found higher intentions to “catch up” on HPV vaccination for unvaccinated young adults that had stronger emotional reactions to rare threats, greater aversion to changing what they think, and higher interest in scientific or numeric information. We propose to improve how we promote vaccines by creating “motivational fit”, communicating vaccination-related information in such a way that vaccine confidence satisfies an audience’s motivational goals better than vaccine hesitancy. The overall objectives of this application are to 1) identify motivational factors that can be used to alleviate specific dimensions of vaccine hesitancy and improve vaccine uptake, especially among rural Americans, 2) create and test vaccination promotion strategies that have motivational fit for use with a public- facing website tailored to addressing specific dimensions of vaccine hesitancy, and 3) lead the development of connections among the ARISe Network centers and our other partners to identify and create innovative solutions to address challenges in immunization services research and practice. At the conclusion of this funding cycle, we will have advanced our theoretical and practical knowledge about immunization service utilization, created a publicly accessible website to address vaccination concerns, made significant contributions to ARISe activities, and facilitated connections among ARISe Network centers and our partners that help generate innovative solutions to addressing the challenges facing immunization services utilization.

NIH Research Projects · FY 2025 · 2024-09

The Prevention Research Center for Rural Health (PRC-RH) mission is to address disparities in and across Midwestern communities to promote well-being. Among many social, structural, and environmental determinants of health, place matters. In the US, 97% of land is considered rural, and 19% of the population live in these places. Rural residents are more likely to die from each of the ten leading causes of death; yet rural health programs are underfunded. Place also intersects with other important social identities, including sexual and gender identity, frequently referred to as LGBTQIA+ (Lesbian, Gay, Bisexual, Transgender, Queer, Questioning, Intersex, Asexual and additional aspects of sexual/gender identity). LGBTQIA+ individuals are at elevated risk of cancer, chronic obstructive pulmonary disease, and cardiovascular disease than their heterosexual and cisgender peers. Less is known about LGBTQIA+ lives in rural areas. Many socio-ecologic factors influence these outcomes including experiences of stigma and discrimination. These experiences also drive risk behaviors including tobacco use. Tobacco use is significantly higher among LGBTQIA+ young adults (YA) than their heterosexual and cisgender peers. Evidence-based cessation strategies, such as Tobacco Quitlines (QL) are available, but YA significantly underutilize them. QL offer free, convenient, confidential cessation services that can address barriers in access to treatment. There is a clear implementation gap in evidence about what works to increase uptake of QL for rural LGBTQIA+ YA who use commercial tobacco products. Community-engaged research with these YA is necessary to center their narratives, to understand unique barriers to uptake of the QL; and to design sustainable, culturally relevant, and scalable implementation strategies to increase uptake of the QL. The PRC-RH focuses on micropolitan communities (n=15) in Iowa (IA); rural communities with populations sized 10,000-<50,000 that are growing in diversity, and serve as hubs for education, employment, economic and health activities, and are frequented by residents of smaller rural communities. Our specific aims are: • Aim 1: Promote health equity in IA’s micropolitan communities. Our approach relies on strengthening capacity to conduct prevention research; providing training and technical assistance, and infrastructure to support Aim 2, and communicating, disseminating and translating evidence-based interventions. • Aim 2: Enhance Quitline uptake and smoking cessation among LGBTQIA+ young adults in Iowa’s micropolitan communities. This project will pilot test implementation strategies in two micropolitan communities, develop an Implementation Playbook, scale up the intervention across Iowa, and share lessons learned and translation products with partners across Region G. • Aim 3: Collaborate with other PRCs in the network and other external partners to co-learn, synergize, share successes, and disseminate and translate products for collective health equity impact.

NIH Research Projects · FY 2026 · 2024-09

Abstract Alzheimer’s disease (AD) is an inexorable and devastating neurodegenerative disease affecting mil- lions of Americans. There are no therapies that could stop or reverse the progression of Alzheimer’s disease, in part because the basic factors driving neuronal death and dysfunction are unknown. There is a critical need to better understand the basic biology of AD in order to develop new disease-modify- ing treatments. A key contributing factor to AD is impaired glucose metabolism. Several observations support this con- clusion. First, aging is a major AD risk factor that impairs brain glucose metabolism, reduces mitochon- drial biogenesis, and decreases ATP levels. Second, neurodegeneration in AD can be directly quanti- fied by imaging glucose metabolism via techniques such as 18F-fluorodeoxyglucose (FDG) positron emission tomography (PET). Third, metabolic diseases such as obesity and diabetes are key risk fac- tors for AD. Fourth, interventions that improve metabolism such as exercise, calorie restriction, and treatment for diabetes can mitigate the risk and progression of AD. Last but not least, Aerobic glycoly- sis, which can be measured by FDG-PET and 15O-PET in vivo imaging, is compromised in patients with Alzheimer’s disease. Despite these data, it is unknown how glucose metabolism contributes to neurodegenerative pro- cesses in AD. Our recent work demonstrated that we can enhance one aspect of brain glucose metab- olism, glycolysis, via an existing drug, terazosin (TZ). This drug is an alpha-1 antagonist, but also acti- vates the first ATP-generating step of glycolysis, phosphoglycerate kinase-1 (PGK1). In this proposal, we will interrogate glycolysis in rodent models of AD, including tau and amyloid mouse lines, while measuring metabolomics, cognitive function, 18F-FDG-PET, and protein aggregation. Our overall hy- pothesis is that glycolysis critically regulates neurodegeneration in AD. Our specific aims investigate if disrupting glycolysis affects rodent AD models and if improving glycolysis mitigates neurodegeneration in AD. Because this is a fundamental mechanism, our work could have far-reaching impact for neuro- degenerative diseases, and could be instrumental in inspiring novel disease-modifying therapies for AD and related diseases.

NIH Research Projects · FY 2024 · 2024-09

Summary/Abstract Sarcoidosis a rare systemic inflammatory disease with high morbidity and increasing mortality. Granulomatous inflammation affects the lungs in 90% of cases, with ~1/3 of patients progressing to experience severe pulmonary disease that can result in lung transplant or death. Sarcoidosis is thought to be due to interaction between an unknown environmental antigen and host genetic susceptibility. Extensive epidemiological evidence supports the involvement of bioaerosol in pulmonary sarcoidosis. However, only one component of bioaerosol has been directly measured in a cohort of patients with sarcoidosis. We hypothesize residential bioaerosol exposure drives immune dysregulation in pulmonary sarcoidosis leading to severe lung disease. We will test this through three aims: Specific Aim 1: Determine the association between rBio and pulmonary sarcoidosis severity. We hypothesize bioaerosol exposures are unique within residences of those experiencing severe pulmonary sarcoidosis compared to exposures of patients with minimal to non-existent fibrosis and controls. We will collect rBio and analyze its composition using traditional and micro/mycobiome techniques, then compare it to patient symptoms, lung function and chest imaging. Specific Aim 2: Determine the role of rBio in peripheral blood immune dysregulation in fibrotic pulmonary sarcoidosis. We will quantify and compare serum biomarkers and immune cell profile to rBio. We will compare these findings to controls, and to patient pulmonary disease severity using patient symptoms, lung function, and chest imaging. Specific Aim 3: Assess the epithelial responses to rBio in severe pulmonary sarcoidosis. We hypothesize epithelial cells from patients with fibrotic pulmonary sarcoidosis will have impaired cell adhesion, and barrier integrity in response to rBio. We will test this hypothesis in vitro by exposing primary human airway epithelial cells from recruited subjects to BDG, LPS and mixed bioaerosol from residences. We will assess protein expression, transcriptomic and functional responses. Completion of this proposal will inform potential disease mechanisms, diagnostic and progression biomarkers, and novel treatments for people with sarcoidosis including environmental remediation

NIH Research Projects · FY 2024 · 2024-09

PROJECT SUMMARY / ABSTRACT Language gives meaning to our inner thoughts, interacting with cognitive functions that flexibly manipulate sensory content in mind. Language combinatorial capacities create meaning by combining symbols (words) and rely on an extensive neural system, which when affected by neurological impact leads to disorders of language, memory and thought. Although animal models have deeply informed understanding of neural systems for which there are correspondences to human cognition, such as those for working memory, the neuronal mechanisms of language and its entanglement with cognitive function remain poorly understood. The proposed interdisciplinary team will seek to break through the status quo by leveraging a comprehensive research program that can provide a well-powered study of human language and working memory interactions with unique scalable data capable of resolving neural function across neocortical layers from single cells to systems. Aim 1a: Our language Combinatoric Transformations via Working Memory (CTWM) task will be conducted with up to 100 patients across our neurosurgical partnering sites during high-density laminar array recordings in the operating room from two key brain areas involved in language combinatorics and working memory. Aim 1b: Insights on neuronal function across the cortical layers will be deeply informed by unprecedented information from single- cell genomic and spatial transcriptomic analyses applied to tissue samples after task performance and the laminar array recordings. Aim 2a is to investigate laminar information flow across the cortical array in local field potentials, and Aim 2b in interaction with available (non-laminar) subdural intracranial EEG recordings from other brain areas. Aim 3a is to pre-operatively scale insights to system-wide levels using laminar fMRI in the same patients with the same task, and Aim 3b will integrate the combined neurophysiological and neuroimaging data via a next-generation generative biophysical model. The anticipated outcomes are first-in-human insights on the interplay between language and cognition, unique openly shared multi-modal data and a model that could be applied world-wide to accelerate the understanding of human laminar circuit motifs in health and disease.

NIH Research Projects · FY 2024 · 2024-09

Cognitive fluctuations –termed “the Lewy Body Roller Coaster” by some families – are a debilitating symptom of Lewy body disorders (LBD), an Alzheimer’s disease related disorder that includes Parkinson’s Disease dementia and Dementia with Lewy Bodies. These unpredictable cognitive changes often lead to the loss of independence in patients that could otherwise function. They are characterized by dramatic changes in two key domains: attention (ability to focus/think) and arousal (ability to stay alert/awake). Presence of fluctuations are a key feature used to diagnose LBD. Despite this, a basic understanding of fluctuations is lacking. Our long-term goal is to determine the underlying mechanisms responsible for cognitive fluctuations in LBD such that targeted, effective treatments can be developed. Animal models allow induction of pathology in restricted brain circuits, providing the opportunity to address key basic and translational questions regarding the origin of variability in attention and arousal. In this proposal, we will use injection of the fibrillar form of alpha-synuclein, the protein associated with LBD, into one hub of the brainstem ascending arousal network which is highly affected in patients with this disease. We will use mouse models to test the overarching hypothesis that alpha-synuclein differentially impacts large projecting neurons in the brainstem that orchestrate brain-wide networks necessary for attention and maintenance of arousal. In Aim 1 we will evaluate which cells are vulnerable to pathology. We will focus on one brainstem region, the Locus Coeruleus, which shows pathology in almost all patients with LBD. We will count cells and use live imaging to directly track changes in axons from this arousal hub. Then, in Aim 2 and 3 we will determine how alpha-synuclein inclusions affect arousal and attention, respectively. In Aim 2 we will evaluate arousal using continuous EEG in the context of time-of-day, as well as after exposure to novelty in the home cage. In Aim 3, we will evaluate cognitive variability using a repeatable timing-task combined with pupillometry and imaging at the single-cell level. This proposal uses a combination of translatable non-invasive techniques (EEG, pupillometry) with powerful laboratory methods able to probe individual neuronal activity. The findings will help us better explain findings seen in human patients. Understanding the processes occurring during cognitive fluctuations is key to eventually developing treatment targets, including non-invasive neuromodulation of abnormal neuronal activity and pharmacological modulation of identified neuronal populations.

NIH Research Projects · FY 2024 · 2024-09

Project Summary/Abstract Myofascial pain remains an underdiagnosed contributor to a range of musculoskeletal pain conditions. The lack of validated biomarkers limits the ability to objectively detect myofascial pain, probe underlying pain mechanisms, and guide targeted treatments. This proposal will address this gap by quantifying the biochemical, biomechanical, and structural properties of myofascial pain using advanced, quantitative imaging techniques. As a model of myofascial pain, we have chosen plantar fasciitis, which affects 1 out of every 10 adults. Our long-term goal is to enhance musculoskeletal pain management by creating better tools for detecting abnormal myofascial tissue that enable more individualized treatment. The objective of the R61 phase is to use novel imaging techniques to develop a diagnostic biosignature to objectively and accurately determine the location and severity of abnormal myofascial tissue. Our approach will use a cross-sectional study design with 3 groups: plantar fasciitis (n=50), Achilles tendinopathy (n=25), and pain-free controls (n=25) to test Specific Aim 1: Develop a diagnostic imaging biosignature of myofascial tissue to differentiate individuals with plantar fasciitis from other foot pain without a myofascial component (Achilles tendinopathy) and from matched pain-free controls. The objective of the R33 phase is to use novel imaging techniques to develop a predictive biosignature to identify individuals most likely to respond to DN, and a response biosignature to guide dosing or continued use of DN for myofascial pain for individuals with plantar foot pain. Our approach will use a parallel-group, doubleblinded randomized controlled trial (RCT) design with imaging measured before, during (1 m.), and after treatment (3 & 6 m.). Participants will be randomized to one of two groups: 1) DN + standard care, or 2) Sham DN + standard care to test Specific Aim 2: Determine 2A) predictive (Independent variable: imaging biosignature; Primary outcome: Pain Intensity) and 2B) response (Independent variable: DN vs. Sham DN; Primary outcome: Imaging biosignature/biomarkers) imaging biosignatures in an RCT. Exploratory Aim 3: Will develop composite biosignatures, that combine multiple imaging biomarkers developed in Aims 1 or 2 with psychosocial factors, to enhance the diagnostic, predictive, or response capability for myofascial pain. Transition criteria. 1) Adequate recruitment with >90% of participants in each group enrolled; 2) Adequate representation with neither sex exceeding 60% of the sample; 3) Minimal missing data (<5%) for collected outcomes; 4) At least 2 diagnostic imaging biomarkers with an ROC AUC > 0.7 and FDRs < 0.1; 5-8) Submit DSMP, Study Accrual and Retention Plan, Final sample size and statistical analysis informed by mock recruitment, and R33 transition application, including implementation of an effective sham DN.

NIH Research Projects · FY 2024 · 2024-09

Project Summary/Abstract Neurodegenerative diseases, including Alzheimer’s, Parkinson’s, and Huntington’s disease, constitute one of the greatest challenges in modern therapeutic development due to an inadequate understanding of the interplay of pro- and anti-apoptotic feedback mechanisms operative in the progression of these diseases. This inadequate understanding is in part due to a lack of practical (crosses blood-brain-barrier, well-studied mechanism of action) biochemical tools to modulate and effect related cellular processes, such as neurotrophic responses (pro-survival, pro-growth, and pro-differentation responses), and metal ion homeostasis levels, which are both significantly perturbed in neurodegenerative contexts. The Williams lab and Epp lab propose to evaluate the mechanism and pathological impacts of a non-peptide small molecule, called trans-banglene (t-BG), which has demonstrated neurotrophic effects in cell culture, primary neurons and mouse models of neurodegeneration, is orally bioavailable, and also has recently been shown by the Williams lab to alter iron-binding proteins in PC 12 cells. This combined impact on neurotrophic responses and iron homeostasis makes t-BG well suited to provide insight into the interplay between these two cellular response mechanisms. However, a cellular target and mechanism of action is not yet known for t-BG. The following proposal outlines work to 1) identify the cell recognition/binding partner and localization upon binding, 2) characterize t-BG treatment impacts on known neurotrophic signal transduction pathways, iron localization, and lipid oxidation profile in cells and tissues and 3) to evaluate impacts on neuronal morphology, plasticity and neurogenesis in AD mouse models. The interdisciplinary setting of the Williams lab enables both synthetic access to derivatives of this molecular scaffold as well as cell response data from biochemical assays of their activity. The Epp lab will concurrently validate mechanistic impacts in hAPOE4 knock-in mouse tissues and measure changes in neurogenesis/neuron structure. Importantly, these mechanistic studies will improve understanding of the differential drivers of neurotrophic effects and iron homeostasis. Once mechanism of action is determined, and validated in mouse models, this orally bioavailable molecular tool can be broadly employed in the biomedical community to study inhibition of neurodegenerative disease progression, helping to create the foundation for new medicinal strategies. Further, once a cellular target is established, future work will use structural information regarding binding mode to inform optimization studies that increase potency and drug-like characteristics for t-BG, improving its utility and facilitating drug development investigations.

NIH Research Projects · FY 2024 · 2024-09

PROJECT SUMMARY/ABSTRACT The US population continues to age, and millions of people will likely be affected by age-related muscle atrophy and weakness (also referred to as sarcopenia) at some point in life. This represents an enormous unmet medical need because sarcopenia lacks effective therapy, compromises independence, and increases all-cause mortality. Skeletal muscle fibers are long-living cells that are particularly susceptible to proteotoxic stress and, therefore, rely on efficient selective protein degradation (i.e., degradation of damaged/misfolded proteins) to remain functional. However, the selective degradation of toxic protein aggregates becomes defective with aging contributing to muscle dysfunction. Protein aggregates are degraded primarily by autophagy, and yet impairments in autophagic rates (i.e., flux) are not commonly observed in aging muscle. Collectively, these observations point to an age-dependent impairment in the autophagic sequestration of protein aggregates in muscle. The research proposed here would address this issue by studying the protein kinase ULK2 and its binding partner FIP200. We have recently demonstrated that skeletal muscle ULK2, but not its better-known paralog ULK1, is required for the autophagic sequestration and degradation of protein aggregates. Hence, defective ULK2 activity could contribute to sarcopenia. ULK2 is activated primarily via phosphorylation. We have identified two sites at ULK2 that are phosphorylated in adult muscle but not in aged muscle suggesting these are functionally important. Further, FIP200, a protein that is phosphorylated by ULK2, is hypo-phosphorylated in aged and ULK2 deficient muscles. This is relevant because FIP200 interacts with toxic protein aggregates marked for autophagy degradation and is required for autophagosomal formation at these aggregates. Our proposed studies will build upon these initial findings and use adult and aging mouse models to address the central hypothesis that ULK2 is required for efficient selective degradation of protein aggregates thereby preserving skeletal muscle quality (i.e., force and mass) across the lifespan. We propose two specific aims to address this hypothesis. In Aim 1, we will establish ULK2 role in the development and treatment of sarcopenia. Here, we will use inducible skeletal muscle-specific mouse models to determine the impact of ULK2 loss and gain-of-function on the degradation of protein aggregates and muscle quality in adult and aged mice. In Aim 2, we will define critical mechanisms by which ULK2 regulates the degradation of protein aggregates in adult and aged muscle. Here, we will establish how phosphorylation modulates ULK2 using rescue-of-function experiments with phospho-blocking and phospho-mimicking ULK2 mutations in ULK2 deficient and aged muscles. Next, we will use phospho-blocking and phospho-mimicking FIP200 mutations to test whether FIP200 is required for ULK2-mediated degradation of protein aggregates and sufficient to rescue the degradation of protein aggregates in aged muscles. This proposal is significant because it delineates a novel ULK2-FIP200 signaling pathway in muscle that may be targeted to preserve proteostasis, treat sarcopenia and extend healthspan.

NIH Research Projects · FY 2025 · 2024-09

PROJECT SUMMARY/ABSTRACT Approximately 20% of older adults in the United States have a voice disorder. One of the most common voice disorders in older adults is presbyphonia, related to changes in the larynx and respiratory system that occur with aging. Persons with presbyphonia have softer, weaker, rougher voices. As a result, they have a harder time communicating and participating in social activities. This can lead to adverse effects on social interaction, overall well-being, and cascade into loneliness, depression, and worse quality of life. While patients commonly report these challenges, the relationship between voice impairment and social interaction has not been adequately studied in older adults. We seek to further understand the impact of presbyphonia on social function and well-being. We hypothesize that older adults with presbyphonia will exhibit elevated social isolation and disconnectedness scores as compared to age-matched control participants without voice disorders. Furthermore, we hypothesize that social isolation and social disconnectedness scores will improve after participation in a voice therapy program specifically designed for older adults with presbyphonia, phonation resistance training exercises (PhoRTE). We will use validated social interaction and voice questionnaires, functional voice assessments, and structured interviews to gain a comprehensive understanding of how presbyphonia affects older adults and what effects participation in voice therapy may have on voice function and social interaction. Our proposed research is innovative as it provides a comprehensive characterization of voice from both functional and social perspectives. Our project is unique because we plan to employ a combination of validated patient-reported outcome measures, innovative voice acoustic analysis, aerodynamic parameters, perceptual voice analysis, and structured interviews with innovative recall technique (Photovoice) to better understand the impact of presbyphonia on social interaction and mood. There are very few studies have utilized Photovoice, which is a qualitative assessment tool where participants take photographs using a camera to document needs and concerns from their own viewpoints. This will enable us to understand our participants’ environments that they may not share during interview. An investigative team with expertise in speech pathology, laryngology, gerontology, qualitative interviewing, acoustic and aerodynamic analysis, and patient-reported outcomes has been assembled to strengthen the quality of the proposed research. This study is significant because it will improve our understanding of how voice disorders affect older adults from a comprehensive perspective. Given the importance of voice in social interaction, and the risks to general health that can occur with social isolation, characterizing this impact is clinically and scientifically valuable. Our work will be able to help a large population of older adults struggling with voice disorders.