Brown University

NSF Awards · FY 2024 · 2024-10

Wireless data traffic continues to grow at an exponential pace, demanding more and more bandwidth. Networks of the future will need to exploit frequencies above 100 gigahertz, which are much higher than what is typically employed today. These high frequencies need to propagate as narrow directional beams, rather than the wide- angle broadcasts currently used by base stations and cell towers. Using beams offers a number of important advantages, but also poses some significant challenges. One key challenge surrounds the question of how to adapt if the beam is blocked by an intervening obstruction between the transmitter and receiver, such as a person walking through the beam path. This research program explores a novel solution to this problem which relies on the generation of beams that follow a curved trajectory. Such beams can be generated in situations where the size of the transmitter is sufficiently large, with the appropriate engineering of the properties of the generated signal at all points across the emitting aperture. The use of such exotic beams in wireless communications is unprecedented, so many open questions must be explored in order to validate the feasibility. This work will open a new realm of possibilities for the implementation of local area networks operating at ultra-high frequencies. This project also includes a significant effort to broaden participation by under-represented groups, at the high school, undergraduate, and graduate levels. This research lays the foundations for the use of self-accelerating beams in mobile wireless local area networks (LANs) operating in the near-field regime. Since conventional link analysis cannot be applied in the near field of a transmitter, fundamental electromagnetic calculations are used to establish heuristic models for link budgets that can be employed to estimate the performance of such links, including a characterization of the effect of receiver aperture and of the near-field to far-field transition for various types of self-accelerating beams. Two different strategies are explored to create electrically reconfigurable metasurfaces that can be used to generate and manipulate such beams, which could be integrated into a transmitting base station for agile adaptation to transient blockage events. In addition, issues facing the control plane will also be explored, including the development of strategies for link discovery using beams with curved trajectories, and the implications of the asymmetry of the channel resulting from the fact that the receiver is in the near field of the transmitter but not vice versa. 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

Nervous systems are biological communication networks that use signaling molecules called neurotransmitters to transfer information critical to every facet of brain function. “Bilingual” neurons are neurons that release two types of neurotransmitters to communicate with other neurons. Co-transmission allows the brain to fine-tune responses with multiple messages, which increases the functional flexibility of the brain, allowing it to accurately respond to a continually changing environment appropriately. The increasing number of examples of “bilingual” neurons found in the brains of animals from flies to humans indicates this is a fundamental mechanism by which neurons communicate. Despite this functional significance, there is still only limited insight into how co-transmission is regulated within neurons, and how the social environment impacts neuron communication. In this proposal, the investigators will use the fruit fly, Drosophila, to identify mechanisms that regulate co-transmission and identify how these mechanisms are dynamically regulated by the animal’s social environment, in both females and males. The outcomes of this work include an in-depth understanding of how multiple neurotransmitters generate behavioral flexibility, and separately provide a potential neuroprotective role in response to a social isolation environment. The project will provide research experience to students in molecular and physiological techniques through training and mentoring. In this proposal, the investigators will leverage their deep understanding of behavior-promoting neurons, spatial transcriptomic approaches, and functional imaging to test the hypothesis that the molecular and physiological mechanisms that regulate co-transmission are themselves dynamically regulated by sex and state-dependent properties. The PIs will use cutting-edge techniques to examine how glutamate+/octopamine+ neurons in the Drosophila model system differ within a novel sex-specific context as well in response to state-dependent changes at the anatomical, transcriptomic and functional level. Specifically, the investigators will first address how the neural dynamics, neurotransmitter levels and distribution of glutamate and octopamine are impacted in the context of sexual dimorphism and the social isolation state. Second, they will identify transcriptional pathways that regulate glutamate or octopamine signaling through single nuclei RNA-seq and the spatial transcriptomics technology, Ex-seq. Laboratory settings are increasingly international and collaborative places, both in the university and in the global biotechnology industry. As a team the investigators are providing a collaborative and interactive training plan for their students to receive international instruction and mentoring, as well as learn new molecular and physiological techniques. Additional student education will occur through laboratory courses taught at Brown University and the University of Montana. Ultimately, this work will fill a large gap in our understanding of the regulation of co-transmission by identifying the rich assortment of communication capabilities that neurons possess in behaving animals. 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 advancing our understanding of how universities nationwide can improve support for science faculty instructors in providing accommodations for students with disabilities in their classes. While the process of providing formal accommodations in higher education classrooms is initiated by students and coordinated typically by a disability or accessibility center, the actual implementation of accommodations is highly dependent on faculty instructors. Because faculty at different institutions have different responsibilities, resources, and student bodies, the context of providing accommodations likely varies greatly by the type of institution. Additional variables including rising numbers of students with disabilities and an increased use of active learning and hybrid/remote instruction inevitably influences a faculty instructor's experiences and willingness to provide accommodations to students with disabilities. By identifying and understanding the factors that impact faculty instructor motivation to provide accommodations, this project aims to elicit needed information on how to support science faculty instructors in meeting the needs of undergraduate students with disabilities. This project plans to identify personal, institutional, and logistical factors that impact how science faculty instructors administer accommodations to students with disabilities. Because factors including class sizes, accessibility center resources, numbers of students who receive accommodations, faculty instructor responsibilities and expectations, and teaching support resources vary greatly by institution, this project will disaggregate findings by four different institution types (community colleges, primarily undergraduate institutions, comprehensive institutions, and research-intensive institutions). This project includes a nationwide interview study to identify how different factors impact a science faculty member's expected ability and value for the task of providing accommodations for students. To increase the generalizability of this work, the project plans to use findings from the interview study to inform development of three survey instruments, designed to measure science faculty's: (1) motivation to provide accommodations; (2) perceptions of the logistical, situational, and instrumental factors that impact student accommodations; and (2) personal knowledge of disability and accommodations. After instrument validation, the project plans to deploy the three survey instruments to science faculty at institutions nationwide. Data analysis will explore how different factors impact science faculty instructor's motivation and experiences with providing accommodations. Outcomes will be disseminated through publications, presentations, as well as videos, recorded talks and blog postings. 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.

NIH Research Projects · FY 2025 · 2024-09

PROJECT SUMMARY APOE4 is a major genetic risk factor for Alzheimer's Disease, which affects millions worldwide. In the United States, over 60% of Alzheimer's patients carry at least one APOE4 allele. Despite three decades of research, the absence of precision medicine targeting APOE4 remains a critical gap. Recent gene therapy breakthroughs, like mRNA vaccines and antisense oligonucleotide-based medicine, raise hope for APOE- focused Alzheimer's treatments. The APOE gene has three common alleles, E2, E3 and E4. APOE3 is the common allele, and it is not associated with susceptibility to Alzheimer’s Disease. APOE4 is the ancestral allele; although it is the susceptibility allele, its frequency has remained high suggesting potential selective advantages. APOE4 and APOE3 alleles are distinguished by a single base difference (C vs. T at SNP rs429358). APOE4 exhibits a dominant-like effect, elevating Alzheimer’s Disease risk in individuals with just one copy of the E4 allele. Even with intense searches for treatments, precision medicine for this devastating disease remains elusive. An incomplete understanding of the regulation of APOE expression and function may have contributed to this therapeutic gap. Precision therapeutics targeting APOE4 while minimizing side effects demand a comprehensive mechanistic understanding of APOE expression regulation and function. Our recent discovery of the enhancer RNA, APOE-activating noncoding RNA (AANCR) is a significant advance, shedding light on cell-type specific APOE expression and its stress responses. This discovery provides critical insights into APOE expression regulation and susceptibility to Alzheimer’s Disease. Our project aims to elucidate how AANCR regulates APOE transcription and how AANCR itself is modulated to maintain cell-type specific and stress-induced APOE expression. Notably, we observed APOE induction in the central nervous system during stress. To advance APOE- targeted interventions, understanding its stress-induced functions is imperative. In stress-activated astrocytes and microglia, we will assess how APOE expression and genotypes affect cellular function. Multiomic analyses will investigate cytokine levels, gene expression patterns, and lipid profiles to characterize the function of APOE. Subsequent co-culture experiments will assess the effects of APOE and these associated factors on neuronal health, including synaptic activity and survival. Leveraging our RNA, genetics, and neurobiology expertise, along with preliminary data, we are uniquely poised to address these critical knowledge gaps. Our project integrates a thorough understanding of APOE regulation in homeostasis and stress response with its broader implications on neuronal health. This dual focus is crucial for developing targeted, effective treatment for Alzheimer's Disease.

NIH Research Projects · FY 2026 · 2024-09

PROJECT ABSTRACT: Among people with HIV infection (PWH), hazardous drinking is a common, modifiable risk factor for cardiovascular disease (CVD) and death. Both alcohol and HIV cause gut dysbiosis. Gut dysbiosis is associated with systemic inflammation and harmful metabolites, each of which is associated with CVD and death. However, the specific bacterial shifts that drive dysbiosis and its harmful effects among PWH who drink are unclear. Our overarching model posits that alcohol associated gut dysbiosis leads to a reduction in specific species of butyrate-producing bacteria, lowering butyrate levels and increasing trimethylamine N-oxide (TMAO). These mechanisms contribute to microbial translocation and vascular inflammation. Ultimately, these processes promote CVD and excess mortality. This application leverages rich existing data from three fully harmonized NIAAA cohort studies (ACME HIV, U01AA026222; TMAO HIV, R01AA025859; META HIV, P01AA029542) in response to NOT-AA-23-011 requesting proposals for use of existing data and biospecimens in alcohol research. We hypothesize that alcohol associated gut dysbiosis will be characterized by reductions in butyrate-producing species (Aim 1); that reductions in these species will associate with increased levels of microbial translocation, inflammation, and harmful metabolites (Aim 2); and that reductions in butyrate-producing species will associate with greater subclinical CVD dysfunction, CVD risk, and mortality risk (Aim 3). Prior studies examining alcohol associated dysbiosis in PWH are limited in two major ways: (1) they rely on 16S characterization of the gut microbiome, which cannot provide granular (i.e., species level) data; or (2) they employ whole genome sequencing (WGS) to collect species level data, but only in small samples. Our application is innovative because it addresses both limitations by utilizing WGS in three existing, fully harmonized NIAAA-funded studies involving 583 PWH who consume alcohol with >1700 longitudinal fecal specimens. Extant data include alcohol measures (AUDIT; Timeline Followback, TLFB; phosphatidyl ethanol, PEth), stored serum/plasma and fecal samples, 16S gut microbiome data, and serum biomarkers for metabolites (e.g., TMAO), microbial translocation (e.g., LBP), inflammation (e.g., IL-6), VACS Index (mortality) and Reynolds Risk (CVD) scores, and echocardiograms. New data to be generated are WGS on all fecal samples from the three studies. Specific Aims are as follows: Aim 1: To characterize alcohol associated dysbiosis using WGS, employing longitudinal fecal specimens. Aim 2: To test the relations of the gut microbiome at species/strain-level with markers of microbial translocation, inflammation, and harmful metabolites. Aim 3: To test the association of species/strain-level changes in butyrate-producing and other gut bacteria with subclinical CVD markers, CVD risk, and mortality risk. IMPACT: Precision medicine approaches utilizing gut microbiota profiles at the species level can be leveraged into novel interventions to mitigate harmful downstream health effects of alcohol (i.e., inflammation, CVD, mortality risk) in PWH.

NIH Research Projects · FY 2025 · 2024-09

SUMMARY/ABSTRACT While there have been developments in treatments for alcohol use disorder (AUD), current pharmacotherapies face several limitations, including the presence of adverse events. Intranasal (IN) insulin has shown promise for use in targeting addictive disorders. The overarching hypothesis of this proposal is based on the premise that IN insulin by providing improvement of brain cell energy and glucose metabolism and stress hormone reduction, may be an ideal approach for treating multiple domains of AUD including memory and impulsivity. Furthermore, studies of IN insulin demonstrate that it is a safe and effective method for delivering insulin to the central nervous system, circumventing the blood brain barrier and reducing adverse events (hypoglycemia). The main goal of this proposed work is to tune up and test an integrated pharmacological, biobehavioral and clinical protocol to test the safety/tolerability of IN insulin as a potential therapeutic for AUD. This is a Phase I/IIa, within-subject, crossover, double-blind, placebo-controlled human laboratory study with an acute IN insulin (80IU) administration compared to placebo in 40 non-treatment-seeking individuals with AUD. In Aim 1, we assess the safety, tolerability and acceptability of IN insulin as pharmacological intervention for AUD. In Aim 2, we evaluate whether there is a difference in adverse events between IN insulin and the placebo condition when co-administered with alcohol. In Aim 3, we will evaluate whether IN insulin, compared to placebo, improves memory and reduce impulsivity after the alcohol challenge. Finally, in Exploratory Aim, we will assess preliminary data on the effect of IN insulin, compare to placebo on alcohol craving. The proposed research will generate: 1) the necessary safety data and 2) the characterization of AUD patient endophenotype who may respond to IN insulin treatment.

NIH Research Projects · FY 2024 · 2024-09

PROJECT SUMMARY Antibiotic-induced disruption (AID) of the gut microbiome can lead to severe conditions like C. diff colitis and may contribute to long-term health issues, including obesity and diabetes. There is an urgent need to develop interventions that mitigate these negative impacts while preserving the antibiotics' effectiveness. Our preliminary data suggest that dietary fiber reduces antibiotic disruption by decreasing the gut's redox potential, which in turn favors a low-energy, fermentative metabolic environment. This environment protects core microbiome members by reducing their metabolic rate and ATP production, which are linked to antibiotic susceptibility. In Aim 1, we will use an ex vivo microbiome culture approach to test endogenous redox sinks and small molecule regulators of bacterial redox as modulators of AID and determine the influence of these modulators on microbiome resilience, recovery, and pathobiont susceptibility. This research aims to identify mechanisms that can be translated into therapies for protecting the microbiome during antibiotic treatment, particularly for vulnerable populations.

NIH Research Projects · FY 2024 · 2024-09

Extreme temperature, humidity, and particulate air pollution are threats to human health, the frequency of intense exposure to these threats is increasing, and their combination particularly impacts aging populations and those with chronic health conditions. To combat these challenges, we propose establishing a new center at Brown University, “Climate, Health, and Aging Innovation and Research Solutions for Communities (CHAIRS- C),” to advance science on the adverse health implications of climate events and develop actionable solutions to promote healthy aging for all. CHAIRS-C will be comprised of an Administrative Core, Research Project, Capacity Building Core, and Community Engagement Core, all designed to efficiently bring together a breadth of existing and emerging climate and aging research with critical community partners. The long-term objectives of CHAIRS-C are to enhance relationships between Brown University and community partners and strengthen interdisciplinary research among existing campus-based units. CHAIRS-C intends to be a national leader in understanding the impacts of climate change on older adults and proposing innovative interventions to mitigate these harmful effects. To achieve these long-term objectives, CHAIRS-C has identified the following specific aims: 1) Strengthening and expanding multi-directional engagement of academic, community-led, and governmental partners around climate-related risks and accessible mitigations for aging populations; 2) Developing new capacity for transdisciplinary research and community engagement in climate and health through shared learning experiences, focused on aging populations; and 3) Sharing findings from best- available exposure modeling and place-based health datasets with community and governmental partners to stimulate actionable, localized responses, particularly for high-risk subgroups facing disparities. The basic tenet of CHAIRS-C is that innovative solutions require partnerships between communities and researchers to generate the appropriate evidence and political will to guide effective and efficient solutions. Neither research nor community action is effective alone. To mitigate the adverse implications of climate change, we must collaborate. CHAIRS-C will merge these approaches to benefit older adults, setting a new standard that will be applicable to other populations facing inequity and health threats related to climate change.

NIH Research Projects · FY 2024 · 2024-09

PROJECT SUMMARY / ABSTRACT As the overall prevalence of mild cognitive impairment (MCI) and Alzheimer’s disease and related dementias (ADRD) grows, there is an urgent need to improve diagnosis rates and identify people earlier in their disease process. An early diagnosis could not only help implement timely measures to reduce or prevent further progression, but also help individuals and families prepare for future financial and care needs. This work aims to gain a better understanding of the individual- and system-level characteristics that influence diagnosis, alongside local culture and practice, and how diagnosis can moderate the effects of cognitive decline and its impact on employment, future care, and quality of life. Our first aim examines whether older adults experiencing cognitive decline during their working life are more likely to experience an earlier, unplanned exit from the workforce than individuals who do not experience cognitive decline. Making use of harmonized, longitudinal survey data across countries, we examine the cognitive and employment trajectories of older adults (born in 1931-1960) from the US, England, and 28 European countries, first observing these individuals during employment age and following them throughout working life and after labor force exit. Our second aim uses linked survey and claims data to assess the concordance between harmonized, survey-based cognitive tests and claims-based diagnosis of MCI and ADRD in the US and six other high-income countries with different approaches to detection. Our analysis of how concordance/discordance in dementia prevalence varies across countries and over time, and for which populations, can help identify scope for cross-country learning. Our third aim is to develop communication-efficient, federated learning algorithms for counterfactual analyses to quantify the relationship between individual characteristics and time to diagnosis and institutionalization across populations in US and peer countries, all the while ensuring strict adherence to each country’s data protection principles. Ultimately, our project aims to leverage longitudinal, harmonized, patient- level data across high-income countries to compare health outcomes for older adults, to gain a comprehensive understanding of the effects of cognitive decline on employment for older adults, and to inform policies related to the detection and care of MCI and ADRD.

NIH Research Projects · FY 2024 · 2024-09

Project Summary Women with racial and ethnic minority identities, specifically Hispanic and Black women exhibit suboptimal physical activity-related behaviors and are disproportionately burdened by obesity and physical-activity related chronic diseases. Mothers often report too many responsibilities and prioritizing their children’s needs and extracurricular activities as barriers to engaging in more physical activity. The proposed study builds on our team’s previous work adapting an evidence-based theory guided physical activity intervention and pilot testing it in a community setting mothers regularly spend time for their children’s extracurricular activities, circumventing this barrier. This innovative intervention, named Moms on the Move, is the first of its kind and additionally circumvents access, transportation, and childcare barriers, which are also commonly cited, especially by low-income and racial and ethnic minority mothers. Given results from our pilot study demonstrating feasibility and acceptability, we aim to conduct a fully powered cluster randomized trial with a waitlist control of the Moms on the Move intervention. We will partner with eight youth football and cheerleading organiza�ons that predominantly serve low-income Hispanic and Black families to carry out the study. Our primary aim is to test the efficacy of the intervention for increasing moderate to vigorous physical activity. We will also test the efficacy of the intervention for physical activity maintenance and examine mediators and moderators of efficacy as exploratory aims. If found to be effective in increasing physical activity, the intervention has the potential for widespread dissemination. This study, along with the diversity statement and Plan for Enhancing Diverse Perspectives (PEDP) demonstrate the PI’s commitment to Diversity, Equity, Inclusion, and Accessibility (DEIA).

NIH Research Projects · FY 2024 · 2024-09

PROJECT SUMMARY/ABSTRACT This is a study of neighborhood change and its impacts on trends in Black-white segregation over a multi-decade time span. It will provide much new information about settlement patterns that continue to impact residents’ health, social class mobility, and quality of daily life. It will trace changes in population composition at the neighborhood scale within constant geographic boundaries and evaluate how different patterns of neighborhood change contributed to increasing or declining segregation in the larger urban area. It will compare the period 1930-1950, 1950-1980, and after 1980. An important contribution of this project is to develop a neighborhood-scale data base with consistent boundaries over time for multiple decades to support the proposed analyses. It will use methods developed for the Longitudinal Tract Data Base (LTDB) for 1970-2020 and the Urban Transition HGIS Project (1880-1940). A major effort will be to incorporate data and map sources that are now becoming available. The project will develop harmonized neighborhood data for 69 major cities for 1930-1950 and for them plus their surrounding suburbs for 1950-2020, making possible detailed studies of suburban development after World War II.

NSF Awards · FY 2024 · 2024-09

This project supports planning for a new Center on Clean Energy and Society (CES). The goal of the project is to investigate the social, political, and behavioral processes relevant to scaling up clean energy infrastructure in the United States and around the world. The planning grant supports organizational activities over a two-year period including interdisciplinary meetings to identify key research on the societal aspects of clean energy development; a synthesis of existing research on clean energy and society; and an outreach meeting with relevant stakeholders. The approval of solar and wind energy projects is a complicated process involving numerous actors and stakeholders at a range of spatial scales. Institutional factors play an especially key role in energy infrastructure development. This planning project supports the development of a human-centered approach to the reliable, affordable, equitable, and effective solutions needed for clean energy development. This project investigates the social and institutional processes of clean energy development. The research project particularly investigates under what conditions does support for a clean energy economy materialize, and whether clean energy development boosts community resilience, energy reliability, and national security. The benefits and the costs of rolling out clean energy fall unequally to different people along lines of income and racial diversity. The proposed CES Center addresses these challenges, and the organizational activities supported by this planning grant lay the groundwork for a broader research program tackling these questions. Ultimately, the goal of this work is to generate knowledge to understand the complex mechanisms grounding the societal dimensions of clean energy development. This involves identifying various social, political, and institutional barriers to clean energy and assessing the effectiveness of various strategies to surmount those barriers. 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 · 2024-09

Everything in biology is connected. Our job as life scientists is to reveal important biological properties in the most impactful, efficient, and economical way. To do so we look for model organisms that are particularly tractable for studying complex biological processes and then apply what we learn to better understand other organisms. For more than a century, sea urchins have provided a valuable research model that has contributed significantly to our understanding of many fundamental biological processes such as fertilization, embryonic development, and cell division. Sea urchins have proven to be a valuable model due to their close genetic relationship to vertebrate animals and many features that make experimentation easier. The goal of this proposal is to create the next generation of tools to enhance the utility of sea urchins as research models that will enable new areas of research and to make these tools widely available to the scientific community. Areas of biological research to be enhanced by the tools created from this proposal include a better understanding of how eggs and sperm interact at fertilization, understanding the rules of embryo development, how nerve cells are made, how sex is determined, how animals protect themselves from environmental insults and from infection, and how tissues and organs can regenerate when they are damaged. The outcomes of this proposal will reach far beyond the scientists, to the public, students and teachers and make the sea urchin a highly attractive and impactful research and education tool of the twenty-first century. Sea urchin researchers have long sought to leverage the experimental tractability of the embryo and adult with genetic approaches but, to date, manipulations have been limited largely to dependence on morpholinos or pharmacology. The overarching goal of this EDGE proposal is to build tools that overcome major obstacles to testing gene functionality in echinoderms, opening up a new era of discovery for diverse and integrated studies across all life history stages of this valuable sister group to chordates. This goal will be realized as follows: (1) Simple and efficient protocols for culturing cells from embryos to investigate gene function in vitro; (2) Rapid, scalable DNA transfection of embryos, adult tissues, and cell cultures for conditional, and reversible gene control; (3) Techniques to promote standardization of sea urchin husbandry with open hardware and cryopreservation for sea urchin germplasm and cell lines; (4) Virtual, interactive educational materials to reach secondary school and undergraduate students and investigators learning from and even considering entering this research community. These integrated new technologies with controlled and heritable genetic manipulations and the ability to test gene function and regulation in in vitro cell-based systems will enable new avenues of investigation that fully exploit the important properties of echinoderms as a research organism. The tools developed in this proposal will remove the bottlenecks and provide scalable and sustainable resources for the community of echinoderm researchers. The proposal was funded by the Enabling Discovery through GEnomics (EDGE) program and the Developmental Systems Cluster in the Division of Integrative Organismal Systems. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NIH Research Projects · FY 2024 · 2024-09

PROJECT SUMMARY Socioeconomically disadvantaged young adults (SDYA) are at a disproportionately greater risk of tobacco- related illness and disease compared to non-disadvantaged young adults in the U.S. Given that quitting smoking before age 30 reduces almost all of the mortality associated with ever smoking, understanding predictors of smoking cessation and relapse in SDYA who smoke is critical to preventing the escalation and continuation of tobacco use in this high-risk group. SDYA who smoke and are transitioning into young adulthood are vulnerable to experiencing a wide range of social-contextual stressors (e.g., financial stress), which can interfere with their motivation to quit and cessation efforts. In line with NIDA’s strategic plans to understand “how social determinants of health increase or decrease risk for addiction over the lifespan,” this MOSAIC K99/R00 grant application aims to provide empirical evidence on the social-contextual predictors of smoking cessation in SDYA who smoke. Social-contextual stressors may be dynamic in nature and vary daily or moment-to-moment. To understand how day-to-day changes in social-contextual stressors affect smoking cessation in SDYA, we propose to combine: a) qualitative interviews focused on the lived experiences of SDYA who smoke to better understand how specific social-contextual stressors are experienced in daily life with b) EMA of these stressors in a real-time, naturalistic environment. The specific aims of the K99 phase are to: 1) gain an in-depth understanding of how social- contextual stressors impact smoking cessation and relapse among SDYA who smoke and attempt to quit smoking in the natural environment; and 2) develop and evaluate the acceptability and feasibility of an EMA protocol. To achieve these aims, a mixed methods approach (qualitative interviews with 30-40 SDYA ages 18- 25 who smoke and previously tried to quit; a pilot EMA study and exit interviews with 15 SDYA who smoke) will be used to refine a protocol for a full EMA study. The R00 phase will include a larger-scale EMA study that will assess the impact of social-contextual stressors on psychopharmacological mechanisms of smoking cessation and relapse experienced at the event-level in 100 SDYA who smoke and are willing to make a serious quit attempt in the next 30 days. The PI, Dr. Mariel Bello, will work with an exceptional team of mentors (Drs. Rachel Cassidy, Suzanne Colby, Jennifer Merrill, Tim Janssen, and Andrea Villanti) to develop expertise in five areas of training: 1) mixed methods research (qualitative + EMA); 2) EMA methodology; 3) intensive longitudinal data analysis; 4) community-engaged research approaches; and 5) professional development skills. Successful completion of the research and training objectives detailed in this proposal will prepare Dr. Mariel Bello for a successful transition to independent faculty researcher, as well as further develop her program of research focused on investigating the etiology and underlying mechanisms of tobacco-related health disparities among marginalized groups. Findings will provide initial evidence on how event-level characteristics lead to smoking relapse in SDYA, which will serve as preliminary data for future R01 applications. 1

NIH Research Projects · FY 2025 · 2024-09

Project Summary Infectious disease is a leading cause of global morbidity and mortality. Transmission dynamic models have played a critical role in guiding interventions related to many infectious pathogens, including HIV, influenza, SARS-CoV-1, ebolaviruses, SARS-CoV-2, and mpox. Models project how potential interventions (e.g., non- pharmaceutical measures, therapeutics, and vaccines) may affect disease future transmission. However, they often rely on small scale studies to project effects, and there have been growing concerns that models may produce inaccurate, overly optimistic estimates of population-level intervention effectiveness. Observational causal inference models, which measure intervention effectiveness in real-world settings, could help address this limitation, but applying these to infectious disease is not straightforward. Observational approaches, such as difference-in-differences and synthetic control methods, estimate the impact of an intervention based on empirical counterfactuals: comparing outcomes of interest between treated units or places and similar untreated units. While well-understood with linear outcomes, they can produce biased and misleading results in the context of nonlinear transmission dynamics. Even where observational models perform well, it further remains challenging to transport estimates to new settings to project the impact of future interventions. To address these issues, this project will develop comprehensive theoretical architecture for synthesizing transmission dynamic models with observational causal inference models – employing empirical counterfactuals while accounting for complex biological and population dynamics. In the retrospective workstream, I will propose robust specifications for observational causal inference models that can estimate unbiased treatment effects in policy evaluations using infectious disease outcomes. I will also develop model selection and decision-analytic methods to address potentially significant parameter uncertainty. In the prospective workstream, I will develop approaches to generalize estimates from observational causal inference models to new settings using transmission dynamic models and update projected effects in real-time based on local surveillance indicators. I will illustrate the implications of our methods by re-analyzing prior studies on COVID-19 as well as applying them to answer new questions about respiratory illness control, in collaboration with partners in state and local public health institutions. Across both workstreams, I will develop and disseminate open-source public tools and software to facilitate adoption of these methods. Overall, this work will produce a suite of methodological innovations to improve understanding of the impact of past policies and the accuracy of future projections, while also supporting their implementation in public health institutions to guide planning and priority setting.

NIH Research Projects · FY 2025 · 2024-09

PROJECT SUMMARY/ABSTRACT Clinical recommendations for the management of diseases are mostly based on the average treatment effects observed in randomized controlled trials. However, the beneficial effects of most treatments vary across individuals. Identifying the factors contributing to treatment response heterogeneity is crucial for improving mechanistic understanding of treatment-disease interactions and optimizing patient outcomes. Recent advances in high-throughput technologies in biology and the development of large-scale databases provide an unprecedented opportunity for a more comprehensive understanding of mechanisms underlying inter-individual variations in treatment responses. Several methods, including subgroup analyses and summary score-based analyses, have been used to assess treatment response heterogeneity. To handle the high dimensionality of covariates, machine learning methods have also been developed to assess treatment heterogeneity. However, despite tremendous advancements in machine learning, two key limitations have hindered a large-scale deployment of the current methods to discover markers underpinning treatment heterogeneity from big data. First, the current approaches can fail to uncover strong but unexpected predictors of treatment response heterogeneity. A key problem is that counterfactual treatment responses for an individual under two possible strategies cannot be directly identified. To make progress, a common approach is to compare the average observed treatment responses across subgroups of individuals, defined either based on one or multiple clinical variables. Nonetheless, such approaches can fail to uncover true signatures for treatment heterogeneity. Second, the current methods for predicting treatment heterogeneity often result in models with limited generalizability. A key reason is that participants in the source population data (on which models are developed) are not a random sample from the target population (on which models will be deployed). When the source population data are not representative of the target population and treatment responses vary across factors that influence participation, algorithms that can tailor the model for use in the new target population will require cutting-edge tools in data science. To address these challenges, we propose novel causal machine learning methods that will enable the identification of markers (and their complex relationships) for individual treatment responses, with algorithms adaptable to a new target population. This project will combine theoretical developments with large-scale simulation studies and empirical evaluations on treatment for patients with stable coronary artery diseases. Successful completion of the proposed research will equip investigators with powerful methods to unlock the full potential of big data, advance our understanding of mechanisms for treatment response heterogeneity, and ultimately improve strategies for preventing and managing a wide range of health conditions and diseases.

NIH Research Projects · FY 2024 · 2024-09

Project Summary A key function of the nervous system is to transform sensory information from the environment into actionable percepts. In a classic hierarchical representation framework, signals from peripheral receptor neurons with simple tuning properties are transformed in primary sensory cortex to represent sensory objects. However, recent data suggest that neural activity in primary sensory cortex strongly correlates with behavior, and that sensory representations undergo large scale changes over time. We here test the hypotheses that behavioral tuning of neurons in the olfactory (piriform) cortex supports the ability to filter out signals predicted by behavior, and that coupling odor exposure to behavior stabilizes representational drift. Olfaction is an ideal model system to study sensory-behavior interactions. Mice exhibit a rich repertoire of olfactory-driven behaviors, including behaviors critical for survival and reproduction, and piriform cortex receives direct sensory inputs from the olfactory bulb and is reciprocally interconnected with higher cognitive and motor areas. We have implemented state-of-the-art experimental approaches to chronically record piriform neural activity while synchronously monitoring behaviors. Our preliminary data suggests that sniffing, facial movements, and locomotion can strongly modulate piriform neuronal activity. Aim 1: To determine whether behavioral signals in piriform cortex subserve predictive processingWe will combine two-photon calcium imaging in head-fixed mice with detailed behavioral monitoring of sniffing, facial movements including whisking, and locomotion, and we will quantify the extent to which piriform odor responses differ across spontaneously occurring behavioral states. We will then use a closed-loop experimental design to directly test whether behavioral signals in piriform cortex serve to filter out expected sensory information. We predict that neuronal responses to behaviorally coupled odors will decrease over time, while responses to behaviorally uncoupled odors will remain unaltered. Aim 2: To determine whether representational drift in piriform cortex is explained by behavioral change. We will quantify the stability of odor representations in piriform cortex, and we will test the extent to which changes in odor tuning (representational drift) can be explained by changes in behavioral state. We predict that representations of odors that consistently occur during defined behavioral states remain stable over time, while responses to behaviorally uncoupled odors will drift. Successful completion of the proposed project will provide new insight into how animal behavior shapes olfactory processing and the generation of odor representations in the mammalian cortex. Our studies will set the stage for future projects aimed at characterizing the neural circuit mechanisms underlying complex odor-behavior representations in the olfactory cortex, and the investigation of complex olfactory-driven behaviors in freely moving mice in naturalistic environments.

NIH Research Projects · FY 2024 · 2024-09

PROJECT ABSTRACT This application proposes to examine where and for whom rural residence is associated with Alzheimer’s disease and Alzheimer’s disease-related dementias (AD/ADRD) in the United States. Analyses will 1) produce novel and robust estimates of dementia prevalence in rural and urban America; and 2) characterize the types of rural places and people most affected by dementia. This research is motivated by growing concerns for the health of rural Americans, roughly 46 million people and 14% of the U.S population. Rural Americans have had poorer health profiles than their urban peers since at least the 1980s, and the gap has widened over time. Yet surprisingly little is known about rural-urban disparities in dementia, which is poised to become one of the most significant population health challenges of the century. Dementia currently affects approximately 6.1 million or 11% of Americans ages 65 and older, and numbers are expected to rise dramatically in the coming decades due to population aging. The challenges associated with dementia may be especially severe in rural communities, where access to quality healthcare and other services for people with dementia and their caregivers is often severely limited. To anticipate and plan for the challenges associated with dementia, its patterning across places and people must be understood. However, demographic estimates of dementia prevalence in rural and urban America are lacking, even at the national level. Moreover, it remains unknown how the prevalence of dementia varies among rural places and people, despite the fact that rural America is not monolithic. The proposed project will therefore develop a demographic overview of rural-urban dementia disparities, including novel analyses of heterogeneity across places (Aim 1) and people (Aim 2). In particular, Aims will explore variation in dementia prevalence at the intersections of rural residence and regional setting (Aim 1a), county context and composition (Aim 1b), and individual-level sociodemographic characteristics (Aim 2). Analyses will be conducted with data from the Health and Retirement Study, a nationally representative survey of older U.S. adults. This application, led by an early-stage investigator, responds to PAR-23-179, which encourages applications generating scientific insights about AD/ADRD, including estimates of disparities, from early-stage investigators and established researchers new to the study of AD/ADRD.

NSF Awards · FY 2024 · 2024-09

With the support of the Chemical Catalysis program in the Division of Chemistry, Professor Eunsuk Kim of Brown University will study new ways to manipulate sulfur in chemical reactions. Sulfur compounds are among the most common and problematic impurities found in crude oil. Their removal is a crucial step in the refining process, necessary to prevent the generation of environmentally harmful products during petroleum combustion, which consumes considerable energy and resources. Conversely, sulfur is a prevalent element in many FDA-approved drugs, highlighting its value in organic synthesis. The project will focus on developing a new class of catalysts capable of efficiently inserting sulfur into molecules or removing it without damaging the remaining parts. It will also train the next generation of scientists, and foster collaboration across different areas of chemistry. Participants will gain valuable research experience applicable to the energy and pharmaceutical industries. Moreover, the program will promote diversity in STEM fields through mentoring underrepresented minorities and female scientists and creating educational materials to inspire future generations. This project will develop a novel class of responsive sulfur atom transfer (SAT) catalysts that are oxidatively stable and have self-repairing capabilities during catalysis. Two groups of molybdenum-containing catalysts, supported by tridentate and tetradentate ligands, will be systematically synthesized, and their catalytic activities will be compared. The reaction mechanisms will also be investigated. The first group of catalysts, supported by a tridentate ligand frame, is responsive, activating only when suitable substrates are present. The second group, supported by a tetradentate ligand frame, exists in equilibrium between active and dormant forms. The presence or absence of the substrate can shift this equilibrium, functioning like a buffer system. In both cases, unintentionally oxidized catalysts can be regenerated in situ via oxygen atom transfer (OAT) reactions, owing to the catalysts’ unique dual catalytic capability for both OAT and SAT. The catalysts developed from this project will be air-stable and effective under mild conditions, creating an immediate impact in the field of synthetic chemistry. The findings will also have broad applications in both the petroleum and pharmaceutical industries. 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 · 2024-09

The signals that animals use to communicate with each other are critical to life, mediating a wide range of social interactions that determine whether individuals live or die, find mates, and compete for opportunities to breed. One of the most spectacular features of animal signals is that they are remarkably diverse, with each species appearing to evolve its own unique set of ornaments and displays. Understanding how these different signals evolve and diversify is a longstanding goal of organismal biology, yet this topic remains mysterious in several ways. We know, for example, very little about how the brain influences the process of social signal evolution. In this IRES project, undergraduate students from around the U.S. will be trained to conduct research that addresses this major knowledge gap. Student participants work with a group of international PIs, who together use integrative approaches to study the evolution and control of animal communication behavior. Study locations include Austria and India, where participants work for a 10-week period during the summer. Research activities center around both laboratory and field experiments that are performed in groups and through independent research projects. Their experience abroad is bookended by pre- and post-travel training to help prepare the participants with appropriate technical and cultural acumen to successfully complete their projects. Students also receive professional development throughout the entire experience, and they will work throughout the summer to help construct conservation exhibits for the local zoo in Vienna, Austria. In this way, the program focuses not only on building research and outreach skills, but also cultivating international proficiency and awareness. Our program fulfills the goals of the IRES program by producing college graduates who are ready to join the global STEM workforce in the 21st century. International collaboration is a critical part of ecology and evolutionary biology, driving major discoveries about the principles of life on Earth. Yet, undergraduate students from the U.S. often encounter hurdles that prevent them from engaging in such collaborative research. This is a problem because it means that our undergraduate population may be underprepared to join the modern STEM workforce, particularly in areas of ecology and evolution. The current research project aims to develop a program that addresses this problem by annually involving 6 undergraduate students from around the US and 1 graduate student in mentored research projects in both Austria and India. The program will last 10 weeks in the summer, and student participants will conduct work that explores how neural systems influence the evolution of elaborate visual displays in frogs. Students will work independently, as well as in large teams, to investigate: 1) how adaptive cognitive traits drive display evolution, and 2) how motor circuits in the spinal cord co-evolve with display diversification. All work will be done in the laboratory and field alongside mentors from the host countries. Thus, student participants are given the chance to not only address fundamental questions in animal communication, but to do so in an international context that helps prepare them for STEM careers in a global landscape. 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 Many older adults who are hospitalized for heart failure (HF) lose their ability to independently perform activities of daily living and then require long-term custodial care in a nursing home—an outcome that many seniors fear more than death. Yet, research to date on post-hospitalization outcomes has focused on readmission and mortality, and has overlooked important patient-centered outcomes like functional recovery and return to one’s own home. Understanding which factors promote functional recovery is critically necessary. Medications are one of the most easily modifiable potential factors, yet their effects on functional recovery are not well-understood. Thus, the overarching objective of this proposal is to examine the impact of medications on functional recovery and successful transition back to home following a HF hospitalization. The proposed research will focus on older adults discharged to a skilled nursing facility (SNF) after HF hospitalization because: 1) nearly one in five patients require SNF care following HF hospitalization; and 2) patients requiring SNF care are most vulnerable to prolonged functional impairment, loss of independence, and the need for long-term custodial care. The central hypothesis is that many commonly prescribed medications may impair participation in rehabilitation, interfere with functional recovery, and/or decrease the likelihood of successful discharge to home from SNFs. This hypothesis will be tested through three specific aims employing a series of rigorous observational studies: Aim 1, Estimate the effects of HF-specific and other medications administered in SNFs, including dose and duration, on function and successful discharge to home after HF hospitalization (outcomes), and examine potential mediators like rehabilitation minutes and cognition; Aim 2, Develop a novel risk score for the cumulative effects of harmful medications that interfere with function and successful discharge to home after HF hospitalization, and validate its predictive performance for key outcomes and mediators; Aim 3, Quantify individual medication and cumulative medication burden effects on function and successful discharge to home across important pre- defined subgroups of older adults with HF, including by dementia status and varying degrees of frailty, multimorbidity, and polypharmacy. To accomplish the three proposed aims, a large innovative database of SNF electronic health record information will be leveraged along with national Minimum Data Set 3.0 clinical assessment records, Medicare claims, Veterans Health Administration data, and other unique datasets. The proposed research is highly significant because it will provide foundational evidence for developing interventions to optimize medication use patterns (via prescribing and deprescribing) and subsequently facilitate functional recovery after HF hospitalization. This research directly addresses the National Institute on Aging's Strategic Goal C to improve the safe use of medications.

NSF Awards · FY 2024 · 2024-09

Algebraic geometry is the study of spaces that can be described as solution sets of systems of polynomial equations. Circles, parabolae, and hyperbolae are all examples, from classical plane geometry, of shapes which are governed by defining polynomials, in these cases polynomials in two variables. In algebraic geometry, the deep connection between algebra (the defining polynomials) and geometry (the resulting shape) is key. Both recently and over the past century, a large effort has been focused on the study of some very particular spaces of long-standing interest, called moduli spaces, of curves and abelian varieties. These are parameter spaces for certain kinds of geometric objects, and they have deep connections throughout geometry, as well as to mathematical physics and combinatorics. This project will develop and employ modern techniques to make new progress on the study of such spaces. The project will also provide research training opportunities for students. This research program is centered on compactifications of moduli spaces and their tropicalizations, i.e., the instantiations of these moduli spaces in the field of tropical geometry. The project uses tropical moduli spaces, which are certain polyhedral complexes, as a geometric instantiation of the boundary combinatorics of an appropriately compactified moduli space. The existence of the tropical space allows the application of combinatorial-geometric techniques, as well as connections to the study of the cohomology of arithmetic groups. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NIH Research Projects · FY 2025 · 2024-09

Project Summary/Abstract Human beings have a remarkable capacity for exerting cognitive control to achieve their goals, even though performing such tasks can be stressful (e.g., getting into college, landing a job or promotion). Although the ability to exert cognitive control to achieve goals in the face of ongoing stress is highly significant for determining one’s productivity, health, and well-being, the neurocomputational mechanisms by which cognitive control is evaluated are poorly understood. Recent research suggests that people consider the controllability of a sustained stressor in deciding how to strategically allocate mental effort, yet how people perform this strategic adjustment is unclear. Whereas substantial research has examined how acute stress (e.g., cold pressor) influences mental effort, less is known about how the contingencies of sustained stress (e.g., ongoing controllable vs. uncontrollable shocks) drive different strategies for mental effort allocation (e.g., attentional focus or response caution). This proposal will investigate the serotonergic influence on neural and computational processes that underlie how individuals exert mental effort in the face of sustained and uncontrollable stressors (shock). I will leverage our novel Stressor Controllability and Cognitive Control (SCCC) model, psychopharmacology, and pharmaco-fMRI to identify these neurocomputational mechanisms and test whether serotonin interacts with the aversiveness and controllability of ongoing stressors to bias distinct effort strategies for control allocation. Aim 1 (K99) will use the SCCC model to generate predictions for how sustained stressors guide different effort strategies (e.g., focus vs. caution) and identify separate sub-processes that reflect the (1) aversiveness and (2) controllability of sustained stressors during these decisions. Aim 2 (K99) will use a pharmacological probe (escitalopram) to test if controllability is a key factor determining when and how SSRIs are effective in modulating strategic goal-directed adjustments in mental effort allocation. Aim 3 (R00) will use pharmaco-fMRI to investigate to what extent distinct brain networks (e.g., dorsal vs. ventral medial prefrontal cortex) underlie stressor controllability and cognitive control, and localize serotonin influences in neural pathways. These Specific Aims support the applicant’s training goals (computational modeling of stress/affect, psychopharmacology). The training plan includes various workshops, courses, and guided readings to help the applicant gain the expertise to conduct trailblazing research on stress and cognitive control as an independent investigator. The intellectual environment at Brown is rich and highly interdisciplinary. The applicant will benefit from frequent interactions with world-renowned faculty with substantial expertise in topics related to the proposed research (e.g., computational modeling of stress, affect, and cognitive control). Understanding the computations, networks, and neurotransmitter systems through which sustained stressors guide mental effort will inform how disrupted neural networks give rise to motivational impairments (e.g., apathy, amotivation). Clarifying the role of serotonin in stressor controllability and mental effort is significant and can help understand why and when people are vulnerable vs. resilient to stressors in psychiatric disorders.

NIH Research Projects · FY 2025 · 2024-09

PROJECT SUMMARY The US opioid crisis has been worsened by the emergence of fentanyl adulterated or associated with the veterinary sedative xylazine (FAAX). Designated by the White House as an “emerging threat to the US” in 2023, FAAX exacerbates overdose risk, contributes to severe skin wounds, and is associated with withdrawal. Naloxone, an opioid antagonist, does not directly reverse xylazine’s sedative effect, exacerbating overdose risk. Our understanding of how FAAX-related skin wounds appear and are treated is limited, but the effects of these wounds are profound. Moreover, withdrawal from FAAX and its effect on medication for opioid use disorder, the treatment of choice for opioid use disorder, is unknown. Further, there is no widely available point-of-care test for xylazine to inform real-time clinical practice, limiting our ability to link those exposed to FAAX to treatment. Recognizing the absence of a widely available point-of-care test, the long-term objective of this proposal is to develop a rule-based natural language processing (NLP) algorithm to identify FAAX-exposed patients. To achieve this, the applicant proposes an exploratory, sequential, mixed methods study that builds upon his formative research. Approximately 20-24 in-depth interviews with people who use drugs (PWUD) exposed to FAAX in Rhode Island (RI) will be conducted to explore FAAX-related overdose, skin wounds, withdrawal experiences, and self-treatment (AIM 1). Then, 8-10 key informant interviews with medical providers in RI to PWUD exposed to FAAX will be conducted to understand emergent FAAX treatment practices and iteratively refine a vocabulary list of FAAX symptom descriptions (i.e., NLP dictionary) following a modified Delphi approach (AIM 2A). Then, we will apply the NLP dictionary via an NLP algorithm to the free-text electronic health records of ~24,000 patients (≥18 years old & opioid or injection drug use diagnostic code) who received emergency department care between 2015-2023 from a RI health system to identify patients exposed to FAAX (AIM 2B). This fellowship will advance the applicant’s expertise beyond what would developed in his doctoral program and enable the application of this skill set to an urgent public health priority aligned with NIDA’s Notice of Special Interest NOT-DA-24-012 (Xylazine: Understanding its use and consequences). Through the sponsorship of an interdisciplinary team with a collective 40+ years of substance use research and expertise in behavioral sciences, epidemiology, addiction medicine, and natural language processing, the applicant will complete the proposed research and the following training goals: (1) receive training in the design, conduct, and analysis of mixed methods research; (2) grow content knowledge and expertise in substance use and socio-epidemiologic research methods to end drug-related harms; (3) develop skills in the use of NLP techniques applied to large datasets; and (4) further the applicants professional development, academic leadership, and scholarly productivity. Completion of this F31 will position the applicant as a mixed methods behavioral scientist who applies computational methods to large datasets via NIH-funded research to improve the health of PWUD.

NSF Awards · FY 2024 · 2024-09

Soft materials underpin important technologies such as adhesives, coatings, drug delivery, and energy storage. One key challenge with such materials is how they change when exposed to fluids, especially if these fluids contain dissolved salts (e.g., seawater, bodily fluids, or battery electrolytes). Soft materials will often dissolve, detach, or excessively swell in salty fluids, leading to their failure. This award supports research into a new class of soft materials designed for salty fluid environments. The influence of molecular scale design on the mechanical properties of these materials will be investigated. The resulting fundamental knowledge will provide a foundation for adhesives or structures that strengthen in environments such as seawater; components that aggregate in response to specific salt species, enhancing desalination plants; and as salt driven muscle-like components for soft robotics. This award will also result in the interdisciplinary education of students in New York and Rhode Island in mechanical engineering and chemical sciences. A novel zipper-like molecular topology of soft polymeric materials decorated with tethered cationic and aromatic groups, termed ZIPers, will be investigated. These materials are simple to prepare on large scale and preliminary data shows that these ZIPers have a complex dependence of equilibrium structure and mechanical properties on the concentration and type of anion present in solution, features that can be dynamically adjusted by changes in ionic content. This work will utilize a combination of synthetic, experimental, and modeling approaches to provide insight into three aspects of their mechanical behavior: (1) the equilibrium structures and corresponding small strain oscillatory response of the ZIPer system as a function of monomer ratio, salt type, and salt concentration; (2) how the structure and crosslink dynamics determine the time dependent large deformation mechanical response of the ZIPer system; (3) potential of the ZIPer system to exhibit salt-driven shape-morphing. New mesoscale and continuum polymer modeling techniques will enable this work and also be standalone contributions to the mechanics of polymers field. This project will advance knowledge of the mechanics of dynamically bonded polymers and provide key insights into the properties of dynamic and responsive soft materials. 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.