University Of Washington

NIH Research Projects · FY 2025 · 2025-08

ABSTRACT In several high-income nations, including the United States, infectious syphilis has been resurgent for over two decades now, while syphilis is still endemic in low- and middle-income countries. Syphilis is therefore still a public global health concern, particularly in consideration that it can lead to neurological sequelae such as dementia and stroke-like syndrome, as well as cardiovascular manifestations potentially leading to death. Furthermore, every year, about half a million pregnancies are adversely affected by congenital transmission of the pathogen. The partial success of recent syphilis control campaigns promoted by the CDC and WHO clearly highlights the necessity of devising novel ways to control this serious infection. Improving our understanding of syphilis pathogenesis and the virulence factors that allow the syphilis agent, Treponema pallidum subsp. pallidum (Tp) to establish infection and persist in the host despite a robust immune response might be the key to new control strategies. A key aspect of the pathogenesis of early syphilis is the hematogenous dissemination of Tp to virtually every bodily organ. However, to reach distant tissues via the bloodstream, Tp must avoid killing by the rapid activation of the complement alternative pathway (AP). Complement evasion is a virtually unexplored topic in syphilis research, and yet it is critical to understanding pathogen persistence. To escape killing, many pathogens employ binding factors to recruit the host complement inhibitor Factor H (FH) from body fluids, thus hijacking its host-protecting function. We demonstrated that also Tp recruits human FH via a 43.1 kDa FH binding protein, and that recruitment occurs by recognizing the FH short consensus repeats (SCR) modules 19-20. Removal of sialic acid from the Tp surface with neuraminidase did not affect FH recruitment by the 43.1 kDa protein. However, studies from the 80’s by T.J. Fitzgerald implied that sialylation of still unidentified macromolecules on Tp surface contributes to evading the AP, which is consistent with the fact that FH SRC19-20 can be recruited by both sialic acid and binding protein(s). In this proposal, we aim to identify the 43.1 kDa ligand. Additionally, we will test the hypothesis that Tp mutants lacking the 43.1 kDa protein or the gene encoding the pathogen’s NeuB sialic acid synthase will be more susceptible to killing by the AP and impaired in their ability to disseminate and cause infection in the rabbit model. If successful, these studies will provide our research community with information about a novel virulence factor of Tp and mutants of this pathogen to be used in comparative studies, in addition to a better understanding of syphilis pathogenesis.

NSF Awards · FY 2025 · 2025-08

Surfaces governed by their mean curvature model many physical phenomena, such as soap films, black hole horizons, capillary surfaces, and other interface behaviors. These topics, particularly minimal surfaces and mean curvature flow (MCF), are pivotal in geometric analysis and contribute to advances across mathematics, physics, and materials science. Under this project, the investigator will conduct a number of research projects concerning the theoretical construction and variational properties of minimal surfaces and mean curvature flow, including the emerging and physically relevant study of capillary action on the boundary. Additionally, the project will promote the development of a diverse and collaborative community through educational and outreach initiatives including undergraduate clubs, curriculum development, research workshops and mentorship programs to support early career researchers. This project includes three primary research directions. In the first subject, the investigator will study the singularity analysis of MCF near cylindrical and conical singularity models, in the presence of interior and boundary curvature. This subject revolves around uniqueness for blow-up analysis of MCF. In the second subjects, the investigator will continue their development of min-max constructions of hypersurfaces with prescribed mean curvature and boundary contact angle. The principle investigator will also discover the regularity and long-time behavior of MCF with capillary boundary action. In the third subject, the investigator will explore the complexity of submanifolds, quantified by area and entropy, and connections to the stability of minimal submanifolds. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NSF Awards · FY 2025 · 2025-08

Hardware resource disaggregation separates individual hardware components from traditional, monolithic servers and connects them via a network. Disaggregation has been used in the context of compute, memory, and storage resources to bring greater flexibility, decrease energy consumption, and reduce costs. This project extends the concept of disaggregation to data center networks with a key research question: Can data centers and data-center applications benefit from disaggregation by moving network functionalities out of end hosts and pooling them together in another system layer? This project explores this question by introducing a rack-level disaggregated network solution called NetFusion, which consists of a pool of programmable Network Interface Cards (NICs) or SmartNICs, each of which can execute network tasks on behalf of end-host applications. NetFusion allows for the consolidation of networking demands associated with both packet processing and network-function processing, enabling statistical multiplexing of networking tasks and bringing disaggregation benefits to data centers and data-center applications. The project addresses a number of challenges in realizing this vision: How to support the safe and fair sharing of NetFusion? How can the system address both the long-term traffic needs and the short-term bursts of applications? How to allocate resources across the pool of SmartNICs? How to support different SmartNICs with varying resources? How can the system provide fault tolerance and react in a timely manner to workload changes? How can applications benefit from network disaggregation? This collaborative project brings together investigators from University of California at San Diego and University of Washington to optimize the network-intensive datacenter applications used by billions of people around the globe on a daily basis. By improving the efficiency of network operations, one can dramatically reduce the cost of provisioning existing datacenter infrastructure as well as make it much cheaper to deploy new public services. The project integrates industry collaborators who will provide access to cutting-edge network technologies and assist in technology transfer to the industry. For the broader community of users and society at large, the project’s artifacts will be made publicly available at https://sites.google.com/cs.washington.edu/netfusion/home, enabling the development of high-performance data center applications. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NIH Research Projects · FY 2026 · 2025-08

PROJECT SUMMARY ABSTRACT The genetic basis of obesity is well documented through classical twin studies and modern sequencing methods that generate genome-wide polygenic risk scores. The strong influences of socioeconomic, environmental, and health-behavior risk factors for obesity have also been identified. However, neither genetic nor environmental factors alone can explain the rapid rise in obesity prevalence over the past forty years. It is likely that the underlying biological drivers of the obesity epidemic lie at the intersection of genetics and the modern environment. The overall goals of the proposed research are to fill gaps in our understanding of the neurobiological underpinnings of genetic risk factors for common obesity, and to probe mechanisms whereby genetic factors may magnify the risk of environmental exposures through effects on the brain. Specifically, rodent models indicate that dietary exposures cause cellular inflammation – known as gliosis – in the mediobasal hypothalamus, which contains the arcuate nucleus, leading to dysfunction of local neurons that regulate body weight, increases in adiposity, and obesity. The cumulative literature from translational studies supports a role for hypothalamic inflammation and gliosis in the pathogenesis of obesity in humans. However, genetic susceptibilities that modify the extent to which obesogenic diets stimulate hypothalamic inflammation and gliosis remain largely uninvestigated. It is also possible that potent environmental stimuli promote hypothalamic gliosis regardless of genetic makeup which could have broad implications for population health. The proposed research therefore uses epidemiologic and twin study approaches to 1) test genetic risk factors for hypothalamic gliosis and 2) test environmental risk factors for obesity and hypothalamic gliosis and determine, through twin study methods, if environmental factors act independently of genetic background to promote obesity and/or hypothalamic gliosis. The proposed studies will utilize genetically informative samples from the Framingham Heart Study, the Adolescent Brain Cognitive Development Study, a brain tissue repository, and the Washington State Twin Registry. Hypothalamic gliosis will be measured both in vivo using magnetic resonance imaging and post-mortem using histopathology performed on hypothalamic tissue. Genotype-phenotype association study designs include both candidate gene and genome-wide approaches. Twin studies are used to disambiguate inherited, environmental, and health behavior risk factors for obesity and hypothalamic gliosis. In sum, the proposed research could significantly impact the field by uncovering molecular and neurobiological pathways involved in obesity pathogenesis, advancing our understanding of the influence of genetic factors on hypothalamic inflammation and gliosis, and opening avenues for novel mechanistic studies or precision health interventions.

NSF Awards · FY 2025 · 2025-08

The University of Washington (Seattle, Washington) will host the 5th Biennial Pacific Northwest Section of the Society for Industrial and Applied Mathematics (SIAM) meeting from October 3-5, 2025. This vertically integrated meeting will bring together individuals from undergraduates to distinguished researchers at universities, national labs, and industry mainly from the Pacific Northwest region. These conference participants, working at the forefront of applied and computational mathematics, have expertise in many of the key priority areas of the NSF Division of Mathematical Sciences (DMS). The goal of the meeting is to facilitate the advancement of knowledge in cutting edge areas of applied mathematics and computational mathematics for the benefit of both the Pacific Northwest region and the US more broadly. Themes for the meeting will include sessions in numerical linear algebra, optimization, numerical methods for solving partial differential equations, image processing, inverse methods and data assimilation, high performance computing, numerical modeling and simulation in the geosciences. This year in particular, the meeting will showcase particular expertise in the Pacific Northwest on hazards modeling, including hazards from earthquakes, tsunamis, debris flows and volcanic activity. A website listing conference activities and details can be found at https://sites.google.com/site/siampnwsection/biennal-meeting. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NIH Research Projects · FY 2025 · 2025-08

PROJECT SUMMARY/ABSTRACT Vector mosquitoes, such as Aedes aegypti, drink human blood to nourish their developing eggs, transmitting devastating human diseases that result in over half a million annual deaths in the process. A comprehensive understanding of the cellular and molecular mechanisms that underlie mosquito blood-feeding behaviors is critical for identifying new strategies to control mosquito populations and mitigate disease transmission. To drink blood, a mosquito inserts a flexible needle-like structure called the labrum into the host’s skin to probe for blood vessels. Although it is clear that different groups of sensory neurons in the tip of the labrum respond to phagostimulant compounds like ATP and other blood components, the molecular receptors mosquitoes use to detect blood are unknown. The sensory processing and behavioral impact of individual classes of labral sensory neurons are also unclear. Gene editing technologies like CRIPSR/Cas9 are powerful tools for probing gene function. However, these techniques remain time consuming and laborious to implement in non-standard genetic model systems, making it a high-risk endeavor to study neofunctionalized or potentially species- specific genes involved in blood detection and other specialized mosquito abilities and behaviors. This project seeks to combine emerging technologies for single-nuclei RNA sequencing with my recently-developed high- throughput genetic analysis approaches to perform a deep mechanistic analysis of the mosquito blood- detection system. We will characterize the diversity of sensory neurons present in the labrum, gaining genetic access to each cell type in order to characterize the anatomical location, functional sensitivity, and behavioral impact of each class. Our high-resolution transcriptomics data will be merged with our new higher-throughput screening approaches to facilitate rapid, unbiased testing of candidate molecular receptors that control blood feeding. Though the gustatory system represents one of the most poorly understood mosquito sensory systems, cutting-edge techniques and recent discoveries in mosquitoes have set the stage for a research program on contact chemosensation that is exciting and feasible. This project is poised to open the labral chemosensory system to molecular study and transform it into an accessible model of mosquito taste. This award will be the first to fully map the inputs to the neural circuits for blood feeding in Ae. aegypti while examining the functional significance of each cell type and their underlying molecular mechanisms. Finally, the approach developed here will provide a blueprint and genetic tools that can be readily ported to facilitate future molecular discovery efforts aimed at addressing other pressing questions in mosquito biology.

NIH Research Projects · FY 2025 · 2025-08

Project Summary Many animals have specialized proprioceptors that fire when a limb reaches the limit of its range. In mammals, including humans, the extremes of joint position are detected by low-threshold Ruffini endings and Pacinian corpuscles embedded within joint capsules. Like other proprioceptors, joint receptors are distributed throughout the body, which has made it challenging to understand if and how they are specialized for sensing and controlling specific movements. This project will leverage tools only available in the fruit fly, Drosophila, to provide new insight into basic neural mechanisms of limb sensorimotor control by specialized proprioceptive organs called hair plates. Hair plates are tightly- packed arrays of sensory hairs positioned close to joints in the insect cuticle. Our preliminary data suggests that hair plate proprioceptors fire at the limits of the joint range, in a manner analogous to mammalian joint receptors. In this project, we will combine experimental and computational approaches to test the hypothesis that hair plates function as proprioceptive limit detectors to stabilize limb posture and guide movement. A deeper understanding of proprioceptive limit detection and its contributions to motor control has the potential to transform the way in which we understand and treat sensorimotor disorders.

NIH Research Projects · FY 2025 · 2025-08

ABSTRACT Effectiveness of pre-exposure prophylaxis (PrEP) for HIV prevention methods currently available to cisgender women hinges on daily medication adherence, yet >50% of women discontinue within the first month of use. Digital technologies to improve adherence to HIV treatment and prevention interventions are rapidly expanding in the WHO African Region, despite mixed effectiveness findings. Systematic reviews note the near absence of articulated mechanisms of action (MoA) for HIV digital health strategies which limits translation into practice and thus population-level impact. Tools from behavioral health research and implementation science are useful to elucidate, articulate, and test MoA for digital strategies. There is substantial pragmatic value in understanding MoAs and moderators for how digital strategies work, including adapting intervention message content balance to emphasize the most potent mechanisms and tailoring content to specific populations. We propose an R21 to utilize data from the mWACh PrEP study (R01NR019220), a hybrid effectiveness-implementation trial that tests the impact of a two-way, interactive, SMS-based platform on PrEP adherence and maintenance (continuing PrEP refills and use) during pregnancy and postpartum in Kenya. The parent study includes 5 study sites based at public sector antenatal clinics in a setting with high HIV prevalence. To date N=600 (100% of planned enrollment) women are enrolled (1:1 randomization) to be followed until 9 months postpartum. The trial utilizes the Information-Motivation-Behavior (IMB) model, which specifies 1) knowledge acquisition, 2) motivation, and 3) behavioral skills as potential MoA. Within this R21, we propose to test hypothesized MoA for the mWACh PrEP digital strategy, assess specific context variables as moderators, and characterize experiences of MoA activation. In Aim 1, we will test whether knowledge acquisition, motivation, and behavior skills are MoA through which mWACh PrEP influences PrEP adherence and maintenance. We will consider both self-reported adherence, hair concentrations of PrEP, and PrEP continuation. We will employ deductive analysis using structural equation modeling and inductive analysis using coincidence analysis. In Aim 2, we will elucidate whether MoA are moderated by mental health, relationship climate, sexual behavior, access to care, and medical history, using structural equation modeling. Finally, in Aim 3, we will characterize how and why MoA are activated by assessing the experiences of women, SMS content, and health provider insights. We will conduct in-depth interviews with women, analyze two-way messages between women and providers, and engage facility and study staff through a workshop to understand activation of MoA. Our study is designed to move the field from theoretical to empirical knowledge of how and why women maintain and sustain PrEP use behaviors. Our findings will have pragmatic utility beyond HIV prevention in pregnancy for adapting digital message content to emphasize potent mechanisms and tailor message content to diverse populations.

NIH Research Projects · FY 2026 · 2025-08

SUMMARY/ABSTRACT Exposures to pollen and other ambient aeroallergens are well-established drivers of allergic rhinitis and asthma, but their role in Chronic Obstructive Pulmonary Disease (COPD) is largely unknown. A lack of aeroallergen monitoring data has contributed to limited research in this area, despite expanding aeroallergen levels associated with climate change. Monitoring technology for aeroallergens is advancing rapidly based on image analysis using artificial intelligence (AI), providing an opportunity to measure aeroallergen concentrations in near-real time and at multiple-locations. Our overall objective is to determine the impact of short- and long-term aeroallergen exposure on COPD outcomes and to ascertain whether allergic phenotypes among those with COPD—including blood eosinophil count, aeroallergen sensitization, sputum characteristics and airway transcriptomics—alter susceptibility to adverse health effects of aeroallergens. We leverage the SPIROMICS and SOURCE cohorts that comprise uniquely phenotyped, prospectively characterized participants with COPD or at high risk for developing COPD. We will develop taxa-specific estimates of daily and seasonal aeroallergen concentrations at individual home addresses using existing data from the nearest National Allergy Bureau (NAB) aeroallergen counting station (between-city measures) and sophisticated fine- scale, spatiotemporal models of aeroallergen concentrations (within-city measures) using advanced geospatial exposure models that incorporate not only the historical NAB monitoring data but also high resolution monitoring data from new aeroallergen monitors with AI-based image analysis. We will assess whether both short- and long-term ambient aeroallergen exposures are associated with respiratory symptoms, frequency and timing of exacerbations, lung function decline by spirometry, CT-based quantitative emphysema and small airway abnormalities, and disease prognosis in the well-characterized SPIROMICS and SOURCE participants. These results will provide historic and real-time pollen counts to inform risk communication, develop personalized treatment approaches and exposure mitigation strategies for patients with COPD, and forecast new risks due to the changing environment.

NIH Research Projects · FY 2025 · 2025-08

Project Summary/Abstract Every year, seasonal influenza viruses emerge with hemagglutinin (HA) surface protein mutations that confer escape from previously-protective neutralizing antibodies. This process is known as antigenic drift, and it necessitates frequent vaccine updates. Historically, the viral strains with the most antigenically drifted HA variants tend to dominate a given influenza season. Previous work has taken advantage of this observation by training forecasting models on antigenic data (e.g., titers from neutralization or hemagglutination-inhibition assays) in addition to genomic and epidemiologic data. However, these assays are low in throughput and scope, and generally only completed for a limited number of strains. Nevertheless, incorporating antigenic measurements for even partial circulating variant diversity in forecasting models has improved their accuracy. Development of methods that could generate more comprehensive datasets – that is, measuring the neutralizing titers of all circulating HA diversity – is therefore an a ractive goal. Here, I propose the development and an application of a next-generation sequencing-based neutralization assay that would parallelize antigenic measurements of ~100 currently circulating pdmH1N1 and H3N2 influenza A viruses in high-throughput. In this approach, influenza viral variants are selected, barcoded and pooled to create a multiplexed virus library. This library will then be used to simultaneously measure neutralizing titers for all viruses against a given serum specimen. Current approaches frequently rely on ferret sera, which do not fully represent the complexities of epitope targeting exhibited by human sera. I propose using this method to profile serum from several different human cohorts. The proposed cohorts were selected to more adequately represent the heterogenous immune responses comprising population immunity as a whole. Using this dataset, I will then test the hypothesis that more comprehensive antigenic measurements will improve the ability to forecast influenza variant success. I will assess the predictive power of these measurements both on their own as well as incorporated into previously established fitness models. Overall, I will develop a method to parallelize neutralization assays with ~100 currently circulating influenza A viruses. I will then use computational methods to ask if these measurements improve our ability to predict influenza strain dominance for a given season. Importantly, a major goal of vaccine strain updates is that the vaccine strain matches the seasonally dominant variant(s). The approach set forth in this proposal therefore has the potential to improve our ability to select vaccine strains.

NIH Research Projects · FY 2025 · 2025-07

PROJECT SUMMARY Lower respiratory tract infections, including pneumonia, are the most common cause of infection-related death worldwide. Melioidosis is a frequently fatal tropical infection caused by the Tier 1 select agent Burkholderia pseudomallei (Bp). Pulmonary melioidosis manifests in 50% of cases and doubles the risk of death. For the first time, domestically acquired cases of melioidosis were recently reported in the United States, highlighting the emerging nature of this severe infection. Pathogen inhalation is considered the most lethal route of infection, and bacteria aerosolization remains a grave bioterrorism threat. As an intracellular pathogen, Bp replicates in host immune cells, including monocytes, alveolar macrophages, and neutrophils. Activation of the inflammasome, an intracellular sensing protein complex, is therefore thought to be critical to host defense against Bp, leading to IL-1β production as well as pyroptosis. Neutrophil influx to the lung is mediated by monocyte and macrophage-derived IL-1β but can be pathogenic in melioidosis, leading to tissue destruction and ineffective bacterial clearance. Compared to adults, children make up only 5-15% of melioidosis cases and more commonly present with cutaneous infections or abscesses. However, little is known regarding the reasons for these differing characteristics. Using pediatric models of melioidosis, we have found that the juvenile host has resistance to pulmonary melioidosis, highlighted by decreased early neutrophil recruitment and lung IL-1β but increased lung monocytes. We hypothesize that pediatric host resistance to pulmonary melioidosis is dependent on an attenuated early monocyte response leading to reduced pathologic inflammation and improved bacterial clearance. To test these hypotheses, we will leverage in vivo and ex vivo models of pulmonary melioidosis as well as our expertise in innate immunity and pediatric pneumonia to undertake the following specific aims: Aim 1. Determine whether monocyte function impacts age-dependent neutrophilic inflammation in the lung in a murine model of pulmonary infection; Aim 2. Define age-dependent immune responses and the contribution of the inflammasome in a human lung model of pulmonary melioidosis. Completion of these aims will elucidate mechanisms driving resistance to pulmonary melioidosis in the juvenile host. Using age-appropriate models of lung infection, we are positioned to identify new modifiable targets for future treatment strategies.

NIH Research Projects · FY 2025 · 2025-07

Abstract: There is now overwhelming consensus that fathers’ influences on children’s development begin before birth and continue throughout the lifespan, with the early childhood period representing a particularly opportune time for programs to engage fathers. Studies of low-income fathers have found that warm and responsive interactions between fathers and their young children uniquely contribute to children’s social, emotional, and other skills, even after controlling for mothers’ parenting contributions (Amodia-Bidakowska et al., 2020; Mills-Koonce et al., 2015; Shannon et al., 2002). Early childhood is also the developmental period in which fathers across family structures and socioeconomic statuses are most likely to be involved in their children’s lives (Carlson & McLanahan, 2010). This suggests a window of opportunity for supporting fathers during children’s earliest years, which may help shape fathers’ involvement and relationships with their children over the lifespan. Despite this growing evidence, early childhood programs continue to focus largely on mother-child interactions, few interventions for low-income fathers have focused on parenting skills, and fewer still have focused on contingent responsiveness. The limited number of rigorous evaluations of fathering programs means we also lack substantial evidence on the causal links between participation in such programs and changes in father and child outcomes (Osborn, 2014). We aim to address these gaps by conducting a randomized controlled trial of a 6-week video coaching program, Filming Interactions to Nurture Development (FINDF), with fathers and their young children. FINDF is delivered through flexible home visits, targets warm and responsive father-child interactions, and uses video recordings to emphasize each father’s parenting strengths in the context of everyday caretaking moments. The sample will comprise of 200 racially and ethnically diverse fathers and their children ages 12-36 months whose families are enrolled in our community partner’s Early Head Start and related early childhood programs. Father-child pairs will be randomized to FINDF or a waitlist control group. Assessments comparing the two groups will occur at baseline, end of program, and 6 months post-program. We propose the following aims: 1) evaluate the main impacts of FINDF on the primary program target (i.e., fathers’ supportive parenting) and related child and parent outcomes (i.e., children’s behavior problems, children’s social-emotional competence, fathers’ parenting stress, fathers’ involvement, and father identity), 2) identify mechanisms of FINDF’s intervention effects, and 3) examine variation by select child, father, and program measures. Together, these aims will test the effectiveness of FINDF as well as how, for whom, and under what conditions FINDF works best or least. This will be one of the first large-scale randomized controlled trials focused on evaluating the impacts and underlying theory of a nurturing fathering program and builds upon promising findings from two preliminary evaluations of FINDF.

NSF Awards · FY 2025 · 2025-07

This project will deepen and broaden our understanding of two closely connected mathematical fields: partial differential equations and differential geometry. The project studies special Lagrangian equations, complex Monge–Ampère equations, and Hamiltonian stationary equations, which provide the mathematical foundation for mirror symmetry in the string theory of modern physics. These equations are also important in nonlinear elasticity and optimal transport. The project provides training opportunities for graduate students and postdoctoral researchers. For special Lagrangian equations, the objectives are to derive (optimal) Schauder and Calderón–Zygmund estimates, regularity and rigidity in dimension five and higher, existence, uniqueness and low regularity with variable continuous general phase, periodic Liouville theorems and existence with constraints, as well as a complex version of rigidity for these equations. The aim of the part of the project devoted to symmetric sigma-k equations is to investigate existence of singular solutions, integrability of the Hessian and partial regularity for the sigma-2 equations in dimension five and higher, to obtain Schauder and Calderón–Zygmund estimates for three- and four-dimensional sigma-2 equations, to study the Liouville problem for sigma-k equations, and to investigate the "double divergence" integral solutions to the sigma-2 equation. The project also aims to demonstrate the triviality of any global solution to complex Monge–Ampère equations, including self-shrinking equations for the Kähler-Ricci flow with certain necessary restrictions and to derive regularity of solutions to the real Monge–Ampère equations under an extrinsic noncollapsing condition. For the case of Hamiltonian stationary equations, the project's goals are to establish rigidity and existence of solutions to the second boundary value problem. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NSF Awards · FY 2025 · 2025-07

This project aims to serve the national interest by promoting best practices in introductory experimental physics. This Level 2 Institutional and Community Transformation project will support introductory physics lab instructors to redesign their labs according to strategies proven by physics education research. Physics labs focused on developing experimentation skills improve students' critical thinking ability and views on experimentation compared to labs focused on reinforcing lecture concepts. These impacts are positive for students. This project will create and sustain an Introductory Physics Labs Institute to create community and resources for introductory physics labs. The significance of this project is in developing instructor expertise, implementing educational innovations, and adapting existing educational innovations for specific teaching and learning environments. The project will also disseminate teaching and learning innovations broadly. The project will build and support an expansive community of passionate lab instructors eager to implement effective, experimentation-focused labs at their institutions. Lab instructors will contribute their instructional resources to an online resource created by this project, the Introductory Physics Labs Portal, modeled on existing highly successful portals developed by the American Association of Physics Teachers. The project applies an asset-based agentic paradigm for faculty change. The scope of this project includes expanding models of faculty-driven educational change to the range of roles involved in lab instruction, including nontenure-track teaching positions, staff, and those who supervise graduate or undergraduate teaching assistants. Project goals include generating significant new scholarship about how STEM lab instructors implement experimentation-focused labs, how they become skilled, confident, and reflective educators, and the impacts of experimentation-focused labs on student skills and perspectives. The materials developed in this project will have been piloted at a range of institution types, thus serving a wide variety of instructional contexts and student populations. The scope of this project is to impact about 45,000 students per year (about 10% of the total students taking introductory labs per year). Multiple STEM programs will benefit from lab instructors using high-quality curricular materials and high-impact pedagogies. Lab instructors will benefit from the support offered by the Introductory Physics Labs Portal in improving their lab courses and becoming better teachers. Students in a wide range of majors will benefit from learning with research-based materials and pedagogies. Second-order impacts are anticipated as undergraduate physics students transition into graduate programs and experimentation or data-related careers. The NSF IUSE: EDU Program supports research and development projects to improve the effectiveness of STEM education for all students. Through the Institutional and Community Transformation track, the program supports efforts to transform and improve STEM education across institutions of higher education and disciplinary communities. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NSF Awards · FY 2025 · 2025-07

The University of Alaska, Fairbanks (UAF) in collaboration with the University of Washington (UW) and University of Rhode Island (URI) propose to pilot a Shared Unified Research Fleet IT Support (SURF-IT) program for the US Academic Research Fleet (ARF). SURF-IT aims to establish a Managed Service Provider (MSP) to deliver essential IT and cybersecurity support to the ARF. By leveraging shared resources among UAF, UW, and URI, SURF-IT proposes to provide cost-effective, centralized technical services. This initiative will enhance operational efficiency, ensure robust cyberinfrastructure, and address the gap in dedicated IT support within the ARF. Oceanographic research vessels in the ARF provide at-sea laboratories that support scientists, engineers, post-doctoral scholars, graduate and undergraduate students as well as technicians and teachers as they pursue fundamental research in the marine environment. The principal impact of the present proposal is under Merit Review Criterion 2 of the Proposal Guidelines (NSF 23-525). It will provide fundamental support for cybersecurity and cyberinfrastructure to technicians, science, and crew for NSF-funded oceanographic research projects (which individually undergo separate review by the relevant research program of NSF). This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NSF Awards · FY 2025 · 2025-07

Modern artificial intelligence (AI) techniques, including large language models (LLMs) like in ChatGPT, have brought many benefits to our society, ushering in a new age of increased productivity and information accessibility. Despite these dramatic technological advances, modern AI techniques exhibit several drawbacks that limit their applicability and usability in many domains. They are trained on data that can easily become out-of-date in a world that currently generates over 400 million terabytes of new data every day. Modern AIs may generate answers that are difficult to explain or validate and are therefore hard to trust. Finally, AIs are famously vulnerable to “hallucination,” producing answers that are simply wrong. The goal of this research is to address these shortcomings with a new computer system and software framework that enables efficient improvements to the reliability and applicability of modern AI. AI’s vulnerability to hallucination can be reduced using techniques that augment the context available to AI engines with knowledge graphs. A knowledge graph is a way of representing information that represents not just individual data items, but connections between them. Graphs encode structure, hierarchy, and complex relationships, which, if accessible to an AI tool, can improve the correctness of its answers; at the same time, graphs can provide additional context which can help explain or validate answers, improving explainability. This research is necessary because current computer architectures and distributed computing platforms are not well suited to simultaneously supporting both LLM and large-scale graph computations. The GPU architectures that currently dominate AI are optimized for computations in which all data are laid out in a very regular, dense pattern, while graph computations have historically required a very different kind of optimization to support irregular data layouts. Additionally, advances in software are necessary to support multiple kinds of graph computations over distributed data to query the structure of graphs, analyze them, and make predictions based on those structures and analyses. This research will produce a system called Panther that comprises a new, highly parallel architecture well-suited to both LLM and graph computations, a new memory system that efficiently supports the combination of large scale graphs and LLMs, and a distributed software framework and applications that collectively realize dramatic improvements for AI efficiency and reliability. We expect Panther to lay the groundwork for the next generation of high-performance trustworthy AI. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NSF Awards · FY 2025 · 2025-07

Internal bores generated by shoaling internal waves are known to be significant mechanisms of energy dissipation, cross-shelf exchange, and vertical mixing. Recent observational work has revealed that obliquely incident internal bores drive strong cross-shelf and along-shelf gradients in energy flux and water properties on the inner shelf. Robust theory suggests this energy flux divergence should drive a mean along-shelf current. However, mean along-shelf flows driven by dissipating internal waves have only been studied in the case of internal wave reflection on the continental margin, not for shoaling internal bores on the inner shelf. The project will examine the wave-mean flow interaction of dissipating shoaling internal bores for along-shelf currents on the inner shelf, including how the dissipation of shoaling internal bores can drive a time-averaged along-shelf current. Physical insights gained from idealized modeling will permit identification of the along-shelf flow in a detailed observational and high-resolution realistic modeling dataset. Along-shelf transport is relevant for biologically and physically important processes such as population connectivity and scalar transport. As such, this work may lead to reinterpretation or re-analysis of existing inner-shelf field observations and guide new experiments. The project will investigate internal bore-driven along-shelf currents, using idealized modeling, analyses of field observations, and realistic circulation model output. A process-motivated numerical experiment will be employed to characterize the along-shelf flow under simplified conditions and systematically varied forcing, while analyses of field observations and realistic model output will verify the presence, structure, and variability of the flow in nature. The relationship of internal bore dissipation to the magnitude and cross-shelf location of the along-shelf current is of particular interest. The numerical model will be used to determine how bore dissipation and the along-shelf current depend on ambient stratification, topographic slope, and planetary rotation. Field data and realistic modeling results will be used to quantify the time-averaged along-shelf circulation and its dynamics. A comparison between idealized modeling results and both observational and realistic modeling data will be vital in confidently attributing the measured along-shelf flow signal to internal bore dissipation. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NSF Awards · FY 2025 · 2025-07

This project aims to serve the national interest by establishing practices to improve mentorship, learning, and engagement in undergraduate research experiences (UREs) in engineering. UREs play a crucial role in enhancing engineering students' academic experiences by providing hands-on, authentic experiential learning opportunities. This level 2 project in the Engaged Student Learning track of the IUSE program will build on an existing toolkit of interventions and best practices that create structured reflection and mentoring activities within engineering UREs. The implementation, adaptation, and outcomes of this toolkit in UREs will be studied across five institutions. This work has the potential to expand access and improve the quality of mentorship in engineering UREs. It will also strengthen the existing partnership between a diverse group of participating institutions, and the knowledge gained will result in the expansion of high-quality, freely available resources for engineering UREs. During the project, the investigators will form an Undergraduate Research Excellence Network (UREN) with URE mentors, including faculty, postdoctoral researchers, and graduate students, to implement the existing toolkit. The toolkit includes student and mentor training videos, activities, instructor guides, and workshops that make the learning and benefits of UREs more visible to and accessible for students and faculty. The UREN will provide structured training and coaching to help mentors form an action plan for adopting these tools in their research mentorship. The implementations will be evaluated through an emergent design studies approach, focusing on mediating processes involving student self-assessment, reflective thinking, and mindset. These findings will be linked with evaluated outcomes related to students' autonomy and self-confidence in research and their ability to connect their research experience with their learning through coursework. This project will increase knowledge about improving learning and engagement in engineering UREs. Evaluating whether the learning gains observed in previous work can be generalized across five institutions will establish this toolkit as an important contribution to enhancing engineering students' learning. Furthermore, it will provide critical insight to inform the development of new pedagogical approaches that leverage student mindset to support experiential learning in STEM fields. The NSF IUSE: EDU Program supports research and development projects to improve the effectiveness of STEM education for all students. Through the Engaged Student Learning track, the program supports the creation, exploration, and implementation of promising practices and tools. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NSF Awards · FY 2025 · 2025-07

High-temperature plasmas, composed of electrically charged particles, interact primarily through collective effects involving many particles at once. However, occasional collisions between just two particles can lead to significant changes, such as the creation of charged ions through electron impact, the release of immense energy in nuclear fusion reactions, and the redistribution of energy and momentum through scattering. While physically accurate models exist to describe both collective interactions and binary collisions in plasmas, they are too complex to solve directly. Instead, simplified models have traditionally been used to predict plasma behavior, including nuclear fusion processes. Recent high-performance inertial confinement fusion (ICF) experiments have produced unexpected results that differ from predictions based on these simplified models. This discrepancy suggests that a more precise, high-fidelity kinetic model is needed to fully understand and optimize fusion reactions. This research project aims to develop a novel computational approach that integrates data compression techniques, fast numerical methods, and advanced mathematical modeling to make high-fidelity plasma simulations feasible on modern supercomputers. By applying this new model to experimental data, plasma behavior can be more accurately reproduced, providing insights that could lead to the design of even more efficient ICF devices, and ultimately improving fusion technologies. Plasma is a state of matter whose intrinsic properties are governed by collective interactions of large ensembles of free charged particles. In many high-temperature plasma applications, such as fusion energy, binary collisions that include atomic and nuclear reactions and elastic scattering are essential to accurately describe kinetic physics. However, the exceedingly complex nature and high dimensionality of the governing kinetic equations for such high-temperature plasmas severely challenge current numerical methods. Recent advancements in fast algorithms for the collision operator and low-rank tensor methods have facilitated addressing this difficult problem. The project aims to develop and apply these low-rank computing techniques to numerically solve the governing equations of kinetic physics in a multi-species, reacting plasma with computational efficiency. The numerical method will be applied to explore kinetic physics in a high-temperature fusion plasma that is undergoing atomic reactions, such as ionization and nuclear fusion reactions releasing energetic charged products that heat the bulk plasma through elastic scattering. These processes are foundational to the operation of fusion plasma devices. The computational methods to be developed in this project have the potential to provide high-fidelity kinetic simulations for fusion plasmas at a manageable computational cost. The novelty of the approach is represented by four key elements: mathematical formulation of reaction collision operators, fast spectral method for the collision operators, low-rank decomposition in the velocity space, and algorithm implementation on GPU systems. The research project will enable unprecedented first-principles modeling of kinetic physics in reacting plasmas, unraveling recent experimental results, and offering new insights into intricate multiscale high-temperature plasma dynamics for optimizing future devices. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NIH Research Projects · FY 2026 · 2025-07

PROJECT SUMMARY Edibles that contain Δ9-tetrahyrocannabinol (THC), the principal psychoactive ingredient produced by the Cannabis plant, are becoming increasingly popular among adolescents, making examination of this method of use on the adolescent developing brain urgently needed. An ongoing collaboration between the Stella, Land and Bruchas laboratories led to the development and validation of THC-gelatin voluntary consumption procedures for rodent and showed that adolescent exposure results in adulthood behavioral impairment due to select changes in molecular and cellular components in specific brain regions. Here we show that adolescent mice readily consume THC-gelatin, and that THC-gelatin consumption is increased when adding chocolate flavor (THC-E-gel) resulting in enhanced acute cannabimimetic effects. This approach can easily be combined with other drugs, here cannabidiol (CBD), to better understand its pharmacological interaction with THC. Adolescence represents a critical period where maturation of neural systems is still occurring, particularly in mesocorticolimbic brain regions, and disruption of this maturation process by drug use may lead to severe behavioral impairments in adulthood. Our recently published studies highlight one of the first successful voluntary consumption models of THC in rodents, thereby enabling the study of its long-term consequences on brain development and behavioral outcomes. Our new goals are to: 1) determine how long-term adolescent use of select regimens of THC-gelatin alone or in combination with CBD impact 2) cannabimimetic responses and natural aversive and reward behaviors in adulthood, which may provide insight as to the mechanism of 3) altered neurotransmission and receptor signaling within the mesocorticolimbic system. Neuronal activity and endocannabinoid signaling will be measured using innovative multi-site fiber photometry recoding of behaving animals, and IHC and electrophysiology will be used to identify structural and circuit changes related to adolescent THC use. Our aims will: Aim 1: Determine the impact of consumed THC- and THC:CBD-E-gel during adolescence on rewarding, avoidance, and exploratory behaviors in adult mice. Aim 2: Isolate how THC:CBD-E-gel consumption during adolescence modifies neural activity across mesocorticolimbic structures during adult motivated behaviors. Aim 3: Define specific molecular and circuit changes in adult mesocorticolimbic brain regions resulting from THC:CBD-E-gel consumption during adolescence. The completion of these studies, which utilize an innovative mouse model of voluntary oral consumption, will increase our pharmacological, molecular and cellular understanding of the impact of THC and THC/CBD use on adolescent brain development, and further determine how such perturbations influence behavior in adulthood.

NSF Awards · FY 2025 · 2025-07

With the support of the Macromolecular, Supramolecular, and Nanochemistry Program in the Division of Chemistry, Professors Forrest Michael and Matthew Golder of the University of Washington will investigate new ways to generate novel plastic and elastic materials with tunable properties and develop new methods for these materials to be chemically recycled. Synthetic plastics and rubbers are essential and ubiquitous products in everyday life, serving as important materials for a wide variety of applications. Though many of these materials find alternative end-of-life uses, our current ability to recycle these materials is very limited. This proposal will investigate novel ways of transforming simple petroleum byproducts into functionalized plastics and rubbers with higher levels of control over the microscopic chemical structure and its tunability. The key to this approach is the use of a unique catalytic functionalization of commodity polymers that can add a wide range of functionality in controllable proportions. Using this catalytic reaction, this project will prepare a variety of new plastics and rubbers and investigate their physical properties. Additionally, this project will develop methods that allow the initial transformation to be chemically reversed, thus regenerating the original material and allowing its reuse in new applications. This functionalization/defunctionalization process will enable a circular life-cycle for these materials, in which they can continually be restored to their original state and then subsequently re-functionalized and reused for novel purposes. The broader impacts of this work will be to allow more sustainable, predictable, and tunable access to plastic and rubber materials, and to greatly improve those materials’ usability and reusability at a fundamental chemical level. This technology stands to change how rubber materials are used and re-used across diverse industries. Additionally, Professors Michael and Golder will provide invaluable cross-disciplinary training for students, and design and implement outreach activities to educate homeschooled students on the use and importance of sustainable plastics. Professors Michael and Golder will develop general synthetic strategies for the reversible introduction of novel functionality and crosslinks into synthetic elastomers. In this project, they will study structure-function relationships and develop fundamental design principles for the generation of novel functionalized thermoplastic and thermoset elastomers using a catalytic amination of polydiene feedstocks. Using this catalytic method, this project will also develop methods for generating thermoset materials from synthetic thermoplastic rubbers that retain the parent alkene microstructure. Additionally, a novel method for deamination of the functionalized thermoplastic and thermoset materials based on the formation and elimination of hydrazides will be developed, thus allowing the functionalized materials to be chemically reverted to their original state in a traceless fashion. This approach will advance our fundamental understanding of elastomer recycling and enable the use of synthetic elastomers as reusable and recoverable building blocks for a variety of materials applications. This technology aims to enable a new circular life cycle for elastomeric building blocks across a diverse range of applications and 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 2025 · 2025-07

This I-Corps project focuses on the development of a leak detection solution for pressurized gas systems. This information is essential for industrial safety and efficiency, yet current methods are outdated and manual. These manual methods require time-consuming inspections by skilled personnel, rely on expensive equipment, and struggle to detect smaller leaks in complex or inaccessible systems. This solution is critical in reducing energy consumption, gas losses, and health risks. Potential customers include small and medium-sized industrial manufacturers and other industrial sectors that emphasize the use of high-pressure gas. Globally, gas leaks lead to significant energy waste and financial loss, with air leaks in U.S. facilities alone contributing an estimated $2.54 billion annually. 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 an advanced, integrated, real-time leak evaluation and detection system. The technology leverages advanced vibration-sensing algorithms and Industrial Internet of Things technologies to create a real-time gas leak detection solution that addresses inefficiencies in traditional manual methods. The system has the ability to continuously monitor gas lines using enabled sensors to deliver real-time feedback and precise alerts across a wide area. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NSF Awards · FY 2025 · 2025-07

The Arctic Ocean has experienced a significant loss in sea-ice coverage since the 1970s, with impacts on marine ecosystems, weather patterns, and economic activities such as fishing, shipping, and resource exploration. Understanding how Arctic sea-ice conditions have varied in the past provides valuable insights into natural patterns in ice coverage and helps refine scientific models used to project future ice cover. This project will investigate Arctic sea-ice cover during past warm periods in the geologic record using advanced geochemical techniques to reconstruct historical ocean conditions. The research will also support workforce development by training graduate and undergraduate students in cutting-edge scientific methods and equipping high school educators with new resources to enhance STEM education. This study will analyze ocean sediment cores to examine Arctic sea-ice coverage and ocean conditions over the past 150,000 years, focusing on two key warm intervals: the Holocene Thermal Maximum (~8,000 years ago) and the Last Interglacial (~130,000 years ago). The research team will use helium and thorium isotopes as a novel, inorganic method for estimating past sea-ice extent, while nitrogen isotope analyses of marine microfossils will provide insights into ocean nutrient levels and biological activity. These data will be collected from three sediment cores spanning a range of Arctic conditions, allowing scientists to assess changes in ice coverage, ocean structure, and nutrient cycling. By integrating these findings with existing data, the project will improve understanding of Arctic environmental history and enhance the accuracy of models used to study changing polar 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 2025 · 2025-07

With the support of the Macromolecular, Supramolecular, and Nanochemistry Program in the Division of Chemistry, Professor Brandi Cossairt of the University of Washington will find ways to make materials called nanocrystals with new, unique properties. She will achieve this by studying how nanocrystals grow from special starting materials known as magic-sized clusters. The fundamental chemistry knowledge of how the structure and composition of these clusters govern the properties of nanocrystals would enable the rational design of new nanomaterials for emerging applications. This research could help create breakthroughs in cutting-edge technologies, including electronics, photonics, quantum information, and catalysis. In addition, Professor Cossairt will contribute to workforce development and education by providing interdisciplinary research training to graduate and undergraduate students, including those from local community colleges, organizing a regional nanoscience workshop, and creating open-access learning materials for new learners in nanoscience. Professor Cossairt and her team will expand the library of known magic-sized clusters across different semiconductor families, develop chiral clusters that can transfer their chirality to larger nanostructures, pioneer methods for low-barrier compositional tuning, and develop a high throughput strategy for studying the conversion of magic-sized clusters to larger nanostructures. These efforts aim to transform the field of nanoscience by developing new and generalizable strategies for semiconductor nanocrystal synthesis, enabling precise control of material properties at the atomic level, and bridging the knowledge gap between molecules and functional nanomaterials. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NSF Awards · FY 2025 · 2025-07

With support from the Chemical Synthesis Program in the Division of Chemistry, Professor Gojko Lalic at the University of Washington is studying the development of new reactions for the synthesis of organic molecules using organoboron compounds and transition metal catalysis. The project is advancing more efficient transformations of common starting materials into more valuable targets, complementing existing methods. These reactions are providing a new approach to forming carbon-carbon bonds, critical for constructing large organic molecules. Beyond practical applications in organic synthesis, the fundamental properties and reactivity of organoboron compounds are being investigated and expanded in these studies. An essential part of the project is its outreach initiative, which fosters connections with the local community. Dr. Lalic's team engages elementary and high school students through activities that inspire interest in science, technology, engineering, and mathematics (STEM) careers. Organoboron compounds are valuable synthetic building blocks due to their availability, stability, and versatile reactivity. Continued advances in the synthetic applications of these compounds is critically important to support the pharmaceutical industry, medicinal chemistry, the synthesis of agrochemicals, and material science. Prof. Lalic and his research team are creating more effective tools for synthesizing complex organic molecules by exploring two new classes of chemical reactions. The first is a new type of cross-coupling reaction using two nucleophilic coupling partners that leverages the ambiphilic nature of organoboron compounds and the ability of transition metal complexes to modulate their reactivity. The second focuses on innovative strategies for homologating organoboron compounds via formal insertion of C2 fragments into carbon-boron bonds. Notably, this C2 fragment insertion involves an unusuallly facile activation of carbon-carbon bonds. Integral to this work are outreach activities, which are designed in collaboration with the local community, to promote science education and engagement. 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.