University Of Washington

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

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.

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.

NIH Research Projects · FY 2025 · 2025-06

Project Abstract The vestibular system detects head motion and modulates central nervous system pathways. Disorders of the vestibular system affect about 69 million Americans and can cause disorientation, imbalance, dizziness, and increased rates of falls. Some vestibulopathies are sensorineural in nature, involving injury to or degeneration of vestibular sensory receptors (hair cells or HCs) or primary sensory neurons (vestibular ganglion neurons or VGNs). Two types of vestibular HCs have been defined: HCI and HCII. VGNs innervate HCI with a cup-like calyx synaptic terminal and HCIIs with bouton-only endings, and they can terminate in either the central/striolar zone or the peripheral/extrastriolar zone of the sensory epithelia. One obstacle for developing new treatments for vestibulopathies is our limited knowledge of how VGNs establish and maintain their region-specific and HC-type specific synaptic contacts and how many distinct subtypes of HCs and VGNs exist. Investigations into neuronal heterogeneity in other sensory systems (e.g., spiral ganglion neurons of the auditory system) have begun to unravel the molecular heterogeneity that drives the anatomic and functional classifications of those neurons. Indeed, studies in SGNs have given us new insights into how the auditory system functions and how sensorineural hearing disorders may be treated. Such characterizations have yet to be undertaken in VGNs. I propose two aims that employ single cell RNA sequencing (scRNAseq) in adult mice. In Aim I, I will test whether VGNs can be classified by distinct transcriptional profiles and correlate their profiles to known anatomic VGN subtypes using hybridization chain reaction, immunocytochemistry, and histological analysis. I seek to determine if molecularly distinct VGN subtypes differ with respect to their cell size, location in the ganglion, zonal projections to the utricular epithelium, and/or terminal morphology on HCs. In Aim II, I hypothesize that, by comparing scRNAseq data from VGNs and from utricular HCI and HCII, I can identify potential cell-to-cell signaling pathways that maintain the distinct morphologies of afferent synaptic terminals in the utricle. I will use the cell-to-cell inference program CellChat, to generate a list of candidate ligand-receptor pairs that may mediate HC-VGN communication. To narrow down signaling pairs that are required for proper afferent terminal morphology, I will take advantage of the finding that conditional knockout (cKO) of Sox2 in adult mouse HCIIs triggers a change in VGN terminals from bouton-type to calyx-type. Genes on my candidate list whose expression is altered in HCIIs after Sox2 cKO are more likely to be necessary to maintain boutons and/or repel calyx formation. This project will inform our understanding of VGN structure and function and the regulatory pathways that may maintain the HC type-specific morphology of VGN terminals. I will conduct this project under the mentorship of Jennifer Stone and David Raible as part of a structured training program that includes education in grantsmanship, statistics, responsible conduct of research, and biology of the inner ear.

NIH Research Projects · FY 2026 · 2025-06

PROJECT SUMMARY Perinatal asphyxia and subsequent acute hypoxic-ischemic encephalopathy (HIE) affects 1.3-4.7/1000 liveborn infants in the US, with the rate at least 2-3-fold higher in low- and middle-income countries (LMICs). Without treatment, two thirds of affected infants die or develop severe neurodevelopmental impairments including intellectual disability, cerebral palsy and epilepsy. Therapeutic hypothermia (TH) has been the standard of care for infants with moderate or severe HIE since 2010; however, the use of TH outside of the high resource setting is not warranted and may be deleterious. As the greatest burden of HIE is in countries that do not have access to the facilities or patient population suitable to provision of TH, finding appropriate therapies for HIE in LMICs is critical. Important differences in the LMIC patient population include evidence of more chronic hypoxia-ischemia (HI), earlier neonatal seizures, and a higher prevalence of poor nutrition. These conditions result in a shift of injury from the deep grey matter to the white matter, but are generally not modeled in preclinical HIE research. To screen and test for LMIC-relevant neuroprotective agents, we have developed complementary in vitro and in vivo models in the developing ferret. Our data in the inflammation sensitized hypoxic-ischemic-hyperoxic (HIH) ferret model of HIE shows injury patterns and behavioral changes consistent with a greater white matter injury that responds to pharmacological neuroprotectants such as erythropoietin (Epo), but not TH. In cultured organotypic ferret brain slices exposed to simulated nutrient deprivation and intermittent oxygen-glucose deprivation (iOGD), we have also shown similar injury patterns, with the white matter being particularly susceptible to nutrient deprivation. We also see region-dependent responses to multiple therapies, suggesting that an optimal therapeutic approach will require combinatorial therapies to provide global neuroprotection and improve long-term outcomes. Building on our preliminary findings, the objectives of our proposed research are to (1) determine the regional specificity and efficacy of multiple promising neurotherapeutic combinations in the in vitro iOGD slice culture model with nutrient deprivation, (2) evaluate dose-dependent treatment interactions and transcriptomic responses to established and novel neurotherapeutic combinations to optimize white matter neuroprotection in vitro, and (3) develop a cocktail of neurotherapeutics optimizing neuroprotection in vivo in the ferret HIH model using ferret-specific physiologically-based pharmacokinetic models. All the included therapeutics are cost-effective, shelf-stable, and do not require specialist equipment to administer or monitor. Our overarching hypotheses are that: (1) neurotherapeutics that provide complementary region-specific neuroprotection in vitro will increase global neuroprotection in vivo, and (2) that compared to monotherapy, combining complementary neurotherapeutics will result in greater neuroprotection across the entire brain that persists into adolescence. Data resulting from this proposal could support a clinical trial in this population for which no specific neuroprotective therapies are currently available.

NIH Research Projects · FY 2026 · 2025-06

ABSTRACT Macrophage activation syndrome (MAS) or secondary hemophagocytic lymphohistiocytosis (sHLH) is a dysfunctional, potentially fatal, hyperinflammatory response that is characterized by abnormal activation of lymphocytes and phagocytes leading to an overproduction of inflammatory cytokines and damage of host tissues. In rheumatic disease, MAS most often occurs in patients with systemic juvenile idiopathic arthritis (sJIA) or Adult-onset Still’s Disease although it can also occur as a complication of other rheumatic diseases, including systemic lupus erythematosus, infection, or malignancy. Myeloid cells such as circulating monocytes play a crucial role in the pathogenesis of MAS. I have discovered evidence of a type I interferon signature in monocytes from subjects with MAS secondary to sJIA, suggesting shared pathogenic features with lupus. Although data from mouse models have implicated TLRs 7 and 9 as critical to driving MAS, human monocytes express TLR7 and TLR8, but not TLR9, suggesting that TLR7 and TLR8 are likely the relevant nucleic acid sensing TLRs in human monocytes during MAS. These data highlight the importance of studying MAS in humans. I have defined specific transcriptional changes in MAS monocytes including upregulation of the homotypic cell surface receptor SLAMF7 and found that SLAMF7 and cytokines important to MAS pathogenesis, such as IL-15 and IL-18, are induced by TLR8 signaling in monocytes. The bone marrow is a key location for immune cell development and a frequent site to identify characteristic hemophagocytes during MAS; novel spatial biology approaches render this an accessible tissue for analysis from historical samples. This project will address the following aims: (1) define the cellular and molecular landscape in bone marrow during MAS and define shared and unique features between sJIA and lupus-driven MAS; (2) test the hypothesis that gene expression changes in the peripheral circulation will reflect changes in the bone marrow; (3) test the hypothesis that TLR8 signaling shapes monocyte immune responses during MAS; and (4) test the hypothesis that TLR8-induced SLAMF7 and IL-15 drive monocyte-CD8+ T cell interactions during MAS. The long-term objective of the proposed research is to elucidate the role of cell extrinsic and cell intrinsic signals in shaping monocyte differentiation and cellular interactions during MAS to better understand the pathogenesis of this potentially life-threatening complication. A K08 award will allow me to capitalize on the rich scientific environment of the University of Washington, Benaroya Research Institute, and Seattle Children’s Research Institute to successfully transition to scientific independence. The proposed research and career development plan will provide me with critical training and mentorship in human immunology, translational research, and transcriptomic data analysis, to further my career goal of enhancing knowledge of mechanisms of MAS/sHLH pathogenesis with the ultimate goal of improving the diagnosis and treatment of patients with MAS/sHLH.

NIH Research Projects · FY 2025 · 2025-06

PROJECT SUMMARY/ABSTRACT Synapses serve as vital intercellular connections facilitating rapid and accurate transmission of information between neurons. Successful nervous system development is dependent on proper synapse formation, an intricate and highly coordinated process regulated by complex cellular and molecular mechanisms. Elucidating the mechanistic underpinnings of synapse formation holds significant promise in advancing our understanding of neurodevelopmental and neurodegenerative disorders. The purpose of this proposal is to uncover novel molecular mechanisms involved in synapse formation, particularly as it pertains to neurological disorders. Using genetics, super resolution microscopy, and in-vivo unbiased proteomics, I will explore novel mechanisms that regulate synapse formation in the nervous system. My doctoral training will provide the essential foundations for me to become a successful independent investigator. Our preliminary studies have led to investigating a ciliary protein with poorly understood function in cilia. We have found this ciliary protein is the most prominent hit in affinity-purification proteomics data with RPM-1. RPM-1 is a known regulator of nervous system development and the human ortholog MYCBP2 is involved in a neurodevelopmental disorder. Using C. elegans as my model organism, research in Aim 1 will investigate the function of this ciliary protein in GABAergic neurons and elucidate its relationship with the RPM-1 ubiquitin ligase and signaling hub. I hypothesize that this ciliary protein has a non-ciliary function in synapse formation of GABAergic motor neurons and is involved in the RPM-1 signaling network. Studies in Aim 2 will focus examine the functional role of this protein in ciliated neurons for the first time using the C. elegans model organism. I will investigate how this player shapes ciliated neuron development by using genetics and neuron-specific transgenic approaches. Completion of these studies will provide me with the necessary knowledge and skillset to further investigate genetic regulatory mechanisms that shape neurodevelopment.

NSF Awards · FY 2025 · 2025-06

The Faculty Early Career Development Program (CAREER) grant supports research that advances fundamental knowledge of the dynamics of segmented structural designs with irregular patterns, thereby promoting the progress of science, and advancing prosperity and welfare. Current bio-inspired engineering primarily emphasizes optimizing regular geometric patterns that are ordered, periodic, and repeated, overlooking the intrinsic geometric irregularities found in nature. This approach misses the opportunities presented by the ubiquitous and intrinsic geometric irregularities of living organisms. This project will attempt to address this critical gap by developing the required engineering models for identifying and applying distinctive irregular patterns to design structures to match the range of functions and energy- and material-efficiency of biological systems. Potential applications include energy harvesting, intelligent actuation and control in vehicles, smart shock absorption, vibration damping, and acoustic attenuation. Drawing inspiration from the musculoskeletal patterns in diving seabirds and stingrays, the new findings plan to yield transformative technological solutions to achieve efficient multifunctional structures. Additionally, the project will develop a user-friendly, open-source application to facilitate interdisciplinary collaboration and make these concepts accessible to scientists, engineers, and the public. This app will help translate insights from biological dynamics into practical applications in biomechanics, biomedical science, and engineering. This research aims to make a transformative shift in current multifunctional structure modeling framework and biodynamics interpretation. Irregular patterns for engineering structures can overcome current limitations in structural dynamics engineering ranging from complex actuation for robots and vehicles to energy extractions from ocean waves. The project will attempt to address those limitations by developing an efficient dynamics modeling framework to predict the distinctive dynamics of irregular patterns in natural structures and demonstrate a wide control range of these dynamics with tunable specialized irregularities in structural patterns. The focus will be on three engineered geometric irregularities --- local rigidity, interfaces, and pattern connectivity. These irregularities should enable control of the wave properties and emerging dynamics, key to achieving advanced engineered structures with dynamic functions. This effort intends to demonstrate (i) impact energy attenuation using a seabird neck-like structure without damping materials and (ii) self-propulsive locomotion without actuators using wave-stingray-like wing structures. Unlocking nature’s irregular pattern principles intends to reach beyond classical mechanics to develop thin, segmented, curved, and light multifunctional structures without compromising structural reliability, stability, or control. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NIH Research Projects · FY 2025 · 2025-06

PROJECT SUMMARY People who use opioids (PWUO) are at increased risk of drug overdose as well as HIV infection or worse HIV outcomes. Retention in opioid use disorder treatment and HIV prevention or treatment (hereafter referred to as HIV care) for PWUO remains suboptimal. Medications for opioid use disorder are gold standard treatments for opioid use disorder (OUD). This includes buprenorphine which has a strong evidence base in reducing the risk of overdose, reductions in drug use, soft-tissue infections, and hospitalizations. Additionally, buprenorphine treatment been shown to improve HIV care outcomes by engaging in PWUO in health care services to reduce infection risk as well as promoting HIV viral load suppression for PWUO living with HIV. While there are successful clinic-based implementation strategies to improve buprenorphine and HIV care access, long-term retention, particularly at 1 year, remains elusive. Achieving this long-term retention goal requires innovations in delivery of these services. Community-based care is a means of service delivery which prioritizes individuals at high risk of falling out of care and/or poor HIV care outcomes with care services delivered directly to them. The propose of this study is to develop the Community-Based Opioid Treatment (CBOT) implementation strategy to deliver buprenorphine and HIV care services to PWUO by nurse care-managers and community outreach workers and then conduct an implementation trial comparing the implementation and clinical effectiveness outcomes of CBOT compared to evidence-based, clinic delivery of opioid treatment. Part 1 of the study will consist of interviewing patients, providers, nurses, and other stakeholders to inform development of CBOT and the blueprint needed to implement this care delivery strategy. Part 1 will conclude with a 3-month pilot of CBOT with n=10 participants, and any needed refinement of the CBOT implementations strategy. Part 2 of the study will be a type-3 hybrid implementation trial. Participants (n=140) will be randomized (1:1) to receive the CBOT implementation strategy for opioid use disorder treatment and HIV care services delivered by a nurse care- manager and community outreach workers or office-based opioid treatment, with opioid use disorder treatment delivered by a nurse care-manager in the clinic setting. Primary implementation outcomes include the feasibility, acceptability, and maintenance of the CBOT implementation strategy. Secondary clinical outcomes are buprenorphine retention and HIV care outcomes (HIV viral load or uptake of HIV testing). Finally, costing measures will be continuously collected to conduct micro-costing analysis. CBOT can be the next tool that clinics and health systems utilize to successfully reach PWUO at risk for or living with HIV who are at high risk of falling out of care and prioritizing them for enhanced services. In summary, this study addresses a pressing need to determine the most effective approach to retention in opioid use disorder treatment and HIV care for a priority population of individuals at high risk of a drug overdose and falling out of established care.

NSF Awards · FY 2025 · 2025-06

This award supports the West Coast Discrete Probability and Combinatorics conference at the University of Washington on July 17-18, 2025. The conference is designed to provide opportunities for graduate students and junior researchers to interact with top experts in the field and for them to learn about some of the most active research areas in mathematics. Each day of the conference features ten 20-minute talks. The short talks will allow graduate students and early-career researchers to present their work. The conference will also provide several informal sessions for researchers to interact outside of the talks in order to help researchers build networks of people with similar interests. The subject of the conference is combinatorics, probability, and the interactions between these two fields. Among the topics are permutations and random walks. The conference focus is on building connections and encouraging interactions between the probability and combinatorics communities. The meeting website is at https://www.coinflippers.org/coin-flippers-2025 This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NIH Research Projects · FY 2026 · 2025-06

PROJECT SUMMARY Organic molecules play an important role in research areas relevant to human health, including biology, medicine, and drug development. One of the main goals of synthetic organic chemistry is to facilitate discovery in these fields by providing access to organic molecules of increasing complexity and variety, and by expanding our ability to efficiently manipulate their structure and other properties. As a result, the development of new organic transformations is a critically important goal of organic chemistry with implications to other research areas relevant to human health. We plan to develop new catalytic transformations for alkene synthesis by exploring the reactivity of organoboron compounds in the presence of transition-metal catalysts. The proposed transformations will also directly address enduring challenges in organic synthesis, such as cross- nucleophile coupling, stereocontrol in synthesis of highly substituted alkenes, two-carbon homologation, and C-C bond activation. Once successfully developed, these transformations will greatly facilitate access to complex alkenes from a wide range of common precursors. Considering the importance of alkenes as reactive intermediate in organic chemistry, this will have significant impact on the synthesis of biologically relevant compounds.

NSF Awards · FY 2025 · 2025-06

This Faculty Early Career Development Program (CAREER) grant funds research, education, and outreach initiatives that will enable autonomous systems, such as robots and self-driving vehicles, to navigate safely around humans. As these technologies become integral to transportation, warehouse logistics, and healthcare, ensuring human safety is paramount. The complexity of real-world environments, however, are shaped by complex and uncertain factors such as social behaviors and contextual cues, which presents significant challenges in assessing and guaranteeing safety. The research activities funded by this award will intend to develop interpretable, data-driven safety models that are crucial for explaining safety incidents and related human perceptions in environments where autonomous systems operate. These models are intended to enhance predictability, improve operational efficiency, and minimize safety risks, thereby optimizing human-system interactions. Educational and outreach efforts funded by this award include collaboration with Harborview Medical Center to deploy safety algorithms in hospital environments, improving patient care. Additional, educational curricula will be enriched with practical safety experiences to enhance pre-engineering math courses at Shoreline Community College. These initiatives will prepare future innovators and regulators to develop and manage trusted autonomous systems. Determining the safety of given scenarios, or the “safety landscape,” involves challenges from uncertainty, social norms, contextual cues, and feedback interactions. The safety-critical nature of human-robot interactions requires data-driven models to be interpretable for regulatory compliance, explainability, and predictability. This research develops a data-driven framework with control-theoretic foundations to address these complexities and provide clear outputs for decision-making and control. The research encompasses three thrusts: (i) data generation, designing systems for collecting safety-critical data; (ii) analysis and modeling, using control-theoretic techniques to decode complex interactions; and (iii) control synthesis, creating socially-aware strategies for safer interactions. The data-driven framework will be evaluated using public human navigation datasets, simulated human-in-the-loop experiments, and real-world testing at a hospital research facility. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NIH Research Projects · FY 2025 · 2025-06

PROJECT SUMMARY To End the HIV Epidemic in the US, we must transform care quality and access in prisons. People who are incarcerated in state prisons face a disproportionate burden of HIV and HIV risk. More than 65% of people in prison have a substance use disorder (SUD), 4 times that of the general population. To treat and prevent HIV in this population, addressing substance use is central—it is a barrier to HIV prevention and engagement in HIV treatment. Research on HIV prevention and SUD among justice-involved groups has focused on jails and community-based services after release, and there has been little attention to prison systems in large, rural states. The focus on shorter jail sentences and post-release services misses that the foundation for successful HIV treatment, HIV prevention, and SUD recovery after release can be laid during incarceration, particularly for people who may be difficult to reach in the community. The objective of this work is to build foundational knowledge on how to strengthen prison health systems to address disparities in HIV treatment, HIV prevention, and SUD treatment. High-performing healthcare systems, such as the Veterans Health Administration (VA), are Learning Health Systems. In Learning Health Systems, researchers partner with clinical leaders and health systems to improve the quality, efficiency, and reach of care while generating generalizable knowledge on care delivery to inform other systems. This project—embedded in Washington’s state prisons—will develop a novel model of a Prison Learning Health System. To build a Learning Health System across Washington’s 11 state prisons, this project will include four key innovations: 1) Build the foundation for a Learning Health System, including key quality metrics and a patient advisory board that will guide research; 2) Define gaps in care access for key conditions (HIV, HIV risk, hepatitis C, opioid use disorder, and stimulant use disorder) by modeling care cascades; 3) Measure patient experience in prison health care, a foundational measure of care quality and engagement; and 4) Work with prison stakeholders to develop and implement strategies to close HIV and SUD care gaps. Overall, this work will launch a trajectory of research to improve care quality while generating knowledge that can inform service delivery in prisons across the country. The trauma and chronic stress of prison are undoubtably harmful to health, but centering HIV and SUD care during incarceration is one step in both Ending the HIV Epidemic and creating a more rehabilitative criminal legal system.

NSF Awards · FY 2025 · 2025-06

The Siberian Arctic ecosystem is experiencing significant changes due to increasing freshwater input, changes in water mass distribution, and varying anthropogenic pressures. This proposal integrates key microscale biogeochemical (MPs, trace metals) and food web (phytoplankton, zooplankton, and the microbial loop) components, to provide an understanding of how these environmental processes interact and impact ecosystem services (e.g. productivity) within the region. The observations will be conducted on the planned for the Nansen and Amundsen Basins Observational System (NABOS) cruise. Key advancements include determining the role of riverine inputs in delivering trace nutrients and MPs to Arctic seas, how sea ice processes dictate the distribution of these elements and compounds, and how these influences control net ecosystem productivity and lower trophic level species composition. This research will provide novel, full water column measurements of trace metals, MPs, and lower trophic level dynamics, including species composition, phytoplankton pigments, total and active cell abundances, net microbial productivity and respiration rates in the East Siberian and Laptev seas. Specifically, we will assess the sources and sinks of trace metals (Fe, Mn, Cu, Ni, Cd, Zn, Pb) and MPs in the coastal Arctic marine ecosystem; describe microbial (bacteria, phytoplankton) species composition and metabolism across varying biogeochemical and salinity regimes; assess phytoplankton taxonomic composition, physiological health, and productivity; and quantify MP microbial colonization and ingestion by zooplankton. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NSF Awards · FY 2025 · 2025-06

The Committee on New Researchers of the Institute of Mathematical Statistics will hold its 25th conference at Vanderbilt University during the three days prior to the Joint Statistical Meeting. The event will include oral and poster presentations by new researchers, plenary talks by established researchers, and open discussions on future directions for statistics, probability, and data science. There will also be panel discussions on teaching and mentoring, publishing, funding, and collaborations. The New Researchers Conference is an annual event organized under the auspices of the Institute of Mathematical Statistics by its Committee on New Researchers. It serves as the flagship meeting for early-career researchers in statistics, probability, and data science. In 2025, Vanderbilt University will host the 25th New Researchers Conference on the three days prior to the Joint Statistical Meetings. The primary objective of the conference is to provide a platform for interaction among new researchers and offer opportunities for mentorship from leaders in the field. This conference is explicitly aimed at developing the next generation of researchers in statistics and probability. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NSF Awards · FY 2025 · 2025-06

This project is about understanding the effect of content generated by large language models (LLMs) on people whose jobs involve assessing information online. Though LLMs have many potential uses, there are no guarantees that their outputs are correct: they sometimes "hallucinate" false text and/or can be tricked by cyber-attackers into doing so. This in turn poses risks to online information exchange. This project's goal is to model the risks that LLMs pose toward effective online discourse and develop tools to help information professionals assess LLM-generated online content. Through studying a variety of professional roles that interact with many different kinds of content, the research will create generalizable models of information risks posed by LLMs, as well as methods and tools for creating community-specific guides for assessing and managing LLM content risks. These tools, combined with planned educational and outreach activities, will help information professionals do more informed, effective work and benefit the roles and communities they serve. The research plan starts with activities aimed at understanding the challenges that arise for information professionals with the increasing use of LLM-based content. Through interviews, co-design activities, and surveys across a variety of information-focused professions, the research team will develop an epistemological framework to characterize information risks posed by the use of LLMs. This framework will then be used to develop both proactive and reactive approaches to assessing and detecting risky LLM use. To support proactive planning, the researchers will develop threat modeling and red-teaming techniques that allow individual information professionals to assess the risks that arise in their own jobs and communities. To support reactive detection, the team will create customizable, mixed-initiative intelligent tools for identifying potential risky LLM-generated content that are well-tuned to their particular context and epistemic practices. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NSF Awards · FY 2025 · 2025-06

This REU Site award to the University of Washington, located in Seattle, WA, will support the training of ten students for nine weeks during the summers of 2025-2027. The rapid advances in genome engineering and sequencing technology have propelled biological research and its commercial applications forward. Genome-scale technologies have transformed medicine, agriculture, energy production, and information technology resulting in many job opportunities for students pursing technology development and computational biology. At the REU Site: Novel Genome-Scale Technologies and Big Data Science, undergraduate students will witness and experience research at the forefront of technology development in genomics and proteomics. This experience will uniquely prepare them for the competitive marketplace of ideas and provide skills that are applicable in a wide range of fields, including biology, computer science and engineering. Their newly acquired skills will benefit the much needed workforce development for the emerging bioeconomy. The students will learn how rigorous research is conducted, and many will present the results of their work at scientific conferences. Assessment of this program will be done through external tools (e.g., Qualtrics). Students should apply to the REU site using NSF ETAP (Education and Training Application: https://etap.nsf.gov). This nine-week program will introduce participating students to leading researchers in technology and algorithm development in biological research and enable them to become involved in the wide range of research questions, applications, and career opportunities that are accessible through Big Data science. The guided hands-on research experience combined with intense instruction in computational biology will empower participants to formulate their own inquiries and exercise their curiosity. Example projects include developing new technologies to probe spatial relationships in human genomes, CRISPR-aided cell lineage tracing in animals, and long-read technologies to understand the gene-regulatory activity of transposons in maize. A series of workshops led by experienced instructors will teach participants strategies to communicate their scientific knowledge, ideas, research findings, and personal journeys to a variety of audiences, including admission committees at STEM graduate programs and recruiters in industry. Each year results from the program assessment will be used to continually improve and refine the program design and student experience. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NSF Awards · FY 2025 · 2025-06

Research on human neuroscience helps unlock knowledge of how healthy brains function as well as enabling greater understanding of brain disease mechanisms. The MNE-Python project, a software tool for analyzing human neuroscience data, has a focus on preparing new maintainers to contribute to the project. The project supports MNE-Python's thousands of clinical, industrial, and scientific users. The project also creates user-facing educational materials, a key development to nurture the growth of the next generation of maintainers. These actions ensure that neuroscience researchers, clinicians, and engineers have ongoing, sustainable support for the software tools they rely on. This project, funded by the Pathways to Enable Open-Source Ecosystems (POSE) program, addresses a common challenge in developing open-source software: how to recruit and retain enough skilled volunteers to keep a project vibrant. This challenge is especially difficult given high volunteer turnover rates and a dynamic hardware and software landscape. MNE-Python seeks to grow the maintainer team and create resources to support future growth. Developers learn how to triage incoming submissions and support requests, optimize code, test the software, and develop solutions. The project also automates some of the more repetitive tasks included in the developer role, such as triaging issues and reviewing submissions, by automatically monitoring and responding to new issues and submissions. This award helps current and future maintainers become more efficient thus ensuring the long-term sustainability of MNE-Python. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NSF Awards · FY 2025 · 2025-06

This project aims to help advance the field of semiconductor manufacturing by addressing a critical challenge in extreme ultraviolet (EUV) photolithography, a technology essential for creating the next generation of integrated circuits with features smaller than 10 nanometers. EUV photolithography is a process used to pattern extremely small features on silicon wafers, which are the building blocks of electronic devices. In this project, development of new photoresists will be carried out. These photoresists are light-sensitive materials used to form a patterned coating on a surface. To develop these photoresists, fundamental studies will be performed to learn what chemical reactions take place when these photoresists are exposed to light. By improving these materials, the project seeks to enhance the effectiveness of EUV photolithography, thereby supporting the growth of the semiconductor industry. This advancement is crucial, as it will enable the production of smaller, faster, and more efficient electronic devices, which are in high demand in today's technology-driven world. Additionally, the project includes educational initiatives to inspire and prepare students for careers in the semiconductor industry. These efforts align with the goals of the US CHIPS Act, which aims to strengthen the domestic semiconductor workforce. During the two-year funding period, this proposed research will uncover the mechanisms behind the crosslinking and chemical etching of ultrathin photoresist films grown by molecular layer deposition (MLD), a vapor-phase method for depositing ultrathin organic-inorganic films with precise control over thickness and composition. Experimentally, the project will uncover process-structure-property relationships by varying the reactants used in the MLD process, leveraging a high-throughput MLD reactor to create a library of aluminum-based EUV photoresists with a variety of organic functional groups of varying photoreactivity and likelihood of forming crystalline structures. These films will be thoroughly characterized to determine the resulting films’ chemical composition, thickness, and surface morphology before and after photopatterning with UV and e-beam sources. This effort will be paired with reactive molecular dynamics computational modeling to further understand film photoreactivity and organic reactant alignment during deposition. This combined experimental and computational approach aims to create a map of the structure of these photoresist films, which will be used to gain insights into the factors that influence strong EUV photoresist performance, supporting the broader adoption of EUV photolithography. This effort represents a significant technological advancement, as the limited existing work in the use of vapor-deposited EUV photoresists has largely focused on proof-of-concept patterning with new elements. Exploiting this library, we will perform convergence research, constructing an experimental model of these organic-inorganic films and comparing it to a computational model constructed through ReaxFF molecular dynamics simulations. This Future Manufacturing award is co-funded by the Divisions of Materials Research (DMR) and Chemistry (CHE) in the Directorate for Mathematical and Physical Sciences (MPS), and the division of Electrical, Communications and Cyber Systems (ECCS) in the Engineering Directorate (ENG). This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NIH Research Projects · FY 2025 · 2025-06

The University of Washington (UW) Eunice Kennedy Shriver Intellectual and Developmental Disabilities Research Center (IDDRC), based at the Institute on Human Development and Disability (IHDD), provides a comprehensive interdisciplinary program of basic and translational research designed to prevent, diagnose, and treat individuals with intellectual and developmental disabilities (IDD). Research is carried out within the framework of the following eight Collaborative Research Areas (CRAs): (1) Biological Basis of Autism; (2) Brain Malformation Disorders; (3) Central Nervous System Injury; (4) Consortium on Early Childhood Intervention; (5) Developmental Toxicology; (6) Epilepsy; (7) Hearing Disorders, and (8) Learning Disabilities. All CRAs are interdisciplinary, include scientists, clinicians, and trainees and are designed to promote translational research. In this application, to facilitate the work of investigators at our IDDRC, we are requesting support for an Administrative Core designed to provide scientific and programmatic leadership and four scientific cores: (1) Genetics -- functional and human genomics and model system components; (2) Brain Imaging – in vivo imaging for human studies and animal models; (3) Animal Behavior – behavioral testing for rodent models and consultation for non-human primate models and application of circuit mapping techniques; and (4) Clinical Translational -- promotes and supports clinical and translational research. We are also proposing to conduct a research project focusing on a unique cerebellar malformation utilizing comprehensive omic approaches that are well integrated with cores and other IDDRC activities. Extensive research training and dissemination activities are also integral components of our IDDRC.

NSF Awards · FY 2025 · 2025-06

The objective of this project is to support the effort in deepening and expanding research alliance on complex cyber-physical infrastructure systems. More specifically, the project conducts two workshops on the topic of enhancing resilience of cyber-physical infrastructure systems in the era of AI. The workshops focus on just-in-time resilience innovations that can be flexibly implemented with available resources. They aim to generate new perspectives toward resilience; new concepts on future models and tools powering infrastructure design, development, and operation; and new market mechanisms capturing hidden capacity within existing assets. Research alliance promotes science, and advances health, prosperity and welfare. By collaborating with Singapore and other allies, the US is well positioned to leverage technologies that have been already developed and tested or are emerging. The workshops are organized around four themes: 1) adaptive capacity of real-world systems; 2) optimizing demand forecasting and service provision; 3) urban designs in an uncertain time; and 4) resilience of the people. Novel real-world case studies are showcased while project ideas and mini proposals are prepared. In addition, workshop outputs form the roadmap for informing future joint funding opportunities. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NSF Awards · FY 2025 · 2025-06

The PIMS-CRM Summer School 2025 will be a great opportunity for graduate students and junior researchers from the US to learn about some of the most active research areas in probability from top experts in the field. The PIMS summer schools in probability theory were launched in 2004, and this will be the 10th school. These summer schools have made an impressive name for themselves and have a proven track record of fostering long-term collaborations between the participants. Past participants have become current academic faculty, able to spread their knowledge further in the research community. The participants will learn the current techniques in cutting-edge areas of probability. It is expected that the participants will engage in active research on some topics covered by the main courses and related areas, and many will give presentations on their current research. The expansive scope of the school (4 weeks, about 100 participants) has academic significance: the courses are able to go into much greater detail than courses in shorter summer schools, and participants are much more likely to form new collaborations. The summer school website is https://secure.math.ubc.ca/Links/ssprob25/ This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NIH Research Projects · FY 2025 · 2025-06

Project Summary/Abstract Millions of homebound patients receive nursing and rehabilitation visits from home health agencies (HHAs) annually, with goals of improving patient function and facilitating successful discharge to the community while avoiding adverse events like falls and inpatient admissions. However, there is minimal evidence to guide HHAs on which care delivery practices will improve patient outcomes, especially for patients with different clinical needs. Three aspects of home health care delivery that are both measurable and modifiable by HHAs include visit mix (e.g., the proportion of physical therapy visits versus nursing visits), service intensity (i.e., the number of visits per week), and visit distribution (i.e., frontloading visits early in the episode versus spreading visits over a longer period). However, there is no comprehensive understanding of the relationships between these practices and patient outcomes. To fill these gaps, we will take a learning health systems approach and partner with a large non-profit company serving over 150,000 patients annually in 23 states to conduct a secondary analysis of 2020 – 2025 data to achieve these aims: 1. Examine relationships between home health care delivery practices (i.e., visit mix, service intensity, and visit frontloading) and patient outcomes (i.e., successful discharge to the community, change in function from admission to discharge, transfer to inpatient facility, injurious falls); 2. Determine if relationships between each home health care delivery practice and patient outcomes differ for patients with different clinical needs. Clinical needs will be based on whether patients primarily require home health for neurologic or musculoskeletal rehabilitation, medication management, behavioral health care, complex nursing interventions, or wound care. Due to the rise in value-based healthcare initiatives that prioritize care quality alongside efforts to lower costs, HHAs are increasingly being held financially accountable for patient outcomes. However, without adequate patient-centered guidance on how to improve outcomes, HHAs are left with cost reduction as the primary strategy to improve the overall value of home health care. We will leverage our unique health system partnership and the lived experience of our advisory committee to examine outcomes across payers and types of home health stays (i.e., admitted to home health post-hospital versus directly from the community) to provide a novel and comprehensive understanding of how care delivery practices impact outcomes. Results from this proposal will help drive patient-centered health system innovation leading to high-quality rehabilitation and nursing practices that generate optimal patient outcomes with the potential to inform care delivery practices for all patients receiving home health nationwide.

NIH Research Projects · FY 2025 · 2025-06

PROJECT SUMMARY/ABSTRACT This is an application to NOSI NOT-DC-24-010 Tackling Acquisition of Language in Kids (TALK) R01 Research Projects. Delayed language emergence in the absence of other cognitive or developmental concerns occurs in approximately 10-20% of children, often referred to as “late talkers”. Past research has shown that starting intervention earlier, such as in the first year of life, leads to more optimal language and learning outcomes. However, the identification of infants at a higher likelihood of language delay that would benefit from intervention remains challenging. In this proposed project, we investigate whether early auditory brain or behavioral measures can serve as prognostic predictors of later language outcomes. We will follow infants longitudinally and obtain measures of auditory and linguistic abilities at 5 timepoints: 3, 6, 11, 18, and 30 months of age. Of these infants, half will be at a low likelihood (LL; 10-20% risk) of having late language emergence and half will have additional risk factors that will put them at a higher likelihood (HL; >20% risk) of late talking. At 3, 6, and 11 months of age, we will measure auditory brain responses to speech using electroencephalography. A 3, 6, 11, and 18 months, we will obtain a comprehensive assay of cross-domain development including auditory skills, receptive and expressive language, cognitive, motor, and adaptive behaviors. At 30 months, we will conduct a thorough language assessment including standardized assessments, a natural language sample, and parent-reports of language and general development. Demographic and environmental variables with potential influence on language outcomes including parental education, socioeconomic status, as well as parental stress and adversity will also be obtained to provide necessary context for data interpretation. In Aim 1, we will characterize the developmental trajectory for auditory brain responses to speech at 3, 6, and 11 months. In Aim 2, we will characterize the developmental trajectory for early auditory and language abilities at 3, 6, and 11 months and examine trajectory relationship with outcomes at 18 and 30 months. In Aim 3, we will identify brain and behavioral measures that best predict 18- and 30-month language outcomes. This proposed research addresses two TALK initiative objectives: 1) to advance our understanding of optimal measures for differentiating developmental trajectories of children at high and low likelihood of late talking, and 2) to reveal early brain and behavioral markers of language delay that may be evident in the first year of life. These results will determine whether language screening in infancy is clinically feasible and if successful, has the potential to lead to improved identification of infants at a higher likelihood of late language emergence, allowing for earlier intervention and prevention.

NIH Research Projects · FY 2025 · 2025-06

Hurdles for controlling tuberculosis (TB) include developing a highly efficacious vaccine, preventing transmission and infection in endemic areas, and discovering drug treatment regimens that work rapidly and kill dormant bacilli within macrophages. After exposure to Mycobacterium tuberculosis (Mtb), outcomes vary widely including resistance, asymptomatic latent infection, active pulmonary disease, and disseminated infections including TB meningitis (TBM). This heterogeneity complicates clinical treatment decisions with regards to choosing the number of drugs and duration of treatment. This broad clinical spectrum also presents a unique opportunity for understanding the biological mechanisms that control TB pathogenesis. A major source of heterogeneity is a combination of genetic variation in both humans and Mtb that are evolving under constant selective pressure. Our overall program objective is to use genetic, genomic, proteomic, and bioinformatic strategies to discover host and pathogen variants of genes and gene products that are associated with TB clinical outcomes and to determine how these variants interact to regulate molecular, cellular, and in vivo functions. Our strategy is anchored upon two powerful cohorts in Vietnam and Uganda (Core A) that capture the full spectrum of resistance to traditional LTBI (latent TB infection), LTBI, pulmonary TB disease, and disseminated disease in the form of TBM. Core A examines paired host and Mtb genetic data and the association with these diverse clinical outcomes. In Project 1, we use genetic and new proteomic strategies to examine how the Mtb genes and variants identified by Core A function and how the encoded proteins interact with and regulate macrophage responses. In Project 2, we use human genetic methods along with proteomic strategies in macrophages to uncover regulatory host genes and variants that are associated with resistance to Mtb infection and/or disseminated TB. In Project 3, we examine in vivo mechanisms of transmission and dissemination that are attributed to specific host genes and pathways and Mtb variants, employing a new and powerful mouse model of infection that recapitulates many of the manifestations that occur in human TB. Core B uses pathway-driven and novel bioinformatics approaches to integrate the genetic results from Core A with the multiple large-scale and diverse datasets to dynamically identify and prioritize pathways and protein networks for functional testing. Together, this multidisciplinary program and strategy will enable us to test our overall hypothesis that variants of Mtb and host genes dictate heterogeneous clinical outcomes and encode factors that interact with and alter innate immune cells. We will use genetic, genomic, proteomic, and bioinformatic strategies to examine variation in Mtb and its paired human host to examine mechanisms of resistance and susceptibility to infection and disease with discovery of biomarkers for clinical management and novel immunomodulatory therapies.