University Of Washington

NIH Research Projects · FY 2025 · 2025-05

Project Summary/Abstract Stem cell (StC) treatments have enormous potential to restore function after chronic spinal cord injury (SCI) due to their regenerative potential. These cells provide trophic factors that support neurite outgrowth and replace lost cells through differentiation into neurons and glia. Despite many encouraging advances, StC therapies still face severe limitations, including the negative effects of the lesion environment on transplanted cells and insufficient integration of differentiated neurons and glia into existing neural circuits. Consequently, StC therapies have produced only modest behavioral improvement in animal studies and human trials for SCI. Several forms of electrical stimulation (ES) have led to improved function after SCI in animals and humans with partial SCIs. These include repetitive stimulus pulses delivered epidurally or intraspinally, and with either open- or closed-loop protocols. These approaches have led to improved motor and autonomic function by promoting neural plasticity in spinal and descending pathways. Electrical polarizations using either direct or oscillating field stimulation can reduce inflammatory responses, facilitate myelin regeneration, enhance neuronal excitability, and cause directed axonal growth. The effects of StC and ES therapies seem complementary. However, there are few studies that have combined StC transplants and any form of spinal ES as a treatment for SCI, and therefore it is not known if the two approaches can magnify or interfere with the rehabilitative benefits and potential of each. The objective of the proposed project is to begin an exploration of the interaction of these two promising treatments. The study will begin a new line of research whose long-term goal is to develop novel combinatorial therapies that will advance clinical practice and improve the quality of life of individuals living with SCI. We will study a rat model of contusive injury of the cervical spinal cord, and transplant rat embryonic neural stem cells derived from the spinal cord since these cells adopt normal motor and sensory fates and support regeneration in animals with SCI. We will apply three different forms of ES that in previous studies have improved the behavior of animals and/or humans with chronic SCI. Our primary goal will be to determine if ES supports the survival and differentiation of StCs, enhances the growth over long distances and synapse formation of axons of new neurons, and promotes the integration of the differentiated cells into spared neural circuits. We will also investigate whether the combined treatments produce improvement in the rats’ motor performance, although the scope of an R21 project will limit our ability to study this issue in depth. If the project is successful, future studies will focus on whether combined StC-ES therapies provide improvements in function beyond that achieved by each treatment alone.

NIH Research Projects · FY 2026 · 2025-05

PROJECT SUMMARY/ABSTRACT Understanding incentive salience for alcohol cues—a “wanting” of alcohol driven by a strong association between alcohol-related cues and a reward—is of critical importance for understanding the etiology of alcohol use disorder (AUD). Enhanced incentive salience for alcohol cues is among the more powerful and immediate precipitating factors driving alcohol use and, over the longer term, has been implicated in development of AUD. Thus, understanding incentive salience for alcohol has emerged as a research priority within addiction science. While studies utilizing fMRI and EEG to investigate incentive salience have consistently identified heightened incentive salience for alcohol as a neural marker of problem alcohol use, these neuroimaging investigations have exclusively measured incentive salience devoid of context. Consequently, there is a critical gap in understanding how this individual-level marker unfolds in real-world settings, where individuals are exposed to a diverse array of alcohol-related stimuli. Therefore, whether incentive salience, as measured via laboratory neuroimaging methods, holds genuine relevance to alcohol use behaviors in individuals’ everyday life remains unknown. The proposed research aims to fill this gap in the literature by leveraging a combined laboratory-ambulatory study design, in a sample of young adult heavy drinkers. More specifically, we will characterize the brain-behavior mechanisms of incentive salience driving alcohol use behaviors in everyday life. Here we extend beyond the laboratory, utilizing not only fMRI and ERP measures of incentive salience but also ambulatory biosensor technology to capture alcohol use behaviors in real world context. Further, in line with NIAAA’s stated goal to examine “how alcohol-related neurobiological and behavioral phenotypes interact with the environment to affect alcohol-related outcomes” (NIAAA Strategic Plan 2017-2021), we will examine how features of everyday drinking contexts may moderate the relationship between incentive salience and alcohol use levels. To achieve this end, the proposed study will utilize innovative ambulatory photograph methods to better characterize the physical and social context of drinking. As an important step toward a contextually-informed, yet mechanistically precise model for understanding AUD etiology, the proposed research has multiple critical implications. In the conceptual realm, findings will inform theoretical models of AUD (e.g., incentive sensitization theory) that may strengthen our understanding of mechanisms underlying AUD development and maintenance. In the clinical realm, findings will inform assessment, prevention, and intervention efforts, by refining the understanding of both individual- and contextual- level risk factors for problem drinking in real-world settings. Finally, in the methodological realm, the proposed research offers a novel experimental paradigm to alcohol researchers, by leveraging the mechanistic precision of neuroimaging techniques and the ecological validity of ambulatory momentary assessment.

NIH Research Projects · FY 2026 · 2025-05

PROJECT SUMMARY/ABSTRACT Nonmedical use of prescription stimulants (NMPS) is most common among college students (American College Health Association, 2023). NMPS has been associated with unwanted physical effects, sleep issues, and lower GPA and is a marker for cannabis and alcohol use; up to 90% of adolescents and young adults who engaged in past-year NMPS report using other drugs, particularly cannabis (Faraone et al., 2020; Kilmer et al., 2021; McCabe et al., 2006b; NIDA, 2014). We test specific mechanisms of a high-risk feedback cycle of the maintenance and escalation of NMPS, based on a novel framework grounded in the previous literature, with a focus on alcohol use, cannabis use, and sleep difficulties (all of which are key public health concerns), and academic stress. NMPS may be a compensatory behavior among those experiencing academic issues, which may have resulted from cannabis/alcohol use and concomitant inconsistent class attendance (Arria et al., 2013b). This feedback cycle operates continuously (not just during finals); therefore, it is critical to test the mechanisms of the proposed feedback cycle across the entire academic quarter. Intensive longitudinal research (e.g., weekly and daily surveys) is needed to best inform this important public health issue and provide a critical, in-depth examination of how weekly fluctuations in academic and sleep issues may contribute to NMPS and how daily fluctuations in alcohol use, cannabis use, and caffeine use may increase an individual’s vulnerability. This R01 application will provide a critical, in-depth examination of the feedback cycle focusing on NMPS, substance use, academics, and sleep. This project will recruit 300 college students (ages 18-25) who report (a) NMPS 5+ times in the past 12 months and (b) 4+ days of alcohol and/or cannabis use in the past 30 days. Across two academic quarters, participants will complete 22 weekly online surveys as well as two 21-day bursts of online morning surveys (corresponding with Fitbit sleep data). The aims are as follows. Aim 1: Using weekly data, examine how the strength of the associations between the key components of the feedback cycle vary as a function of time across the quarter. Aim 2: Using weekly data, test specific mechanisms of the feedback cycle at the week level to identify which factors of the feedback cycle, when elevated, confer heightened risk in a given week. Aim 3: Using daily data, test specific mechanisms of the feedback cycle at the day level to identify which factors of the feedback cycle, when elevated, confer heightened acute risk on a given day. Exploratory analyses will examine baseline moderators: class standing, sex assigned at birth, gender, fraternity/sorority membership, symptoms of alcohol use disorder, symptoms of cannabis use disorder, impulsivity, and sensation seeking. This application can inform our knowledge of the behavioral mechanisms that contribute to substance use and will lead to refined interventions for students who use multiple substances, enhancing our ability to target specific aspects of the feedback cycle.

NIH Research Projects · FY 2026 · 2025-05

ABSTRACT The Ending the HIV Epidemic (EHE) Initiative has an ambitious goal of a 75% reduction in new HIV infections in the US by 2025, and a 90% reduction by 2030. To meet these targets, progress will be required across all four EHE pillars (diagnosis, treatment, prevention, and response), and across all 57 Phase I EHE jurisdictions. Implementation science, with a focus on improving the delivery of evidence-based interventions at scale, has the potential to catalyze EHE investments by identifying how to deliver interventions and contribute to the EHE targets. The Research Alliance in Implementation Science to End HIV (RAISE) Regional Consultative Hub (RCH) was founded in 2022 with supplemental EHE funding to the University of Washington/Fred Hutch Center for AIDS Research with the objective of maximizing the impact EHE investments through the support of EHE-funded implementation science efforts in priority jurisdictions. Our application leverages the depth and breadth of implementation science capabilities and training opportunities at the University of Washington and the National Alliance of State and Territorial AIDS Directors (NASTAD). The RAISE team is ideally situated to continue to link implementation science research with public health programs to enhance the impact of EHE. Our faculty is at the forefront in defining multidisciplinary, implementation science research methods, and has developed novel training curricula in public health and implementation science. Furthermore, RAISE-affiliated investigators lead diverse programs to implement and scale-up HIV prevention and treatment interventions that have developed strong, collaborative relationships with health departments throughout the U.S. Our proposed activities are designed to enhance the impact of EHE investments through building timely and appropriate implementation science capacity, fostering academic-public health collaborations, developing generalizable knowledge on effective implementation strategies, and meeting EHE reporting requirements. The RAISE hub proposes three aims to achieve the project goals. First, to provide implementation science consultation services to select NIH- supported EHE research projects and support these projects to meet funding reporting requirements, develop effective dissemination strategies, and foster cross-site research opportunities. This aim will leverage our implementation science expertise and existing training curricula in study designs; selection and development of implementation strategies; implementation science theories, models and frameworks; implementation outcome selection and deployment; economic evaluations; and health department/academic research partnership development. Second, in conjunction with NASTAD, to strengthen and expand the RAISE implementation science learning platform that links health departments with implementation researchers to foster relevant and robust research that is responsive to health department needs and enhances the impact of their implementation efforts. Third, also in conjunction with NASTAD, foster improved implementation of local HIV treatment services in EHE jurisdictions through the establishment of two 18-month learning collaboratives.

NIH Research Projects · FY 2026 · 2025-05

PROJECT SUMMARY Humans have limited regenerative potential after extensive musculoskeletal injuries, particularly following limb loss. As such, the ability to biologically restore the missing limb will significantly improve the quality of life for millions of amputees. To this end, the murine digit has emerged as a powerful pre-clinical model to investigate potential mechanisms for mammalian limb regeneration. Previous studies showed that combined delivery of bone morphogenetic protein 2 (BMP2) and BMP9 to amputated digits stimulated skeletal elongation and cartilage/synovial joint regeneration, respectively. This suggests that presenting appropriate soluble cues to endogenous cells at the amputation site can restore key signaling pathways involved in limb morphogenesis. However, these studies relied on multiple surgeries to deliver proteins in a time- and location-dependent manner, which would be clinically challenging. Therefore, the overarching goal of this Trailblazer Award proposal is to develop a translational strategy to sequentially deliver BMP2 and BMP9 and assess its potential to spatiotemporally control bone and joint formation after digit amputation. To direct protein release towards specific regional compartments, we will engineer BMP2- and BMP9-releasing micron-sized hydrogels (‘microgels’) that can be co-delivered as a single injection and then separated in vivo using an externally applied magnetic field. We will test the central hypothesis that spatiotemporally delivering BMP2 and BMP9 using magnetic microgels will promote progenitor cell-mediated regeneration of bone followed by articular cartilage after digit amputation. To test this hypothesis, in Aim 1 we will fabricate and evaluate bioactive magnetic field-responsive microgels in vitro. In Aim 2, we will probe the in vivo therapeutic effect of microgel-mediated growth factor delivery to non- regenerative amputated digits in adult mice. By developing a novel biomaterial delivery platform to release multiple growth factors in a localized and tunable fashion, this Trailblazer Award proposal will open new avenues to therapies that will help restore the biological composition and structure of complex musculoskeletal tissues. More broadly, this innovative technology may find widespread application for treating commonly injured tissues that regenerate via outgrowth, including spinal cord, peripheral nerves, vasculature, as well as engineering composite tissue interfaces that require modular and user-controlled chemokine gradients, such as the tendon enthesis.

NIH Research Projects · FY 2026 · 2025-05

ABSTRACT: Background: Cytomegalovirus (CMV) is a highly seroprevalent human herpesvirus (HHV) of particular clinical significance in the immunocompromised patient population. Solid organ transplant (SOT) from a CMV-infected donor (D+) to a naïve recipient (D+/R-) leads to a unique mechanism of primary CMV infection in ~80% of recipients. CMV disease, such as pneumonitis, retinitis, or primary CMV syndrome, occurs in ~30% of patients, most commonly after cessation of antiviral prophylaxis after day 100. The immune mechanisms of protection from disease risk in this scenario are not known, but this risk was reduced to 10% in a randomized, controlled trial of pre-emptive therapy vs prophylaxis in orthotopic liver transplant (OLT) (CAPSIL study). Pre-emptive therapy, where viremia is monitored and treated only when it reaches above pre-specified levels, is thought to enable the development of immunity in the early post-transplant period. Evaluation of participant samples from the CAPSIL study showed increased CMV-specific CD4 and CD8+ T cells, expression of markers of terminal differentiation in the T cell and NK cell populations, and neutralizing antibody (nAb) levels in patients managed with pre-emptive CMV therapy. A clinically useful measure of risk of CMV disease is urgently needed to guide efforts at prevention. Summary of Proposal: We propose here to identify the factors of the humoral CMV response most correlated with CMV disease risk and combine this with quantification of the CMV-specific T cell repertoire by T cell receptor (TCR) sequencing and sequence-similarity methods. The Central Hypothesis is that a measure of immunity inclusive of both humoral and cellular factors will be most informative to predict disease risk. Rationale: While nAb levels, thought to substantially reflect antibodies specific to CMV surface pentameric complex, are seen to be increased in patients treated pre-emptively for CMV, gB-binding antibody levels are a known correlate of protection in primary, natural infection. Antibodies preventing cell-to-cell viral spread may also be influential. Elucidation of the mechanism by which CMV nAb levels correlate with disease risk in D+/R- OLT is needed. Prior to CAPSIL, T cell immunity was thought to be the primary mediator of CMV protection in SOT but has not been shown to correlate with disease risk in D+/R- OLT. Intrinsic limitations of T cell assay-based correlates of disease risk, such as lab-to-lab variability, would be improved by use of a sequence-based measure. In Aim 1 we will characterize the neutralizing and non-neutralizing antibody response and map the CMV-specific B cell repertoire in samples from the CAPSIL trial. In Aim 2, we will quantify and characterize the CMV-specific T cell repertoire using TCR sequence-based analysis. We will correlate findings from both Aims with the results from the CAPSIL trial to characterize the immune signatures of CMV disease risk in D+/R- OLT. Together, these aims will inform further CMV disease prevention strategies, the primary goal being identification of persons at high risk of CMV disease who would benefit from prolonged monitoring, or persons at low risk of CMV disease who could safely shorten prophylaxis or monitoring.

NIH Research Projects · FY 2026 · 2025-05

PROJECT SUMMARY/ABSTRACT In the U.S., marked reductions in child lead exposure is noted as one of its greatest public health accomplishments. Core features of successful programs in the U.S. include screening to identify children with higher blood lead levels (BLLs), “healthy home” programs to identify household sources, surveillance, and regulatory policy to remove lead from the environment. Yet lead toxicity remains a major global public health concern, accounting for 63% of the global burden of idiopathic intellectual disability. Evidence is clear that child blood lead levels (BLLs) once considered "safe” (< 10 ug/dL) are linked to compromised cognitive and behavioral development. Among the one in three children with BLL exceeding current WHO guidelines (≥ 5 ug/dL), 90% reside in low and middle income countries (LMICs). Both WHO and UNICEF highlight the need for programs to identify children with higher BLLs in LMICs, including sub-Saharan Africa (SSA), and need for protocols to respond to cases of elevated exposure. We adapt BLL screening and “healthy home” lead prevention program experience in the U.S. for an SSA city context - where BLL testing and follow up protocols are needed most and can leverage the city context to build awareness - and evaluate them in foundational implementation activities in Nairobi. Kenya has promising institutional strength in lead exposure science, and the team leverages a 30-year research collaborative joining the University of Washington and the University of Nairobi. In Aim 1, protocols for a Nairobi-relevant Lead Exposure Intervention Program (LEIP) are developed and refined with input from key stakeholders, then piloted in the team’s ongoing cohort of mother-child dyads in Nairobi (age 24-36 months, N=356). Mother exit interviews inform acceptability and understanding of exposure risk surveys and risk mitigation messaging for further refinement. In Aim 2, the refined LEIP protocol is implemented, providing blood lead testing during routine pediatric care visits at a public Nairobi clinic (N~500 children, age 9-24 month), and two implementation strategies are evaluated. Caregivers of children with BLL ≥5 ug/dL (N=100) will be randomized (N = 50 each arm) to immediate tailored risk reduction messaging alone versus additional home visit for enhanced messaging informed by an observational checklist for home risk factors. Follow-up at 3 and 9 months will include BLL rechecks and assessment of caregiver knowledge and risk reduction behaviors. Aim 3 identifies barriers to lead exposure mitigation and strategies to overcome them, using semi-structured interviews with key persons (provider and policy level) and caregivers (individual level) involved in Aim 2. The project will inform on minimum implementable urban SSA appropriate delivery models, based on approaches reducing lead exposure for millions of children in high income countries for decades, and will identify contextual factors critical for sustainable program success in future iterations. Capacity building activities and data on child BLLs and household lead sources will fill existing critical gaps and stimulate multi-level momentum for policy changes.

NSF Awards · FY 2025 · 2025-05

Below the surface, in the ocean’s “twilight zone” – the water from roughly 150 to 600 meters deep – sinking organic matter from surface waters is consumed by bacteria. The more organic carbon is consumed in the twilight zone, the less sinks to the deep ocean and to sediments. Thus, the activity of bacteria in the twilight zone is an important control on the ocean carbon cycle. In this project, a team of researchers will test the idea that the metabolism of bacteria in the twilight zone may be partly controlled by iron, an essential nutrient. This work will have implications for understanding ocean biology and chemistry. The project will promote workforce development through support of an early career research scientist and a graduate student. The lead investigator will develop a related laboratory module for an undergraduate course based on this work. Preliminary data demonstrate that iron availability impacts the total carbon consumption rate by heterotrophic bacteria in the mesopelagic ocean, and that heterotrophic bacteria in this region of the water column are co-limited by iron and carbon. The team will use a combination of laboratory culturing studies and field experiments to test three related hypotheses about why and how this co-limitation occurs. The experiments will span a range in iron and carbon conditions, will test steady state versus pulse conditions, and will examine varying degrees of carbon lability. The three hypotheses they will test are: H1) Heterotrophic bacteria maintain high iron quotas in steady state conditions in the mesopelagic due to changes in the availability of iron and carbon in the transition from the surface to the mesopelagic and the cellular allocation of iron varies depending on the iron to carbon ratio at steady-state conditions, H2) The high iron quotas maintained by copiotrophic bacteria in the mesopelagic allows them to respond efficiently to pulses of new carbon, and the response is proportional to the quotas established in the steady-state environment, the magnitude of the carbon pulse, and the lability of the carbon substrate, and H3) The composition of organic material and iron homeostasis of heterotrophic bacteria affects total carbon consumption in the mesopelagic. The expected outcomes of the work are an increased mechanistic understanding of how the iron status of heterotrophic bacteria in the mesopelagic ocean impacts their ability to consume organic carbon, and how and why there is widespread co-limitation throughout the upper mesopelagic ocean. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NIH Research Projects · FY 2026 · 2025-05

Project Summary/Abstract: Early perceptual learning is crucial for later language development. A rich, native language environment shapes perceptual development during a critical period, which in turn predicts later language development. To date, most research on the critical period of perceptual development focused on language users who had a rich, early, spoken language environment. Little is known about the perceptual development when the language environment is impoverished, delayed, and visual. Deaf babies often lack a sufficient natural language environment when they do not have signing parents. Such reduced early language experience often results in atypical language and brain development, including reduced perceptual sensitivity. Due to previous methodological constraints, we still know little about the neural mechanisms underlying early perceptual processing in sign languages and how it is affected by lacking sufficient early language. The current study aims to 1) establish a visual mismatch response (vMMR) paradigm in ASL using anatomically constrained MEG, and 2) examine the effect of early language experience on pre-attentive perceptual processing for ASL. We adopt a neural measure widely used with spoken languages, the auditory mismatch responses (aMMR), to the visual domain. We establish the vMMR paradigm by comparing hearing signers and nonsigners’ pre-attentive neural sensitivity to changes between real-signs and fake-signs contrasting only in the handshape in American Sign Language (ASL). We use Magnetoencephalography (MEG) combined with MRI scans to provide better temporal and spatial precision when characterizing the vMMR signals. Once we establish the vMMR paradigm, we will further examine the role of early language experience by testing deaf individuals with varying early language environments: native signers with ASL exposure from birth, early signers with ASL exposure between ages 5 to 7, and severely delayed signers with ASL exposure after age 12. Based on existing literature, we predict increased vMMR, especially when detecting real-signs from fake-signs, by hearing native signers as compared to hearing non-signers, with both modality-specific (parieto-occipital) and modality- general (fronto-temporal) generators. We also predict reduced and/or delayed vMMR by severely delayed signers as compared to deaf native and early signers. We also predict more visual (parieto-occipital) and less language (fronto-temporal) activations by severely delayed signers. This project serves as an important initial step to examine pre-attentive perceptual processing in ASL, furthering our understanding of language development in relation to early language environment and perceptual learning. Findings from the project can also provide guidance to parents and practitioners regarding the early language environment for deaf babies, and also support diagnosis and intervention for deaf children who are at risk of language deprivation.

NSF Awards · FY 2025 · 2025-05

The objective of this project is to support research on deep learning (DL)-based methodologies for discovering the governing equations of traffic dynamics and probing how connected and automated vehicles (CAVs) behave and interact with other road users. With rapid development of artificial intelligence and availability of ubiquitous traffic data, the project aims to transform the methods of learning traffic dynamics from conventional studies to a DL-based automatic paradigm. New traffic dynamics models with CAVs are essential for achieving safety, mobility, and other goals related to future transportation systems. The project team adopts an “open science” approach to encourage collaborations, stimulate interests, and grow research capacity for this important topic. Results are integrated into existing and new courses and provide opportunities for graduate and undergraduate students to participate in cutting-edge research. Findings are broadly shared with transportation agencies, academic communities, and the industry via publications, meetings, and presentations/webinars. This project develops specialized, effective methods for learning traffic dynamics, especially for traffic flow with CAVs, from data directly. This is accomplished by designing new DL structures to address data noises, a coordinated learning framework to deal with the unique features of traffic dynamics due to diverse vehicle classes and/or driving behaviors. Equally important, it formulates new metrics and methods for four essential objectives: accuracy, parsimony, interpretability, and generalizability. Understanding of governing equations of traffic dynamics is fundamental to traffic prediction, transportation planning, traffic management and control. The project thus advances the scientific discovery of new traffic dynamics with CAVs and informs society to better prepare for the wide deployment of emerging technologies. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NSF Awards · FY 2025 · 2025-05

The project supports a workshop addressing the rigor and reproducibility of research conducted in the area of electrocatalysis. Electrocatalysis research has ramped up significantly in recent years as related to energy-efficient manufacture of fuels and chemicals. The workshop is led by Dr. Eric Stuve of the University of Washington, with co-organizers Ezra Clark (Pennsylvania State University) and Liney Arnadottir (Oregon State University). More than 50 experts from the academic community will convene at the University of Washington campus in Seattle on July 8-10, 2025 to determine how research in electrocatalysis can meet the highest standards of scientific inquiry. The participants will include senior, junior, and student researchers from both large and small research groups. Workshop outcomes will be widely disseminated within the research community via a report to NSF and an article in a high-impact catalysis journal. Electrocatalysis is a broad research area of fundamental importance in developing new technologies in clean energy and electrosynthesis. Two key examples are production of green hydrogen by using renewable electricity for electrolysis of water, and electroreduction of CO2 into valuable chemicals and fuels. To support researchers in these critical areas, there is a need for better standards for water oxidation and oxygen evolution, CO2 reduction, hydrogen oxidation, general electrochemical experimental procedures,and analysis of results. The Workshop on Rigor and Reproducibility in Electrocatalysis will examine how research in electrocatalysis can meet the highest standards of scientific inquiry. The primary goals of the Workshop are: 1. Identify, evaluate, and codify practices and expectations for conducting and reporting rigorous and reproducible research in electrocatalysis, 2. Strengthen the caliber of electrocatalysis research through exchange of scientific ideas among researchers, and 3. Foster relationships that promote professional development of current researchers and recruiting of new students to the field. The planned topics of discussion are: (1) electrocatalyst preparation and characterization; (2) electrochemical kinetics; (3) best practices, education, and professional development, (4) spectroscopies and operando analysis; and (5) microkinetics, theory, and benchmarking. The workshop will be conducted over two and one-half days, consisting of four half-day sessions devoted to each topic and a final half-day session to prepare recommendations related to technical challenges and workforce development. The Workshop promises to make a substantial impact on electrocatalysis research, both in strengthening the findings of current and near-future research efforts and by laying the groundwork for coordinated longer-term research to address the concomitant needs of science and technology. The final report will provide guidelines for experiment design, measurements, and benchmarks, recommendations for comprehensive data analysis, and standards for preparing and reviewing publications. Well-defined concepts in electrocatalysis rigor and reproducibility will also inform preparation of research proposals and their review by funding agencies. 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 · 2025-05

Dissolved oxygen is essential for supporting life in marine habitats and for controlling the cycling of carbon and nutrients in the global ocean. Historical observations have shown that oxygen concentrations are declining in many parts of the oceans, termed “ocean deoxygenation”. The causes of the decline are linked to changes in surface water temperature and its impact on oxygen solubility, along with variations in the strength of the biological pump, ocean circulation, vertical mixing, ventilation, and biochemical processes. It is difficult to calculate exactly how much ocean oxygen has been lost to the atmosphere and how much has been redistributed within the ocean interior. This project will compare observation-based gridded oxygen datasets with the purpose of generating comparable four-dimensional (space and time) estimates of global oxygen distribution, assessing their similarities and differences and promoting scientific understanding of the drivers of ocean deoxygenation. The project will promote workforce development through support of an early career investigator, a postdoctoral researcher, a graduate student, and several undergraduate interns. The project has two primary goals. The first goal is to identify the causes of disagreements between different gridded oxygen datasets by conducting an intercomparison of oxygen datasets from common in situ observational and model-based profiles. Many factors can affect estimates of a deoxygenation trend: existing observational studies use different sets of raw data, measurement platforms, data quality control metrics, land-ocean masks, vertical and horizontal grids and interpolation methods. Because variations in any of these factors can lead to different estimates, it is difficult to make direct comparisons and determine the causes of disagreements among datasets. Standardized protocols will be applied to isolate the interpolation method as the only source of discrepancy and to assess uncertainties in global oxygen inventory trends. The second goal is to test hypotheses for the underlying causes of ocean deoxygenation. The suite of new datasets will be used to evaluate the roles of oxygen solubility, the biological pump, and physical and biogeochemical processes driving global ocean deoxygenation. Further, the mechanisms driving the expansion of the tropical ocean oxygen minimum zones will be explored. The use of novel datasets with unprecedented spatio-temporal resolution in these analyses will enable new insights into global and regional oxygen content changes. The suite of gridded oxygen datasets will be made available via public data repositories, and the results of the product intercomparisons and deoxygenation analyses will be disseminated via open-access papers. Collaboration with the Scientific Committee on Oceanic Research (SCOR) Working Group 168 will enhance access and utility of gridded oxygen datasets through sharing and exchange of ideas, experimental protocols and data products. 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 · 2025-05

David J. Masiello of the University of Washington is supported by an award from the Chemical Theory, Models and Computational Methods Program in the Division of Chemistry to develop theoretical models and companion numerical tools capable of elucidating and driving new experiments involving the control of chiral light-matter interactions in tailored optical environments composed of 2D periodic plasmonic lattices that host dispersive collective excitations known as lattice plasmon polaritons (LPPs). The work described in this proposal lies at the intersection between nanophotonics and condensed matter physics, both of which are central to advances in modern optoelectronic and quantum information technologies. Specifically, Masiello and his team of graduate students and postdoctoral associates will investigate the LPP excitations in 2D plasmonic arrays of varying lattice symmetry and sublattice basis structure using reciprocal-space theoretical models that scale with the number of particles in the unit cell as opposed to the overall number of particles in the array. Such a reciprocal-space approach will enable detailed investigation of the complex optical environments arising from honeycomb, kagome, Kekulé, and moiré lattice geometries, which can exhibit optical excitations endowed with well-defined chirality that can preferentially couple to surrounding chiral molecular excitations. The broader impacts of this work will specifically focus on mentoring undergraduate students, who are new to the University of Washington, to join in the proposed research. The theoretical and computational research proposed will investigate a progression of projects that collectively seek to organize understanding of specific nanoscale quantum optical processes occurring in 2D periodic assembles of plasmonic nanoparticles coupled to chiral/achiral quantum emitters. The proposed work will produce rigorous, analytical models and companion open-source numerical codes to describe LPP mode hybridization, eigenstructure, and optical response in complex non-Bravais lattices that optionally break both parity and time reversal symmetry to host chiral excitations. Specifically, the technical focus of this work will study (1) the optically-driven lattice responses and (2) eigenstructure of LPPs, both without and with coupling to chiral/achiral quantum emitters in 2D plasmonic arrays, and (3) new classes of chiral optical probes possessing complementary energy, momentum, pseudo-angular momentum (PAM), and polarization structure to resolve chiral LPP excitations at their natural response scales. Through the development and implementation of new models as well as by regular discussions with experimental collaborators, the broader impacts of this work will train young scientists to learn the critical-thinking skills necessary to become the next generation of leaders in science and technology. 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 · 2025-05

A Summer School and Hackathon event on Structure-Preserving Scientific Computing and Machine Learning will take place at the University of Washington, Seattle on June 16-25, 2025. Structure-Preserving Scientific Computing is an emerging field of research focused on the design of efficient numerical methods or algorithms that preserve fundamental mathematical structures or properties of continuous models at the discrete level. Such approaches are often essential to maintain accuracy and stability of numerical solutions, as well as to enhance efficiency in large-scale simulations. Moreover, scientific machine learning, which utilizes machine learning techniques to solve scientific computing problems, can also benefit from incorporating structure-preserving ideas to improve their prediction capability and generalizability on data-driven models. The main objectives of this Summer School and Hackathon event are: 1) Create a synergistic opportunity for established researchers, industry partners, postdocs, and graduate students to meet, network, and share the latest cutting-edge research in structure-preserving scientific computing. 2) Engage and provide training to graduate students working in computational mathematics. 3) Enable early career researchers to form strong connections and receive mentorship with world-leading experts and industry project leaders. 4) Cultivate long-lasting collaborations and innovative research among students and researchers at all career stages from academia, government agencies, industry, and beyond. The Summer School will feature world-renowned experts delivering four minicourses on topics in Structure-Preserving Scientific Computing and Machine Learning, including operator splitting, dynamical low-rank methods, neural ordinary differential equations (ODEs), and neural operators. Building on this synergy, the subsequent Hackathon will challenge students to apply their newly acquired knowledge to real-world applications through four projects, led by project leaders from academia, government agencies, industry, and national laboratories. Event details and applications for graduate student participation will be posted on the conference website: https://sites.google.com/view/crg-spd/events/seattle-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 · 2025-04

SUMMARY Burkholderia pseudomallei is a recognized bioterrorism agent by the Centers for Disease Control and the causative agent of melioidosis – an emerging disease in the United States and in other developed countries. Upon infection, B. pseudomallei persists despite rapid host immune responses including exposure to macrophage-derived nitric oxide (NO). Currently, the mechanism employed by B. pseudomallei and other pathogens to evade host-produced NO is unknow. We've identified through bioinformatic studies a widely conserved gene in B. pseudomallei and in numerous other bacterial pathogens that encodes for a unique mono-heme cytochrome. We've tentatively designated this protein cyt BP1. Proteins in this family react with N-oxides including NO; however, no member in pathogens have been characterized. We hypothesize that cyt BP1 and its homologues which are present in a large group of persistent pathogens are key defense proteins that detoxify host-produced NO. We therefore propose to characterize cyt Bp1 and eventually its orthologues in other pathogens. Findings from this proposed study could be key in elucidating the mechanism employed by persistent pathogens in NO defense, persistence, and virulence. Specifically, we aim to 1. characterize the phenotype of disruption mutants encoding for bp1orthologues in model organisms 2. characterize the catalytic function of cyt BP1 in NO conversion; and 3. determine the structure-function relationship of cyt BP1. This proposal will support the very first characterization of what is likely a NO-detoxifying protein from B. pseudomallei and other pathogens. Elucidation of cyt BP1 function could be a key first step in the mechanistic understanding of the NO-defense system, and in the development of therapeutic agents for the treatment of persistent infections.

NIH Research Projects · FY 2026 · 2025-04

Despite significant advances in understanding antigen-presenting cells (APCs) and their roles in adaptive immunity, the mechanisms that optimize their function in tissue surveillance and antigen sampling remain elusive. This is particularly critical in cancer, where effective tumor antigen presentation in lymph nodes (LNs) necessitates the coordinated efforts of diverse dendritic cell (DC) populations. Migratory DCs transport tumor antigens to LNs, while LN-resident DCs (DC1) specialize in initiating CD8 T cell responses. This project explores two previously underappreciated aspects of LN-resident DC1 biology: the molecular regulation of their positioning in LNs via integrins, and the impact of this positioning on interactions with migratory DCs for efficient antigen transfer and generation of robust anti-tumor T cell responses. We previously discovered that DC subsets inhabit distinct regions in LNs, with LN-resident DC1 preferentially localizing in the T cell zone and near blood vessels. The molecular regulation and function of this distribution is unknown. Our preliminary data now indicate that DC1 positioning near blood vessels is regulated by the integrin, CD11a. We hypothesize that CD11a facilitates DC1 tethering to blood vessels and perivascular migratory DCs, both rich in CD11a ligands, thus coordinating DC subset organization in LNs. Our data also shows that CD11a integrin enables LN-resident DC1 to interact with migratory DCs. Previous studies have shown that in cancer, migratory DCs are required to transport tumor antigens into LNs, where they hand-off these antigens to LN-resident DC1 for cross-presentation and generation of anti-tumor CD8 T cell responses. While integrins are known to support this process via exosomes, the spatial dynamics of how this occurs in vivo and the specific role of CD11a integrin in antigen transfer to LN-resident DC1 in settings of cancer remains unknown. Therefore, our data raise an exciting hypothesis that by enabling interactions of LN-resident DC1 with migratory DCs, CD11a enhances antigen hand-off and promotes robust induction of anti-tumor T cell immunity. This project employs cutting-edge imaging and genetic techniques to address three specific aims: 1) Elucidate the role of CD11a in regulating LN-resident DC1 positioning and cell-cell interactions in both steady- state and tumor-draining LNs; 2) Investigate the role of CD11a in tumor antigen transfer among DC subsets; and 3) Determine the impact of CD11a expression by DC1 on anti-tumor CD8 T cell immunity. By uncovering the molecular and functional mechanisms underlying LN-resident DC1 positioning and function, this research will significantly enhance our understanding of cellular organization in lymphoid organs and its impact on innate- adaptive cell crosstalk necessary for the generation of adaptive immune responses. Moreover, our focus on investigating these processes in cancer settings offers promising translational potential for novel therapeutic strategies aimed at boosting anti-tumor immunity through targeting specific cellular interactions.

NSF Awards · FY 2025 · 2025-04

Improving prediction of tropical cyclones (TCs) is critical to society due to their devastating impacts. In the US, nine of the top ten costliest natural disasters have been caused by TCs, commonly known as hurricanes. One of the grand challenges in TC forecasting is accurately predicting when and where these storms will develop, referred to as TC genesis. Current operational forecasts provide 1 – 2-week outlooks for TC genesis, but with limited skill, and predictions at 3– 6-week lead time remain a knowledge gap. The Madden-Julian Oscillation (MJO), a 30 – 90-day atmospheric mode in the Indo-Pacific region, is known to influence TC genesis worldwide. However, the precise physical drivers of this relationship are unknown. This research leverages interpretable machine learning (ML) to uncover the nonlinear relationships between the MJO and TC genesis, which may not be easily detected using conventional statistical methods. By applying deep learning techniques, this study aims to improve TC genesis prediction at 1 – 2 week lead times and explore the feasibility of extending prediction to 3 – 6 weeks. The project provides broader societal and educational benefits, including supporting graduate student training in ML, developing a public outreach demonstration website, and sharing machine-learning-ready datasets and open-source code for the research community and the public. The research will use deep learning neural networks to better understand and predict how the MJO convection physically influences TC genesis at 1 – 6-week lead times. This Lagrangian MJO-LPT data will provide the actual locations of the MJO convection and integrate with 3-D atmospheric fields including geopotential height, winds, and relative humidity for the first time. It distinguishes from traditional MJO indices that are based on anomalies. Using the full spatio-temporal evolution of MJO convection together with 3-D fields is a major advancement beyond current methods of TC genesis prediction that rely on 1-D inputs. Interpretability methods, including saliency maps, spatial sensitivity, and local interpretable model-agnostic explanations (LIME), will be used to uncover characteristic spatio-temporal patterns that identify atmospheric teleconnections. The associated dynamical systems such as jet streams, troughs, and ridges are hypothesized to mediate the MJO’s effect on TC genesis. The deep learning models developed in this project are expected to improve the physical understanding needed for TC genesis prediction at 1 – 6 week lead times. 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 · 2025-04

ABSTRACT Stillbirth (i.e., fetal demise after 20 weeks’ gestation) is a common and devastating adverse pregnancy outcome that affects 1 in 160 pregnancies (~23,600 pregnancies in the US each year) and has lifelong medical and psychosocial impacts for affected individuals and their families. Rates of stillbirth are alarmingly disparate among US populations—non-Hispanic Black, American Indian/Alaskan Native, and Pacific Islander-identifying individuals have a 2-fold higher stillbirth rate compared to other racial groups. Available data does not explain the basis for these disparities and lacks fundamental social determinants of health (SDOH) information. While placental pathology, fetal autopsy, and genetic testing are the highest yield tests for determining the cause of fetal demise, many patients do not have a complete workup due to patient, provider, and systems-level issues. Finally, despite advances in non-invasive technologies to assess placental function and overall pregnancy health across gestation, the mechanisms underlying placental dysfunction at the maternal-fetal interface remain poorly understood, stillbirth remains difficult to predict, and preventative measures are limited. Multi-disciplinary interventions at all levels are urgently needed to address stillbirth outcomes. In recognition of this urgent need, the NIH-NICHD released the NOSI, “The Road to Prevention of Stillbirth” to support transdisciplinary stillbirth research efforts. In response to this NOSI, we leverage the international infrastructure of the Fetal Genomics Consortium (FCG) and the local infrastructure of the University of Washington Pregnancy Biorepository (WPR) to launch a multi-faceted initiative to: improve clinical evaluation and data collection for stillbirth, advance tools to evaluate maternal-fetal interface immune biology and detect placenta dysfunction, and develop novel models to predict an individual’s risk of stillbirth. Specifically, we aim to: (1) standardize clinical evaluation, genetic testing, and data collection from patients with stillbirth by implementing a Stillbirth Evaluation Pathway across the University of Washington (UW) hospital network; (2) delineate maternal-fetal interface genomic and immune signatures associated with placental dysfunction and stillbirth using paired maternal-fetal whole genome sequencing data, cell-free DNA/RNA metrics, and placental immune signatures; and (3) develop a personalized, high-fidelity tool using machine learning approaches to predict the risk for stillbirth in pregnant individuals longitudinally. Taken together, these aims will facilitate a precision medicine approach for stillbirth and advance equity in care. The rich dataset of integrated clinical, SDOH, and genomic information harmonized within the larger infrastructure of the FGC network will create an invaluable tool for the research community for future investigations. Ultimately, these insights will enable the development of novel interventions, therapeutics, and prevention strategies with the potential to dramatically improve reproductive health.

NSF Awards · FY 2025 · 2025-04

This award provides partial support for the seventh International Conference on "The Effects of Noise on Aquatic Life" to be held in Prague, Czech Republic, from June 29 to July 4, 2025. This conference builds on the success of previous meetings held in Nyborg, Denmark (2007), Cork, Ireland (2010), Budapest, Hungary (2013), Dublin, Ireland (2016), The Hague, Netherlands (2019), and Berlin, Germany (2022). The major goal of this conference is to advance the understanding of underwater noise impacts on aquatic life, with a particular focus on progress achieved since the last meeting in 2022. Support is requested primarily seeking funding primarily to support the participation of students, postdoctoral researchers, and representatives from developing nations, enabling them to attend and contribute to the meeting. The meeting should help shape future research and understanding of effects of noise on aquatic life. Based on experience from the earlier meetings, the interactions and networking that took place has resulted in new collaborations between investigators and industry. 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 · 2025-04

Project Summary Diabetes and obesity are interconnected diseases with significant public health ramifications. Overnutrition triggers immune cell activation in the brain that promotes weight gain and was therefore presumed to worsen glucose tolerance. On the contrary, we recently discovered a marked dissociation between the regulation of energy balance and glucose homeostasis by microglia. Mice with microglia-specific deletion of inflammatory signaling are protected from diet-induced obesity but show glycemic dysregulation when compared with weight-matched controls. Similarly, mice with impaired prostaglandin signaling in microglia show unaltered inflammatory responses but less diet-induced phagocytic activity, resulting in leaner mice but without a glucose benefit. In contrast, genetically increasing microglial inflammatory signaling triggers weight gain even on a chow diet but nevertheless improves glucose tolerance relative to the leaner control mice. Thus, there is a bidirectional relationship between microglial activation and glucose tolerance. To explore mechanism, we developed a mouse model with the Gq-coupled DREADD receptor hM3D expressed in microglia. Chemogenetic microglial activation evokes an acute improvement in glucose tolerance even in the setting of HFD feeding. The mechanism involves a TNF-dependent pathway by which glucose- triggered neuronal activity is increased in melanocortin neurons, ultimately leading to parasympathetic enhancement of insulin secretion. Importantly, Gi-coupled DREADD activation worsens glucose tolerance, providing a rationale to test Gi-GPCR antagonists for anti-diabetic efficacy. Our preliminary data show that central blockade of the P2Y12 receptor, a major microglia-specific Gi-GPCR, markedly improves glucose tolerance, supporting the viability of this approach. In this proposal, we will further explore the therapeutic potential of this system in preclinical models of diabetes and explore mechanisms contributing to the glycemic benefits. In Aim 1, we will perform the first studies measuring neuronal activity in response to a direct cell- specific manipulation of microglial activation state. Specifically, we will use electrophysiology and fiber photometry to determine how microglia modulate melanocortin neuron glucose sensing and electrical activity. In Aim 2, we will assess the natural history of microglial state changes during the development of DIO and DM2 along with the impact of chronic microglial activation. Further, we will assess the contribution of microglial phagocytic capacity to metabolic regulation using tools related to the key regulatory protein MerTK. Finally, we will test the participation of the P2Y12 receptor in the regulation of glucose homeostasis by microglia. Together, these studies will help test the hypothesis that microglial inflammatory signaling and phagocytic capacity function to offset obesity-associated glucose intolerance via alterations to hypothalamic glucose sensing, a mechanism that can be harnessed to improve glycemia in the setting of T2D.

NIH Research Projects · FY 2026 · 2025-04

PROJECT SUMMARY Community-acquired pneumonia (CAP) is a common cause of morbidity and mortality in hospitalized patients but therapeutics are limited. In response, identification of modifiable pathways to alter host response and improve outcomes in patients with severe CAP has been highlighted as a NHLBI research priority. Our research group has identified angiopoietin-like 4 (ANGPTL4) as a potential mediator in adverse outcomes in CAP from viral and bacterial pathogens. We have generated preliminary data in a discovery proteomic analysis of 5000 different plasma proteins. We found that ANGPTL4 was one of the top proteins associated with fewer ventilator free days and worse hospital mortality in severe CAP due to COVID-19. Next, in a multi-center cohort, we replicated these findings in COVID-19 that higher ANGPTL4 concentrations were associated with worse clinical outcomes, and obtained preliminary evidence that ANGPTL4 is also associated with outcomes in severe CAP due to bacteria3. We also have generated data that genetically targeting Angptl4 is protective in mice with severe influenza, a finding that is supported by pre-clinical data that inhibition of ANGPTL4 signaling through a monoclonal antibody is protective in viral pneumonia. In addition, independent research groups have also found that ANGPTL4 is associated with clinical outcomes in severe CAP. Together, these findings support our hypothesis that ANGPTL4 expression is a significant determinant of outcomes from CAP, independent of pathogen type, and that modulation can lead to improved clinical outcomes. To further examine this hypothesis, we will use complementary clinical and pre-clinical studies in the following aims. In Aim 1, we will determine the relationship between plasma ANGPTL4 levels and outcomes in a hospitalized population with varying severity at enrollment (acute care and ICU) and pathogen type (viral and bacterial). In Aim 2, we will infer causal relationships between ANGPTL4 concentrations and risk for pulmonary and extra- pulmonary organ dysfunction using a non-overlapping 2-sample Mendelian randomization genetic approach. In Aim 3, we will evaluate the role of ANGPTL4 in pre-clinical models of viral and bacterial pneumonia and determine the relative contributions of the proteolytically processed cANGPTL4 and nANGPTL4 peptides. The outstanding qualifications of our team in the fields of sepsis, community acquired pneumonia, molecular epidemiology, and pre-clinical models uniquely position us to deliver an integrated molecular view of host response in CAP that is not only responsive to the challenges in severe CAP care identified by global leaders, but could fundamentally alter paradigms of patient care in severe CAP. The long-term goals are to delineate the role of ANGPTL4 in severe CAP through understanding which clinical outcomes are most closely linked with ANGPTL4 levels through epidemiological and genetic causal inference analyses and to understand the cell of origin and relative contributions of different cleavage products of ANGPTL4 through pre-clinical studies.

NIH Research Projects · FY 2026 · 2025-04

PROJECT SUMMARY / ABSTRACT Engineering advances applied to miniaturized analytical instrumentation will be employed to improve sensitivity and throughput of thin-layer chromatography enabling single-cell analyses of the biochemical activity of lipid modifying enzymes in the cells of patients. By utilizing micro- and nanofabrication techniques, the proposed work will develop a novel ultra-miniaturized device termed picoliter thin-layer chromatography (pTLC) suitable for assays at high throughput and sensitivity. A multidisciplinary collaboration encompassing bioengineering, chemistry and oncology will develop the pTLC chip and integrate its supporting hardware to create an easy-to-use instrument readily amenable to point-of-care applications in a clinical setting. Sample handling and analysis protocols will be developed to ensure system compatibility with common laboratory workflows. The improvements engendered by miniaturized chromatography and nanofabrication of silica gels in this lab-on-chip device will enable experiments that demonstrate the potential and power of the platform by assessing of the roles of specific enzyme targets in dynamic reprogramming underlying resistance to chemotherapy in patients with acute myeloid leukemia (AML). The technique will capitalize on recent synthetic lipid innovations to employ a large and growing list of commercially available, cell-loadable, fluorescent, and clickable lipid probes now available or in development. These probes will be used to simultaneously elucidate enzyme activity in the sphingolipid, phosphoinositide and fatty acid signaling pathways hypothesized to serve critical roles in developing resistance to targeted therapies. By simultaneously tracking multiple signaling pathways in individual patient cells, we will identify the strategies that AML cells use to dynamically reprogram their growth-promoting pathways during and after drug treatment. A powerful attribute of these measurements is their performance on single cells from patient samples avoiding the confounding aspects of averaged data yielded by bulk cell analysis and genetic drift in cell lines. This work will demonstrate that the pTLC platform can provide key information from which the best treatment option(s) may in the future be chosen for patients with various cancers and will contribute fundamental data in the emerging field of precision medicine.

NSF Awards · FY 2025 · 2025-04

Improving agricultural practices to ensure food security and the supply of valuable bioproducts is vitally important for society. Agricultural practices could be improved by using biotechnology to manipulate crop traits or to replace expensive pesticides with plant-produced, affordable compounds. However, both approaches require engineering multiple genes or pathways to yield predictable outcomes. Thus far, predicting the expression in plants of synthetic genes and pathways, even those composed of well-characterized DNA sequences, remains a major challenge. Indeed, when individual pathway genes are assembled into larger designs, their performance becomes unpredictable because regulatory elements and genic regions that encode proteins show strong context-dependent properties. Moreover, plant biotechnology relies on only a handful of regulatory elements, often of bacterial and viral origin, that constitutively and ubiquitously drive gene expression, interfering with growth and reducing crop yields. This lack of programmable and tunable regulatory elements contributes to unpredictable gene expression through expression interference and silencing. Together, the results of this study will enable the construction of multi-gene cassettes in which the expression of each gene is induced in response to a specific stimulus and at a specified level to produce optimal pathway flux. These efforts will generate large numbers of programmable and tunable regulatory elements and combinations of elements for future synthetic biology efforts in plants. Beyond transgenes, the ability to ‘program’ plants with predictable expression characteristics will deliver breakthroughs in manipulating endogenous pathways that control plant growth and yields, thereby making feasible the targeted engineering of resilient and high-yielding crops. This project exploits a toolbox of novel experimental and computational strategies pioneered by this interdisciplinary collaborative team to make plant gene expression predictable by constructing programmable and tunable multi-gene cassettes that produce antifeedants and insect pheromones as alternatives to traditional pesticides. There are three objectives, each one testing novel hypotheses as to the causes of specific challenges: 1) to develop a large repertoire of programmable and tunable synthetic regulatory elements, massively parallel reporter assays, machine learning and in silico evolution will be used; 2) to control gene expression levels more precisely through insulation and RNA stabilization, recent innovations in vaccine research will be applied to identify and test plant-based insulators in multi-gene cassettes while innovative computational machine learning strategies will be used to design optimized gene versions with increased RNA stability and codon usage; and, 3) to determine expression-limiting features, genetic engineering and a new single-molecule method to explore chromatin architecture will be used to manipulate gene order and position, DNA shape, torsional stress, and nucleosome occupancy. All project outcomes, including but not limited to sequence data and genetic resources, will be available through deposition to long-term repositories, publication, and on request. 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 · 2025-04

PROJECT SUMMARY For over a century, Pavlovian fear conditioning paradigms have been pivotal in studying basic associative fear memory formation through conditioned stimulus (CS) pathways, significantly enhancing our understanding of fear- and anxiety-related disorders in humans. However, given that the brain's fear system may operate differently under real-world risks, it is essential to explore neural dynamics and behavioral outcomes within ecologically relevant scenarios. This application proposes to utilize our established 'approach food-avoid predator' paradigm in rats to investigate the primary fear circuit mechanisms involved in risky decision-making within spatial environments featuring lifelike agents of danger. This approach leverages how the biologically-primed innate or unconditioned stimulus (US) pathways process and adapt to potential and actual attacks. Aim 1: We will test the hypothesis that the amygdala functions as a pivotal relay, processing biological threat information from the midbrain and transmitting fear signals to specific corticolimbic structures, thereby guiding risky goal-directed decisions. This investigation will thoroughly examine the dynamics of predatory pathways among the periaqueductal gray, amygdala, hippocampus, and medial prefrontal cortex, spanning anatomical, neurophysiological, and causal dimensions. Aim 2: We will characterize the changes in midbrain-corticolimbic mechanisms resulting from a singular life-and- death event—a nociceptive shock to the dorsal neck/body during evasion from a predatory threat—that cause generalized, nonassociative fear responses. These observations could yield insights into post-trauma-like avoidance behaviors. Our research has dual significance. Firstly, it enhances foundational knowledge from fear conditioning paradigms that emphasize CS pathway-mediated learned fear responses by offering a broader perspective on fear mechanisms incorporating US pathway-mediated innate and nonassociative fear responses. Secondly, it integrates dynamic agent-induced trauma perspectives relevant to interpersonal threat conditions. This comprehensive approach holds the potential to advance treatments for trauma disorders, particularly those stemming from assaults.

NSF Awards · FY 2025 · 2025-04

Artificial Intelligence (AI) methods depend on data. However, much of the most valuable biomedical data is subject to strict access controls due to its sensitivity. This significantly hinders the data’s ability to be findable, accessible, interoperable, and reusable (FAIR), effectively making it “dark data.” Dark data is a major reason why AI remains underdeveloped in healthcare. To address this problem, this project will develop methods that can safely and securely illuminate dark health data and make it accessible for research without compromising the privacy of the data donors. By creating fully open but privacy-preserving replicas of the original datasets, the project will empower researchers to find, access, inspect, socialize, critique, and reuse this data. Systematically illuminating dark data will support beneficial AI health applications, particularly for data stored in isolated repositories, such as data about rare diseases. This project’s goal is to advance the state-of-the-art in privacy-preserving biomedical data sharing through the development of a software library with efficient algorithms and cryptographic protocols. This will enable data custodians from secured, siloed repositories to contribute data to a joint and secure synthetic data generation process. The solution combines Secure Multiparty Computation with Differential Privacy techniques to ensure input privacy (data custodians do not need to disclose their data to anyone, including intermediary and aggregating servers) and output privacy, where the synthetic data sets do not reveal sensitive information about individuals in the training data. Additionally, the project will improve the understanding of current techniques’ strengths and limitations in training generative artificial intelligence models for high-fidelity and high-utility synthetic genomics (germline) data. It will investigate the limits of direct germline sequence generation using state-of-the-art generative foundation models, generate variant call file data using frontier models for tabular data generation, and validate the concordance of mutation annotation files derived from synthetic and original variant call files by comparing pathogenicity predictions. The project focuses on rare diseases such as Neurofibromatosis and Acute Myeloid Leukemia, where existing data is minimal and fragmented across different data custodians. 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.