Duke University

NIH Research Projects · FY 2025 · 2025-07

PROJECT SUMMARY This application is a request for funds to support a conference titled the ‘Simian Collective’ (SimCo) that highlights nonhuman primate neuroscience research in the United States and its unique role in providing translational models of human neurological, neuropsychiatric diseases and disorders, and models of healthy and impaired aging. SimCo seeks to build a crucial community effort to address key challenges facing the field of nonhuman primate neuroscience in the 21st Century. The conference is strategically organized to stress that maximizing the impact of nonhuman primate neuroscience research in the modern era necessitates complementary goals of Science, Ethics, Education and Advocacy. Owing to the shared functional organization of the primate brain, our simian cousins are uniquely powerful models from which we can learn many facets of human brain function in both health and disease. This cutting-edge research must continue to grow and receive renewed investments to prosper. The SimCo meeting will also emphasize that the phylogenetic advantages of using a primate model, which shares many unique neural and cognitive characteristics with humans, for investigative research must also be balanced by the crucial neuroethical considerations that inevitably emerge because of these similarities. Furthermore, the Simian Collective will also emphasize the responsibility of the members of the field to educate our scientific colleagues and the public about the unique importance of nonhuman primate research and to advocate for its significance. The program of the meeting emphasizes the complementary relationship between these core tenets and seeks to build a community initiative to promote and ensure nonhuman primate neuroscience research in the coming years. The past three conferences were extraordinarily successful with increasing attendance, year over year. SimCo 2024 had ~250 attendees across all levels – technical staff, students, post-doctoral fellows, and assistant, associate and full professors. We anticipate that this community will continue to grow, attract new talent, and remain a vibrant contributor to neuroscience research.

NIH Research Projects · FY 2025 · 2025-07

Project Summary/Abstract Activated and hyper-reactive neutrophils play a significant role in sickle cell disease (SCD). Recent evidence suggests that abnormally reactive neutrophils contribute to many of the thromboinflammatory complications of SCD, including acute chest syndrome and stroke. To prevent these complications or to treat acute events, many patients with SCD undergo a procedure called red cell exchange (RCE). RCE is an automated procedure which removes the patient’s endogenous red cells containing abnormal hemoglobin S (HbS) and infuses healthy donor red cells containing HbA. RCE is standard of care in both the inpatient and outpatient setting, as achievement and/or maintenance of HbS < 20-30% has been shown to reduce the otherwise high incidence of recurrent stroke and also leads to resolution of acute chest syndrome. However, whether RCE affects neutrophil activation and hyper-reactivity, thereby contributing to its beneficial effect on SCD complications, is unknown. To answer this question, as shown in preliminary data, we have begun to enroll a cohort of patients with SCD who undergo chronic RCE in the outpatient setting. Our preliminary data support the hypothesis that RCE reduces neutrophil hyper-reactivity, resulting in significantly attenuated degranulation responses to a range of agonists, including bacterial ligands. Furthermore, we show that these changes in neutrophil reactivity may be due to the presence/absence of circulating HbA/HbS. Based on the preliminary data presented in this application, we will test the hypothesis that RCE, and the replacement of abnormal HbS red cells with normal HbA red cells, modulates neutrophil reactivity and function. In Aim 1, we will comprehensively determine the effect of RCE on neutrophil function and phenotype and establish the time course of changes in neutrophil function. As well, we will perform a pilot study examining neutrophil function pre- and post-RCE in patients hospitalized with acute chest syndrome to determine whether our findings are applicable during an acute inflammatory event. In Aim 2, we will establish the multiple mechanisms whereby RCE modulates neutrophil reactivity. We will investigate 3 major pathways by which RCE may be modulating neutrophil function. Using artificially created admixtures of HbA and HbS red cells as well as admixtures obtained from SCD patients pre/post RCE, we will examine interactions between (1) neutrophil Siglec-9 and SS RBC glycophorin A, (2) neutrophils and phosphatidylserine exposed on SS RBCs, and (3) neutrophils and SS RBC adhesion molecules. As well, we will establish the impact of RCE on thromboinflammatory activity including heterotypic aggregate formation and markers of endothelial damage. Together, these studies build on our novel observation that RCE modulates neutrophil function. The overall goal of this proposal is to understand the effect of transfusion on neutrophil activation and to determine if inhibition of neutrophil reactivity can be used as a functional endpoint to establish personalized therapeutic targets for SCD patients. Findings from this proposal will guide future studies to identify functional biomarkers for high risk patients and will provide additional biological insight into the emerging role of neutrophils in SCD.

NSF Awards · FY 2025 · 2025-07

The goal of this project is to establish American Computer Science Education Researchers as world leaders in the study of computing education. This project will provide support to American computing science education researchers, practitioners, and graduate students to help offset the cost of attending the Special Interest Group in Computer Science Education (SIGCSE) Association of Computing Machinery (ACM) Global Computing Education Conference (CompEd). SIGCSE created ACM CompEd to provide computing science educators with the opportunity to collaborate with and meet new colleagues in countries other than North America and Europe. By making the cost of attendance more affordable, more Americans will be able to share research results in computer science education and collaborate with faculty from around the globe. This project will provide travel support to approximately fifty US participants. By providing American faculty, postdocs, graduate students and undergraduate students with the ability to interact and establish partnerships with academics from outside America, new research opportunities and collaborations will be developed, establishing American Researchers as leaders in the field. Graduate students will benefit from the opportunity to work both with foreign graduate students and other computing education researchers. Undergraduate computing students will benefit both from the innovations that get discovered/developed as well as from the opportunities to work on exciting and innovative projects in computing education. The NSF IUSE: EDU Program supports research and development projects to improve the effectiveness of STEM education for all students. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NIH Research Projects · FY 2026 · 2025-07

Tobacco use is a chronic relapsing condition. That is, even with state-of-the-art treatment, >70% of smoking cessation attempts end in relapse (i.e., a return to regular smoking). Research demonstrates that everyday environments associated with smoking trigger craving for cigarettes, provoke smoking, and lead to relapse. However, despite this knowledge, our understanding of environmental correlates of smoking has been limited by a reliance on self-report, leading to imprecise information about the physical environments in which people live. To overcome this challenge, our team has pioneered the development of digital envirotyping, which uses digital tools (e.g., sensors, cameras, artificial intelligence) to efficiently and accurately characterize and categorize environments with the goal of identifying environmental markers of behavior and health. Foundational to our digital envirotyping research is computer vision (CV), a type of artificial intelligence (AI) that enables computer systems to recognize objects and scenes in digital images, mimicking how humans perceive and understand visual information. With CV we can extract detailed and accurate information (i.e., objects and location types) about the everyday environments of people who smoke (PWS) and relate that information to smoking behavior. After validating the use of CV, we used CV to develop enviromarkers of relapse risk. To do this, we first developed photographic ecological momentary assessment (photoEMA) and in a study of PWS, we collected 8,008 pictures over a two-week period. The algorithm we trained with this data was again effective at predicting smoking risk. Importantly, we identified a novel enviromarker in which people higher in nicotine dependence (and thus at greater risk for relapse when they quit) are exposed to a more consistent level of environment-related smoking risk as they move between their smoking and nonsmoking environments. Research is now needed to advance digital envirotyping and enviromarker development in the field of tobacco addiction. We will recruit a diverse, national sample of n=500 adults who are interested in quitting smoking. For two weeks prior to quitting, they will undergo photoEMA in which they will take two pictures of their current environment when they smoke, and randomly 10 times per day resulting in >300,000 images total. Cessation will be supported by nicotine replacement therapy (i.e., nicotine patch). Our primary clinical outcome will be days to relapse. Our specific aims are to (1) further develop, refine, and validate methods for efficient digital envirotyping at scale, (2) leverage CV and AI approaches to develop enviromarkers of smoking relapse, and (3) conduct analyses to increase understanding of environmental smoking risk in these two important tobacco use disparities groups. This program of research in digital envirotyping has the potential to (1) advance the efficient and objective measurement of everyday environments thus representing a major step beyond traditional self- report methods, and (2) advance the development of enviromarkers which can lead to more personalized and precise cessation interventions that are tailored to individuals’ specific environmental risk factors.

NIH Research Projects · FY 2025 · 2025-07

TITLE: Developing Hyperpolarized Nitrogen-15 MRI Agents for Probing Glutamine Metabolism PROJECT SUMMARY/ABSTRACT Glutamine is the most abundant free amino acid in the body. Glutamine has a versatile role in cell metabolism, participating in tricarboxylic acid (TCA) cycle supplementation and the biosynthesis of nucleotides, glutathione (GSH), and other nonessential amino acids. It is increasingly recognized that quantification of glutamine metabolism is abnormal in multiple diseases including cancer, diabetes, and neurodegeneration. Glutamine deprivation suppresses cancer growth and even induces cell death in several cancers. Various cancers develop glutamine dependence and addiction to maintain continuous growth, survival, invasion, metastasis, and resistance to cancer treatments. Imaging agents for effectively monitoring the stepwise metabolic process of glutamine in vivo will have significant impacts for a better understanding of glutaminolysis and their contribution to cancers. Our long-term goal is to develop hyperpolarized 15N-MRI probes for abnormal metabolism for diagnosis and treatment of diseases. The objective of this proposal is to develop nitrogen-15 (15N)-labeled probes that are capable of monitoring the stepwise process of glutamine metabolism by hyperpolarized (HP) magnetic resonance spectroscopy and imaging (MRS/MRI). Toward this goal, we will design, synthesize, and optimize novel 15N-labelled probes, with Aim 1 targeting the conversion of glutamine to glutamate by glutaminase and Aim 2 targeting the glutamine-derived production of alpha-ketoglutarate and 2-hydroxyglutarate. These 15N- labelled probes will be evaluated on their potentials as effective imaging agents to deliver long-lived hyperpolarized 15N NMR signals for sensitive and specific detection of the targeted metabolic step. Overall impacts of this R21 grant are two-fold. First, the developed HP 15N-MRI agents will advance the ability of imaging glutamine in vivo, convey more accurate and comprehensive information of abnormal glutaminolysis, and offer new metabolic biomarkers for cancers. Second, the successful in vivo imaging by 15N-tagged HP-MRI probe will unbridle 15N-MRI agents from traditional limitations restricted to 15N-isotope labeled nitrogen atoms in heteroarenes and peralkylatedamines, to achieve much greater potentials and broader applications in basic biomedical and translational research.

NIH Research Projects · FY 2025 · 2025-07

Abstract: Hematological malignancies like leukemias, lymphomas and multiple myeloma are all too often incurable without highly toxic immunotherapy like allogeneic hematopoietic stem cell transplantation (HCT). The advent of less toxic and more targeted, engineered chimeric antigen receptor (CAR) cytotoxic cells has been a major advance. Unfortunately, use of CAR-engineered cells is available only to a small subset of cancer patients whose tumor cells express known antigens. This limitation is due to the inability to produce the tumor-targeting, antigen- binding part of the chimeric receptor. This critical cell surface antigen-targeting part of a CAR, the single chain fragment variable region (or scFv) is not derived from a T cell. The scFv is derived from antibody-producing, B Cell Receptor (BCR)-Activated B cells because antibodies, unlike T Cell Receptors, bind to three-dimensional structures on tumor cell surfaces in an unrestricted manner. Our objective is to leverage what we have learned about the mechanisms of B cell tolerance in patients who develop immune toxicity and have decreased cancer relapsed rates to ask whether anti-tumor B cells can be cloned from patients after HCT to engineer less toxic, more targeted immune cell that eradicate hematological malignancies. Important findings regarding B cells by our group and others over the last 15 years have revealed that host and tumor-reactive B cells survive after HCT when immune tolerance mechanisms are broken in patient with chronic graft versus host disease (cGVHD). Altered immune homeostasis/balance after HCT, donor B cells develop under constant activation of the B Cell Receptor (BCR) by ubiquitous alloantigens (foreign/host and tumor antigens) and excess B Cell Activating Factor (BAFF). Both alloantigen activation of the BCR and BAFF promote survival of B cells that potentially produce polyreactive antibodies. Thus, we hypothesize early after HCT, B cells are primed for production of antibodies with tumor-binding potential. In Aim 1, we will employ HCT- related factors that promote BCR-activated B cells in order to clone cells that would otherwise die via immune tolerance death mechanisms. In Aim 2, we will establish a tumor identification strategy using pooled CRISPR knockdown in a flow cytometry-based assay. Our immediate objective in this R21 proposal is to understand and overcome barriers by harnessing human tumor antigen-responsive, antibody-producing B cells and methods that identify tumor binding receptors (scFV) to engineering novel cancer-eradicating CARs. We will capitalize on what we’ve learned about B cell tolerance after HCT, along with our collaborators at Duke, to establish a pipeline for B cell for rapid cloning of key anti-tumor antibody fragments, scFv, for CAR production.

NSF Awards · FY 2025 · 2025-07

Selenium is a common trace element found in seawater and sediments. It has six stable isotopes whose ratios allow it to track oxygen content and biochemical reactions in seawater. So far, Selenium isotopes have proven difficult to measure accurately due to their low concentration. This project will develop new methods to measure Selenium isotopes. Water samples taken along a profile across the Eastern Pacific Ocean and from sediments in the Black Sea will be used. These samples have very low oxygen seawater. This low oxygen seawater provides ideal conditions to calibrate the isotopes of Selenium to oxygenation. The project includes education and training in stable isotope techniques in geosciences. Two graduate-level workshops on state-of-the art elemental isotope analysis will be held. Workshops will introduce advanced hands-on techniques and theory for trace element analysis. Also, middle- and high-school students will visit the research laboratory and learn about Selenium contamination in the local environment. Selenium is a trace element that is both an essential micronutrient and a toxin at relatively low concentrations. It inhabits four oxidation states in surface environments and is comprised of six stable isotopes, the relative abundances of which are fractionated during biogeochemical reactions. Selenium isotope systematics therefore hold great promise for tracking its cycling in nature, including in reconstructions of paleo-environmental conditions using ancient sediments. However, the understanding of Selenium isotope mass balance in the modern ocean remains poor due to a lack of data. This project seeks to develop and refine methods for measuring Selenium isotopes in seawater and marine sediments. The research team will make the first phase-specific Se isotopes along transect through the East Pacific and through recent marine sediment cores with the goal of calibrating modern Selenium isotope mass balance in the oceans for use in reconstructions of paleo-oceanographic oxidation and nutrient dynamics. As part of the project, the team will host workshops for graduate students focused on state-of-the-art mass spectrometry for trace element isotope analysis. The team will also host lab visits for Durham high school students to engage with environmental chemistry research and see how isotopes are used to study coal-ash contamination of North Carolina lakes. 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

Scientific workloads have outgrown the capabilities of today's campus networks, driven by two key trends: the increasing adoption of machine learning (ML) in scientific research, and the growing need to access and process large-scale datasets. Remote Direct Memory Access (RDMA) has emerged as a key network technology to provide high-bandwidth, low-latency communication for distributed ML and fast data storage. This project explores an RDMA-based campus network design and implementation that enables the shared use of distributed, heterogeneous Graphics Processing Units (GPUs) to accelerate scientific applications and fast access to research data storage. The project entails four research thrusts. First, high-bandwidth, low-latency RDMA network infrastructure will be established to connect campus GPUs using standard data center-class network hardware. Second, new workload scheduling systems and algorithms will be developed to make efficient usage of the RDMA network. Third, storage disaggregation over RDMA will be enabled, allowing compute servers to access remote NVMe-class storage with minimal performance overheads. Finally, varied science applications, such as large language models (LLMs), domain-specific natural language processing (NLP), medical image processing, and cryo-electron microscopy (CryoEM) will be evaluated on top of the RDMA network, the workload scheduler, and the disaggregated storage. This project presents a first step toward improving the efficiency and utilization of Duke University's compute infrastructure by connecting centralized and individual GPU servers via a high-speed RDMA network. It is expected to reduce the time, effort, and financial burden that researchers typically face in enabling the scaling of scientific workloads in a number of scientific fields including but not limited to ML and LLMs, biomedical imaging, and molecular dynamics. The project will contribute to workforce development by training graduate and undergraduate students in high-performance computing, network optimization, and large-scale data management. Software artifacts, papers, and tutorials developed as part of this project will be released on the following website https://sites.duke.edu/dream/. This website will be regularly maintained for five years after the completion of the project. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NSF Awards · FY 2025 · 2025-07

This project is centered in an area of mathematics called symplectic geometry, which has a long history dating back to the advent of Newtonian mechanics in physics. The central objects of study in this project are Legendrian links, which may be visualized as certain loops of string in three-dimensional space tied together at their ends. Legendrian links play a key role in the modern study of symplectic geometry in three and four dimensions. The project seeks to develop and explore new algebraic structures associated to Legendrian links, by combining an established framework, developed over the past few decades, with recent ideas from other areas of mathematics such as combinatorics and algebraic geometry. This research will create new algebraic structures that can be applied to answer some long-unsolved questions in symplectic geometry. The Principal Investigator will also train future mathematicians through his work organizing undergraduate summer research programs at Duke University and other extracurricular activities for students. The project is built around an algebraic invariant of Legendrian links called Legendrian contact homology, which was originally developed roughly three decades ago and has emerged as one of the premier tools in modern symplectic topology. The Principal Investigator will develop a number of interrelated enhancements of Legendrian contact homology. Some are combinatorial in nature, including a quantization of Legendrian contact homology that has a conjectural relationship to mirror symmetry; others are more geometric, including a topological stable homotopy type that lifts Legendrian contact homology into the realm of Floer homotopy theory. These enhancements, which can be viewed as strengthened versions of existing invariants, are motivated by recently-discovered connections between symplectic geometry and other mathematical areas such as cluster theory in combinatorics. This project will apply the enhanced invariants to study open questions in symplectic topology, notably the question of classifying certain surfaces in four dimensions, called Lagrangian fillings, with prescribed boundary conditions. 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 · 2025-07

ABSTRACT Cardioembolic stroke (stroke coming from the heart) is the most lethal form of ischemic stroke, causing sudden, permanent deficits in strength, sensation, speech, and sight. The most common cause of cardioembolic stroke in older Americans is atrial fibrillation (AF), a chronic, cardiac arrythmia that can be clinically silent yet portend a risk of life-threatening stroke. There are approximately 700,000 people with undiagnosed AF in the United States. A recent NHLBI working group published recommendations for future directions in cardiac monitoring, a strategy to detect clinically silent AF and – ideally – intervene before it is too late. One facet of the recommendations was that individual clinical features should be used to target cardiac monitoring in patients who may be at highest risk of clinically silent AF. Retinal stroke (central retinal artery occlusion) is a disabling subset of ischemic stroke. It is not known whether AF is associated with retinal stroke. Knowing whether AF represents an independent risk factor for retinal stroke would be valuable, because it would motivate clinicians to pursue cardiac monitoring in patients with retinal stroke, and boost the odds of detection of AF in this vulnerable patient population. Compelling preliminary data that AF is a risk factor for retinal stroke is presented, however there are key limitations to its interpretation given the inherent biases in observational literature. The current application proposes to do approach this question from a distinct perspective. The central hypothesis of this proposal is that oral anticoagulation therapy modifies the observed association between AF and retinal stroke. Testing this hypothesis provides indirect evidence of an association between AF and retinal stroke, given that anticoagulation reduces thromboembolism in patients with AF. During this project, the principal investigator will continue to receive intensive mentorship with an added focus on instrumental variable analysis. An instrumental variable is a variable which is highly associated with a downstream exposure (in this case anticoagulation) but not associated with the key study end point (other than via its association with a downstream exposure) and not associated with unmeasured confounding. Specific Aim 1 will construct an instrumental variable – individual prescriber preference for anticoagulation use – and determine whether such a prescriber preference is associated with the hazard of retinal stroke. Specific Aim 2 with determine whether changes in anticoagulation exposure within individual Medicare beneficiaries is associated with the odds of retinal stroke, by means of a case-crossover design. Results of this project – whether positive, neutral or negative – will inform our understanding of the biology of retinal stroke, allow physicians to more appropriately counsel patients on the benefits and possible harms of anticoagulation, and allow the refinement of instrumental variable analysis when applied to time to event data. Completion of the proposed work will allow the PI to branch out into a new research direction informed by the results of the parent K23 and advance his long-term objective of becoming an independent investigator.

NSF Awards · FY 2025 · 2025-07

This award funds a research project that combines extremely rich and detailed data with economic theory to study how the burden of market failures is shared in the economy. Market failures prevent resources, such as labor and capital, from being used in the places where they are most valuable. While it is known that market failures are a feature of all economies and contribute to income differences across countries, the question of which types of households are affected most by these market failures is much less researched. This project makes progress on this gap by developing tools to connect and analyze multiple datasets that provide an extensive set of links in the economy between households and firms, between both households and firms and the government, and between the firms themselves. Understanding which groups benefit and which groups lose out from policies that address such market failures is vital to the design of approaches that maximize the welfare of any nation. The research outcomes could be essential for researchers and decisionmakers in shaping optimal U.S. policies and potentially enhancing the wellbeing of households and businesses. This award funds a research project that develops tools to estimate distortions—markups, markdowns, and taxes that prevents resources being allocated to their best uses—at a highly disaggregated level and trace them to individuals through arbitrary trade, employment, and financial networks. This methodology is applied to administrative data, where the research team can map out the flow of goods and money for the entire economy by linking firm-to-firm networks with firm-to-consumer, firm-to-lender, and firm-to-employee networks alongside ownership registries. These methods reveal how the burden of distortions is shared among households belonging to different regions, demographic groups, skill groups, and income levels. In addition, they enable answers to various questions, such as which distortions do the most to compress and expand the distribution of living standards; what trade-offs are observed in approaches designed to improve the impacts of distortions; and to what degree overlapping distortions necessitate our wide-ranging analysis as opposed to focusing on one specific distortion or sector at a time. The theory and methods are developed in a way that they can be applied to any country with similar data. This project advances knowledge in several ways. First, it operationalizes recent theoretical work on general equilibrium models of heterogeneous agents in distorted economic environments. Second, by assembling a complete empirical mapping of economic relationships between agents in an economy, it measures the distributional impact of the main distortions that are present in an economy (those on labor, capital, output, and intermediate inputs) throughout all sectors. This is relevant because studying the impact of reducing distortions in one specific market is influenced by distortions in other markets. Thus, to fully assess the trade-offs of reducing distortions, one needs to go beyond specific distortions and specific sectors. The results have the potential to significantly reshape how economists perceive the implications of market distortions and the policies responding to them. By addressing who bears the costs and who benefits from market distortions, a key theme for decisionmakers, the findings of this research could lead to optimal policies related to market failures and enhance the welfare of the U.S. population. 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

From devising efficient agricultural practices to modelling the flow of blood in coronary arteries to investigating weather patterns on Jupiter, the study of fluid flow is essential to almost all aspects of life. This project is concerned with some of the fundamental aspects of the dynamics of incompressible fluids. The kinds of questions considered in the project have been around for millennia, even if the precise mathematical questions were only posed three centuries ago. Some of the important questions the primary investigator (PI) considers in this project relate to the degree to which the classical mathematical equations of fluid mechanics actually model physical reality, whether the equations themselves can break down, and what the equations predict on long time scales. The project contains three general directions of research: the formation of singularities in incompressible fluids, the study of steady solutions to the incompressible Euler equation in two and three dimensions, and the phenomenon of fluid mixing. The PI investigates scale-invariant and self-similar singularities in the three-dimensional Euler equation and related models and, additionally, study the possibility of non-constructive proofs of singularity formation. The study of steady solutions to the Euler equation and the phenomenon of fluid mixing represents an attempt toward understanding aspects of the long-time behavior of inviscid two-dimensional fluids in the large. 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

Plants create a variety of lateral organs, such as roots, leaves, and flowers, as they grow. Each of these new organs has specific functions that are important for plants, and they all impact agricultural yields in crop plants. Research suggests that there are both developmental similarities and differences between the different organ types. The basis of this is unclear. Many genes are known to contribute to the creation of lateral organs, with some genes impacting one organ type and others impact more than one. Understanding the common and different functions of plant genes in the development of different organ types is an important goal which can help crop improvement. However, there is a limitation in the technology available to study this at a scale that will be informative. The goal of this proposal is to create a semi-automated system to determine what genes are active in different lateral organ types. This system will be able to look at many genes in parallel, an advantage over older technologies. The project will also compare two divergent plant species and define the role of a cell signaling pathway on gene function in different organ types to help understand how evolution and cell signaling pathways shape lateral organ formation. Lastly, the project will create databases for other scientists to use in their research, and a workshop to train other scientists on the use of the semi-automated system, which will enable other researchers to use this approach in their studies. Lateral organ production, including flowers and roots, is a critical feature of many crop traits and as such the project will help inform future efforts to improve crop productivity and ensure food security. During plant development common signaling pathways and transcription factors (TFs) often operate in seemingly distinct processes. Understanding how individual plant signaling pathways and TFs are repurposed in different contexts remains a challenge. Traditional methods for defining individual TF functions are time consuming and labor intensive. As the number of TFs impacting plant processes increases, this creates a technical bottleneck. To address this, this proposal will develop a new high-throughput platform to identify TF targets in vivo and use this platform to identify context-specific TF binding sites during lateral organ development across tissue types and across species. The project team has identified a peptide signaling pathway as a novel driver of lateral organ formation in roots and shoots and identified a suite of TFs that impact peptide-mediated lateral organ formation. As such, the project will also use this platform to define how peptide signaling shapes TF targeting in different lateral organs and interrogate the mechanisms underlying context-specific TF binding sites using a combination of genetic, biochemical, and genomics approaches. The project will also generate web-based interfaces for other researchers to explore and utilize data from the project, and hands-on workshops to train researchers in the use of the platform, expanding the impact of the project. This award was funded as part of a lead agency opportunity between NSF and Swiss NSF where NSF funds the US investigator, Swiss NSF funds the Swiss partner. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NSF Awards · FY 2025 · 2025-07

With the support of the Chemical Synthesis Program in the Division of Chemistry, Professor Qiu Wang of Duke University is studying new ways to use cyclopropanes as building blocks in organic synthesis. Catalytic methods are being developed that transform readily available cyclopropanes that lack traditional activating structural features, into high-value richly functionalized products that can be used in many industries, such as agriculture, consumer household products, materials, and those related to human health. These activities are providing training opportunities for students in organic synthesis and catalytic new method development. Outreach efforts are also being pursued to improve the STEM training pipeline, broaden student participation in research, and engage the local community. Synthetic applications of simple cyclopropanes to deliver versatile functionalized products without specific activating groups are highly attractive yet represent unmet challenges for organic chemists. Professor Wang and her research team are developing new catalysts and novel methods to achieve selective ring-opening/1,3-difunctionalization reactions of non-activated cyclopropanes. Strategies in copper catalysis, photocatalysis, and electrochemistry are being investigated to promote regio- and enantioselective carbon-carbon bond cleavage of cyclopropanes for the synthesis of 1,3-difunctionalized compounds and heterocyclic frameworks. New fundamental insights obtained in these studies are being used to further develop new multi-component processes for the preparation of highly sought-after targets in organic synthesis, medicinal chemistry, and agrochemicals. 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 · 2025-07

ABSTRACT Talaromycosis is caused by the dimorphic fungus Talaromyces marneffei (Tm) endemic in Southeast Asia where it is a leading the cause of death among patients with advanced HIV disease with a mortality on treatment of 30%. Treatment options are limited to just two drugs: amphotericin B deoxycholate (DAmB) which has substantial toxicity and itraconazole which has poor bioavailability. Our research team has recently delivered the landmark IVAP trial demonstrating the superiority of DAmB over itraconazole in survival and rate of fungal clearance, propelling DAmB as the first-line therapy in 2019. Although highly potent, DAmB infusion over 14 days is associated with serious toxicity; hence the drug has largely been abandoned in high-income countries. As a roadmap to identify safer and more effective antifungal strategies, our proposal applies three major advances made in AIDS-associated mycoses to accelerate treatment for talaromycosis. First, clinical trials in cryptococcosis show that shorter (5-7 days) courses of DAmB is as effective but less toxic than the standard 14- day course. Second, the AMBITION trial has shown that a single 10 mg/kg dose of liposomal amphotericin B (LAmB) is as effective as 7-14 days of DAmB but has 30% less toxicity, leading to rapid endorsement by the WHO as the first-line therapy for cryptococcal meningitis in 2022. Third, addition of flucytosine (5FC) to DAmB has been shown to be safe, improves fungal clearance and survival. These advances in cryptococcosis lead us to hypothesize that 1) a single 10mg/kg dose of LAmB will be superior to 14 days of DAmB and 2) the addition of 5FC will be superior to DAmB or LAmB alone in Tm complication free survival. We will build on our experience in leading the five-center IVAP trial in Vietnam to conduct a factorial, partially placebo-controlled trial to test two hypotheses within one LAmB-FAST trial, thus cutting time to knowledge and cost by half. We propose three related but independent specific aims: AIM 1. Determine if a single 10mg/kg dose of LAmB is superior to 14 days of DAmB in Tm complication-free survival. AIM 2. Determine if combination therapy with 5FC is superior to DAmB or LAmB alone in Tm complication-free survival. The primary outcome for both aims 1 and 2 is hazard of a composite of death, Tm complications, and AEs grade 3 or higher. Secondary outcomes include: 1) All-cause mortality; 2) Fungal clearance rate over first 14 days; 3) A novel 4-scale hierarchical outcome of i. Mortality, ii. Tm complications, iii. AE grade 3, iv. Quality of life scores; 3) Rates of Tm DNA and Tm antigen decline over first 12 weeks. In AIM 3, we will leverage rare access to a well-characterized and treated talaromycosis cohort to conduct a follow-on nested randomized controlled sub-study testing whether a HIV viral load guided strategy of stopping itraconazole chemoprophylaxis (STOP SHORT) is non-inferior the current CD4 guided strategy in the prevention of talaromycosis relapse and death. Impact statement. The results of this trial are likely to change treatment guidelines for talaromycosis.

NIH Research Projects · FY 2025 · 2025-07

Project Summary/Abstract Chagas disease, caused by infection with the parasite Trypanosoma cruzi, has been deemed the most neglected of neglected tropical diseases. The parasite is transmitted to humans by bloodsucking insects that usually live in cracks in the walls of mud and straw houses common to poor rural and urban communities. It can also be transmitted through blood transfusion and mother-to-child transmission, which is increasingly common. An estimated 10 million people are infected and 30-40% of those will develop severe and often fatal heart disease due to the infection. High rates of immigration from Latin America have brought many people who are unknowingly infected into the US, where doctors are unfamiliar with the disease. Most people are infected as children, a time when infection is “brilliantly treatable”, but only an estimated 1% of patients are treated. This is due, in large part, to the lack of an effective means to diagnose infection. Infection can only be diagnosed by blood sampling but the quality of rapid diagnostic tests currently available is poor. Multiple public health organizations have identified the development of high-quality point-of-care rapid diagnostic tests for Chagas as an urgent need. Here, we propose to generate a panel of antibodies that can detect T. cruzi, markers that circulate in the blood during infection. We have identified 3 candidate diagnostic T. cruzi Ags that are present in blood and highly conserved among all T. cruzi strains. Here, we will generate antibodies specific for these targets, determine their binding characteristics, and test their ability to detect these markers in blood serum obtained from dogs, non-human primates, and humans that acquired T. cruzi through natural infections. Antibodies that display good diagnostic accuracy in these studies will be selected for further characterization and development in future studies, so that they can be deployed in new high-sensitivity point-of-care diagnostic tests for Chagas Disease. We have previously used these procedures to develop a point-of-care diagnostic assay for Ebola virus that displays a sensitivity better than the current gold standard, PCR. The successful completion of these studies will result in the first antibodies diagnostic for T. cruzi infection, allowing construction of the first point-of-care assay that can detect markers of Chagas Disease in the blood. This work will thus markedly improve our ability to diagnose Chagas Disease, allowing early treatment and improved management of those who are infected.

NIH Research Projects · FY 2025 · 2025-07

Plasmodium falciparum control has stalled, and further progress reducing infections and deaths will require a highly-effective malaria vaccine. Individuals exposed to malaria develop protective immune responses gradually over several infections. Studies of immune responses to P. falciparum have consistently demonstrated that targets which exhibit very high diversity are critical for these protective responses. However, immunity to these antigens is dominated by strain-specific responses, which confer partial but imperfect protection to heterologous strains. This is a challenge for current vaccine candidates, including the first licensed malaria vaccine RTS,S, which are based on a single antigenic variant for a protein target and suffer from reduced efficacy to non-vaccine strains. There is evidence for strain-transcendent immunity in naturally exposed populations where individuals mount broadly protective responses after a few infections, despite the presence of dozens if not hundreds of different strains. Understanding how to elicit strain-transcendent immunity towards key, diverse antigenic targets has the potential to transform the next generation of vaccine products. Prior longitudinal studies of infection and disease are unable to furnish this insight mainly because they suffer from the inability to distinguish protection from lack of exposure in naturally exposed populations. As a consequence, there is no clear phenotype of protection, producing an incomplete understanding of the acquisition of protective immunity. Using our unique, longstanding cohort encompassing ~600 people in 75 households (initiated in 2017) in a high-transmission community in Western Kenya, we are able to pinpoint parasite transmission events to the individual-level, characterize the variant composition of multi-strain P. falciparum exposures, and document the outcome (no infection or protected vs. infected with or without symptoms) at the variant level. By leveraging known exposures to clearly define protection phenotypes within a natural system that encompasses a high degree of parasite diversity, we are uniquely-positioned to answer longstanding questions about protective immune responses. The goal of the proposed work is to use our unique system to advance multi-variant vaccine design. In our first Aim, we will quantify the strain-specific risk of malaria infection following a confirmed infectious bite (exposure). In the second Aim, we will leverage peri- exposure and post-exposure samples to correlate strain-specific protection following an infectious bite with strain-specific immune responses in order to identify strain-transcendent responses, and then identify variants that most effectively promote strain-transcendent responses. Our hypothesis is that a minimum set of strain- specific immune responses will be associated with strain-transcendent protection from infection after exposure. By exploring heterologous versus homologous strain-specific responses to elucidate a minimum set of antigenic variants required to confer strain-transcendent protection, we can facilitate the development and delivery of the next generation of P. falciparum vaccines.

NSF Awards · FY 2025 · 2025-07

This CAREER project studies the science of risk-taking. The PI specifically tests for the variables that impact decision-making in adolescence and young adulthood regarding their risks of injury, especially concussion and brain trauma. The research develops a data driven framework of how young people assess risk of brain injury and how that impacts their behavior and future goals. The broader impacts of the research involve collaborations with local and national agencies working towards mitigation of injuries and the implementation of safety measures. The integrated educational plan involves the establishment of a public-facing social science lab to train undergraduates in anthropological science and public health. The research will also inform the development of a new curriculum to train students and the public on the science of risk, injury, and medicine. In order to investigate the relationship between injuries and the science of risk among youth, the PI conducts qualitative research in both educational and clinical settings. The project utilizes a longitudinal research design that follows one cohort of youth over four years. The research includes a mix of qualitative research methods including life histories and clinical tracking of brain trauma. Research findings and broader impacts advance scholarship in the science of risk and decision-making, medical anthropology, and public health. 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

Over 100 trillion megabytes of data are currently consumed per year by mobile users in the U.S. alone. All this traffic is transported to users’ devices through cell sites (base stations) from the cloud. In a traditional cellular network, both the radio head and the baseband processing unit are located together at the cell site. In future radio access networks (RANs), the radio unit (RU) is located at the cell site while the processing unit is located at the distributed/centralized unit (DU/CU), which could be located in a metropolitan area. Fronthaul is a critical component of radio access networks (RANs), supporting the data transport between the RU and the DU/CU over a fiber optic network. Current mobile fronthaul employs digital radio-over-fiber (DRoF) technology based on digital interfaces such as the enhanced Common Public Radio Interface (eCPRI), which has a limited capacity and inefficient utilization of the underlying fiber networks. In contrast, analog radio-over-fiber (ARoF), which directly modulates radio frequency (RF) signals onto light for transmission over low-loss fibers at low latency, presents a promising approach for mobile fronthaul due to its high capacity and spectral efficiency, and the support of significantly simplified RU architecture. This project aims to enhance the efficiency and scalability of next-generation mobile networks by employing ARoF-based fronthaul. By moving away from the DRoF-based fronthaul approaches, ARoF-based fronthaul can facilitate more flexible network deployment, seamless integration with virtualized RANs, and efficient resource allocation across the wireless and optical domains. The research tasks proposed in this project target the following scientific directions over three interrelated research thrusts: (i) Development of a unified framework for efficient transmission of multi-band and coherent RF signals over ARoF-based mobile fronthaul; (ii) Design of an efficient control architecture for reconfigurable mobile fronthaul networks supporting the coexistence of heterogeneous signals, incorporating dynamic resource allocation across the wireless and optical domains while ensuring seamless and adaptive network operations; (iii) Development of and experimentation with novel communication, spectrum sensing, and resource allocation paradigms that can be uniquely enabled by ARoF signals traversing the mobile fronthaul network. This project plans to enhance the efficiency and scalability of next-generation mobile fronthaul. Specifically, this is expected to lead to expediting the adoption of ARoF technology in mobile networks and unleash the bandwidth capabilities of the fronthaul fiber, resulting in improved resource utilization in both the last-mile wireless access networks and the underlying fronthaul fiber infrastructure. By jointly optimizing the network performance across the wireless and optical domains, this project provides a meeting ground for wireless communication and optical networking research, and a platform to engage graduate, undergraduate, and high-school students in networking and communications research. 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

ABSTRACT Premature (i.e., occurring before age 40 years) and early menopause (i.e., occurring at age 40-44 years) significantly impact women (biological sex) treated for childhood, adolescent, or early-onset adult cancers. Among these women, premature or early menopause are common, resulting from certain chemotherapies (e.g., alkylating agents), radiation treatments (e.g., pelvic radiation), surgeries (e.g., oophorectomy), and endocrine therapies (e.g., ovarian function suppression). Premature and early menopause elevate the risk for cardiovascular disease, ischemic stroke, type 2 diabetes, osteoporosis, cognitive decline, neurological disorders, and depressive symptoms, which together result in an increased risk of morbidity and early mortality. The significant long-term health impacts of premature and early menopause are further exacerbated by the effects of women’s cancer treatments (e.g., chemotherapy-related cardiotoxicities). Women with premature or early menopause after cancer also commonly experience symptoms such as hot flushes, sleeping problems, and sexual dysfunction that have negative impacts on their daily activities and quality of life. There is a critical need for novel interventions to address the many challenges faced by women experiencing premature or early menopause after cancer. We propose to develop and pilot test a novel nurse navigator-delivered intervention that is guided by the Empowerment Model for Managing Menopause and integrates 1) personalized, risk-based menopause education and decision support guided by the Ottawa Decision Support Framework, 2) skills derived from patient activation theory to improve knowledge, increase self-efficacy, and increase engagement in self- management, and 3) cognitive behavioral based skills to manage menopausal symptoms. Intervention development and initial evaluation are consistent with Stage 1 of the NIH Stage Model for Behavioral Intervention Development. Aim 1. Preliminary intervention content will be developed with input obtained in interviews with women (N=24) experiencing premature or early menopause after cancer and medical providers (N=24) who care for this population. The prototype intervention will be refined with input by the study advisory council. Next, women (N=9) experiencing premature or early menopause after cancer will receive the intervention and provide feedback to further refine content, format, and procedures. Aim 2. Intervention feasibility and acceptability will be examined in a pilot randomized controlled trial (RCT). A new sample of women experiencing premature or early menopause after cancer will be randomized to receive the intervention or educational materials to examine the feasibility of study recruitment (N=60 in 10 months), participant retention (>80% intervention completion) and acceptability. We will also examine patterns of change in intervention targets (i.e., risk-based knowledge, decisional conflict, self-efficacy, patient activation and menopausal symptoms) and exit interview data from intervention participants.

NIH Research Projects · FY 2025 · 2025-06

PROJECT SUMMARY The neonatal period of life is a critical time of rapid development. To fuel this growth, the neonatal intestine must selectively absorb nutrients while establishing an immune defense against lumenal pathogens. These two core functions are intimately linked, as impaired nutrition early in life impairs systemic immune function. However, the connections between neonatal nutrient uptake and immune development remain poorly understood. Unlike adults, neonates utilize a unique mode of nutrient absorption: macromolecules are absorbed in bulk and subsequently degraded by lysosomes. Our lab has identified three transcription factors crucial to this process: MAFB, cMAF, and BLIMP1. Deleting these genes from the intestinal epithelium prevents macromolecular uptake, leading to neonatal malnutrition and lasting growth defects. Further, our preliminary data indicate that the loss of these transcription factors restricts T cell infiltration in the neonatal intestine, and leads to lasting defects in T cell localization in adults. However, the mechanisms through which MAFB, cMAF, and BLIMP1 control neonatal nutrition and intestinal immune development remain poorly understood. The long-term goal of this project is to elucidate the mechanisms that direct neonatal nutrition and immunity, and determine the long-term functional consequences to organismal health. There is a pressing need to understand nutrition-immune connections mechanistically, as undernutrition currently affects over 140 million children globally and is implicated in almost half of pediatric mortality cases. To this end, the aims proposed in this application will provide a mechanistic understanding of the role of MAFB, cMAF, and BLIMP1 in the neonatal intestine. Aim 1 will leverage bioinformatic analysis combined with genetic mouse models to define the gene regulatory networks controlled by these transcription factors, and how these networks control the function of absorptive epithelial cells. Aim 2 will utilize loss-of-function mouse models to determine how MAFB, cMAF, and BLIMP1 regulate the infiltration of diverse immune populations in the neonatal and adult intestine, and how these transcription factors impact immune cell function and susceptibility to infection. The proposed research will take place under the mentorship of Dr. Terry Lechler within the Duke University School of Medicine. This environment will provide a network of collaborators and experts (both clinical and basic science) in the fields of cell biology, developmental biology, and gastroenterology, that will provide input and feedback as this project progresses. This project will also utilize multiple core facilities and shred resource centers available on campus, in order to accelerate the progress of the proposed aims. The training plan also includes attending scientific conferences annually to receive feedback from the broader field. Together, the proposed project will reveal the molecular networks that control neonatal nutrition and immune development. This work will provide mechanistic insight into a poorly understood yet critical stage of life, and will inform future studies into the effects of neonatal malnutrition on human patients.

NSF Awards · FY 2025 · 2025-06

Technological advances have made it possible to collect massive datasets in many scientific applications. A major challenge is to create algorithms that can analyze these datasets efficiently while also providing guarantees on the quality of the analysis. This project focuses on iterative algorithms that start with an initial guess and then refine it until they reach a solution of the desired quality. Prior work has made it possible to design efficient iterative algorithms with excellent performance guarantees, under the assumption that all of the data is processed synchronously, without any losses or errors. However, large datasets often need to be distributed across multiple servers, leading to asynchronous updates, partial losses, and errors. The main contribution of this project is a novel framework for the design and analysis of iterative algorithms that process very large datasets in a distributed fashion. This framework naturally captures many of the phenomena that arise in distributed data processing, and can be used to design strategies that are more efficient than requiring the servers to maintain perfect synchronization. Furthermore, this research will train undergraduate and graduate students to be experts on distributed processing of massive datasets. It will also lead to the creation of educational materials, such as tutorial articles, focused on the statistical analysis of massive datasets. From a technical perspective, this project builds on the approximate message passing framework, which is an established methodology for precise probabilistic characterizations of iterative inference algorithms, such as matrix estimation and linear regression, in the high-dimensional setting. The project will expand the approximate message passing framework to scenarios with distributed, dynamic, and stochastic data processing. This framework will be used to create iterative algorithms that can handle partial updates, distributed computation, and dynamic data, as well as to maximize the efficiency of these algorithms, in terms of the number of iterations or the overall compute budget. The project will also explore a new proof technique based on Gaussian coupling in order to provide non-asymptotic guarantees on the performance of approximate message passing with long-term memory, non-separable denoising functions, and very high iteration counts. 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 groundswell of available data and computation power to learn from data has produced advanced automation across many domains, but cybersecurity has lagged these trends. Cybersecurity data sharing comes primarily in the form of indicators of compromise (IoCs) that describe patterns or artifacts that have already been classified as associated with malicious activity. Identifying malicious activity and distilling one or more IoCs from it, however, is often a manual process that is slowed and/or decayed by the siloed viewpoints of different organizations. This project's broader significance and importance are in pioneering a new approach to organizational data sharing that prioritizes support for targeted queries on the operational states of other organizations to overcome these siloed viewpoints. This project's novelties are in identifying opportunities for organizations to diagnose events by posing and responding to such queries and in developing technologies to do so, while simultaneously protecting operational privacy for the organizations. The technical core of this project is a new approach to intrusion detection enabled by cross-organization queries, supported by specialized cryptographic protocols to pose queries and receive responses in a way that minimizes collateral leakage. The project also contributes novel mechanisms to motivate participation in these data exchanges, and to prioritize the partners to which queries should be posed to receive the highest-quality answers. This project couples these technical advances with engagement with the operational cybersecurity community via the Workshop on Security Operations Center (SOC) Operations and Construction (WOSOC) and with foci on integrating this research into educational efforts at the investigators' institutions and in engaging students in research. In doing so, the project strives to align its technical vision with the needs of the operational community and to produce students who can effect this vision within it. 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 Center of Excellence (CoE) is a research initiative that brings together experts from various fields to develop innovative solutions for multi-scale modeling in infectious and immune-mediated disease (IID). The CoE consists of the: Administrative Core (AC), Community Development and Education Core (CDEC), Model and Data Sharing Core (MDSC), and three Research Projects (RP). Each component plays a crucial role. The AC serves as a central hub, connecting various entities, and plays a critical role in pivoting CoE resources during disease outbreaks. It administers the Opportunities Fund, supporting proposals from investigators across NIAID- sponsored modeling groups. The CDEC will develop educational resources, build communities of practice and learning, organize research experiences for graduate students and postdoctoral fellows, and set up document sharing facilities, messaging platforms, and a centralized website to facilitate knowledge sharing. The MDSC will develop an informatics infrastructure that enables seamless integration of data and models across different scales, facilitating more accurate predictions and informed decision-making. The RPs focus on bridging models of host-virus interactions across biological scales. RP1 models humoral defense against viral pathogens, using antibody-antigen molecular dynamics at the molecule scale to understand the constraints limiting the evolution of immune repertoires at the individual scale. RP2 models the immune cell as a target of viral infection, using agent-based models of lymphoid tissue at the cell scale to inform host-pathogen dynamics at the individual scale. RP3 models the interactions between individuals and populations, using agent based models of host-pathogen interactions at the individual scale to inform stochastic epidemic models at the population scale. The research focuses on modeling a set of clinically important viruses, including HIV-1, SARS-CoV-2, Epstein Barr Virus (EBV), and others. The models can be used to study disease pathogenesis, the effect of medical interventions, and disease transmission in heterogeneous population networks. Key strengths of the proposed CoE are (1) the ability to coordinate administrative approaches and technologies for the infectious disease modeling community; (2) a collaborative environment that encourages knowledge sharing, innovation, and the development of cutting- edge solutions; (3) balanced representation of the experimental and computational communities within each Core and RP; (4) extensive experience with IID modeling, team science, education, and community development; (5) robust informatics infrastructure for model and data sharing that already hosts large-scale NIH- funded projects; (6) exceptional strengths integrating generative deep learning with computational modeling in the MDSC and RPs, and (7) the importance of the proposed research to develop more accurate IID models that can inform public health policy and decision-making. The unique strengths of the proposed CoE make it an ideal platform for advancing IID research, developing innovative solutions to complex problems, and responding during infectious disease outbreaks, epidemics and pandemics.

NIH Research Projects · FY 2026 · 2025-06

Abstract Neuroimaging of infants and young children is increasingly used to monitor brain development that can ultimately influence long-term health and behavioral outcomes. Our research team is one of four centers participating in the Outcomes of Babies with Opioid Exposure (OBOE) study, a national effort to assess the effects of antenatal opioid exposure on baby development. These babies have neonatal opioid withdrawal symptoms at birth and struggle to maintain sleep or stillness during the MR scan. This patient population, and other pediatric patients in general, stress significant unmet needs for motion robust and quantitative imaging techniques for baby developmental assessment. However, there are unique challenges to imaging non-sedated babies using MRI, including high failure rate (no usable MRI data) due to motion, lack of quantitative and sensitive image markers for developmental assessment, and lack of imaging analysis tools specific for fast-evolving baby brains. In this proposal, we have established a multi-PI team, including MR Fingerprinting imaging developers (CWRU), baby imaging analysis and AI experts (UNC) and high-risk neonate clinical experts (UH) to address the unmet needs for baby imaging, and use the imaging tools to assess developmental delays of the opioid- exposed babies. We will achieve our goal with the following aims: Aim 1: Develop a motion-robust and comprehensive MRF scan to provide multiple quantitative tissue property maps for non-sedated babies; Aim 2: Develop baby-centric image processing tools and derive quantitative image features to characterize whole brain tissue changes; and Aim 3: Quantitatively assess developmental changes in opioid-exposed babies and predict the risk of developmental delays. This project will provide an imaging tool to relate quantitative features in brain structure and development to neurologic functions, opening the opportunity for early targeted interventions aimed at improving outcomes. The high quality, fast and motion robust MRF scans will have a broad impact for pediatric patients on improving scan success rate and reducing the sedation rate. The quantitative and comprehensive MRF scans will also have great potentials in assessing longitudinal changes regarding development alternations and therapeutic response.