University Of Wisconsin-Madison

NIH Research Projects · FY 2025 · 2025-09

PROJECT SUMMARY Dilated cardiomyopathy (DCM) is the most common form of heart disease and is characterized by patients developing ventricular dilation, contractile dysfunction and ventricular arrhythmias, which can ultimately lead to heart failure. A pathogenic mutation in the phospholamban (PLN) gene, resulting in the deletion of amino acid arginine 14 (PLN-R14del), has been associated with the onset of DCM. PLN is a transmembrane protein in the sarcoplasmic reticulum (SR) that is dynamically regulated by its post-translational modifications (PTMs) and plays a crucial role in calcium (Ca2+)-handling and heart contractility. The dysregulation of PLN's PTM state when mutated impacts its structure and ability to regulate SR Ca2+ ATPase (SERCA2a) and the translocation of Ca2+ ions. However, the molecular mechanism of pathogenesis remains unclear as a notable subset of carriers remain asymptomatic in later age, contributing to the high phenotypic variability observed with this mutation. Current treatments for PLN-R14del patients focus on symptom management rather than preventing disease progression, emphasizing the urgent need for a deeper understanding of PLN-R14del and its downstream consequences. Herein, I propose to leverage the power of high-resolution mass spectrometry (MS)-based proteomics, human clinical samples and patient-specific human induced pluripotent stem cell derived cardiomyocytes (hiPSC-CMs) to enable a deeper characterization of disease pathogenesis. I will use top-down proteomics to characterize proteoforms – protein products from a single gene resulting from genetic mutations, alternative splicing, or PTMs – which will be integrated and bioinformatically analyzed with bottom-up proteomics data sets to identify the molecular mechanisms, pathways and proteins involved in pathological remodeling. My novel top-down proteomics methods enable the characterization of proteoforms from diverse subcellular regions (membrane- bound, sarcomere, SR, mitochondria, etc.) with minimal sample requirements. These technological advancements will help bridge the gap between the genotype and phenotype of PLN-R14del patients. Aim 1 will comprehensively examine the molecular composition of human cardiac tissue from late-stage DCM patients with the PLN-R14del mutation compared to DCM patients with no PLN mutation and healthy donors with no cardiac history. To address the discrepancies between symptomatic and asymptomatic carriers, Aim 2 will utilize patient- specific hiPSC-CMs and proteomics to characterize the molecular and physiological differences between patients that carry the same mutation, yet express high phenotypic variability. The success of this work will provide a transformative understanding of the underlying biological mechanisms altered within PLN-R14del DCM and can aid in the pursuit of novel therapeutic strategies or targets for treating and perhaps preventing this devastating disease.

NSF Awards · FY 2025 · 2025-09

With the support of the Chemical Measurement and Imaging Program in the Division of Chemistry, Professor Randall Goldsmith of the University of Wisconsin-Madison will develop a chemical measurement system capable of measuring the time-varying charge on a dynamic single organometallic molecule. The new system will be able to reveal nuances in charge and coordination environment, an unprecedented new single-molecule measurement capacity, and an exciting result that paves the way to monitoring the shifting structure of a single catalyst molecule. This research will provide new insights into catalyst mechanisms by providing a molecular movie, revealing mechanistic details leading to the discovery of future catalysts and ultimately contributing to the development of new materials, cheaper fuels, and more accessible pharmaceuticals. Graduate and undergraduate students will gain highly interdisciplinary experience by blending reaction mechanism with cutting-edge instrumentation science. Outreach activities will involve K-12 students, teachers, and the general public in observing fluorescence from plants, microplastics, and even smaller items like single molecules using a portable microscope system. This research effort will develop a radically new way to encode information into the fluorescence of a single catalyst molecule. The proposed work will use single-molecule electrometry in which arrays of patterned nanowells create shallow electrostatic traps for solution-phase molecules. The rate at which the molecules leave these traps will be a sensitive function of their total charge, allowing a snapshot determination of the complex’s charge. This snapshot determination will allow a new perspective on catalyst charge dynamics of unprecedented detail, with measured effective charges reporting on catalyst oxidation state, ligand environment, and solvation. Most importantly, the measurement technique can be applied to chemically dynamic operational catalysts, allowing the observation of changes to the effective charge throughout the catalytic cycle, a unique measurement capability. 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 · 2025-09

Project Summary In the heart, perturbation in the balance of channels that produce the ventricular action potential (AP) can lead to dangerous arrhythmias and sudden cardiac death. How excitable cells regulate the precise the bal- ance of ion channels mediating electrical signaling is poorly understood. Previous studies in the Robertson lab have shown that ion channels are co-regulated at the translational level, via pairs of interacting mRNA during biosynthesis. My project aims to investigate how and where this cotranslational regulation occurs. Previous studies found that mRNAs of functionally related ion channels – including hERG1a, Cav1.2, Nav1.5, and KCNQ1- critical for the AP co-purify with nascent proteins via antibody pull-down. These associations were also identified using single-molecule fluorescence in situ hybridization (smFISH) combined with immu- nofluorescence. Similarly, alternative transcripts hERG1a and 1b associate during biosynthesis of heter- omeric channels producing the repolarizing current IKr. However, technical obstacles have limited the charac- terization of hERG1b within the regulatory framework of functionally related but distinct ion channels pairs. My project leverages RNAscope, a smFISH technique capable of detecting hERG1b to probe several key questions, and for which I provide preliminary data supporting its implementation. In Aim 1, I will determine whether hERG1a channels co-synthesized with functionally related channels are homotetramers, or whether they are heterotetramers with hERG1b. In Aim 2, I will determine whether these channel pairs are synthesized in the perinuclear ER, or near their functional domains. Using engineered micropatterned iPSC-CMs, and mature human myocardium I will apply RNAscope to test the hypothesis that a subset of translational com- plexes localize near insertion sites on the T-tubule and intercalated disc. This fellowship training plan is intended to prepare me for a career as tenure-track faculty and will include weekly mentoring sessions with Dr. Robertson to discuss progress toward IDP goals, participation in lab meetings, participation and presentation in journal clubs, managing collaboration with Dr. Lee Eckhardt’s lab, the cardiac tissue bank and the Translational Research Initiatives in Pathology lab, and mentoring students in a richly diverse laboratory. I will gain more knowledge in RNA biology, biogenesis, single-molecule micros- copy, advanced analysis techniques, and new human cellular and tissue cardiac models. I plan to broaden my network and present my work at local symposia and international conferences, with the goal of becoming a versatile and collaborative scientist prepared for the next steps in my career.

NSF Awards · FY 2025 · 2025-09

This project will provide all undergraduate engineering students at the University of Wisconsin-Madison a functional introduction to sustainability in the context of their engineering major. This is relevant to the continually evolving nature of the necessary body of knowledge in engineering, and how to create the engineers of the future which society needs, using the Engineering for One Planet (EOP) Framework which is aligned with the ABET learning outcomes. Future engineers will need to be prepared to address environmental and social sustainability for increasingly complex engineered systems that support human well-being. This need is already evident for some engineering disciplines, such as according to the American Society for Civil Engineering (ASCE) Code of Ethics, engineers are tasked with advancing and protecting the health, safety, and welfare of the public through engineering practice. In particular sustainability is also listed in the ASCE body of knowledge “The curriculum must include application of principles of sustainability, risk, resilience, diversity, equity, and conclusion to civil engineering problems.” This work will integrate sustainability into current systems and ensure future engineers are prepared for professional demands through curricular transformation that is needed which reevaluates and fosters fundamental sustainability skills and mindsets. This work aligns with the Research in the Formation of Engineers program (RFE) as it will advance the understanding of professional formation in engineering in that this work will transform engineering education so that all engineering students at UW-Madison encounter environmental and social sustainability principles as an integrated part of their education and are equipped with the tools needed to incorporate these principles into their future research, careers, and innovations. To engineer a sustainable future for the world, engineering education must first evolve as the required breadth of knowledge evolves. The overarching goal of USEE is for all undergraduate engineering students at the University of Wisconsin-Madison to be exposed to sustainability in the context of engineering at least once in their required course curriculum. The intellectual merit of USEE is multifaceted 1) it seeks to integrate sustainability into required undergraduate engineering curriculum in a relevant and sympathetic manner utilizing the EOP framework, 2) USEE seeks to generate new insights as to how exposure and experience with sustainability curriculum impacts the formation of engineering identities, and 3) USEE will generate new insight as to the education of faculty and instructors and their confidence in teaching about sustainability in an engineering context. In particular, USEE will focus on producing engineers who are ready to serve the public good. By nature, this project offers substantial broader impacts that are integrated into the research objectives. Overarching, USEE is transformative in creating new knowledge around the formation of engineers and sustainability. Beyond that, it seeks to educate around 4,000 undergraduate engineering students in sustainability over the course of the proposed timeline. Educational efforts realized during this project will be shared with the broader community in order to enable greater application of these methods, including challenges encountered during implementation and how those challenges are addressed. This project is funded by the Division of Engineering Education & Centers with additional support provided by The Lemelson Foundation. 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 · 2025-09

The end of the last ice age and its transformation of North American ecosystems provides a natural experiment for studying how far species and ecosystems can move as environments change and a naturally engaging way to teach students about the history of their local landscapes. This project will employ state-of-the-art open databases of fossils and Earth system models to map past biome distributions in North America and measure how far these biomes moved as ice sheets melted, temperatures rose, and rainfall patterns shifted. The project focuses on four major ecotones: Arctic treeline, the northern transition from temperate to cold-hardy trees, the eastern Great Plains, and the Great Plains transition between cool-season and warm-season grasses. These ecotones moved by hundreds to thousands of miles in the past; this project will more precisely estimate these movements and quantify the amount of movement per degree Celsius warming or mm rainfall change. This information is directly relevant to land managers and policymakers seeking to help species adapt to current changes and to mitigate risks associated with ecosystem transformations. The project will harness the rich datasets and visualizations produced by this project to develop a variety of data-powered and place-based educational materials for multiple student audiences and shared through multiple in-person and online venues. Land cover reconstructions for the last 21,000 years will be based on fossil pollen datasets drawn from the Neotoma Paleoecology Database and new compilations of carbon isotopic data. Land cover will be reconstructed using the REVEALS model and interpolated using a Bayesian hierarchical model with spatial dependence. Past temperature and rainfall patterns will be reconstructed using paleoclimate data assimilation (PDA), an ensemble of Earth system models, and over 600 proxy records from LiPDverse. A novel addition of statistical downscaling into the PDA workflow will enable high-resolution reconstructions and the modeling of local ecotone movements as a function of changes in temperature and rainfall. A hands-on, specimen-rich demonstration will be built for K-5 students and the general public that teaches about past ecosystem change and will be deployed via in-person science fairs, meetings of opportunity, and on-line educational portals. The project also will build new high-school to college-level curricular materials that draw upon these high-quality datasets and data visualizations, engaging students in scaffolded analysis and interpretation of data about ecosystem change at local to global scales. Curricular materials will be shared via the Teach the Earth website, which reaches >5 million visitors annually. This project also will engage with Tribal and agency land management professionals, train early-career researchers, and openly share these next-generation reconstructions of past environments and ecosystems. 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 · 2025-09

Glaciers and ice sheets move under their own weight, redistributing ice from regions of snowfall at high elevations to regions of ice loss at low elevations. A key driver of glacier movement is sliding at the ice-bed interface. A glacier’s sliding speed depends on the amount of water underneath the ice, with high water pressures typically corresponding to faster sliding. However, for many glaciers where the subglacial bed is soft and permeable, the complexity of water flow and drainage remains poorly understood. This project will investigate the movement of water at the ice-bed interface through a combination of laboratory and theoretical approaches. This project will support several undergraduate and graduate students and offer hands-on training in experimental and numerical techniques. The team will build an improved model of subglacial water flow, which will reduce uncertainty in future ice discharge from polar ice sheets, and ultimately lead to better forecasts of future sea level rise. The fast movement of many West Antarctic ice streams and outlet glaciers is due to slip at the ice-bed interface. Liquid water at the bed reduces the basal resistance to flow and increases slip speed. Experimental and theoretical studies have investigated the relationship between water pressure at the bed and basal resistance to flow, and identified that the effective pressure (the difference between ice overburden pressure and water pressure) is a key quantity. However, water pressure on soft (i.e., deformable and erodible) beds remains poorly modeled. This project will use a range of theoretical, numerical, and experimental techniques to (1) derive a model of distributed water flow in the bed-till aperture and within the till; (2) analyze the conditions that determine whether distributed drainage will occur predominantly within the till or at the ice-bed interface; and (3) solve this model numerically to determine how the system can be parameterized for large-scale simulations of the Antarctic ice sheet. This project will improve our understanding of basal slip and the effective pressure underneath glaciers, one of the main uncertainties in ice flow modeling. This in turn will lead to a better understanding of glacier and ice sheet dynamics, ultimately enhancing projections of future sea level rise and informing planning for coastal communities. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NSF Awards · FY 2025 · 2025-09

Recent advances in data science and statistics have revolutionized how researchers uncover cause-and-effect relationships from complex, real-world data. Many pressing questions—such as whether flu vaccination reduces infection rates, whether sanitation programs improve children’s health, or whether educational policies enhance student outcomes—cannot be answered through randomized experiments alone. Observational data, while abundant, often pose serious challenges due to hidden biases, unmeasured factors, or interconnected influences among individuals. For example, a person’s risk of flu depends not only on their own vaccination status but also on whether people around them are vaccinated, while unmeasured behaviors such as health-seeking habits can distort results. This project tackles these challenges by developing advanced statistical methodologies that improve the reliability of causal conclusions. In particular, it enhances a class of techniques known as distributional balancing methods, which create fair, comparable groups across the full range of observed variables. By extending these methods to account for complex data structures and unobserved confounding, the project will equip scientists and policymakers with more trustworthy evidence for decision-making. The research outcomes will impact healthcare, education, economics, and environmental policy, while also contributing to science through open-source software, user-friendly resources, and the training of students in cutting-edge statistical methods. Technically, the project focuses on two complementary innovations. First, it develops a novel framework for distributional balancing in settings where data exhibit dependency structures, such as patients treated within hospitals, students nested within schools, or individuals connected by social networks. The proposed methodology constructs balancing weights by aligning the joint distribution of covariates between treatment groups while explicitly accounting for clustering and network effects, which pose major challenges for current balancing methods. The approach includes diagnostic procedures for assessing covariate balance under dependence and robust sensitivity analysis for evaluating the stability of causal conclusions. Second, the project introduces a new integration of instrumental variable (IV) techniques with reproducing kernel Hilbert space (RKHS)-based distributional balancing. This extension allows researchers to address unmeasured confounding by leveraging valid instruments and estimating balancing weights with respect to flexible, nonparametric distributional distances. The resulting IV-balancing methods provide both theoretical guarantees and computational efficiency, expanding the toolkit of modern causal inference. Together, these methodological advances fill critical gaps in existing frameworks, enabling robust causal analysis in complex observational studies and yielding immediate applications in healthcare policy evaluation, biomedical research, and other domains where confounding and dependency are inherent. 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 · 2025-09

PROJECT SUMMARY/ABSTRACT Acute kidney injury (AKI), a serious complication in up to half of preterm neonates, independently increases morbidity and mortality. Current detection methods, such as near-infrared spectroscopy (NIRS), can identify kidney hypoxia—a precursor to AKI—earlier than traditional methods. However, effective therapies to prevent or treat AKI in this vulnerable population remain elusive. Intriguingly, non-randomized studies suggest that caffeine, a common medication in neonatal care, may lower AKI risk. Yet, rigorous investigations, particularly randomized trials focused on AKI prevention, are lacking since the landmark Caffeine Therapy for Apnea of Prematurity trial. Our long-term goal is to conduct a multicenter clinical trial to test the hypothesis that treatment of kidney hypoxia with caffeine will reduce rates of AKI and improve two-year-old kidney outcomes. “Optimizing Caffeine Therapy for Hypoxia in Preterm Neonates: A Randomized Trial Assessing Efficacy, Acute Kidney and Brain Injury, Safety, and Pharmacokinetics” is a five-year R01 that responds specifically to PAR-23-130: Translational Research in Maternal and Pediatric Pharmacology and Therapeutics. Our research team has developed the necessary protocols and tools using NIRS to measure kidney and cerebral oxygenation in preterm neonates. We have found significant associations between improvements in kidney oxygenation after daily maintenance doses of caffeine in preterm neonates with kidney hypoxia. We propose to investigate if an additional bolus dose of caffeine (either 10 mg/kg or 20 mg/kg) is more effective than placebo in treating kidney hypoxia in preterm neonates <30 weeks’ gestation with at least 30 minutes of kidney hypoxia (oxygenation <50%) in a randomized clinical trial. We aim to investigate the immediate and short-term kidney (Aim 1) and brain outcomes (Aim 2) and to develop a pharmacokinetic model of kidney hypoxia and caffeine levels (Aim 3). Our research stands out for its innovative approach: using changes in kidney oxygenation, measured by NIRS, as the primary outcome to promptly assess the efficacy of our proposed intervention. The research holds significant potential; should the intervention prove effective, it paves the way for a large-scale, multi-center trial aimed at investigating caffeine's role in preventing and reducing the incidence of AKI, as well as improving kidney outcomes over a two-year period. Our team, with its robust pilot data and dedicated focus on neonatal kidney research, is ideally suited to fulfill the objectives of this award.

NIH Research Projects · FY 2025 · 2025-09

Our goal is to improve the assessment of cutaneous wound healing by quantitatively measuring biomarkers of vascular perfusion and hypoxia. Our research employs photoacoustic imaging (PAI), which is an outstanding imaging modality for interrogating the entire wound depth at 4-5 mm in pre-clinical models and eventually in patients. For comparison, optical imaging methods cannot reliably measure biomarkers deeper than 1-2 mm into tissues. To meet this goal, we have developed Dynamic Contrast Enhanced (DCE) PAI that can evaluate vascular perfusion in wounds. Our DCE PAI approach can quantitatively measure pharmacokinetics parameters of perfusion rates of the agent in the tissue. We have also adapted our Oxygen Sensitive (OS) PAI method for wound healing studies that can measure oxyhemoglobin (HbO2), deoxyhemoglobin (Hb), total hemoglobin (HbT) and oxygensaturation (%sO2). We have shown that OS PAI and DCE PAI both detect early-stage wound healing which precedes a significant change in wound area. In an excisional model, showing the strong impact that OS- DCE PAI can provide. We will further refine OS-DCE PAI for imaging wound healing models. We will improve our methodology by performing DCE PAI with our advanced analysis method that avoids complications from variable light absorbance and scattering in deep tissues. We will investigate multiparametric analyses to demonstrate that combined measurements of oxygenation and vascular perfusion can improve wound healing diagnoses relative to a single parameter. We will also evaluate our DCE PAI method that uses a single absorbance wavelength relative to multi-wavelength imaging, which will expand our method to perform multislice PAI that can cover an entire wound. Imaging the entire wound will allow us to investigate the diagnostic utility of evaluating voxel distributions of our imaging measurements, and the utility of regional analyses. Each of these improvements is designed to improve the clinical translation of OS-DCE PAI. To demonstrate the strong impact of our research, we will use our OS-DCE PAI methodology to evaluate our excisional “punch” wound model, ischemic “crush” wound model, and burn model with normal mice and diabetic mice. Importantly, we have established each of these wound models in our research program. We will test diabetic mice to support eventual clinical translation, because diabetic patients with foot & leg ulcers and other wounds is a major chronic problem in current health care. Our deliverable is a new OS-DCE PAI method that will position us at the doorstep of clinical translation of our OE-DCE PAI method to monitor patients with burns, diabetic foot ulcers, and other wounds. Our top-ranked Burn and Wound Center at the University of Wisconsin is highly motivated to support clinical translation. The three manufacturers of clinical PAI instruments have expressed strong interest in our research with wound healing that can expand the market for clinical PAI.

NIH Research Projects · FY 2025 · 2025-09

Project Summary/Abstract Hematopoietic stem and progenitor cells (HSPCs) reside in a microenvironment that regulates their behavior by interactions with niche support cells. During development of the mammalian embryo HSPCs are born in the dorsal aorta and migrate to the fetal liver, where they expand and differentiate. Fetal liver HSPCs are proliferative and when transplanted have a greater capacity for reconstituting the blood system compared to quiescent adult HSPCs. However, the genetic networks regulating fetal liver HSPCs, and their maturation, are poorly understood. To dissect these networks, we are characterizing a viable integrin α4 (itga4) mutant zebrafish model with perturbed interaction between HSPCs and the mammalian fetal liver equivalent—the caudal hematopoietic tissue (CHT). Preliminary analysis of HSPCs at 5 days post fertilization (dpf), after migration from the CHT to the presumptive adult kidney marrow niche, detected transcriptomic and epigenomic differences between wild-type (WT) and itga4 mutant HSPCs, indicating reprogramming of HSPCs after interaction with the CHT niche. Gene Set Enrichment Analysis (GSEA) of differentially expressed genes between WT and itga4 mutant HSPCs showed enrichment of inflammatory signaling in itga4 mutant HSPCs which did not lodge in the CHT niche. Motif analysis of accessible chromatin regions unique to itga4 mutant HSPCs revealed potential regulatory factors of HSPC reprogramming, such as ets1 and AP-1 factors. We hypothesize that bypass of the CHT niche prevents correct HSPC programming and transition to quiescence, causing itga4 mutant HSPCs to remain in an immature state. In Aim 1, we will analyze the proliferative capacity, inflammatory profile, and stem cell capacity of HSPCs that did (WT) or did not lodge in the CHT niche (itga4 mutant) to characterize the programming event initiated by itga4-mediated interactions between HSPCs and the CHT niche. In Aim 2, we will map the epigenomic landscape and perform multiomic analysis of WT and itga4 mutant HSPCs to determine the gene regulatory networks underlying the developmental switch of HSPCs from proliferation to quiescence. We will utilize our unique zebrafish system and multiomic approaches to dissect the developmental networks of HSPC regulation. By understanding the transitions between proliferative and quiescent HSPC states, our findings could translate into novel approaches for stem cell expansion and improved stem cell therapy.

NSF Awards · FY 2025 · 2025-09

Bacteria commonly swim through complex biological fluids like mucus, playing a crucial role in health and disease, from infections in the lungs to microbial imbalances in the gut. Understanding how bacteria move through biological fluids is the first step toward developing new ways to cure and prevent such infections. Many mathematical tools describing how microorganisms swim through fluids like water were developed in the 1950s-1970s. These foundational theories continue to be used today. However, mucus is a far more complex and challenging environment than water. It is composed of macromolecular proteins (mucins) that confer it viscoelastic properties, simultaneously flowing like a fluid, yet capable of recoiling like elastic solids. Mathematical tools for studying bacterial locomotion through such complex biological fluids are lacking. This research will combine mathematics, computer simulations, and laboratory experiments to create a more comprehensive picture of this process. It will first investigate the fluid mechanics of propulsion through complex fluids using a single bacterial flagellum. This will be followed by a study of how multiple flagella bundle together, a standard feature of many bacteria like E. coli. Finally, the collective behavior of large groups of bacteria in fluids like mucus will be investigated. Knowledge so gained will be instructive in the design of new medicines, the prevention of dangerous infections of mucosal surfaces, and in the management of stubborn biofilms. The research focuses on bacterial flagellar propulsion in mucus, and in a better-controlled anisotropic, viscoelastic fluid: a lyotropic liquid crystal (LC). Using mathematical modeling and analysis, numerical simulations, and experiments, this project will address three interconnected problems. First, a novel slender body theory will be derived from first principles, alongside controlled experiments, to quantify the forces, flow fields, and resulting dynamics of individual bacterial flagella within a nematic LC environment. Theories will be tested against full numerical simulations of Ericksen-Leslie and Beris-Edwards model LC fluids. The first aim will be extended to encompass the coordinated behavior of multiple flagella forming helical bundles, a key aspect of bacterial locomotion. Finally, the emergent behavior and dynamics of many bacteria interacting within LCs will be modeled and analyzed, bridging the gap between individual flagellar mechanics and population-level phenomena. The expected outcomes include significant advances in our understanding of general fluid-structure interactions in complex biological media. The mathematical machinery developed will be applicable to a wide range of nearby problems in biology and engineering and will illuminate new mechanical aspects of evolutionary biology. 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 · 2025-09

Project Summary/Abstract The long-term objective of the research is to understand the mechanism of general anesthesia, relating specific molecular- and cellular-level targets to their behavioral-level consequences. This proposal focuses on the role of hippocampal GABAA receptors in the suppression of learning and memory. Three specific aims test the hypotheses that etomidate and other general anesthetics suppress memory by targeting 5-GABAARs on Lamp5-expressing interneurons (Lamp5-INs), that they do so through an excitatory action on the axons of Lamp5-INs, and that they enhance memory by targeting one of the classes of non-Cck-INs. Specific Aim 1) Test the role of 5-GABAARs on Lamp5-INs in etomidate modulation of inhibitory neurotransmission and memory, studying mice in which 5-GABAARs have been eliminated from Lamp5-expressing interneurons, testing effects of etomidate on contextual conditioning, on place cell and spatial engram formation as neural correlates of hippocampal memory, and on anesthetic-induced changes in neurotransmission. Specific Aim 2) Identify the interneuron subtype(s) that counteract Cck-INs to enhance memory, studying mice in which 5-GABAARs have been eliminated using combinations of Cre-drivers. Specifc Aim 3) Test whether other anesthetics suppress memory through 5-GABAARs on Lamp5-INs, studying effects of propofol, midazolam, sevoflurane, and ketamine on contextual conditioning and place cell and spatial engram formation in mice in which 5-GABAARs have been eliminated from Lamp5-expressing interneurons. Overall, the experiments will further our understanding of the mechanisms by which anesthetics suppress learning. More broadly, they will contribute to our basic understanding of how memory is supported and controlled by interneurons. Given the essential role of interneurons in circuit function, the results will have widespread application to learning deficits in Alzheimer’s disease and numerous other diseases associated with impairments of learning and memory.

NIH Research Projects · FY 2025 · 2025-09

Project Summary Sensorimotor adaptation, learning from the mismatch between the predicted sensory feedback of our intended motor action and the actual sensory feedback we observe, is a fundamental skill that supports accurate movement control, such as speech. One common paradigm used to study the mechanisms of speech adaptation is examining how speakers adjust their speech production in response to an external perturbation applied to the auditory feedback of their speech acoustics in real time. While this paradigm has been proposed as a tool to assess the mechanisms of speech deficits in various neurogenic disorders, reduced speech adaptation is commonly found across various clinical populations, despite impairments in very different neural structures. This pattern is not well-predicted by the current models of speech motor control, potentially because speech adaptation may not involve a single learning process (as in current models) but, as suggested by extensive work in other (nonspeech) motor domains, two distinct processes – a fast process that learns quickly from error but retains less, and a slow process that learns slowly but retains more. Here, we test the hypothesis that adaptation in speech, like in other motor domains, involves separable fast and slow processes by translating a behavioral paradigm known to uncover multiple learning processes across motor domains to speech for the first time (Aim 1). Separately, we will test the neurocomputational basis of adaptation by combining this novel behavioral paradigm with continuous theta-burst transcranial magnetic stimulation to temporarily inhibit regions known to affect adaptation (Aim 2). By assessing behavioral correlates of both fast and slow processes after stimulation, we can separately assess which regions are involved in each process. We test this both in speech and, as a control, in reaching, which is known involved both the fast and slow processes. As the neural networks underlying these separate processes in reaching have not been well established this work additionally provides the first assessment of the neurocomputational basis of adaptation across multiple motor domains, allowing us to test the domain generality of the two-process model of adaptation. Even in the case that we only find a single adaptation process in speech, comparison of the neural findings in speech and those in reaching allows us to test whether the neural substrate underlying speech adaptation maps onto the analogous regions involved for the fast or slow process (or both) in reaching. This research will improve our understanding of the computational processes in speech adaptation and refine the neural mechanisms of sensorimotor adaptation across all motor domains. This work will provide a first step towards developing more sensitive measures that can differentiate control deficits through speech adaptation which may help the development of speech therapy that precisely targets the mechanisms of speech deficits across various clinical populations.

NSF Awards · FY 2025 · 2025-09

Non-technical abstract: The collective behavior of quantum particles that compose materials presents us with numerous puzzles. This project aims to solve some of these puzzles by recreating such collective behavior within superconducting circuits. The project employs fluxonium qubits, which behave like magnetic atoms when cooled to low temperatures. Utilizing the greater freedom in design and the control that circuits provide, the research team intends to study multiple collective phenomena that appear in materials with magnetic impurities. Such phenomena include transitions between quantum phases of matter, quantum entanglement, and the process by which quantum systems reach thermal equilibrium. The research results are expected to advance our understanding of quantum states of matter. Selected ideas inspired by the research are adapted for live demonstrations presented by the principal investigator during The Wonders of Physics annual shows at the University of Wisconsin-Madison, as well as for museum exhibits, and for hands-on activities designed for teachers, thereby increasing K-12 students' engagement with quantum science and technology. The research activities provide training in state-of-the-art quantum information science and condensed matter physics to undergraduate and graduate students. Technical abstract: While quantum many-body phenomena play a central role in condensed matter physics, their experimental investigation is often challenging in natural settings. This project uses superconducting circuits to develop a scalable platform for analog quantum simulations of several many-body models. The platform's key elements are fluxonium qubits, chosen for their strong anharmonicity and record-high coherence, and high-impedance transmission lines. Employing fluxonium in the role of spin, the project aims to implement single- and multi-channel Kondo, two-impurity Kondo, Kondo lattice, and spin chain models. The research goals include testing theoretical predictions for a ferromagnetic–antiferromagnetic quantum phase transition, entanglement scaling, non-Fermi liquid behavior, and many-body localization. The research findings are likely to provide new insights into fundamental problems in condensed matter physics, including quantum phase transitions, high-temperature superconductivity, heavy-fermion materials, and the thermodynamics of large quantum systems. The latter is not only of fundamental interest but also helps in the design and control of multi-qubit quantum processors. 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 · 2025-09

The understanding of the origin of ultra high-energy particles and light is one of the central challenges in contemporary astronomy and astrophysics. It is a study that will lead us to a better understanding of the dynamics of the cosmos. The High-Altitude Water Cherenkov Observatory (HAWC), a technologically advanced gamma-ray and cosmic-ray detector located on the slopes of Sierra Negra volcano in Mexico, is among the most sensitive gamma-ray observatories in the world. Since 2015, HAWC has accumulated high-quality data sets of gamma rays and cosmic rays from the Northern sky. This project will study high energy gamma rays and cosmic rays recorded by HAWC, with the goal to uncover the nature of extreme astrophysical objects that emit light at energies of trillions of electron volts (TeV). These studies will contribute to our understanding of particle acceleration and its propagation in space. In parallel to advancing scientific knowledge, this project prepares students across educational levels to join the national science and technology workforce. The project will bring the excitement of this research to the public through outreach activities. Taking advantage of HAWC's new data pass and by implementing advanced analysis algorithms, these gamma-ray studies will tackle important questions of gamma-ray astrophysics. A central focus is the investigation of TeV halos, which are extended gamma-ray structures surrounding middle-aged pulsars. The research will involve identifying new TeV halos, characterizing their morphology and spectral properties, and interpreting these findings in the context of local particle injection and diffusion in pulsar environments. Additionally, the team will analyze HAWC's cosmic-ray data to measure and interpret anisotropies in the arrival direction distribution of Galactic cosmic rays. These complementary studies aim to improve our understanding of particle acceleration mechanisms, transport processes, and their role in shaping the high-energy universe. This project advances the objectives of "Windows on the Universe: the Era of Multi-Messenger Astrophysics", one of the 10 Big Ideas for Future NSF Investments. 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 · 2025-09

This project focuses on complex analysis, a branch of mathematics that investigates the theory of calculus over the complex. Complex analysis serves as an important tool in numerous applications: It plays a crucial role in physics (e.g., modeling airflow over airfoils and analyzing dispersion relations in optics), engineering (e.g., signal processing and control theory), and computer science (e.g., image processing and quantum computation). The theory of complex analysis in one variable is classical and well understood, but when additional variables are introduced, many mysteries remain. In this project, the investigator will further the theoretical understanding of complex analysis of several variables. The proposed activities also involve collaboration with and mentoring of junior researchers at the undergraduate, graduate, and postdoctoral level. The investigator will study the Gromov hyperbolicity of the Kobayashi metric; regularity properties of biholomorphic mappings between families of domains in complex Euclidean spaces; quantitative versions of the Hartogs’ extension theorem and analytic continuation; and proper holomorphic maps between unit balls. These topics involve a range of mathematical fields, including differential geometry, metric geometry, geometric group theory, Lie theory, and dynamical systems. Thus, the project will not only contribute to the field of several complex variables but also strengthen its ties with these other areas. 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 · 2025-09

Sodium metal anode-based battery chemistry is a promising candidate for next generation energy storage systems due to its high energy density, natural abundance, and low cost. These advantages make it well suited for large-scale or grid-scale applications such as electric grids and transportation. However, the practical use of sodium batteries is hindered by challenges in controlling the battery materials’ decay, which directly affects battery performance attributes such as power, shelf life, and cycle life. This project will develop new materials characterization tools to study the interior of the batteries’ materials under changing conditions similar to how it would operate to store and discharge energy. The resulting fundamental knowledge will help enable the rational design of next generation batteries and electrochemical systems. These insights will not only promote the progress of science but also support the development of alternative energy storage technologies beyond lithium-ion, contributing to enhanced national energy security and use of domestic critical materials. Additionally, the project will engage undergraduate and graduate students through hands-on research experiences, while expanding science outreach to K-12 students to promote scientific literacy and awareness of sustainable energy. These efforts will help expand the workforce in science and engineering and help cultivate a skilled workforce to address future energy challenges. This project will advance fundamental understanding of the interfacial solvation structure and dynamics at sodium metal–electrolyte interfaces in sodium-ion batteries, a critical yet underexplored area in battery science. The project will develop and apply advanced characterization techniques that integrate high resolution spectroscopy with electrochemical measurements. These tools will enable direct investigation of both static and dynamic molecular interactions at the metal–electrolyte interface, providing unprecedented spatial and temporal resolution. Specifically, the project will probe processes such as solid electrolyte interphase formation and ion transport, which are critical to the development of more stable and efficient sodium metal batteries. The insights generated through this work will inform the rational design of electrolytes and interfaces for sodium metal batteries and, more broadly, for emerging energy storage 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 · 2025-09

The objective of this EArly-concept Grants for Exploratory Research (EAGER) project is to support research focused on developing and piloting a novel method for faster and more accurate assessment of flood mitigation infrastructure performance. While billions of public dollars have been invested in levees, detention basins, channel realignments, and other flood-mitigation infrastructures, nationwide assessment of their performance is lacking. Few researchers have attempted to merge infrastructure records with continent-scale satellite observations and replace anecdotal, piecemeal evaluation with satellite-verified report cards. The research looks to advance knowledge by generating observed flood data to measure if and where such infrastructures reduce flooding in the US. The research trains undergraduates and postdocs to produce data science tools and prepares them for artificial intelligence, remote sensing, and other technical career opportunities. Current floodplain maps underrepresent flood risk, which most research attributes to failure to produce frequent updates or incorporate different flood drivers. Yet, the “undermapping” phenomena could also be due to reductions in regulatory floodplains though the Letters of Map Revision (LOMR) policies. While traditional assessment relies on expensive physics-based flood models and site investigations, this research project seeks to develop and pilot an observation-based method that enables faster and more accurate assessment of flood risk reduction. Two key questions look to be addressed: 1) where flood mitigation infrastructures are effective at reducing flooding in the US and 2) where new opportunities exist for optimal investment. The research project will analyze locations where flood maps have been modified due to LOMR policies and will look to build a tempo-spatial database of flood events from multiple satellite observations from 2001 to 2025 using machine learning. The database will then augmented with layout of flood mitigation infrastructures. All code, time series, satellite flood layers, and flood exposure change analytics will be released as open-source, enabling engineers, planners, insurers, and researchers to prioritize investments, calibrate models, and design innovative solutions. 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 · 2025-09

The behavior of ice sheets during past warm periods can be used to help us better project how ice sheets and sea level will respond in the future under conditions of sustained warming. In turn, this knowledge can be leveraged to help build more resilient coastal communities and protect and defend our coastlines. Currently there is debate about the dynamics of the polar ice sheets during the most recent past warm period in the geological record, known as the Last Interglacial around 125,000 years ago. Some reconstructions for this time interval suggest a stable/slow rising sea level from ice sheets retreat, while others cite evidence consistent with more variable sea level from rapid ice sheet volume changes. While evidence for this problem remains controversial, a new methodology was recently applied, and firm evidence was found for a brief local fall in sea level at a single location. However, the timing and rate of sea level change are still poorly constrained, and the global extent of this feature remains unknown. This project seeks to build on this new approach and combine it with high-precision dating to refine our understanding of the rates and extent of Last Interglacial ice sheet retreat and sea level change. This project will provide professional development and mentoring opportunities for the fellow and develop a virtual field trip website using drone and other imagery to expand accessibility of sea level research. Shallow marine carbonates such as coral reefs can be used to help reconstruct the magnitude of past sea level changes. This project will leverage existing samples collected from fossil coral reefs around the globe that grew during the Last Interglacial. The focus will be on Last Interglacial coral reef deposits in Western Australia and the Seychelles that contain three distinct generations of reef growth separated by disconformities or transitional sedimentary facies, to test the question of sea-level variability. The main goals of the project are (1) to assess whether there is evidence of subaerial exposure associated with the sedimentary surfaces bounding the reef units and (2) define the time represented between the deposition of reef units. New cutting-edge, super resolution autofluorescence (SRAF) microscopy that can reveal fine-scale carbonate petrography will be combined with U-series coral geochronology within detailed stratigraphic frameworks to determine the timing and magnitude of potential subaerial exposure events and to correlate observed relative sea-level change between sites. This project will produce important proxy data to calibrate and improve ice sheet models to determine which ice sheets were most susceptible to past warming and how future ice sheet retreat will affect U.S. and global coastlines. 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 · 2025-09

Hydrogels have great potential for applications in healthcare, robotics, and more. Additive manufacturing of hydrogel enables building 3D objects with sophisticated structures. However, a key challenge is the lack of cost-efficient methodologies for designing the hydrogel synthesis and printing processes together to achieve desired product performance. This award enables research in creating hydrogels with customized features tailored for distinct applications with lower cost, reducing the cost of additive-manufactured hydrogel products. If successful, the outcomes of this research are expected to shorten the design cycle of new materials and processes and facilitate wide utilization and rapid scale-up to industry. This research aims to develop a unique analytical design framework, consisting of (a) interpretable and efficient uncertainty quantification models that adaptively accommodate the model complexity and (b) a unique decision algorithm for the multistage experiments that simultaneously decides the next experimental operation and the volume of material, in order to make diverse products achieving multiple targeted functionalities. Additionally, the experimental platform, dynamic-fluid-assisted micro-continuous liquid interface printing (DF-μCLIP), offers a dedicated “hardware in the loop” system that synergizes in-situ hydrogel synthesis and printing for implementing the design optimization procedure. The resulting integrated material discovery and manufacturing platform has broad potential impact across material and manufacturing systems. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NSF Awards · FY 2025 · 2025-09

Technologies that are essential for modern life, from computers to jet engines, rely on advanced materials. Easily accessible data on materials properties is critical to allowing developers of technologies to determine what materials they need and to helping guide researchers in the development of new materials. However, materials data is typically shared through millions of scientific papers, making it difficult to develop a database of relevant properties. The recent advent of large language models (LLMs), like ChatGPT, now make it possible to automate the complex task of reading thousands of papers and extracting key data. This project refines the use LLMs to extract data and related knowledge from scientific papers, including from text, tables, and plots. The project then develops an easy to use web interface to allow people to apply these methods and quickly access large amounts of automatically curated materials data. If successful, it will allow entrepreneurs, engineers, and scientists to quickly extract specialized curated databases from the vast scientific literature and help accelerate technological developments across the many industries that used advanced materials. The platform allows users to extract structured materials data from text, tables, and plots, and extract complex Processing-Structure-Property-Performance (PSPP) relationships. Designed for accessibility, the interface will require no expertise in LLMs or coding, making it a powerful tool for researchers across disciplines. The service will utilize state-of-the-art LLM text and image capabilities and integrate cutting-edge LLM workflows, including prompt engineering, chain-of-thought reasoning, and retrieval-augmented generation, supported by a robust backend architecture (FastAPI, React.js, Material-UI). The Intellectual Merit of the project includes both the development of practical methods for accurate materials data extraction with LLMs and development of online resources to deliver those methods to non-experts. The project develops methods to overcome limitations in existing data extraction techniques by leveraging LLMs advanced capabilities in zero-shot learning, chain-of-thought reasoning, and multimodal data analysis. Key broader impacts include (i) advancing data-centric science by enabling rapid database creation, (ii) improving education by putting outcomes into summer schools, conferences, and courses, (iii) increasing training of undergraduates in hands-on research building skills in coding, machine learning, and project management, and (iv) increasing training for graduate students in both materials science and advanced data science, preparing them for leadership in these critical fields. This award by the Office of Advanced Cyberinfrastructure is jointly supported by the Division of Graduate Education within the Directorate for STEM Education and Division of Material Research within the Directorate of Mathematical and Physical Science. 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 · 2025-09

This REU program addresses critical national challenges related to the aging highway infrastructure and limited maintenance funding by preparing undergraduate students to apply digital technologies to infrastructure engineering. Focusing on digital twins—virtual models that mirror physical road assets—the program equips students with the knowledge, skills, and tools to improve infrastructure monitoring, decision-making, and long-term resilience. It supports NSF’s mission by advancing science, promoting national welfare, and developing a skilled STEM workforce capable of leading digital innovation in infrastructure. Through hands-on research, mentorship, and international collaboration, students gain interdisciplinary experience that blends engineering, computing, and data science. The program also broadens access to emerging research areas and prepares participants for graduate study and future careers in infrastructure systems. The objective of this REU site is to engage U.S. undergraduate students in interdisciplinary research on digital twins for road infrastructure. Over three summers, 24 students from West Virginia University, the University of Wisconsin–Madison, and nearby institutions will participate in a 10-week program—eight weeks at U.S. host institutions, followed by two weeks at the University of Cambridge’s Laing O’Rourke Center. Students will conduct research on data acquisition, modeling, simulation, and decision-support tools for digital replicas of road assets. Activities will address challenges such as creating scalable models, integrating sensor data, and validating digital twin outputs for infrastructure monitoring and maintenance planning. The program combines civil engineering, computing, and data science to expose students to real-world infrastructure systems and emerging digital technologies, while fostering transatlantic collaboration and broadening their academic and professional perspectives. This project is jointly funded by the Division of Engineering Education and Centers (EEC) and the Division of Civil, Mechanical and Manufacturing Innovation (CMMI). 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 · 2025-09

PROJECT SUMMARY Kaposi's sarcoma, caused by Kaposi's sarcoma-associated herpesvirus (KSHV), remains a major health challenge for people living with HIV and other immunocompromised patients. While research has historically focused on the latent cycle of KSHV infection, recent evidence demonstrates that viral reactivation to the lytic cycle is crucial for tumor development through growth factor secretion and maintenance of latently infected cells. This central role of the lytic cycle offers a new therapeutic opportunity. Therefore, there is a need to discover strategies to block KSHV reactivation and its associated pro-tumor activities, as a starting point to develop new targeted therapies. Type I interferons (IFNs) potently block KSHV replication at early stages of the lytic cycle. However, direct IFN administration causes severe systemic side effects in patients, limiting its use. We recently discovered that KSHV hijacks cellular caspase enzymes to suppress IFN responses. This finding suggests that caspase inhibition could restore antiviral IFN responses in infected cells and serve as an alternative approach to leveraging IFN response for therapy. However, we do not yet know whether manipulating caspase activity and type I IFNs can block the pro-tumor activities of lytic replication. This is because IFN responses have been studied in conventional 2D cell culture infection models that poorly mimic KSHV infection in tumors. To address this gap, we will use a recently developed 3D primary human endothelial cell organoid model. These organoids better recapitulate characteristics of Kaposi’s sarcoma tumors, including stable maintenance of the latently infected cell mass through spontaneous viral reactivation and changes in cell morphology and differentiation. We will use this new model to test the hypothesis that activation of the IFN pathway, either through direct IFN administration or caspase inhibition, disrupts two key tumorigenic processes due to lytic reactivation: growth factor secretion and maintenance of the latently infected cell population. We will first dissect type I IFN and caspase signaling during KSHV infection in organoids and compare it to IFN and caspase activation in Kaposi’s sarcoma tumor tissue (Aim 1). We will then test how inducing IFN responses through direct IFN administration or caspase inhibition affects growth factor secretion and maintenance of the latently infected cell population (Aim 2). This study will thus evaluate the potential for modulation of caspases and IFN responses in blocking KSHV tumorigenic activities and as therapeutic strategy against Kaposi’s sarcoma. Success could lead to new targeted treatments for Kaposi’s sarcoma while providing a foundation for future mechanistic studies of KSHV pathogenesis.

NSF Awards · FY 2025 · 2025-09

The Paleobiology Database (PBDB) is one of the most impactful and widely used digital representations of the fossil record, capturing our best understanding of the age, location, identity, and geological context of fossils. Data held in the PBDB have been used in over 2,000 scientific publications and in a wide range of educational and public outreach materials. The PBDB is an essential resource for geoscientists, biologists, students, educators, and the public. Although the research and educational impact of the PBDB is tremendous, there are key issues with its current computer infrastructure, which was designed in the late 1990s and early 2000s. This project will combine PBDB with the Integrative Paleobotany Portal (PBot) to create a more modern and flexible digital system: the PBDB 2.0. Planned project activities will transform the PBDB to be more useful to a broad community of researchers, educators, and students in the Earth and life sciences, as well as the general public. In particular, the PBDB will adopt features from PBot that will allow users to easily contribute and interact with fossil identifications tied to specimen images, and outreach activities will further motivate community participation with PBDB. This project undertakes a complete technological overhaul of the PBDB, one of the most prominent and widely used fossil databases. Technical improvements include coupling the PBDB with the PBot, whose cutting-edge conceptual framework provides innovative user-centric capabilities. Specifically, development of the PBDB 2.0 will: 1) overhaul the PBDB's data model, database, and application logic to integrate PBot functions, streamline data entry, and improve technical sustainability; 2) create a more capable application programming interface; 3) construct a new web application to leverage back-end upgrades and facilitate new science; and 4) host community events and activities to assess progress, train new members, mobilize data, and produce new educational/outreach materials. Long-term costs of paleobiological cyberinfrastructure will be substantially reduced by consolidating development effort, expanding the PBDB's current functionality to better serve a large community, enhancing overall user experiences, mobilizing new science-critical data, and improving alignments with other data systems. Upgrades will provide explicit support for uncertain taxonomic classification, introduce a more specimen-forward approach to organizing fossil data, make high quality specimen images available alongside data, and add workbench capabilities. Researchers from around the world will utilize the PBDB 2.0 to understand Earth history and Earth systems processes, conduct Rules of Life research, and interpret ecological and evolutionary change across all taxonomic groups, continents, and time periods. The refreshed PBDB 2.0 will make it easier for anyone in the broader community, from professional Earth and life scientists to children, to engage with fossil science. This award by the Geoinformatics program within the Division of Earth Sciences is jointly supported by the Infrastructure Capacity for Biological Research program within the Division of Biological Infrastructure. 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 · 2025-09

Oxygen is crucial for macroscopic life, yet the causes and repercussions of its accumulation in the atmosphere are poorly understood. A key question for resolving the trajectory of planetary habitability is if chemical shifts recorded in ~2.4-2.0 billion-year-old rocks reflect global-scale oxygen changes or regional-local conditions. To answer this question, rock cores from Gabon, which hosts the best-preserved sedimentary archive across this interval, will be analyzed for possible chemical imprints of oxygenation. This project serves the national interest by promoting the progress of fundamental science that identifies how Earth became habitable. Synergistic outreach objectives include initiatives such as community tables at farmers’ markets from Northeast-Midwest USA to enhance public scientific literacy and undergraduate curriculum development to support an American STEM workforce that is globally competitive through improved education. This interdisciplinary project applies stratigraphy, paleomagnetism, geochemistry, and geochronology to assess whether extreme geochemical shifts in the wake of the Great Oxidation Event (GOE) reflect global, regional, or local-diagenetic conditions. Laterally correlative drill cores across shallow-to-deep paleoenvironments in the Francevillian sub-basins of Gabon will be applied to test the hypothesis that, in the Paleoproterozoic, there was a prolonged overshoot in O₂ coeval with a widespread perturbation of the carbon cycle. The objectives are: 1) Create a detailed stratigraphic framework and isolate primary magnetizations to examine facies and latitudinal climate-belt controls; 2) Assess a variety of isotopic and geochemical criteria in carbonates to determine if a primary “oxygen overshoot” is preserved; and 3) Apply U-Pb zircon geochronology/geochemistry and carbonate Rb-Sr isotope compositions to evaluate if geochemical shifts are of global relevance. The results will facilitate detailed tracking of the dynamics of oxygenation and concurrent environmental changes in the wake of the GOE—including extraordinary disturbances to the carbon cycle—that are key for deciphering this tipping point in the trajectory of planetary habitability. 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.