University Of Texas At Austin

NIH Research Projects · FY 2025 · 2025-09

PROJECT SUMMARY To realize the potential of peptide- and protein-based therapeutics, conformational control is essential. Current strategies focus on either optimizing the amino-acid sequence toward a desired structure or creating covalent bonds between amino-acid side chains to restrict conformational flexibility. Though these strategies have demonstrated important successes, they require extensive optimization and limit the availability of side-chain functionalities that could instead be optimized for target engagement. A central goal of our laboratory is therefore to develop more general strategies to specify peptide/protein structure. To do so, we will evaluate new chemical approaches to preorganize individual amino acids without sacrificing side-chain functionality. Inspired by differences in the conformational propensities of natural amino acids, we will synthesize minimally modified amino-acid analogs that favor specific secondary structures. Initial priorities include the synthesis of amino-acid analogs that modify their proteinogenic counterparts’ intrinsic propensities to adopt beta-sheet secondary structures. We are also interested in controlling the conformation and interactions of glycine residues, which play a unique role in protein structure and yet remain difficult to constrain. After synthesizing a suite of novel amino-acid analogs, we will evaluate their conformational propensities by studying the folding thermodynamics of model peptides/proteins that incorporate these residues. We will also evaluate the ability of peptides incorporating modified amino acids to engage with important biological targets, especially misfolded proteins and transmembrane helices. Our results will inform the design of peptides and proteins with improved conformational control, thereby supporting a variety of applications across medicine and biotechnology.

NSF Awards · FY 2025 · 2025-09

This project investigates a previously unknown mechanism by which proteins come together on the surfaces of cells to transmit information from the outside world, which could ultimately be harnessed to communicate with cells and tissues. Like fences and walls, cells use lipid membrane to protect themselves and divide their contents into functional compartments. While this compartmentalization is useful to cells, it also requires cells to develop ways of communicating across membrane boundaries. This project investigates a new means of communication through membranes in which a liquid-like droplet of protein on one side of the membrane locally rearranges lipids to send a signal to a droplet of protein on the opposite side of the membrane. By explaining the mechanism behind this newly discovered form of communication, this research provides a better understanding of how cells communicate with the outside world and with one another. Ultimately, this understanding has the potential to inspire new ways of controlling cellular behavior to meet biomedical needs. In parallel, the investigators are conducting a multi-level outreach program involving local schools, teachers, undergraduates, and graduate students. To inspire the next generation of biophysicists, this program partners with participants to create new hands-on experiments for K-12 students. Liquid-like protein condensates organize diverse cellular functions. Though originally discovered in the cytosol and nucleoplasm, many condensates function on membrane surfaces. This work is inspired by the recent discovery that condensates on one side of a suspended planar membrane colocalize spontaneously with those on the other side, resulting in transbilayer coupling. These findings suggest a new means of transbilayer communication. This project aims to identify the fundamental mechanisms responsible for transbilayer coupling of protein condensates. The research involves quantitative biophysics experiments, guided by molecular-level simulations. Further, as a physiological example of condensate coupling, transbilayer interactions between glycosphingolipids and actin are being investigated. In particular, the role of coupling between condensates consisting of extracellular Galectin proteins and intracellular condensates consisting of actin-interacting proteins is being evaluated. These studies are providing novel biophysical insights and experimentally validated simulation tools for understanding and predicting the impact of protein condensates on membrane surfaces throughout the cell. Specifically, this work has the potential for a transformative impact on biophysical understanding of cell biology by elucidating the molecular-scale mechanisms behind a previously unknown mechanism for transbilayer communication and evaluating the role of this mechanism in the cellular process of glycosphingolipid traffic. 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 goals of this proposal are to: (1) acquire the experimental skills and career training necessary to expand my research program into cellular aging/senescence and molecular biology, (2) investigate how the accumulation of senescent cells (SnCs) and their senescence-associated secretory phenotypes (SASPs) impact osteocyte mechanobiology in a 3D bone-mimicking microenvironment, and (3) generate foundational data to support future NIH R01 applications. Our previous studies have shown that SnC accumulation with age at various sites has anti-resorptive and anabolic effects, ultimately leading to bone loss. However, the mechanisms by which local and systemic SnCs disrupt osteocyte mechanosensation during aging remain unclear. This proposal addresses three crucial knowledge gaps: (Aim 1) How do local vs. systemic SnCs and SASP influence cytoskeletal stiffness and membrane viscoelasticity in healthy osteocytes? (Aim 2) How do age-related changes in cytoskeletal stiffness impact osteocyte responses to mechanical stimuli? (Aim 3) What are the reciprocal effects of senescence between osteocytes and bone marrow mesenchymal stem cells (BMSCs)? My preliminary data show that senescent osteocytes exhibit time-dependent increases in cytoskeletal stiffness, with local interactions between senescent and healthy osteocytes having a greater impact than systemic SASP exposure. Based on these data, my central hypothesis is that senescent osteocytes impair healthy osteocyte mechanosensation through cytoskeletal stiffening, with local and systemic interactions differentially impacting healthy osteocytes. To test this, I will develop novel 2D and 3D co-culture models using our visible light-induced 3D bioprinting technique and biocompatible hydrogel-based bio-inks to mimic the bone microenvironment. These models will allow investigation into how SnCs within the bone microenvironment, both locally and systemically, affect osteocyte mechanobiology and mechanosensation. Micromechanical properties of osteocytes and their surrounding matrix will be measured using optical fiber-based interferometry nanoindentation coupled with live- cell immunofluorescence staining. These biophysical measurements will be correlated with gene and protein expression analyses to mechanistically determine the impact of SnCs in the bone microenvironment on osteocyte mechanobiology. The successful completion of these aims will provide critical mechanistic insights into how bone mechanobiology is altered by aging and cellular senescence, supporting the development of therapeutic strategies to rejuvenate or eliminate SnCs to restore osteocyte function. The proposed training plan integrates advanced techniques in cellular senescence and biomolecular assays, with opportunities to extend into transgenic mouse models, which will support my future research projects and R01 applications.

NSF Awards · FY 2025 · 2025-09

There is a growing need to educate more students in quantum science—an exciting and rapidly advancing field that underpins many modern technologies, including semiconductor chips and medical imaging tools like MRI. Currently, quantum science is primarily taught within physics and chemistry departments, and existing courses and training approaches often fall short in supporting the interdisciplinary collaboration needed to solve the field’s most pressing questions. This National Science Foundation Research Traineeship (NRT) award at University of Texas at Austin brings together faculty from the Cockrell School of Engineering and the College of Natural Science to design new courses and hands-on learning experiences to prepare graduate students from diverse academic backgrounds for the quantum workforce of the future. The University of Texas at Austin—recognized for its strong science and technology ecosystem—offers an ideal environment for this initiative. Austin’s expanding high-tech industry and the recently established Texas Quantum Institute will provide students with meaningful connections to real-world applications and opportunities in quantum research and the broader STEM workforce. NRT trainees will gain valuable skills through research, teamwork, mentorship, career development, and community engagement. Approximately 100 graduate students will participate in this program and 16 funded graduate trainees from several departments, including electrical engineering, computer science, mechanical engineering, and physics, will be served. This project will prepare participating students for careers in the growing quantum technology sector. Trainees will also participate in public outreach activities at nearby high schools and community colleges, reaching an additional 300-500 individuals. Led by faculty from electrical engineering, computer science, mechanical engineering, and physics, this NRT research program is built around four interlinked research themes: foundational studies of qubits; quantum transduction through photonic and acoustic integration; quantum algorithm development; and applied research in quantum networking, communication, sensing, and simulation. These projects hold great promise towards scalable technologies in quantum networks, quantum sensors, and quantum algorithms. The project is laterally integrated across quantum platforms and vertically integrated across colleges, departments, and researchers. Trainees will engage in collaborative research projects that bring together different fields and encourage innovative thinking across disciplines while being mentored by a multidisciplinary faculty committee. The project will create five new quantum science and technology (QST) courses that include hands-on learning to provide foundational training for students from a wide range of academic backgrounds. The project will also build a well-rounded training experience that combines QST courses, interdisciplinary research, skill-building workshops, mentoring, internships, and public engagement activities. Trainees will receive grounding in perspectives from industry and entrepreneurship to help prepare them for broad career outcomes. Additional graduate and undergraduate students will be encouraged to join QST classes, attend seminars, and participate in research efforts. One outcome of the project is institutionalization of a graduate certificate in QST to help prepare a skilled workforce in quantum science beyond the life of the grant. The NSF Research Traineeship (NRT) Program is designed to encourage the development and implementation of bold, new, and potentially transformative models for STEM graduate education training. The program is dedicated to effective training of STEM graduate students in high priority interdisciplinary or convergent research areas through comprehensive traineeship models that are innovative, evidence-based, and aligned with changing workforce and research needs. 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

PART 1: NON-TECHNICAL SUMMARY The operation of batteries critically relies on the movement of charged ions through an electrolyte medium. If solids could be used as electrolyte rather than the flammable liquids employed today, the resulting devices would be safer. Furthermore, among the possible ions, magnesium and calcium carry twice the charge of lithium, the current technological incumbent, so batteries based on these metal ions could also store more energy while minimizing the use of critical materials. However, these "multivalent" ions have difficulty moving through solids, which has prevented their use in practical batteries. With support from the Solid State and Materials Chemistry program in the Division of Materials Research at NSF, researchers at University of Texas at Austin and University of Illinois Chicago combine advanced computer simulations with laboratory experiments in a feedback loop to design materials that overcome this fundamental barrier. The simulations predict atomic structures and chemical compositions that should allow fast calcium or magnesium movement. The team then synthesizes the best candidates, measures their properties as electrolytes, and uses the results to refine the predictive models. Success in this work could lead to a new class of solid electrolyte batteries that combine high energy storage with safe operation. To enhance the impact of the research, the project aims to introduce undergraduates to cutting-edge scientific topics early in their career, conducts student exchange between institutions to enhance workforce development, and promotes wide exchanges of ideas through international symposia. These efforts advance fundamental knowledge in materials chemistry, train the next generation of scientists and engineers, and contribute to U.S. goals for innovation in energy and technologies with secure supply chains. PART 2: TECHNICAL SUMMARY Achieving fast conduction of multivalent ions through solids remains a fundamental challenge in solid state chemistry. With support from the Solid State and Materials Chemistry program in the Division of Materials Research at NSF, this project integrates computational and synthetic exploration to identify and develop solid electrolytes with high conductivity for magnesium and calcium. The work focuses on broad families of mixed anion compounds of magnesium and calcium crystallizing in an anti-perovskite structure. The anionic sublattice is formed by different combinations of pnictides or rotatable cluster anions in order to assess their impact on ion dynamics. The technical approach involves first-principles calculations to screen candidate compounds that are chemically stable, exhibit rotatable anions, and possess low ion-migration barriers. In parallel, the team pursues the synthesis of predicted phases to validate and enhance computations. After successful synthesis of promising candidates, the atomic structure and ion transport are measured using X-ray diffraction, impedance spectroscopy, and nuclear magnetic resonance techniques. Lastly, to further enhance the movement of ions, predictions are used to guide the experimental introduction of aliovalent dopants on the anion sublattice to generate cation vacancies. This integrated theory-experiment approach seeks to establish design principles for fast multivalent-ion conduction in solid electrolytes that push new boundaries in the movement of ions through solids while informing the development of batteries with unique performance. 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 lack of cell culture strategies that faithfully replicate both form and function of the extracellular matrix (ECM) hinders our ability to effectively monitor, diagnose, and treat disease. This arises from the contemporary reliance on in vitro cell culture methods that fail to replicate complex biological structures, while in vivo cell cultures use animal models that have disparate physiology from humans. As a result, there is a gap in fundamental knowledge surrounding how cells respond to various stimuli (or cues), limiting our ability to understand and fight illness. Filling this gap necessitates new precision processes to create 3D structures that emulate the natural ECM for in vitro cell culture. Herein, a feedback loop between digital light processing (DLP) 3D printing and cell studies will provide new process-structure-function relationships between the technology to create biomimetic scaffolds and concomitant cell-matrix interactions. Open fundamental questions to be addressed herein include: 1) To what extent does using visible and near infrared light in DLP 3D printing improve cell viability and metabolic activity over using UV light? 2) What are the optimal microscopic mesh sizes and macroscopic pore geometries to facilitate uniform cell morphology and proliferation? 3) How does the layered topography of DLP 3D printed structures influence cell behavior (e.g., adhesion, mobility, and differentiation)? 4) How do cells respond to sharp vs. smooth interfaces where a cue is transitioning (e.g., stiffness gradients)? 5) How do cellular responses vary for individual vs. combined mechanical and biochemical cues? Answers to these questions will be accomplished using human mesenchymal stem cells (hMSCs) as a model system given their multipotent versatility and microenvironment sensitivity that is representative of many cell types. DLP 3D printing was selected as the fabrication platform owing to its unparalleled combination of speed, resolution, and low cost. However, this technique to-date has been predominantly restricted to harmful UV light exposure, toxic acrylic resins, and the production of rigid homogeneous parts that differ from the vital heterogeneity and softness present in many ECMs. The Page lab is uniquely positioned to address these issues given their existing expertise and infrastructure that will enable integration of heterogeneity into biomimetic structures by using benign visible to near infrared (multi-)color and intensity (grayscale) light projection. This will allow for precise 3D spatial control over network structure, mechanical properties, and protein tagging. hMSCs will be directly encapsulated in synthetic ECM mimetics that emulate tissues ranging in stiffness from lungs (“supersoft”) to ligaments (“hard”). Additionally, localization of proteins (e.g., growth factors) will be used to direct adhesion, movement, and growth of hMSCs. Cell viability and behavior within the 3D scaffolds will be systematically characterized to elicit structure-function relationships that address the above fundamental questions and that will inform further bioprinting optimization and cell culture. If successful, this work will provide a platform to improve our capability to monitor, diagnose, and treat diseases in a non-invasive in vitro manner.

NSF Awards · FY 2025 · 2025-09

The El Niño Southern Oscillation (ENSO) is a dominant source of year-to-year variability in temperature and rainfall affecting many regions of the world. The response of ENSO to external forcing varies in different climate models. Therefore, it is critical to test the fidelity of those models with records of past ENSO behavior from archives such as corals and cave deposits. However, there are few records of ENSO variability from times such as the last glacial period and deglaciation when there were large changes in external climate forcing. This project will reconstruct ENSO and Tropical Pacific Decadal Variability (TPDV) with corals and cave deposits from Vanuatu, Solomon Islands, and the Philippines to reconstruct changes in ENSO and TPDV. The results will be compared to climate model simulations of glacial and deglacial time periods to analyze the physical mechanisms of interannual and decadal variability in the tropical Pacific. This project will improve understanding of ENSO and TPDV and has the potential to improve predictability of these phenenomena. The project includes support for postdoc and undergraduate participation in the research, and collaboration with University of the South Pacific (USP) and Vanuatu Meteorology and Geohazards Department (VMGD). The goal of the project is to measure geochemical changes in fossil corals from Vanuatu and speleothems from Vanuatu, Solomon Islands, and Philippines to reconstruct changes in ENSO and TPDV. The results will be compared to climate model output from the Community Earth System Model (CESM) 1.2 and analyze the physical mechanisms of TPDV changes and test the hypothesis that El Niño Southern Oscillation (ENSO) was reduced and TPDV was stronger during glacial times compared to preindustrial times. The project includes support for postdoc and undergraduate participation in the research, and collaboration with University of the South Pacific (USP) and Vanuatu Meteorology and Geohazards Department (VMGD). 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 Effective emotion regulation (ER) is essential for successful development, as difficulties in ER are associated with significant emotional, behavioral, and mental problems. Early in life, parental responses to their child’s negative emotions play a significant role in the development of adaptive ER. However, little work has explored how in-the-moment parental responses during in-vivo emotional events influence children’s ER. Furthermore, while the functioning of biological systems is crucial in shaping the development of effective emotional processes, there is a significant gap in understanding how in-the-moment parental responses influence children’s neural and physiological regulation. Aligning with NICHD’s Strategic Objective 4 which focuses on “improving child and adolescent health and the transition to adulthood”, this K99/R00 proposal aims to explore how in-the-moment parental responses influence key neural and physiological markers of ER, especially in response to negative emotions (Aims 1, 3, and 4). Additionally, the quality of the parent-child relationship is hypothesized to play a crucial role in moderating the effects of the relationship between parental responses and children’s neural and physiological regulation. Therefore, the proposed study will also examine how parent-child relationship quality influences the association between parental responses and the child’s neural and physiological ER (Aims 2, 5). This research will employ EEG and ECG measures (i.e., alpha asymmetry, respiratory sinus arrhythmia) to assess children’s neural and physiological ER processes. Observational assessments of parental responses will also be conducted to capture dynamic parent-child interactions. The findings from this project could significantly improve our understanding of how in-the-moment parenting affects child ER by integrating neural and physiological data, offering insights that may inform future intervention strategies. The K99/R00 phase of the award will provide essential training in four key areas: 1) EEG and ECG methodologies; 2) behavioral coding of parental responses to children’s negative emotions; 3) longitudinal study design, data collection, and analysis; 4) theoretical and methodological approaches to studying the impact of parent-child relationship quality on child ER. A multidisciplinary team of mentors and consultants has been assembled to support the candidate in achieving these training objectives. Ultimately, this research will offer new insights into the dynamic relationship between parenting and children’s neural and physiological regulation during early to middle childhood, a period when ER transitions from being primarily externally regulated by parents to becoming more internally regulated by the child. The proposed research and training plan will prepare the candidate to establish an independent and distinctive research program that employs multi-modal methods to advance the field of developmental psychology, with the long-term goal of informing evidence-based strategies that promote healthy emotional development in children.

NIH Research Projects · FY 2026 · 2025-09

Abstract The global population is aging rapidly, with an estimated 2.1 billion people aged 60 or over expected by 2050. Aging baby boomers are contributing to an increase in heavy alcohol consumption and alcohol use disorders (AUDs). Indeed, AUD rates have increased by 82.5% in those aged 65 and over, which exacerbates risk for cognitive decline, accelerated aging, dementia, and early death. Excessive alcohol intake in aged individuals likely dysregulates immune dynamics in brain. The neuroimmune system critically regulates cognitive and behavioral changes with aging – pathological inflammatory priming and/or reactivity occurs with neurodegenerative disorders and elicits cognitive decline. The main resident immune cell of the CNS, microglia, help maintain a healthy milieu by surveying for damage or infection; by responding to damage-related cues; and by phagocytosing dying cells and excess synapses. Microglia play key roles in alcohol-induced neuroinflammation and in aging-related neurotoxicity; however, little is known about how alcohol and aging intersect at the level of the neuroimmune system. Thus, here we propose that neuroinflammatory responses are dysregulated in the aged brain resulting in increased vulnerability to the neuropathological effects of heavy, alcohol exposure. We provide strong preliminary data demonstrating that heavy binge-like exposure to alcohol leads to substantial and progressive impairments in cognition and an altered neuroimmune environment. Our overall objective is to determine whether dysregulated neuroimmune, and particularly microglia, function is critical to this heightened age-associated damage following heavy, alcohol exposure. The central hypothesis of this proposal is that heavy alcohol exposure in aging produces delayed hippocampal neurodegeneration and cognitive deficits through impaired microglia phagocytic and inflammatory functions. The proposal addresses the following specific aims: First, characterize the interaction of aging and heavy, binge-like alcohol exposure on corticolimbic structure and function. Second, determine how aging and alcohol interact to induce changes in microglia phenotype and function following heavy, alcohol exposure. Third, interrogate the role of microglia dysfunction following alcohol in aged rats on corticolimbic structure and function. The third mechanism-focused aim will examine the precise role of microglia in contributing to damage in the aged brain in response to alcohol. The proposal is innovative in combining expertise in alcohol use disorders, aging, and neuroimmunology. It uses state-of-the-art approaches including ex vivo microglia functional assays, confocal microscopy and 3D cellular reconstructions, microglia depletion, and single cell RNA-sequencing to identify novel pathways perturbed by alcohol exposure in the aging system. This contribution will be significant as alcohol use is a growing concern in aged populations but an understudied area. The proposed studies will provide a mechanistic foundation to elucidate novel targets for therapeutic intervention to reduce alcohol-induced brain and cognitive/behavioral impairments and explore alcohol's acceleration of brain aging.

NSF Awards · FY 2025 · 2025-09

One of the biggest unknowns in projecting future sea level is how fast the Antarctic Ice Sheet will melt in response to continued warming. An increase in high-latitude snowfall may offset some ice sheet melt due to warming of surrounding ocean and atmosphere, though it is not yet known how effective this compensating mechanism is, or under what timescales or conditions it might be important. To better understand these competing processes, researchers are investigating moisture-driven mechanisms of ice sheet growth during a past interval in Earth’s history where the climate was warm (the Miocene Climate Optimum, about 17 to 14.8 million years ago). During this time, Earth was warmer than today, yet geologic records hint at episodes where Antarctica was gaining ice. This project brings together an interdisciplinary team of experts across three institutions to investigate the potential for moisture-driven ice growth using a combination of advanced Earth system models and geologic data, while providing hands-on interdisciplinary geoscience training for graduate and undergraduate students. Researchers will use isotope-enabled climate and ice sheet models to test a suite of hypothesized mechanisms for precipitation-driven Antarctic ice growth during the Miocene Climate Optimum. Each model simulation tracks the oxygen isotopic concentration of ice, generating a modeled oxygen isotope signal that can be compared directly against deep-sea isotopic records. To evaluate model simulations, the team will generate a new high-resolution record of Antarctic Ice Sheet volume using paired benthic foraminiferal oxygen isotopes and Mg/Ca measurements from a deep-sea sediment core from 17-15 Ma, providing a key dataset for model validation alongside a synthesis of published geologic records spanning this time. Data-model comparisons will evaluate how well each modeled mechanism can explain the observed ice volume and oxygen isotope changes recorded in deep sea sediments. Specifically, investigators will explore the ice-growth potential of local polar mechanisms (such as ice-proximal ocean warmth and sea ice cover), as well as global hemispheric processes (such as CO2 and orbital forcing) that influence the heat and moisture transport to the ice sheet. Miocene data and model output will contribute to international community synthesis efforts, and project results will provide critical context for understanding long-term trajectories of global sea level. 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 Induced pluripotent stem cells (iPSCs) offer immense promise for autologous therapies by using the recipient’s own cells to engineer new functional tissue. Many of the targeted diseases for iPSC treatment research, such as cardiovascular diseases, are disproportionally found in aging individuals. While iPSCs have been generated from donors of all ages, even centenarians, the influence of donor age on iPSC functionality remains a critically understudied aspect. Moreover, the role of environmental age on differentiated iPSC functionality is not well understood. This research aims to comprehensively address this gap, particularly focusing on the effects of age- related changes in both the donor and environment of iPSC-derived endothelial progenitors (iPSC-EPs). My preliminary data indicates that iPSC-EPs from mature donors (above the age of 30) exhibit a diminished capacity for self-assembling into microvasculature. Building on this observation, I propose a two-fold investigation (Fig. 1). Firstly, I will characterize differences between iPSC-EPs sourced from neonatal, mature, and aged donors, exploring differentiation yield, methylation patterns, gene expression levels, and vascular cell biopotency. This analysis will provide a holistic understanding of how donor age persists through iPSC differentiation into vascular lineages. Secondly, I will investigate the influence of age-related changes in the microenvironment on iPSC-EP functionality by employing innovative 3D hydrogel environments with tunable stiffness and variable composition properties (Fig 1.). With age, there is a general increase in tissue stiffness, but also a change in extracellular protein composition. By decoupling the effects of stiffness from ECM composition, I expect to characterize the specific contributions of these factors and their role in determining microvascular plexus structure, gene expression, and protein expression profiles. Through the examination of iPSC lines sourced from neonatal, mature, and aged donors, matched by sex and somatic cell origin, this research aims to provide crucial insights into the potential limitations of using iPSCs from older individuals for tissue-engineered vascular applications. I hypothesize that age-related differences in gene expression will result in limited microvasculature formation in iPSC-EPs from aged donors, but exposure to a young microenvironment may offer a promising avenue for rejuvenation. This study holds significance for advancing the field of iPSC research and informing the development of effective strategies for personalized vascular therapies, especially as it relates to targeted aged populations.

NSF Awards · FY 2025 · 2025-09

This project aims to develop a new artificial intelligence system that works alongside mathematicians to tackle problems that have resisted solutions for nearly a century. Recent advances in large language models can generate creative insights and partial reasoning steps, but they often make mistakes and cannot guarantee correctness. In contrast, traditional tools for verifying mathematical proofs offer rigorous guarantees but are not well-suited for automatically navigating the vast search spaces involved in complex mathematical discovery. This research combines the strengths of both approaches: using AI to explore promising ideas and using formal logic to rigorously verify and refine them. As a high-impact test case, the team will focus on the Hadamard Conjecture, a longstanding open problem with applications in quantum error correction, communication systems, and coding theory. The project will also produce open-source tools, educational materials, and outreach programs to broaden participation in advanced mathematics and AI. The research introduces a unified framework with three key components: (1) a self-evolving reasoning pipeline that uses synthetic data to guide exploration of promising matrix constructions; (2) chain-of-thought and curriculum learning to help AI decompose complex mathematical tasks into simpler subproblems, integrate partial solutions, and generalize from simpler to more difficult problems; and (3) formal verification tools, such as Lean, integrated with preference alignment to ensure correctness and enable a self-improving system guided by symbolic proof signals. Together, these elements form a closed-loop system for scalable, trustworthy proof generation. Anticipated outcomes include new Hadamard matrix constructions, practical software for AI-assisted mathematics, and foundational advances in combining learning and logic for mathematical problem solving. 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

Alcohol use disorders is a complex polygenic disease. Cell-type specific data from medial prefrontal cortex (mPFC) from alcohol-dependent mice shows dysregulated gene co-expression networks and transcription factors. This proposal tests the hypothesis that genetic rescuing of dependence-dysregulated gene regulatory networks and co-expression modules will result in reversing escalated alcohol use. The proposal tests this hypothesis in three specific aims: Aim 1 (K99): To test the effect of genetic rescuing an astrocytic dependence-upregulated gene co-expression module on escalated alcohol drinking through performing parallel perturbations of the top connected hub genes of the module. This aim will assess the contribution of gene co-expression modules to alcohol drinking phenotype; Aim 2 (K99): To identify cell-type specific dependence-dysregulated chromatin accessibility and gene regulatory networks. This aim will allow for the (a) construction of cell type-specific gene regulatory networks through connecting cell type-specific chromatin accessibility to gene expression data in alcohol-dependent and control samples, allowing for the identification of alcohol-dysregulated gene regulatory networks, Aim3 (R00): To reverse alcohol escalation through rescuing alcohol-dysregulated gene regulatory networks. This aim performs global non cell-type specific perturbation of a set of transcription factors in alcohol-dependent mice followed by characterization of the resulting changes in alcohol-drinking phenotypes. Dr. Nihal Salem’s goal is to be an independent researcher in the field of alcohol research and to develop a research program that spans genomics, bioinformatics, and functional studies linking transcriptomics to alcohol drinking phenotypes. This proposal outlines a research and training plan to provide Dr. Salem with two years of mentored postdoctoral training and three years of support to start her independent research direction.

NIH Research Projects · FY 2025 · 2025-08

Abstract The prevalence of both obesity and cognitive disorders has increased over the past decades, a period during which the number of environmental endocrine-disrupting chemicals (EDCs) has also grown. EDCs are associated with increased metabolic problems and obesity. EDCs also have links to cognitive disorders such as attention-deficit/hyperactivity disorder (ADHD). The fact that obesity and behavioral problems often co-exist in individuals suggests the heretofore unexplored possibility that EDCs play a role in their co-morbidity. This project aims to explore how EDCs disrupt cognitive and food reward processes in the brain, with a focus on dopamine (DA) pathways, which are critical for regulating both cognitive function and motivated eating behavior in the brain reward system. Using a curated EDC mixture, NeuroMix (NMX), which comprises environmentally relevant EDCs below the no observed adverse effect level with known obesogenic and neurodevelopmental impacts, this research will investigate how exposure to EDCs lead to neuromolecular reprogramming of the brain’s reward system and impacts related behaviors. Specifically, in an established rat model, I will examine how NMX impacts food reward, motivation, and cognitive flexibility, and whether these effects are sex-specific. Additionally, the study will investigate the intergenerational effects of EDC exposure on motivated eating and cognitive behavior, as previous findings suggest that some EDCs cause epigenetic reprogramming of neuromolecular processes, leading to new or worsened behavioral and physiological disruptions to emerge in later generations. To achieve these objectives, I will leverage advanced molecular techniques, including single nucleus RNA sequencing (snRNA-seq) and bisulfite sequencing, to analyze DA-specific gene expression and epigenetic modifications throughout the brain’s reward system. By linking molecular disruptions with behavioral outcomes, this study seeks to define the mechanisms by which EDCs drive the convergence of obesity and cognitive disorders, providing a comprehensive model of behavioral obesogenics. The findings from this project will offer novel insights into the role of environmental chemicals in the comorbid development of obesity and neurodevelopmental disorders like ADHD, with implications for public health strategies aimed at mitigating the multiplicative risks associated with EDC exposure. These goals meet the NIEHS’ strategic goal to “investigate the effects of the environment on genome structure and function”, including epigenetic regulation of biological processes, while including sex as a biological variable.

NIH Research Projects · FY 2025 · 2025-08

PROJECT SUMMARY Stroke is the second leading cause of death worldwide, with acute ischemic strokes representing 87% of all stroke cases. Given the number of individuals experiencing acute ischemic strokes, there is a pressing need to improve therapies for this disease. A recent treatment for large vessel occlusion, which accounts for up to 46% of all acute ischemic strokes and 98.8% of all poststroke mortality, is mechanical thrombectomy. The main forms of thrombectomy include using a stent retriever to trap and extract the occlusive clot or an aspiration catheter to remove the clot via suction. While this is an effective treatment for large vessel occlusion, studies show that only 50% of treated patients achieve good functional outcomes. Additionally, up to 40% of patients experience distal embolization, where the clot breaks into fragments during removal; these fragments travel distally and cause further damage to the cerebral vasculature. Individual studies have shown that adjusting treatment parameters such as i) stent retriever length, size, and withdrawal speed, or ii) aspiration catheter size, distance from the clot, and suction pressure improve patient outcomes. These studies are limited though, and no study has thoroughly investigated the impact of all these treatment parameters on procedural outcomes such as i) degree of recanalization, ii) number of passes needed to recanalize, and iii) occurrence of distal embolization for clots of varied geometry, composition, and location. It has been noted that computational models could overcome this gap; they can be used to systematically test all treatment parameters for clots of varied geometry, composition, and location. The advantage of this approach is in the reduction of time and resources needed to study thrombectomy treatments, as experiments can be difficult to perform, costly, and time-consuming. Despite this, few computational models exist that capture the complex physics of thrombectomy, let alone investigate the sensitivity of procedural outcomes to treatment parameters. To fill this gap, the proposed project aims to develop and validate an open-source computational model of thrombectomy (Aim 1) and optimize thrombectomy for clots of varied geometry, composition, and location using computational models (Aim 2). The aims will use state-of- the-art techniques in experimental and computational biomechanics. Our current lack of knowledge is potentially withholding better treatment strategies for large vessel occlusion in acute ischemic stroke. Thus, my ultimate goal is to identify optimal thrombectomy treatment options and inspire the development of new thrombectomy devices and strategies. Along with the research strategy, the fellowship training plan is organized to offer the applicant professional development toward an independent research career in a top-tier institutional environment at the University of Texas at Austin under the sponsorship of a leading expert in blood clot biomechanics. Upon completion of the training program, the applicant will be ideally prepared for further postdoctoral training and eventually a faculty position in cardiovascular disease research.

NIH Research Projects · FY 2025 · 2025-08

Project Summary Cystic fibrosis (CF) patients with nonsense mutations of the disease-causing CF transmembrane conductance regulator gene (CFTR) cannot benefit from existing small molecule therapies and need gene therapy of the CFTR mutation to restore any function and ultimately, for a cure. Since 95% of CF-associated comorbidities affect the respiratory tract, pulmonary administration of gene therapies would be advantageous, as it would increase the therapeutic index by significantly increasing dosing 10- to 20-fold without incurring the off-tissue toxicity seen with systemic administration. For inhalation gene therapy, the gene delivery systems must possess the physicochemical properties to overcome the transport barriers, such as mucus and reach the target cells in the airways at therapeutic concentrations. However, current approaches in the clinic would need repeated dosing since they do not target the basal cells, or the airway stem cells, for one-time, permanent correction. Also, gene therapy approaches currently in clinical trials do not fix the mutation but provide a corrected CFTR copy, whereby the therapeutic benefit is temporary. To address these challenges, it would be desirable to develop nucleic acid delivery systems that can reach the airway basal cells and fix the CFTR mutation towards permanent correction of lung CF disease. Here, we will develop peptide surface-functionalized lipid nanoparticles (pepLNPs) for pulmonary delivery that can reach the basal cells in vivo and deliver base editors in relevant cell culture and animal models to precisely edit and correct specific G542X and G553X nonsense mutations present in CF. Previously, we have identified peptide ligands that can penetrate through the mucus barrier present in CF and in preliminary evidence, demonstrate that these pepLNPs, can reach and achieve editing in the basal cells. Leveraging our platform technology, we propose to make pepLNP formulations that can stably encapsulate, protect, and deliver mRNA encoding base editing components, to reach, and edit basal cells in vitro and in vivo. Importantly, we will elucidate how these pepLNPs penetrate through the mucus barrier and are taken up by basal cells. Finally, we will validate that upon delivery to the basal cells, pepLNPs will deliver adenine base editors to correct the genotype and restore functional phenotype of cells that had possessed the previously undruggable nonsense CFTR mutations. This proposed work can have a transformative impact, as it aims to achieve one- time, “permanent” correction for durable gene therapy of CF by targeting the basal cells and specifically fixing the inherent CFTR mutation. While this strategy focuses on CF, in the long-term, this strategy can transform treatment of many genetic diseases needing permanent correction.

NSF Awards · FY 2025 · 2025-08

Representation theory can be broadly understood as the mathematical study of symmetry. The symmetries that arise in quantum mechanics are called "unitary representations." One of the major unsolved problems in representation theory is to classify unitary representations. This problem has driven a considerable portion of all research in representation theory over the past eighty years; its solution would have far-reaching ramifications in several neighboring fields, including number theory, harmonic analysis, signal processing, and theoretical physics. The PI proposes to develop a new geometric approach to this problem. This approach will lead to substantial new insights into the structure of unitary representations and, hopefully, a solution to the problem of computing the unitary dual. The project also provides research training opportunities for graduate students. There are two main existing approaches to the study of unitary representations: the orbit method philosophy of Kirillov and Kostant, and the Hodge theory approach of Schmid and Vilonen. The orbit method seeks to parameterize the unitary dual of a Lie group G in terms of (roughly speaking) orbits for G on the dual space of its Lie algebra. The Hodge theory approach seeks to understand unitary representations by localizing over the flag variety and applying tools from Hodge theory. These approaches work along two different axes. Whereas the orbit method provides mainly hints as to where one should look for unitary representations, Hodge theory provides a powerful apparatus for proving that representations are unitary. Neither approach seems sufficient, on its own, to solve the problem of computing the unitary dual. In this project the PI proposes to develop a unified geometric approach to unitary representation theory by combining the orbit method with techniques from Hodge theory. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NSF Awards · FY 2025 · 2025-08

A challenge of developing artificial intelligence (AI) that can work with and serve human needs is developing systems that can smoothly communicate with humans. An aspect of human communication that is effortless for humans, but that remains challenging for AI systems, is communication about space – that is, where people and things are and where they are going. Simple words like “this” and “there” help speakers point to objects, give directions, and share information. These words are important in every human language, and they are critical to get right for robotic systems that will inhabit human spaces and interact with human users. But these words are used in different ways across languages, and scientists do not yet fully understand why. This project quantitatively and experimentally measures how people talk about space using computer models and experiments. The researchers work with speakers of a variety of languages, analyze how people choose words to describe space, and build computer models that explain how this communication works. Other benefits to society include providing innovative educational opportunities that support workforce development for AI and other language technology industries. This research investigates how human languages express spatial relationships using deictic words (e.g., “this,” “that,” “here,” “there”). The project integrates cross-linguistic experimental data with information-theoretic computational models – specifically using the Information Bottleneck approach that was developed to explain artificial neural network behavior – to explore how people balance accuracy and simplicity when using spatial language. Using methods such as behavioral experiments, geospatial analysis, and machine learning, the project explores the cognitive and environmental pressures that shape how speakers refer to locations and objects. The models developed in this project also provide insights into how AI systems can more naturally interpret and produce spatial language, supporting improvements in areas such as robotics and AI more generally. This award is made possible through the NSF-UKRI lead agency opportunity. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NSF Awards · FY 2025 · 2025-08

This project develops synthetic cells that mimic the essential functions of biological platelets – shape transformation, biochemical secretion, and mechanical adhesion – to promote blood clotting in a programmable and externally controllable manner. Platelets are among the simplest cells in the human body, yet they perform a complex and highly coordinated sequence of actions in response to vascular injury. The proposed synthetic cells emulate these sophisticated behaviors using light-activated control systems and biochemical recognition, enabling them to work in concert with natural platelets to initiate and reinforce clot formation. This work addresses a critical biomedical need by offering a potential solution to the persistent shortage of donor platelets used in trauma care, surgery, and cancer treatment. More broadly, the project demonstrates how synthetic cells can be engineered to interact functionally with living systems. The investigators are also implementing a robust educational outreach program that engages undergraduates, graduate students, K–12 teachers and students in hands-on research and classroom-based learning. By integrating cutting-edge research with multi-level education and outreach, this project trains the next generation of scientists and engineers. Synthetic cell research has made tremendous progress over several decades but now sits at a crossroads, where integrating multiple functionalities into a single synthetic cell remains elusive. This project aims to construct platelet-like synthetic cells with three coordinated, externally controllable capabilities. First, the project is developing light-responsive protein condensates that drive actin polymerization and cytoskeletal remodeling, enabling synthetic cells to undergo shape transformations that mimic platelet activation. Second, the team is engineering connexin nanopores that can be gated by near-infrared light to release dense granule components into the extracellular environment, thereby activating nearby natural platelets. Third, the project chemically reconstructs integrin complexes across synthetic cell membranes, forming transmembrane mechanical linkages that connect extracellular fibrin binding to intracellular actin networks. These three modules are developed independently and then integrated into a single synthetic cell platform capable of responding to external stimuli with precise spatiotemporal control. The resulting synthetic cells are evaluated in vitro for their ability to promote clot formation and activate natural platelets under both static and flow conditions. This project significantly advances the state of the art in synthetic cell engineering by demonstrating the coordinated function of multiple synthetic subsystems within a membrane-encapsulated platform. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NSF Awards · FY 2025 · 2025-08

Sustainability of water supplies in the Andes Region in South America is put at risk by a warming climate, which is causing glacier retreat and contributing to the decline of lakes and reservoirs. This research project will analyze sediment cores from Lake Titicaca—the highest navigable freshwater lake in the world—and use these data to help uncover how natural Earth system processes have influenced water supply, glacier coverage, and ecosystems in the high Andes over the past 370,000 years. The findings will help explain when and why major droughts occurred in the past—and what these events can reveal about future water-related risks. Findings will be shared through a bilingual website, public presentations and outreach. All data and models will be freely available to researchers, policy makers, and local partners. By linking ancient climate events with present-day challenges, this work will help regional planners and communities understand and address future risks to water resources. This research project will develop a new record of precipitation, isotopes, temperature, and lake level spanning the past ~370,000 years using legacy drill cores from Lake Titicaca. The project will use these data to explore how the surrounding environment has changed, with a focus on understanding long-term water resource availability in the Andes. The analysis of geochemical and isotopic signals preserved in the sediments will be used to reconstruct how the regional environment responded to environmental shifts over glacial–interglacial timescales. To deepen understanding of these changes, the sediment-based environmental reconstructions will be paired with computer model simulations and AI-assisted methods for refining large-scale data to the local level. New time-slice experiments with isotope-enabled climate models spanning the last glacial cycle will help to better understand the drivers of environmental changes, including the relative roles of local and remote forcings on the South American Monsoon System, and will be a resource for future research by the paleoclimate community. This award is co-funded by the Division of Earth Sciences (EAR) and the Division of Atmospheric and Geospace Sciences (AGS). This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NSF Awards · FY 2025 · 2025-08

The mathematical description of interacting particles is a fundamental and challenging problem with broad implications across physics and engineering. While microscopic models involve large systems of ordinary differential equations, such formulations become impractical due to the prohibitively large size of the system. At larger scales, effective models take the form of kinetic equations –such as the Boltzmann and Landau equations- and at the macroscopic level, continuum equations like the Euler and Navier-Stokes equations. Importantly, these equations are connected: in certain asymptotic settings fluid equations can be rigorously derived from kinetic equations. Due to the complexity of the kinetic Boltzmann and Landau equations, recent research has been devoted to simplified kinetic models. These simplifications, while advantageous for the understanding of collision from a mathematical perspective, have limited direct applicability. With a solid mathematical foundation for these simplified models now in place, this project advances the field by studying more complex kinetic models that incorporate different physical phenomena. The objective of this research project is to gain a comprehensive mathematical understanding of several fundamental kinetic models arising in physics. The first project centers on the quantum Landau equation, with particular focus on the global well-posedness, singularity formation, and regularity of its solutions. Progress on these questions is expected to open new research directions within the field. The second project addresses the existence of regular solutions to the inhomogeneous Landau equation. This work involves novel approximation methods that could provide new insights into this well-known and challenging problem in non-linear kinetic theory. The mathematical methods and techniques developed through these studies are expected to serve as a foundation for tackling more complex models in the physics literature and to help generate specifically designed problems suitable for training junior researchers, including graduate students and postdoctoral fellows. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NSF Awards · FY 2025 · 2025-08

This project develops new statistical tools to address a common and important challenge in scientific research: drawing reliable conclusions from data in which observations on variables of interest are imprecise and contaminated by measurement errors. In many real-world studies, from nutrition and health research to astronomy, neuroimaging, and social science, measurements are often noisy, making it difficult to identify meaningful patterns or relationships. Existing statistical methods typically handle such problems under overly simplistic conditions, limiting their usefulness in complex, real-world, multivariate settings. By developing more flexible, principled methods that address realistic measurement error scenarios, this project aims to promote the national interest by supporting more accurate, data-driven decision-making in health, policy, and other applied fields. The project also contributes to workforce development in statistics and data science through graduate training, ensuring that students gain experience with modern data-driven research approaches. Technically, the project develops novel Bayesian hierarchical frameworks for multivariate density deconvolution and related regression-with-errors-in-variables problems. It introduces covariate-informed density deconvolution methods that flexibly allow both the variables of interest and their measurement errors to vary with associated predictors. These methods incorporate automatic covariate selection and permit different sets of predictors for different coordinates of multivariate outcomes, enhancing both flexibility and interpretability. In addition, the project addresses the largely unexplored area of median density deconvolution, developing tools for modeling measurement errors centered around a median rather than a mean. Both topics are important yet overlooked scenarios in current research. While the proposed methods are demonstrated in nutrition epidemiology contexts, they are broadly generalizable to a wide range of scientific fields where measurement error poses a challenge. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NSF Awards · FY 2025 · 2025-08

Understanding the use of grammatical structures in innovative modes of language expression supports a scientific explanation of how language is used to express the range of human experience. This doctoral dissertation project describes the grammar of a language and analyzes how that grammar changes in innovative modes of language expression. This project yields new knowledge about the nature of the grammar and mechanisms for verbal expression, which in turn broadens the linguistic basis for artificial intelligence and other language technologies. The project also benefits society by supporting workforce development through training in computational and other language science research methods, and by creating tools for presenting and disseminating research products in educational contexts. Languages show significant variety in their grammars, including how grammars are used in innovative modes of language expression. Understanding the range of human expression through language is critical for understanding the nature and range of human capacity itself. This doctoral dissertation project documents and analyzes the grammar and sound structure of a language by recording and analyzing speech in a variety of genres and by collaborating with community members to understand its grammatical patterns. An emphasis is placed on a system of metrics in a model of language expression that has a complexity and type normally associated with written language. Both the grammatical description and the study of diverse modes of verbal expression are used to produce pedagogical materials and archives, intended to provide the scientific community with a model for leveraging linguistic research for concrete translational benefits. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NIH Research Projects · FY 2025 · 2025-08

PROJECT SUMMARY (See instructions): Family caregivers of people with dementia have to decide between tube feeding and hand feeding when persistent eating problems arise, This decision can be difficult for Chinese-American dementia caregivers, due to the interplay of culture, potential absence of a patient's advance directive, poor understanding of dementia, and lack of knowledge on the risks and benefits of tube feeding. There is a high prevalence of tube feeding among Chinese older adults with advanced dementia; however, tube feeding does not have health benefits for older adults with advanced dementia, and may in fact be related to increased risk and discomfort. Shared decision-making is a process by which patients, family members, and healthcare providers work together to create care plans that balance clinical evidence and patient preferences and values with risks and expected outcomes. Current clinical discussions on feeding tubes rarely meet this standard. Limited research has been conducted to improve decision quality regarding feeding options among Chinese-American dementia caregivers. The goal of this study is to pilot test a culturally adapted decision aid intervention to support Chinese American dementia caregivers in decision making about feeding options. In the R00 phase, the candidate aims to refine and evaluate the efficacy of the decision aid in a pilot randomized controlled trial among 60 Chinese American dementia caregivers. By the end of the R00 award, Dr. Pei will complete the transition from observational and explanatory research to behavioral intervention work and submit an R01 proposal.

NSF Awards · FY 2025 · 2025-08

An award is made to University of Texas at Austin to develop methods for deep-tissue optical imaging by computationally decoding light scattering in biological tissue. Optical imaging is popular for enabling high-resolution and high-speed bio-imaging with morphological and molecular contrast. However, it is limited by light scattering, which scrambles sample-specific information and restricts imaging depths to well below the distances that light can travel within tissue. Decoding this scrambled information could extend imaging depths by an order-of-magnitude, which would be transformative for large-scale 3D imaging of intact or in-vivo samples. Furthermore, project developments can be applied to any wave-based regime limited by scattering, such as acoustics, lidar, x-ray, etc. These developments will be closely integrated with the creation of the LegoCellScope platform, which will consist of modular and low-cost projects to train students on the theory and application of computational imaging. This resource will be shared through outreach programs and integrated into local school curricula, with the goal of equipping students with practical imaging skills that can support future careers in image science. This CAREER project will specifically focus on developing imaging pipelines to achieve computational scatter-correction in real-world biological samples. To accomplish this, project developments will develop: (1) novel hardware systems (both in transmission and reflection) that utilize specialized illumination modules to encode sample-specific scattering information into raw measurements; and (2) novel inverse-scattering frameworks (for diffracted and fluorescent light) combining physics-based models with data-driven approaches. Data-driven priors will be trained on ground-truth scattering measurements obtained from bio-mimicking physical and quasi-digital phantoms. This project aims to showcase these developments in the fields of developmental biology and neuroimaging by achieving extended imaging depths in scattering embryo and brain tissues. If successful, this would mark a major milestone toward overcoming the scattering limit, which is currently the primary challenge for deep-tissue imaging. 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.