University Of Notre Dame

NSF Awards · FY 2025 · 2025-10

This project will study data management practices at user facilities with the goal of improving how research data is organized, stored, and shared. User facilities represent a major investment from NSF and each one has unique data formats and cyberinfrastructure. The project will target selected NSF Major and mid-scale facilities to examine current practices in order to create a roadmap aligned with FAIR principles that facilities can use for improvements in data management and to support open science and improve the national research infrastructure ecosystem. Current data management practices at selected user facilities will be assessed through surveys of the facility personnel and of the facilities' users. The assessment will include topics relevant to the FAIR principles, including data provenance, transfer, packaging, and storage, as well as how data is enriched and deposited for dissemination and citation. Best practices and data formats will be identified, and a roadmap will be created. The roadmap will be shared publicly for feedback through community-building workshops, and elements will be evaluated with hands-on pilot projects at the surveyed facilities. The findings are expected to be useful not only to the surveyed facilities, but to other user facilities and research facilities broadly for assessing and improving their data 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 · 2025-10

This project will study policies for interactive dialogue systems to help programmers with non-functional requirements. Interactive dialogue systems are Artificial Intelligence (AI)-based software systems, today largely built on large language models, which communicate with programmers to help them do software engineering tasks. Dialogue policies are the rules, user simulations, and human feedback mechanisms needed to train interactive dialogue systems to handle specific types of conversations. In the context of this project, non-functional requirements capture qualities about software related to legal regulations, contractual obligations, or other characteristics of software that are difficult to describe and yet necessary to implement. The project focuses on privacy and related legal needs. The vision for this project is to achieve a breakthrough in making AI-based dialogue systems capable of helping programmers find and implement non-functional requirements, specifically related to privacy and other legal needs. The basic plan for the proposed work is to: (1) design and conduct experiments about how software engineers interact with dialogue systems to implement non-functional requirements; (2) design models to represent these interactions in terms of dialogue policies; and (3) apply these policies to improve large language models and other AI-based interactive dialogue systems through fine-tuning and modifying training procedures such as custom loss functions. 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 · 2025-10

This project aims to investigate and develop a novel approach for realizing tunable and reconfigurable terahertz (THz) filters using optical control signals instead of electrical control wires which cause performance degradation in THz integrated circuits. The new approach enables high performance adaptive THz filters and more advanced communication circuits for 6G-and-beyond wireless communications, which is an emerging technological area with a wide range of applications that will generate significant benefits to American society. In addition to future wireless communications, the research of this project will benefit a wide range of other science disciplines using THz spectrum for sensing and imaging, such as radio astronomy, geoscience, chemistry, biology, and medicine. THz imaging can also be used for detecting concealed objects at various security screening checkpoints. The key results and concepts from this research will be incorporated into related courses taught by the principal investigators (PIs), and the graduate students working on this project will be trained with interdisciplinary knowledge in semiconductor physics and THz engineering, covering both devices and systems. Undergraduate students will be involved through summer and honors thesis research. Through the project's outreach plan, the PIs will promote science and engineering education with hands-on STEM activities among local middle- and high-schools through the NSF Research Experiences for Teachers (RET) program and several lab tours. The objective of this research is to investigate and develop a novel approach enabled by optically controlled switching technology to realize high-performance tunable and reconfigurable THz filters that are urgently needed in advanced sensing and imaging as well as next generation (6G and beyond) communications. The new approach is to seamlessly integrate the switching elements into planar THz circuits such as resonators (e.g., split-ring resonators, waveguide-cavity resonators and slot resonators) for optical control without any electrical control wires. This eliminates performance degradation due to parasitic effects from electrical control circuit networks, thus offering far more design flexibility and frequency scalability than the existing state-of-the-art technologies. Three waveguide filter prototypes including a probe-based microstrip configuration, an E-plane-coupled in-line chip design with cavity-based structure, as well as a free-space quasi-optical frequency-selective surface (FSS) architecture will be systematically studied and demonstrated. These prototypes are expected to achieve advanced THz frequency control and selection capability with superior performance and unique functionalities. The research team anticipates that the filter technologies developed in this project will have significant impacts on the designs of future adaptive THz communication and sensing 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.

NIH Research Projects · FY 2025 · 2025-09

PROJECT SUMMARY/ABSTRACT Long-term Objectives: The goal of this project is to develop a theoretical framework explaining why alcohol use is associated with non-suicidal self-injury (NSSI) in order to better understand if and how alcohol increases the likelihood of engaging in NSSI and the harms associated with NSSI. Training in qualitative/mixed methods, ecological momentary assessment (EMA) methodology, statistics, and scientific communication will prepare the applicant for an academic research career investigating the association between alcohol use and NSSI. Specific Aims: The proposed project will (1) use qualitative interviews to develop a preliminary theoretical model for how acute alcohol use impacts NSSI and a tailored EMA battery of items. To examine and refine the preliminary theoretical model, I will then (2) prospectively examine alcohol use, newly defined mechanisms, and NSSI in daily life. Finally, I will (3) conduct cognitive interviews evaluating participant experiences reporting on alcohol use and NSSI in daily life. Cognitive interview data will be used to further refine the initial theoretical model of alcohol use and NSSI. Training Plan: The training plan draws upon the expertise of a highly skilled mentoring team, with knowledge in qualitative and mixed methods (Drs. Banks and Miller-Graff), EMA and its application to examine alcohol use/NSSI episodes (Drs. Carpenter and Trull), and advanced statistical methods (Drs. Lane and Wang). The proposed fellowship will enable the applicant to gain expertise in the association between alcohol use and NSSI, qualitative and mixed method approaches, the design of EMA protocols, as well as quantitative techniques appropriate for intensive longitudinal data. Additionally, the applicant will be prepared for her next career stage by strengthening her scientific communication skills and publication record. Research Design and Method: To build a conceptual model of how acute alcohol use impacts NSSI, this project will use a sequential mixed-methods design, drawing on the strengths of qualitative and quantitative methods. Qualitative interviews will be used to develop a preliminary theoretical model for how acute alcohol use impacts NSSI. Next, a 21-day EMA protocol will prospectively examine associations between alcohol use and NSSI. EMA will evaluate near real-time changes, which can be used to evaluate the effects of alcohol on NSSI, as well as associations between mechanisms potentially impacted by alcohol and NSSI. Finally, a subset of participants will participate in cognitive interviews after completing EMA. Mixed method information gathered through EMA and cognitive interviewing will be used to refine an initial theoretical model. Significance: The proposed project will explore the processes underlying the established cross-sectional association between frequent, impairing alcohol use and NSSI. A mixed method approach will be used to develop a new conceptual model to explain the effects of acute alcohol use on NSSI.

NIH Research Projects · FY 2025 · 2025-09

PROJECT SUMMARY/ABSTRACT Recent advances in intervention research have revealed the promise of transdiagnostic, modular approaches implemented by lay paraprofessionals for the treatment of the most prevalent mental health concerns in settings affected by adversity (e.g., anxiety, depression, posttraumatic stress), but to date, few effectiveness trials have examined the indirect effects of treatment on intergenerational and economic outcomes or moderators of treatment effectiveness. There is thus a critical need not only for the continued expansion of the evidence-basis for care in low-resource settings, but also for the evaluation of factors contributing to effectiveness across multiple dimensions to gain a better understanding of the sustainability, long-term benefits, and cost-effectiveness of these approaches. The current study will conduct a rigorous evaluation of an existing program, the Common Elements Treatment Approach (CETA) with women (N=300) who are mothers of young children (ages 4-6). The trial will take place in the context of an integrated community care setting in Lima, Peru’s most populous and impoverished district, San Juan de Lurigancho. Our primary aims are to (1) evaluate the primary and indirect effects of CETA (2) examine moderators of treatment effectiveness, including implementation quality and neighborhood factors and (3) examine CETA’s cost effectiveness. Our central hypotheses are that (H1a) CETA will improve women’s mental health, intimate partner violence, and parenting and that (H1b) CETA will have indirect benefits for women’s economic outcomes and for their children’s adjustment. We also hypothesize (H2) that effectiveness will be enhanced by strong implementation quality and the presence of neighborhood promotive factors, and weakened by neighborhood disadvantage. Hypotheses will be evaluated using an RCT employing a longitudinal design with assessments at baseline (T1), post-test (T2), 6-month follow-up (T3) and 12-month follow-up (T4). Women will be randomized into the intervention condition (CETA + Enhanced Case Management [ECM]) or the comparison condition (ECM). Robust, multi-source (i.e., participant, therapist, supervisor, census data) and multi-method data (i.e., interview, observational assessment, google street view coding) will be gathered. The contribution will be significant by advancing research on both direct and long-term benefits of maternal mental health care for family systems, and is likely to provide important insights into the sustainability and cost effectiveness of these approaches. The expected outcome is an evidence-based, cost-effective, integrated approach to maternal mental health care that can be readily implemented by local organizations. Further, we anticipate that learnings from this project will respond to broader global public health concerns and provide opportunity for cross-context reciprocal innovation. Expanding the evaluation of CETA delivered in Spanish not only has advantages for the specific context under study, but provides an important foundation for addressing health disparities in Spanish- language mental health services in the US as well.

NSF Awards · FY 2025 · 2025-09

Non-technical Abstract: A good example of directional response of a system can be found in a semiconductor diode, where current flows more easily in one direction than the other. Similar behavior in superconductors can lead to applications in next-generation superconducting and quantum technologies. This project investigates superconducting materials exhibiting such effects at the atomic scale, with the objective of providing insights into superconductivity and its underlying mechanisms. The research activities are integrated with a research-centered educational plan for students and researchers across various disciplines, emphasizing critical thinking and the development of technical expertise. To broaden and sustain educational impact, the project includes a “STEM Teachers Residency” program, through which middle school teachers participate directly in research and co-develop innovative curriculum materials for nationwide dissemination. Public and scientific outreach efforts include the design and construction of educational demonstration setups for use in classrooms, research facilities, and the Children’s Museum of South Bend. Technical Abstract: The superconducting diode effect is a manifestation of non-reciprocal superconductivity. It typically requires simultaneous breaking of both inversion and time-reversal symmetries. The ability to detect and tune this effect not only offers a path to discovering symmetry-breaking unconventional superconductivity, but also enables immediate applications in superconducting electronics, spintronics, and quantum technologies. The research team leverages scanned Josephson tunneling microscopy to investigate the superconducting diode effect at the atomic scale and cryogenic temperatures. The goal is to reveal and control local intrinsic symmetry-breaking patterns in non-reciprocal superconductors that remain undetectable via macroscopic devices or optical measurements, due to factors such as crystal twinning and surface degradation. The project aims to derive signatures of the superconducting diode effect in atomic-scale Josephson junctions and to develop a new imaging modality that enables flexible choices of junction materials and interlayer twistability. Interdisciplinary education and outreach activities targeting students, middle school teachers, and the general public are fully integrated into the project, along with comprehensive training for students and postdoctoral researchers in numerical modeling, experimental techniques, and advanced instrumentation. 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

Minimal surfaces are surfaces which (locally) minimize area for their boundary, and are mathematical models of soap films, or more generally any physical interface whose area and energy are proportional. Minimal surfaces are important as both models and tools, and have found applications ranging from knot theory to general relativity. Like the soap films they model, minimal surfaces may not always be smooth -- for example bubble clusters in a bathtub will exhibit singular junctions where multiple bubbles meet. The goal of this project is to better understand the singular nature of minimal surfaces, when singularities can or cannot exist, and what the surface looks like near singularities. In addition to these research goals, the PI will mentor graduate and undergraduate students, and will continue supporting the local math outreach programs for elementary and middle school students. A significant goal of this project is to understand boundary singularities of capillary minimal surfaces, which are surfaces meeting a container at a prescribed angle, like liquid in a cup. The PI aims to construct examples of singular capillary surfaces, to investigate notions of generic regularity in the capillary setting, and push further the relationship between small-angle capillary minimal surfaces and the one-phase Bernoulli problem. A second goal of the project is to better understand entire minimal surfaces asymptotic to cylindrical cones, which effectively model degeneration towards cylindrical singularities. A third goal is to investigate the nature of minimal surfaces near tetrahedral singularities (which model the junction of 4 bubbles meeting at a point), and in particular whether tetrahedral singularities must persist or can be perturbed away into Y-type junctions. 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

Particle physics seeks to describe how the basic building blocks of matter interact to form the world we observe. The particles and forces observed in the last century of experiments are united into a single theory by the Standard Model (SM). In its current form, however, the SM conflicts with measurements of the universe at larger length scales. For example, it does not explain the nature of dark matter observed in galaxies. These disagreements suggest the SM is only part of a larger theory with other particles and forces that have not been discovered yet. The High Energy Physics Group at the University of Notre Dame, as a member of the Compact Muon Solenoid (CMS) experiment at the Large Hadron Collider (LHC) at CERN, is searching for signs of physics beyond the Standard Model in the proton-proton collisions at the LHC. The group's work includes searches for direct evidence of new physics, work on upgrades to the CMS detector, and a strong educational outreach initiative. As the LHC finishes its third run of data-taking, the Notre Dame group continues its leading role in physics analyses. The group is involved in multiple searches for exotic behavior in the Higgs sector, searches for supersymmetry, and is pioneering techniques in both effective field theory and data scouting. The group’s technical contributions are broad, including: electromagnetic calorimeter operations and management of the U.S. contributions; leadership in High Level Trigger monitoring; leadership in the CMS Simulation effort and Data Preservation; research and development for experimental upgrades of the CMS calorimeter and tracking detectors for improved performance at high luminosity; and in Computing, the group holds a U.S. CMS management position related to university-based computing facilities. The centerpiece of the group’s outreach efforts is QuarkNet, now in its twenty-seventh year. Notre Dame is the managing institute for this national program. QuarkNet currently consists of 54 Centers across the United States and Puerto Rico, and has been expanded to include eleven different experimental programs at seven national and foreign laboratories. Through QuarkNet, the particle physics field is creating a suite of outreach materials and demonstration projects that bring the excitement of particle physics to the public on several levels. 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

Research Project Management (RPM) is the structured planning, coordination, and oversight of research activities to help faculty researchers and institutions achieve their goals more efficiently and effectively. Although project management is widely used in other sectors, RPM remains underrecognized and inconsistently applied across U.S. research institutions. This project, Shaping the Future of Research Project Management: A Survey on Practice and Needs, brings together a national team of experts from multiple institutions to explore RPM further. The goal is to better understand how RPM is currently used, how it is perceived within the research community, and what future interventions would be most impactful to institutions of all shapes and sizes. In the future, survey data will be used to identify unique challenges and opportunities, ultimately supporting the development of targeted RPM tools and training development. This work supports the National Science Foundation’s mission by promoting the progress of science, strengthening the research workforce, and enhancing the national research infrastructure. The findings will be used to shape new programs and policies that boost research productivity, and then share them widely with the public, educators, and research professionals. While project management is widely used in other sectors, it is underutilized in research and inconsistently applied across institutions. This project will generate actionable data that can inform a scalable national model for RPM integration. This planning project will design, pilot, and distribute comprehensive surveys to assess the incidence, perceptions, and applications of RPM across U.S. research institutions. Using rigorous survey design and statistical analysis, the project will identify key trends, challenges, and best practices with comparative insights between various institutions to assess how RPM is understood and used across diverse research settings. The primary objective is to develop a comprehensive understanding of RPM practices and needs. Expected outcomes include: (1) enhanced understanding of RPM structures and challenges across institutions; (2) data-driven recommendations for developing targeted RPM related interventions, training programs, and resources; and (3) academic contributions to the growing literature on RPM. These outcomes will support the formalization of RPM as a recognized field and provide a foundation for future research and capacity-building efforts. Findings will be shared through publications, presentations, and webinars to ensure accessibility and impact across the research community and the public. 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

With the support of the Macromolecular, Supramolecular and Nanochemistry Program in the Division of Chemistry, Professor Hartland of the University of Notre Dame and Professor Masiello of the University of Washington are studying how nanomaterials interact with their environment. The work will involve measurements of the vibrations of the nanomaterials, and comparison of the experimental data to theory. The results from these studies will generate new information about how nanostructures absorb and reflect acoustic waves, which is important for sonar applications, and the conversion of elastic energy into heat, which is critical for understanding fatigue in materials. The information from this project will also be important for improving the performance of sensors made from nano-optomechanical devices, and for understanding the distances over which nanomaterials feel their environment. The research will be carried out by graduate and undergraduate students from the Universities of Notre Dame and Washington (as well as undergraduate students from nearby primarily undergraduate institutions), and high school students from local school districts. By performing the research in this project these students will learn the critical-thinking skills necessary to become the next generation of leaders in science and technology. With the support of the Macromolecular, Supramolecular and Nanochemistry Program in the Division of Chemistry, Professor Hartland of the University of Notre Dame and Professor Masiello of the University of Washington are studying the frequencies and lifetimes of nanostructure vibrations using a combined experimental/theoretical modeling approach. Transient absorption microscopy experiments will be used to interrogate single nanoparticles to generate precise information about the homogeneous dephasing times of their vibrations. The theory involves the development of a Green’s function approach to describe the hybridization and decay of the acoustic modes of the particles, as well as the modified local density of acoustic states induced by the environment. The results from this project will determine whether the properties of strongly coupled acoustic vibrations can be understood from the properties of the uncoupled modes, and whether “backaction” from reflected acoustic waves affects the vibrational lifetimes and/or frequencies of the nanostructures. The length scale over which the nanoparticle vibrations “feel” their environment will be investigated by studying single optically trapped particles. The way thermoelastic damping in metals is affected by frequency will also be investigated. 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 Cryptococcus neoformans, the etiological agent of cryptococcal meningitis (CM), is a globally distributed environmental yeast that mainly causes infections in immunocompromised individuals. Particularly in low- resource countries, the mortality rate of CM can reach 81% and accounts for 19% of HIV/AIDS-related deaths each year. Despite this high burden, CM treatment options are suboptimal, largely due to an incomplete understanding of the fungal biology and host-pathogen interactions. In immunocompromised individuals, once inhaled, C. neoformans escapes from the lungs and disseminates with special predilection for the central nervous system (CNS). Once in the brain, C. neoformans interacts with microglia, the tissue-resident macrophages of the CNS. Previous studies indirectly showed that microglia are ineffective at controlling this fungal infection. It has also been shown that many phagocytosed yeasts can survive, replicate, and avoid killing in the microglial phagosome, and this can be influenced by prior yeast opsonization. The mechanisms underlying this fungal survival and proliferation within the CNS, however, remain unclear. My preliminary studies have expanded on these previous findings, showing that immortalized and primary human microglia have decreased phagocytic and killing activity that is specific to C. neoformans. This has led to my central hypothesis that C. neoformans survives in the CNS by using both novel, capsule-independent, antiphagocytic mechanisms and phagosome maturation disruption within microglia, and that these mechanisms vary based on yeast opsonization. To test this, I will use an immortalized human microglia cell line to study the interactions between these immune cells and C. neoformans. This model is advantageous as it is more translational that rodent-derived cell lines, and it is easier to culture and obtain than primary human microglia. Experiments in Aim #1 will define the process of phagosome maturation in microglia after engulfment of wild-type C. neoformans. I will look at phagosome development, acidification, damage, and subsequent function. Experiments in Aim #2 will identify antiphagocytic cryptococcal proteins and determine their impact on microglia killing efficiency and phagosome maturation. Experiments in Aim #3 will define if yeast opsonization leads to differential receptor engagement and how this impacts the outcome of the infection. Specifically, I will study how opsonization impacts microglial phagosome maturation and killing efficiency, as well as study the receptors necessary for cryptococcal recognition and engulfment. Overall, my project takes advantage of the expertise in cryptococcal-phagocyte interactions and glia biology and function of my sponsor and co-sponsor laboratories, respectively, and will yield a better understanding of the interactions between C. neoformans and microglia, ultimately contributing to the knowledge of fungal biology and CM pathogenesis, making it more likely that effective therapeutics to treat CM will be developed.

NIH Research Projects · FY 2025 · 2025-09

PROJECT SUMMARY Often considered simple connectors, protein loops are extraordinarily important structures, regulating essential biological functions by forming macromolecular interactions and initiating signaling cascades. When mutated, loops propagate cellular dysfunction and disease, transcending a multitude of infectious, hereditary, and physiological disorders. Despite their importance, we have a limited understanding of loop structures as well as how loops alter protein structure, activity, and allosteric communication. Historically, a powerful tool to elucidate such structure-function relationships has been small molecules. In the pursuit of drug discovery, several covalent ligands have been serendipitously discovered to target cysteine residues in loops, leading to potent and selective small molecule probes. However, there is little emphasis on understanding the molecular, biophysical, and/or structural basis of the observed selectivity; and thus, scientists are limited in extrapolating these discoveries to target novel loop structures. In our current work, we have utilized covalent ligands to build structure-affinity relationships for two unique protein loops, which have revealed the key role of i) ligand shape in loop recognition and differential regulation of protein activity; ii) small molecule feature diversity in predicting covalent bond formation to loops; and iii) loop motion in the rate of covalent bond formation. Building upon these observations, we identified an exceptional model system to systematically study small molecule:loop interactions. As one of the most abundant human protein domains, RNA Recognition Motifs (RRMs) have a well-defined globular fold, loops that orthosterically and allosterically regulate RNA binding, and > 125 cysteines in loop structures for covalent bond formation. Utilizing RRMs, this proposal will elucidate guiding principles that describe ligand and loop features critical for i) molecular recognition, ii) regulating protein activity and structure, and iii) altering orthosteric and allosteric communication. These first-in-kind principles can be harnessed to rationally design small molecule modulators of novel loop structures. As current state-of-the-art is limited to massive screening campaigns and/or serendipity, a rational approach to loop targeting will be paradigm-shifting for chemical probe and therapeutic discovery. Furthermore, ligands discovered for RRM domains will transform our fundamental understanding of disease; approximately 25% of disease-annotated mutations are in RNA-binding proteins, which are an intractable, underprivileged protein class ripe for innovative small molecule discovery strategies. In the future, we expect these principles to guide the targeting of other dynamic and/or disordered structures, such as interdomain-linkers and intrinsically disordered regions, that when selectively targeted, expands protein ligandability to encompass the entire human proteome.

NSF Awards · FY 2025 · 2025-09

A series of four regional conferences in the Midwest on Quantum Symmetries will be held Fall 2025, and Spring 2026, 2027, and 2028, at Iowa State University, Illinois State University, Indiana University, and Purdue University. The primary objective of these conferences is to discuss significant recent advances in Quantum Symmetry and explore the interplay between various research areas, while providing an environment that supports wide participation and career development. These conferences will bring together graduate students working on their masters or Ph.D.s, postdoctoral researchers, early-career researchers, and established experts in Quantum Symmetries to catalyze research progress by disseminating recent discoveries in the field, sharing open problems, hosting new and ongoing collaborations, and mentoring early-career participants. By creating a network of researchers amongst the participants, the conference series will strengthen ties between regional institutions and support the breadth of subtopics being investigated in the region as well as the range of personnel performing these investigations. The topic of these conferences is Quantum Symmetry broadly viewed, but anchored in the mathematics modeling quantum behavior with the goal of advancing knowledge in Quantum Symmetry. Quantum Symmetry is a fundamental concept that permeates mathematics and physics, providing deep connections between topological, conformal, and more general quantum field theories and algebraic structures such as vertex operator algebras, Hopf algebras, tensor categories, and higher categories. These areas of mathematics study the structures which give rise to precise models for quantum behavior and are crucial for progress in applications such as quantum computing and error correction, enhanced encryption, and resolving the physical models of quantum mechanics with Einstein’s theory of relativity. The interconnectedness of these many subfields within the field of Quantum Symmetry makes the interdisciplinary collaborations and cross-fertilization of ideas facilitated by these conferences all the more important. More information about these conferences may be found at https://www3.nd.edu/~kbarron/QuaSy-Con.html . 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

Research into ceramic production and exchange in past societies has led to wide-ranging understanding of social, economic, and political organization in these ancient systems as well as implications for contemporary societies. Much of this work has utilized chemical analysis of ceramics using neutron activation analysis (NAA) and the American Southwest has been one area of intensive research. Existing NAA data represent significant research investment, but the combined power of this investment remains unrealized largely due to two impediments: 1) existing databases require synthesis and standardization; and 2) analytical methods that can systematically compare compositional data at these macroregional scales needs more development. This project produces a standardized, expanded, and broadly accessible database of more than 30,000 ceramic compositional analyses that will allow new big-data approaches (AI and machine learning) to large-scale interactions. The resulting databases are updated and readily available for a broad range of future research. Recent developments in artificial intelligence and machine learning allow exploration of large-scale multivariate data at scales that facilitate the exploration of regional-scale interaction. This project develops new methods for analyzing NAA data using social network analysis (SNA) tools that allow one to evaluate models and expectations derived from social network theory using findings of past networks based on typological similarities. Shifting Southwestern NAA studies from narrowly focused individual projects to regionally informed large-scale investigations allows researchers to more effectively sample sites or regions for NAA, making small samples considerably more valuable while not duplicating existing data. The methods developed in this project are directly applicable to other regions with comparable NAA databases. 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 addresses the needs of scientific communities studying the Earth, planets, stars, and their cosmic environments for a robust and extensible modeling framework specifically adapted to the surface of a sphere. The aim is to develop a very general scientific software framework called GeoMesh-HAMMER that is suitable for running on supercomputers. GeoMesh-HAMMER will be used to study the dynamics of different space plasma environments, including the magnetospheres around planets, stellar winds, and planetary nebulae. The novelty of this approach is in leveraging recent advances in modeling technologies for rarefied plasmas that are not in a state of equilibrium, but whose thermal properties are affected by magnetic fields and the presence of different gas species. In addition, the framework aims to implement state of the art techniques to concentrate the computational resources on the regions of greatest interest, such as a shock wave in front of a magnetosphere, or a burst of plasma from the sun known as a coronal mass ejection, with a much sparser allocation of computing resources for the surrounding space. This approach dramatically improves the efficiency of computer models, resulting in increased productivity and reduced power usage. GeoMesh-HAMMER will be built using an open source development strategy in collaboration with space science and astrophysics communities to maximize the impact on as many fields of study as possible. The adaptive multi-level framework is not limited to solar or space physics, but could also find applications in modeling weather, ocean currents, geodynamics, and digital mapping, all of which play immensely important roles in modern society. Computational astrophysics and computational space physics are fields of study that have seen an increasing amount of shared interest in recent years. Both fields rely on simulating novel flow physics that was not accessible until recently. Both fields have a great need to accurately simulate problems on meshes that are optimized for spherical geometry, are adaptive, and are free of coordinate singularities. Finally, both fields are seeing the need for going beyond the magnetohydrodynamic approximation. The commonality in the needs for the space physics and astrophysics communities argues for a common framework between the two communities. This project is based on the realization that computational physics informs the development of innovative cyberinfrastructure (CI), which in turn supports the best physics-driven needs of the two communities. This project addresses community building around the proposed CI with the goal of realizing a decades long goal of both communities to model rarefied multi-component magnetized plasmas not in the state of thermodynamic equilibrium. To achieve the best advantage of these advances, the solution methods for these equations have to be embedded in a CI that supports spherical meshes with adaptive mesh refinement (AMR) and are free from singularities. The proposed framework will incorporate state of the art technologies such as fluctuation-form update to handle non-conservative terms and physical constraint preservation so that high Mach number flows and strong magnetic fields can be simulated. The CI, called GeoMesh-HAMMER, will be a powerful new tool for both communities to carry out simulations of planetary and stellar environments on spherical geodesic-based meshes. This award by the Office of Advanced Cyberinfrastructure is jointly supported by the Division of Physics in the Directorate for Mathematical and Physical Sciences. 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

With support from the Chemical Structure and Dynamics (CSD) program in the Division of Chemistry, Professors Jon Camden at the University of Notre Dame and Lasse Jensen at Pennsylvania State University are combining sophisticated experimental and computational approaches to disentangle the relative contributions of electromagnetic and chemical enhancements in surface-enhanced spectroscopy. While it has been known for half a century that chemical effects play an important role in surface enhanced spectroscopies, a comprehensive understanding of these contributions remains elusive. Furthermore, employing current theoretical methods to predict the magnitude of chemical enhancements can be in error by several orders of magnitude, limiting their utility. Therefore, Professor Camden, Jensen, and their students will employ a non-traditional approach to understanding the chemical enhancement mechanism by combining experimental measurements using nonlinear spectroscopy with newly developed theoretical methods for calculating the nonlinear response properties. Their discoveries could advance the use of surface-enhanced spectroscopy by enabling high-quality predictions of the chemical enhancements and the rational design of molecular systems that maximize the spectroscopic response of molecules at surfaces. This work will additionally support a STEM teacher residency program and tools for visualizing molecular vibrations for the undergraduate chemistry curriculum, which will enable the proposed research to foster the next generation of STEM students. Specifically, this proposal addresses three outstanding fundamental scientific questions and challenges related to the chemical mechanism of surface enhanced spectroscopy. First, a comparison of surface-enhanced Raman scattering (SERS) and surface-enhanced hyper-Raman scattering (SEHRS) spectra of non-resonant probe molecules will be undertaken to address how static chemical effects can modify the overall enhancement factors. Second, a wavelength-scanned measurement of SEHRS spectra for resonant probe molecules will address how resonant chemical effects can modify the overall enhancement factors. Third, the first experimental measurements and theoretical calculations of non-degenerate SEHRS will be made to establish a benchmark and further characterize resonance effects in the enhancement mechanism. The experimental measurements will be complimented by the development of new computational approaches to model and interpret SEHRS. The combined experimental and theoretical studies will provide detailed insights into the chemical mechanism and serve as a comprehensive benchmark of the theoretical models. 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 cell wall is a structural edifice critical for survival of bacteria. Its biosynthetic machinery and the cell wall itself are targets of antibiotics. Cell wall is a crosslinked polymer that encases the entire bacterium, whose structure has been estimated to be larger than the chromosome. The complex biosynthetic and recycling processes of cell wall and its regulation during homeostasis are largely unknown. The Mobashery laboratory studies these processes in the Gram-negative bacterium Pseudomonas aeruginosa, with emphasis on cell-wall recycling. Two directions are proposed. The first is the study of the cytoplasmic pathway for recycling of muropeptides, which are fragments of the cell wall that have been internalized to the cytoplasm. A sequence of six enzymatic reactions constitutes this pathway, which brings the metabolites to a point of merger with the de novo pathway for the biosynthesis of cell-wall precursors. We proposed to investigate the mechanistic details of these enzymes individually. Meanwhile, all six genes have been cloned and the respective recombinant proteins have been purified to homogeneity. We have reconstituted the pathway in vitro and we have been able to observe the full metabolic flux for it. The reconstituted pathway has been miniaturized as a fluorescence assay for high throughput screening of compounds as inhibitors of these enzymes. An argument is presented that an inhibitor of the de novo biosynthesis (fosfomycin) should synergize well with an inhibitor of any step in the recycling pathway, whereby the action of the two inhibitors should shut down biosynthesis of the peptidoglycan entirely, which will be fatal for the Gram-negative bacteria. In the second direction, the mechanistic nexus between cell-wall recycling and manifestation of resistance to b-lactam antibiotics has been established. Historically, b-lactam antibiotics have been antibiotics of choice for treatment of infections by Gram-negative bacteria, including P. aeruginosa. In an attempt to disrupt this link, we have devised a fluorescent reporter strain of P. aeruginosa that fluoresces when cell-wall recycling takes place. The screening of a focused natural-product library (390 compounds) against the reporter strain for shutting down cell-wall recycling potentiates the activity of the b-lactam antibiotics, which otherwise will be ineffective in treating the resistant bacterium. Several compounds were identified with activity in this screening. We plan to screen two additional compounds libraries, at which time the positive hits will be assessed for selection of one or more for synthesis and evaluation of analogs with enhanced activity against a broader collection of Gram-negative bacteria.

NIH Research Projects · FY 2025 · 2025-09

PROJECT SUMMARY: An ever-expanding arsenal of insulin variants with customizable pharmacokinetics has enhanced the standard of care for individuals with diabetes. Rapid-acting options are employed alongside mealtime, while long-lasting analogs offer basal support throughout the day. However, developing insulin variants that dynamically adjust bioavailability and potency in response to changes in glucose levels, aligning with real-time therapeutic need, remains an ongoing target. The realization of this long-sought vision of glucose-responsive insulin has the potential to simplify dosing protocols and improve glycemic control, effectively mitigating both hyperglycemic and hypoglycemic episodes and their associated health complications; insulin therapy would instead be ready to respond to elevated blood glucose levels as needed. Meanwhile, the clinical impact of once-weekly antidiabetic medications (e.g., GLP-1 analogs) underscores the benefits of reduced dosing frequency in enhancing therapeutic adherence. While once-weekly insulin is a near-term clinical possibility, the development of glucose-responsive insulin has proven more elusive. In this project, we present a platform aimed at achieving both week-long AND glucose-responsive insulin from a single injection. Our preliminary approach involved chemically modifying insulin with a novel glucose binder in combination with a dendrimer carrier. This approach coupled electrostatic complexation with glucose-sensing dynamic-covalent bonding to create a subcutaneous nanocomplex insulin depot. Early results support the ability of this depot to respond to glucose challenge by promptly increasing serum insulin levels, as well as its ability to sustain function for at least a week in a diabetic swine model. However, the translation of this technology to clinical use may encounter certain challenges. This proposal focuses on addressing these anticipated hurdles and further validating the platform. One key concern is that chemical modification of insulin can reduce its potency and receptor binding affinity. To mitigate this issue, we will explore alternative linkers and conjugation strategies to minimize the impact of chemical modifications on insulin function. Additionally, the dendrimer carrier presents potential risks related to toxicity, limited biodegradation, and clearance. Drawing inspiration from degradable cationic carriers commonly used in gene delivery, we will investigate versions that offer improved biocompatibility and clearance. We will validate optimized formulations for their efficacy in diabetic rodents and assess their glucose-specific potency in rodent glucose-clamped models. Finally, we will confirm therapeutic function of our improved platform in a "human-sized" diabetic swine model, both in response to simulated meals and in the context of long-term blood glucose control with once-weekly dosing. Our innovative strategy to develop a week-long AND glucose-responsive insulin depot holds promise as a clinically viable product with direct impact on the lives of a rapidly growing population of individuals with all forms of diabetes.

NSF Awards · FY 2025 · 2025-08

Large language models (LLMs) are advancing the state of the art in nearly all areas of artificial intelligence, yet they remain poorly understood. At a time when new abilities as well as new limitations of LLMs are continually coming to light, a clear understanding of what they can and cannot do (that is, their expressivity) is becoming increasingly important. Furthermore, differentiating between the tasks that LLMs can solve at all scales, and those that LLMs can solve at small scales but are guaranteed to fail on at larger scales can be central to the success of some applications of LLMs, particularly where safety guarantees are needed. These questions can be answered with certainty only by mathematical verification. This project is contributing to the study of connections between LLM expressivity and mathematical logic. It is using those connections to reap both theoretical and practical benefits, in the form of new guarantees for LLMs, new extensions of LLMs, new methods for explaining how LLMs work, as well as new developments in mathematical logic. Just as the Curry-Howard isomorphism established a deep connection between logic and programming languages that enabled many results to be exchanged between the two fields, we are developing a "Curry-Howard isomorphism for neural networks": not merely a connection between one kind of neural network and one logic, but a correspondence between the elements of neural networks and the elements of logic that leads to a rich exchange of ideas between the two fields. This connection is establishing new theoretical results about neural networks and driving the development of new neural networks. In the other direction, the proposed research program is pursuing new and exciting developments in logic and model theory, particularly at the intersection of finite model theory and continuous logic, which has not been previously studied. The project is creating interdisciplinary collaborations, not only within the project itself but also between researchers in logic and deep learning more broadly. 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 award provides support to U.S. researchers participating in a project competitively selected by a 55-country initiative on global change research through the Belmont Forum. The Belmont Forum is a consortium of research funding organizations focused on support for transdisciplinary approaches to global environmental change challenges and opportunities. It aims to accelerate delivery of the international research most urgently needed to remove critical barriers to sustainability by aligning and mobilizing international resources. Each partner country provides funding for their researchers within a consortium to alleviate the need for funds to cross international borders. This approach facilitates effective leveraging of national resources to support excellent research on topics of global relevance best tackled through a multinational approach, recognizing that global challenges need global solutions. Working together in this Collaborative Research Action, the partner agencies have provided support to foster global transdisciplinary research teams of natural, health and social scientists and stakeholders from across the globe to improve understanding of climate, environment and health pathways to protect and promote health. The projects will provide crucial new understanding into the health implications arising from the impacts of climate change and variability on; 1) decision-science approaches to adaptation and implementation, 2) food, environment, and biological security and 3) risks to ecosystems and populations. This award provides support for the U.S. researchers to cooperate in consortia that consist of partners from at least three of the participating countries to increase our knowledge of the complex linkages and pathways between the climate, environment and health to help solve complex challenges that face societies. The BioARC project seeks to develop an interdisciplinary network of scientists, health professionals, and stakeholders to build the missing physical, human, and material infrastructure to stop pandemics at their source. These various forms of infrastructure will be centered on the development of multiple in-country biorepositories spread throughout The Americas, where pathogens with pandemic potential (e.g., Zika, Andes Virus) and neglected tropical diseases (e.g., Dengue, Chagas, and hookworm infection) have previously emerged and spread. This new infrastructure will provide the critical spatial, temporal, and taxonomic sampling and associated informatics necessary to understand the role of environmental drivers in host-pathogen dynamics, enabling a more proactive and predictive approach to pathogen emergence. This project directly addresses a critical challenge to pandemic preparedness. COVID-19 directly illustrated the high costs of pandemics to human wellbeing and the persistent gaps in our approach to preventing pathogen emergence. As humans and wildlife increasingly share space, opportunities for spillovers grow. Additionally, environmental stresses can cause wildlife to shed pathogens more readily as stress induced by things like habitat loss, heat exposure, or food scarcity decreases immune functionality that would typically keep pathogen shedding low. The project will focus on improving biorepository infrastructure including equipment and databases. The project team will develop training modules on museum science, fieldwork, molecular genetics, informatics, geospatial data analysis, science communication, and interdisciplinary network development. The project will develop best practices for biorepositories and relational databases for pathogens, interdisciplinary workflows for wildlife pathogen surveillance, communication across One Health disciplines, and strategies for biorepository decision-maker coordination. The goal of developing best practices is to enable the standardization of procedures for similar efforts locally and globally, and to form the foundation for an early-warning system for zoonotic diseases that will improve U.S. national security and build the U.S. workforce. The project will reduce costs of outbreak response by creating the capacity and data to establish baselines for wildlife pathogen dynamics, detecting deviations from these baselines, informing models, and enabling timely biosecurity decisions. The project will develop a robust, enduring system to safeguard human and animal populations from infectious diseases. 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

ABSTRACT Malaria remains a significant public health challenge, with 234 million cases and 593,000 deaths in Africa in 2021. The emergence of partial resistance to artemisinin in Africa will likely worsen this situation leading to failure to control the parasite with the main frontline drugs artemisinin combination therapies. Arteminsinin resistance also will likely lead to resistance to partner drugs used in combination. Evidence suggests that resistance to lumefantrine, the partner drug in the most common ACT in Africa, artemether-lumefantrine (AL), is also emerging. Our proposal leverages multiple parasite lines from UK travelers who failed AL therapy, including isolates with high-level stable lumefantrine resistance, to investigate resistance mechanisms. We aim to gain insight and understand the underlying cellular and genetic alterations associated with lumefantrine resistance using multi-omics, murine genetic crosses, and CRISPR technology. We will achieve this through the following specific aims: Specific Aim 1: Conduct a detailed analysis of in vitro phenotypes and genome variation in P. falciparum isolates from African patients who failed AL treatment from the UK research biobank. Using two high-level resistant, intermediate and sensitive parasites, we will clone these parasites by limiting dilution to ensure purity and phenotype them through standard IC50 testing. Targeted sequencing of known drug resistance genes will identify potential mutations, and isolates will be assessed for gametocyte production for use in genetic crosses. This aim will create a well-characterized renewable resource related to lumefantrine as well as artemisinin resistance Specific Aim 2: Determine genomic, transcriptional, and translational differences associated with reduced lumefantrine sensitivity. Using well-defined isolates from the UK Malaria Reference Lab, we will perform telomere to telomere genome sequencing, single-cell RNA sequencing, bulk RNAseq, and proteomics to identify stage-specific expression changes and potential causative mutations. We will use CRISPR gene editing to evaluate the impact of known MDR1 and CRT mutations as well as other discovered candidates on lumefantrine resistance. Specific Aim 3: Identify quantitative trait loci (QTLs) associated with stable in vitro lumefantrine resistance through genetic crosses in humanized mice with human hepatocyte grafts. We will cross lumefantrine-resistant parasites with complementary drug-susceptible parasites, analyze recombinants under drug pressure, and perform QTL mapping. CRISPR editing will validate the polymorphisms associated with lumefantrine susceptibility. This comprehensive investigation will yield a valuable extensive bank of characterized isolates, actionable molecular markers, and insights into the mechanisms of lumefantrine resistance, advancing our understanding and control of malaria lumefantrine resistance.

NIH Research Projects · FY 2025 · 2025-08

PROJECT SUMMARY Pathogenic mycobacteria, including Mycobacterium tuberculosis, cause acute and chronic infections that significantly im- pact human health. Mycobacterium marinum is a non-tubercular mycobacterial pathogen and a well-established model for studying several aspects of M. tuberculosis pathogenesis, including ESX-1 secretion. Early during infection, pathogenic mycobacteria reside in and adapt to the phagosome. The pH of mycobacterial phagosomes differs based on the immunolog- ical activation state of macrophages. Although mycobacteria escape the phagosome using the ESX-1 secretion system, the mechanisms used by ESX-1 to lyse phagosomes under conditions of varied pH is a major gap in our fundamental under- standing of mycobacterial infections. The applicant’s preliminary data suggest that the ESX-1 system switches which sub- strates are secreted in response to acidic pH. The long-term goal is to understand the molecular mechanisms of mycobacte- rial pathogenesis. The objective of this proposal is to determine how ESX-1 secretion promotes lysis in response to varying pH in vitro and during infection. The central hypothesis is that pathogenic mycobacteria switch the substrates secreted by ESX-1 in response to acidic pH to lyse phagosomes in macrophages of different immunological activation states. The ra- tionale for this project is that defining how mycobacteria respond to different host cell physiologies may offer critical insight important for considering treatment and prevention of mycobacterial diseases. The central hypothesis will be tested by following these specific aims: 1) Define the genetic requirements for hemolysis at acidic pH. Under the first aim, targeted and unbiased molecular genetic approaches combined with qRT-PCR, IP followed by proteomics and ESX-1 functional assays will be used to identify the genes and mechanisms underlying lytic activity at acidic pH. 2) Measure changes in ESX- 1 secretion in response to acidic pH. The second aim will use proteomics to measure changes to the secreted proteomes of M. marinum and M. tuberculosis at acidic pH. 3) Investigate substrate switching during mycobacterial infection. The third aim will combine molecular genetics, chemical inhibitors of acidification and immune-activated infection models, and ani- mal models to determine if specific substrates are conditionally transcribed and required during M. marinum and M. tuber- culosis infection. The research proposed research is conceptually innovative because it tests the idea that ESX-1 switches substrates to lyse phagosomes associated with heterogeneous macrophage physiologies. The formation of multiple ESX-1 assemblies in response to environmental cues is conceptually innovative. There is technical innovation in the chemical inhibition of ESX-1 lytic activity, through leveraging a unique and comprehensive M. marinum strain collection for use with established proteomics work flows, and in the use of differentially activated cellular and animal models of infection. The successful completion of this proposal will be significant because it will identify seminal ESX-dependent virulence mech- anisms and provide new insight into mycobacterial infection biology by generating understanding of how mycobacteria respond to heterogeneous host cells during infection.

NIH Research Projects · FY 2025 · 2025-08

PROJECT ABSTRACT Endogenous neural stem cells play a crucial role in neurogenesis and gliogenesis in the adult healthy brain and following injury or disease. In response to demyelination, or the loss of myelin sheaths surrounding axons, endogenous neural stem cells contribute to repair by upregulating gliogenesis and differentiating into myelinating oligodendrocytes. However, there is a gap in our current understanding of the mechanisms regulating adult neural stem cell-mediated remyelination. In particular, it remains unclear how neurovascular interactions within the stem cell niche respond to demyelination, and how this shapes neural stem cell behavior. We previously identified Endothelin-1 as a novel regulator of neural stem cells during development. In the adult brain, we find that endothelial cell-derived Endothelin-1 signals to neural stem cells as part of the neurovascular unit. Loss of this signaling pathway promotes gliogenesis from quiescent neural stem cells. Therefore, we hypothesize that Endothelin-1 signaling maintains adult neural stem cell quiescence, preventing differentiation in both the healthy and demyelinated brain. We will test this hypothesis through the following specific aims: In aim 1, we will use conditional knockout mice and primary cell culture to determine if Endothelin-1 signaling regulates neural stem cell quiescence in the healthy adult mouse brain. In aim 2, we will use knockout mice and the cuprizone toxicity demyelination mouse model to determine the role of Endothelin-1 signaling in neural stem cell-derived remyelination. Overall, these results will provide critical insight into the mechanism of Endothelin-1 signaling in adult neural stem cells and the feasibility of targeting this pathway to enhance remyelination.

NIH Research Projects · FY 2025 · 2025-08

PROJECT SUMMARY: The treatment of diabetes and obesity has seen an inflection in recent years with the approval of once-weekly glucagon-like peptide 1 receptor agonists (GLP1-RAs), which offer support in glucose metabolism for a week following a single injection. In spite of more convenient once-weekly self-administration, improving over the daily or twice-daily injection schedules of earlier agents in this class, the use of these newer GLP1-RAs still suffers from sub-optimal therapeutic persistence due to a combination of side-effects and poor compliance with self-administration schedules. The creation of GLP1-RA therapies with multi-month duration of function would circumvent both challenges. First, controlled release GLP1RA depots are known from clinical evidence to reduce side-effects compared to administration of the free peptides. Second, a multi-month dosing schedule would better correspond to the schedule of routine clinical touch-points with physicians or pharmacists and thereby avoid the need for self-administration entirely. Our preliminary work leveraged the identity of GLP1- RAs as synthetic peptides amendable to synthesis by standard solid-phase methods, further engineering these through facile side-chain modifications to present motifs that promote nanofibrillar self-assembly and hydrogelation. The resulting injectable self-assembling GLP1-RAs offered long-lasting serum concentrations and improved therapeutic outcomes when assessed in a rat model of type 2 diabetes. This proposal will seek to build on this initial concept by further tuning the engineered self-assembly motif to enable robust single- component nanofiber assembly and hydrogelation while ensuring potent receptor signaling and physicochemical stability. The enhanced designs will then be assessed as injectable depots for their ability to control blood glucose and weight gain in a model of type 2 diabetes, along with a detailed assessment of their biocompatibility in the context of subcutaneous application. Finally, the modularity of this approach will be assessed by integrating a next-generation therapeutic in this class that functions through simultaneous signaling of three separate receptors involved in metabolic regulation. Through these studies, our innovative concept to develop a long-lasting GLP1-RA depot by direct self-assembly of the therapeutic agent will be further optimized and assessed for its potential in combating the ongoing diabetes and obesity epidemics. Specifically, this approach conceives of new self-assembling therapeutic peptide depots that offer controlled release to reduce dosing frequency and stable serum concentrations to better mitigate side-effects.

NSF Awards · FY 2025 · 2025-08

This project addresses the critical need to improve scientific models that combine observed data with established physical laws. As researchers increasingly rely on large and complex datasets, there is growing interest in "hybrid models" that merge data-driven insights with the knowledge embedded in mathematical equations, such as those used in physics. However, current methods lack the theory necessary for reliable and interpretable results, especially in understanding spatial phenomena like fluid movement. This project will develop a new modeling framework that bridges the gap between data and physical understanding, enabling more accurate and consistent spatial predictions. The project will also foster outreach by creating open-source tools. The project develops a novel functional framework for hybrid spatial models that regularize data-driven predictions using Partial Differential Equations (PDEs). The approach formulates spatial regression as a functional optimization problem, where the solution is penalized by the governing PDE, enabling the derivation of fundamental mathematical results. The research has three main objectives: (1) to establish a theoretical foundation for these hybrid models by ensuring well-posedness; (2) to implement inference and spatial interpolation using both finite element methods and Hilbert space basis decompositions; and (3) to apply the methodology to fluid dynamics, generating physically consistent predictions. This framework is transformative in statistical methodology, integrating data science with physical modeling. It advances inferential techniques for spatial functional data and supports reproducibility through open-source software. 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.