University Of Chicago

NSF Awards · FY 2024 · 2024-09

With the support of the Macromolecular, Supramolecular and Nanochemistry Program in the Division of Chemistry, Prof. Esser-Kahn of the University of Chicago will explore a method of polymer synthesis mediated by electric fields. The research will focus on the mechanism of how electric fields can be used to control and mediate the vibration of particles that produce chemical reactions. By examining the mechanism of both vibration and chemical reaction, the team will explore a new method to generate polymers and materials that can, shortly, be compatible with programmable interfaces via computer. The potential impacts of this work include enabling new forms of adhesives. Understanding these processes could improve other materials developments. Prof. Esser-Kahn, plans to continue his new educational program for high school students at the University of Chicago. This program educates 30 students each year, selected from 120 applicants, provides them with coursework and hands-on training to develop an understanding of engineering and design and the fundamentals of energy storage and transfer. The team hopes to retain and improve the outcomes of the program, which has served more than 100 students with a launching platform for their enrollment in STEM programs across the United States, with 50% enrollment in STEM PhDs. The project will examine how the particle's surface, as it charges, induces new forms of reactivity. This reactivity is focused on ionic interactions that mediate particles' interactions with solutions and their ability to transfer electrons to reagents for polymerization. We will determine how the electric field influences the particles' rate of reactivity and their interplay with the solution based on the ionic interaction between the particle and the double layer formed by the solvent and secondary ions. The interplay between the solvent, ions, and dipole will be examined to determine how these ratios influence the reactivity of different species. 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 2024 · 2024-09

To advance research in biological hydrostats – soft-bodied structures made mostly of water – this award supports a symposium at the Society for Integrative and Comparative Biology annual meeting in January 2025 that brings together researchers working on soft-bodied organs in a wide range of animals. Biological hydrostats are everywhere in nature, including structures such as human tongues, octopus tentacles, elephant trunks, and flatworm bodies. These hydrostats serve many important tasks, from movement to reproduction to feeding, and yet there are still many unanswered questions about how different hydrostats work to perform those tasks. Answering these questions is important to biologists who seek to understand how the biodiversity of hydrostat structures came to be. These questions are also important to bioengineers who wish to design the next generations of soft-bodied robots, and to physicians and speech therapists who seek new ways to help human patients struggling with speech and difficulty in chewing and swallowing. The goals of the symposium are to share quantitative and theoretical approaches that have been deployed in the study of hydrostat function in different animals, to provide networking opportunities for researchers from diverse backgrounds and career stages, and to identify new questions that will drive this field forward. A series of papers based on the symposium presentations will be published and disseminated. Hydrostatic structures are found across multiple scales of anatomical organization, from polyps to elephant trunks. The ability to transmit forces through internal hydrostatic pressure is critical for many aspects of organismal performance. Recent methodological and conceptual advances have expanded our understanding of hydrostat structure, physiology, and motor control, but we still have little insight into how biological and mechanical factors drive and control hydrostat shape change, movement, and transfer of force. Research on biological hydrostats is proceeding apace in diverse organ systems and animal lineages. Novel imaging modalities are yielding new insights into the three-dimensional structure of biological hydrostats, and high-speed videography and XROMM are making it possible to measure hydrostatic deformation in vivo in some organisms. The symposium and complementary contributed posters at the annual meeting of the Society for Integrative and Comparative Biology will bring together researchers in different fields, including early-career scientists, who are studying hydrostats in different animal systems with a range of modern tools, to bridge subdiciplines, promote new collaborations, and identify gaps and future research needs. The symposium will (1) highlight diverse quantitative approaches that have been deployed in the study of hydrostatic structures in different animal lineages, (2) discuss the power and limitations of existing conceptual frameworks explaining hydrostatic function, and (3) identify new ways to integrate different data modalities to address questions in the field. 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 2024 · 2024-09

This workshop will convene experts in rare and extreme event detection and characterization representing a broad range of application domains and disciplines, including statistics, machine learning, applied mathematics, operations research, space weather, materials science, and climate modeling. Unanticipated rare and extreme events can be catastrophic in the domains of damaging high energy solar flares, sudden fuselage failure, and extreme terrestrial storms, causing significant loss of life and livelihood. Progress in modeling and predicting of such high risk events will require novel multidisciplinary approaches and this is what this conference seeks to uncover. It also seeks to catalyze new collaborations across these methodological and applicational domains. The goal is of convening experts with complementary backgrounds is to identify key challenges and opportunities, with an emphasis on methodologies that may be leveraged across domains. The focus on data-driven methods encompasses recent efforts in machine learning, including physics-informed machine learning and generative models, and how such tools may advance rare and extreme event forecasting. The agenda will also include physics-driven approaches, including simulations, both as a source of fundamental insights into the modeling of rare events and as a mechanism for generating data to complement real-world data used to train data-driven models. This two-day workshop will be held at the University of Chicago on November 20-21, 2024. It will feature lectures from experts across the spectrum of disciplines listed above, panel discussions, poster sessions, and lightning talks. 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 2024 · 2024-09

The current cosmological model for a theory of the Big Bang still leaves open a question how the entire observable Universe being spawned in a dramatic, exponential "Inflation" from a sub-nuclear, microscopical volume to the current macro-scale volume of spacetime. While extraordinarily sensitive measurements of the Cosmic Microwave Background (CMB) radiation (temperature and polarization at mm/sub-mm wavelengths) are traditionally associated with large CMB surveys, the ultra-deep “sky maps” are crucial for exploiting the full power of new cosmological observables and provide groundbreaking constraints on the duration and timing of the Big Bang’s short Inflation period and the follow-on Epoch of Reionization. The new-generation SPT-3G+ camera will be used to produce a survey of the mm/sub-mm sky with an unprecedented combination of area, sensitivity, and angular resolution. These measurements will cover the same sky as the ongoing SPT-3G and BICEP-Array surveys, but the resulting maps will provide new insights into the Epoch of Reionization, the growth of structures in the Universe, improve constraints on cosmic Inflation, and provide a new window into mm/sub-mm Galactic and extragalactic astrophysical transients. This award will support the construction of a new camera, SPT-3G+, that will have unique capabilities not provided by any planned instrument. SPT-3G+ will enable extraordinarily sensitive measurements of the temperature and polarization of the mm/sub-mm wave sky, extending the ultra-low-noise, wide-sky-area observations traditionally associated with large CMB surveys to include frequencies above the peak of the CMB blackbody emission curve. This work builds on the experience and successes of the SPT team, which has built three cameras for the SPT and used them to produce high-impact studies of the CMB. In addition to the proposed mm/sub-mm survey, the SPT-3G+ camera will provide a platform for innovative instrumentation with the potential for new probes of astrophysics and cosmology, including in the burgeoning field of mm-wave line intensity mapping. Finally, the SPT-3G+ camera and optics are designed to allow the SPT to continue its crucial role as part of the Event Horizon Telescope (EHT). The proposed activities will include a junior college internship and mentoring program, that will involve students in the development, integration, and testing of the SPT-3G+ camera. 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 2024 · 2024-09

Precise measurements of the motions of stars on the celestial sphere are critical for understanding the formation and content of the Milky Way galaxy. Astronomers create computer models of the motions of stars to help understand assembly history of the Milky Way, the nature of dark matter, and look for planets around nearby stars. However, the motions of stars are extremely and difficult to measure. Moderately bright stars have been measured with exquisite precision by the European Space Agency’s Gaia spacecraft, but larger telescopes are required to measure fainter stars. The investigators will develop and apply new techniques to measure the motions of faint stars using some of the world’s most powerful ground-based survey telescopes. As part of this project, the investigators will provide scientific and technical training for graduate and undergraduate students. Furthermore, the investigators will engage and educate the general public with visualizations of the dynamic motion of stars in the Milky Way. The investigators will measure the astrometric positions of stars in hundreds of thousands of images collected by the Dark Energy Camera (DECam) on NSF’s 4-m Blanco Telescope. The investigators will use the DECam data to perform best-ever measurements of the proper motions of hundreds of millions of stars that are too faint to have been measured previously. The DECam data cover nearly the entire sky area of the Vera C. Rubin Observatory’s unprecedented Legacy Survey of Space and Time (LSST). The investigators will combine the DECam and LSST data to measure the positions and motions of stars much more precisely than would be possible with the first year of LSST alone. This research award is partially funded by a generous gift from Charles Simonyi to the NSF Astronomy division. The project includes significant contributions to Vera C. Rubin Observatory’s Legacy Survey of Space and Time. 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 · 2024-09

ABSTRACT Background: Black men who have sex with men (MSM) are disproportionately impacted by HIV and face many barriers to care engagement, such as housing instability, unemployment, and criminal justice involvement. Interventions to address these factors are resource intensive and logistically challenging, and the best implementation strategies remain unclear. Agent-based models (ABMs) can be used to virtually evaluate candidate interventions and implementation strategies to facilitate more efficient and timely intervention development, and combined with iterative community and public health stakeholder feedback can provide important insights about which intervention strategies and implementation levers would be most effective and efficient in real-world settings. Objective: Building on an existing ABM platform, this proposal will utilize multiple existing local data sources and new data collected through qualitative interviews and focus groups to better understand barriers to linkage, engagement, and retention in HIV care among Black MSM. We will combine methods from epidemiology, agent-based modeling, and implementation science to understand the potential impact of strategies to increase engagement and retention in HIV care on population-level HIV transmission. Methods: We will characterize individual, clinical, and system level barriers to engagement and retention in care, identify relevant implementation levers, and use this information to simulate (Phase 1) and pilot (Phase 2) implementation strategies to improve re-linkage, engagement, and retention in care among previously diagnosed individuals who are not consistently engaged in care. Significance: A better understanding of where and how to focus efforts to relink out of care individuals and to improve HIV care engagement and retention has the potential to have an important impact on the HIV epidemic. Once developed, our methods and models can be adapted to other geographic areas to reflect local prevention priorities and can serve as an example application of implementation science and ABM methods to advance HIV prevention science.

NIH Research Projects · FY 2025 · 2024-08

ABSTRACT The increasing prevalence of diet-related chronic conditions, such as obesity, diabetes, and cardiovascular disease, has elevated the importance of improving nutrition as a national health priority. However, critical evidence remains limited on the long-term health outcomes and economic impacts of interventions aimed at improving dietary intake and reducing food and nutrition insecurity. This project seeks to fill these critical gaps by evaluating the health and economic effects of selected food and nutrition interventions, generating evidence to inform national priorities related to reducing diet-related disease and improving population health. Guided by three criteria – (a) strategic priorities outlined in the national report on Hunger, Nutrition, and Health, (b) a conceptual framework incorporating the health impact pyramid and NIMHD research framework on the domains of influence (population- vs. individual-level), and (c) the availability of supporting empirical evidence, we will evaluate four promising and scalable interventions: (1) expanding the USDA-supported Gus Schumacher Nutrition Incentive Program and (2) reforming the Supplemental Nutrition Assistance Program (SNAP) benefit structure and eligibility, (3) increasing adoption of nutrition-related screening in clinical settings, and (4) enhancing access to dietary and lifestyle counseling. To estimate the long-term health and economic impacts of these interventions, we will use a validated, NIH-funded, dynamic microsimulation model that simulates diet-related disease progression in U.S. adults over the life course. The model incorporates demographic, behavioral, and clinical risk factors and is designed to evaluate long-term population health outcomes, medical expenditures, and intervention costs. Through comprehensive scenario, sensitivity, and subgroup analyses, we will assess variation in effectiveness and cost-effectiveness across population subgroups, considering differences in baseline risks (e.g., food insecurity) or vulnerability to the risk (e.g., effects of food insecurity on outcomes) or intervention’s effects across demographic subgroups. Our research team brings interdisciplinary expertise in policy evaluation, simulation modeling, nutrition science, and health economics. We are uniquely positioned to: (Aim 1) measure long-term population health effects of food and nutrition interventions; (Aim 2) estimate long-term effects on health across population subgroups; and (Aim 3) quantify economic impacts and cost-effectiveness. An independent dissemination aim will improve knowledge translation to end-users by legal and administrative feasibility analysis and developing a web-based platform, the National Food and Nutrition Policy Impact Simulator. This project responds to the need for actionable, policy-relevant evidence to inform national strategies to reduce diet-related disease and improve population health. Findings will support identifying food and nutrition interventions that offer the greatest potential for improving population health and achieving cost-effectiveness.

NIH Research Projects · FY 2026 · 2024-08

Modified Project Summary/Abstract Section Violence is the leading cause of mortality among US children. In Chicago, violence disproportionately affects children on the South and West sides, with studies documenting community violence exposure as high as 85% in some neighborhoods. Research also shows that social, economic, and health factors, such as poverty and lack of access to quality health and educational resources, increase the risk of violence. Sustained community violence exposure has a detrimental impact on youth’s overall well-being, reducing school engagement, encouraging maladaptive behaviors, and eroding mental health. Therefore, it is critical to develop and implement violence prevention interventions that address the social, economic, educational, and health factors that exacerbate youth involvement in community violence. Such efforts must reach across all levels of the social-ecological model, moving beyond individual and interpersonal focused interventions to address the upstream factors that impact violence. Research shows that community health workers (CHWs) can apply their expertise to prevent violence by serving as a nexus between families and social and health services. Also, legal assistance can be used to address social and economic factors that contribute to community violence, as seen in medical-legal partnerships. Thus, this project’s objective is to evaluate a novel youth violence prevention program that combines CHWs and legal assistance—Community Health Advocates in Mitigating and Preventing Violence (CHAMP-V) with and without Legal Aid Wraparound (LAW). We hypothesize that community health advocacy and legal advocacy can work synergistically to reduce violent behavior and improve educational outcomes by holistically addressing social, economic, education, and health-related needs of middle school youth and their families. To test this hypothesis, we will conduct a cluster randomized trial comparing the two intervention groups. In Aim 1, we will adapt the CHW and legal aid interventions to ensure relevance to school settings using a community-driven approach that engages parents/guardians and school principals/staff through focus groups and interviews. Aim 2 will evaluate the effectiveness of CHAMP-V versus CHAMP-V+LAW on violence-related and educational outcomes, using primary survey data as well as administrative data from the Chicago Police Department and Chicago Public Schools. Aim 3 will examine implementation factors and mechanisms by which the interventions promote change in social, economic, educational, and health needs that impact youth violence, using service delivery logs and interviews. Results from this study will provide rigorous evidence about the effect of CHW and legal advocacy strategies to prevent community violence for middle school youth and their families, while offering a scalable approach that targets all levels of the social-ecological model. Further, by addressing various causes of violence, such programs are vital to help interrupt the cycle of stress, trauma, and violence that contribute to adverse health, education, and mortality outcomes in communities.

NSF Awards · FY 2024 · 2024-08

This award will fund a research program that will use three projects to develop improved econometric methods for understanding earnings heterogeneity in matched employer-employee data and intergenerational mobility in large administrative registers. The first project will re-examine understanding of the role firms and worker differences play in earnings heterogeneity -- the idea that earning heterogeneity stems from differences in wages across firms as well differences in worker productivity. The researchers will examine in detail the extent to which these conclusions rely on assumptions about worker mobility and the way in which their wages depend on the changes on employment across firms. The second project will conduct a similar exercise, but the focus will be on understanding intergenerational mobility. The third project will propose improvements in the methodology for ranking of places that are constructed by introducing new selection techniques and new error terms in order to provide a better explanation that does not rely on these special assumptions. The results of this research will improve methods of studying wage heterogeneity and intergenerational mobility and thus provide strategy inputs. This award funds a research project to develop econometric methods to quantify the importance of firm heterogeneity, worker heterogeneity, and worker sorting for earning heterogeneity and intergenerational mobility. The core of the research project is a re-examination of the assumptions underlying the econometric models to study wage heterogeneity and intergenerational mobility. The research consists of three projects. The first project re-examines the role of firm heterogeneity, worker heterogeneity, worker sorting, wage dynamics, and geographical mobility in determining earning heterogeneity. The second project will use the same methodology to study intergenerational mobility. The third project will propose improvements in which confidence sets for ranking places of mobility will be constructed by exploiting moment selection techniques and by introducing new error rates based on generalized error rates that arise in multiple testing. The results of this research will improve methods studying of wage heterogeneity and intergenerational mobility and will therefore provide inputs into strategies to reduce wage heterogeneity and increase intergenerational mobility. 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 2024 · 2024-08

This award funds the research activities of Professor Savdeep Sethi at the University of Chicago. The microscopic structure of space and time are one of the enduring mysteries of nature. Did space and time emerge in some kind of Big Bang? Will the universe end in a Big Crunch? What is the nature of dark energy? In order to answer such basic questions about the physics of our universe, we need a quantum theory of gravity. String theory remains our leading candidate for such a theory. In his research, Professor Sethi aims to explore the physics of string theories both with and without a remarkable structure called supersymmetry. This research program has concomitant broader impacts in four areas. The first comes from providing research opportunities for undergraduates, including continued participation in the Summer REU Opportunities for Minorities and Women program at the University of Chicago, and through direct research opportunities. The second is promoting equity by organizing conferences like the Conference for Undergraduate Women in Physics. The third is through public outreach programs like the Life Long Learning program. The final aspect involves improving interdisciplinary ties with both cosmologists and mathematicians through lectures at schools and workshops, through direct collaboration and by organizing workshops. The research goals center on several broad topics. The first is exploring the three known non-supersymmetric string theories in ten dimensions. The specific goal is investigating the space-time potential energy and understanding the nature of its critical points. This potential is an ingredient in recently constructed models that provide laboratories for exploring holography without supersymmetry. The second set of questions involve supersymmetry in differing ways: the first is to explore more deeply quantum field theories deformed by irrelevant operators. The second is to develop a symbolic computation package that can generate supersymmetric Lagrangians with higher derivative couplings. The third is to study the moduli space of compactified field theory with the aim of computing partition functions via localization. The fourth direction is to finally unravel the complete set of constraints imposed by maximal supersymmetry in field theory and supergravity. The final topic is to connect the program in mathematics to classify Fano four-folds to M-theory AdS flux solutions in three dimensions. 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 2024 · 2024-08

Linguistic communication is a goal-driven process. Very often when humans try to understand a conversation or a piece of text, they ask “what is it about?”. Question under Discussion is a technical term that is used to capture this intuition, reflecting the idea that meaningful linguistic exchange involves structuring discourse context around relevant “issues” or questions. Communication between speakers is successful if conversational partners are cooperative and try to resolve the relevant issues together. Despite the important role QUD plays in linguistic theory, there exists a challenge in systematically evaluating the wide range of potential QUDs within naturalistic real-world discourse. Individual speakers may perceive different issues as relevant, even when presented with the same context, introducing uncertainty on what is the most salient issue. Such uncertainty can lead to miscommunication. The current project aims to develop methodologies to quantify QUD uncertainty in naturalistic discourse, and also investigate how QUD uncertainty impacts language comprehension in general. Four research questions will be addressed: (i) Can the concept of Question under Discussion be effectively quantified and analyzed in naturalistic discourse? (ii) How does QUD-(un)certainty influence people’s allocation of attention during language comprehension? (iii) Does QUD-(un)certainty account for the variation in how people make pragmatic inferences? (iv) Are there cross-linguistic and cross-cultural differences regarding how QUDs arise in contexts and how they impact language comprehension? To pursue these objectives, this project constructs open-access corpora for naturalistic discourse in two languages. Both corpora include rich annotation of QUD information. The second objective of the project is to develop behavioral methods to collect reading time data over the internet, which provides information to draw conclusions about people’s language comprehension behavior. Combining behavioral and computational methods, this project tests several linking hypotheses that connect QUD uncertainty to people’s reading time data, quantifying the effect of QUDs on human language comprehension. 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 · 2024-08

PROJECT SUMMARY Lupus nephritis (LN) is the most common severe manifestation of systemic lupus erythematosus (SLE) Disease progression is associated with tubulointerstitial hypoxia and metabolic dysfunction, capillary rarefaction, accumulation of immune infiltrates and fibrosis. Complete remission rates in patients with LN are <50% (and often <30%) even in the setting of rigorous clinical trials and responses cannot currently be predicted by clinical and histologic features at initial biopsy. We currently have insufficient understanding of why clinical outcomes do not always correlate with histologic changes, why only some patients with interstitial kidney inflammation progress to ESRD, and how to predict responses to therapeutic intervention. We do not know which human in situ disease mechanisms are manifest in which murine LN models. Indeed, murine models have often failed to predict clinical utility in human LN. While no murine model provides a holistic picture of human LN, this would not be expected as the human disease is very heterogeneous. Rather, we propose an overall hypothesis that specific pathogenic human LN immune states are quantitatively replicated in select murine models of lupus nephritis. We will test this hypothesis using innovative high- dimensional confocal microscopy and AI-driven analysis of both human and murine LN tissue. These studies will be complemented by directed mechanistic studies in relevant LN murine models. Specific Aims: Aim 1. To define prognostically important in situ autoimmune states in human LN. We hypothesize that specific in situ immunological architectures, associated with specific CD4- T cell and myeloid cell populations, will define therapy-resistant, progressive renal disease. Aim 2. Quantify in situ T cell states in murine LN models and their relationship to human LN. We hypothesize that in situ T cell architectures implicated in progressive human LN will be approximated in select murine LN models and that these areas reflect sites of pathogenic CD8+ T cell clonal expansion. Aim 3: To quantify in situ myeloid immune states in murine LN models and their relationship to human LN. We hypothesize that in situ myeloid cell architectures implicated in progressive human LN will be identified in mouse models, and that only some myeloid subsets will be associated with tissue injury and fibrosis. This information will inform complementary functional studies in mice.

NIH Research Projects · FY 2025 · 2024-08

Project Summary/Abstract The majority of the PD patients have a long history of constipation before the onset of the motor symptoms of PD. Abnormal gut microbiota (dysbiosis) and its metabolomics have been proposed to play a crucial role in the formation and migration of pathologies found in Parkinson’s disease (PD) – leading to the notion of a “Gut Microbiome-Brain Axis” in the pathogenesis of PD. However, it remains unclear whether the PD-associated gut dysbiosis is a cause or consequence. The goal of the proposed studies is to gain a better understanding of the role of gut dysbiosis in the development, progression, and prognosis of PD, which will lay the foundation for the identification of microbiome-based predictive biomarkers and open opportunities to develop gut microbiome- based targeted interventions to prevent, mitigate and treat different phenotypes or forms of PD at various stages. Our multi-disciplinary team proposes a multi-pronged approach that will include cross-sectional and longitudinal studies of PD patients with different age at the onset, clinical manifestation, and severity of motor and non-motor symptoms. Clinical metadata will be collected along with fecal microbiota samples that will be subjected to functional multi’omic analyses that includes two discovery tools: a supervised metabolomics panel and a novel transfer RNA-based (MSRseq) technology developed by our team that can simultaneously track gut microbial membership and function on different time scales. These measures are important in defining states of gut microbiota health and managing patients with gut dysbiosis back to eubiosis. Our studies will also be unique because of the large Black PD patient population at the University of Chicago (35% here vs < 6% elsewhere) who come from underserved urban communities on the South and West sides of Chicago. So little information is available on Black populations with PD because of disparities in socioeconomic status and health care access. The clinical study design is unique in having both cross-sectional and longitudinal arms and training and validation cohort components, where fecal microbiota and skin and colonoscopic biopsies for α-synuclein will be collected at years 1, 3 and 5 along with clinical metadata that includes PD phenotypes or forms, age at disease onset (early vs usual mid vs late onset), clinical manifestations (tremor dominant vs akinetic rigidity or postural instability and gait disorder form vs the mixed), severity of motor and non-motor symptoms, and race (Black vs White), and age- and sex-matched healthy controls. Machine learning (ML) and artificial intelligence (AI) will be used to identify best performing PD predictive gut microbiota and metabolic biomarkers. To gain additional insights into potential gut microbial drivers and mediators that underpin etiopathogenesis of different PD phenotypes and progression, we will identify PD-promoting microbiota candidates and mediators for which microbiome-based interventions that potentially prevent, mitigate, or treat PD can be developed. The clinical meta-data and multi’omic gut microbiota data will be deposited with the Coordinating and Data Management Center (CDMC) to be available to the broader research community for hypothesis generation and testing.

NSF Awards · FY 2024 · 2024-08

Recent advances in deep reinforcement learning (RL) have shown impressive results across a variety of applications. However, the broader application of RL often faces significant challenges, particularly in real-world scenarios such as robots interacting with the environment or autonomous driving. The challenges in these complex environments are due factors such as the intricacy of the task requirements and/or few opportunities for the system to know the response is correct (i.e., sparse reward functions). Moreover, extensive physical interactions with the environment are costly because they take considerable time and staffing and sometimes even unsafe due to potential physical interactions during exploration. Leveraging the principles of active learning and curriculum RL, the project seeks to enhance the performance of RL systems in completing difficult tasks in complex environments, while optimizing resource allocation and reducing the need for expensive environment interactions. This project intends to fundamentally reshape the RL landscape by developing task and environment representations specifically for active design in RL. More concretely, this project is structured around four interconnected thrusts. First, Active Environment Design for RL (ACED-RL) aims to identify a sequence of auxiliary environments that best facilitate learning in the target environment. Second, active task design for RL seeks to establish a scalable active task selection strategy, allowing the learner to be trained sequentially in these tasks, facilitating RL, and transferring the acquired knowledge to the target problem. Third, active joint task and environment Design combines active task and environment design to generate RL curricula. This approach extends to settings involving multiple agents, accounting for challenges posed by simultaneous learning and non-stationary agent behaviors. Finally, the project will evaluate the proposed approaches across various high-impact machine learning applications, including standard RL benchmarks, autonomous driving, robotic manipulation, and scientific experimental design. 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 · 2024-08

Project Summary/Abstract Imaging cells and tissue labeled with fluorescent molecules and proteins is critical in biological research, enabling visualization of the locations of specific proteins, receptors, or genotypes within cells and tissue. However, our current imaging modalities are not capable of simultaneous functional imaging of molecules/proteins and structural imaging of cellular and subcellular features in whole tissues, limiting both our fundamental biomedical understanding of diseases and strategies for treatment. Leveraging recent advances in the development of photoemission electron microscopy for high-resolution imaging of biological tissue for volume electron microscopy, the proposed research program seeks to develop BRAVE-EM, Biological Real-space Absorption Visualization by photoemission - Electron Microscopy, to combine the wavelength specificity of optical light microscopy with the spatial resolution and volume imaging of electron microscopy. Developing BRAVE-EM will enable imaging of fluorescent molecule and protein labels in biological tissues with spatial resolution <20 nm, while remaining compatible with recent advances in the volume electron microscopy infrastructure. Using volume electron microscopy and BRAVE-EM, we will answer questions in cancer biology, such as how heterogeneity in cancer-associated fibroblasts and variations in protein expression in the tumor stroma of pancreatic tissue samples influences cancer metabolism and disease progression.

NSF Awards · FY 2024 · 2024-08

Non-technical abstract: The next generation of computing systems requires an efficient high-density memory with low power consumption. While magnetic bits are highly common, interconnects between bits are lossy. To reduce energy loss, it is necessary to change the material properties of interconnects. This project studies entirely new types of connections between magnetic bits, specifically by combining superconductors, magnets, and chiral molecules. This combination can create an unusual electronic state that enables near lossless interactions between bits. Such interconnects can then be implanted in the next generation of magnetic classical and quantum logic circuits. The proposed research relies on the proven expertise of three PIs that have overlapping and complementary skill in measurements, device fabrication, and local-probe studies, and who will work in tight coordination to achieve research goals. The proposed work will foster international collaborations and cooperation, particularly for students at all levels. High-school students and teachers will be integrated into the research, graduate students will gain experience in translation and international collaboration, and the PIs will work toward creating and implementing best-practices for greater inclusivity in research, especially considering international perspectives. Technical abstract: The project focuses on studying spin manipulation and control via interactions between chiral molecules (ChMs), ferromagnets, and superconductors, and on the integration of these three components for superconducting-spintronic applications. Spin-selective electron transport is typically associated with the use of magnetized materials, a process that is usually highly dissipative and of low efficiency. A drastically new solution to the problem has emerged from the discovery that ChMs function as spin-filters with surprisingly high efficiency, and thus transport through them is spin-selective. Moreover, recent works from the PIs reveal that adsorbing ChMs on various materials leads to spin manipulation. This project will examine the basic principles of chiral interactions in superconducting-magnetic junctions with the goal of improving interconnects between magnetic bits. This system generates a surface triplet state that may reduce spin phase decoherence. Specific studies will include exploring phase coherence using the Aharonov-Bohm and Josephson effects, monitoring anomalous magnetoresistance in chiral-magnetic structures, and determining chirality-induced spin polarization effects. Using a judiciously selected combination of magnetic and superconducting materials over which ChMs will be adsorbed, the research will lead to a deeper fundamental and practical understanding of hybrid magnetic superconducting chiral systems, thus enabling one to manipulate, transfer and exploit magnetic information in these systems. The proposed research relies on the proven expertise of three PIs that have overlapping and complementary skills in transport measurements, chiral-spintronics device fabrication, and local-probe techniques, and who will work in close coordination to achieve research goals. 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 · 2024-08

ABSTRACT/SUMMARY The Center for Cellular Adaptation is an interdisciplinary team comprised of biologists, physicists, and data scientists embarking a comprehensive project to develop a multiscale, predictive understanding of how cells adapt to changes in their environment. This research could potentially lead to innovative, holistic therapeutic interventions for a range of diseases that reprogram maladaptive cellular states. The project is divided into three main scientific thrusts, each exploring different timescales of cellular adaptation. The first thrust aims to understand the adaptive roles of stress-induced biomolecular condensates in physiological adaptation. Membrane-free assemblies of macromolecules induced during stress were previously thought to be toxic but are now known at least in some cases to be adaptive assemblies with physical properties shaped by evolution. By studying condensates in diverse environmental contexts, we aim to link the properties of these condensates to cellular function and fitness. The second thrust seeks to understand how cells prioritize environmental responses at the transcriptomic level. Cells typically respond to single environmental stressors by repressing growth-related genes and activating stress-specific genes. However, it is unknown how cells respond in complex environments with multiple stressors. We will generate single-cell transcriptomes from yeast and pancreatic cancer cells under a wide range of environmental conditions to understand how cells prioritize – and how malignant cancer reprioritize – environmental signals. The third thrust will explore the relationship between physiological and evolutionary adaptation, aiming to understand how stress responses contribute to evolutionary adaptation. We will use CRISPRi screening coupled to single cell transcriptomics (Perturb-seq) to test the hypothesis that the effects of genetic mutations on the transcriptome will be similar to the effects of environmental perturbations. We will also identify novel phenotypic capacitors that promote genetic diversity in cell populations to enable long-term adaptation. The challenging nature of these research goals necessitates the diverse collaboration of expertise involved in The Center for Cellular Adaptation. Our highly collaborative research model will be coordinated by regular monthly meetings involving all Center PIs, collaborators, and trainees to discuss ongoing research. Additionally, the PIs will meet monthly to evaluate progress as well as elicit feedback from an advisory board of experts on an annual basis. This integrated, multi-scale approach to understanding cells may provide a novel unified framework connecting adaptive processes across timescales and the maladaptive processes that culminate in aging, cancer, and neurodegeneration.

NSF Awards · FY 2024 · 2024-08

This Award will fund a research project that will study the long-term effects of comprehensive support for Community college students from low-income backgrounds. Although Community colleges have the potential to be powerful vehicles for economic mobility, most students who enroll in community colleges do not earn a degree within three years. While research shows that providing holistic support focused on the social, academic, financial, and professional needs of students dramatically improve associate’s degree completion, there is little evidence on the long-term effects of these programs on students’ education and employment outcomes. This research project will combine data from participants in the One Million Degree (OMD) project, a Chicago area project that provides comprehensive support to community college students, with several administrative data set for the study. Outcomes of interest include community college graduation, graduation from four-year college, employment and wages, and contact with the criminal justice system. The researchers will also provide the first comprehensive cost-benefit analysis of such programs. The results of this research project will provide inputs into policies to improve outcomes for community college students. The results will also be helpful to college administrators as well as increase community college graduation, education, increase human capital formation, economic growth, income, and economic mobility. This Award will fund a project to study the the long-term effects of a holistic support program--- One Million Degrees (OMD), a Chicago area organization that provides comprehensive support for community college students. The project builds on a randomized controlled trial (RCT) that finds a short-term positive effect of this support. The project will link data from the original RCT study sample to administrative data on employment status, wages, longer term associate’s degree completion, transfer to four-year colleges, and bachelor's degree attainment, to track the long-term outcomes of the participants in the OMD program. In addition, the PIs will conduct a comprehensive cost-effectiveness analysis to understand the cost of the improved outcomes that result from program participation. This research results will provide essential information to policy makers and practitioners about the benefits of investing in holistic support programs for community college students. In addition to helping to increase human capital formation, the results could also provide inputs into policies to reduce educational and economic inequalities in the United States. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NIH Research Projects · FY 2026 · 2024-08

Recently, as part of the enhancing Genotype Tissue-Expression (eGTEx) project, methylome data on subsets of GTEx samples (N=987) from nine tissue types of 424 subjects have been generated by co-I Pierce’s lab to complement existing expression quantitative trait locus (eQTL) data. As part of eGTEx, our group conducted the standard methylation QTL (mQTL) mapping for each of the nine tissues and multi-tissue mQTL analysis using existing methods. The challenges in our mQTL analyses motivates the development of the methods in our first aim. In Aim 1, we propose to develop methods for integrative QTL mapping, integrating multi-tissue mQTL with multi-tissue eQTL statistics to improve the detection of QTLs with co-occurring effects in related tissues and/or omics data types. In addition, we propose to extend the method to map multi-cell-type single-cell eQTLs by integrating bulk-tissue QTL statistics with cell-type-specific QTL statistics. In Aim 2, we propose to develop multivariable Mendelian randomization (MR) methods for mapping risk genes accounting for confounding from DNA methylation. We illustrate that existing MR methods proposed for complex trait exposures insufficiently address challenges in studying gene expression as exposure, due to violations of instrumental variable assumptions. We propose to develop MR methods for modeling multi-tissue expression levels as exposure adjusting for multi-tissue methylation, leveraging multi-tissue eQTL and mQTL statistics to improve effect consistency of instrumental variables. In Aim 3, we will analyze GTEx and sc-eQTLGen data for QTL analyses, will apply the proposed MR methods to map risk genes for complex diseases and traits with a focus on cardiovascular diseases and Alzheimer’s disease, and will conduct replication and validation analysis. We will develop efficient and scalable software. Our application highlights the importance of jointly examining multi-omics traits from multiple cellular contexts in studying genetic regulatory mechanisms underlying susceptibility to complex traits and diseases.

NIH Research Projects · FY 2025 · 2024-08

PROJECT SUMMARY The intricate orchestration of genetic and epigenetic dynamics in neurobiological systems plays a central role in substance use disorders (SUDs), with cocaine use constituting a significant public health concern. This project employs a cutting-edge, interdisciplinary approach to elucidate the epigenetic landscapes and gene regulatory networks activated following cocaine self-administration in a mouse model, as well as to understand how epigenetic variations influence these processes. The project comprises three core objectives at the intersection of genomics, epigenomics, neuroscience, and computational biology. First, we will conduct high-resolution chromatin accessibility and DNA methylation profiling to delineate cell-type and circuit-specific epigenetic configurations post-cocaine self-administration in mice. This analysis aims to uncover granular alterations in the epigenome, illuminating the regulatory pathways implicated in cocaine-induced neural plasticity and behavioral adaptations. Second, we will leverage the Hybrid Mouse Diversity Panel (HMDP), comprising approximately 100 different strains of mice, to investigate variances in epigenetic regulation. Utilizing the HMDP as a mechanistic intermediary, we aim to identify epigenetic variations underlying strain-specific susceptibilities and resistances to cocaine exposure, thus deepening our understanding of the genetic and epigenetic factors associated with cocaine self-administration. Lastly, we will construct cell-type and circuit-specific gene regulatory networks that encapsulate the interplay of genetic and epigenetic factors. These networks will be established through rigorous computational analyses that integrate genomic, epigenomic, and transcriptomic data. In summary, this project aims not only to detail regulatory dynamics but also to identify key nodes and pathways for potential therapeutic intervention, representing a significant stride towards alleviating the global burden of cocaine use disorder. The work pushes the boundaries of current epigenetic studies in SUDs by employing a multidimensional approach to unravel the complex genetic and epigenetic landscapes governing cocaine response. The outcomes are expected to fundamentally enhance our understanding and present unprecedented avenues for therapeutic innovation.

NIH Research Projects · FY 2025 · 2024-08

PROJECT SUMMARY Transcription factors (TFs) are master regulators of gene expression and have been implicated in many disease states, including in cancer. Of these, the basic helix-loop-helix (bHLH) MYC TF family members are notorious drivers of oncogenic expression programs and are implicated in approximately 70% of all cancers. TFs influence gene expression by binding to their cognate DNA sequences and recruiting the appropriate transcriptional machinery to activate or inhibit gene expression. Although TFs are well-validated targets for cancer therapeutics, the featureless nature of the protein-protein and protein-DNA interactions required for their function is resistant to traditional drug development pipelines. Indeed, some small molecule inhibitors of bHLH-TF proteins have been reported, but their low potency and unclear mechanism of action have stalled their translation into clinical use. To address this challenge, we have developed a platform of fully synthetic, modular TF mimetics. Our approach employs strategic chemical stabilization of peptide secondary, tertiary and quaternary structure to yield synthetic transcriptional repressors (STRs) capable of binding target DNA sequences with high affinity and specificity. The initial class of STRs, derived from the bHLH protein MAX, inhibit MYC/MAX-DNA binding and block MYC-driven oncogenic phenotypes in cells. Building upon these preliminary data, this proposal aims to explore and expand into novel STR architectures and validate lead STRs capable of opposing oncogenic gene expression programs and phenotypes in animal models of MYC-driven cancers. Our expertise in synthetic chemistry and biochemical profiling of TF function, as well as our established collaborations with leaders in the fields of epigenetic and transcriptomic profiling and in vivo imaging, will be leveraged in the service of the following specific aims: 1) structural and biochemical optimization of hyperstable and ultrapotent STRs targeting MYC, 2) enhancing cellular and pharmacologic delivery of STRs coupled with quantitative mapping of STR- reprogramming of epigenetic and transcriptomic landscapes in MYC-dependent cancer cells, and 3) evaluation of lead STRs in in vivo models of both MYC-dependent solid tumors (neuroblastoma) and liquid cancers (lymphoma). Successful completion of these aims will generate potent, specific, and pharmacologically tenable STRs and prioritize them for further study as MYC-targeted therapeutics. Beyond this direct goal, this work will provide new insight into MYC-mediated gene regulation in cancer and establish a blueprint for the development of STRs targeting other TF-dependent gene expression networks in the future.

NIH Research Projects · FY 2025 · 2024-08

Project Summary/Abstract The aging of the population in industrialized nations is increasing the number of ischemic strokes that present in the emergency rooms of hospitals. In the ischemic stroke neurons die rapidly (estimated at 1 million neurons per minute) prompting the need for rapid triage and treatment to open the blocked blood vessel. We have previously established that the exact rate at which neurons die and size of the infarction grows is highly variable among patients and depends strongly on the degree of leptomeningeal arterial collateralization. The goal of this proposal is to test a new biopharmaceutical agent (Sanguinate®) that is designed to boost the collateralization in ischemic stroke as well as deliver and release oxygen locally in tissue with low oxygen tension. We believe that this approach will reduce infarct volume in all strokes and reduce reperfusion injury in those successfully recanalized by during interventional procedures. Sanguinate® is an investigational bio-pharmaceutical blood substitute that facilitates the transfer of oxygen to oxygen-deprived cells and tissues. Sanguinate’s unique oxygen-delivery system has the potential to treat hypoxia/ischemia. Sanguinate® is purified bovine hemoglobin that has been pegylated and combined with carbon monoxide to suppress vasoconstriction and provide anti-inflammatory effects. The bovine hemoglobin then carries oxygen for targeted release to areas with a low partial pressure of oxygen (ischemic tissue). It has been shown to successfully address detrimental vasoconstrictive side effects associated with older generation artificial blood products, but the effect on tissue perfusion, infarct volumes, infarct growth and tissue hypoxia and have not been directly measured. The rationale for this work is that brain infarcts grow rapidly if a blood vessel feeding the brain is blocked and even with the most efficient triage and shortest door-to-needle time, millions of neurons will die. There is an unmet need for an easy, safe i.v. infusion that can stop to growth of an infract and unlike thrombolytic agents, be safely administered to all patients as soon as symptoms arise. We will establish the effectiveness of a new pharmaceutical that can be easily deployed in emergency rooms, ambulances and satellite hospitals prior to transfer to a stroke center comparing doses and time-to-treatment effect with serial imaging a biomarkers of brain damage and inflammation in a controlled model of ischemic stroke. Our findings will elucidate the mechanism of action of the agent and inform the design of future human clinical trials.

NSF Awards · FY 2024 · 2024-08

During the past several decades, linguists and psychologists have discovered dozens of new languages emerging in communities around the world, offering unprecedented scientific opportunities to address important questions, previously deemed intractable, about where language comes from and how it can be structured in new and surprising ways. Since the 1960s, studying signed languages has generated deeper understandings of the core properties of language and how those properties can be realized in the visual-manual modality. This project builds on that work to ask how language can emerge and grow in the tactile modality. The researchers are asking this question in an historically unprecedented time when some DeafBlind communities are communicating via reciprocal, tactile channels. They call this practice and the language emerging from it, "Protactile," or "PT." Previous research demonstrated that PT communication triggered systemic changes in "sub-lexical structure," which is the level of language that supplies the basic units needed to create words and phrases and the rules that determine how those units can be combined. This was precipitated by a shift from "air space" (on and around the body of the signer), to "contact space," (on the body of the addressee). This change led to new phonological units and a conventionalized system for coordinating the four articulators of speaker and addressee to make combinations of those units possible in complex constructions, which are used to express spatial relations and direction. This project asks how those mechanisms and structures are being used to build words in the core lexicon, or the highly conventionalized words one would expect to find in a dictionary. 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 · 2024-08

We propose to develop a new microscope for connectomes with the potential to reduce the price of a connectomic voxel by order(s) of magnitude. We will focus on a relatively unexplored type of EM microcopy based on excitation of photoelectrons by UV light and their detection with standard widefield EM optics (PEEM). Simply, PEEMs for connectomes can combine the reliability of SEM imaging with the thruput of TEM imaging. We have demonstrated for the first time that PEEMs can see synapse and we have designed a tailored PEEM microscope with strong UV excitation from lasers and direct EM detectors that can work at Gigahertz imaging rates. We will explore collecting 1000s of ultra-thin brain slices (UTBS) using two state of the art automated approaches, the ATUM and Mag-C. We will optimize this pipeline, extending our current sample preparation to support such imaging rates, adding Gas Cluster Ion milling to improve the Z-resolution of PEEM connectomes, and, by designing, developing, and integrating a new generation of fast stages that keep up with imaging rates. Finally, we will instantiate auto- acquisition and quality assurance algorithms, e.g., auto-focus, auto-sigmate, etc. to facilitate the imaging and collection of 1000s of ultrathin brain sections. We provide clear metrics for success and achieving those milestones, we argue, could revolutionize how EM conenctomes are made.

NIH Research Projects · FY 2025 · 2024-08

Project Summary In cardiovascular disease diagnosis, treatment, and monitoring, a plethora of deformable biointerface devices are utilized. These devices are adept at gauging physiological metrics, administering bioelectrical modulation, or dispensing therapeutics. Notwithstanding the advent of preclinical biotechnologies like optogenetics and cell-based biological pacing, non-genetic electronic pacing persists as the predominant therapeutic approach for cardiac rhythm anomalies. Recently, semiconductors have been identified as promising instruments for non-genetic cardiovascular investigations. Our team is focusing on designing minimally invasive photostimulation tools specifically tailored for cardiac pacing applications. We recently published several photoelectrochemical methods for optically modulating cardiac activity in cultured cells and adult rodent models ex vivo. Using these methods, we can achieve light-activated modulation of cardiac tissue with a light intensity comparable to that used in optogenetics. In this current work, Tian, Hibino, Jia and Aziz will work together to expand and strengthen our newest photostimulation system, porosity-based silicon heterojunctions, for multi-site, leadless, nongenetic, and optoelectronic modulation of cardiac tissues. Specifically, our team aims to design, fabricate, and evaluate a range of porosity-based heterojunctions tailored for optical modulation of cardiac tissues. We will synthesize silicon membranes with non- porous/nanoporous heterojunctions and three-dimensional surface topographies. To enhance the stability of these heterojunctions and modulate their longevity under physiological conditions, we will employ atomic layer deposition to passivate the silicon interfaces. We plan to modify the surface with metal or metal-oxide catalysts to bolster signal transduction. To support the silicon heterojunctions, we will integrate soft matrices, including polymers and hydrogels, enhancing both biocompatibility and signal transduction at biointerfaces. Concurrently, we will produce biocompatible, stretchable optical fibers tailored for in vivo photostimulation. Our team is also developing a catheter-analogous minimally invasive photostimulation tool. For multi-site optical pacing, we will engineer and assess the requisite software, mechanical, electrical, and optical subsystems. We will validate the performance metrics of our random access photostimulation tools, including accuracy, scanning velocity, and power delivery, followed by ex vivo photostimulation trials. In vivo biocompatibility assessments will be conducted in a rat model, while we will gauge heart pacing efficacy in acute and chronic scenarios using single-chamber, dual-chamber, and multi-site stimulations in a pig model. We will test our hypothesis that deformable and biocompatible heterojunction devices can be used for multi-site cardiac resynchronization therapy. The new designs for semiconductor-based biointerfaces will allow for minimally-invasive, wireless, nongenetic, multiscale, and random access photostimulation.