Northwestern University

NSF Awards · FY 2025 · 2025-04

This project is a renewal of the REU site at the Center for Interdisciplinary Exploration and Research in Astrophysics (CIERA) at Northwestern University (NU). The REU program will support ten undergraduate students per year and the RET program will support four teachers per year. Mentors come from four departments: Physics & Astronomy, Earth & Planetary Science, Engineering Sciences & Applied Mathematics, and Electrical & Computer Engineering. The proposed projects are centered on research methods in astrophysics, included theory, computation, instrumentation, and experiments. Students will have access to the high-performance computing facility at Northwestern, instruments at Fermilab, and a variety of astronomical telescopes. REU students will learn how astrophysical studies prepare them with a wide range of skills and can lead them to a variety of professional paths. The CIERA REU site gives students the experience of doing interdisciplinary astrophysical research, exposes them to a wide array of exciting research areas in astrophysics, and builds a community among the students and NU researchers. RET participants also carry out authentic astrophysics research, learn about cutting edge science, and work with experts from NU's Baxter Center for Science Education to turn their experience into high school curricular materials. The CIERA RET program has the potential to reach hundreds of students each year through these curricular activities. The REU program recruits a significant fraction of its participants from Chicago area undergraduate institutions, and the RET program recruits teachers from the Chicagoland high schools, in particular the Chicago Public School District’s 157 high schools, and more than 100,000 high school students. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NIH Research Projects · FY 2026 · 2025-04

Abstract Prostate cancer is one of the most common cancers among men, and although it can successfully be treated in some men, others develop resistance to therapies and can relapse. Thus, it is prudent to discover new therapeutic targets and develop therapeutic strategies that utilize already developed therapies to expedite the development of new treatment options for prostate cancer patients. Prostate cancer can be caused at genetic and epigenetic levels. Not only do epigenetic modifications include unwinding of genes (i.e., DNA) so they can be expressed as RNA, but this epigenetic regulation can also edit RNA. One epigenetic modifier is protein enzyme enhancer of zest homolog 2 (EZH2) that normally modifies the histone H3K27, thereby, tightly winding DNA and silencing gene expression. Our previous work showed that EZH2 is upregulated in advanced prostate carcinomas and metastatic prostate cancer, and prostate cancer patients who have higher expression levels of EZH2 have shorter survival times than prostate cancer patients with low or no expression of EZH2. Surprisingly, we recently discovered that dysregulation of EZH2 alters N6-methyladenosine (m6A), which is totally different from its well-known canonical function as a histone lysine methyltransferase. mRNA methylation can affect the stability of RNA and induce alternative splicing of mRNA, which will alter important regulation of the RNA and protein translation fidelity. These aberrant effects on RNA by alterations in RNA modifications are associated with cancer, in particular, prostate cancer. Therefore, investigating this novel EZH2 non-canonical function in N6-methyladenosine will help us better understand the progression of advanced prostate cancer. Although the development of EZH2 inhibitors has been an active area of investigation and multiple biotech and pharmaceutical companies have been developing such drugs, EZH2 inhibitors alone have not been proven effective in most solid cancers. Thus, identifying new therapeutics targets will lead to the development of new drugs that can be combined with already developed drugs, hence, expediting the development of new treatment options for cancer. Our data show, for the first time, that EZH2 enhances global m6A modification levels via activating m6A reader YTHDF1, enhancing m6A writers METTL14/WTAP protein synthesis, and inducing tumor suppressor mRNA degradation. Most advanced prostate cancer cells have higher expression levels of EZH2 and m6A compared to those in benign prostate epithelial cells and early-stage prostate cancer cells, suggesting the importance of EZH2 and m6A in prostate cancer progression. In the proposed project, we will precisely identify how EZH2 regulates m6A via its non- canonical role in prostate cancer. Understanding these mechanisms will lead to the future design of new inhibitors of EZH2 and m6A writers/readers. Therefore, our work provides a novel rationale to target both METTL3 and EZH2, and we predict that the inhibition of both m6A and EZH2 will achieve a better therapeutic efficacy than inhibiting either m6A or EZH2 alone.

NIH Research Projects · FY 2026 · 2025-04

PROJECT SUMMARY/ABSTRACT School-based health centers (SBHCs) aim to improve child and adolescent health by providing health care at schools. SBHCs have become increasingly widespread in recent decades, with over 2,500 SBHCs serving more than 6 million students. While existing research finds that SBHCs are positively correlated with health care use and contemporaneous educational outcomes, differences between students at schools with and without SBHCs may confound these estimates. Moreover, while a large literature shows that childhood health has lasting impacts on later adult health, human capital, and economic outcomes, surprisingly little is known about the impacts of SBHCs on students’ long-run trajectories. This project aims to advance knowledge on these issues by using difference-in-difference models to measure the causal effects of SBHCs on students’ health care utilization and their short- and long-term behavioral, educational, and economic outcomes. The project will examine the effects of SBHCs on the provision of psychotropic medications for school-aged youth using 13 years of data covering the near universe of antidepressant, anti-anxiety, and antipsychotic prescriptions across the entire US linked with information on the openings of over 1,800 SBHCs. The project will also consider impacts on youth health care use more generally using nearly a decade of administrative Medicaid claims data covering the entire US. The project will further estimate the effects of SBHCs on a range of student outcomes—including attendance, disciplinary actions, high school graduation, college enrollment/graduation, and adult employment and earnings—using 26 years of administrative data on all public school students in Texas linked with information on the openings of 54 SBHCs. For student-level outcomes observed before and after an SBHC opening, the analysis will compare the before/after change in outcomes of students at schools that experienced an SBHC opening relative to the before/after change over the same period for students at matched control schools without SBHCs. The analysis of prescription and other health care outcomes will follow a similar design, comparing before/after changes in outcomes in areas surrounding schools following an SBHC opening relative to the before/after change over the same period in areas either slightly further away from the treated school or in areas near matched control schools. For long-term student-level outcomes only observed post-exposure, the analysis will compare outcomes among students enrolled in schools at the time of the SBHC opening to those who already aged out of the school relative to the difference between these cohorts at matched control schools. The project will identify groups of students that are most affected by SBHC access by conducting subgroup analyses by student characteristics such as race/ethnicity and socioeconomic background. The project will also conduct separate analyses by service offerings and staffing patterns to compare effects by SBHC characteristics. Results will help policymakers, schools, health care providers, and parents understand the impacts of SBHCs on youth, thereby helping inform discussions about further expansions of such centers across the US.

NIH Research Projects · FY 2026 · 2025-04

PROJECT SUMMARY/ ABSTRACT REM sleep is accompanied by dreams characterized by vivid visual experience, which evidently indicates that our brain holds a generative model of the world. Converging studies suggest that we perceive the world through such a generative model and the abnormal expression of the model could underlie some psychiatric disorders. Thus, it is important to understand how our brain supports the generative model. The goal of this project is to elucidate the neurophysiological basis for the generative model by focusing on the neuronal activity during REM sleep, during which the brain’s generative model is detached from the external world. In the mentored phase of the award, I first propose to investigate rapid eye movements as a readout of the generative model during REM sleep. Rapid eye movements during REM sleep are proposed to represent active sampling of the virtual visual environment of dreams. However, this hypothesis is poorly supported by physiological evidence. To provide physiological evidence to test the hypothesis, I will focus on the activity of the head direction (HD) cells, which code for the animals’ HD relative to the environment. The activity pattern of HD cells during REM sleep is similar to what is observed during wake. This makes it possible to decode virtual HD during REM sleep. I will test whether rapid eye movements during REM sleep can predict changes in HD decoded from HD cells recorded in the anterodorsal thalamus. To achieve this goal, I will combine large scale electrophysiological recordings, advanced decoding methods, and miniaturized eye tracking systems. In the R00 phase, I propose to investigate the superior colliculus (SC) as the neuronal substrate for virtual head orienting and rapid eye movements during REM sleep. The SC is an important hub for head and eye orienting in awake animals. I will test whether spontaneous activity in the SC during REM sleep predicts changes in virtual HD by simultaneously recording neuronal activity in the SC and in the anterodorsal thalamus as well as monitoring rapid eye movements. I will further test the causal impact of the SC activity on virtual head orienting and rapid eye movements by activating and inactivating the SC during REM sleep. In summary, this project will provide new insights into the neurophysiological understanding of how the generative model of the world and our interaction with it is organized during REM sleep. This will constitute the critical step to understand how we see the world through the internal model and how the abnormal expression of the model could underlie the pathogenesis of some psychiatric disorders such as schizophrenia. The technical and scientific expertise that I will acquire during the training period of the award will be crucial for setting the basis of research programs in my own independent laboratory focusing on the role of the SC in orchestrating the generative model during REM sleep. In addition to this, intense career development training, the guidance from the mentoring team, as well as the collaboration and the rich intellectual interaction in the UCSF neuroscience community will ensure my successful transition into an independent investigator.

NIH Research Projects · FY 2026 · 2025-04

Project Summary The electron transport chain (ETC) is central to cellular metabolism, facilitating ATP synthesis through the establishment of an electromotive proton gradient across the inner mitochondrial membrane. Pioneering work in mitochondrial biology has revealed an additional role for the ETC in cellular signaling, both through the generation of reactive oxygen species (ROS) and through modulation of epigenetic and post-translational modifying enzyme activity by TCA cycle metabolites. While considerable effort has been made towards characterizing the effects of ETC dysfunction in tumorigenesis and human disorders of central metabolism, the role of individual ETC complexes during tissue morphogenesis remains largely unknown. Though previous work by our lab has shown that epidermal loss of ETC Complex III results in embryonic lethality and severe barrier defects through impaired epidermal differentiation, whether this defect reflects a requirement for Complex III activity, or a specific dependency on Complex I or II remains unclear. To answer this question, we have generated two novel mouse models with epithelial-specific deletions of Ndufs2, a critical Complex I component, and Sdhd, a crucial subunit of Complex II. Intriguingly, our preliminary data has shown that Ndufs2 is largely dispensable for normal hair and skin development, while Sdhd deletion results in numerous morphological defects, comprising a patchy hair coat, bumpy, lesioned skin, keratin plugging of the hair canal, and the expansion of infundibular and sebaceous gland populations. Loss of Sdhd is associated with an increase in Myc expression within the hair follicle, suggesting that these malformations are driven by an abnormal Myc-driven transit amplifying program within the upper hair follicle and sebaceous gland. These results contrast with a recent study by our collaborator, Navdeep Chandel, which showed that Complex I, but not Complex II, was essential for normal lung development, suggesting that individual respiratory complexes regulate epithelial development in a lineage-specific manner. I hypothesize that loss of a functional Complex II drives alterations in transcriptional programs, chromatin state, and gene expression via inhibition of a- ketoglutarate-dependent epigenetic modifiers, resulting in compromised epithelial stem cell fate specification, lineage formation, and differentiation. Here, I propose to (1) determine the function of Complex II in epidermal fate specification and skin morphogenesis and (2) investigate the mechanisms through which Complex II controls the epithelial cell transcriptome. Experiments proposed in Aim 1 will focus on conducting a comprehensive phenotypic, transcriptomic, and metabolomic analysis of Sdhd cKO mice. Aim 2 focuses on the analysis of epigenetic perturbations induced by loss of Complex II function through Cut&Run sequencing as well as single cell multiomic identification of candidate transcriptional regulators driving the response to Sdhd deletion in epidermal lineages. My results will provide important new insights into the role of the ETC in tissue morphogenesis, with implications for the study of tumorigenesis, stem cell biology, and aging.

NSF Awards · FY 2025 · 2025-04

Organisms often face life-and-death decisions under time pressure, such as adapting to sudden environmental changes or evading predators. Understanding how organisms make accurate, time-sensitive decisions with incomplete information is critical to determine how they process and respond to environmental signals. This project focuses on understanding how the bacterial pathogen Salmonella Typhimurium makes time-sensitive decisions when engulfed by immune cells. Using quantitative approaches to track decision-making in single bacteria in real-time, this research investigates how Salmonella balances speed and accuracy to survive the hostile environment of an immune cell. Understanding how bacteria make life-and-death decisions in this environment could lay the groundwork to disrupt bacterial decision-making as a means to treat disease. This project will generate fundamental new knowledge about cellular decision-making, with potential applications in synthetic biology, such as designing bacteria for sustainable agriculture, pollution cleanup, and disease diagnosis. The interdisciplinary educational component introduces high school students to cutting-edge artificial intelligence (AI) techniques through a hands-on curriculum integrating biology, coding, and imaging. When engulfed by a macrophage, Salmonella must rapidly adapt to the phagosome environment and activate virulence genes to survive. Activation of virulence genes is time-sensitive, as the host is actively attempting to neutralize the bacteria. However, phagosomal stimuli appear gradually and heterogeneously, making it challenging for the bacteria to rapidly classify this new environment. This project investigates how Salmonella use contextual cues for rapid and accurate decision-making in the intracellular environment. By combining microfluidics and live-cell imaging, this project tracks virulence responses at the single-cell level to determine how contextual cues impact the accuracy of the response. This research will position us to predict and perturb bacterial decision-making in the phagosome while also uncovering general principles about how cells balance the need for speed with accuracy when adapting to new environments. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NIH Research Projects · FY 2026 · 2025-04

Project Summary Adoptively transferred natural killer (ATNK) cells have an established and likely growing role for the treatment of hematologic malignancies, particularly in the context of hematopoietic stem cell transplants. However, despite a growing understanding of the critical role these cells play in the immune response against solid tumors, multiple trials have failed to translate these findings to the clinic. One major reason for this disconnect may relate to the immune suppressive tumor microenvironment (TME). In our published studies, we have demonstrated that antibody B10G5 targeting the MHC I chain related molecule (MIC) that is broadly expressed by human solid tumors can significantly modulate TME, re-invigorating CD8 T cell activity, reviving, activating, and sustaining circulating NK cells. Our anti-MIC antibody serves as a partial agonist antibody that captures the immune suppressive sMIC secreted by tumors, to form an agonist for the NKG2D receptor to upregulate the key signaling molecule CD3z to enable NK cells better function through ADCC and NCRs. We also reported that B10G5 can increase the high affinity enable IL-2Ra expression on NK cells, and sensitize them to low doses of IL-2 in the TME. However, development and optimization of combination therapy with this antibody is challenging with current pre-clinical models as there are numerous differences between murine and human NK cells. Most importantly for our purposes is that the MIC gene is not present in mice. Although our group developed a MIC expressing murine models to overcome this, its power is limited in addressing questions related to NK cell combination therapies. To better model adoptive NK therapy, we have been studying canine soft tissue sarcomas (STS) in client-owned (pet) dogs as predictive models for human undifferentiated pleomorphic sarcoma (UPS) which is the human STS subtype most analogous to canine STS. We developed reliable protocols for generating canine NK cell products at therapeutic doses, from various sources, using procedures appropriate for the veterinary clinic and mirroring those used for humans. The Specific Aims are: Aim 1: To determine the safe and effective dose of B10G5 in activating endogenous NK cells infiltrating canine STS and reshaping the TME. We hypothesize that B10G5 will activate infiltrating NK cells, and possible CD8T cells, reshaping the STS tumor immune microenvironment for tumor control. Aim 2: To optimize the adoptive transfer of NK cells for STS. We hypothesize LD chemotherapy will promote persistence and proliferation of both allogeneic and autologous NK product. Aim 3: To determine if B10G5 will act synergistically with ATNK. We hypothesize that B10G5 will enable adoptively transferred NK cells to effectively eliminate canine STS.

NSF Awards · FY 2025 · 2025-04

NON-TECHNICAL SUMMARY This award supports research aimed at improving our understanding of ion transport in spatially-confined, electrically-charged environments. Living organisms employ ions to transmit sensory signals, store information in memory, and convert chemical energy into work. These functionalities often involve ions in confined aqueous environments. In biological systems, ion transport occurs through channels, proteins, and membranes, where the confined geometries enable enhanced responsiveness to stimuli. Within cellular environments, these stimuli are self-generated by changes in local ionic and molecular compositions. The team hypothesizes that the response of ions to external stimuli in artificial channels and synthetic confined morphologies can be used to emulate neuronal functions, such as information signaling and processing. To explore this, they aim to investigate the mechanisms by which information and energy are transferred via ionic structural changes and motion in confined environments. Ionic motion in solutions is typically driven externally by electric fields (electro-osmosis) or ionic concentration gradients (ionic diffusion-osmosis) and is strongly influenced by geometry and surface properties. Surface-induced electro-osmosis and ionic diffusion-osmosis occur when electric fields or gradients are self-generated due to non-uniform surface properties. These properties include spatially varying chemical activity, ion fluxes, and structural asymmetries, such as irregular charge distributions or asymmetric geometries. The supported research will focus on developing theoretical, numerical, and computational approaches to design and analyze both externally driven and surface-induced ionic flows in confined systems, with an emphasis on understanding the roles of surface and geometric effects. The goal will be to uncover the mechanisms underlying ionic signaling to enable the design of ionic systems capable of storing and transferring information, mimicking brain-like functionalities. This research has the potential to lay the foundation for the development of ionic machines—soft, adaptive materials that encode and process information using ionic currents. Additionally, the team is committed to educating students and postdocs in this emerging interdisciplinary field, which has immense technological relevance and promises to drive innovations in futuristic applications. TECHNICAL SUMMARY This award supports research aimed at improving our understanding of ion transport in spatially-confined, electrically-charged environments. The team will attempt to design biomimetic materials that perform information and energy transference in nanochannels using ions as charge carriers. They will develop molecular simulations and continuum theory to determine the relationship between memory effects and ionic microstructures in the transport of ions. They will employ classification schemes to assess the system's ionic clustering conditions, topology, and time evolution required to produce non-linear and time-dependent ionic conductivities. These features are essential to create memory effects. The team will also explore the mechanisms to modify ionic conductivity in nanochannels by considering polarizable surfaces of various geometries and the impact of direct and time-dependent biasing electric fields. There are currently no efficient computational methods to address surface polarization effects on strong confinement by topologies other than flat. To develop ionic signals' information transference and processing paradigms, the team will develop computational methods to investigate ionic currents at pore boundaries and non-symmetric structures. They will also develop analytical models and numerical methods to analyze the combined effect of ionic fluxes with charge patterns in surface-induced electro-osmosis and ionic diffusion-osmosis. The supported research will answer fundamental questions about information transference, signaling, and key biophysical processes. It will provide a physical understanding of molecular interactions in nano- and micro-sized confinement of charge-containing systems. In doing so, it will aid the design of new materials for various applications, including water desalination, ion separation, and blue energy harvesting. This award will impact diverse fields, including biology, neuroscience, and materials science, by employing the results of the supported research to interpret experimental measurements and design new functionalities. The results of all studies will be published in peer-reviewed journals, and the ream will develop open-source computational codes to assist researchers working on related theoretical and computational problems. The award will also enable training of students and postdocs in a highly interdisciplinary area of research. The participating students and postdoctoral researchers will acquire knowledge in several disciplines, including statistical mechanics, electrostatics, fluid mechanics, and thermodynamics. In addition, the students will learn and develop numerical techniques, molecular simulation methods, and different computational skills, including high-performance computing techniques and programming languages. Overall, students and postdocs will receive training to pursue a career in diverse fields, including environmental science, biotechnology, informatics, computer science, and materials science. The team will support undergraduate students via post-baccalaureate positions as summer internships or during the academic year in the local colleges to help them gain knowledge of research in iontronics, an emerging field that employs ionic flows to design ionic machines that perform advanced functionalities. STATEMENT OF MERIT REVIEW This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NIH Research Projects · FY 2026 · 2025-04

PROJECT SUMMARY/ABSTRACT Dopamine dysfunction is implicated in a wide range of neuropsychiatric diseases, but how changes in dopamine signaling modulate downstream neural circuits to cause the symptoms of these diseases is not well understood. Using in vivo imaging, we have determined how excess dopamine changes activity in D1 and D2 dopamine receptor-expressing spiny projection neurons (SPNs) in the dorsal striatum (Yun et al., Nat Neurosci, 2023). In parallel, we developed a genetic approach to selectively activate the substantia nigra pars compacta (SNc) dopamine neurons that innervate the dorsal striatum (Moya et al, Neuropsychopharmacology 2023). This proposal combines these approaches and their insights to inform our understanding of dopamine-associated diseases and therapeutic strategies for treating them. Specifically, we have shown that selectively activating SNc dopamine neurons in mice disrupts spatial working memory and misconstrues perception in an assay of auditory perception confidence. These findings are relevant to dopamine-associated diseases with deficits in cognition and perception such as schizophrenia. To determine the neural substrates underlying these symptoms, we will use miniature microscopes to image calcium activity in D1 and D2 dopamine receptor-expressing spiny projection neurons (SPNs) in the dorsal striatum, under normal and hyperdopaminergic conditions (by selectively activating SNc dopamine neurons). Based on their distinct anatomical connections and implications in behavior, we will image D1- and D2-SPN activity in the dorsomedial striatum (DMS) during working memory and caudal tail of the dorsal striatum (TS) during auditory perception. After determining how activating SNc dopamine projections to the dorsal striatum alter task-related D1- and D2-SPN activity in each sub-region and behavioral process, we will use chemogenetics (i.e., DREADD manipulations) to counteract the effects of nigrostriatal dopamine on D1- and D2-SPN activity levels. We will do this in each striatal subregion to determine whether dopamine-driven alterations in the activity of each cell type are preferentially involved in working memory or perceptual deficits. Because existing antipsychotic drugs preferentially block D2 dopamine receptors and are more effective for abnormal perception than cognitive deficits, our overarching hypothesis is that dopamine driven-changes in D2-SPN activity are more associated with faulty perception and those in D1-SPN activity with working memory deficits. However, our recent discovery that antipsychotics also affect the activity of D1-SPNs (Yun et al., Nat Neurosci, 2023) requires the rigorous adjudication of this hypothesis. Our work will inform our understanding subcortical dopamine’s role in working memory and perception and constrain therapeutic strategies for normalizing the symptoms associated with these processes when the dopamine system goes awry.

NIH Research Projects · FY 2026 · 2025-03

Project Summary The known determinants of risk for estrogen receptor (ER)-negative breast cancer are genetic or systemic/behavioral factors. In contrast, few if any local factors in the breast environment serve to identify women at risk for ER negative tumors. Local in-breast factors are of great interest however, since they may be more specifically targetable for breast cancer prevention than systemic factors. In this innovative submission, we propose that the expression of neural genes, a recently identified “Hallmark of Cancer”, results from epigenetic reprogramming consequent to lipid-induced altered metabolic flux. Studies of metachronous breast cancers that develop in the opposite breast show a similarity to the ER status of the index primary. Therefore, we employed the contralateral unaffected breast (CUB) of women undergoing surgical therapy for newly diagnosed unilateral breast cancer as a model to discover potential markers of ER- risk. In a previous study, we identified a lipid metabolism (LiMe) gene signature, which was enriched in the CUBs of women with ER- breast cancer. In order discover mechanisms by which lipid metabolism pathways would aid ER- breast cancer development, we established an in vitro model in which the ER and progesterone receptor (PR) negative cell lines MCF- 10A/12A and breast microstructures are exposed to octanoic acid (OA), a medium chain eight-carbon fatty acid. Using this model system, we observed dynamic and profound changes in gene expression, accompanied by changes in chromatin packing density, chromatin accessibility and histone methylation. Significant increase in metabolic flux was observed in 38 reactions, among them those of the serine, one- carbon, glycine (SOG) pathway and the methionine cycle with a consequent increase in S-adenosylmethionine (SAM) concentration. An intriguing and unexpected finding was expression of genes involved in nervous system development, which we hypothesize results from SAM driven histone methylation. We propose to pursue these provocative results as follows. Aim 1 explores whether the OA-mediated increase in the expression of specific neural genes is also observed at the protein level. Based upon gene expression, a specific subset of basal cells (BSL1) are hypothesized to be those undergoing the epithelial to neural flip. BSL1 will be isolated from breast microstructures, exposed to OA and assayed for neurite outgrowth. Aim 2’s goal is to determine which other histone methylations are responsible for the increased expression of genes associated with neurons and decreased expression of those associated with epithelial cells. Aim 3 is constructed to determine whether specific SNPs associated with ER-breast cancer produce a microenvironment in vivo that mirrors the OA rich experimental environment. These investigations have the potential to reveal a set of novel metabolic-fostered alterations that may be utilized as targets for breast cancer prevention.

NSF Awards · FY 2025 · 2025-03

The objective of this project is to study properties of network data when the total data is too large to look at or the access to the data in some other way restricted, e.g., we can look only at the neighborhoods of some data points. Much real-world data is indeed of this type, like the link structure of web pages or the call records of cell phones. From this partial data, we still want to answer questions about the entire network, like finding communities within the network. This network inference and network reconstruction is made possible by making assumptions on the process that generated the network. In addition to the research on network inference and reconstruction algorithms, the investigator will train students, from the secondary to graduate level, in this topic, and disseminate knowledge through a monograph. The investigator has partnered with the Kohl Children's Museum of Greater Chicago to develop exhibits and programming to raise children’s interest and understanding of probability theory and will continue to engage with the public through the media. The project will study three research directions. (1) Community Detection in Spatial Networks: Traditionally, probabilistic network models have not included a spatial dimension and thus do not accurately reflect transitive behavior in real-world networks, for example, “the friend of my friend is also my friend.'' The project will work towards a theory for spatial networks, answering foundational questions on statistical limits and developing efficient algorithms for inference. (2) Optimization for Inference: Optimization algorithms have been used with great success for inference problems on networks, yet there are some problems for which we do not know whether an optimization algorithm is the best algorithm for a given task. The project will investigate the power of optimization algorithms for network inference tasks, including semidefinite programming for community detection and quadratic programming for graph matching. (3) Reconstructing Networks: Network reconstruction tasks involve determining the connectivity structure of a large network given a noisy or fragmented copy of the network. The project will tackle open problems in reconstructing a network from unlabeled local neighborhoods of nodes, identifying a graph’s isomorphism class from its local neighborhoods, and planted subgraph recovery. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NIH Research Projects · FY 2026 · 2025-03

ABSTRACT Nearly 1 in 5 postpartum patients will have a repeat pregnancy after a short interpregnancy interval (sIPI), defined as less than 18 months between a prior birth and subsequent conception. Several adverse outcomes are linked to sIPI, including preterm delivery, low birth weight, and infant mortality. Risks are greatest for shorter IPIs and unintended pregnancies. Guidelines therefore recommend clinicians advise postpartum patients to avoid a sIPI of <6 months and consider delaying pregnancy for 18 months; contraceptive options should also be discussed. Yet up to 40% of patients never receive any postpartum care, missing opportunities for counseling. Health system factors, like fragmentation in care and difficulty scheduling and navigating visits, are frequently cited barriers. Among patients who do attend postpartum care, only half receive counseling on healthy birth spacing. While contraceptive counseling is usually provided, it is rarely comprehensive or patient-centered. As a result, most patients are unaware of the consequences of sIPI and the time recommended between pregnancies. Nearly half do not use any postpartum contraception or use a less effective method, increasing risk of repeat pregnancy. On the patient-level, the role of psychosocial (e.g., depression, stress) and behavioral (e.g., alcohol use, sleep) factors on postpartum contraceptive use and sIPI are poorly understood, despite the considerable physical and mental demands of the postpartum period. Similarly, the impact of low health literacy, or difficulty `finding, understanding, and using information to inform health actions' has been linked to worse contraceptive knowledge and poor understanding of fecundity, but has not been studied in relation to postpartum contraceptive use or sIPI. Finally, despite reproduction being a dyadic behavior, partner-level factors, including partner health literacy and partner-reported psychosocial and behavioral factors, and their impact on postpartum contraceptive use and sIPI remain understudied. Research has also not considered how these factors vary and interact within a dyad. Unraveling these relationships can provide crucial information on how - and who - to target in future interventions. To address these evidence gaps, we will conduct a longitudinal cohort study among 960 English- and Spanish-speaking postpartum patients recruited from academic and community health centers in Chicago, IL and any eligible, cohabitating partners (N=400). Data will be collected at 6 timepoints over 21 months to capture modifiable, multilevel factors affecting postpartum contraceptive use and unintended sIPI. Our aims are to: 1) Examine the effect of patient health literacy and psychosocial and behavioral factors on birth spacing knowledge, postpartum contraceptive method choice, use, and unintended sIPI; 2) Investigate the impact of the health system on patient postpartum care utilization, birth spacing knowledge, postpartum contraceptive method choice, and unintended sIPI; and 3) Among dyads, explore the influence of patient and partner health literacy and psychosocial and behavioral factors on postpartum contraceptive method choice, use, and unintended sIPI.

NIH Research Projects · FY 2026 · 2025-02

Abstract The outcomes of cancer metastasis result from the dynamic battles and interactive reprogramming between malignant cancer cells and the host defense system, especially immune cells. As one of the most challenging and unmet tasks in the cancer clinic, effective metastasis control or prevention demands better understanding and targeting strategies to reprogram the tumor-host ecosystems. The interplay is not only determined by evolving heterogeneity and regeneration of tumor cells but also the fitness of immune system. While tumor- infiltrated immune cells have been relatively well studied, the interactions between white blood cells (WBCs) and circulating tumor cells (CTCs) are only at the beginning to be elucidated. In this proposal, our goal is to identify molecular regulators of CTC-host interactions in one of the most aggressive subtypes of breast cancer, triple- negative breast cancer (TNBC) which lacks expression of estrogen receptor (ER), progesterone receptor (PR), and HER2 for targeted therapies, thereby blocking its metastasis to visceral organs such as the lungs. Combining computational ranking of proteomic candidates, tumor specific expression, and clinical association of breast cancer outcomes, we have identified one of the top enriched surface proteins in TNBC, PlexinB2 (PB2), which drives the formation of homotypic tumor clusters and heterotypic CTC-monocyte clusters through interactions with the Semaphorin ligands. CTC clusters with properties of stem cell plasticity and immune evasion are considered the seeds of distant metastases which account for 90% of solid tumor-related mortality. We hypothesize that targeting the PB2 pathway interferes with CTC-immune interactions and inhibits metastasis of TNBC. Three specific aims are proposed to test the hypothesis: (1) determine clinical relevance of the PB2 network in human TNBC, (2) dissect the molecular mechanisms underlying PB2-driven CTC cluster formation, and (3) targeting PB2 in CTC clusters and metastasis in preclinical modelsin vivo. As proof-of-concept, anti-PB2 neutralizing antibodies provide a new therapeutic opportunity to block CTC clusters and metastasis in TNBC.

NSF Awards · FY 2025 · 2025-02

Language-based generative artificial intelligence (AI) is transforming scientific research, opening new opportunities to empower discovery and broader participation through the use of natural language interfaces to scientific workflows and AI-enabled cyberinfrastructure. To fully exploit NSF’s investments in cyberinfrastructure, there is a critical need to develop and understand the integration, programming, and use of AI across scientific computing resources and high-resolution environmental sensors and instruments such as cameras, microphones, and weather sensors. This new AI-enabled cyberinfrastructure will accelerate data analysis and software generation with powerful multi-modal large language models (LLMs). It harnesses LLMs to democratize access to AI, enabling individuals without programming skills to conduct experiments and allowing the scientific community to develop natural language interfaces, empowering a new generation of scientists, broadening participation in AI research through outreach programs, and enhancing representation. Hands-on training and educational resources for students will provide technical skills and enhance the nation’s AI workforce development. The Sage Grande Testbed (SGT) is designed to revolutionize the integration of LLMs and edge computing in scientific research, extending NSF’s cyberinfrastructure to support advanced AI applications across various domains. It builds on SAGE, an AI-enabled platform developed through NSF’s Mid-Scale Research Infrastructure program to integrate natural language processing capabilities with cloud-based software environments, enabling seamless scientific inquiries and reducing the complexity of using advanced cyberinfrastructure. SGT supports a library of LLMs to support natural language queries, fostering breakthrough research and hands-on education. The testbed addresses generative AI, the computing continuum, and scientific measurement and observation, and provides cyberinfrastructure to evaluate AI trust factors, including hallucinations, bias, and safety as well as AI-generated and AI-controlled cyber-physical systems necessary for field measurements and real-time data analysis. 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 · 2025-02

Non-technical Abstract Quantum information processing (QIP) has rapidly emerged as a compelling research direction, driven by the prospect of quantum computers capable of performing calculations that are too large for any current or conceivable future classical (non-quantum) supercomputer. The Achilles heel of QIP has been dissipation, the friction that both generates heat and destroys the long-lived quantum correlations among quantum bits ("qubits") necessary for QIP, so far limiting quantum information systems in both size and complexity. Such correlations among qubits are called "entanglement," and a goal of this research is to produce any desired entangled state of qubits, which becomes the starting point for a quantum computation. A powerful approach to address this general problem is quantum reservoir engineering: the idea is to turn the tables on dissipation and use it as a resource for steering a quantum system, such that the dissipation-driven dynamics naturally relax the system to the state of interest. This CAREER project supports basic research into developing a novel reservoir engineering framework and leverages it for entanglement generation in noisy quantum systems. From a practical standpoint, this will help identify critical milestones for establishing reservoir engineering as a standard paradigm for scalable and robust entanglement generation, which has applications in all areas of quantum information science, including quantum computing, sensing and communication. In addition, the proposed research will enable fundamental advances in the physics of quantum systems coupled to a noisy environment by developing theoretical tools to rigorously explore the validity of standard dissipative models in the presence of noise that varies, and is correlated, in time. The education and training aspect in this project will assume a multi-pronged approach that will expose graduate and undergraduate students to a wide variety of analytical and computational techniques in quantum information and quantum optics. Aided and informed by close connections with experimental realizations of solid-state qubits, the aim will be to provide the trainees a holistic view of the polyglot field of QIP and address the strategic national need to create a "quantum-smart" workforce. The training aspect will be integrated with broad educational and outreach goals via new and continuing curriculum and course development initiatives, public talks, and promoting open access venues for communicating research results. Technical Abstract Quantum reservoir engineering is an attractive approach for correcting errors and realizing stable quantum coherences autonomously. The basic idea is to tailor the dissipative environment of the target systems so that this engineered dissipation relaxes the system to and sustains it in a desired target state. While versatile, existing schemes for dissipative state preparation rely exclusively on time-independent dissipative dynamics, which can leave the protocols susceptible to unwanted spurious dissipation. The PI's broad vision is that this project will enable a transformative new class of dissipative state preparation protocols with dramatically improved speed, fidelity and robustness to errors. To this end, the research will broadly focus on two directions: (i) study of dynamics driven by time-dependent dissipation, and (ii) study of dynamics driven by correlated dissipation. These theoretical studies will involve developing a comprehensive analytical and numerical framework with some of the first explorations of the validity of open quantum systems descriptions, especially in a context where non-trivial dissipation is a useful resource. For instance, the outcomes of this project will address fundamental questions pertaining to implications of adiabaticity and non-Markovianity for reservoir engineering and provide useful pointers for quantum error correction and error mitigation in the presence of correlated noise. This has transformative potential not only for the entanglement stabilization protocols envisioned here but also for any platform involving dynamic control of quantum systems. The PI maintains an active collaboration with experimental groups who will test the ideas on Josephson-junction-based superconducting platforms. Thus this research will complement and advance the rapidly growing experimental capabilities in quantum control of low-dimensional open systems in the near-term. Further, it will help strengthen interdisciplinary connections between disparate fields of quantum information/quantum optics, optimal control and strongly-interacting field theories, all of which focus on far-from-equilibrium quantum dynamics. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NIH Research Projects · FY 2026 · 2025-02

PROJECT SUMMARY Alternative poison exon (PE) splicing is a critical regulatory mechanism that tightly controls protein expression across time and cell type. When included in an mRNA transcript, a PE introduces a premature termination codon that triggers nonsense-mediated mRNA decay (NMD) to degrade the transcript. Alternative PE splicing is critical for mediating proper neurodevelopment. For example, the voltage-gated sodium channel (VGSC) genes SCN1A (NaV1.1) and SCN8A (NaV1.6) splice PEs into mRNA transcripts in neural progenitor cells, but not in mature neurons, resulting in productive mRNA that can then be translated into functional VGSCs to support neuronal electrophysiology. Pathogenic variants near PE splice sites can cause aberrant PE splicing patterns that result in neurodevelopmental disorders (NDDs) like Dravet syndrome, caused by abnormal PE splicing in SCN1A and SCN8A. Although important in regulating the dynamics of neurodevelopment, PEs have been largely understudied due to the technical challenges in identifying these exons. PEs are inherently difficult to detect using short-read RNA sequencing (SRS) because NMD quickly degrades PE-containing transcripts, resulting in low transcript abundance. Moreover, it is challenging to computationally resolve the exact location of a PE in an mRNA isoform using SRS because the reads rarely span entire splice junctions. To overcome these biological and technical obstacles, I will develop POISEN (Poison exOn dIScovery for long-rEad traNscriptomes), a bioinformatics pipeline to identify PEs in long-read RNA sequencing (LRS) data. I hypothesize that the computational identification of PEs using LRS data will enable the discovery of novel PEs and define the cell type and temporal specificity of PEs across neurodevelopment. In Aim 1, I will perform bulk LRS on induced pluripotent stem cell-derived cerebral organoids (COs) grown at three distinct time points to recapitulate different stages of human neurodevelopment. Using these CO long-read transcriptomes, I will program POISEN to systematically identify PEs. To validate the PEs identified in CO transcriptomes, I will use cycloheximide (CHX) treatment to upregulate the abundance of PE-containing transcripts. I will then compare CHX-treated and control COs using bulk SRS, applying a differential exon usage analysis to evaluate the increase in PE expression in CHX-treated COs versus control COs. I will also perform an enrichment analysis on NDD- and epilepsy-related genes that express PEs to gain insight into the biological processes influenced by alternative PE splicing. In Aim 2, I will perform single-cell LRS on COs grown for the same time points as in Aim 1 and evaluate PE splicing patterns according to cell type and time point. I will create an online browser to house the data and results of this study as a useful resource for the scientific community to leverage in probing the understudied phenomenon of alternative PE splicing in neurodevelopment and NDDs. This study will result in the first bioinformatics pipeline for detecting PEs in LRS data, facilitating the discovery of PEs relevant to neurodevelopment and novel therapeutic targets for genetic epilepsy disorders and other NDDs.

NIH Research Projects · FY 2026 · 2025-02

Abstract Primary Graft Dysfunction (PGD) has a 30% prevalence post lung transplantation (LTx) and is the leading cause of morbidity and mortality. The mechanisms that contribute to PGD are complex. However, the process of ischemia reperfusion injury (IRI) and degree of injury to the lung microvasculature are known contributors to PGD development. Despite significantly worsening short and long-term survival outcomes, there are currently no FDA approved therapies for PGD. Injury to the microvascular beds leads to dysfunctional and activated vascular endothelial cells which are pro-inflammatory, lack barrier integrity, and improperly regulate immune cell extravasation [17,18]. Bone morphogenetic protein 9 (BMP9) is a critical lung microvascular homeostasis and quiescent factor. Loss of BMP9 signaling has been shown to promote lung pathology in a number of lung acute and chronic diseases. Whether BMP signaling plays a role in the acute lung injury seen in LTx PGD has not been previously investigated. Here we present novel preliminary data showing that BMP signaling is significantly downregulated as a consequence of IRI, using in vitro and in vivo models of LTx. We further demonstrate that exogenous augmentation of circulating BMP9 significantly reduces post-LTx IRI. Based on these novel data, the important role that BMP signaling plays in endothelial homeostasis, and protective effects that exogenous BMP9 therapy yields in other experimental lung injuries, we hypothesize that impaired microvascular BMP signaling promotes lung endothelial injury and the development of primary graft dysfunction. Our overarching goal is to mechanistically dissect and define how BMP microvascular homeostasis pathway is impacted by lung transplantation and develop pathway-specific novel pharmacotherapeutic interventions. SA. 1. Determine the mechanisms by which BMP signaling contributes to primary graft dysfunction and SA. 2. Explore the therapeutic potential of modulating the BMP9 signaling axis as a means to improve LTx outcomes. We hypothesize that augmentation of BMPR2 signaling will promote protection from IRI and the development of PGD. On completion of these studies, our short-term goal will provide novel insights into the role of the BMP signaling pathway in endothelial injury and LTx. These proposed studies will further support our long-term goal to provide important information that could contribute to the establishment of tailored BMP signaling pathway interventions that could serve as novel pharmacotherapeutic strategy to improve early lung transplant outcomes. Based on the literature, these therapies may translate to significantly improved long-term allograft survival.

NIH Research Projects · FY 2026 · 2025-02

Project Summary Parkinson’s disease (PD) is the most common age-dependent movement disorder; however, it remains mysterious how aging predisposes the brain to PD. As the body ages, senescent cells become accumulated in multiple organs, including the brain. Recent evidence showed that removal of senescent glial cells, including microglia, alleviates disease phenotypes in animal models of Alzheimer’s disease (AD) and PD. Microglia are brain-specific macrophages that continuously survey the brain to maintain brain homeostasis. Senescent microglia may lose their neuroprotective functions and secret senescence-associated secretory phenotype (SASP), leading to chronic inflammation. Therefore, there is a critical need to examine the impact of senescent microglia on human PD. Our preliminary data with single-nucleus RNA sequencing (snRNA-seq) technology revealed that a subset of microglia expresses more senescence-related genes in human PD brain. The long- term objectives of this research are to elucidate whether and how microglia become senescent in PD and to characterize the molecular signature of senescent microglia for finding out therapeutic targets. In Aim1, we will determine whether senescent microglia become accumulated in PD and establish the relationship between autophagic flux and microglial senescence using human PD postmortem brain. Autophagy is a cellular degradation pathway responsible for removing damaged cellular organelles, protein aggregates, and invading foreign substances. Autophagy plays a role in extending healthy lifespan and preventing cellular senescence in animal models. Our preliminary data highlights that autophagy prevents microglial senescence in mouse. In Aim2, we will characterize the transcriptomic and proteomic signatures of senescent microglia in human PD postmortem brain by employing snRNA-seq and spatial omics technologies. In Aim 3, we will utilize human microglia from induced pluripotent stem cells (iPSC) to study the roles of autophagy in microglial senescence. We will apply RNA-seq and LC-MS/MS to elucidate the transcriptomic profile and SASP of senescent microglia, respectively. Lastly, we will determine the effect of SASP from senescent microglia on the survival of human dopaminergic neurons. Successful completion of this project will 1) provide evidence for microglial senescence in human PD brain, 2) characterize the molecular signature of senescent microglia, and 3) provide insight into the mechanism of how autophagy regulates microglial senescence and how senescent microglia affect dopaminergic neurons.

NIH Research Projects · FY 2026 · 2025-02

PROJECT SUMMARY/ABSTRACT Heart failure impacts over 5 million Americans annually. Obesity increases risk factors associated with heart failure. The gene MTCH2 has genetic variants that associate with both cardiomyopathy and obesity. The human genetic data support that reduction of MTCH2 protein increases the risk for cardiomyopathy and promotes a reduction in body mass. MTCH2 encodes an outer mitochondrial membrane protein important for mitochondrial dynamics and metabolism, and MTCH2 protein was recently identified as an insertase for outer mitochondrial membrane proteins. To study the role of cardiac Mtch2 in the heart, we created cardiomyocyte- specific Mtch2 KO mice (cMtch2 KO). cMtch2 KO mice develop decreased systolic function in males earlier than female mice. Male cMtch2 KO mice have reduced fat mass compared to controls prior to systolic dysfunction. cMtch2 KO mice fail to hypertrophy their hearts in response to isoproterenol challenge, and instead lose function and lose a large percentage of their body mass compared to controls. These data support the idea that deletion of cardiac Mtch2 induces mitochondrial dysfunction and increases energetics to maintain cardiac contraction at the cost of body fat. When challenged by a stressor, such as aging or isoproterenol, the damaged mitochondria can no longer increase energetics required to maintain function. To explore the mechanism by which reduced MTCH2 protein results in damaged mitochondria, we performed mass spectrometry on mitochondria isolated from cMtch2 KO hearts revealing a significant decrease in FUNDC2, a potential target of Mtch2’s insertase function. FUNDC2 is linked to mitochondrial dynamics, apoptosis/autophagy, and activation of the transcription factor SREBP1. I hypothesize that reduction of MTCH2 sensitizes the heart to diet-induced cardiomyopathy due to mis-insertion of FUNDC2. In Aim 1 of this proposal, I will overexpress FUNDC2 in cMtch2 KO mice and determine if restoring FUNDC2 to the mitochondria rescues both the development of cardiomyopathy and impaired body composition. In Aim 2, I will measure how MTCH2 influences mitochondrial interactions with the sarcoplasmic reticulum and sarcomere. In Aim 3, I will test if globally reducing Mtch2 leads to cardiomyopathy when sensitized by high fat diet. The data gathered from these aims will elucidate the mechanism by which removal or reduction of MTCH2 from the mitochondrial outer membrane induces mitochondrial dysfunction, sarcomere dysfunction, and ultimately, impaired heart function.

NSF Awards · FY 2025 · 2025-02

Social information can be linguistically represented in many ways, such as with word endings or as part of the word’s definition. For example, some words are stereotypically gendered because the word itself is not linguistically marked for gender, but it still carries information influenced by social experiences. This doctoral dissertation project advances an understanding of how the various representations of social information in nouns differently impact language comprehension and processing. Additionally, this project tests possible social information in adjectives, which has not been previously studied in language processing. Additional benefits to society include educational and workforce development opportunities for undergraduate students who receive training in psycholinguistic research methods. Research in linguistics shows that gender bias plays a crucial role when forming a coreferential dependency, which is the process of linking a pronoun with a larger noun phrase that the pronoun replaces and refers to. Influence of gender on coreferential dependency formation has been found in online processing measures, with a slowdown in reading times when a noun phrase, though grammatically accessible, is judged by the perceiver as “mismatching” the pronoun in gender. This project uses eye-tracking measures to investigate how differences in processing may reflect differences in the social representation of a word and/or differences in the sentence structure and context surrounding the target word. Additionally, new methods for testing social information are developed. De-identified data and code are made publicly available, as a major goal of this project is providing updated norming results on nouns, as well the first publicly available norming results on adjectives. 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 · 2025-02

Humans live in social groups, but current biocultural changes have led to significant variation in levels of social connectedness or belonging, which may activate the neuro-immune networks that regulate inflammation. Inflammation is a form of stress response that can have negative health effects, but that is also necessary for adaptation and health. To date, studies of social connectedness and inflammation are limited to individuals from populations with similar levels of social belonging, and these studies emphasize negative social conditions, so that the impact of positive social connections remain understudied. This Doctoral Dissertation Research project adopts a biocultural approach to investigate how variations in belonging affect inflammatory regulation dynamics among adults from social contexts with varying levels of belonging. The study integrates iterative ethnography, with surveys and minimally invasive biological sampling to identify the conditions under which varying levels of connectedness may lead to adaptive or maladaptive inflammatory levels. The study builds STEM capacity through student training, and expands its impact through outreach activities. Scientists have demonstrated that the inflammatory system is sensitive to social experiences such as belonging and exclusion. Social threats can activate the same conserved neuro-inflammatory pathways as physical ones, involving the hypothalamic pituitary adrenocortical (HPA) axis and the sympathetic nervous system’s regulation of acute inflammation. Chronic activation of these pathways can lead to a conserved transcriptional response to adversity (CTRA) and promote a pro-inflammatory phenotype by impairing the downregulation of inflammation in innate immune cells. While ex-vivo cell culture models have advanced our understanding of these processes, they remain limited by costly and invasive sampling methods that require sterile laboratory conditions. Moreover, the effects of positive social connections on inflammation regulation remain underexplored. This Doctoral Dissertation Research project contributes to biocultural frameworks of belonging and inflammatory regulation by: 1) developing a culturally and geographically specific measure of belonging among peoples experiencing different cultural conditions, 2) adapting an ex-vivo cell culture protocol with dried blood spots for use in field settings, and 3) synthesizing novel data to elucidate how diverse social contexts influence biological variation and health in increasingly complex social settings. 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 · 2025-02

Molecules in our cells and genes in our genome do not function in isolation. Instead, they operate collectively and under the influence of environmental factors. Despite the growing success of network models capturing single factor and pairwise effects, higher-order interactions between multiple genetic and environmental factors remain poorly understood. While elementary interactions in physics have been adequately captured at the pairwise level, higher-order interactions play a critical role in complex systems, requiring new approaches. Such higher-order interactions are also decisive for most types of cancer and complex diseases, triggered by the interplay of multiple factors. This knowledge gap prevents us from linking genotype to phenotype, systematically identifying therapeutic biomarkers, or designing efficacious drug combinations. The overarching goal of this CAREER award is to break down the existing conceptual and computational barriers, thereby deepening our understanding of higher-order interactions and insights into complex systems. Specifically, the Principal Investigator (PI) will develop a systematic framework to predict how biological fitness in eukaryotic model systems is influenced by combinations of mutations and environmental factors, including genetic, chemical-genetic, and drug-drug interactions. This will be achieved by creating a versatile hypergraph framework that models both pairwise and higher-order interactions, leveraging advanced methods from statistical physics and graph theory. In collaboration with experimental partners, this project will extend recent progress in network models of pairwise interactions to encompass interactions involving three or more components. In synergy with the research objectives, the PI will expand the lab’s High School outreach activities and will lead a community effort to organize art exhibits showcasing the captivating aesthetic beauty and hidden patterns of biological networks. 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 · 2025-02

PROJECT SUMMARY Clonal hematopoiesis (CH) is a pre-malignant condition characterized by the clonal expansion of the mutated hematopoietic stem and progenitor cells (HSPCs). CH represents a significant public health concern, over 10% of individuals aged 70 and above carry CH mutations. This blood disorder predominantly affects older adults and elevates the risk of hematologic malignancies nearly 13 folds. As the US population projected to be markedly aged in the next three decades, the implications of CH will become increasingly significant. First being recognized as a distinct category of precursor myeloid disease state by WHO in 2022, there is not yet any FDA approved treatment toward CH, highlighting an urgent medical need. This project aims to investigate how inflammation, especially that originating form the non-hematopoietic cells within the bone marrow microenvironment, contributes to the CH progression. We have found Gasdermin D (GSDMD) loss-of-function in the non-hematopoietic stromal cells significantly mitigated the CH progression in mice. To further translate our findings from mice to humans, we have developed a novel human bone marrow organoid model. This model autonomously generates multi-lineage hematopoietic cells and non-hematopoietic stromal cells within a 3D vascular network, closely resembling the human bone marrow microenvironment. Notably, we generated GSDMD-/- organoids and engrafted them with patient-derived HSPCs carrying TET2 mutations, we observed a significant reduction in myeloid-biased hematopoiesis of the engrafted HSPCs with in GSDMD-/- organoids compared to WT organoids. Moving forward, we will employ spatial transcriptomic analysis coupled with single-cell RNA sequencing to uncover the mechanisms by which GSDMD influences cell-cell interactions in both mouse models and human organoid models. Ultimately, we plan to create a novel patient-derived xenograft mouse model by implanting the organoid into NSG immunodeficient mice, further advancing our ability to model human CH in vivo. The successful completion of this project will provide critical insights into the cellular and molecular mechanisms of the protective effect of GSDMD deficiency in the bone marrow microenvironment. It will lay the groundwork for potential therapeutic strategies targeting dysregulated inflammation in non- hematopoietic cells, serving as a stepping stone for my transition to independent investigations as a PI.

NIH Research Projects · FY 2026 · 2025-02

PROJECT SUMMARY Dysregulation of neural control over gastrointestinal (GI) function is the principal cause of many digestive and metabolic disorders. While significant strides have been made in uncovering the molecular and cellular constituents of signals traveling from the gut to the brain, the reciprocal brain-to-gut communication remains largely unknown. Researchers are severely limited by the lack of specialized tools to study GI function. In response to this critical need, the overall objective in this proposal is to develop an implantable sensor enabling precise examination of gastric motility in small animal models. Towards this goal, the proposed research leverages recent breakthroughs in stretchable bio-electronics to address two specific aims: 1) Developing a miniature implantable, wireless device for chronic monitoring of gastric motility in awake, freely moving mice; 2) Employing optogenetic and microfluidic techniques to manipulate stomach activity and modulate motility . This application is poised to introduce groundbreaking methodologies for exploring the neural regulation of gastric motility, and, in the long-term, provide therapeutic strategies to alleviate gastroparesis.

NIH Research Projects · FY 2026 · 2025-02

Thorp Project Summary Abstract Acute ischemic injury and heart failure (HF) are significant causes of morbidity and mortality that lack effective therapeutic strategies. Though diverse in their etiology, a common and critical contributor to their disease pathophysiology is the chronically activated macrophage phagocyte. As such, the resolution of cardiac inflammation through selective dampening of macrophge hyperactivity and the promotion of inflammation resolution, has the potential to ameliorate pathophysiology and improve heart health. In the case of HF, which has been earmarked as a research priority by the National Institutes of Health, risk factors such as high fat and hypertension are commonly present and directly contribute to chronic inflammation. During cardiac injuruy and HF, the extent of inflammation and inflammatory macrophages in the myocardium has been linked to the degree of cardiac fibrosis and myocardial stress, and this likely contributes to impaired cardiac performance. However, underlying causal mechanisms and immune molecular protagonists remain incomplete. A similar lack of understanding pertains to how innate inflammation contributes to crosstalk with other cells found in the heart, including cardiac lymphatics. In this setting, cell subsets and molecular factors that regulate inflammation resolution and tissue repair remain unclear. Taken together, our studies will focus on and identify key and maladaptive immunometabolic signaling pathways specific to cardiac disease. In the case of heart failure, we will examine on how risk factors synergize to rewire macrophage signaling circuits that fuel chronic cardiac inflammation. We will also elucidate new pathways by which macrophages communicate with progenitor cells, the underlying molecular mechanisms, and the potential of therapeutic amelioration. Our overall objectives leverage newly generated and cutting-edge experimental tools through approaches in experimental animals and humans. These studies will combine improved basic understanding of novel and disease-specific cellular mechanisms with the identification of new therapeutic candidates for heart failure, inflammation resolution, and tissue inury.