University Of Illinois At Chicago

NSF Awards · FY 2024 · 2024-08

In this project, the investigator seeks to significantly expand his work on applications of model theory, a branch of mathematical logic, to tackle several far-reaching open problems centered around the study of geometric structures. Roughly speaking, a geometric structure modeled on a geometry (G,X) is a space that locally (i.e. upon zooming in) looks like the given space X and on which there are local symmetries coming from the action of the group G on X. These structures have been studied extensively since their introduction by Ehresmann in the 1930’s and in this project the PI aims to continue to explore their connections to number theory and differential equations. The project will involve training of graduate students. The main objective is to make progress on fundamental questions about the algebraic nature of the wide class of special functions coming from geometric structures (as well as from other physical applications) and to use those to attack related problems in diophantine geometry. More precisely, building on his recent work on a differential approach to functional transcendence, the investigator aims to 1) tackle major transcendence problems such as the Ax-Lindemann-Weierstrass and Ax-Schanuel conjectures for uniformizing functions of geometric structures in higher dimensions, 2) initiate the study of the Existential Closedness and the Zilber-Pink conjecture for Fuchsian functions using a differential approach and 3) study the structure of the sets defined by (possibly other) classical differential and difference equations. 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 study examines what types of organizations are displaced from gentrifying areas and what happens to these organizations after displacement by collecting historical and contemporary data on the geography of local community organizations in the United States. Neighborhood change can be tremendously disruptive to residents and the community organizations that serve them. While much research examines residents who are displaced from their homes due to processes such as gentrification, little scholarship focuses on the displacement of local community organizations in areas undergoing neighborhood change. Community organizations promote civil society, provide needed goods and services, and enhance the health of communities, all of which can be lost when community organizations are displaced. Data from this study will be used to examine the connections between neighborhood change and the locations where community organizations open, close, or move over time. This research will combine geographic information science (GIS) and statistical analysis to digitize and geocode a comprehensive guidebook of local community organizations that serve demographic populations in the United States. The guidebook has been in continuous publication since 1973 and includes the locations and organizational types of hundreds of thousands of local community organizations. Digitizing and geocoding these data will provide an unparalleled look at the spatial evolution of community organizations displaced by gentrification. Analyses that come out of this project will advance knowledge of urban studies, organizational dynamics, and community well-being. The project will culminate in the creation of an interactive website that will enable members of the public to visualize trends in organizational displacement and anticipate what might happen to community organizations in gentrifying neighborhoods in the future. 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- Nitric oxide (NO) is an essential signaling molecule that mediates dichotomous effects along a pathophysiological concentration gradient. Low levels maintain physiological homeostasis, while at high concentrations NO contributes to disease pathogenesis. Although mechanisms of physiologic NO signaling are relatively well established, these canonical pathways do not sufficiently explain how NO drives pathological alterations in gene expression. Epigenetic mechanisms, such as methylation of DNA and RNA, are central regulators of gene expression. Our recent publication and preliminary data demonstrate that NO inhibits DNA and mRNA demethylases, which causes the enrichment of DNA and mRNA methyl-adducts on genes transcriptionally regulated by NO. Specifically, our data demonstrate that a concentration gradient of NO differentially inhibits the activities of both DNA demethylases (TET; ten-eleven translocation, ALKBH2) and mRNA demethylases (FTO; fat mass and obesity associated protein, ALKBH5) by forming a dinitrosyl iron complex (DNIC) at the catalytic mononuclear iron atom. We found that each of these Fe(II)/2-oxoglutarate (2- OG)-dependent demethylases (2-ODD) had a different sensitivity to NO-dependent inhibition. In cells, this inhibition resulted in gene-specific enrichment of 5mC on DNA and m6A on mRNA; both of which are critical gene-regulatory methyl-modifications. However, it is unknow whether NO regulates methyl-adducts beyond m6A and 5mC and whether changes in DNA and mRNA methylation mechanistically drive NO-mediated changes in gene expression. Thus, we hypothesize that NO differentially inhibits DNA and RNA demethylases in a concentration-dependent manner to modulate the distribution of methyl-adducts on DNA and RNA, which in turn control the expression of specific NO-regulated genes. Aim 1 will use isolated 2-ODD enzymes to determine the structure-function relationship of NO bound to each enzyme. Kinetic studies will delineate the differential sensitivities of each enzyme to NO. These data will be applied to cellular models to define the effect of a pathophysiological gradient of NO, through demethylase inhibition, induces differential profiles of multiple methyl- adducts on DNA/mRNA. Aim 2 will use cell models to identify NO-regulated genes that are also enriched in DNA and mRNA methyl adducts. With CRISPR techniques we will modify DNA and mRNA methyl-sites and measure corresponding changes in gene expression to demonstrate a causal-link between NO-dependent DNA/mRNA methylation and gene expression. These studies will elucidate a novel molecular mechanism of signaling whereby NO regulates gene expression by inhibiting 2-ODD demethylases in a concentration-dependent manner thus providing a foundational understanding of the role of NO dysregulation in pathogenic gene expression.

NIH Research Projects · FY 2025 · 2024-08

ABSTRACT Chronic pain represents a serious and growing health concern that affects at least one in five American adults. Despite the high risk of tolerance, physical dependence, and addiction, opioid analgesics continue to be a major component of pain management. Furthermore, opioids are only weakly effective for the approximately 30-40% of chronic pain patients suffering from neuropathic pain arising from lesions or disease of the somatosensory nervous system. Non-opioid first-line treatments for neuropathic pain are also only marginally effective and suffer from serious adverse effects. Clearly, there is an urgent need for new analgesic drug targets and for new classes of drugs that can effectively and safely treat neuropathic pain. The long-term goal of this research project is to fill this gap by establishing the role of the α9α10 nicotinic acetylcholine receptor (nAChR) in neuropathic pain and developing effective antagonists against it. Evidence from peptidic α9α10 antagonists and α9-knockout mice indicates that inhibition of α9α10 function successfully attenuates allodynia and hyperalgesia in several animal models of neuropathic pain. However, the poor drug-like properties of existing α9α10 antagonists hinders them from being easily translated into the clinic. Previous efforts to discover novel α9α10 ligands have been thwarted by technical challenges in adapting α9α10 nAChRs for high-throughput screening and compound optimization assays. Furthermore, the difficulty in expressing α9α10 in mammalian cells has left unanswered questions regarding the structure and function of this promising drug target. Building on a recent discovery that TMIE is an essential auxiliary protein for α9α10 receptor expression, we have engineered a novel HEK293 cell line that stably expresses functional α9α10 receptors. The objective of this application is to leverage this innovative cell line to develop novel α9α10 antagonists and interrogate the location, function, and structure of the receptor. Moreover, we will investigate the in vivo efficacy of pharmacological inhibition of α9α10 activity in multiple neuropathic pain models in mice, studying both spontaneous pain and evoked hypersensitivity. The results from these studies will provide strong evidence that α9α10 nAChRs play a causal role in driving neuropathic pain and represent a bona fide target for analgesia, and will deliver promising lead compounds targeting this mechanism.

NIH Research Projects · FY 2025 · 2024-08

High grade serous ovarian cancer (HGSOC) is the deadliest form of ovarian cancer accounting for 70% of all ovarian cases and the fifth leading cause of death in women. Only in the last six years have frontline therapy changed for ovarian cancer patients with breast cancer gene (BRCA) mutation by the addition of PARP inhibitors. Natural products account for 50% of FDA approved drugs used in the clinic today. With the prevalence of drug resistance leading to relapse and death of ovarian cancer patients, new drug treatment and therapeutic strategies are needed. The focus of this proposal is to study the efficacy and mechanism of the novel natural products didesmethylrocaglamide and phyllanthusmin34 isolated and purified by our collaborative team. Didesmethylrocaglamide (DDR) is a naturally occurring derivative of rocaglamide with potent anti-tumor activity isolated from the Aglaia plant species, whereas phyllanthusmin34 (PHY34) is a synthetic derivative of phyllanthusmin D, a natural compound isolated from Phyllanthus species. Recently, we confirmed that these compounds are cytotoxic and apoptotic in HGSOC from different mechanisms of action. DDR inhibits mRNA translation by stabilizing RNA binding of eukaryotic initiation factor (eIF) 4A whereas PHY34 inhibits autophagy by blocking the ATPase subunit (ATPV0A2) and inhibiting lysosomal acidification. DDR like other rocaglates inhibits mRNA translation which leads to cell death; however, a survival mechanism to generate proteins could occur through autophagy. Protein recycling can be halted by blocking autophagy with an inhibitor like PHY34. We hypothesize that DDR combinatorial treatment with the autophagy inhibitor, PHY34, are a rationale combination for HGSOC and will test their efficacy in models that no longer respond to frontline therapy of platinum and taxanes. We therefore aim to study combinatorial effects on tumor burden in a xenograft and syngeneic model. In addition, we will explore interferon response from natural killer (NK) cells in a syngeneic model because phyllanthusmin compounds have been shown to activate NK cells in addition to blocking autophagy. Secondly, we will also determine the mechanism of action for the combinatorial treatment effects of DDR and PHY34 in sensitive and resistant HGSOC cell lines through proteomic analysis prioritized by pathway analysis, fold change, and validated by western blot and qPCR. Overall, we will gain valuable insight into the role of natural products as new strategies to combat HGSOC. Implementing this research program will foster the development of the candidate as an independent researcher and the career goals to establish a research laboratory and tenured faculty position to further natural products cancer discovery.

NIH Research Projects · FY 2025 · 2024-08

Project Summary Staphylococcus aureus is a Gram-positive pathogen that causes a wide range of superficial and invasive infections. An essential component of S. aureus infectivity and pathogenicity is the cell wall. Comprised of a thick layer of peptidoglycan (PG), the cell wall not only ensures cell viability but also provides protection against external stressors. Given its vital role in bacterial cell survival, PG is a major target of clinically relevant antibiotics. Apart from its role as a protective barrier, S. aureus PG serves as a pathogen-associated molecular pattern that promotes inflammation during infection. However, the full extent of pattern recognition receptors responsible for sensing S. aureus PG and the molecular features required for recognition are not fully explored. Nevertheless, we know that host-PG interactions can stimulate robust inflammation and production of the critical pro- inflammatory cytokine, IL-1β. Indeed, the prior literature argues that the degree of PG recognition by immune cells can shift the nature and duration of the IL-1β response, potentially leading to either infection clearance or inflammatory pathology and persistence. S. aureus PG is composed of repeating disaccharide subunits that are highly crosslinked via peptide cross-bridges. These glycans are remodeled by four hydrolases known as glucosaminidases. Recently, our lab surveyed glucosaminidase mutants to determine how PG remodeling might drive innate immunity. Our findings highlighted that a single enzyme, SagB, was required for S. aureus-mediated induction of IL-1β by bone marrow-derived macrophages. Notably, a ΔsagB mutant failed to stimulate the production of IL-1β while leaving other pro-inflammatory cytokines unaffected. Purified PG isolated from WT S. aureus was sufficient to induce macrophage production of IL-1β, whereas PG from a ΔsagB mutant did not. Furthermore, a ΔsagB mutant elicited reduced IL-1β in infected skin along with decreased inflammatory pathology. In systemic infections, the ΔsagB mutant displayed attenuated virulence. Lastly, we discovered that the SagB-mediated IL-1β response was independent of the NLRP3 inflammasome and caspase-1/11 activation, suggesting the requirement of other caspases or proteases in PG-mediated IL-1β maturation. Based on these findings, we hypothesize that SagB processes PG to generate specific glycans crucial for IL-1β maturation via an NLRP3-independent process (Aim 1) and that SagB-processed PG elicits IL-1β and promotes inflammatory pathology in vivo (Aim 2). Aim 1 will (i) determine the minimal PG component required to induce IL-1β from macrophages, (ii) interrogate the cellular pathway PG activates to produce IL-1β, and (iii) assess the localization of PG using cellular and immunological approaches. Aim 2 will use both systemic and skin and soft tissue infection models to determine if SagB is required to promote inflammation and if SagB-dependent IL-1β production is required to stimulate these responses. Altogether, this project will provide critical information on the significance of PG remodeling in innate immunity and will provide insight into how PG glycans contribute to inflammatory pathology during infection.

NIH Research Projects · FY 2025 · 2024-08

Project Summary/Abstract: Candidate: This K23 award will provide an opportunity for Dr. Pappalardo to realize her goal of becoming an independently funded clinician scientist leading multi-level community-engaged implementation science interventions that dismantle persistent asthma health disparities through health policy and system-level change. The goal of this K23 project is to test school-based asthma health policy implementation interventions in community settings with a high asthma burden. Through her research and career development plans, Dr. Pappalardo will attain expertise in the following areas: human-centered design, health policy, healthcare administration and organizational change, and implementation science methodologies. She will do so through a combination of formal coursework, guided mentorship, and practical experience facilitated by the secured research effort. Environment: The University of Illinois Chicago (UIC) provides an ideal environment for Dr. Pappalardo’s research career advancement. UIC’s Clinical and Translational Science Award (CTSA) program provides research services including the Biostatistics Core. The Institute for Health Research and Policy, Center for Dissemination and Implementation Science, Office of Population Health Sciences, and the health disparities research focus of UIC’s Department of Pediatrics and Medicine provide a rich academic environment for Dr. Pappalardo to further her education. UIC houses a nationally recognized School of Public Health that provides clinician scientists online options and flexibility, which Dr. Pappalardo will leverage to earn a Master of Public Health in Health Policy and Administration. Through these resources, Dr. Pappalardo will obtain further training in implementation science (IS), with a focus in mixed methods and multi-level intervention trial design. Dr. Pappalardo created an expert mentorship committee to guide her academic growth. Each mentor possesses their own exceptional records of publication and funding and are all seasoned mentors to others in similar early-stage investigator roles. Research: Dr. Pappalardo will utilize community- engaged research and implementation science methods (Exploration, Preparation, Implementation and Sustainability or EPIS determinants framework) to understand the determinants of districts who have yet to implement stock inhalers (Aim 1) and devise targeted implementation strategies through human centered design methods to address these barriers (Aim 2). Aim 3 will pilot test implementation strategies in three schools in one to two high asthma burden Illinois counties. Dr. Pappalardo will assess process-level implementation and early effectiveness outcomes of a stock inhaler intervention in comparison to the early adopters across Illinois using the Reach Effectiveness, Adoption, Implementation and Maintenance outcomes framework (RE-AIM). Results from Aim 3 will inform a future R01-level randomized, stepped wedge implementation trial of an asthma management program focusing on asthma medication access for children with asthma affected by health disparities in a variety of settings across Illinois.

NSF Awards · FY 2024 · 2024-08

Developing sensing circuits and systems capable of perceiving the physical environment is an essential step toward next-generation cyber-physical systems that leverage computation, communication, and sensing integrated with the physical domain. The recent introduction of a class of artificial intelligence (AI) methods known as deep learning has drastically advanced vision-based environment perception. However, the applicability of these methods is significantly limited by their reliance on vast amounts of 3D annotations for training, which are expensive, unnatural, and often unobtainable. Acquiring 3D annotations necessitates specialized data captured by 3D sensors rather than utilizing abundant and readily available images or videos. Moreover, it requires a controlled environment or compromises with inaccurate subjective labeling. This project aims to address real-time environment perception in a very challenging, largely unexplored, yet highly practical setting, where only 2D annotations are available during training, by modeling and learning rich space-time structures of the environment. The outcomes of this project will significantly impact cyber-physical systems and facilitate a wide range of applications, from robots in manufacturing and personal services to autonomous vehicles that enhance people’s mobility and safety. Furthermore, this project will tightly integrate research and education at the University of Illinois Chicago (UIC), which is a Minority Serving Institution (MSI), through curriculum development, research training for high school, undergraduate, and graduate students, and community outreach. This project will address real-time environment perception when only 2D annotations are available during training by systematically pursuing a novel approach that decomposes the complex physical environment into geometry and motion substructures in 3D space and models their rich space-time interactions. From streaming video, the trained system will not only recognize objects and scene layouts in the environment but also estimate their 3D geometry and 3D motion in real time. This project is focused on (1) establishing a self-supervised framework for lifting 2D objects to 3D, by bridging geometry and motion, brightness constancy, and differentiable depth rendering, (2) scaling 2D-to-3D lifting of individual objects to perceiving the entire environment, by modeling and learning short-term and long-term dynamics of the environment, and (3) achieving flexible and generalizable environment perception by handling articulated motion and out-of-distribution environments. The new approach is expected to be efficient in terms of the amount of annotations required for training, scalable to a wide range of objects, and robust to the complexity and diversity of real-world environments. This project will advance and enrich the fundamental research of visual sensing, perception, and learning. Moreover, this project will demonstrate the usability and robustness of the proposed approach in real cyber-physical systems. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NSF Awards · FY 2024 · 2024-08

The objective of this initiative is to enhance student participation at the Great Lakes Symposium on Very Large Scale Integration (VLSI) (GLSVLSI 2024) in Clearwater, Florida, USA, by providing financial support. This support aims to encourage attendance among students across diverse VLSI areas, such as circuits and systems, computer-aided design, emerging computing, hardware security, machine learning, and microelectronic education. Given the diverse expertise of GLSVLSI attendees, spanning various VLSI domains, sponsoring student participation is expected to foster interdisciplinary collaboration and cultivate a dynamic academic community. Through active involvement in GLSVLSI sessions, poster presentations, and networking opportunities, students can contribute to knowledge advancement in their fields while gaining valuable insights from fellow scholars and experts. This travel grant for GLSVLSI 2024 seeks to provide financial assistance to 20 US-based student attendees, covering their registration fees. A portion of the grant, totaling 25%, will be allocated to support diversity, including undergraduates, females, and people from underrepresented populations. This initiative aims to enhance institutional, geographic, and demographic diversity and inclusion within the academic community, ensuring equitable access to scholarly opportunities for students from varied backgrounds. By removing financial barriers and facilitating student participation, the grant facilitates knowledge exchange, collaboration, and the dissemination of research findings, thereby enriching the academic experience of the symposium and advancing both the field and principles of diversity, equity, and inclusion. 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

This proposal aims to develop high-performing, fair, and interpretable large language models (LLMs) to detect Alzheimer's disease (AD) and its precursor stages. In doing so, its overarching goal is to advance healthcare through the innovative and responsible use of LLMs to recognize AD, mild cognitive impairment (MCI), and preclinical AD from transcribed unstructured speech samples, prioritizing fairness in their deployment. Evidence has demonstrated that language is impaired early in AD, including in the MCI and even prodromal AD stage. Moreover, recent natural language processing (NLP) approaches have shown that informative markers of this impairment can be captured from spontaneous speech samples. LLMs, a new cornerstone of NLP, have shown promise at addressing healthcare tasks, but concerns exist regarding their potential biases and poor explainability. We will test the use of LLMs to identify early stages of the AD trajectory from transcribed unstructured speech samples, making fairness and explainability a central piece of our aims. We hypothesize that the use of fair, explainable LLMs for early AD detection may overcome data constraints and interpretability issues common while enabling effective low-resource learning for this purpose. We will test this hypothesis through three aims: (1) building on our shared expertise and prior work, we will design LLM-based models for detecting MCI and dementia and explore their use in detecting the earliest preclinical stage; (2) we will enhance model fairness and interpretability through innovative demonstration example selection and domain-aligned instruction tuning techniques, and develop new methods for explaining LLM output in healthcare settings; and (3) we will validate our methods by assessing their alignment with clinical parameters related to AD and MCI. We will also perform a pioneering exploration of the extent to which our findings are repeatable beyond English settings. Expected outcomes include groundbreaking generalizable insights in NLP and AI fairness and interpretability, and domain-specific advances that could help ensure wide access to AD and MCI detection. This may lay groundwork for a low-cost, scalable, non-invasive alternative for cognitive health screening and reduce healthcare disparities via fairer access to high-quality cognitive health assessment. At an economic scale, this work may reduce long-term burden on the healthcare system and improve quality of life, benefitting individuals and society.

NIH Research Projects · FY 2025 · 2024-07

Colorectal cancer (CRC) is the 3rd most common cancer in the United States for both male and females. Advancements in treatment options are successfully helping CRC survivors (CRCS; post treatment) live longer with currently 1.4 million CRCS in the United States. Despite living longer CRCS are experiencing negative psychological (i.e., cognitive impairments) and physiological (i.e., arterial stiffness) of the disease. CRCS experience impairments in aspects of cognition including cognitive processing speed (CPS), learning and memory, and executive function with CPS being the most impaired cognitive domain. CRCS further experience increased levels of arterial stiffness particularly measures of carotid-femoral pulse wave velocity (cfPWV). Physical activity (PA) is recommended following a cancer diagnosis to improve quality of life, alleviate symptoms of cancer and treatment, and decrease risk for recurrence and development of comorbidities including hypertension, diabetes, and hyperlipidemia; however, levels of PA are reduced in CRCS. In the general population and diseased populations moderate-to-vigorous PA (MVPA) is associated with improvement in various domains of cognition including CPS and better outcomes of arterial stiffness, particularly cfPWV suggesting that MVPA may occupy a similar beneficial role for CRCS and alleviate side effects and improve quality of life and longevity. The proposed cross-sectional, comparative research study is guided by the central hypothesis that CRCS will exhibit (a) worse vascular and cognitive function and lower PA levels than matched controls, and (b) stronger associations among those variables that will support (c) analyses of vascular function as a mediator of the association between PA and cognition in CRCS. The following aims will be tested (1) compare CPS, cfPWV, and MVPA between CRCS and matched controls; (2) examine the associations among CPS, cfPWV, and MVPA; and (3) determine if cfPWV serves a mediator of the association between MVPA and CPS. The following training goals will guide the completion of this study including: (i) didactic and experiential training in the CRC progression, development, treatment options and survivorship; (ii) clinical training in the administration, scoring, and interpretation of neuropsychological tests from the International Cancer Cognition Task Force battery; (iii) educational and clinical training to further understand the clinical application of cardiovascular function and risks; and (iv) research training in the initialization, calibration, data processing, and interpretation of Actigraph accelerometers. The outcomes of this study will highlight the importance of cognition, vascular function, and PA levels and associations in CRCS as well as lay a foundation for future research on PA behavioral interventions in this population. The proposed research and training goals with my collaborating team will help me achieve my short-term goal of completing the proposed study and support my long-term goal of receiving a faculty and research position in the field of exercise oncology.

NIH Research Projects · FY 2026 · 2024-07

The purpose of this K23 Mentored Patient-Oriented Career Development Award application is to support the applicant’s long-term goal to develop an independent research program focused on improving the health and quality of life for adults with chronic kidney disease (CKD) through healthy lifestyle behaviors. Adults with CKD are extremely sedentary, and the poor health outcomes associated with CKD may be modifiable by addressing sedentary behavior- a lifestyle behavior associated with adverse health consequences. Black adults are disproportionately affected by CKD and have some of the worst health outcomes among those with CKD. Theory-based behavioral interventions can effectively reduce sedentary time, but research is lacking on theory-based sedentary reducing interventions adapted to meet the unique needs of the at-risk population of adults of with CKD. The overall goal of this award is to adapt an evidenced-based intervention to reduce sedentary time for adults with CKD guided by patient-centered design. During Aim 1, an evidenced-based sedentary reducing intervention will be adapted to address unique factors that influence sedentary behavior for those with CKD. Adaptation of the intervention will be led by a Patient Advisory Board comprised of Black adults with CKD. In Aim 2, we will conduct a 12-week pilot randomized controlled trial of the adapted intervention (RESET-CKD) to reduce sedentary time for Black adults with CKD. In Aim 3, we will explore the lived experience of the RESET-CKD intervention participants and identify barriers and facilitators to reducing sedentary time. These findings will be used to inform the development of the efficacy trial that will follow this K23 award. Under the guidance of the multidisciplinary mentoring team, the applicant will receive training in clinical trial design and mixed methods to conduct this innovative work and expand the applicant’s program of research. Completion of this proposal will generate data to support an R01 application to conduct a large, randomized controlled intervention to decrease sedentary time and improve outcomes in adults with CKD. This K23 Award will support the candidate’s career development as a nurse scientist by conducting mentored research focused on decreasing sedentary behavior for adults with CKD.

NIH Research Projects · FY 2025 · 2024-07

ABSTRACT Title: WASp signaling in T-cell lymphomas Peripheral T-cell lymphomas (PTCL) are aggressive disorders, with less than 50% overall survival after 2-3 years of diagnosis. These dismal outcomes are in no small part secondary to the limited number of available biomarkers of disease progression and the limited knowledge of T-cell lymphoma biology. Emergent evidence indicates that the actin cytoskeleton plays a pivotal role during T-cell lymphomas' development and growth; however, actin-related proteins' role as actionable targets in T-cell lymphomas still needs to be defined. Our preliminary findings demonstrate that the actin regulatory protein Wiskott-Aldrich syndrome protein (WASp) is associated with decreased event-free survival and promotes T-cell lymphoma growth and survival. In this proposal, we will leverage a genetically engineered murine (GEM) model that develops spontaneous peripheral T-cell lymphomas (SNF5FL/CD4cre), and we will capitalize on an international consortium of more than 100 T-cell lymphoma cases collected with accompanying annotated clinical outcomes, to test the role of WASp during the assembly of actin-dependent signaling complexes upstream of oncogenic transcriptional signaling, and define the role of the tumor microenvironment driving WASp-dependent oncogenic signaling.

NIH Research Projects · FY 2026 · 2024-07

In South Africa’s HIV epidemic, a large proportion of HIV transmission occurs by men (via sex) to women, but men are much less likely to seek HIV testing, and many remain undiagnosed. HIV stigma is a key barrier to recruiting men to HIV testing, as they report feeling blamed by their partners and communities for HIV in South Africa and elsewhere. Stigma must be addressed to increase testing among men and other testing-avoidant people, to locate undiagnosed cases and make progress towards reducing HIV transmission and getting undiagnosed cases into treatment. Peer recruitment is an effective mechanism to promote HIV testing, because people seek health information from peers, and peers influence health behavior norms of networks. However, standard risk network recruitment is limited in that: 1) recruiting one’s own risk partners can trigger stigma and blame for HIV; and 2) it excludes people who have not engaged in HIV risk behavior recently but may have long-term undiagnosed HIV. We developed an “expanded social network recruitment to HIV testing” intervention to address these limitations and reduce stigma as a barrier to testing. Our intervention asks newly diagnosed HIV+ “seeds” to recruit their expanded network members (i.e., anyone they know) who they think could be HIV+ unaware, tests these network members, and refers them to HIV treatment (if positive) or follow-up testing (if negative). By asking participants to recruit non-risk-partners, our intervention aims to increase their comfort and likelihood of recruiting others, especially those who have avoided testing due to stigma. Our pilot studies found that our intervention recruits men to HIV testing at much higher rates than standard risk network recruitment; locates previously undiagnosed cases at a much higher rate per seed; and recruits people who have not tested in years, have never tested, and/or have not engaged in HIV risk behavior recently but are HIV positive-unaware. It also reduces HIV-related stigma and increases HIV-related social support among networks; and 76% of newly-diagnosed intervention participants started HIV treatment within 10 weeks. As participants recruit each other, their discussions help to normalize talking about HIV, thereby improving levels of stigma and support, which in turn should increase HIV service use and improve HIV care cascade outcomes. We will conduct a site-randomized trial of our intervention among 32 Department of Health clinics in KwaZulu-Natal, South Africa. We will compare intervention clinics to business-as-usual control clinics on: their rates of recruiting men to testing (Aim 1a) and locating undiagnosed cases (1b); reported HIV-related stigma and social support (Aim 2a); and treatment cascade outcomes (2b). We will also use qualitative methods and implementation science to develop best practices (Aim 3) for scale-up and adaptation to the U.S. South. Findings of this uniquely cost-effective and time-efficient test of this novel intervention can be used to inform how to reduce HIV transmission and improve timely linkage to care in settings within the U.S. South that have similarly high rates of undiagnosed men and similarly high levels of HIV stigma.

NIH Research Projects · FY 2024 · 2024-07

Abstract COVID-19 increases the risk of vascular contributions to cognitive impairment and dementia (VCID). VCID is one of the most prevalent forms of dementia, so the potential public health impact of the COVID-19 pandemic on future VCID is substantial. However, the mechanisms by which COVID-19 modifies VCID are unknown. Identifying mechanisms that regulate how prior COVID-19 influences the brain endothelial cell response to vascular stress is important. Here, we provide preliminary evidence that COVID-19 decreases resistance to VCID by weakening the blood-brain barrier (BBB). This is accompanied by cerebrovascular inflammation. This grant will test the novel mechanism that SARS-CoV-2 infection accelerates VCID by suppressing cerebrovascular Wnt/β-catenin signaling. In Aim 1, we determine how prior SARS-CoV-2 infection influences BBB permeability and cognition upon subsequent vascular insult, by genetic and epigenetic modification. In Aim 2 we use endothelial-targeted genetic interventions to assess the contribution of Wnt/β- cat targets to resistance to post-infectious VCID. In Aim 3, we ask whether established post-infectious VCID can be reversed by increasing cerebrovascular Wnt/β-catenin. These studies could lead to novel approaches to identify individuals at high risk for VCID and novel potential therapeutic strategies to mitigate the impact of prior infection on the development of dementia.

NIH Research Projects · FY 2025 · 2024-07

PROJECT SUMMARY/ABSTRACT Schistosome parasites infect 200 million people, resulting in significant morbidity and more than 200,000 deaths annually. Schistosomiasis control strategies rely almost exclusively on chemotherapy, and tens of millions of people are treated with the only available drug, praziquantel (PZQ). There are no new drugs in the clinical pipeline. With projected levels of PZQ use, it is inevitable that PZQ-resistant parasites will evolve. Therefore, it is imperative to find new drug targets and drugs for schistosomiasis treatment, our long-term objective. We identified a highly promising drug target: the worm selenocysteine-containing enzyme thioredoxin glutathione reductase (TGR). We established that TGR is a central and essential mediator of antioxidant defenses in the worm. The antioxidant defenses of vertebrates are diversified to three enzymes, glutathione reductase, thioredoxin reductase, and glutaredoxin, whereas schistosomes rely solely on TGR. TGR is a chokepoint and its inhibition leads to rapid worm death in all developmental stages. In contrast, PZQ has poor activity against juvenile worms, often resulting in partial cures. TGR is a defined molecular target, active as a recombinant protein, and we have established biochemical assays amenable to rapid compound screening, SAR, and optimization. We initiated several HTS of large compound libraries, which identified TGR inhibitors that have been used to obtain both liganded and ligand-free crystal structures of TGR, allowing a structure-based approach to hit optimization. These studies have elucidated an inhibitory mechanism that is completely novel for this family of proteins, allowing the development of non-covalent inhibitors. We hypothesize that it will be possible to optimize our novel TGR inhibitors for potency for TGR inhibition and selectivity against human glutathione reductase and thioredoxin reductase enzymes in vitro and schistosomicidal efficacy in vivo, our short-term objectives. Our aims are to optimize novel TGR inhibitors using cutting-edge structure- and ligand-based computer-aided design and medicinal chemistry to improve potency, selectivity, solubility, toxicity, and bioavailability. This will be complemented by X-ray crystallography and cryo-electron microscopy. Medicinal chemistry will be informed by enzymatic analysis of TGR and orthologous human enzymes, metabolic stability, in vitro cell toxicity, and activity against ex vivo worms. Finally, select compounds will be assessed for PK/PD properties and efficacy against schistosome infections in mice. To accomplish these aims, we assembled a team of experts in schistosome biochemistry and drug discovery, medicinal chemistry, computer-aided molecular design, chemical and structural biology of TGR. The varied and synergistic expertise of the team will facilitate overcoming critical barriers to development of schistosomicidal therapeutics. While additional preclinical studies would be needed, discovery of TGR inhibitors with demonstrated activity in animal models is the first step in the development of novel therapeutic approaches for the treatment of schistosomiasis.

NIH Research Projects · FY 2025 · 2024-07

This R34 application responds to RFA-MH-23-260 by adapting and piloting a novel intervention for suicide prevention in primary care for women at moderate or high risk for suicide in a low- and middle-income countries. The study takes place in Tajikistan, a postwar country in Central Asia, where Dr. Weine, Dr. Pirova, Dr. Bahromov, and other collaborators successfully implemented a D43 research capacity building project and an R21 and R01 on stepped care for women’s mental health in primary care. This study also builds on the team’s prior research that demonstrated the effectiveness of nurse- and peer-led interventions, identified risk and protective factors for suicide among women, and on the PREVAIL peer-led suicide prevention model. The specific aims for this new project are: Aim 1: Adapt the evidence-based PREVAIL model into a new SUSTAIN nurse- and peer-led suicide prevention model in primary care for women at moderate or high suicide risk in rural and urban Tajikistan using a participatory co-design process (the Transcreation Framework) with multi-level partners. Aim 2: Evaluate a pilot implementation of the SUSTAIN model in primary care among 96 women with moderate to high suicide risk, 48 randomized to SUSTAIN and 48 to an enhanced usual care condition, with both groups followed for 9 months for suicidal ideations or behaviors, mental health outcomes, and mediators. Aim 3: Assess the acceptability, feasibility, appropriateness, potential for scalability and sustainability, programmatic costs, and partnership of SUSTAIN to inform a future hybrid type 2 effectiveness-implementation pragmatic trial.

NIH Research Projects · FY 2025 · 2024-07

Overall The Great Lakes Center for Occupational Health and Safety/Illinois Education and Research Center (GLC-OHS) has been funded by the National Institute for Occupational Safety and Health since 1977. Our mission is to improve, promote, and maintain the health of workers and communities through innovative and interdisciplinary activities, with the Specific Aims to 1) Educate graduate students for professional practice and/or research and to prepare them to contribute to the advancement of occupational and environmental health, safety, equity, inclusion, and well-being. 2) Prepare OHS professionals to be leaders who expand awareness of and solutions for improving public and worker health, safety, equity, inclusion, and well-being. 3) Enhance the capabilities of employers, worker organizations, government agencies and communities to solve occupational and environmental health, safety and well-being challenges through outreach and technical assistance. 4) Enrich the knowledge base for solving current and future occupational and environmental health safety and well-being issues through academic, research and practice-based experiences. 5) Foster networks of academic, professional and community organizations that advocate for and raise awareness of occupational and environmental health, safety, and well-being issues. 6) Translate and disseminate OHS best practices in partnership with diverse local, regional, national partners and community groups. Our facilities span two campuses of the University of Illinois – the University of Illinois at Chicago (UIC) and the University of Illinois at Urbana-Champaign (UIUC), and multiple colleges on those two campuses including the School of Public Health (SPH), the College of Engineering (COE) and the College of Agricultural, Consumer and Environmental Sciences. The administration of the GLC-OHS is based in the Division of Environmental and Occupational Health Sciences (EOHS) in the UIC SPH. The current GLC-OHS is comprised of 9 programs. With the addition of a proposed reconfigured Targeted Research Training program, we are proposing a total of 10 programs: Agricultural Safety and Health, Industrial Hygiene, Occupational and Environmental Epidemiology, Occupational Medicine, Occupational Safety, Planning and Evaluation, Targeted Research Training – proposed, Continuing Education, Outreach, Pilot Projects Research Training. Degrees offered by the GLC- OHS include Master of Public Health, Master of Science in Public Health, and Doctor of Philosophy. Our trainees are funded with stipends and tuition support, and in addition to their academic programs they participate in robust inter-disciplinary activities. With this proposal we have included new focus on diversity, equity, and inclusion in our recruitment and retention of trainees and faculty, and we have included a new emphasis on training and research on the application of artificial intelligence to occupational safety and health.

NIH Research Projects · FY 2025 · 2024-07

At a time when foundational scientific knowledge is expanding rapidly, there is a critical need to invest in training the next generation of physician-scientists capable of translating scientific discovery into improved patient care. Clinician-scientists serve as vital links between advances in disease pathobiology and innovations in clinical practice. The University of Illinois Chicago (UIC) Medical Scientist Training Program (MSTP) offers a combined MD/PhD training pathway designed to cultivate highly skilled physician-scientists. Established in 2003 and NIH-funded for over 15 years, the UIC MSTP integrates rigorous scientific research training with clinical education, mentoring, and career development. The program’s primary objective is to provide a comprehensive, well-integrated training experience that prepares graduates to lead biomedical research efforts and advance evidence-based clinical care. Trainees explore disease mechanisms at the molecular and cellular level through approaches that include ‘omics’ technologies, whole animal models, clinical studies, and translational research. The MSTP environment is rich with interdisciplinary training opportunities provided by accomplished clinician-scientists and scientist mentors with strong records in research and mentoring. Currently, 102 students are enrolled in the program, selected through a mission-driven admissions process. The entering cohort has five-year average metrics of 3.7 GPA and 514 MCAT, with a matriculation rate of 4% from an average applicant pool of 318. The average time to complete both degrees is 8.0 years, and graduates consistently match into competitive residency programs. Recent programmatic enhancements include: the creation of a structured advising house system to support longitudinal mentoring; development of a new Graduate Education in bioMedical Sciences (GEMS) program with interdisciplinary tracks; expansion of research opportunities through nontraditional PhD pathways; structured mentor training on research core competencies; and implementation of a comprehensive program evaluation system to provide continual feedback on advising, educational, and administrative components. We are confident that the UIC MSTP will continue to develop physician-scientists equipped to advance biomedical discovery and improve patient outcomes. We are requesting continued funding for 10 trainee positions to support this mission.

NIH Research Projects · FY 2025 · 2024-07

Youth brought into the legal system face diminished psychological wellbeing and heightened psychological distress compared with peers who have not been arrested, on average, impairing current quality of life and long-term whole person health. Emotion dysregulation appears to contribute to low wellbeing and high distress on the individual level, and it can be improved via mindfulness meditation. Meditation can be taught by smartphone app, reaching youth on probation in their daily lives. In a prior study (K99/R00DA047890), we collaborated with a range of stakeholders in Chicago Cook County, the 2nd largest juvenile legal system in the U.S., to identify determinants (i.e., barriers and facilitators) of implementing a 1-month mindfulness meditation app with youth on probation, create a multi-component implementation plan, and run a fully remote feasibility clinical trial. Preliminary mixed-methods data strongly supported feasibility, including successful recruitment, enrollment, and randomization of n=50 youth on probation; high objective app usage (i.e., adherence); and high retention at 1 (86%) and 6 (81%) months. Study activities included adapting an app comprised of evidence-based meditation practices for relevance to youth on probation, creating a control app matched for time and structure, and automating systems to identify and re-engage non-users of both apps. Now, our team faces critical barriers to building on these successes and running a fully-powered trial that can produce effectiveness and implementation data generalizable beyond a single site. On the individual level, youths’ backgrounds differ across legal systems; determining if youth from diverse backgrounds will adequately adhere to the meditation app is a key concern. Organizationally, marked heterogeneity across legal systems precludes uniform approaches to recruiting, enrolling, and retaining youth, and can impact health and implementation outcomes. The proposed study will thus expand feasibility testing into 4 rural and urban counties (i.e., sites) in 2 new states: Oregon and New York. Our team will form relationships in each county and conduct theoretically-guided interviews to (a) identify determinants of implementing the meditation app and running the trial at each site, and (b) guide corresponding refinements to our recruitment, retention, and other procedures. Youth on probation (n=120; 30/site) will then be individually randomized to use the meditation or control app for 30 days. Youth will report on health outcomes (wellbeing and distress) at baseline, 1, and 6 months, and complete “bursts” of ecological momentary assessment at baseline and 1 month to capture the mechanistic target (emotion dysregulation) in real time. Also at 1 month, youth, officers, and leadership at each site will interview on feasibility. These mixed-methods data will inform the development of a hybrid type 2 effectiveness-implementation trial spanning diverse counties in Oregon, Illinois, and New York. The present study is thus a carefully-designed step toward promoting scalable programming that holds the potential to improve whole person health and help address health disparities among legal-involved youth.

NSF Awards · FY 2024 · 2024-07

To pursue the promise of the big data revolution, the current project is concerned with a particular form of such data, high dimensional high frequency data (HD2), where series of high-dimensional observations can see new data updates in fractions of milliseconds. With technological advances in data collection, HD2 data occurs in medicine (from neuroscience to patient care), finance and economics, geosciences (such as earthquake data), marine science (fishing and shipping), and, of course, in internet data. This research project focuses on how to extract information from HD2 data, and how to turn this data into knowledge. As part of the process, the project develops cutting-edge mathematics and statistical methodology to uncover the dependence structure governing HD2 data. It interfaces with concepts of artificial intelligence. In addition to developing a general theory, the project is concerned with applications to financial data, including risk management, forecasting, and portfolio management. More precise estimators, with improved margins of error, will be useful in all these areas of finance. The results are of interest to main-street investors, regulators and policymakers, and the results are entirely in the public domain. The project will also provide research training opportunities for students. In more detail, the project will focus on four linked questions for HD2 data: contiguity, matrix decompositions, uncertainty quantification, and the estimation of spot quantities. The investigators will extend their contiguity theory to the common case where observations have noise, which also permits the use of longer local intervals. Under a contiguous probability, the structure of the observations is often more accessible (frequently Gaussian) in local neighborhoods, facilitating statistical analysis. This is achieved without altering the underlying models. Because the effect of the probability change is quite transparent, this approach also enables more direct uncertainty quantification. To model HD2 data, the investigators will explore time-varying matrix decompositions, including the development of a singular value decomposition (SVD) for high frequency data, as a more direct path to a factor model. Both SVD and principal component analysis (PCA) benefit from contiguity, which eases both the time-varying construction, and uncertainty quantification. The latter is of particular importance not only to set standard errors, but also to determine the trade-offs involved in estimation under longitudinal variation: for example, how many minutes or days are required to estimate a covariance matrix, or singular vectors? The investigators also plan to develop volatility matrices for the drift part of a financial process, and their PCAs. The work on matrix decompositions will also benefit from projected results on spot estimation, which also ties in with contiguity. It is expected that the consequences of the contiguity and the HD2 inference will be transformational, leading to more efficient estimators and better prediction, and that this approach will form a new paradigm for high frequency data. 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 · 2024-06

Aligned with the NIMH 2023 Strategic Plan, which highlights suicide prevention and digital health as research priorities, the proposed project is consistent with NIH’s strategic goal to examine mental illness trajectories across the lifespan. The proposed project utilizes high-resolution digital health sleep data in a clinical trial to identify periods of acute suicide risk and potential sleep-related treatment targets, while also examining the impact of the menstrual cycle in these processes. Suicide is a leading cause of death, and it is important for ongoing studies to focus on when patients may be at imminent risk. Emerging research suggests the menstrual cycle and sleep disturbances are time-varying modulators of acute depression and suicidality. The primary mentor’s prior work substantiates a link between cyclical changes in ovarian steroids and suicidality and confirms that most patients recruited for recent suicidal ideation (SI) demonstrate perimenstrual worsening of SI. Further, the laboratory’s two crossover RCTs demonstrate that natural perimenstrual steroid withdrawal serves as a recurring trigger for worsened suicidality and depression that can be reversed with E2+P4 supplementation. However, treatment of this kind is not feasible long-term due to clotting and hormone-dependent cancer risks, so it is critical to identify physiological mediators of these effects which may be treatment targets. Sleep disturbances also predict acute increases in suicidality/depression and there is within-person worsening in sleep perimenstrually suggesting that sleep may be a time-varying physiological mediator for the relationship between the cyclical hormones and suicidality in some people. The proposed study will utilize archival data from the primary mentor’s recently completed R01-funded RCT, which the candidate was instrumental in collecting, in 150 AFAB transdiagnostic patients with suicidality, including 1-3 months of daily surveys, hormonally confirmed cycle phases, and wearable sleep data (Oura ring), to evaluate the role of sleep in perimenstrual exacerbation of SI/depression. The proposed study has several novel aspects: 1) High temporal resolution sleep data across long observation periods; 2) Analytic methods that consider individual differences in cyclical hormone sensitivity and sleep patterns; 3) Experimental ovarian hormone manipulation to establish causality in the relationship between sleep disturbances, cycling hormones, and suicidality/depression. The proposed project will provide clinical trial research experience, training in nomothetic and idiographic statistical modeling, and collaborative mentorship in methods and clinical exposure in sleep and reproductive psychiatry to help the candidate achieve long-term career goals in academic medicine.

NIH Research Projects · FY 2024 · 2024-06

OVERALL PROJECT ABSTRACT The University of Illinois at Chicago (UIC) Maternal Health Research Center of Excellence (Center) will effectively contribute to eliminating maternal morbidity and mortality by taking a system-level approach to addressing maternal health inequity. The Center convenes investigators and leaders from diverse disciplines and embodies decades of maternal health expertise in research, education, and community partnership, including several pioneers in the field of maternal health. The overall goal of the Center is to advance maternal health research by examining the mechanisms by which structural inequity contributes to maternal health disparities and to develop innovative clinical strategies to prevent maternal mortality (MM), reduce severe maternal morbidity (SMM), and promote maternal health equity in partnership with communities. We will move away from a focus on individual outcomes and contributors to inequality and focus on studying ways to leverage systems for large-scale impact. The theme of the Center is to Synergize Multilevel Systems of Change for maternal health equity. The Specific aims include: Aim 1. Conduct robust interprofessional research on maternal health equity, using a multilevel approach, with the goal of decreasing preventable maternal mortality and severe maternal morbidity, and promote maternal health equity among women that experience persistent disparities. Aim 2. Serve as a hub for maternal health career development and work-force training for early-stage investigators interested in research training. Aim 3. Disseminate effective strategies for improving comprehensive postpartum care and innovative research methods to address maternal health inequalities. Aim 4. Serve as a research resource and build a repository of maternal health data (biological, clinical, survey, neighborhood) broadly available for use by researchers. Aim 5. Facilitate and strengthen community partnerships to support the development of, and engagement in, scholarship, dissemination, and translation of maternal health research. The UIC Maternal Health Research Center of Excellence consists of three Cores: Research, Community Partnership, and Training. We propose three complimentary projects: 1) Multilevel exposure to adversity across the life-course; 2) Multilevel predictive modeling for maternal health equity; and 3) Implementing a novel model of postpartum care to improve outcomes in rural and urban community sites (prospective intervention).

NSF Awards · FY 2024 · 2024-06

Ribosomes are molecular machines. They produce cellular proteins. Like a computer that can run different programs, a ribosome can make different proteins encoded in the genetic message. The normal ribosome is generally not well-equipped for making specific designer proteins. The objective of this project is to investigate one approach to creating more effective designer protein production. This will involve the construction of a ribosome that is hard-wired for making one specific protein. This will be achieved by incorporating the genetic message into the ribosome itself. The design of the resulting ribosome could then be optimized to efficiently produce the desired protein. Undergraduates and high school students will participate in summer-long research projects supporting this award. In the cell, ribosomes associate with different mRNAs to synthesize different proteins required for cell growth and proliferation. Expression of designer proteins that do not contribute essential functions for cell metabolism acts to divert ribosomes away from producing those essential proteins. Diverting ribosomes in that way can reduce the fitness of the cell to grow and multiply. The strategy being tested is functional isolation of such ribosomes from ‘normal’ cellular translation. The isolation will be achieved by covalently attaching mRNA to ribosomal RNA. The resulting ribosome-mRNA hybrid (iRibo-T) is expected to translate only one specific mRNA and, therefore, is suitable for altering its catalytic capacity and other properties. The new design will be employed for optimizing expression of medically and industrially relevant poly-lysine containing proteins whose translation are problematic for the unaltered bacterial ribosomes. 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 · 2024-06

In the digital age, the ability to identify anomalies quickly and accurately within massive datasets is critical for ensuring the safety, security, and efficiency of numerous sectors, including healthcare, national security, and finance. Anomalies, which represent deviations from the norm, can indicate critical issues such as potential security breaches, health crises, or financial fraud. The open tools and systems for anomaly detection (AD) are often fragmented, complex, and not easily accessible. This project aims to revolutionize this landscape by developing an integrated, open-source ecosystem that simplifies AD. By making advanced detection tools widely available and user-friendly, the OpenAD ecosystem will empower researchers, businesses, and public institutions to leverage the full potential of AD. This project seeks to unify existing AD systems into a comprehensive ecosystem that supports diverse data types and application domains. This ecosystem will integrate a wide range of open-source AD tools, including those for tabular, graph, and time-series data, and provide a platform for seamless integration of model evaluation, automation, and acceleration. The project's goals include developing a standardized development environment, enhancing tools for automating and accelerating detection processes, and establishing a governance structure to guide community contributions and project evolution. By leveraging the collective expertise of a diverse community of developers, researchers, and users, OpenAD aims to overcome current limitations in AD. The resulting ecosystem will not only facilitate more effective and efficient detection of anomalies across various domains but also foster innovation and collaboration within the scientific community. Through OpenAD, AD tools will be more accessible, powerful, and capable of addressing the complex challenges of the increasingly data-driven world. 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.