University Of Illinois At Chicago

NSF Awards · FY 2024 · 2024-09

This project focuses on the mathematical area of probability theory, the study of random structures. Random structures are ubiquitous throughout the sciences for their use as models as well as their use in the design of algorithms. The main focus of this project is on random structures in high dimensions, meaning random structures with many degrees of freedom. Some examples are random matrices, random sphere packings and random polynomials. Each of these classes of models has direct application in various other scientific fields such as data science, statistical physics and theoretical computer science. The project includes workshops for early-career researchers and graduate students, with an aim of bringing together disparate mathematical subfields. The project consists of three components, with specific problems chosen with the aim of developing new techniques in high-dimensional probability and the use of analytic approaches in probability theory. The first component of the project concerns universality properties of random polynomials along with their use in optimization and algorithmic problems. The second component focuses on the structure of random sphere packings using connections to more combinatorial objects such as independent sets. The third component studies the non-asymptotic theory of random matrices with a focus on extremal behavior such as understanding the behavior of the least singular value in models without independent entries. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NSF Awards · FY 2024 · 2024-09

The National AI Research Resource (NAIRR) workshop aims to establish an accessible AI software stack that democratizes AI capabilities and empowers diverse users. By bringing together academics, researchers, and industry experts, the workshop will address immediate and long-term objectives for the NAIRR pilot, pinpointing critical components for various scientific research domains. Focus areas will include real-time data analysis, AI-based decision-making, privacy, security, and software portability across emerging AI hardware platforms. This collaborative effort is designed to ensure that the resulting AI software stack meets the needs of a broad spectrum of users, from beginners to experts, fostering an inclusive AI ecosystem. The workshop's outcomes will emphasize the creation of ethical, transparent, and trustworthy AI software tailored for scientific research. The workshop aims to foster innovation, enhance diversity, and ensure equitable access to AI resources by leveraging existing software stacks from academia, national laboratories, and industry. Discussions will address user-support needs, funding requirements, and procedures for incorporating new software developments into the NAIRR stack. The workshop will culminate in the production of a comprehensive report detailing the necessary AI software stack to serve users ranging from beginners to experts, thereby fostering an inclusive AI ecosystem. This effort will lay the foundation for a robust, democratized AI research infrastructure, driving innovation across the U.S. AI landscape. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NIH Research Projects · FY 2025 · 2024-09

Hepatic fibrosis is a major cause of mortality in patients with non-alcoholic steatohepatitis (NASH). Hepatic fibrosis also plays a major role in the development of hepatocellular carcinoma (HCC, which is a second leading cause of cancer mortality world-wide. Hepatic stellate cells (HSCs) that generate hepatic fibrosis are activated by liver injury, but the mechanism of their activation is not fully understood. Upon activation HSCs start expressing genes such as alpha-smooth muscle actin (aSMA) and collagen type 1a1 (Col1a1), which are markers of hepatic fibrosis. Upon activation HSCs become highly glycolytic and consequently produce high level of lactate. Lactate has been suggested to play a role in regulating gene expression upon HSCs activation, but the mechanism remains elusive. We found that high glycolysis and lactate production in activated HSCs is largely due to the induction of hexokinase 2 (HK2) expression. Our results show that HK2 is required for the activation of HSCs and liver fibrosis. Interestingly, we found that lactate produced, because of HK2 expression, induces histone lactylation, which is required for gene expression in activated HSCs. In the absence of HK2 the induction of gene expression is impaired in HSCs, but lactate could override the effect of HK2 deletion on gene expression. We also found that HK2 deletion in hepatocytes attenuates NASH-induced hepatocarcinogenesis. Therefore, our results suggest that targeting HK2 could be therapeutic for both liver fibrosis and NASH-induced HCC. In this grant application we will further validate the role of HK2 in liver fibrosis and how it affects NASH-induced HCC. We will employ a mouse model of NASH-induced HCC in which there is extensive fibrosis. We will use these mice to study the role of HK2 in the interplay between liver fibrosis and HCC. Finally, as a proof of concept, we will verify if systemic HK2 deletion, which does not elicit adverse physiological consequences, could inhibit both fibrosis and HCC in a mouse model of NASH-induced HCC.

NIH Research Projects · FY 2025 · 2024-09

Abstract This is an application to the Countermeasures Against Chemical Threats (CounterACT) NIH-wide program part of the Chemical Countermeasures Research Program. Sulfur mustard (SM), a chemical warfare agent, and nitrogen mustard (NM), a chemotherapeutic agent, are both potent vesicants. The cornea is exquisitely sensitive to these agents leading to keratitis, vascularization, ulceration, and perforations. Following acute SM exposure, a subset of patients will experience chronic/delayed-onset ocular complications known as mustard gas keratopathy (MGK). Delayed MGK reportedly can manifest several years after the initial exposure and presents with severe corneal disease with significant visual loss. We have made the observation that in experimental animal models of NM injury to the cornea, there is dose-dependent increased senescence in the cornea. We hypothesize that senescence in the cornea promotes tissue dysfunction and inflammationand that senescence after mustard injury contributes to the progression of chronic MGK and the severity of delayed MGK. We further hypothesize that reducing/eliminating senescent cells may alter the progression and severity of MGK. In this application we propose in Aim1 to investigate the role of senescence and SASP in the progression of corneal disease following acute exposure to NM; and in Aim 2 to investigate the role of senescence in a new model of delayed MGK. At the conclusion of these studies, we expect to have an improved understanding of the role of senescence in the development of MGK and identify novel approaches for its prevention/treatment.

NSF Awards · FY 2024 · 2024-09

Cities are loci of resource consumption, economic activity, and innovation. Given the increasing ability to collect, transmit, store, and analyze data, there is the opportunity to go beyond today’s understanding of cities to enable better operations, better planning, and better policies. While there are already troves of open data about cities, their potential remains underexplored because of unique challenges related to the diversity and scale of urban data and the complex computations required to obtain trustworthy insights. This project builds tools and infrastructure that meet the unique requirements of urban computing. The open-source cyberinfrastructure supports data-driven exploration and empowers a broad range of stakeholders to analyze and model urban data at scale. This cyberinfrastructure serves as a catalyst to create and sustain a cohesive community around urban computing. By enabling sharing and collaboration, this cyberinfrastructure also streamlines and advances urban research and democratizes urban computing. The project includes activities and mechanisms to engage the community and integrate the results to support education. This project addresses two critical obstacles in urban computing: (1) the lack of documented, robust, well-engineered tools and open computing platforms and (2) the dispersed community of cross-disciplinary researchers and developers, which limits knowledge sharing and collective solutions. A core component of the project is the development of a cyberinfrastructure that integrates methods and tools for the exploration of urban data that are scalable, reusable, and interoperable, and solutions to common challenges, including data discovery, cleaning, analytics, modeling, visualization, and reproducibility. The project deploys a cloud-based, open, collaborative environment that supports the use of this infrastructure over large and diverse urban data sets, allowing communities of users to quickly create analyses that are reproducible by design and that can be debugged, shared, and extended. The intellectual merit lies within the novelty of the tools and techniques it produces, as well as in the software engineering challenges involved in developing, maintaining, and supporting cyberinfrastructure that will be deployed and widely adopted. This Office of Advanced Cyberinfrastrucure project is jointly funded by the Cyberinfrastructure for Sustained Scientific Innovation (CSSI) program and the National Discovery Cloud for Climate (NDC-C). This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NSF Awards · FY 2024 · 2024-09

The broader impact of this I-Corps project is the development of a drug to mitigate/recover from long-term neurotoxic side effects of radiation. This technology holds promise in managing radiation injuries during cancer treatment. By targeting mitochondrial dysfunction and promoting the growth of neural progenitor cells, the approach aims to address radiation induced injuries during surface cancer therapy. This technology may also help mitigate/recover from long-term neurotoxic side effects of radiation. Cognitive impairment and white matter disease are common concerns in patients undergoing radiation therapy; Protecting or regenerating neural progenitor cells may alleviate these issues. This approach could enhance patient outcomes and improve quality of life. Potential markets include patients with surface cancer (i.e., breast, head, and neck cancers). This I-Corps project utilizes experiential learning coupled with a first-hand investigation of the industry ecosystem to assess the translation potential of the technology. This solution is based on the development of a drug to mitigate/recover mitochondrial dysfunction from long-term neurotoxic side effects of radiation. This technology represents a groundbreaking approach in the management of radiation injuries as it has not been explored previously. Radiation damages critical tissues. Agents that are safe and promote neural progenitor cells growth in affected areas may promote tissue repair and regeneration. This effect may not only replace damaged cells faster but also modulate the inflammatory response. Moreover, the product can cross the blood-brain barrier, reaching brain regions affected by radiation and offering localized repair. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NIH Research Projects · FY 2025 · 2024-09

ABSTRACT The acute respiratory distress syndrome (ARDS) is characterized by pulmonary vascular leak and flooding of the normally air-filled alveolar space with protein rich edema fluid and causes severe hypoxemia, respiratory failure and death among critically ill patients. Identification of genetic factors which modify the risk of developing ARDS or influence clinical outcomes may improve our pathologic understanding of this disease. Human variants in the gene LRRC16A are implicated in improved ARDS outcomes but the mechanism remains unknown. LRRC16A encodes capping protein, Arp 2/3 and myosin-I linker (CARMIL1), a cytoskeletal regulatory protein which has been studied primarily in cell motility. CARMIL contributes to peripheral actin polymerization by antagonizing capping protein at the end of growing actin strands. Decreased CARMIL expression slows cell migration by attenuating protrusion of the cell membrane. Maintenance of pulmonary endothelial cell (EC) barrier function is critical to prevent lung vascular leak. Cytoskeletal rearrangement and force generation determine barrier integrity through dynamic changes to the plasma membrane and cell shape. Peripheral actin polymerization protrudes the endothelial cell membrane to increase contact with neighboring cells, reduce intercellular gaps and increase barrier function. We hypothesize that CARMIL1 is a key regulator of peripheral actin structure and branched actin polymerization which facilitate membrane protrusion to determine EC barrier function. This proposal will use complementary biochemical, imaging and functional studies to characterize the role of CARMIL1 in EC barrier function. We will investigate CARMIL1 in the context of known regulators of endothelial cytoskeletal and membrane dynamics to improve our understanding of the mechanisms responsible for pulmonary vascular leak. Specific Aim 1 will investigate the role of CARMIL1 in EC peripheral actin structures and dynamics by employing biochemical and advanced imaging techniques after CARMIL1 silencing and/or overexpression of wild-type or variant constructs. Specific Aim 2 will determine the effect of modified CARMIL1 expression on EC barrier integrity using multiple assays of local and global permeability. Specific Aim 3 will characterize the function of endothelial CARMIL1 in murine lung injury. Endothelial specific delivery of siRNA and lentiviral constructs will investigate the effect of CARMIL1 manipulation on the intact lung vasculature following inflammatory or infectious insults. These studies will provide novel mechanistic insights into the cellular mechanisms of ARDS and provide a link between CARMIL1 variants and clinical outcomes. This knowledge has the potential to identify new therapeutic targets and improve the care of future patients.

NSF Awards · FY 2024 · 2024-09

Research supported by this grant focuses on the science of electrified ejection, transport, and vaporization dynamics of nanodroplets, which constitute very small volumes in the yoctoliter-to-zeptoliter (i.e., 10-24 to 10-21 liters) range. The new knowledge gained will be leveraged to yield an all-on-a-chip, integrated circuit compatible nanomanufacturing technique with efficiencies in pattern resolution, operating power, cost, and system complexity. This technique has the potential to find use in diverse industries such as integrated circuits, micro-/nano- electromechanical systems, flexible electronics, touchscreen, industrial spraying, and security printing. The project will train students on interdisciplinary topics such as chip fabrication, materials science, nanotechnology and electrohydrodynamics. Further impacts will be achieved through K-12 centered outreach programs that include emphasis on minority and underrepresented students, organization of a Summer School on Nanomanufacturing, and engagement with the industry as a part of technology transfer initiatives. Overall, the scientific contributions and broader impacts of this project will advance economic prosperity and national security through technology as well as workforce development in nanomanufacturing. The research objective of this project is to test the hypothesis that nanoscopic miniaturization and monolithic, on-chip electrification of nozzles in a nanoelectrohydrodynamic printer will yield a transformative new performance regime of sub-continuum nano-dripping. In this regime, droplets with diameters smaller than 20 nanometers will be extracted using ultra-low electric stresses to additively print three-dimensional, solid-state patterns in the deep-nanometer size regime. While electrohydrodynamic droplet ejection at the micro- and macro-scales arises from a combination of fluid surface tension, electric, viscous and inertial forces, continuum theory does not adequately explain meniscus instability in the deep-nanometer regime where thermal fluctuations at the liquid-air interface and electrokinetic contributions have been predicted to play a significant role. The project's hypothesis will be tested using a synergistic combination of coupled-physics experiments and mesoscale Many-body Dissipative Particle Dynamics simulations involving a Scanning Nanodroplet Additive Printer-on-a-Chip (SNAP-Chip). SNAP-Chip will miniaturize both the nozzle and the nozzle-electrode gap by at least an order of magnitude in comparison to micron-scale geometries of prior art through the fabrication of a droplet generator on a silicon substrate. This miniaturization makes sub-continuum nano-dripping experimentally accessible and will be employed to print features that are sized as low as single-digit nanometers in three-dimensions. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NIH Research Projects · FY 2024 · 2024-09

PROJECT SUMMARY This proposal seeks to understand and predict the onset and duration of the menopause transition using a Systems Metabolic approach. Menopause, which is the complete cessation of menstruation, increases the risks of cardiovascular disorders, osteoporosis, depression, and cognitive decline. The menopause transition, occurring roughly 3-5 years before menopause, in same cases it can last up to 10 years, is marked by reduced quality of life due to symptoms like hot flashes, sleep problems, migraines, lack of concentration, and irritability. Current clinical tools such as Anti-Mullerian Hormone (AMH) or Follicle Stimulating Hormone (FSH) can detect whether the menopause transition has already started but cannot estimate its commencement or duration. Identifying better biomarkers is challenging due to the complex spatial and temporal heterogeneity of the ovary, compounded by the presence of different cell types in the ovary such as somatic (e.g., estrogen producers), stromal, immune, epithelial, and endothelial cells. To understand the role of ovarian spatiotemporal heterogeneity in the menopause transition and the decline of reproductive potential, a systems approach is needed to consider spatial and age-dependent inter- and intra-cellular signaling and metabolic communication within the ovary. Genome-scale metabolic models (GMMs) are network-based systems approaches that have been used to study inter- and intra-cellular metabolic communication in the ovary. While current ovarian GMMs are cell-specific and multicellular, they have not accounted yet for cell location within the ovary or explored ovarian aging, both crucial for understanding the menopause transition. We plan to address these limitations by generating spatially- informed cell-specific multicellular GMMs) to identify ovarian-produced metabolites that can be secreted into circulation and are significantly associated with the state of the menopause transition, and hence could serve as novel biomarkers of reproductive potential its rate of decline. Our long-term goal is to create a platform for early prediction of menopause transition onset and duration to reduce the risk of menopause-related diseases. Our overarching hypothesis is that the integration of dynamic multi-omics data (single-cell and spatial transcriptomics and non-targeted metabolomics) with prior metabolomic knowledge encoded into GMMs could serve to identify novel metabolic markers of reproductive potential and its rate of decline. Test this, we aim to develop spatially- informed cell-specific multicellular GMMs using publicly and newly collected single-cell and spatial transcriptomics data from prepubertal (3 weeks) to reproductive aged mice (18 months); and identify ovarian- synthesized metabolites measurable in circulation and significantly associated with reproduction potential and its rate of decline. Success in this proposal could identify minimally-invasive biomarkers that can prospectively predict the rate of decline in reproductive potential and lay the groundwork for future interventions to delay early or premature menopause, alleviate symptoms, and reduce the risk of future menopause-related diseases. Our dynamic spatially-informed network-based models could be applied to study aging in other organs, e.g., brain.

NIH Research Projects · FY 2023 · 2024-08

Project Summary Rates of alcohol use and misuse are increasing faster among older adults than among any other age group. Simultaneously, the prevalence of heart failure (HF), a major cause of reduced lifespan and health span among older adults, has also been increasing. It is possible that alcohol use and misuse exacerbate and accelerate HF, both directly via biological mechanisms and indirectly by hindering the ability to engage in the rigorous self-management required to avoid adverse health outcomes. If so, addressing alcohol use and misuse among older adults with HF has the potential to substantially improve morbidity, mortality, and quality of life for this population. Yet, despite these hypotheses, little is known about the effects of alcohol use and misuse among older adults with HF nor about the alcohol-related care received by this population. The specific aims of this application are to use rigorous causal inference and machine learning methods to 1) estimate the relationships of alcohol use and misuse with HF self-management behaviors for the first time and 2) produce less biased and more generalizable estimates of the relationships between alcohol use and misuse and adverse HF outcomes, which are currently poorly understood. In addition, we will 3) characterize the quantity and sources (venue, provider specialty, length of patient-provider relationship, provider participation in Accountable Care Organizations) of documented alcohol-related care currently received by older adults with HF. To accomplish these aims, we will utilize a linkage of two existing data sources: Medicare fee-for-service claims and the Health and Retirement Study (HRS), a nationally representative longitudinal panel of 22,000+ older adults. The research will be accomplished by a strong team of experts in alcohol use and misuse, cardiovascular conditions, aging populations, mental health care coordination, and analyses of Medicare claims and HRS. This research has the potential to inform critically needed evidence-based guidelines for clinical management of HF patients as well as future research developing interventions and policies that will improve the delivery of alcohol-related care and overall health outcomes among this population. As such, it helps advance NIAAA’s strategic goal of identifying and reducing alcohol’s influence on health and disease throughout the lifespan. It also responds directly to NIAAA Notice of Special Interest NOT-AA-20-018 “Secondary Analyses of Existing Alcohol Research Data.”

NIH Research Projects · FY 2025 · 2024-08

Project Summary/Abstract South Africa has the greatest burden of HIV infection in the world, and South African adolescent girls and young women (SA-AGYW) ages 15-24 are at greatest risk. Mental health distress (anxiety, trauma, depression) and intimate partner violence (IPV) are implicated as drivers of HIV, yet few studies have assessed the combined effects of mental health and IPV on SA-AGYW sexual risk behavior (early sexual debut, no condom use at last sex, multiple sexual partners). Notably, high warmth and frequent communication about sexual topics between female caregivers and AGYW are associated with reduced AGYW sexual risk behavior, but few studies have examined the impact of female caregiver-AGYW communication and warmth in the presence of mental health distress and IPV on AGYW sexual risk taking. The proposed fellowship will provide much needed training to prepare me for a career as a physician scientist with a global health program of research. Guided by an expert mentorship team to oversee my training activities, I will gain skills in adolescent and young adult mental health distress, sexual risk behaviors, and their roles as drivers of HIV infection, HIV epidemiology, advanced qualitative research, and complete my medical and PhD degrees. I will use these new skills to carry out a mixed methods research study integrating quantitative and qualitative methods to accomplish two specific aims. In Aim 1, I will conduct secondary analyses of baseline data from a large HIV prevention intervention involving SA-AGYW and their female caregivers (IMARA-SA). Analyses of 642 AGYW will examine mental health distress, IPV, and AGYW-caregiver warmth and communication as drivers of AGYW sexually transmitted infections, including HIV. Preliminary data from the parent study revealed high rates mental health distress and IPV. I hypothesize that increased warmth and communication between AGYW and female caregivers will decrease the association between mental health distress and sexual risk behaviors even in the presence of IPV. In Aim 2, I will supplement the quantitative analysis with 20- 30 qualitative interviews with SA-AGYW with experiences of IPV. I will purposively select participants from the parent study who have completed the 12-month follow up and reported IPV. Interviews will offer new insight into the impact of female caregiver communication about addressing experiences of IPV and sexual risk behavior. The findings from aims 1 and 2 will inform interventions to improve the SA-AGYW mental health, lessen IPV exposure, and strengthen sexual and reproductive health. Mentorship provided by an experienced team with a long history of collaboration will ensure excellent training, extensive opportunities to publish in high impact journals and present at international scientific conferences, and exposure to colleagues through networking. This F30 fellowship will provide a well-rounded education that empowers me to become a physician-scientist with a program of research focused on AGYW sexual and reproductive health.

NIH Research Projects · FY 2025 · 2024-08

Alzheimer’s disease (AD) is the most common cause of dementia worldwide. Ninety five percent of AD cases are sporadic late onset (LOAD) of unknown cause. Aging is the greatest risk factor of LOAD. Pathologically, AD is characterized by brain aggregates of β-amyloid (Aβ) and neurofibrillary tangles. Clinically it is characterized by progressive memory loss and cognitive deficits. Hippocampal-dependent episodic memory is the earliest deficit to be clinically detected and the most severely impaired throughout disease progression. Adult hippocampal neurogenesis (AHN) is an integral process for hippocampal memory formation that occurs in the dentate gyrus (DG). We and others have shown that AHN is impaired in AD mouse models and patients. Several genome-wide association studies (GWAS) have identified PICALM, the gene encoding for Phosphatidylinositol Binding Clathrin Assembly Protein, as a genetic risk factor for LOAD. However, how PICALM polymorphism induces pathology and memory loss is yet to be fully understood. My preliminary studies show that PICALM is expressed in neural stem and progenitor cells (NSPCs) in the mouse hippocampus, as well as in neurons derived from human induced pluripotent stem cells (iPSC), and its expression appears to be stage-specific. Further, knocking out PICALM in iPSC- derived neural progenitor cells, precursors and new neurons reduced levels of b- III-tubulin and neurofilament, suggesting that PICALM regulates neuronal maturation. Additionally, the ratio between the mature and immature form of b-Amyloid precursor protein (b-APP) was altered in PICALM KO cells throughout neurogenesis stages, suggesting that PICALM regulates b-APP metabolism. Interestingly, levels of PICALM in the hippocampus of adult mice are significantly reduced with age, while its cleavage products are increased. Thus, we hypothesize that PICALM regulates AHN and b-APP metabolism, and that altered expression of PICALM in NSPCs in LOAD impairs AHN and contributes to amyloidosis and hippocampus-dependent memory deficits. To address this hypothesis, experiments in Aim 1 will examine the role of PICALM in AHN using a conditional knockout of PICALM in AHN in mice and determine its role in AHN-dependent learning and memory. Aim 2 will elucidate the role of PICALM in impaired neurogenesis and amyloidosis in AD in iPSC- derived human forebrain neurons harboring PICALM polymorphisms and PICALM knockout. These experiments will provide new information about a novel regulator of hippocampal neurogenesis and a mechanism by which AHN is impaired in LOAD and contributes to pathology and memory loss.

NIH Research Projects · FY 2025 · 2024-08

PROJECT SUMMARY Senescent cells (SnCs) accumulate in tissues with increased organismal age. SnCs have been associated with multiple age-associated chronic diseases and implicated as contributing pathological factors in Alzheimer’s disease (AD). Brain vasculature aging contributes to AD progression and vascular dysfunction is observed early on in the disease. Recent studies suggest that endothelial senescence impairs the barrier function of the brain endothelium. However, SnCs within the brain vasculature have not been studied in the context of AD. I examined multiple human and mouse single-cell RNA-seq datasets from organisms of different ages to create a resource that identifies SnCs in different cell types and tissues. My preliminary data indicate that the brain vasculature has an increased SnC burden in AD and that the blood-brain barrier expresses receptors for SnC signaling. However, the phenotype and molecular signatures of AD-associated SnCs have not been resolved. I hypothesize that senescent brain vascular cells have distinct and targetable molecular patterns and that their disruptive effect on healthy vascular cells can be lessened by interrupting specific SnC signaling pathways. Moreover, I have shown that transposable elements and human endogenous viral elements are upregulated in endothelial inflammation, cellular senescence, and AD. Transposable elements differentially regulated in endothelial inflammation were co-expressed with important inflammatory and senescence regulators, such as NFKB and CDKN2A. I hypothesize that transposable elements expressed during inflammation and senescence contribute to sterile inflammation and loss of blood-brain barrier integrity. I will transcriptionally characterize SnCs within the brain vasculature of human AD patients and mouse models by examining existing single-cell AD datasets. I will find unique patterns of mRNA expression, regulatory mechanisms, and cell-cell interactions specific to AD- associated SnCs. I will train a semi-supervised convolutional neural network to identify senescent cells within the AD brain vasculature. I will test how SnC signaling contributes to AD by ablating receptors required in SnC signaling in brain microvascular endothelial cells with CRISPR-Cas9 then test the effect on barrier integrity in the presence of SASP molecules. Next, I will find transposable elements uniquely expressed in senescent brain endothelial cells and bystander cells during AD. I will uncover regulatory mechanisms within the cells that contribute to the aberrant activation of transposable elements and examine the pathways these elements activate that contribute to barrier dysregulation. I will test how shRNA knockdown of expressed transposable element RNA affects the inflammatory and barrier phenotypes in brain endothelial cells. The proposed studies will teach me multiple computational approaches, such as machine learning, as well as advanced genetic manipulation in cells and animal models.

NSF Awards · FY 2024 · 2024-08

The abundance of data, coupled with recent advancements in computation, has revolutionized almost every aspect of modern life, and the central role of data structures in this revolution is undeniable. As data-driven technologies root in our lives, their drawbacks and potential harms when they make biased decisions become increasingly evident. To resolve such bias issues, this project revisits classical approximate query processing data structures through the lens of fairness. It envisions a future where fairness is a first-class citizen of database systems, where the potential fairness issues of database indices are identified and resolved. The project has the potential to involve under-represented minorities who find algorithmic fairness an interesting topic to which they can contribute. To effectively accomplish its objective, this project aims to design data structures with theoretical guarantees that achieve group fairness across domains such as hashing, membership estimation, aggregate query estimation, and approximate ranking and selection query answering. The ultimate objective is to develop a system for fair data structures for approximate query processing that can readily integrate into existing data management systems. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NIH Research Projects · FY 2025 · 2024-08

PROJECT SUMMARY Distal (or small) airways including the terminal and respiratory bronchioles (TRB) are the sites of damage in several lung diseases. Pathologies of small airway lesions are poorly understood as the cellular composition and properties of TRB regions are yet to be fully characterized. Respiratory bronchioles (RB) are extremely small airways, about 200 µm in diameter. Importantly, the anatomy of mice – the most commonly used model organisms – is significantly different in these regions. Murine lungs lack RBs, and their terminal bronchioles open directly into alveoli at the bronchio-alveolar duct junction (BADJ). These challenges have resulted in RBs remaining as a black box of human lungs. We optimized microdissection protocols to enrich RBs from human lungs and generated single-cell transcriptomic maps. We identified seven novel cell populations in the TRB regions. Importantly, we show that these cells have no equivalent cell types in mice. All these data point towards the need to develop new models to effectively understand small airways in health and disease. We show here in our preliminary data that primary human stem cell cultures well capture the small airway biology. Further, we find that small airways of ferrets have similar cellular composition to those of humans suggesting that they can serve as a model to study small airways. Utilizing these two models coupled with single-cell transcriptomics we propose to address the following specific aims. 1) Delineate the terminal and respiratory bronchiolar epithelial lineage trajectories. 2) Study the cell-intrinsic transcriptional networks that maintain distal basal cell identity. At the conclusion of this study, we would have significantly advanced our understanding of human terminal and respiratory bronchioles. We will develop the first TRB-specific lineage tracing model in ferrets. Our study will determine the cell-intrinsic mechanisms that determine TRB stem cell identity and progeny. These results will assist in developing effective therapies for diseases involving small airways.

NSF Awards · FY 2024 · 2024-08

This research project is at the forefront of addressing security vulnerabilities in resource-limited, normally-off energy harvesting devices widely utilized across various Internet of Things (IoT) applications. Ranging from wearable devices to remote sensing and industrial systems, the potential impact of securing these devices is significant. The project's novelties are its focus on discovering the inherent vulnerabilities of these devices, including physical attacks, unanticipated power outages and failures, and other unique threats, and proposing effective solutions for them. Exploiting these vulnerabilities could lead to irreparable damage to property and lives, considering the extensive network of connected devices. The project's broader significance and importance lie in the critical need for comprehensive, lightweight defense strategies, as the existing ones either exhibit high overheads or are incomplete, rendering them unfit for resource-constrained nodes. The technical approach of this research revolves around the development of Secure Intermittent-Robust Computation (SIRC) for these computing nodes. This is achieved by capitalizing on emerging non-volatile (NV), spin-based devices to construct lightweight reconfigurable logic. The assurance of intermittent-robust computation during various attacks is facilitated by storing intermediate circuit values in NV devices. Concurrently, the research employs innovative circuit-architecture-algorithm techniques, promising notable advances in the domain of IoT security. This research effectively bridges the gap between the ever-present security threats and the limitations of current defense schemes, marking a significant stride toward the resilient future of IoT applications. 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

Freezing of drops on cold surfaces or Sessile-drop freezing (SDF) is ubiquitous in the natural and industrial world, impacting various applications such as icing on surfaces, freeze casting, and desalination. The presence of solutes like salt, organic materials, or particles within the water can significantly influence freezing behavior. While pure water droplet freezing has been extensively studied, there is limited understanding of how solute-laden droplets freeze, especially under microgravity conditions found in space. This research will focus on understanding how solutes affect the freezing of water droplets in the International Space Station (ISS) microgravity environment. By eliminating the effects of gravity, this work aims to gain clearer insights into the fundamental processes. This research could lead to significant advancements in our understanding of freezing dynamics, with potential benefits including developing better anti-icing coatings, improved manufacturing processes using freeze casting, improved methods for desalinating impure water using freezing, and enhanced models for ice formation in the environment. This project also aims to foster educational opportunities for undergraduate students, particularly those from underrepresented communities, by engaging them in hands-on experimental and computational work, thereby cultivating a diverse and skilled workforce equipped to tackle future scientific and engineering challenges. This award aims to elucidate the roles of gravity on the freezing dynamics of sessile drops in the presence of soluble and insoluble particles. This project involves several key tasks: fabricating samples and solutions for ISS experiments, coordinating with NASA implementation partners to prepare the experimental rig, overseeing test runs and final experiments at the ISS, and conducting thorough data analysis. Additional tasks include obtaining on-ground SDF results with varied surface orientations and performing phase-field simulations to understand freezing dynamics, shape evolution, solute segregation, and solutal Marangoni flows inside droplets with and without gravity. Advanced characterization techniques, such as optical/infrared imaging, micro-computed tomography, and computational studies, will enable a comprehensive analysis of these phenomena and the development of accurate freezing models. The research outcomes are expected to inform the development of novel anti-icing coatings, advance manufacturing processes like freeze casting, and create new freezing desalination systems. The high-quality experimental data from the ISS will also help improve existing freezing models. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NSF Awards · FY 2024 · 2024-08

Cloud-based computation and communication encounter several severe challenges, including high latency, questionable scalability, quality of service, privacy, and security. These issues can be addressed by transitioning computing architecture from a traditional cloud-centric mindset to a thing-centric (data-centric) perspective. However, nearly 90% of the data generated by the Internet of Things (IoT) is not analyzed using the conventional mechanism, due to limited computing ability and constraints in power and area. Hence, resource-limited IoTs should be developed optimally to enhance overall performance and extend lifetime. Our objective in this project is to transition from the conventional paradigm to a Sense-Decide-Action mechanism, which can analyze data locally, autonomously, and sustainably instead of sending it to the cloud, thereby reducing the amount of communication via a new cross-layer co-design approach. The broader impact and significance of our project lie in systematically paving the way for innovative foundational computing schemes. These strategies enable efficient instant computing and the necessary design approaches for real-time processing and decision-making systems. This progress brings us closer to the reality of accommodating over a trillion interconnected devices and improving the data privacy of resource-limited IoTs for critical applications, including healthcare monitoring, automotive applications, and industrial sensing. The technical approach of this research revolves around the development of low-overhead strategies to accelerate edge intelligence sensory nodes' autonomous operation within an environment. This is achieved by (1) designing and analyzing non-von-Neumann architectures, co-integrating conversion and processing capabilities in conjunction with an unconventional number system to alleviate the existing data movement issue between off/on-chip and processor; and (2) implementing processing units for both generic computations and domain-specific and emerging applications. This automated process of architecture engineering creates search space, defines design strategy, and identifies the optimal architecture to improve metrics such as lifetime energy reduction and overall performance. We evaluate the functionalities and performance of the proposed Thrusts through extensive modeling and simulations, beginning from circuit-level design and progressing upwards. This research effectively establishes novel lightweight heterogeneous edge intelligence capable of autonomously processing various data and compute-intensive tasks in an energy-scarce environment, marking a significant step towards the efficient future of IoT applications. 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 2024 · 2024-08

Project Summary The enclosed application seeks to enhance the animal housing facilities at the University of Illinois Chicago (UIC). UIC's animal care and use program consists of eight centrally managed animal facilities totaling approximately 135,000 sq. ft. of animal housing and support space. The facilities support the research efforts of approximately 300 investigators and covers housing and husbandry of approximately 40,000 animals. The program is supported by a staff of ACLAM board certified veterinarians, post-doctoral fellows in laboratory animal medicine, certified veterinary technicians, and a strong animal care staff. Towards our efforts to modernize university research facilities, we are seeking to add environmental monitoring to the Biological Resources Laboratory (the institution's centralized animal facility) as well as 7 other centrally managed animal facilities at UIC. Specifically, we will purchase and install a Rees Scientific environmental monitoring system in the UIC animal facilities. The requested wired and wireless monitoring will provide temperature, humidity, and light monitoring. Real-time 24/7 monitoring of animal room temperatures requires a robust environmental monitoring system capable of not only identifying when temperatures fall out of an acceptable range but also capable of notifying multiple response team members through a variety of communication methods, such as phone, text or email. Once in place and operational the Rees Scientific environmental monitoring system will monitor in real- time 24/7 common extrinsic factors known to affect animal research including temperature, humidity, and light. In addition, the system will track pressure differentials in select bio and chemical hazard rooms. In all cases the system will notify animal care, research and facilities management staff when parameters fall outside the designated range for an animal species, research model and/or functional room use. In summary, this project will address a fundamental need in improved animal husbandry, minimize variables and facilitate state of the art biomedical research.

NIH Research Projects · FY 2025 · 2024-08

Several common mechanisms have been implicated in neurodegenerative diseases. The accumulation of misfolded proteins, microtubule disruption, mitochondrial dysfunction, upregulation of autophagy, and oxidative stress are all known contributors to neurodegeneration. Because there are currently no effective treatments for neurodegenerative diseases, there is a critical need for developing new model systems to study neurodegenerative mechanisms in order to identify novel therapeutic targets. C. elegans has been used as a genetic model to study neurodegeneration because of its well-defined nervous system and the C. elegans model system enables identification of common mechanisms in neurodegeneration that are conserved across the animal kingdom. This project seeks to identify a novel common mechanism in neurodegeneration that has not been reported before, which is the precocious neuronal differentiation. We model human congenital hydrocephalus associated human Trim71 genetic variants in C. elegans neurons by knocking in the de novo p.Arg608His mutation at a homologous position in the C. elegans lin-41 gene using the CRISPR engineering. lin-41, the C. elegans homolog of Trim71, was identified as a heterochronic gene that coordinates the temporal sequence of cell division and differentiation in many C. elegans cell types and tissues. The created lin-41(xr77) mutant allele, like the human and mouse de novo p.Arg608His mutation in Trim71, causes precocious neuronal differentiation. To our surprise, it additionally exhibits adult stage early-onset neurodegeneration, which has never been reported before. Premature neuronal differentiation in lin-41 mutants results in precociously, yet properly, built neuronal structures, that function normally in young adult stage. Other heterochronic mutations that cause precocious neuronal differentiation, including lin-14 and lin-28 mutant alleles, also result in early-onset neurodegeneration. We reason since neuronal structures in these mutants are built earlier than the normal schedule, they break down earlier, leading to adult stage early-onset neurodegeneration. We thus hypothesize that the timing of neuronal differentiation and the timing of neurodegeneration have a strong relationship in heterochronic mutants. This project aims to determine whether heterochronic perturbations that cause delayed neuronal differentiation result in a delay in normal age-related neurodegeneration. In addition, we will determine whether the heterochronic gene lin-14, like the heterochronic gene lin-41, is required and functions during early development to deter precocious neuronal differentiation, which in turn prevents future adult stage early-onset neurodegeneration.

NSF Awards · FY 2024 · 2024-08

With the support of the Chemical Synthesis Program of the Chemistry Division, Professor Tom G. Driver of the University of Illinois Chicago (UIC) is studying the development of new reactions to synthesize medium-ring molecules. Despite their established important bioactivity, this scaffold is underrepresented in pharmaceutical compound libraries because of the lack of synthetic methods for their construction. The goal of this project is to develop new metal-catalyzed processes that leverage and tame the reactivity of highly reactive metal carbenes to trigger new bond formation to create these important molecules. UIC is a designated Minority- and Hispanic Serving institution, and the hypothesis-driven nature of this project is well suited for the education of scientists at all levels. Professor Driver has tailored his research program to provide opportunities for students to advance in their professional development. The funded project also includes research experiences for high school students to inspire their pursuit of careers in STEM fields, and Chemistry Career Fair professional development activities to show the types of jobs and careers undergraduate- and graduate students can aspire to. Medium-sized carbocycles and heterocycles are critical structural motifs in pharmaceuticals and natural products. Despite their established use as scaffolds in drugs, medium-ring molecules remain underrepresented in pharmaceutical compound libraries, which is attributed to the shortage of synthetic methods to construct them. The experiments proposed with this proposal address gaps in state-of-the-art methods by exploiting the novel reactivity embedded in non-carbonyl stabilized metal carbene catalytic intermediates to develop new reactions that form seven- and eight-membered rings through the construction of C–C, C–S, C–O, and C–N bonds. Towards that end, our goals are: (1) to develop new metal-catalyzed cyclization-migration reactions of metal carbenes to construct medium-ring heterocycles by exploiting their unique reactivity with esters; (2) to develop new ring-expansion reactions of metal carbenes to construct all carbon medium-sized rings through a unique C–C bond activation mechanism; and (3) to leverage the reactivity of non-carbonyl-stabilized metal carbenes to participate in [2,3] rearrangements via ylides to enable synthesis of medium-sized heterocycles. The resulting medium-ring compounds are being added to UICentre for Drug Discovery’s novel small molecule library and submitted to our HTS facility for screening to initiate future collaborations. This project serves as a fertile ground for the training of students to advance in their scientific careers and hosting professional career development activities to meet the goals outlined by PCAST to transform and charge the STEM-student pipeline. 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 C programming language is widely used in both the basic software that makes computers work, and in high-performance applications that need to perform many computations at the same time (concurrently). Unfortunately, C code is highly error-prone, and concurrent C code is even more so. The goal of this project is to guarantee that concurrent C programs always run correctly by developing tools for mathematically proving the correctness of those programs. The project’s novelties are the development of an end-to-end toolchain for concurrent C programs, with interactive and automatic proof tools at the top, a precise model of the behavior of concurrent C programs (including the latest high-performance concurrency features) in the middle, and a formal connection to the code that the computer actually executes at the bottom. The project’s impacts are more reliable software and a reduction in software failures, including those that lead to lost productivity, privacy and security breaches, and even physical safety incidents (for instance, due to bugs in car software). The project builds on the newest version of the Verified Software Toolchain (VST), a tool for proving that C programs meet specifications written in separation logic. Notably, VST is formally connected to the CompCert verified compiler, so that programs verified in VST are mathematically guaranteed to compile to assembly code with the desired behavior. The project extends VST in two directions. First, it integrates RefinedC, an annotation-based verifier for C based on the Iris separation logic framework; the newest version of VST also rests on Iris foundations, so the investigator will reimplement RefinedC’s annotations in VST and extend them to more features of the C language, yielding a semi-automatic end-to-end verification system for C programs. Second, the project extends VST’s logic and foundational guarantees to concurrent programs, including those that use the atomic operations introduced in the C11 standard. This includes both sequentially consistent operations (where each memory address appears to contain a single value) and, ultimately, weak-memory operations (where different threads may see different values at the same address). The end result is a complete toolchain for guaranteeing that high-performance concurrent C programs meet their specifications when compiled and run. 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

Copper (Cu) plays a critical role in the transition to renewable energy. This metal is also crucial for giving access to electricity to approximately 2.6 billion people. To this end, a better understanding is needed of how Cu accumulates in significant concentrations. This project will improve the understanding of the conditions that produce magmas that form Cu deposits. Most of the world’s Cu comes from porphyry Cu deposits. The researchers will test models of porphyry Cu deposit formation by studying deposits in Sonora, Mexico. They also aim to develop geochemical tools that can help the discovery of new deposits and ensure the availability of Cu in the future. This project will support a Latino early-career scientist at a minority-serving institution and train a graduate student and two undergraduate students from groups underrepresented in STEM fields. The project will also enhance collaboration between US and Mexican researchers through joint fieldwork. Proposed models for the formation of porphyry Cu deposits rely on the oxidizing signature of parental magmas. However, whether this redox signature is source-controlled or controlled by processes occurring during magma ascent remains a contested question. To help settle this important ongoing debate (which will result in a better understanding), they will measure the redox state and constrain the petrogenesis and geochemical signatures of adakites and porphyry Cu deposits in this region. This combined approach will not only improve the understanding of porphyry-Cu-deposits formation but will also aid in future exploration efforts. This project will support a Latino early-career scientist and train a graduate student and two undergraduate students from underrepresented groups at a minority-serving institution. This research project will also foster international collaboration between US and Mexican researchers. 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

Project Summary HIV-1 presents a severe global health challenge. Due to the high genetic variability of HIV and the lifelong duration of the standard treatment, resistant mutations pose an acute challenge. As such, understanding the mechanisms of resistance is crucial for the rational design of antivirals. The current approach for understanding drug resistance focuses on identifying important interactions in the protein-drug complex based on intuitions. These insights have led to intriguing structure-based drug design strategies. However, resistance for drugs designed by these strategies readily developed, reflecting their limitations. This is due to two major gaps in the current approach: (1) It does not consider the conformational dynamics inherent to ligand binding, which are vital to decoding drug resistance. For example, the interplay between active-site and non-active site mutations in PR cannot be understood from structures alone. (2) This empirical, qualitative approach lacks a rigorous method to quantify how different residues and interactions individually and collectively contribute to binding affinity. We propose to fill these two gaps with a physics-based rigorous approach centered on protein conformational dynamics that control ligand binding, the process at the heart of drug potency and resistance. We will leverage a novel method we developed for identifying the exact reaction coordinates, the few essential coordinates of a protein that control its conformational dynamics and ligand binding. We will develop a rigorous method for decomposing the ligand binding free energy into contributions from individual residue-residue interactions. This method will enable us to identify residues and interactions critical for drug resistance. We will apply it to HIV-1 protease inhibitors, aiming to elucidate the mechanisms of resistance. We will also develop protocols for adjusting protein-protein and protein-ligand interactions to manipulate protein dynamics and combat drug resistance. To verify our understanding of resistance mechanisms and protocols for manipulating protein interactions and dynamics, we will test two types of computational predictions in infection assays. 1) We will design mutations that confer stronger resistance than current variants, aiming to establish the limits of drug resistance. 2) We will introduce additional mutations to existing mutants to neutralize their resistance, aiming to establishing the range for countering resistance. These will be achieved through two specific aims. The goal of this project is to develop a computational toolkit for rigorously and systematically dissecting protein drug resistance mechanisms that will enable rationale design of effective counterstrategies and validate it with virology assays. The insights from this project will fuel our long-term goal: to design the next-generation HIV antivirals that not only neutralize current resistant mutants but also minimize chances of new resistant mutations.