University Of Texas Rio Grande Valley

NSF Awards · FY 2024 · 2024-10

With support from the Improving Undergraduate STEM Education: Hispanic-Serving Institutions (HSI Program), this Educational Instrumentation project at The University of Texas Rio Grande Valley (UTRGV) will strengthen undergraduate learning in Mechanical Engineering as well as Information and Engineering Systems. Specifically, this project will secure a High-Performance Computing Cluster, which will allow students to conduct virtual experiments on fluid flow and heat transfer, simulate structural stress and strain, develop programs for secure digital transactions, and design and test models for cybersecurity using machine learning algorithms in Computational Fluid Dynamics, Finite Element Analysis, BLOCKCHAIN, and Cybersecurity Machine Learning courses. An estimated 200 students and 5 faculty will utilize the project-funded equipment each year. In addition to providing improved experiences in Mechanical Engineering as well as Information and Engineering Systems courses, the new equipment will also be used in Senior Design, and Undergraduate Research courses at UTRGV as well as in engaging approximately 30 high school students and 5 teachers in a yearly one-week long summer camp that would extend beyond the two-year funding duration of the project. The goals of this project are to enrich the learning and experiences of undergraduate students by providing critical equipment in Mechanical Engineering as well as Information and Engineering Systems. The high-performance computing cluster, consisting of both CPU and GPU nodes, will offer the computational power necessary for conducting extensive Computational Fluid Dynamics (CFD) and Finite Element Analysis (FEA) simulations. It will also support the development of Decentralized Applications (DApps) and Non-Fungible Tokens (NFTs), as well as the analysis of a comprehensive Machine Learning (ML) pipeline on realistic datasets. Students will acquire skills in accessing high-performance computing resources, utilizing massively-parallel Navier-Stokes solvers, developing robust smart contract codes, and efficiently building, running, and analyzing Machine Learning algorithms for cybersecurity applications. The project will assess the impact of the project funded equipment using a comprehensive assessment approach tailored to the involved courses. Each assessment will consist of two components: an objective component and a subjective component. The objective component will measure how well students have understood the key concepts of their respective classes, while the subjective component will gauge students’ overall satisfaction with the project and the high-performance computer cluster. Additionally, an assessment plan will be developed for the proposed one-week summer camp designed for high school students. This project is funded by the HSI Program, which aims to enhance undergraduate STEM education, broaden participation in STEM, and increase capacity to engage in the development and implementation of innovations to improve STEM teaching and learning at HSIs. 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 · 2024-10

This BCSER Individual Investigator Development (IID) project will build the PIs expertise in STEM education research study design, research methods, and data analysis techniques to complement their Civil Engineering expertise. In addition, to planned professional development the project will support a pilot STEM education research project. The pilot is designed to result in new knowledge about remedial math training for civil engineering undergraduate students. This research is important because retention and success in undergraduate engineering programs is heavily influenced by students' math skills. The PI will acquire expertise in study design, research methods & data analysis techniques, and gain familiarity with advances in computational, quantitative, qualitative, and evaluative research methodologies. Through a pilot research project embedded into this proposal, the PI aims to increase the number of civil engineering graduates from the University of Texas Rio Grande Valley and beyond. The research builds on aspects of the "Funds of Knowledge" framework which is an asset-based method with connections to familial integration and student knowledge. Research on teaching remedial math skills as part of an engineering curriculum will contribute to the body of STEM Education research, increase the PI's capacity to carry out STEM Education research, and, in turn, will enhance the nation's STEM education enterprise. Project findings will be shared through publications and presentations. The success of this project will be assessed through regular meetings with the advisory board. The project is supported by NSF's EDU Core Research Building Capacity in STEM Education Research (ECR: BCSER) program, which is designed to build investigators' capacity to carry out high-quality STEM education research. 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 · 2024-10

This project aims to serve the national interest by (1) improving programs preparing novice college mathematics instructors and (2) establishing leadership development for faculty who are the Providers of teaching-focused professional development (TPD) for those novices. Extensive educational research has identified evidence-based instructional practices that support undergraduates' persistence and learning in science, technology, engineering, and mathematics (STEM). For undergraduates to benefit from advancements in instructional practices, novice instructors (e.g., graduate students) need opportunities to develop expertise in those practices. For novice instructors to develop that expertise, Providers (i.e., those who facilitate TPD for instructors) themselves need opportunities to develop expertise in teaching about teaching. Providers face daunting challenges: no curricular packages (e.g., textbook, assessment items) exist for teaching graduate students how to teach mathematics. This effort builds upon previous work addressing these needs through workshops for Providers and creating a library of individual activities for TPD. Experienced Providers will assemble lessons from the library of activities, create assessments of learning about teaching, and teach new Providers about use of these packages. An innovation in the project is attention to a particular group of Providers, whose ambitions include scholarly work related to the development of novice instructors. These Provider-Scholars will be the next generation of leaders in this field. Greater Provider skill will improve instruction by novices and boost learning opportunities and outcomes for undergraduates. The goals of the project are (1) to develop curricular packages for learning about teaching college mathematics which will be piloted by Providers and (2) to build new research-based understanding of the knowledge, skills, dispositions, and communities Providers develop as they grow professionally into Provider-Scholars and Stewards (i.e., Provider-Scholars who also have leadership roles). Project research and evaluation will use a mixed-methods convergent design so complementary data are collected concurrently or, as appropriate, sequentially. This approach combines the strengths of quantitative data collection and analysis (e.g., large sample, repeated measures) with those of qualitative methods (e.g., participant voices, rich detail). In particular, the exploratory research questions are: (RQ1) What is the nature of Provider-Scholar knowledge, skills, and dispositions for engaging in scholarly work as Stewards? (RQ2) What is the nature of Steward, Provider-Scholar, and Provider engagement in the work and community growth? Project evaluation questions are: (EQ1) To what extent is project exploratory research implemented as planned? (EQ2) To what extent is the project succeeding in developing and piloting starter packages and Provider orientation with target communities? (EQ3) How can the project do better in supporting the professional community, including stewardship and leadership capacity development? The project intends to build professional community through collaborative working groups of experienced Provider-Scholars and education researchers. Mathematics graduate students (94% of whom have teaching related responsibilities while in graduate school) will benefit from the strengthening of TPD programs achieved by equipping new Providers with “starter packages” of resources informed by research findings about student-responsive teaching and learning. A robust community of Providers whose scholarly activity is about TPD will seed the next generation of leaders. The NSF IUSE: EDU Program supports research and development projects to improve the effectiveness of STEM education for all students. Through its Institutional and Community Transformation track, the program supports efforts to transform and improve STEM education across institutions of higher education and disciplinary communities. 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 · 2024-10

This project is an Expand AI Partnership between the University of Texas Rio Grande Valley (UTRGV), a Hispanic-serving institution (HSI), and the AI Institute for Advances in Optimization (AI4OPT) at Georgia Tech, an NSF-sponsored AI institute focused on automated decision-making and mathematical optimization. In this project, UTRGV, a Hispanic-serving institution, leads a new collaboration with an AI Institute focused on scaling up already-established research and education programs at UTRGV and to pursue shared, complementary goals around developing AI with use for society in mind and for developing the next generation of AI education and workforce talent. The partnership aims to enhance and expand UTRGV's AI capacity in research, education, and workforce development and create new academic opportunities through strategic and synergistic programs with AI4OPT focused around AI-driven autonomous robots and sensors for use in transportation. This collaborative project focuses on AI-driven autonomous robots and sensors for advanced predictive condition monitoring of Critical Transportation Infrastructures (CTIs) (e.g., highways, railways, bridges), a new use case for AI4OPT, transcending traditional reactive monitoring methods to more reliable and proactive practices. UTRGV will focus on developing autonomous robots and sensors, collecting data, training/testing AI models, expanding its AI infrastructure, developing specialized AI courses, supporting the newly approved doctoral program in computer science with interdisciplinary applications, and facilitating the training of students and junior faculty. AI4OPT will use data generated by UTRGV to develop mathematical optimization models and refine AI models for robust predictive maintenance. Simultaneously, they will train UTRGV students and junior faculty on advanced AI model optimization. Project ARISE will enhance the educational and research opportunities for students at UTRGV by integrating advanced research into educational activities, offering summer immersion programs at Georgia Tech, and expanding UTRGV’s AI capacity. The partnership will also expand UTRGV’s AI curriculum by partnering through course development in AI, autonomous robots (UAVs and UGVs), sensors, and data mining, to support advanced AI skills training for students and professional development for junior faculty. The ExpandAI Program supports AI-powered education and workforce development, infrastructure and research at Minority Serving Institutions to strengthen U.S. research and education pathways and provide communities with new opportunities in STEM careers. This project is funded by the HSI Program, which aims to enhance undergraduate STEM education and enhance participation in STEMs. 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

We propose a high impact collaborative project to overcome barriers to understanding the roles and regulation of Forkhead box subfamily O transcription factors FOXO -1, -3, and -4 (FOXO) in stem cell contexts. Stem cells repopulate the lining of the intestinal tract, muscle, and blood lineages, yet also drive devastating diseases such as cancer. Evolutionarily conserved, partially redundant FOXO transcription factors are needed for stem cell maintenance in a litany of contexts such as embryonic, cancer, mesenchymal, hematopoietic, and neural cell lineages, as well as direct specification of subsequent lineages in a context-dependent manner. Canonically, high PI3K output leads to cytoplasmic/inactive FOXO factors. Stem cells, however, are fundamentally rewired to have both high PI3K Pathway activity and nuclear/active FOXO factors. Prior work shows that FOXO factors directly bind to and activate stem genes in both embryonic stem cells and the poor prognosis cancer glioblastoma multiforme (GBM) to drive stem cell fate. However, the precise mechanisms utilized by FOXO transcription factors in driving stemness, hindering differentiation, and determining cell fate are incompletely understood. Our novel, preliminary insights indicate that nuclear-localized FOXOs engage both the NOTCH and JAK/STAT signaling pathways. Our preliminary evidence demonstrates a strong loss in the gene expression of NOTCH Pathway components NOTCH1 and NOTCH3, as well as their targets including HES1, in FOXO4 loss-of-function contexts. Our preliminary data indicates that FOXO factors share the ability to promote NOTCH output. Motivated by our preliminary findings and published work (by others), we propose examining whether FOXO - 1, -3, and -4 redundantly drive NOTCH1 and NOTCH3 gene expression in GBM and myoblasts. Our preliminary work with FOXO transcription factor disruption mutants shows that FOXO4 acts uniquely to hinder JAK/STAT3 activation and expression of targets IGF1, PDGF and TH. Of note, FOXO3 disruption led to a loss in STAT3 activation, underscoring unique contributions of FOXO factors to the JAK/STAT Pathway. We propose to dissect the ability of FOXO factors to differentially regulate the JAK/STAT Pathway in GBM and myoblast settings. Our long-term goal is to delineate FOXO-driven fundamental biological processes that aid stem cell maintenance and cell fate by promoting the NOTCH Pathway and differentially regulating the JAK/STAT Pathway. The proposed work will integrally involve student researchers and will promote the research environment at UTRGV.

NSF Awards · FY 2024 · 2024-09

Suspended particulate material is a complex mixture of living and detrital organic and inorganic material. The composition and concentration of suspended particulate material vary greatly throughout the ocean and can be considerably influenced by local processes. The microbial and biogeochemical processes occurring within this material greatly influence the flow of carbon and other nutrients through the marine environment. The scale of the ocean makes these particulate processes globally relevant and, at the same time, challenging to fully characterize. Equipping robotic vehicles with a sensor system capable of rapidly distinguishing environmental variations in marine particle size, shape, and composition will enable navigation based on the properties of the ambient particle field. More specifically, it will enable the targeted collection of samples by autonomous robotic vehicles to those zones of the ocean where particle processes are most relevant and dynamic. This research will develop an optical sensing instrumentation suite and integrate it with existing robotic sampling tools for both remotely operated vehicle Jason and the autonomous underwater vehicle Clio and optimize their use to characterize hydrothermal plume particle processes in an engineering sea trial in the vent fields of the Juan de Fuca Ridge. This research will develop an optical sensing system to directly characterize marine particles and enable adaptive robotic collection of biogeochemical and biological samples from autonomous vehicles and remotely operated platforms. The optical sensing components of this system will characterize marine particles based on multiple parameters indicative of size, shape, and composition. Optical sensing will be based on a tightly integrated sensor suite consisting of camera-based particle imaging, using both wide-field stereoscopic and microscopic cameras, fluorometry, and optical transmission sensors. These sensors will be controlled by a single board computer capable of running real-time classification algorithms that can be used to control adaptive particle and fluid sampling systems. The close integration of the sensing elements is intended to both achieve a smaller overall payload size and allow for maximum control of sensing parameters including timing, sequencing, and frequency. The intent is to maximize the use of open-source software and hardware so that the resulting design can be shared within the broader community to allow for modification, adaptation, and experimentation. The goal is to improve the oceanographic community's ability to target novel biogeochemical environments using robotic oceanographic vehicles so that we can more efficiently study geochemically important environments in an otherwise very large ocean. This optical sensing system will be designed to enhance the observational capabilities of both large and small underwater vehicles and platforms. The system will consist of a stereo camera pair, a flow-cell/microscope camera, a commercial chlorophyll-a fluorometer, a commercial backscatter sensor, an electronic stack in a custom pressure housing, and an adaptive sampling subsystem. The operation of the system will be tested both in the laboratory and in field on remotely operated vehicle Jason and autonomous underwater vehicle Clio in the hydrothermal plumes of the Juan de Fuca Ridge during an engineering sea trial cruise in 2026. 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

HSIs are substantially underfunded compared to other institutions of higher education due to relatively low endowment revenue and tuition fees. Chronic underfunding leads to infrastructural and technological disparities that disadvantage students as they pursue advanced educational and professional opportunities. This project creates an alliance between four Texas HSIs to improve institutional competitiveness through: 1) research focused on and directly relevant to creating opportunities across demographic and socio-economic groups; 2) the establishment of physical lab spaces with state-of-the-art computing resources and statistical analysis software; 3) the creation of a virtual lab across all four campuses to facilitate student and faculty mentorship and collaboration; and 4) preparation of students from HSIs to enter graduate programs. The project brings students and faculty together from R1, R2, and M1 classified HSIs to conduct research relevant to creating opportunities across all demographics and socio-economic groups through two interconnected studies. Applying multi-method comparative designs, these studies will advance a deeper understanding of attitudes, experiences, attitudes on immigration, and other thematic areas to address core questions on inequality and opportunity. The creation of physical and virtual lab spaces for these studies will foster equal participation in scientific innovation at each of the collaborating universities by allocating infrastructural resources in proportion to need. These labs will facilitate the development of research and the dissemination of important findings through yearly mini-conferences showcasing student and faculty work, academic publications targeting traditional disciplinary outlets, and white papers designed to make the research accessible to the general public. Collectively, the alliance of four universities will address four objectives: (1) the theoretical and methodological development of sociological research, (2) promoting research opportunities for students and faculty at under-resourced HSIs, (3) conducting meaningful research on critical sociological issues important to the Texas and national social context, and (4) creating a pipeline for students from HSIs into scientific training and doctoral graduate programs. 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

Time-series data arises frequently in medical applications such as sensor monitoring over time. While deep neural networks have been extensively employed to analyze such medical time-series data, current networks often rely on spurious features that misalign with medical expertise. The spurious correlations between time-series data features and labels are biased in observed data, which undermines the robustness of the deep network to generalize to new patients in complex and dynamic environments. The project aims to address the need for reliable deep learning in ubiquitous medical-sensor applications with the goal of technological improvement in healthcare quality. The educational plan will foster broader participation among undergraduate and graduate students - particularly within the Hispanic community in South Texas - through dedicated research, education, and outreach initiatives. The primary goal of this project is to facilitate robustness of time-series deep-learning models via systematically defining and mitigating spurious correlations between input confounders and output decisions. Specifically, this project aims to achieve the research goal by developing robust techniques via following: 1) identifying input confounders prevalent at various levels of time-series data - including point, segment, and structure levels - to understand their spurious correlations with target labels; 2) designing knowledge-editing mitigation strategies to locate neuron groups responsible for spurious correlations so as to efficiently correct them; and 3) investigating the approach in two medical-sensor applications: monitoring for Parkinson's disease and detection of falls in the elderly. The research outcome will yield open-source tools and potentially benefit a wide range of sensor-based medical-monitoring and diagnosis tasks. 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

Advanced microscopies play a critical role in understanding material properties and drive research innovation in next-generation materials and processing. A photo-induced force microscope (PiFM) allows researchers to identify and analyze materials at the molecular scale which cannot be achieved using conventional spectroscopy and microscopy. This Major Research Instrumentation (MRI) grant supports the University of Texas Rio Grande Valley (UTRGV) with the acquisition and installation of the PiFM that will stimulate high-quality research in various research areas including functional nanomaterials, nano-biomaterials, advanced material processing, semiconductor material and processing, and energy materials and sustainability. This instrument will enable the UTRGV researchers from Engineering, Physics, Chemistry and Medicine to study fundamental aspects of functional nano and biomaterials, benefitting students enrolled in newly inaugurated doctoral program in Materials Science and Engineering, and master’s program in Biomedical Engineering. Utilizing the Center for Advanced Manufacturing Innovation and Cyber Systems, Texas Manufacturing Assistance Center and Partnership for Research and Education in Materials Science at UTRGV, this instrument will be offered to broader regional academic partners, industry collaborators, and K-12 students through outreach activities to elevate materials and manufacturing research and education in the Rio Grande Valley. The Major Research Instrumentation award will support the University of Texas Rio Grande Valley in acquiring and installing a photo-induced force microscope (PiFM), a powerful nanoanalytical imaging tool that offers simultaneous acquisition of 3D topographic images with molecular compound identification at the nanoscale. The researched instrument will potentially enhance the existing research and educational infrastructure and provide a state-of-the-art materials research facility to a broad range of users in Rio Grande Valley. The instrument has the capability of chemical mapping of complex nanomaterials with better than 10-nanometer spatial resolution. Additionally, the PiFM allows hyperspectral imaging, consisting of both topographic information and a full spectrum at each pixel of the image, allowing the detection of nanoscale molecular distribution mapping. These unprecedented abilities are achieved in PiFM by combining atomic force microscopy with near-field optical interactions induced by a tunable excitation laser. The PiFM will serve a team of investigators with ongoing diverse materials and processes research including one-dimensional and two-dimensional nanomaterials and nanocomposites, conductive chitosan/nanoparticles Films for neural activity, nano-scale fungal bio foam materials and functional biomaterials for battery applications, metal oxide-based flexible substrates for biosensing, ultrasonic assisted sintering for semiconductor packaging, nano cellulose loaded hybrid biopolymers for tissue constructs, and additive alloying and metal matrix composites. 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

PROJECT SUMMARY/ABSTRACT Bleeding in Hemophilia A (HA) is currently prevented by regular infusions of therapeutic factor VIII (FVIII) proteins (tFVIIIs). Unfortunately, ~30% of all severe HA patients (HAPs) develop antibodies called FVIII inhibitors (FEIs) that neutralize tFVIIIs and greatly increase morbidity & mortality. FEIs develop significantly more often in HAPs with Mexican ancestry (MA) vs. non-Hispanic white (NHW) ancestry. This research seeks to identify genetic and environmental variables underlying the high incidence of FEIs in HAPs of MA by applying novel omic approaches in a powerful systematic immunoepidemiologic study of the immunogenicity of tFVIIIs. We will leverage a unique resource, the My Life, Our Future (MLOF) repository, which has ~400 such subjects already enrolled in our study. We have four main aims. Aim 1: To enroll and extensively characterize a cohort of 200 severe HAPs with MA. We will recruit 200 severe HAPs (including 30 sib pairs) in the US and Mexico. Relevant clinical data and blood samples will be collected to assess FEI risk. We will use the (i) WGS and mRNA-Seq data from these 200 new individuals plus the ~400 subjects of MA in the MLOF project (N=600) and (ii) functional CD4 T-cell data from all 200 new subjects. We will assess intracellular (i) CRM status (i.e., presence or absence of FVIII antigen) in all 200 new subjects, as this variable underlies the contribution of F8 mutation type to FEI risk. Aim 2: To elucidate the genetic basis of FEI risk in MA severe HAPs using trans-omic endophenotypes. Using a novel statistical genetics approach employing both close and distant relatedness in the overall sample of ~600 MA severe HAPs, we will identify endophenotypes genetically correlated with FEI risk from novel phenotypic measures immunologically related to FEI development. The best endophenotypes for FEI risk will be genetically characterized using both quantitative genetic methods and variant-specific association analyses. Aim 3: To detect and characterize environmental effects on FEI risk. Using a novel statistical genetic approach to maximize systematic environmental signals influencing FEI risk, we will search for environmental traits reflected in high-dimensional transcriptomic biomarkers that are correlated with FEI development. Aim 4: To perform a case/control peptidomic analysis of FEI risk. We will select a subset of 40 HAPs as 20 FEI discordant sib pairs (one brother has a FEI and the other does not) and recruit their carrier mothers. We will characterize each subject’s tFVIII peptidome, i.e., the HLA-class-II (HLAII)-bound collection of tFVIII-derived-peptides (tFVIII:dPs) that are presented to their CD4 T-cells. We will then identify the “culprit tFVIII:dP” and “offending HLAII allele” (OHA), which are most correlated with FEI development in the proband of each sib pair. Finally, we will evaluate the relevance of our findings using: 1) CRISPR/Cas9 to knockout (ko) specific OHAs in their B-lymphoblastoid cells (BLCs) in vitro; and 2) their ko BLCs for functional T-cell studies. As tFVIIIs are more immunogenic in HAPs with MA, this study is likely to identify new determinants of FEI risk (both genetic & non-genetic) which will assist the development of new (i) diagnostics that are more accurate, (ii) therapeutics with improved safety and efficacy, and (iii) management strategies that reduce race- and ethnicity-based disparities in health outcomes.

NSF Awards · FY 2024 · 2024-09

Time series data (i.e., a collection of observations for a single subject at different time intervals) is one of the most prevalent data types in a wide range of research domains. For example, times series data are common in meteorology, medicine, and physics. However, the process of labeling time series data often demands a substantial amount of time. Typically, only domain experts have the capability to effectively label time series data. Consequently, data labels are often scarce in most real-world time series applications. To overcome this challenge, an approach called Contrastive Self-Supervised Learning (CSSL) has been developed in the research community. However, the effectiveness of CSSL framework is highly related to the definition of “semantic similarity” among time series data that represents the characteristics of the underlying system. In CSSL framework, the errors (whether they were wrongly considered similar or dissimilar samples) will likely generate meaningless or even misleading models that impact on the final artificial intelligence (AI)-driven models that utilize time series data. This project aims to address these challenges by conducting a systematic analysis of the CSSL framework for time series data and developing innovative algorithms to alleviate the identified limitations. Additionally, this project will specifically focus on smart manufacturing system related application where time series sensors are widely recognized for their energy efficiency but lack data labeling. Furthermore, the project has a detailed plan to integrate research outcomes into existing courses and develop new courses at the University of Texas Rio Grande Valley. Lastly, the project will promote the participation of Hispanic students in STEM research and participate in outreach events in the local community. The technical aims of the project are divided into two tasks corresponding to the two major steps in the CSSL framework: the view augmentation step, which aims at augmenting semantically correlated samples and the negative sample sampling step which aims at sampling semantically unrelated samples. The project aims to integrate the concept of time series motifs, a key primitive used to unveil underlying natural mechanisms in a wide variety of time series, into CSSL frameworks. Specifically, the project consists of two thrusts: 1) To address the challenge of difficulty to preserve semantic meaning in view augmentation operator, the project aims to design a motif-aware augmentation operator to use detected motifs to regularize the semantics of augmented data; and 2) To address the challenge of difficulty to sample high-quality negative samples, the project aims to design a motif-aware negative sampling to avoid low-quality negative samples induced by noises and redundancy existed in the time series data. The investigated theories and methodologies will deepen the understanding of the intrinsic working mechanism of the self-supervised time series representation and contribute to the research in a wide range of domain 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 2025 · 2024-08

Project Summary/Abstract Although health professions (allied health, nursing, social work, clinical psychology) represent more than 80% of the healthcare workforce, rigorous research within these fields, a cornerstone of evidence-based practice, is often trailing behind that of other medical professions. The urgency of closing this gap is amplified for health professionals practicing in communities characterized by poverty, low educational attainment, health care access challenges and, consequently, poor health outcomes. Thus, building and strengthening HP biomedical research capacity is vital to improving health. The primary goal of the proposed study is to lay the foundation for a robust health professions research environment at the University of Texas Rio Grande Valley (UTRGV). Located along the Texas-Mexico border, UTRGV serves one of the most medically underserved regions in the United States. Guided by a conceptual framework that integrates multiple levels and domains of influence, our overall objective is to engage the UTRGV HP community in a structured, comprehensive research needs assessment and develop a corresponding action plan characterized by clear, feasible, measurable, sustainable, and institutionally championed action items that support high-quality, cutting-edge biomedical research. To achieve our objective, our multidisciplinary team will conduct an environmental scan, analyze research- related policies and procedures, assess faculty research capacity and needs, examine the institutional research support infrastructure, and explore student research support and opportunities. This will allow us to: Aim 1. Identify the structural, systemic, social, and psychological factors impacting biomedical research productivity of HP faculty. Aim 2. Identify the critical interactions between factors, domains and levels of influence enabling and hindering research productivity. Aim 3. Develop an action plan to strengthen biomedical research capacity of HP faculty, with a focus on community-relevant health. Our work will add a much-needed perspective to advance health from bench to bedside. The proposed assessment and action plan promise to build a multidisciplinary, interprofessional biomedical research capacity that will uniquely position UTRGV to advance health research, support the pipeline of the future biomedical research workforce, and serve as a research capacity building model for resource-limited institutions.

NIH Research Projects · FY 2026 · 2024-08

Overall Project Summary: The Rio Grande Valley (RGV), located in South Texas along the US-Mexico region, is home to Hispanic/Latino American (HA/LA) populations who disproportionately suffer from several cancers despite improvements in the last several years in overall health care (diagnosis and treatment). The proposed Rio Grande Valley Cancer Health Disparity Research Center (RGV-CHDRC), located at the University of Texas Rio Grande Valley (UTRGV), will develop a comprehensive, biomedical research infrastructure building capacity to reduce cancer chronic disease disparities in the RGV region using multi-domain and multifactorial (basic, clinical, behavioral, social, biological) cutting-edge research, engaging relevant community partners/stake holders, and developing local health disparity research workforce. This center will establish collaborations with local and national educational, research, and medical institutions as well as nationally renowned research-intensive institutions, such as University of Texas MD Anderson Cancer Center, University of Texas Southwestern, and Baylor College of Medicine. We propose three research projects: 1) a basic biomedical research project on etiology of liver cancer, 2) a social/behavioral research project on prolonged psychosocial stress cancer and 3) a clinical and health service research project on cervical cancer and HPV screening, along with four cores - Administrative Core, Investigator Development Core, Community Engagement Core, and Research Capacity Core. The proposed research projects will delineate molecular and socio-behavioral determinants of health, influences of cancer and its associated chronic diseases health disparity, clinical manifestation of early cancer diagnosis, and if sociobehavioral interventions that can reduce burden of these chronic diseases and improve quality of life of the cancer patients. These projects will conduct basic and clinical translational research to improve early diagnosis of liver and cervical cancers and develop strategies to enhance therapeutic outcomes of chemotherapies by applying culturally tailored interventions. This U54 application will foster and promote collaboration between research projects and core facilities, engage community partners, and facilitate translation of science into practice. The main objectives of our RCMI application are to: 1) Enhance biomedical research infrastructure and capacity building at UTRGV and in the RGV; 2) Conduct impactful research on variable factors associated with cancer disparities; 3) Develop relationships and establish collaborations among local and top tier research institutions, 4) Offer advance level training and mentoring opportunities for RGV students and faculty members across the region; 5) Disseminate scientific knowledge from the project to the local community partners, researchers and stake holders. These activities will be crucial for developing successful intervention strategies to eliminate cancer and chronic diseases and health disparities in RGV populations. This funding will allow NIMHD to have its footprint in the RGV and provide NIMHD access to the unique Hispanic population data.

NSF Awards · FY 2024 · 2024-08

This project is devoted to the study of extremal point configurations, both in continuous cases such as Euclidean spaces or spheres and in discrete spaces. One particular area of focus is packing problems. A typical question in this area is to find the most efficient, or dense, packing. These types of questions have been well known in mathematics and science for a long time, starting with the Kepler conjecture about the densest sphere packing in three dimensions and with the kissing number problem that was the subject of disagreement between Isaac Newton and David Gregory at the end of the 17th century. A second focus area is the search for configurations that minimize energy. Probably the most famous example of this type is the Thomson problem asking to find the location of electrons in the sphere with the smallest cumulative electrostatic energy. The PI plans to mentor both undergraduate and graduate students and reach out to a wider audience by organizing research talks and public lectures. In more detail, this project will focus on the study and applications of extremal point configurations. One direction of research concerns sets with few pairwise distances. In the discrete case, sets with few distances are the subject of the Erdős–Ko–Rado and similar theorems. In the continuous case, one of the important objects of study is the set of equiangular lines. The PI will apply and extend the general method of finding upper bounds on sets with prescribed distances in two-point homogeneous spaces, including both the discrete and continuous regimes. A second direction of research concerns plank covering problems, that is, coverings of convex regions in Euclidean space by the regions between pairs of parallel hyperplanes. These questions go back to the Tarski problem and the Fejes Tóth zone conjecture. Recently, a version of the polynomial method brought several far-reaching generalizations of the results in this area. The PI will further develop this method and apply it to plank coverings and similar problems. Finally, a third direction of research is the study of energetically optimal configurations using a variety of analytic and optimization methods, including linear programming and semi-definite programming approach, with the goal of solving relevant problems in discrete and convex geometry. 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

Non-technical Abstract: Proposed effort is focused on providing an annual venue dedicated to the NSF CREST/HBCU-RISE/PRP Programs community, where principal investigators, directors, faculty, staff, and students can meet and discuss relevant topics and issues, share best practices, and network. A three-year conference grant will bring together NSF personnel and broad CREST community. Three equally important components will form the basis of the annual meetings starting in 2024 through 2026. These are: (1) NSF Personnel Portion, with the beginning of each annual meeting will be dedicated to issues, topics, or information dissemination by the NSF personnel who are administering these grants; (2) PI Meeting Portion where each annual meeting will feature four sessions, workshops, or panels as appropriate, which will cover topics of importance for the collective PIs associated with the three programs (CREST, HBCU-RISE, PRP); and (3) Early Career Investigators Portion, with each annual meeting featuring a workshop for early career investigators focusing on grant writing and the merit review process. Technical Abstract: Planned meetings will promote sharing of best practices among CREST/HBCU-RISE/PRP community members, leading to improved quality of science and training at funded sites, more effective execution of grants, increase in competitiveness and research success across the spectrum of funded projects. External evaluation will provide informative assessment of outcomes and will help establish a model for similar conferences going forward. Networking across the CREST community and including NSF personnel will help inform both the program management and the community of researchers and educators, leading to enhanced opportunities for sustainable success. 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 · 2024-07

With support from the Improving Undergraduate STEM Education: Hispanic-Serving Institutions (HSI Program), this Track 2 project aims to improve the success and persistence rates in Calculus I and II courses and shorten the time to complete calculus sequence by coordinating calculus instruction and together implementing multi-intervention activities across two major Hispanic-Serving Institutions: The University of Texas Rio Grande Valley (UTRGV) and South Texas College (STC). Calculus is a gateway course for students entering STEM fields. Successful completion of calculus courses is essential for students to persist and maintain progress in their STEM program. However, calculus courses remain a bottleneck for student progression in STEM fields. In this program, a team from STC and UTRGV will implement two major activities: (1) increase calculus course coordination across the two institutions; (2) provide a multi-level student support system while paying particular attention to five student groups (i) first-generation college students, (ii) students from low-income families, (iii) students retaking Calculus I or II after a failed first attempt, (iv) students who take calculus with time gap, and (v) non-traditional students. By improving student success in calculus, the program will increase the participation of students from underrepresented groups in STEM fields and the workforce. The implemented support structures will serve as a model for other STEM programs nationwide. The program will provide a pathway for institutions to positively influence student retention, improve time progression through undergraduate STEM programs, increase student self-efficacy and confidence with advanced STEM courses, and develop scientific identity. The project goals are to: 1) enhance the quality of teaching in Calculus I and II, 2) increase pass and persistence rates; 3) better prepare students for subsequent courses; 4) increase students’ sense of belonging in mathematics; and 5) shorten completion time in calculus courses. The content and instruction of Calculus I/II will be realigned and standardized between STC and UTRGV to improve the transition between courses from Pre-Calculus through Calculus II and facilitate the students’ transfer between institutions. Students will be supported in-class with activities and interventions such as early-semester supplemental instruction, in-class peer assistants, and exam retakes. Instructors will be provided professional development focusing on key groups such as first-generation college students, students from low-income families, students repeating Calculus I/II, and students taking a calculus class with long time gaps between prerequisite courses. By the end of this project, the project investigators will determine the extent to which the activities enhance instructors' beliefs and practices, improve student achievement and timely completion of their calculus courses, and foster students' sense of belonging and mathematics identity development. Findings from this project will contribute to the knowledge base on student achievement, persistence in mathematics and other STEM fields, sense of belonging in the mathematics discipline, and mathematics identity. The HSI Program aims to enhance undergraduate STEM education and build capacity at HSIs. Projects supported by the HSI Program will also generate new knowledge on how to achieve these aims. 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 · 2024-07

PROJECT SUMMARY/ABSTRACT The goal is to establish a state-of-the-art vivarium, which will be dedicated exclusively to the UTRGV Laboratory Opossum (Monodelphis domestica) Research Resource, and which will provide expanded opportunities for biomedical research with this unique laboratory animal to investigators and students at UTRGV and other institutions. This resource is the only large research colony of any marsupial species, and it contains the only genetic stocks and inbred strains that have been developed for any marsupial species. The resource is widely shared with investigators from other institutions, and it serves as the only readily accessible source of research animals, breeding nuclei, and biological materials from this species, and of opportunities for investigators from other institutions to conduct hands-on (or remote) research with this species without establishing their own colonies. State funds were secured for construction of the building that will contain the new vivarium, and the building will be ready for occupancy early in 2024. Use of the funds was restricted to the building and fixed equipment; the funds could not be used for caging. To fill the gap in funding, the single specific aim of this proposal is to purchase and install ten racks of a state-of-the-art IVC system. Sixteen racks currently in use are available to be moved to the new vivarium. The complete caging system will include 13 Optimice racks (1,300 cages) for individually housed opossums and 13 Optirat racks (546 cages) for mated pairs, mothers with litters, and groups of littermates. Six racks of each type will be installed in each of two breeding/holding rooms; and one rack of each type will be installed in a smaller room for research with infectious agents or for quarantine purposes. The breeding/holding rooms will house the 20 genetic stocks and inbred strains that comprise the breeding colony, as well as animals used in research that does not involve infectious agents. The current opossum resource has a steady state of 1,200 animals, which are housed in an overcrowded vivarium with many deficiencies. The new vivarium and caging system will enable the steady state of the colony to increase to 1,726 animals, which will be maintained under optimal conditions for animal welfare and for financial and operational efficiency. That number of animals will be sufficient in the intermediate-term future for maintaining the 20 breeding groups and providing sufficient animals and research capacity to meet the national need. The IVCs will provide maximal protection from the transmission of infectious diseases, high air quality for the animals, and minimal exposure of staff to allergens that emanate from the animals. Moreover, the selected caging system is the ultimate in green technology design; it depends on filtered room exhaust air being pulled through the cages and out of the building by the HVAC system, rather than on motors and blowers. The overarching outcome will be to establish an efficient, high-quality, high-capacity laboratory opossum research resource that is capable of meeting current demand for laboratory opossums for biomedical research, and of fulfilling the increasing institutional and national need for this species well into the future.

NIH Research Projects · FY 2024 · 2024-07

PROJECT SUMMARY/ABSTRACT Nicotinic acetylcholine receptors (nAChRs) are involved in a variety of fundamental physiological processes, and dysfunction in these receptors is associated with many human disorders. The structure and function of human nAChRs have been extensively studied; however, the combinations of different nAChR subunits making various nAChR subtypes as well as their extracellular regions binding a structurally diverse range of ligands, pose challenges in understanding and characterizing a specific nAChR. Fortunately, animal venom toxins provide a unique tool to study the structure and function of nAChRs because throughout millions of years of natural selection, animal venom toxins have been fine-tuned to endue with high selectivity towards specific targets such as neuronal nAChRs in prey organisms in order to quickly paralyze and capture their prey. Our goal is to identify animal toxins that selectively interact with human nAChR subtypes and decipher the molecular mechanisms underpinning their interactions for characterizing the downstream signaling pathways. The objective of this project is to empower and inspire rising undergraduate students through biomedical research activities designed to engage students early in their career in human health-related sciences. After submitting the NINDS R15 research proposal, we identified strong interactions of snake D49-1 PLA2 with nAChR β2 and β4 subunits. Therefore, in this project we will structurally map both D49-1 and human nAChR β2 and β4 subunits to identify the segment(s) involved in the interaction. The project is designed to prepare the next-generation of scientists to pursue human health-related research. Student, Christine Vega, a senior undergraduate student (UG) in biology department, will be the mentee. Christine has already participated in venom research since Spring 2022, published one peer-reviewed paper, organized several posters, and obtained internal UTRGV funds. Christine’s career goal is to work in medical science, and she will be involved in all aspects of this project and conduct most experiments under PI’s instruction. The expected outcomes of this project will 1) generate a unique tool (polypeptide) for probing the stages of gating cycle of a specific nAChRs, and 2) help Christine make the successful transition to human health-related research. The project is impactful because: 1) it will lead Christine into medical science throughout one-year training in biomedical research; 2) Christine will become a role model of UTRGV UGs for transitioning their discipline into medical sciences; and 3) the project will attract more underrepresented UGs to our program for their early career in medical disciplines.

NIH Research Projects · FY 2025 · 2024-07

PROJECT SUMMARY/ABSTRACT Neurofibromatosis type 1 (NF1) is a common genetic disease caused by mutations in the gene NF1. Most NF1 pediatric patients present with diverse neurological conditions, including learning disabilities, attention deficit and hyperactivity disorder (ADHD), and motor skill issues. No specific treatments for these issues are available and most patients perform poorly in school. Brain white matter (WM) and myelin abnormalities are commonly observed in parallel with the peak of neurological conditions in NF1, yet no clear evidence can link abnormal myelin and brain dysfunction in NF1. This represents a critical barrier to progress in the NF1 field. In contrast, evidence of central roles for myelin in regulating learning and mood is rapidly increasing. Hence, this project’s goal is to use the most recent information and tools on myelin biology to unveil specific impacts of Nf1 mutation on oligodendrocyte (OL; brain myelinating cell) / myelin development and related brain dysfunction. Understand- ing mechanisms for Nf1 mutation in mouse models will diversify therapeutic tools and schedules for NF1 treat- ments. Indirect evidence suggests roles for Nf1 in every step of OL formation and myelin development, and our preliminary results suggest transiently increased brain WM/myelin in infants with NF1. Moreover, life-long anal- yses in Nf1+/- mice suggest hyperproliferation of OL precursors (OPCs) and increased OL production in postna- tal development and, contrastingly, defective OPC proliferation in adults. Correlatively, juvenile Nf1+/- mice show increased activity and learning in a myelin regulated motor skill test (complex wheel; CW), and impaired activ- ity/learning in 1-year old Nf1+/- mice. These mice, however, have Nf1 mutated in every cell; thus, to unveil links between Nf1-driven abnormal myelin biology and brain function we propose using myelin specific models. We hypothesize that postnatally induced Nf1 mutation in OPCs increases their proliferation/differentiation, which causes transient hyperactivity and improved learning curves of fine motor skills in the CW test. To test this idea, we will use a tamoxifen inducible system to mutate Nf1 in mouse OPCs (nNf1). The Aim 1 will define the OL lineage progression in nNf1 mice, Aim 2 will test nNf1 impact on CW activity and learning, and Aim 3 will assess the rescue of phenotypes. Successful completion of these aims will help to settle a long-lasting debate on myelin- behavior links in NF1. In the mid-term, results will help to propose therapeutic targets and windows of time for interventions in NF1 patients. In line with NIH mission, this study will generate fundamental neuroscience knowledge and promote reduction of the burden of neurological diseases, particularly of NF1 on pediatric pa- tients. The PI’s expertise and research network in NF1, myelin biology, and mouse genetics will be essential for the timely completion of the aims. Furthermore, this study involves direct participation of undergraduate minority- in-science students and will produce data for high impact publications to achieve research excellence.

NSF Awards · FY 2024 · 2024-06

This new three-year REU Site: Interdisciplinary Research Experience for Undergraduates in Materials Science and Engineering at UTRGV is hosted by the University of Texas Rio Grande Valley (UTRGV) to support ten undergraduate students each year in cutting edge and comprehensive engineering research for 10 weeks. REU students will engage in hands-on learning experiences in materials science and engineering to enrich their skills in the interrelationship between structure-processing-properties and performance of materials and nano/biomaterials. One goal is to expand participants’ knowledge and understanding of the technical aspects of research and use diverse materials in real applications. UTRGV offers students opportunities to experience immersive research in a highly relevant engineering discipline and located in a unique section of the country. Students will be encouraged to present their experimental results at local and national conferences. Participants will also explore advanced degree opportunities to further their education and research at Masters and Ph. D in materials science and engineering level. This new three-year REU Site: Interdisciplinary Research Experience for Undergraduates in Materials Science and Engineering at UTRGV is hosted by the University of Texas Rio Grande Valley (UTRGV). This site focuses on research and scientific discovery in materials science and engineering and nano/biomaterials. The REU site is an interdisciplinary research program covering multiple areas related to materials science and engineering, such as polymers nanocomposites for device fabrication, carbon nanotubes, carbon nanofibers, nanocomposite brush for sensors and semiconductors, nanomaterials for Lithium-ion batteries and nano/biomaterials for biosensors and tissue engineering related applications. Students will learn how to use advanced characterization, synthesizing and fabrication techniques of materials and nano/biomaterials. Objectives of the project include strengthening participants’ academic, research, technical writing and speaking, safety, and professional capabilities and interests; enhancing participants’ understanding of academic ethics and improving their research skills; and improving the inclination and readiness to pursue graduate studies. Students will be encouraged to present their experimental results at local and national conferences. Participants will explore advanced degree opportunities to further their education and research at Masters and Ph. D in materials science and engineering level. This Site is supported in part by funds provided to the National Science Foundation by the Semiconductor Research Corporation. This project is supported in part by the HSI Program, which aims to enhance undergraduate STEM education, broaden participation in STEM, and build capacity at HSIs. 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 · 2023-09

Modified Project Summary/Abstract Section The University of Texas Rio Grande Valley (UTRGV) has established a Center for Genome Research that is building UTRGV’s genomics research capacity by 1) expanding genomic research capabilities and discoveries in two innovative research projects; and 2) enhancing the size and quality of the available genomics workforce. Leveraging the activities and resources available in the two innovative research projects, the Center’s structure and approach are designed to expand the pool of genomic scientists, clinician scientists, and researchers, at both the doctoral and technical staff levels, who can perform cutting-edge multidisciplinary genomics research. The Center’s Workforce Development Core includes efforts to develop pathways for pre-college students interested in careers in genetics and genomics to ensure that training programs will expand and become self-sustaining in the future. The Center’s Community Engagement Core is designed to improve genomic literacy in the local population and increase interest in participation in genomic studies. The research in the two multidisciplinary projects to be supported by the Center is focused on diseases that are important health issues in South Texas, nonalcoholic fatty liver disease and major depressive disorder. The team science-focused research will be meaningful to our trainees since the diseases under investigation disproportionately impact the region. The research programs leverage state-of-the-art instrumentation to provide outstanding training opportunities for faculty, students, postdocs, and residents. Cutting-edge technologies are incorporated into the projects, maximizing the impact of training and research experiences. Techniques and approaches used in the projects include bioinformatics, computational genomics, statistical genetics, molecular genetics, genetic epidemiology, genomics, proteomics, exposomics, stem cell biology, novel statistical methods, environmental chemistry, environmental epidemiology, neuroscience, imaging genomics, and medical anthropology. The proposed research areas provide an outstanding range of training opportunities and are rich with potential spin-off projects for junior faculty and senior faculty seeking to branch into genomics. Through the activities of its Administrative Core, Workforce Development Core, Community Engagement Core, and Research Projects, the UTRGV Center for Genome Research will support cutting-edge genomic research, capacity building, and training in genomics.

NIH Research Projects · FY 2024 · 2023-09

PROJECT SUMMARY/ABSTRACT Chronic pain is a major health condition in people living with Human Immunodeficiency Virus-1 (PLWH) despite the use of combined antiretroviral therapy (ART). Unlike other human immunodeficiency virus (HIV) areas of research (e.g., HIV-associated neurocognitive disorder, vaccine), chronic pain is an understudied area of research despite the prevalence of pain in PLWH, lack of effective analgesic therapy, and incomplete understanding of mechanisms. The development of therapeutic strategies and a better understanding of HIV- related neuropathic pain mechanisms have been hampered by the lack of a suitable animal model that mimics chronic neuropathic pain in PLWH. The current small animal model for HIV-related neuropathic pain consists of the acute administration of a single HIV viral protein, such as glycoprotein 120 (gp120). This model has served to determine the pain response to this viral protein and its mechanism of action. However, in addition to gp120, other HIV viral proteins, HIV-1 transactivator of transcription (Tat), and Viral protein R (Vpr) can produce pain. Therefore, a single HIV protein is unlikely to be the only contributor to HIV-neuropathic pain and mimics the HIV chronic condition where there is a continuous presence of HIV and a simultaneous presence of viral proteins. The proposed studies will test the hypothesis that EcoHIV-infected mice develop a neuropathic pain-like condition with behavioral and pathological changes that mimic PLWH with chronic neuropathic pain. A multidisciplinary approach of behavior, pharmacology, molecular biology, biochemistry, and histopathology will test this hypothesis. Aim 1. We will perform comprehensive studies to characterize neuropathic pain in EcoHIV- infected mice. We will use a battery of behavioral assessments of sensory and spontaneous/ongoing pain. Analyzing markers clinically used for the diagnosis of HIV-associated peripheral neuropathy (e.g., decrease in intraepidermal nerve fiber density) will serve to validate the EcoHIV-associated neuropathic pain model. We will also analyze neuroinflammation, a key player in the induction and maintenance of chronic pain. The proposed studies will have a significant impact on the fields of HIV and pain by providing a small animal model to study HIV-related neuropathic pain, which has been lacking. Characterization of the EcoHIV-related neuropathic pain model will advance current research on pain in the context of HIV by laying the groundwork for urgently and critically needed studies.

NIH Research Projects · FY 2025 · 2023-09

Project Summary The endocrine hormone estrogen (E2) actions by binding to its estrogen-receptor alpha (ERα), stimulates a robust mitogenic response in ER+ cells. In this regard, signal-regulated divergent transcription and its products have emerged as an important class of molecules that regulate various endocrine pathways such as estrogen and androgen signaling. Recent studies suggest that divergent transcripts are cell- and tissue-specifically expressed, and the E2-regulated divergent transcription is critical to eliciting full E2-driven gene expression. E2 signaling triggers a highly coordinated transcriptional program, leading to a robust mitogenic response that drives different cellular activities. Understanding the molecular mechanisms through which divergent transcription or transcripts regulate E2-responsive, ERα-dependent transcription will increase our understanding of the diseases caused by aberrant E2-signaling. Deciphering the molecular mechanisms of action of divergent transcripts in ER+ cells will be very important. In the preliminary study involving cellular and genomic approaches, E2- regulated divergent RNAs were identified and annotated. In addition, the initial characterization of a novel E2- regulated divergent transcript suggests that it controls E2-driven cellular processes and gene expression. In the current proposal, the molecular mechanisms by which divergent transcripts regulate E2-dependent signaling will be determined. The overarching hypothesis is that specific biochemical and structural properties of divergent transcripts underlie their ability to control critical E2-dependent pathways. A complementary set of biochemical, molecular, cell-based, proteomic, and genomic assays will be used to study the molecular mechanisms by which divergent transcript regulates E2-dependent transcription and growth of ER+ cells: specifically (1) Aim 1 will determine the molecular mechanisms of action of E2-regulated divergent transcript, in E2-dependent signaling, and (2) Aim 2 will identify the mechanism by which divergent transcripts control the assembly of E2-dependent gene regulatory complex. Successful completion of these aims will yield a new understanding of how divergent transcripts control key E2-dependent cellular pathways.

NIH Research Projects · FY 2025 · 2023-09

PROJECT SUMMARY We propose to perform a novel study in the field of cellular epidemiology, that has been made possible by the recent revolution in induced pluripotent stem cell (iPSC) technology. It is well known that there are many cell- specific functions and behaviors that have been missed by the limitations of having to rely on easily obtainable cells, such as blood cells or lymphoblastoid cell lines, for epidemiological studies of disease causation, risk factors, and biomarker identification. Advances in iPSC technologies now allow us to consider non-invasive large-scale deep cellular phenotyping efforts on disease-appropriate cell types in human subjects. Robust derivation of iPSC lines and their differentiation into organ-specific cell types is possible from blood cells. An important benefit of iPSC-derived cells is that observed biological variation primarily represents genetic influences, since most of the epigenetic memory of the historical organismal environment is lost. Our proposed study involves an innovative experimental approach to human genotype×environment interaction (GEI). While GEI is thought to exist widely, it is relatively poorly studied in humans due to environmental heterogeneity and the difficulty of controlling environmental exposures. Our iPSC-based cellular approach allows us to rigorously test for GEI experimentally by examining cellular phenotypic variation before and after a controlled environmental challenge. Our study will be the first and largest study to model human GEI in two different iPSC-derived cell types. First, we will determine if the expected neurotoxic effect of snake venom in neural stem cells (NSCs) is genetically driven, and secondly, whether the suspected differential response of alveolar epithelial type 2 cells (AT2s) to environmental pollutant exposure has a genetic basis. This project will leverage a major existing human resource, the Mexican American Family Study (MAFS). We will use existing cryo-preserved iPSC lines from 400 MAFS participants for the generation of well-characterized NSCs and AT2. We propose a novel experimental and efficient pedigree-based approach for studying the genetic basis of cellular response to environmental stress (i.e, GEI), which has previously been difficult to assess. Our aims are: 1) assess genetic basis of NSC response to snake venom; 2) assess genetic basis of AT2 response to a benzo[a]pyrene pollution; 3) examine the genetic basis of environmental disruption of cellular transcriptional coherence/homeostasis; and 4) identify pleiotropic effects of cellular stress resilience on human organismal phenotypes relevant to health. This project will employ a novel experimental and efficient pedigree-based approach for studying human GEI, which has previously been difficult to assess. It also will help establish the feasibility of epidemiological scale utilization of iPSC technology to attack biomedical problems. Finally, we expect that the proposed project will rigorously establish the cellular basis of GEI influencing complex phenotypes of relevance to human health.

NIH Research Projects · FY 2026 · 2023-02

SUMMARY Human morbidity and mortality due to tuberculosis (TB), caused by the bacterial pathogen Mycobacterium tuberculosis (Mtb), continue to be of significant health concern throughout the world. Bacille Calmette-Guerin (BCG) still remains the only approved vaccine against TB. Although BCG is considered safe and partially effective against extra-pulmonary childhood TB, its ability to protect against childhood and adult pulmonary TB is still questionable. In addition, there is a concern that BCG does not induce long lasting immune responses in the immunized individuals. However, our findings with Mtb- and BCG- derived recombinant vaccines strongly suggest that BCG can be improved to be more efficacious against TB. The goal of this proposal is to improve BCG by rationally deleting genes. We plan to sequentially delete three genes of BCG namely sapM, zmp1 and nuoG, through homologous recombination, to result in a triple knockout BCG (BCG-TKO) strain. These genes encode proteins that enable BCG to evade host immune response by preventing phagosome-lysosomal fusion, autophagy, apoptosis and other related processes in the antigen presenting cells (APCs) such as dendritic cells and macrophages. We hypothesize that deletion of these genes will allow the BCG-TKO strain to be efficiently processed by APCs, which will lead to increased antigen presentation to the immune cells and enhanced in vivo immunogenicity and efficacy. Additionally, we anticipate that deletion of these genes will reduce the virulence of the BCG, thus making the BCG-TKO to be HIV safe. We plan to accomplish our goal with three aims: 1) construct a BCG-TKO strain through homologous recombination, 2) analyze the immunogenicity and safety of the BCG-TKO strain in a SCID mouse model, and 3) investigate the efficacy of the BCG-TKO in the regular and humanized mouse models with and without HIV infection. Overall, we expect that this proposal will produce a highly efficacious, third generation BCG vaccine against TB that will be suitable for administration even in HIV infected infants.