University Of Houston

NSF Awards · FY 2024 · 2024-08

The National Center for Airborne Laser Mapping (NCALM), in operation since 2003, is a facility jointly operated by the University of Houston and the University of California Berkeley. NCALM provides airborne laser scanning surveys, high-resolution airborne digital images, and data processing expertise to the earth science community for the creation of high-quality three-dimensional (3D) data of Earth’s surface (topography), the built-environment, and vegetation. These 3D data are used by scientists to study natural processes such as landslides, earthquakes, volcanoes, the modeling of flood behavior, and storage of atmospheric carbon in forests, among many applications. NCALM is focused on three primary goals: 1) train and educate graduate students to meet the needs of industry, government, and academia; 2) advance technology that allows for the creation of high-resolution and high-accuracy 3D data; and 3) provide research-quality 3D digital data to the scientific community. Under the current award, NCALM will continue providing the research community with research-quality elevation data of Earth’s surface (topography, vegetation, and shallow water bathymetry) and digital aerial imaging. A key contribution of the facility has been the Seed project program for which graduate students from US institutions prepare proposals to request lidar data for their thesis or dissertation. These requests are competitively evaluated by an independent committee based on intellectual merit and broader impacts. In addition to the SEED program, NCALM will include a workshop to solicit input from MSI geoscience faculty and establish a short-term MSI faculty-in-residence program at NCALM. There is an increasing need to rapidly acquire high-resolution topography data immediately after an extreme event. In response to this evolving need, NCALM will pilot an "NCALM NOW" service through which researchers can request surveys to quickly acquire perishable data immediately after events. 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 summary: Since high-temperature superconductors (HTS) were discovered and awarded a Nobel prize, many prototypes of electronic and electric applications based on HTS materials have been demonstrated. A great impact on reducing energy loss and environment impact is anticipated from adopting superconducting devices and systems, including fusion systems for energy, electric propulsion for electric aircrafts, wind-powered generators, high efficiency electric power grid, superconductor magnets for high-energy physics and NMR/MRI in medicine, etc. Significant market penetration of HTS technologies, however, requires performance-cost balanced HTS materials and demands basic material research to resolve the critical issues relevant to applications in achieving high superconducting critical current density, Jc. Growth of nanoscale impurities (so-called artificial pinning centers or APCs) in HTS matrix provides a powerful approach to raise Jc in APC/HTS nanocomposites, and the method can be directly implemented to large-scale commercial HTS devices and systems. The objective of this project, supported by the Ceramics Program in the Division of Materials Research at NSF, is to investigate the growth mechanism of APC/HTS nanocomposite films in a novel multilayer approach developed by this team for strain-field guided Ca diffusion to, and cation replacement on the HTS crystal lattice, aiming to achieve a precise control over the microstructure of the APC/HTS nanocomposites for enhanced Jc at high applied magnetic fields (H). The goal is to achieve high, H-orientation independent Jc in APC/HTS nanocomposites demanded for a variety of commercial applications ranging from lightweight electric-propulsion aircraft to high-efficiency power grid, to environmental-friendly fusion, etc. The project emphasizes forefront workforce training in science and engineering and the cutting-edge research capability that integrates nanoscale material design, fabrication, modeling and characterization which will attract high-quality students to pursue careers in science and technology. Technical summary: A long-standing question in superconductors is whether the theoretical depairing limit of superconducting critical current density Jc (so-called Jd) can be reached in high-temperature superconductors (HTS) through low-cost, controllable, strain-mediated, self-assembly of nanoscale APCs to pin the magnetic vortices with optimal efficiency. Addressing the challenge in approaching the Jd in APC/HTS nanocomposites demands understanding and controlling the strain fields at atomic to macroscopic scales. Such control cannot be achieved using the traditional trial-and-error approach. The proposed integrated modeling-synthesis-characterization approach represents a leap forward from the traditionally empirical one via materials by design. The recent success of this team in the development of a novel multilayer approach for strain-field guided Ca diffusion to, and cation replacement on the HTS Y123 (i.e. YBa2Cu3O7) crystalline lattice is a demonstration of this approach. Two integrated research themes are proposed focusing on understanding and manipulating strain fields towards controllable growth of APC/RE123 nanocomposite films for optimal critical temperature Tc and Jc in a strong magnetic field (H) approaching the theoretical depairing limit. Theme 1 will focus on modeling and simulation of the effect of Ca diffusion and cation replacement on the strain field in BaZrO3 1D-APC/RE123 multilayer nanocomposites, which will guide the sample synthesis by varying the nanocomposite structure design and processing parameters. Theme 2 consists of a workflow of characterization of strain field (Ca distribution and cation replacement, lattice constant, etc.) using advanced high-resolution electron microscopy-based characterization with the modeling and synthesis in Theme 1 to develop a machine-learning approach towards materials-by-design in superconductor nanocomposites for high, H-orientation independent Jc using a microscopic control of the strain field effect in APC/RE123 nanocomposites. The goal is to achieve a thorough understanding of strain-field guided Ca diffusion and cation replacement in tunning the strain field on the APC/Y123 multilayer nanocomposites towards achieving the Jd and a new material-by-design approach for a spectrum of functional ceramic materials. 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

ABSTRACT Peer-reviewed publications are essential for successful careers in biomedical research. The development of strong writing skills is critical for early stage investigators because publishing in reputable scientific journals significantly increases the likelihood that they will successfully navigate critical transition points in their careers, pass third-year review, achieve tenure and promotion, and receive favorable scores on extramural grant applications. Persistence is required to establish effective writing habits and strong writing skills, particularly since revision is the essence of writing well. The absence of gold-standard interventions designed to assist early-stage investigators in developing scientific writing skills is remarkable given that these skills are essential for success in biomedical science. Early-stage investigators from groups underrepresented in biomedical science tend to have fewer opportunities to develop robust writing skills aligned with research careers. Those who transition to their first faculty positions without establishing writing skills and habits often have lower rates of scholarly productivity which can negatively influence the impact scores on NIH grant applications. Writing for publication programs have become commonplace over the past two decades and many attempt to facilitate writing productivity through writing groups or writing courses Writing accountability groups (WAGs) are semi-structured, peer-led writing groups with a core group of participants that meet weekly over 10-weeks to develop a daily practice of writing scientific manuscripts. Structured writing courses emphasize writing skills improvement and train participants how to write a scientific manuscript from start to finish. Both approaches have been successful in increasing scientific manuscript productivity, however none have been evaluated in appropriately powered, theoretically driven, randomized trials. To our knowledge only two studies exclusively focused on early-stage investigators from groups underrepresented in biomedical science. The objective of the proposed Write from the Start study is to assess the outcomes, benefits, burdens, and participant satisfaction of a 6-month randomized controlled trial (RCT) on manuscript writing productivity. Early-stage investigators from backgrounds underrepresented in biomedical science (n=120) will be randomly assigned to 1) an enhanced, virtual peer-led WAG + a virtual, manuscript writing course or 2) the virtual manuscript writing course alone. The number of scientific articles published 24-months will be the primary endpoint. We will test the central hypothesis that assignment to the virtual, enhanced, peer-led WAG + virtual writing course compared to the virtual writing course alone will have favorable effects on scientific publication rates.

NSF Awards · FY 2024 · 2024-08

High pressures are one of the most recognizable features of the largest habitat on Earth, the deep oceans. Pressures in the deep sea reach up to 1100 times atmospheric pressure, influencing life across scales, from genetic code to whole ecosystems. This research will use cross-disciplinary techniques in genomics, chemistry, biophysics, and physiology to understand how fishes are adapted high pressures. By comparing the genetic code and protein structures of fishes that live from surface waters to the ocean’s deepest trenches, the researchers aim to determine how high pressures have shaped evolution into deep-sea habitats. The project will also investigate how shallow-living fishes that are seeking colder habitats in deeper waters due to increasing temperatures with climate change may respond to increased pressures, informing management and conservation. These data will provide insight into the ways that pressure and temperature interact to govern biological processes, a fundamental question in biology. Research activities will directly involve undergraduate and graduate students and a postdoctoral fellow, providing valuable training, mentorship, and transformative opportunities for early career scientists across identity groups. The project will communicate deep-sea biology across broad audiences through the development of educational resources for middle, high school, and undergraduate students and a workshop following the research expedition, increasing appreciation for, and understanding of deep-sea habitats. Deep-sea ecosystems are characterized by the physiologically challenging environmental conditions of high pressures, cold temperatures, limited nutrient availability, and absence of sunlight. Despite the potential of hydrostatic pressure to impact nearly all of life’s processes, this key environmental variable is often overlooked. To understand evolution and adaptation in deep-sea fishes and to investigate the effects of pressure on shallow-living organisms moving into deeper waters due to increasing sea surface temperatures, this research addresses three interdisciplinary objectives using integrative techniques. First, genetic data from 100 species of perciform fishes from habitat depths 0–8,000 m will be used to characterize convergent and divergent patterns of genome evolution on a site, gene, and pathway level. Second, biomolecules involved in metabolism, cell structure and movement, and stress responses will be expressed and their structural changes across a full temperature-pressure regime will be measured using high pressure small-angle X-ray scattering, comparing shallow- and deep-adapted perciform taxa. Finally, the PIs will establish a new system to use the zebrafish embryo as a genetically tractable model organism to measure transcriptional responses to changing bathymetric conditions, examine the interacting effects of temperature and pressure on physiological stress responses, and to experimentally test pressure adaptation hypotheses, such as the ability of thermal acclimation to facilitate pressure tolerance through overlapping molecular stress responses, in vivo. Together, these results stand to inform understanding of evolution into deep-sea habitats, biochemical mechanisms of pressure adaptation, and marine organisms’ responses to bathymetric range shifts during climate change. This award was co-funded by the Physiological Mechanisms and Biomechanics Program in BIO/IOS and Evolutionary Processes in BIO/DEB. 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

Breast reconstruction can help feminine-presenting individuals retain or regain quality of life by mitigating the impacts of body image disruption due to appearance changes arising from mastectomy. Autologous reconstruction is widely recognized as effective, with long term advantages over other techniques. However, autologous reconstruction procedures are complex, lengthy operations requiring substantial skill and experience. Moreover, a revision procedure is typically required to adequately restore the patient’s bodily form; in some cases, multiple revisions are needed. Prior work investigated simple molds that merely copied the preoperative shape and size of the patient's breasts, or a mirrored version of the contralateral breast in the case of unilateral breast reconstruction. But many patients desire or require a different breast form after mastectomy and so simply copying the preoperative ‘native’ breast form is inadequate. The proposed study would shift current clinical practice paradigms by enabling patient-specific molds for patients whose reconstructive goals are not merely to reproduce their preoperative breasts. Moreover, while a few proof-of-concept studies have demonstrated the feasibility of using patient-specific molds to shape tissue into a breast form, a critical barrier to progress in the field is that no one has rigorously evaluated their impact. In contrast, the proposed study includes a randomized controlled clinical trial for evaluation. The goal of this study is to develop clinical decision-support algorithms for designing patient-specific breast molds for tissue shaping. We hypothesize that autologous reconstruction will be more efficient when performed with patient-specific molds designed using our clinical decision-support algorithms. The proposed project is significant because it has the potential to improve the efficiency of autologous breast reconstruction, an important component of breast cancer rehabilitation. The investigators are a multi-disciplinary team bringing complementary expertise in biomedical informatics, biostatistics, engineering technology, and reconstructive procedures. This innovative project seeks to overcome the limitations of prior studies by developing clinical decision-support algorithms to enable design of patient- specific molds that are suitable for patients whose reconstructive goals are more complex than reproducing their preoperative appearance. Our approach entails developing clinical decision-support algorithms informed by our experience in image perception, machine learning, image processing, and shape modeling, and conducting a thorough evaluation in a randomized controlled clinical trial. Our team will benefit from the extensive resources available in the Multidisciplinary Breast Reconstruction Research Program. After successful completion of this study, we will pursue a path to clinical translation analogous to existing products and services, such as current systems for designing patient-specific molds used in mandible reconstruction.

NSF Awards · FY 2024 · 2024-08

With the support of the Macromolecular, Supramolecular and Nanochemistry Program in the Division of Chemistry, Professor Eva Harth at the University of Houston and Professor Krzysztof Matyjaszewski at Carnegie Mellon University aim to develop polymeric materials based on segmented polar-polyolefin copolymers with complex properties. These polymers can then assemble into nanostructures, such as spheres, cylinders or wormlike structures. These polymers are desired to advance energy storage materials and plastic material upcycling. This is made possible by the ability to precisely design and place molecular units along the polymer chains. Some of these are reactive units in non-polar plastic materials and others are for highly activated exchange reactions allowing the precise positioning of activators to further modify the material. Results of this research enhance the knowledge in how to combine normally incompatible polar and non-polar polymer chains to gain access to novel materials. The collaborators are actively engaged in undergraduate training and committed to graduate education, dissemination, and communication of the findings to educate the general public and develop the next generation of polymer scientists. Under this award, Professor Harth and Professor Matyjaszewski and their teams will further advance the unique radical/spin coupling methodology, the polyolefin active ester exchange process and developing novel polyethylene end-capping approaches to yield precision functional polyolefins from mono- and binuclear α-diimine Pd(II) complexes. These methodologies will be used to form di- and triblock architectures as well as star polymers with strategically positioned polyolefin and polyacrylic segments. The anchoring of suitable initiation units for controlled radical polymerization and modern atom transfer radical polymerization (ATRP) techniques such as regenerative ATRP with ppm Cu catalysts and benign reducing agents will be utilized and further developed to expand the range of monomers and techniques for polar poly(meth)acrylate - polyolefin block copolymer synthesis and self-assembly. Polyolefin macromonomers for ATRP will be investigated to form bottle brush architectures and combs. These collaborative approaches will not only make segmented polar polyolefin structures more attainable but also enable the exploration of novel architectures including stars, bottlebrushes, and other tailored nanostructures, which have previously been limited by the unavailability of suitable precursors. 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

Researchers in the social sciences increasingly utilize event data sets when studying crime, protests, and terrorism. These data sets provide information on each incident, including where it occurred, who was involved, what the consequences were, etc. Unfortunately, the recorded location of incidents in these data sets are often inaccurate, due to limitations in the available information from which they are drawn (ex. incomplete media reports). Left unaddressed, these geolocation errors impair one’s ability to effectively learn about the underlying process of interest from these data. For example, geolocation errors may cause researchers to infer spatial patterns from these data that would not be found with the correct locations. In this research, investigators will develop statistical methods to better account for geolocation errors in these kinds of data. The statistical methods developed will then be applied to data on political violence, demonstrating their importance for improved understanding of real-world problems. The multidisciplinary project will also provide training for the next generation of researchers at the intersection of statistics and the social sciences. This collaborative project includes support and mentorship for graduate students. Spatial point processes are a natural approach for modeling event data. However, geolocation errors produce two distinct, but related, problems for these methods: i) duplicate event locations, and ii) inaccurate spatial coordinate information. In this project, investigators will address both issues, developing a computationally efficient statistical inference method to account for geolocation error in spatial point pattern data within the Log-Gaussian Cox Process framework. Various geolocation error structures will be considered, including nonstationary errors, to better reflect complex real-world applications. The project will include research on both the finite-sample performance and asymptotic behavior of the estimators from the developed inference methods. These methods will be used to analyze real-world political violence data from various sources. 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 nuclear envelope (NE) is a physical barrier between the cytoplasm and the nucleus that is essential for the survival and function of eukaryotic cells. The NE has a complex geometry, consisting of two lipid membranes fused at hundreds of donut-shaped pores and maintained at a stable distance from each other. How the NE’s complex geometry enables its critical functions is not understood. Prior work suggests that double-layered membrane geometries have unexpected mechanical properties that are not found in manufactured materials. This award supports studies to develop new fundamental insight into the mechanical properties of the NE, with two broad goals: 1) discover the link between NE structure and NE mechanical properties, and 2) identify mechanical principles for the design of a new generation of biologically inspired complex materials with unique functions. Findings from this project will be used to develop physics-based games for a virtual mechanics and biomechanics lab (VMBL) for teaching students about the interplay between topology and mechanics in 2D materials. The project will train students from underrepresented groups and promote their success in research and teaching. The overarching goal of this experimental and computational project is to explain how passive forces, active forces, and geometry impact NE mechanics. The researchers will experimentally quantify spatial fluctuations in the NE under perturbations of passive load-bearing proteins, active force-generating cytoskeletal proteins, and ATP depletion. Monte Carlo simulations on a double membrane system with donut-shaped pores will be performed to interpret these experimental observations and quantify NE mechanics. Experimental data will provide snapshots of membrane geometry which will be interpreted with the computational model to develop insights into the underlying mechanics and forces. Overall, the study will unravel the interplay between geometry, topology, and mechanics in soft 2D materials. 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

Many U.S. cities experience combined sewer overflows (CSOs) during wet weather. The resulting release of sewage and stormwater can have negative environmental and health consequences. Of particular concern are marginalized communities residing historically in flood-prone zones, which face heightened susceptibility to CSO impacts. Current urban wastewater systems were designed to withstand peak flows derived from outdated precipitation records. With climate change producing more frequent and intense rainfall, cities face urgent challenges to manage and mitigate CSOs in an equitable manner. This project will directly address these challenges by developing a model of the Des Moines, IA combined sewer system using real-world data. This system is similar to that of many other major U.S. cities, and therefore provides a framework for researchers to study the resilience of wastewater systems. By prioritizing equity in the scientific approach and proactively integrating future climate conditions, this research bridges the gap in system-level resilience assessment for wastewater systems, and will provide insights into the vulnerability of marginalized communities to CSOs amid climate change. This research aims to analyze the resilience of combined sewer systems in response to climate change and assess potential CSO exposures and impacts on marginalized communities. An integrated modeling framework will be created enabled by cutting-edge development in below-ground drainage modeling and it will be coupled with a qualitative-quantitative survey method to perform relevant, local phenomena-based research. The project is expected to 1) advance data analytics and modeling methodologies for urban wastewater systems; 2) assess system-level resilience of the test-bed system (i.e., Des Moines, IA) to wet weather conditions under the influence of climate change; and 3) uncover the vulnerability of marginalized communities to future likely CSO incidents. This research aims to catalyze equitable solutions in the management and mitigation of CSOs, fostering enduring benefits for marginalized communities. In addition, it will provide unique opportunities for graduate and undergraduate students to work collaboratively across universities and directly with industry collaborators, enabling a pipeline for both personnel and research to move more rapidly in and out of academia. This project is funded jointly by the CBET Environmental Sustainability program and the CBET Environmental Engineering program. 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

Cardiac fibrosis is the formation of scar tissue in the heart. This scar tissue leads to impairment in heart function. The heart is composed of several types of cells including cardiomyocytes, fibroblasts, and endothelial cells. Each type plays a critical role in heart function and tissue maintenance. During heart disease, these cells undergo transitions in response to environmental stressors. The ultimate objective of this Faculty Early Career Development Program (CAREER) award is to investigate how different cells in the heart respond to chemical and mechanical signals that cause cardiac fibrosis. The research will focus on developing a 3D tissue model that mimics the dynamics of chemical and mechanical cues in cardiac function. This project will determine how these different cells contribute to scar tissue formation and ultimately to heart dysfunction. The proposed integration of research and education will support the recruitment of graduate and undergraduate researchers from diverse and historically excluded groups into Science, Technology, Engineering, and Mathematics (STEM) careers. A specific focus will be the training of current and pre-service middle and high school teachers from the Houston metropolitan area in developing teaching modules for 7-12th graders based on tissue engineering for cardiac health. The central goal of this CAREER project is to leverage mechanically tunable hydrogel-based heart tissue models to investigate cellular, biomolecular, and mechanical cues in the onset and progression of cardiac fibrosis. This project seeks to evaluate the role of maternal autoantibodies in concert with cytokines in fibroblast and endothelial activation. The specific research objectives are to: 1) determine the role of the endothelial mesenchymal transition in cardiac fibrosis, and 2) develop a 3D cardiac fibrosis model and microfabrication techniques to investigate tissue remodeling cascades. The heart chip will support the interrogation of endothelial transition that may facilitate autoantibody translocation into the heart as well as fibroblast transdifferentiation in autoantibody mediated cardiac fibrosis. Additionally, studies will probe the impact of mechanical cues on heart tissue remodeling during disease. The integration of research and education will aim to: 1) develop the HeartChips_Teach initiative that will introduce pre-service STEM teachers to tissue engineering concepts and develop effective teaching modules for 7-12th grade students, and 2) plan ChipSquad Teaching Workshops that will train teachers from middle and high schools located in the Third Ward and Houston metro area that have a high percentage of students belonging to historically excluded groups. Teachers will be trained to develop tissue engineering modules inspired by the proposed research and suitable for executing in their classroom. The modules will be broadly disseminated and integrated into an education plan that supports 7-12th graders and K-12 STEM teachers. An industrial partner will be engaged to enhance the research and education experience by providing a more applied scientific perspective in the investigation and training process. The award will support graduate and undergraduate researchers at the University of Houston, a minority serving institution, and foster learning experiences that broaden exposure to the field of tissue engineering, thus training the next generation of diverse scientists and engineers. 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

NON-TECHNICAL SUMMARY: The pursuit of energy-efficient lighting has led to the emergence of phosphor-converted light-emitting diodes (pc-LEDs), offering the promise of reducing global energy consumption and carbon dioxide emissions while revolutionizing lighting technologies. However, a significant challenge remains in finding new luminescent phosphors that efficiently convert blue LED light into high-quality white light, while also meeting the necessary chemical and thermal stability requirements for long-term consumer and commercial use. Traditional methods have struggled to uncover suitable phosphors due to the difficulty in predicting crucial optical and chemical properties a priori. The proposed research project addresses this challenge by integrating machine learning with materials synthesis to expedite the discovery of efficient and stable phosphor powders compatible with blue LEDs. By developing machine learning models, the goal is to predict the optical response and chemical stability of bulk ceramic phosphors, thereby identifying promising candidates for further synthesis and testing. Additionally, the academic team will collaborate with industry leaders to ensure that our phosphors meet the rigorous requirements for commercial applications. This interdisciplinary effort not only advances lighting technology but also has broader impacts across various research fields, such as solar cells, by establishing a framework for predicting material optical properties. Furthermore, this program delivers hands-on research experiences for high school and undergraduate students, facilitated through initiatives like the ACS Project SEED and the Welch Summer Scholars Program, as well as an upper-level undergraduate course that integrates coding and statistics skills with materials science education. By uniting materials chemistry, ceramic science, and data science, while enhancing the connections between academia and industry, this project will be pivotal in equipping the next generation of scientists to confront the challenges of future industries. TECHNICAL SUMMARY: Replacing traditional fluorescent light bulbs with energy-efficient phosphor-converted light-emitting diodes (pc-LEDs) represents a direct approach to reducing electricity consumption. This technology relies on bulk ceramic phosphor powders, which, when applied to blue-emitting InGaN LED chips, absorb and partially convert the LED emission to produce a broad-spectrum white light. The central hypothesis of the project is that machine learning can guide the synthesis of novel phosphors predicted to possess an optimal set of optical properties, thus enhancing LED adoption rates. Objectives include the development of machine learning models to reconstruct a phosphor's excitation spectra and multi-objective regression to predict emission color. Validation will involve synthesizing rare-earth-substituted phosphors using high-temperature ceramic or solution-based "soft-chemical" methods, followed by characterization using X-ray and neutron scattering and photoluminescence spectroscopy. Moreover, the project addresses the critical need for improved chemical and thermal stability of phosphors in pc-LED-based lighting, crucial for extended operational lifetimes in harsh environments. Traditional stability assessment methods are time-consuming, often taking years. Therefore, the project proposes support vector machine and time-series machine learning modeling methods to analyze and extrapolate chemical stability information, expediting testing and materials improvements. Ultimately, the project aims to produce phosphors with enhanced optical properties, including strong absorption of blue LED radiation, desirable emission colors, and stability in challenging conditions, facilitating advanced high-quality LED lighting technologies. 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 · 2024-07

Communication between the myocardium and endocardium, separated by a layer of cardiac jelly, is essential for heart morphogenesis, especially trabecular formation. Trabeculae are sheet-like structures that increase surface area when the coronary system is not yet established. Lack of trabeculation causes embryonic demise, and excess trabeculation causes left ventricular noncompaction cardiomyopathy (LVNC). The mortality of patients with LVNC ranges from 5% to 47%. Despite its clinical importance, the mechanisms of trabeculation are not fully understood, and how the communication between cardiomyocytes (CMs) in the myocardium and endocardial cells (ECs) in the endocardium is achieved and regulates trabeculation is not fully known. Some ligands and receptors engaged in myocardium-endocardium communication are localized to membranes of CMs and ECs, yet how ligand/receptor-mediated interactions occur across the cardiac jelly has yet to be deciphered. Unlike direct cell-cell interactions, distant cell-cell communication can be achieved via several mechanisms, including diffusible factors such as morphogens and recently discovered novel microstructures such as tunneling nanotubes (TNTs) in cultured mammalian cells or cytonemes in flies. Whether a microstructure that regulates signaling interaction among distant cells in vivo in mammals was not reported, and whether a similar structure regulates the signaling interaction between the CMs and ECs during cardiovascular morphogenesis is unknown. Via genetic labeling, electron microscopy (EM), and cryogenic-EM (Cryo-EM), our preliminary data show a nanotube-like microstructure, which is named signaling bridges (SBs), extend from CMs across cardiac jelly to reach ECs temporally; SB is sufficient to activate Notch signaling; disruption of SB by deleting Cdc42 or by chemicals hinders Notch activation and alters CM cellular behaviors, resulting in trabeculation defects. These novel preliminary data establish the essential roles of SBs in signal transduction and trabeculation during cardiac morphogenesis; however, details regarding SB structure, function, and regulatory mechanisms impacting heart morphogenesis remain unknown. We hypothesize that SBs are required for the signaling interaction between the CMs and ECs to control cellular behaviors during trabeculation (Fig. 1). Three aims are proposed: we will apply various electron microscopy to determine the ultrastructure and function of SBs in Aim I; interrogate how SBs transduce signaling between ECs and CMs in Aim II; elucidate how SB mediated interaction regulate trabecular morphogenesis in Aim III. Completing the proposed studies will determine how signal interaction between the CMs and ECs is achieved and how SBs regulate cellular behavior and trabecular formation. The discovery of SBs and their functions in vivo opens new avenues for understanding intercellular interaction during cardiac morphogenesis. Successful completion of this study will expand our understanding of the etiology of trabeculation defects and, ultimately, the etiology of LVNC, thereby providing a base for developing new therapeutic strategies for mitigating LVNC.

NIH Research Projects · FY 2024 · 2024-07

Project Summary The broader use of T-cell-based therapies is still hindered by challenges related to the identification of peptide- targets that are both immunogenic (capable of activating T-cells) and safe (do not trigger on-target/off-tumor or off-target toxicities). This is in part due to persistent dependency on biased sequence-based methods, despite recent breakthroughs in structural modeling and machine learning that could be leveraged to support new workflows for the identification of tumor-associated antigens (TAAs). To address this issue, and foster the design of better T-cell-based immunotherapies, we propose a new computational environment (HLA-arena 2.0) that will integrate existing ITCR resources, with new bioinformatics methods for structural modeling and analysis of key cellular immunity receptors; namely T-cell receptors (TCRs) and Human Leukocyte Antigen (HLA) receptors. Our working hypothesis is that the combination of multi-omics data with large-scale structure-based analysis can overcome most of the limitations of existing pipelines for TAA discovery, therefore enabling the design of better and safer T-cell-based immunotherapies. To test this hypothesis, we will implement a new workflow for structure-guided TAA discovery, integrating HLA-Arena with pVACtools (ITCR-funded package for sequence-based neoantigen discovery) and CrossDome (an R package for off-target toxicity prediction). In collaboration with researchers from MD Anderson Cancer Center, the PI will develop and test workflows to address existing needs in T-cell- based immunotherapy. We will focus on two different cancer types, that represent different challenges for cancer immunotherapy. In collaboration with Dr. Lizée, we will benchmark our structure-guided TAA discovery workflow using immunopeptidomics data on melanoma. We will also run off-target toxicity predictions to identify the safest among 10 potentially therapeutic T-cell clones targeting two melanoma-derived TAAs from SLC45A2. Melanoma is a type of solid tumor for which greater success has been observed with immunotherapy treatments. On the other hand, acute myeloid leukemia (AML) is a type of blood cancer in which severe reactions to immunotherapy have been observed. In this context, we will work with Dr. Abbas to examine transcriptomic datasets (bulk and single-cell data) from AML patients, aiming at uncovering TAAs and TCRs that are associated with effective immune response to AML. Finally, we will use CrossDome and existing data on known TAAs to develop The Cancer off-target Toxicity Atlas (TCTA). For each known TAA, this new database will contain a list of potential off-targets that should be tested when targeting these TAAs with immunotherapies. Predicted off-targets will be annotated with additional data (e.g., tissue expression, HLA-binding, immunogenicity, etc). All methods will be made available to the community through user-friendly workflows, facilitating the design of better and safer T-cell-based immunotherapies for numerous types of cancer. The proposed methods will be deeply integrated into the ITCR network, creating many opportunities for future collaborations. In addition, the long-term goals of the proposed research are well aligned with NCI’s mission to achieve more effective and less toxic cancer treatments, therefore helping people live longer and healthier lives.

NIH Research Projects · FY 2026 · 2024-05

Vision loss in type 2 diabetes (T2DM) results from diabetic retinopathy (DR) which can appear at any retinal location without warning. Diabetes is the leading cause of blindness in working aged Americans but it can be difficult for clinicians to determine who will start on a path to vision loss and when. There are also millions of Americans (up to 44% of the population) with prediabetes (PreDM). These patients have impaired fasting glucose, elevated Hemoglobin A1c (HbA1c) and/or Oral Glucose Tolerance Tests (OGTT). They are at higher risk for T2DM, and most do not know their diagnosis. There is a major gap in our understanding of how and when PreDM affects the eye. It is important we close this gap as there are no treatments in the eye outside of glycemic control for early T2DM and PreDM. Methods for early diagnosis and detection, especially if location- specific, could aid in delaying DR and over the long term, saving sight. Our long-term goal is to understand how glucose dysregulation impacts the vascular and neural retina, cornea and tear film. We also seek to understand if systemic objective phenotypic differences (meaning tests of T2DM health such as fat distribution, activity levels from accelerometry and OGTT) in these patients are related to or predictive of ocular health. It is known that current tests of ocular structure and function such as multifocal electroretinograms (mfERG), ocular coherence tomography angiography (OCTA), adaptive optics scanning laser ophthalmoscopy (AOSLO), corneal confocal microscopy and tear composition are altered in early T2DM. However, PreDM has not been included in this work, and local retinal oxygenation changes have never been evaluated with these other ocular tests. There is also no knowledge as to which objective systemic and lifestyle factors put the patient most at risk for ocular changes in PreDM. Our central hypothesis is that local retinal oxygenation is altered by changes in glucose tolerance. This drives the relationship between vessel changes and retinal function, in local retinal areas. In Aim 1, a cross sectional study, we will compare subjects in the following groups: controls, PreDM patients with a wide range of impaired glucose tolerance, T2DM with no DR, and T2DM with DR. We will also use the best objective measures available to fully phenotype subject characteristics with regards to factors such as body fat and sedentary lifestyle. We will then evaluate differences between groups for structural and functional eye testing using the tests above, as well as local oximetry and levels of glucose impairment to see relationships in systemic and eye health. In Aim 2, we will follow these subjects at 1 and 2 years in a prospective cohort study to see how these phenotypes influence ocular change over time. We also plan to evaluate the timeline of ocular structure and function changes across the eye. We expect that differences in impaired glucose tolerance/phenotypes will alter ocular testing over time especially in PreDM. The ability to predict which areas are most affected and which patients are most at risk, could constitute a significant advance in diagnosis and management of this disease, which has reached epidemic proportions.

NIH Research Projects · FY 2025 · 2024-04

Abstract Black adults are disproportionately impacted by serious mental illness (SMI) and have been found to underutilize formal mental health services and seek support and help outside the formal setting to manage their mental health, creating unique pathways to mental health recovery. The recovery processes among Black adults with SMI are understudied, contributing to a lack of understanding of the recovery processes among Black adults with SMI and how they experience recovery through formal care (therapy, medication), informal support (peer, family, faith-based) and personal recovery (self-management). Despite the objective need for formal treatment, Black adults may still experience recovery from their mental health when help- seeking from multiple pathways. Multiple pathways to recovery exist, but less is known about the key mechanisms of recovery that Black adults specifically utilize to achieve recovery. The goal of this study is to understand how Black adults with SMI navigate the process of finding and then deciding to use formal services, informal supports, both or personal recovery, and which mechanisms within these unique pathways are critical to promoting recovery. It is grounded in the CHIME personal recovery framework, which encompasses five recovery processes, including Connectedness, Hope, and optimism about the future, Identity, Meaning in Life, and Empowerment, to deepen our understanding of how Black adults with SMI conceptualize the recovery process in relation to the CHIME framework and understand how service use (formal care, informal supports, or both, and personal recovery) promote and interact with the CHIME recovery processes. A qualitative phenomenological research design will be used to address the following aims: Aim 1: To explore how the dimensions of the recovery process (Connectedness, etc.) are experienced by Black adults with SMI, explore whether there are additional dimensions of recovery specific to Black adults with SMI, and to examine which of these dimensions are most salient for this population and Aim 2: To identify how formal and informal pathways of mental health supports facilitate the dimensions of the recovery process and what specific aspects of these supports facilitate recovery in Black adults with SMI. A purposive-convenience sampling approach will be used to recruit Black adults with SMI (n=40) from two groups – those who are involved in formal services or have used them in the last year (n=20) and those who have not sought formal services but engaged with informal and personal approaches to recovery within the last year (n=20). Data collection includes one semi-structured interview and interpretive phenomenological analysis will guide data analysis.

NIH Research Projects · FY 2025 · 2024-04

Project Summary: Despite the widespread occurrence of alternative splicing in skeletal muscle, the role of very few muscle-specific protein isoforms produced by alternative splicing has been studied. In contrast, altered transcript splicing and splicing regulator expression is frequently found in muscle dystrophies and aging-associated decline in muscle function and metabolism. Skeletal muscle makes up to 40% of body weight in healthy human adults and plays a predominant role in regulating whole-body metabolism. Yet, the role of alternate protein products of alternative splicing in skeletal muscle function and metabolism is largely unknown. My recent work demonstrated that the Rbfox family of RNA-binding proteins is vital for regulating skeletal muscle homeostasis in adulthood. Inducible Rbfox knockout in adult mouse skeletal muscle caused ~50% reduction in muscle mass within four weeks, altered glucose metabolism, and splicing of >740 gene transcripts. Many RBFOX-regulated alternative exons are evolutionarily conserved, suggesting roles for the alternate protein isoforms in adult skeletal muscle function. RBFOX proteins regulate mutually exclusive ⍺1 and ⍺2 exons of the MEF2D transcription factor to produce the predominant adult skeletal muscle-specific isoform, MEF2D⍺2. The four MEF2 (MEF2A-D) members of the highly conserved family of transcription factors are important for embryonic muscle development, but their role in the adult skeletal muscle is not known. The ⍺2 exon inclusion increases to >75% after birth to produce the predominant MEF2D⍺2 isoform in adult skeletal muscle. To determine the role of MEF2D⍺2, I deleted the ⍺2-exon of Mef2d using CRISPR-Cas9 to generate, Mef2d⍺2 Eko mouse line. Compared to wild-type mice, Mef2d ⍺2 Eko mice displayed reduced running capacity and muscle fatty acid oxidation. Our preliminary data indicate minimal to no change in muscle transcriptome in muscles of Mef2d⍺2 Eko mice. We also found that most MEF2D is present in the cytosolic fraction of skeletal muscle and interacts with mitochondrial and muscle metabolic proteins. Given the reduced muscle fatty acid oxidation in skeletal muscles of Mef2d⍺2 Eko mice, we hypothesize that MEF2D⍺2 protein interacts with metabolic proteins in the cytosol to optimize fatty oxidation in adult skeletal muscle. In aim1, we will identify and validate proteins interacting with MEF2D⍺2 exclusively or preferentially in vivo. In aim2, we will determine the impact of the loss of MEF2D⍺2 on its interactors and muscle fatty acid oxidation and validate top MEF2D⍺2-protein interactions in human skeletal muscle tissues. A disruption in skeletal muscle glucose and fatty acid metabolism often manifests before the development of type II diabetes and obesity, one of the most prevalent lifestyle diseases of the modern world. Thus, our work will identify a new non-canonical role of MEF2D⍺2 in muscle metabolism, which we expect to be conserved across evolution as MEF2D⍺2 exon and splice sites are conserved from fish to humans.

NIH Research Projects · FY 2025 · 2024-04

PROJECT SUMMARY Myelofibrosis (MF) is a severe disease with a low median survival rate of six years and a declining quality of life. JAK2 inhibitors have revolutionized treatment for patients with MF; however, only 30%-40% of patients respond strongly to this therapy. Identifying non-responders early is vital to clinically recommend higher-risk by effective alternative therapies that are not suggested as first-line treatments. Histopathologic examination of bone marrow biopsies is the current standard for identifying non-responders. However, this process is failing patients as it takes three years to reach a definitive conclusion. We aim to reduce this assessment period to six months, thereby improving health outcomes for non-responders and increasing their chances of recovery before the disease causes irreparable damage. This research is essential because non-responders comprise most treated MF patients (60%-70%). To accurately monitor treatment response, it is necessary to identify hematopoietic BM areas and recognize abnormal reticulin-fibers patterns within these areas. However, current methods are inadequate, as they can only identify non-responders reliably after three years. Therefore, we propose a new technology that addresses all the challenges with MF treatment assessment in a single instrument. This technology is observer- independent, label-free, and quantitative, filling a critical gap in the state-of-the-art. Although histopathology is the gold-standard method, it is susceptible to high inter-observer variability in MF due to the qualitative nature of visual inspections. This variability is because of the difficulty in recognizing fiber-pattern trends from immunohistochemical staining data. Our technology overcomes these limitations by providing a comprehensive and quantitative evaluation of the evolution of fibrosis in MF. Our proposed method using mid-infrared spectroscopic imaging (MIRSI) technologies and machine learning addresses an unmet clinical need in assessing the treatment response of MF, benefiting thousands of patients. Our preliminary studies show that MIRSI can distinguish between different tissue subtypes, including hematopoietic tissue, with high accuracy and create detailed maps of reticulin fiber disorganization within hematopoietic areas, providing a precise visualization of fibrosis progression. We propose using a MIRSI-based treatment response score to identify early trends in disease progression. We aim to validate our approach using 678 samples spanning multiple time points for each patient. This strategy will provide a robust numerical tracking of fibrosis progression, facilitate early identification of non-responders, allow them to transfer to novel therapies with disease-modifying activity, and improve the current treatment paradigm.

NIH Research Projects · FY 2026 · 2024-04

PROJECT SUMMARY/ABSTRACT Atherosclerosis-related cardiovascular diseases (CVD) remain the leading cause of death worldwide. Current therapies mainly focus on managing the risk of atherosclerosis, rather than directly targeting the plaque- causing cells. However, these treatments still carry a significant residual risk for CVD, along with various side effects. Epigenetics and metabolism often occur early in various diseases and their close interaction has led to the emergence of the concept of “metaboloepigenetics”. Yet, the precise mechanisms by which they respond to environmental cues and contribute to chromatin modifications in atherosclerosis remains unaddressed. Global changes in the epigenome are driven in part by the SWItch/Sucrose Non-Fermentable (SWI/SNF) chromatin remodeling complex. This complex utilize the ATP energy to alter chromatin structure and modulate chromatin accessibility to various molecular players, such as transcriptional machinery, cofactors. The mutually exclusive BAF60 subunits serve as a link between the SWI/SNF complex and specific transcription factors. We have demonstrated that BAF60c is essential for preservation of vascular smooth muscle cells (VSMC) contractile phenotype by strengthening serum response factor (SRF) association with its coactivator P300 and the SWI/SNF complex. Our preliminary data further show that BAF60c is the most abundant BAF60 family member specifically expressed in VSMC in the normal arterial wall, and its expression decreases in human and mouse atherosclerotic lesions. Furthermore, BAF60c deficiency in VSMC aggravates atherosclerosis in mice. Knockdown of BAF60c leads to disturbed PPARγ activation and VSMC dysfunction, characteried by increased anaerobic glycolysis, oxidative stress, lipid accumulation, transition to macrophage-like cells and foam cells. Therefore, I hypothesized that BAF60c-PPARγ axis protects against atherogenesis through metaboloepigenetic modulation of VSMC homeostasis. Our long-term objectives are to elucidate how metabolo-epigenetic interplay modulates vascular cell behavior and fate in CVD and to uncover novel therapeutic avenues for CVD by targeting BAF60c-dependent metaboloepigenetic modifications. Specifically, Aim 1 will define the protective role of BAF60c-PPARγ axis in atherogenesis using both male and female VSMC-specific knockout and transgenic mice; Aim 2 will define the mechanisms underlying BAF60c-PPARγ axis in regulation of VSMC dysfunction in atherosclerosis in vitro. In summary, these studies will provide unique mechanistic insights into the role of Baf60c-dependent metaboloepigenetics in VSMC homeostasis during atherosclerosis. They will pave the way for further exploration of metaboloepigenetics in CVD. In addition, these findings will support future endeavors to target BAF60c-dependent metaboloepigenetics and to combine metabolism inhibitors and epigenetic modulators as potential therapeutic strategies for CVD.

NIH Research Projects · FY 2026 · 2024-02

PROJECT SUMMARY The laboratory studies how genetic variation, sex differences, and environmental heterogeneity affect phenotypic differences within and between species. Determining how genetic and environmental factors affect phenotypes—and how those effects differ between sexes—is essential for understanding the mechanistic basis of traits, including many human diseases. The laboratory’s current research has three primary areas of focus: the genetic basis of sex-specific cellular, physiological, and behavioral variation; sex chromosomes and sexually dimorphic gene expression; and the regulation of the immune response to bacterial infection. The goals for the next five years involve determining the genetic mechanisms responsible for phenotypic variation within and amongst genotypes, sexes, and environments. This research will address important gaps in our understanding of why there is phenotypic variance within genotypes, and how that variation relates to phenotypic differences across genotypes, sexes, and environments. The project will accomplish its goals by combining experimental and genomic approaches across multiple species that are informative of general principles because of their unique biological features or available genetic tools. Two of those species—house fly (Musca domestica) and Drosophila pseudoobscura—harbor natural genetic variation that will be used to determine how genotype, environment, and sex interact to affect phenotypes. A third species, Drosophila melanogaster, is a powerful model organism with a rich suite of genetic and genomic resources that will be used to determine the mechanistic basis of phenotypic variation. The project will use quantitative and population genomic approaches in all three species to measure how genotype, environment, and sex contribute phenotypic variation within and among individual organisms. Comparative and functional genomics approaches across these species and their close relatives will also be used to identify genes and regulatory networks that could underly phenotypic variation. Hypothesized mechanisms identified from the quantitative, population, comparative, and functional genomics analyses will be tested using the powerful D. melanogaster genetic toolkit. The laboratory is well-suited to perform this work because of its expertise using evolutionary and functional genomics approaches to study phenotypic and genetic variation within and across species.

NIH Research Projects · FY 2025 · 2024-02

Although oral vancomycin (VAN) treatment failures in Clostridioides difficile infection (CDI) are common, antibiotic susceptibility testing is not conducted in the clinical setting. This has resulted in, and is in part due to, the lack of established susceptibility measure(s) corresponding with clinical outcomes. Our long-term goal is to develop clinically relevant microbiologic susceptibility measures that are predictive of patient outcomes in patients with CDI. The objective of this proposal is to determine if VAN inhibitory or bactericidal concentrations against C. difficile isolates are predictive of sustained clinical cure. The central hypothesis is that bactericidal concentrations will be more discriminatory and clinically significant than inhibitory concentrations in predicting outcomes. The rationale underlying this proposal is well supported by CDI pathophysiology, VAN drug characteristics, and preliminary data. As CDI is a toxin-mediated disease, ongoing production of toxins worsens clinical outcomes. Toxins are predominately produced during the stationary growth phase in which cell wall synthesis slows, thereby decreasing VAN effectiveness and allowing for continued toxin production at concentrations around the MIC. VAN MICs are also relatively non-discriminatory and generally cluster between 0.5-2 μg/mL. Isolates with the most common resistance mechanism, vanG-mediated resistance, are also known to have disproportionately increased MBCs compared to MICs. The central hypothesis will be tested by pursuing two specific aims: 1) Determine the variance of VAN bactericidal concentrations stratified by C. difficile MICs; 2) Determine if VAN bactericidal measures or MIC better predicts sustained clinical cure in hospitalized patients given VAN for CDI. This project will prove innovative through challenging the current clinical practice paradigm that VAN susceptibility testing is not needed for patients with CDI, through the expansion of our valuable biobank of 600 patients with CDI that will enable future in-depth mechanistic studies, and development of a high-throughput ATP assay to perform bactericidal concentration testing for future studies. The proposed research is significant as CDI is the most common healthcare-acquire infection and VAN is the most common antibiotic used to treat it; a VAN susceptibility measure corresponding with outcomes is critical to ensuring optimal VAN use and desirable patient outcomes. The expected outcome will provide valuable preliminary data allowing for a future stream of research into molecular diagnostics and point-of-care susceptibility tests incorporate VAN susceptibility. Compared to the CLSI-recommended but labor-intensive broth microdilution MBC method, the high-throughput ATP bioluminescence MBC assays will enable future research studies and implementation into clinical microbiology labs. These studies also lay the foundation for the PI to further expand into CDI translational research and become an independent researcher.

NIH Research Projects · FY 2026 · 2024-01

Project Summary: The University of Houston Cardiovascular Undergraduate Research Experience (UHCURE) builds on over 40 years of internationally recognized cardiovascular research and more than 10 years of a comprehensive Summer Undergraduate Research Fellowship. The main goal of UH-CURE is to equip the next generation of cardiovascular researchers with transdisciplinary research experience and a set of translatable skills to prepare them for successful research careers. The Specific Aims are: (1) To engage 10 undergraduate students annually in cutting-edge cardiovascular research across multiple disciplines, with the goal for 80% of students to report that UH-CURE has increased their interest in cardiovascular research; (2) To develop responsible research skills, with the goal for 100% of students and mentors to report improvements in students’ ability and confidence to conduct experiments and analyze data responsibly; (3) To raise awareness of the multidisciplinary and collaborative approach that combines pharmacology, pharmaceutical sciences, medicinal chemistry, and computational and AI-driven methods in cardiovascular research to advance drug discovery, with the goal for 80% of participants feel UH-CURE has significantly increased their understanding of transdisciplinary research opportunities and importance; (4) To cultivate the basic and transferable skills necessary for succeeding in graduate school and a career in biomedical research, with the goal for 80% of students to report or demonstrate a notable increase in these skills and confidence in applying for and succeeding in graduate programs; (5) To encourage students to pursue further training in cardiovascular research, with 70% pursuing additional research opportunities. These Aims will be achieved by (1) engaging students in cutting-edge cardiovascular research under faculty mentorship; (2) enhancing understanding of transdisciplinary cardiovascular research, analytical skills, and research rigor while building confidence; (3) offering targeted professional and career development through panels and workshops, networking, and guidance on crafting an individual development plan, CV, and graduate school applications; (4) cultivating transferable skills crucial for success in graduate and professional training, with a comprehensive understanding of cardiovascular career opportunities for long-term research goals; and (5) strengthening communication and presentation skills through a cohort trip to a national research conference, providing research experience, presentation practice, networking, and scientific engagement. UH-CURE program outcomes will be assessed through structured evaluations of trainees and mentors, meetings with Program Directors, and reviews of oral presentations and written research reports. Mentorship will extend beyond the 10-week program to support applications to graduate schools and to sustain career development. By providing early, rigorous exposure to cardiovascular research, UHCURE strengthens the pipeline of biomedical scientists addressing cardiovascular disease and supports the NIH’s mission to advance research training and improve human health.

NSF Awards · FY 2024 · 2024-01

Leveraging the recent abundance of U.S. shale gas resources as a chemical production feedstock requires the use of catalytic upgrading strategies. Constraints related to chemical composition and geographical distribution of both the feedstocks and products require the development of innovative catalytic strategies that can take advantage of these new resources. Motivated by the continuous growth of cost-competitive renewable electric power, the use of electrochemical strategies to enable the activation of hydrocarbon resources provides a unique opportunity to reduce the environmental impact and cost of chemical manufacturing by avoiding the high pressures and temperatures synonymous with thermally driven chemical transformations. Furthermore, the electrochemical approach is more resistant to major disruption events that pose resilience and safety threats in traditional chemical manufacturing supply chains. Therefore, the development of electrically driven chemical reaction strategies in this research program has significant transformative potential. Direct electrochemical catalytic upgrading of hydrocarbon resources, however, currently is limited by both slow reaction rates and poor selectivity to desired products. This study will advance the development of catalytic resonance, whereby the energetics of a catalyst is modulated in time to maximize the reaction rate and selectivity towards the desired product. This study will integrate concepts of sustainable chemical transformation, renewable energy sources, and catalytic kinetics into an educational plan that will engage students both at UMass and the surrounding area. The impact of outreach efforts will be expanded by developing educational online content, using simple and effective teaching techniques to communicate the fundamental science behind energy related applications. This study will focus on developing a fundamental understanding of catalytic resonance for the electrochemical oxidation of hydrocarbons into value-added oxygenates. While renewable and cost-effective energy to drive the electrochemical reactions is readily available, the rate of catalytic turnover associated with the electrochemical oxidation of hydrocarbons (e.g., alkanes, alkenes) limits the approach. Metal catalysts that do exhibit appreciable electrocatalytic activity are plagued by the lack of selectivity to partial oxidation products due to the over-oxidation of hydrocarbons into carbon dioxide as an undesirable product. Under steady-state conditions, the challenges to catalytic activity and selectivity share a similar origin: balancing the necessary adsorbate coverages, kinetic driving force, and the combination of faradaic and non-faradaic elementary steps involved in the catalytic cycle. Controlled energetic oscillations of the catalytic working electrode decouples the rate-determining factors, allowing for their independent tuning by accessing non-equilibrium states that cannot be sustained under static conditions. While this study will focus on hydrocarbon oxidation, the work will develop the understanding and capabilities needed for extending the concept of catalytic resonance to other important chemical transformations. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NIH Research Projects · FY 2026 · 2024-01

PROJECT SUMMARY In stroke-induced aphasia, deficits in auditory comprehension are prevalent, which has negative consequences for everyday communication and quality of life, as well as speech-language assessment and treatment. Auditory comprehension is not a monolithic process, but rather relies on processing multidimensional acoustic and linguistic cues contained in spoken language. There are few clinical tools available for identifying level(s) of auditory comprehension deficit(s) in aphasia, with typical assessments limited to single words and sentences. While such assessments may allow for precise identification of where deficits exist, they lack ecological validity. Moreover, these tasks require overt responses which utilize cognitive resources beyond those required for auditory comprehension, impeding precise characterization of deficits. Recent computational advances allow for objective examination of neural correlates of auditory comprehension across levels of processing (e.g., spectrotemporal, lexical) using an ecologically valid task wherein individuals listen to continuous speech while electroencephalography (EEG) responses are collected, with no overt responses required. This approach, temporal response function (TRF) modeling, involves fitting a linear function to map multivariate features of the continuous speech stimulus (e.g., spectrogram, lexical frequency) onto the EEG data. The resulting TRF is used to derive a predicted EEG, and the relation between the TRF-predicted EEG and observed EEG provides a measure of the fidelity of neural processing of that feature. TRF modeling has shown promise for use in clinical populations. However, researchers have yet to assess validity and test-retest reliability of TRF-derived measures of auditory comprehension in individuals with language disorders, severely limiting their clinical utility. The proposed study thus has two specific aims: to examine the validity (Aim 1) and test-retest reliability (Aim 2) of TRF-derived measures of auditory comprehension from the level of spectrotemporal processing through semantic and syntactic processing. To this end, 40 individuals with stroke- induced aphasia and 40 older adult control participants will complete a comprehensive cognitive-linguistic battery comprising tightly controlled tasks and standardized assessments designed to measure different levels of cognitive-linguistic processing. They will also listen to a continuous narrative while EEG responses are recorded at two timepoints. TRF modeling will be used to derive measures reflecting neural correlates of auditory comprehension which will be compared to performance on the cognitive-linguistic battery (Aim 1) and across the two timepoints (Aim 2). The proposed study has the potential to improve characterization of auditory comprehension in aphasia. Moreover, knowledge of normal variability across sessions for TRF-derived measures will help researchers to make informed inferences about treatment-related outcomes or spontaneous recovery so that test-retest variability is not mistakenly attributed to meaningful change.

NIH Research Projects · FY 2026 · 2024-01

PROJECT SUMMARY Histology is the current standard for diagnosis and predicting long-term disease outcomes in lupus nephritis (LN). However, diagnosis and prognosis are challenging due to significant inter-pathologist variance and multiple pitfalls in histopathology. We propose combining conventional histology with independent information from two complementary optical imaging modalities that provide additional morphological, biochemical and molecular context to LN, thus overcoming current diagnostic challenges. We will utilize milling with ultraviolet surface excitation (MUSE) to provide protein-specific histology and mid-infrared spectroscopic imaging (MIRSI) for label- free biochemical identification of small molecules and metabolites. Acquiring co-registered imaging data with high speed and good resolution from these imaging modalities is challenging, and we propose a new experimental platform for comprehensive biopsy imaging that addresses this challenge. We will identify new structural and molecular features across these modalities that are decisive for LN diagnosis. A deep learning architecture will be used to combine information from across all modalities, optimize feature selection and quantification. We present extensive preliminary data from kidneys of wildtype and LN murine models demonstrating the efficacy of our techniques. We will validate the efficacy of LN diagnostic metrics from murine models using archival human kidney biopsy samples. We also present data from human subjects with Class II LN (non-proliferative), Class IV LN (proliferative) and minimal change disease (control) and demonstrate statistically significant metrics derived from our imaging modalities that enable improved LN diagnosis.

NSF Awards · FY 2023 · 2023-12

Generalization of Deep Neural Networks (DNNs) has become a challenging problem. Many DNNs do not remain predictive when the distribution of data changes or there are small disturbances in the input. A major reason for this challenge is shortcut learning, which refer to decisions based on relationships in the data that exist, but which are not causal. These decisions fail when the model is transferred to real-world scenarios because of spurious correlations. This project is to investigate shortcut identification and mitigation in deep learning. The successful outcome of this research will lead to advances in providing theoretical understandings, and developing robust and generalizable DNN algorithms to analyze datasets with various types of shortcuts. The education program that integrates machine learning, industrial engineering, and health informatics is to train students with essential data analytics tools in information systems, to attract, mentor and retain members from underrepresented groups. The primary goal of this project is to systematically investigate the identification and mitigation of shortcut features from a data-centric perspective to facilitate the generalization of deep learning. The developed data-centric mechanisms could be directly adopted in real-world data analytics systems. Specifically, this project studies shortcut identification and detection at different levels, including instance-, feature-, and task-levels, and then performs shortcut mitigation through data augmentation and training regularization. This project also demonstrates how the proposed research innovations could be embedded in two DNN based real medical informatics systems. The proposed frameworks uncover the intrinsic properties of shortcut learning by calibrating shortcut features from different categories of distribution shift, and enable their comprehension and adoption for researchers and practitioners. 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.