University Of California-Irvine

NIH Research Projects · FY 2025 · 2024-09

Guided by my 16 years of experience and leadership in the NCI-sponsored clinical trial networks (NCI-CTNs), this R50 Research Specialist award offers critical support necessary to fully engage in high-yield activities across a spectrum of educational, leadership, and clinical trials-related research endeavors. Fundamental to each proposed activity is a consistent focus on improving outcomes via modern clinical trial development. I will continue to provide strong leadership in my roles as member of the NCI-Cancer Prevention Steering Committee and Co-Chair of the NCI-Gastrointestinal Rectal-Anal Task Force, inspiring the submission of novel concepts and rigorous, equitable review, enhancing the multispecialty expertise of the committee’s membership panel. As Principal Investigator (PI) for the ongoing NCI-NCORP Phase III clinical trial S0820/PACES (Preventing Adenomas of the Colon with Eflornithine and Sulindac), I am committed to completing all research activities within the five-year period of this grant, yielding the highest quality data for meaningful interpretation of our results. Given existing strong nationwide collaborations, this R50 grant will enable me to continue to engage in novel patient recruitment strategies for NCI-network-based clinical trials as we build upon our prior randomized trial evidence. I aim to leverage the protected time provided by this R50 grant to mentor junior faculty and clinical fellows from various cancer-related disciplines at our institution (UC Irvine Chao Family Comprehensive Center, UCI-CFCCC) on NCI-CTN research methodologies. Moreover, this R50 grant provides the autonomy to advance into new leadership positions that become available over the next five years locally (at UCI-CFCCC, where I currently serve as Vice Chair of the Data Safety Monitoring Board) and nationally (within SWOG and the various NCI Steering Committees). Lastly, given UC Irvine’s historic strengths in early phase cancer prevention clinical trials, this grant creates an exciting opportunity for our Cancer Center to re-engage with the NCI-Division of Cancer Prevention Clinical Trial Network (CP-CTNet). As Site PI, I propose to lead UCI as a CP-CTNet Affiliate Organization, expanding the access of our catchment area’s population to early phase cancer prevention clinical trials.

NIH Research Projects · FY 2025 · 2024-09

Abstract Accurate dose delivery at the tumor site is crucial for the success of radiotherapy (RT) for cancer treatment. However, as yet there are no techniques in clinics with the ability to monitor RT. This project proposes X-ray- induced acoustic (XA) computed tomography (XACT) to facilitate dose monitoring during RT. Pulsed X-ray radiation, when absorbed by tissues, leads to thermoelastic expansion which generates acoustic waves. These waves can be sensed by ultrasonic transducers around the irradiated tissue and fed to an XACT algorithm to reconstruct the X-ray energy deposition (XED) maps. As an expert in computational biomedical imaging, Dr. Pandey’s current challenge is to develop efficient XACT algorithms to enable real-time/near real-time quantitative monitoring of the XED: the focus of the proposed project. Existing RT setups in clinics only need to integrate a transducer array to adopt XACT-based radiation dosimetry without significantly affecting existing RT practices. Dr. Pandey is key personnel in the ongoing projects funded by the NIH/NCI (R37 CA240806) and the American Cancer Society (133697-RSG-19-110-01-CCE); Dr. Liangzhong Xiang is the Principal Investigator. These projects aim to achieve in vivo dosimetry using XACT. Although XACT has seen substantial utilization in dosimetry research, certain challenges hinder its clinical translation. The first one being suboptimal signal-to-noise ratios (SNR) in XA signals and the main focus of Dr. Xiang’s R37 research is towards developing advanced instrumentation to resolve this. Dr. Pandey’s research as well as this R50 proposal addresses the algorithmic challenges which include the limited view artifacts, absence of quantitative dose information, and lack of the capability of correcting for acoustic heterogeneity in the reconstructed dose maps. The key objectives of this proposal are coherent with the aims of the ongoing NCI and ACS projects. Protons, owing to their unique energy deposition characteristics, are an attractive choice for RT. Much like X- rays, clinical pulsed proton beams are also known to produce acoustic waves and Dr. Xiang’s group’s recent preliminary studies (with Dr. Pandey’s contribution) have shown the capability of dose monitoring during proton therapy which led to the NIH/NCI U01 Award (U01CA288351). Since XA and proton-induced acoustic waves share the underlying physics, Dr. Pandey’s algorithms from the R50 award will also benefit the U01 grant. Dr. Pandey’s doctoral and postdoctoral training in developing advanced model-based (MB) algorithms for acoustic tomographic modalities and experience with XACT qualify him to achieve the proposed aims. MB reconstructions are computationally intensive and hence, graphics processing units-based acceleration will be implemented for achieving real-time/near real-time dose monitoring. The R50 award will provide protected time for Dr. Pandey to express his research creativity to grow into a seasoned research scientist and help achieve the goals of the proposed R37 & U01 projects which will push for the clinical translation of XACT and protoacoustics for radiation dosimetry.

NSF Awards · FY 2024 · 2024-09

Recent advancements in natural language processing (NLP) have led to a rapid increase in available text data, sparking research developments in precision medicine, economics, recommendation systems, and social science. While existing deep learning methods can predict outcomes accurately, it remains unclear how to disentangle, quantify, and use complex relationships among observed textual variables. Causal inference presents a solution for extracting trustworthy causal relationships and establishing counterfactual realities. This research project aims to develop statistical theories, methods, and algorithms to learn causal structure and establish causal identifications for text data. The project will impact various sectors, including the medical, financial, and health communities, promoting interdisciplinary collaboration. To tackle the challenges imposed by text data, the research project aims to solve the following tasks: (1) Establish a new approach to low-dimensional representation learning for text variables, with a primary focus on causal identifications; (2) Develop the textual causal structural learning and causal direction learning to identify the complex causal relationships between different text variables of interest, (3) Build a comprehensive analysis framework for average and heterogeneous textual causal effects that are able to accommodate textual features, textual actions, and textual outcomes, and develop their estimations with multiple robustness. (4) Construct an individualized online policy optimization framework tailored for text variables. During the involvement of the project, efficient computational algorithms that are designed to handle the challenges posed by large-scale and heterogeneous text data will be developed and implemented. In addition, the project will conduct software development for target applications in precision medicine and personalized recommendations. 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

Recent years have seen an increased integration of ecology and evolution in the understanding of microbial populations and communities. For instance application and development of population genetic models allows investigation of the evolution of microbes in the host, and the ways in which spatial dynamics can shape evolutionary change. Increased integration physiological theories with ecology also increases predictability of microbial community assembly and function. These current advances make it clear that it is important to foster interdisciplinary interactions in understanding microbiomes. Conferences can play a central role in this type of fostering. However, travel costs, both monetary and environmental, are a barrier to increased conference participation. This conference will integrate microbiology, evolutionary ecology, physics, and mathematics, driving innovation in fundamental and applied questions. This conference will explore a novel mechanism for conferences that will allow the benefits of in person meetings while retaining the global networking available through virtual meetings. The project will develop a more sustainable model of conferences in the future and will promote the organizing similar conferences in other fields. Decreased cost will foster increased participation of a scientifically and demographically diverse set of participants. Virtual conferences as a result of the pandemic have provided an alternative to in person conferences that is more sustainable and accessible, but lack important aspects of in person encounters with colleagues. As a solution this conference will explore a hub-based conference model in microbial ecology and evolution. This entire conference will consist of six hubs meeting on the same day and interacting across four countries (USA, Mexico, UK, Switzerland). Each of the hubs will highlighting cutting-edge microbial ecology and evolution from a highly interdisciplinary perspective. This funding will support 3 USA based hubs, including awards to promote travel of students from historically underrepresented minorities in STEM. 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

This project digitizes and disseminates the historical Survey of Consumer Finances (h-SCF) from 1947-1977 and complementary data on household insurance holdings that fills an important gap in the data collected by the h-SCF. The h-SCF includes data on household demographics, location, income, assets, debts, purchase intentions, and even financial beliefs, sophistication, and expectations, among other topics. These data are unique for including information on household geography (crucial, e.g., for studying exposure to local rules or regional economic conditions) and economic expectations (important, e.g., to understanding the wedge between beliefs and behavior) that are lacking in existing data sets. Life insurance was a then-prevalent and biased savings vehicle that is poorly covered in the SCF and understudied generally. This newly digitized data can serve as an empirical foundation for models of inflation, portfolio choice, consumption, and other matters critical to rule design. This project illustrates the utility of the data by using it as the basis for a series of research papers on the causes and consequences of heterogeneity as they relate to financial decision-making and household wellbeing. This project makes several contributions. The first set of contributions pertains to data. The novel data the project generates will provide new answers about America’s past that resonate in the present. Specifically, these data will allow researchers to chart the evolution of financial behavior, wealth, and heterogeneity over a period that both is historically significant (encompassing major demographic, economic, and rule change) and offers a clean setting for causal identification. The data will also allow critical but hitherto largely ignored spatial considerations to inform future research on long-run wealth accumulation, heterogeneity, and intergenerational mobility; and enable more rigorous and micro-founded long-run analysis and rule design, increasing the timespan for testing macro models relying on household data. By filling gaps in the data available to study household finance and the evolution of American wealth and heterogeneity, this data contribution relieves a major constraint both to historical and economic knowledge, and to equitable, evidence-based rule design. The second set of contributions pertain to economic theory. The project advances knowledge on portfolio composition in the past and the causes and consequences of portfolio-choice differences, among other phenomena. Associated papers will illuminate, among other things, the extent to which practical barriers to financial access shape portfolios; whether the initial exclusion of Black households from Social Security can help explain their persistently higher participation in life insurance today, despite the decline in its returns; and the demographically redistributive effects of inflation. These papers explicitly consider the role of group identity at the intersection of macro and household finance and generate new evidence to inform policies that have substantive implications for economic justice and equality of opportunity. 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: Astrocytes are known to be dysfunctional in Huntington’s disease (HD); however, further research is needed to understand how these star-like cells develop in the context of HD. HD is a devastating, progressive, genetic neurodegenerative disease, and recent work suggests mutant Huntingtin (mHTT), the cause of disease, may trigger early molecular and cellular changes during neurodevelopment that sets up susceptibility. Data suggests mHTT impacts the maturation of neural cells into adult life and throughout disease progression. While HD is primarily characterized by the degeneration of medium spiny neurons in the striatum and atrophy of the cortex, astrocytes have become a prominent cell type of interest as a contributor to the onset and progression of the disease. Astrocytes guard and support the brain by stabilizing the blood-brain barrier, responding to stressors, and regulating ions and neurotransmitter homeostasis, all of which are dysregulated in HD. Our lab at UC Irvine has shown developmental deficits using single-nuclei RNA sequencing (snRNAseq) in HD human induced PSC- derived astrocytes (iAstros) and in rapidly progressing R6/2 HD mouse cortex and striatum. We also confirmed that HD iAstros have decreased RNA and protein of transcription factors (TFs) SOX9 and ATF3, results that support a role for these TFs in dysregulated maturation and developmental pathways. Lacking in the snRNAseq from mice is spatial information, thus I conducted spatial transcriptomics of postnatal day 0 (P0), 4-week and 12- week-old control and R6/2 mice and found early dysregulation of astrocytic developmental genes and a possible role for neuronal-derived signaling factors in astrocyte developmental impairment. Several questions remain: 1) whether HD astrocyte dysmaturation is an initial delay of maturation or a persistent impairment, 2) what is mechanistically driving spatial maturation impairments, and 3) what the impact is of astrocyte deficits on neighboring cells. I hypothesize that early impairments in astrocyte maturation set up susceptibility to HD progression later in life. To begin to address these gaps in knowledge, in Aim 1, I will investigate the role of dysregulated TFs, SOX9 and ATF3, with overexpression and knockdown in iAstros and assess cellular maturation, function, morphology, and transcriptomic pathways. Aim 2 then utilizes the spatial transcriptomics data integrated with snRNAseq to evaluate temporal and spatial regulators of regional changes with a focus on astrocyte development and maturation, and the contributions of neuronal-astrocyte signaling. I will infer cellular communication between neurons and astrocytes through ligand-receptor analysis and functionally validate my preliminary findings in vitro with iAstros. This proposal uses innovative approaches to provide the scientific community with a novel investigation of dysfunctional astrocytic developmental trajectories in HD with the aim of influencing early therapeutic interventions to impact the onset or progression of disease. My laboratory environment at UCI and individualized mentorship from my sponsors supporting my research skills in perturbing in vitro cell models and bioinformatics analysis will help to burgeon my growth as a young scientist.

NSF Awards · FY 2024 · 2024-09

Conditions such as stroke lead to a permanent loss of brain tissue. 3D neural networks (3DNN) assembled from brain cells may offer a promising way to repair damaged tissue and restore lost brain functions after stroke. These 3DNNs can be taught to recognize intentions, perform motor functions, and self-correct for mistakes. This EFRI BEGIN OI study aims to develop 3DNNs and assess their ability to process brain signals underlying movement intentions, generate movement behavior, and use feedback to self-correct. 3D bioprinting techniques to produce robust, reliable, and reproducible 3DNNs will be developed. Core principles to program the 3DNNs with intelligent behavior will be established. Further anticipating the ethical, moral, legal, and social challenges of this technology and establishing a framework for responsible conduct of research will ensure its ethical development. The research will expand public participation in science/engineering by: providing educational opportunities in advanced bioengineering and neuroscience techniques; introducing students to the critical analysis of ethical, legal, and social dimensions of research; engaging the general public, including persons with disabilities, in relevant educational opportunities; and contributing to public understanding of ethical, legal, and social implications of developing intelligent 3DNNs. Cultured 3D neural networks offer a promising path to repair stroke-damaged tissue and restore lost neurological functions. As such, the long-term vision of this EFRI BEGIN OI project is to develop 3DNNs that interface with other brain/body areas and employ self-organizing properties to learn to interpret input and feedback signals. These 3DNNs could be trained to recognize cognitive signals, actuate motor functions, and self-correct for errors. Before this grand vision can be achieved, this study seeks to demonstrate proof-of-concept that cultured 3DNNs in vitro can indeed interpret brain signals underlying motor intentions, execute motor behavior, and utilize feedback to self-correct. While immense knowledge gaps exist across various scientific disciplines, critical areas for pursuing the above vision were identified. Specifically, this study will focus on establishing fabrication and maintenance methodologies to produce robust, reliable, reproducible 3DNNs and core principles to confer intelligent behavior upon them. Achieving these goals will provide the basis for future 3DNN iterations. Further anticipating the ethical, legal, and social challenges of this technology and establishing a framework for responsible conduct of research will ensure its ethical development and application in society. Finally, while this study is motivated by a neurorestoration application, its successful completion will advance the field of biocomputing broadly. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NSF Awards · FY 2024 · 2024-09

The ability to create nanoscale structures and materials has enabled groundbreaking advances in various science and nanotechnology applications. Electron beam lithography (EBL) is one of the most reliable and important techniques for creating ultrasmall nanostructures and nanomaterials. Many ongoing projects in the STEM disciplines have an urgent need for the proposed instrument. The long-range objective in acquiring the proposed equipment is to form a nanofabrication hub at the University of California Irvine (UCI) that (1) cultivates a multidisciplinary nanoscience research and teaching program incorporating EBL at a minority serving public institution, UCI; (2) significantly improves access to and affordability of EBL capabilities in Southern California, particularly at minority-serving institutions such as California State Universities, as well as local industry; and (3) exposes Southern California K-12 students to nanoscale science and technology. Acquiring a dedicated EBL system would significantly enhance UCI’s ongoing nanotechnology research and education for research groups on campus and nearby smaller colleges, opening a path toward leading-edge nanoscale technologies. Intellectual Merit: The EBL instrument will enable advanced development of emerging nano-sciences and nano-devices at UCI, including novel nano-photonic devices, nano-bio/chemical sensors, nano-electronic devices, and nano-medical components for transformative technologies that improve human life: for instance, ultrathin metasurface photonics for next-generation imaging and display technologies, nanoscale spintronic devices for novel memory and hard drives, mechanical lab-on-a-chip nanoscale devices and sensitive bio/nano-sensors. Nano-components and devices fabricated by the system (e.g., ultrathin optical lenses, on-chip biosensors) will be used for educational and outreach demonstrations. Broader Impacts: UCI is a minority-serving and public institution serving ~ 25% underrepresented graduate and undergraduate students in the Schools of Physical Sciences and of Engineering. Acquisition of an EBL instrument will facilitate training and education for more than 150 next-generation scientists and engineers in nanotechnology, many of whom are from underrepresented groups. Exploratory use awards and discounted usage fee will be established to enhance nanoscience and nanotechnology research at smaller and minority-serving colleges in Southern California utilizing the instrument. Strong outreach and workshop activities, and our commitment to student success will give low-income students an enviable introduction to nanoscience that can help foster greater representation in the STEM fields. 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

This NSF project aims to quantify the maximal amount of power that can be drawn from variations in temperature, or in chemical potentials, by systems that can either be engineered or exist already in the physical and biological world. Motivating paradigms include chemical concentration gradients in organisms that power biological engines as well as thermal gradients that may power nano-engines. A model gyrating engine is proposed to study theoretical limits to the maximal power and optimal efficiency that thermal engines can operate during finite-time cyclic operations. The sought quantitative theory to explain limits on how much power can be generated, and suggest ways to attain such, will have a broad range of applications in engineered systems and in gaining insights into biological ones. The intellectual merits of the project include contrasting the performance of model engines to that of naturally occurring biological processes, such as bacterial flagellar motors, and to derive theoretical bounds that limit the amount power that can be generated by physical processes. The broader impact of the project is to enable technological breakthroughs in nanoscale engines and in understanding biological processes, that in turn will bring economic and societal benefits, and inspire younger generations of students. The fundamental issue that the project aims to quantify is the tradeoff between work produced and dissipation generated by a process that operates in a cyclic manner, over a finite period, and in contact with heat baths of different temperature. Such a problem, to quantify the power that can be generated by exploiting thermal gradients has been a challenging one in classical thermodynamics, yet amenable to the tools of stochastic control that have been developed in recent years. The goal of the NSF project is to thereby advance the understanding, and develop computational tools for the analysis and synthesis of processes that act as thermodynamic gyrating engines generating power from their anisotropic thermal environment. 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

Graphs, representing complex sensing and other societal systems like disease networks, social networks, and communication networks, are essential in understanding interactions within these systems. By accurately modeling relationships and structures within data via graphs, today machine learning over graphs (LoGs) plays a vital role in various applications. However, LoG introduces additional hyperparameters such as graph topologies and nodal embeddings into the already complicated neural network training processes. Traditionally, LoG approaches relied on user-defined heuristics to extract features encoding structural information about a graph. However, this process becomes prohibitively expensive in large models and high-dimensional data regimes, and the performance of LoGs highly depends on the choice of these hyperparameters. To address these challenges, the project puts forth a unified bi-level optimization-based training framework for LoGs with automatic selection of hyperparameters. The project also supports the education and diversity goals of the NSF by integrating LoGs research advances into machine learning courses taught in University of California at Irvine and Rensselaer Polytechnic Institute, making cutting-edge LoGs techniques more accessible to a wider range of researchers and students, fostering innovation and inclusivity in the scientific community. Towards this goal, this project aims to develop a bi-level optimization (BLO) framework for trustworthy and efficient LoG, called BLoG. In addition to the basic algorithm and optimization theory development for BLoG, the project will build a tri-level BLoG problem for robust and adversarial graph neural network training tasks, tailoring gradient-based BLO algorithms to these problems. The project will also develop a BLoG framework with multiple lower-level problems for multiple LoG tasks, named Fast-BLoG. Fast-BLoG will tackle fast and efficient semi-supervised graph neural network training. The project will highlight the advantages and new technical challenges of using the BLoG framework for handling machine learning tasks over graphs. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NSF Awards · FY 2024 · 2024-09

The amplification of extreme events, more frequent flooding and intense fires caused by climate change, combined with escalating anthropogenic alterations like deforestation and changing land-use practices, have led to a period of rapid transformation across landscapes. These transformations unfold over a range of space and time scales, from catastrophic rapid events due to landslides and debris flows to longer-term impacts due to bank erosion and shifting rivers in response to increased sediment and streamflow, affecting the environment, ecosystem services, and our society. Field observations of landscapes over the range of space and time scales needed for studying landscape reorganization are not available, and in cases of rapid change, such as after landslides and post-fire debris flows, real-time high-resolution observations are limited and expensive. Our research will capitalize on a unique data set of experimental landscapes where "nature" was left alone to structure and evolve landscapes under prescribed uplift and precipitation rates. The data was collected at the lab at very high resolution in space and time (0.5 mm and 5 mins) over the full evolution of the landscape (~10 h) under different conditions (steady and transient) of precipitation and uplift. These data sets offer a unique opportunity to study the workings of landscapes and the emergence of erosional extremes in response to change using novel data analytics methodologies, such as process-relevant and physics-informed Machine Learning/AI techniques. The overall goal of this research is to advance our predictive understanding of landscapes and identify the most relevant geomorphic variables driving erosion under various climatic forcings, including the emergence of highly erosional events. It is expected that this effort will inform the development of predictive models that can be used for landscape planning and management. The specific objectives of this research are: (1) Extract the local geomorphic transport laws driving landscape evolution under different climatic forcing using the large-scale experimental data and novel physics-informed explainable Artificial Intelligence (xAI) methods, (2) Quantify the imprint of structural connectivity (neighborhood dependence) on emergent behavior and nonlocal transport laws using geomorphologically-inspired Graph Neural Networks that acknowledge the landscape connectivity emerging from the flow accumulation process, and (3) Leverage the transferability of ML models (Transfer Learning) for identification of areas of extreme erosion where fewer observations are available, with a specific application to post-fire hazard assessment. This award by the Division of Research, Innovation, Synergies, and Education within the Directorate for Geosciences is jointly supported by the National Discovery Cloud for Climate initiative within the Office of Advanced Cyberinfrastructure within the Directorate for Computer and Information Science and Engineering. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NIH Research Projects · FY 2024 · 2024-09

Project Summary Adoption of digital histopathology has increased demands for gigapixel image analysis tools and methods for clinical applications. Integration of deep learning algorithms for automated tumor segmentation and cancer diagnosis from Hematoxylin and Eosin (H&E) dye or virtual (stainless) staining of tissue biopsy images have been reported. There is a significant lack of explanation and performance evaluation (black box phenomenon) of tumor segmentation and stainless staining deep learning models limiting clinician adoption in oncology practice. Results from these deep learning systems are known after the biopsy is irreversibly processed by H&E staining, and do not include confirmatory immunohistochemistry (IHC) biomarker staining diagnosis performed on adjacent tissue sections. We have previously described deep neural network systems to convert native nonstained whole slide prostate tissue biopsy images (WSI) to virtual computationally H&E stained versions validated for tumor segmentation with high precision. The goal of this proposal is developing novel methods and algorithms for pixel-by-pixel explanations to clinicians and cancer researchers for explainability of virtual H&E staining augmented with prostate tumor grade segmentation and IHC expression patterns by deep learning models for digital biopsies. Our previously published and physician authenticated Generative Adversarial Neural Network (GAN-CS) models trained with 93,199 image pairs of prostate biopsy images for virtual H&E staining and prostate tumor segmentations, and a publicly available database of clinically validated IHC analysis of prostate biopsy images will be used to generate the explainability software. A histological map that visualizes and interprets correspondence between neural representations in GAN-CS model with virtually stained prostate Gleason grade tumors in WSI at a pixel level will be generated. A separate explainable GAN- CSS model for segmentation and Gleason grading of tumors using clinician annotations from H&E and conjunctive IHC image biomarker labels will also be generated. Researchers can upload WSI into GAN-CS/S software to perform computational H&E staining multiplexed with morphological tumor segmentations and IHC expression with pixel-by-pixel visualization and explanation to characterize cellular phenotypes for cancer research and accelerate histopathology diagnoses. The open source software toolkit developed from this research can be generalized to majority of deep learning model architectures using disease labels from widely available non-stained, chemical, or virtual H&E and IHC stained images from different cancer types.

NIH Research Projects · FY 2025 · 2024-09

ABSTRACT Auditory function relies on highly specialized and precise neuronal connectivity. A significant challenge for the field of auditory neuroscience is to understand how these neural circuits form during development. Our previous work suggests an important function for caspase-3, a protease best known for its role in apoptosis. Cleaved (active) caspase-3 is present in the developing auditory brainstem prior to the period of programmed cell death. During embryonic development, it is first seen in auditory nerve axons, then in the synaptic target of these axons in nucleus magnocellularis (NM), then in the synaptic target of NM, in nucleus laminaris (NL) dendrites. Caspase-3 inhibition during development results in substantial errors in NM axon targeting and in structural abnormalities in NL, with incomplete lamination. We propose to investigate the regulation of caspase-3 activation during development. We will examine the basis for the progression of caspase-3 activation through the auditory pathway and test the hypothesis that cleaved caspase-3 is necessary in auditory axons for activation of caspase-3 in their synaptic targets. Given the extent of anatomical circuit disruption that occurs when caspase-3 is inhibited, we will investigate the effects of caspase-3 inhibition on maturation of auditory brainstem synapses. We will test auditory brainstem responses in hatchlings after caspase-3 inhibition to determine effects on hearing. We have begun to investigate the molecules through which caspase-3 influences auditory development. Our proteomics study revealed hundreds of proteins that are cleaved by caspase-3 in the developing auditory brainstem. Gene ontology analysis revealed that the most abundant cellular localization category for caspase-3 substrates was exosomes/extracellular vesicles (EVs). This finding suggests an overarching model in which caspase-3 influences the composition of EVs, which in turn provide an effective means of local communication between cells during development. We will examine enriched EV samples using tandem mass spectrometry to determine how caspase-3 regulates the protein content of EVs. We will test whether pharmacological disruption of EV formation impairs auditory development. We will use an EV grafting strategy to investigate whether EVs can rescue developmental deficits in caspase-3 inhibited host embryos. Together, these studies will advance our understanding of neural circuit assembly in the developing auditory brainstem.

NIH Research Projects · FY 2024 · 2024-09

Project summary/abstract Advances in in vivo biomedical imaging are critical for revolutionizing the ability of researchers and clinicians to peer inside the living body. These advances often catalyze major steps forward in our understanding of biomolecular and physiological processes. At present, the power of fluorescence imaging for deep tissue biomedical imaging is limited by the relative opacity of biological tissues and fluids at visible to short near-infrared wavelengths < 1,000 nm. The NIR-II tissue transparency window (1,000 to 1,700 nm) presents the opportunity to achieve molecular fluorescence imaging at centimeter-scale depths, for monitoring biomolecular processes at high spatial resolutions and in real time. To fully realize the transformative potential of NIR-II fluorescence deep tissue imaging, we must develop fluorophores that overcome major challenges of existing organic dyes and nanoparticles with NIR-II emission, such as low brightness, large size, low solubility, and toxicity. This proposed research program pioneers a new approach to develop small, bright, tunable, and biocompatible NIR-II emitters for targeted molecular imaging in vivo. We will exploit a novel class of NIR-emissive DNA-stabilized silver nanoclusters (AgN- DNAs) with 1-3 nm sizes, high-quantum yield emission, tunable fluorescence colors, and compatibility with nucleic acid chemistries. Recent experiments have uncovered the first AgN- DNAs with NIR-II emission and support the promise of creating a palette of these nanoclusters that emit throughout the NIR-II spectral region. Using high-throughput experimental screening and machine learning approaches, we will develop a set of bright, stable, and NIR-II emitting AgN- DNAs that are well-suited for in vivo imaging. In tandem, we will develop chemical strategies to transform these nanoclusters into biolabels for targeted molecular imaging by conjugating AgN- DNAs to aptamers, peptides, antibodies, and other biomolecules of interest. These hybrid biolabels will enable targeted staining and NIR-II fluorescence imaging of tumors, organs, and other targets. The utility of the new NIR-II biolabels for fluorescence imaging will be assessed in tissue models and then tested in vivo in mouse models for vascular imaging and for tracking novel breast cancer therapeutics. We envision that these new fluorescent probes will enable a new era of deep tissue fluorescence imaging, with a versatile range of applications from cancer research and therapeutics development to microvascular imaging.

NIH Research Projects · FY 2025 · 2024-09

Project Summary/ Abstract Huntington’s Disease (HD) is a devastating neurological disease with no available disease modifying therapies. Accordingly, there is a dire need to identify new therapeutic targets that can slow down disease progression and improve symptoms. HD is an inherited autosomal disease caused by expansion of the CAG repeat sequence in the Huntingtin gene, resulting in structural atrophy of the striatum and cortex. Approaches to reduce the levels of mutant Huntingtin protein in the brains of patients have so far been unsuccessful in clinical trials, so it is essential to identify new therapeutic targets. Studies have found genetic variants of multiple DNA damage repair proteins that affect the age of onset of HD. This, combined with the accumulation of DNA damage seen in HD brains and models, implicates defective DNA damage repair as a critical driver of the pathology of HD. Wild-type Huntingtin protein is part of a transcription coupled DNA damage repair complex in neurons, termed the transcription coupled non-homologous end joining (TC-NHEJ) complex. This complex is recruited to genes being actively transcribed, so that DNA double strand breaks can be quickly repaired, preserving genomic integrity and neuronal survival. Huntingtin interacts with numerous DNA damage repair proteins in this complex including PNKP, and DNA-PK. Interestingly, our preliminary data also show TAR DNA-binding protein 43 (TDP- 43) is associated with Huntingtin TC-NHEJ complex, and this interaction increases after DNA damage. TDP-43 is expelled from the nucleus and phosphorylated TDP-43 accumulates in the cytosol in several neurological diseases including HD. Another hallmark of HD is the increased level of protein SUMOylation. DNA damage repair proteins are also often regulated by SUMO, so it is important to learn how post translational modifications affect TC-NHEJ activity in unaffected and HD cells. The working hypothesis of this proposal is that incorporation of mutant Huntington into the TC-NHEJ DNA repair complex disrupts critical protein-protein interactions and promotes excess SUMOylation, resulting in decreased DNA damage repair and accumulation of DNA damage. Identifying critical protein interactions and post-translational modifications to boost DNA damage repair in HD will provide a new spectrum of potential therapeutic targets. To accomplish this, I will define the relationship between the SUMO E3 ligase PIAS1 and PNKP (Aim 1). I will identify the interface between these two proteins and design mutant iPSC lines to determine if disrupting binding between these two proteins improves DNA damage repair in HD lines. I will investigate whether TDP-43 is essential for activity of the TC-NHEJ complex (Aim 2), and how its phosphorylation and expulsion from the nucleus affects DNA damage repair. I will identify the E3 SUMO ligase for TDP-43 (Aim 3) to enable studies which modulate TDP-43 SUMOylation.

NSF Awards · FY 2024 · 2024-09

The mission of the Cal-Bridge program is to dramatically increase the number of underrepresented minority (URM) and women students completing PhD degrees in STEM disciplines and going on to join the STEM professoriate and technical workforce leadership. Students selected for the program are designated as Cal-Bridge scholars, and join a vibrant cohort-based mentoring and undergraduate research program spanning a diverse statewide network of 10 University of California (UC), 23 California State University (CSU) campuses, and 116 California Community College (CCC) campuses. With the overall CSU lead housed at CSU San Bernardino, and the UC and overall program leadership housed at UC Irvine, a network of nearly 300 CSU and UC faculty serve as mentors to Cal-Bridge scholars in the four STEM fields of Physics, Astronomy, Computer Science and Mathematics. Approximately 150 Cal-Bridge scholars will join the program over the next three years, with as many as 30-40 matriculating to PhD programs each year. The Cal-Bridge program has been running effectively as a state-wide program for 10 years; a new NSF award allows for the solidification of the program in its new fields of Computer Science and Mathematics, and for the enrichment of its extra-curricular offerings and support structures. The Cal-Bridge undergraduate program supports college juniors and seniors as they work toward enrollment in a PhD program by providing financial support for individual students as well as intensive, sustained, joint mentoring of students by CSU and UC faculty. These resources facilitate the persistence of Cal-Bridge undergraduate scholars in completing their BS degree and in successfully transitioning to a STEM PhD program. The program identifies students with academic potential, using research-based criteria developed by other successful bridge. Once selected, Cal-Bridge scholars benefit from five key elements of the program: 1. Full need-based scholarship at their CSU campus during their junior and senior years of college. 2. Two faculty mentors: one from a UC campus and one from their CSU campus, with joint mentoring on a biweekly basis. 3. Extensive professional development and participation in a cohort of academically- minded peers from underrepresented backgrounds, via regular in-person and online workshops. 4. Supervised research with UC faculty or at other REU programs during the summers, and the opportunity to present their results at regional and national scientific conferences. 5. A strong network of peer and near-peer mentoring that provides a critical additional level of support Additional goals of the program are that UC Cal-Bridge mentors improve their understanding of traditionally underrepresented students, and that UC PhD admission programs develop more holistic admissions processes that lead to greater acceptance of students from non-traditional backgrounds. 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

Cardiovascular disease is the leading cause of death nationwide. Unequal care and access to care for cardiovascular disease is a critical national problem. Innovative engineering approaches, user-acceptable wearable devices, and technology-enabled data mining have unrealized promise in both advancing care and improving access. To take advantage of these approaches and technologies, workforce training must be reconsidered and redesigned. This National Science Foundation Research Traineeship (NRT) Integrated Biomedical Engineering Social Science Training (BEST) award engages faculty and students at the University of California Irvine in a new graduate education model that brings together biomedical engineers, behavioral scientists, and psychological scientists to develop a next generation workforce able to solve problems at the intersection of cardiovascular health and technology. Through interdisciplinary workshops, courses, and a summer research internship, trainees will learn to recognize, develop, and use technological solutions to increase access to cardiovascular health and healthcare. The program will serve 30-40 students from the departments of biomedical engineering, health, society, and behavior, and psychological sciences with two years of funding provided to 15 doctoral students. The convergent training in biomedical engineering and social sciences, and engagement with community and industry partners will prepare the trainees for careers in which they transform practices in industry, government, and academia. Trainees will receive interdisciplinary training in social determinants of health, engineering design, and best practices in collaboration and scientific mentoring. Moreover, training will include a unique immersive research internship in a community care center to ensure that those most affected by lack of access are engaged in finding solutions. The research theme of using technology to advance cardiovascular health, healthcare, and healthcare access will serve as the basis for meaningful interdisciplinary collaboration. The workforce trained through this NRT program will be able to use new and existing technologies to understand the root causes of cardiovascular health disparities, develop tools and systems that improve cardiovascular health and healthcare, and study the individual, local, and national barriers to acceptance of novel technologies for improved cardiovascular health and healthcare. The program will introduce trainees to the science of team science and will provide team science skill training at multiple stages of each trainee’s participation in the program to support continued development of team-based approaches to problem solving. The project outcomes will be a demonstrated, well evaluated model for transformative graduate training that is effective in developing trainees with the knowledge, skills, and values to collaboratively address health issues with technology. Finally, a science of collaboration study conducted throughout the NRT project will explore the dynamics and efficacy of strategies designed to promote interdisciplinary collaboration by faculty and trainees in this program. The NSF Research Traineeship (NRT) Program is designed to encourage the development and implementation of bold, new, and potentially transformative models for STEM graduate education training. The program is dedicated to effective training of STEM graduate students in high priority interdisciplinary or convergent research areas through comprehensive traineeship models that are innovative, evidence-based, and aligned with changing workforce and research needs. 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. Accumulation of α-synuclein (α-syn) protein aggregates in brain neurons is thought to play a causal role in Parkinson's disease (PD). There is mounting evidence that the gut is a source of α-syn aggregates in the brain; however, the factors involved remain incompletely understood, limiting development of treatments to prevent PD. We propose a gut microbiota-mediated mechanism of α-syn aggregation. In the brain, α-syn aggregation results when oxidative stress within the host transforms iron and dopamine into a toxic pair. This toxic pair kills dopamine-producing neurons, decreasing dopamine levels and causing motor dysfunction. We hypothesize that in the gut, the microbiota—not the host—creates the oxidizing redox potential that modulates α-syn aggregation. Our preliminary experiments in vitro and in a C. elegans model of PD indicate that when the gut microbe E. coli performs nitrate respiration, yielding the oxidizing agent nitrite, a formerly innocuous trio of gut molecules—Fe2+, dopamine, and α-syn monomers—transforms into one that generates toxic α-syn aggregates. What remains unknown is the impact of bacterial nitrate respiration on α-syn aggregation in the mammalian gut. As accumulation of α-syn aggregates in intestinal tissue foreshadows neurodegeneration in the brain, there is a critical need to discover the factors that initiate aggregation of α-syn in the GI tract so that early interventions can be developed to stop PD before neurons die. This application’s objective is to determine the molecular mechanism underlying nitrite-induced α-syn aggregation in intestinal epithelial cells and to examine this mechanism as a gateway for α-syn aggregates to spread to neurons and cause motor impairment. Such work would represent a major step toward demonstrating the relevance of this phenomenon in human PD. The proposed approach to address these knowledge gaps entails (1) revealing the role of dopamine in α-syn aggregation in host intestinal cells by using chemical and genetic tools, (2) determining the impacts of nearly 100 gut microbes (in isolation and in combination) on α-syn aggregation in intestinal cells and mapping biochemical responses via proteomics, and (3) tracking the formation and fate of α-syn aggregates in intestinal cells by using bioluminescent reporters. Upon completing this research, our contribution will be a detailed molecular mechanism for how the gut microbiome initiates α-syn aggregation in PD. Our 3 complementary but independent specific aims interrogate this process at the level of molecules (Aim 1), the microbial ecosystem (Aim 2), and host physiology (Aim 3), providing a holistic roadmap for clinical translation. This work is innovative because it employs an unprecedented systems-level approach to define and control the gut microbiome’s role in PD. It is significant because it will likely reveal new therapeutic targets for PD, potentially including intestinal dopamine and common species of gut bacteria. The most promising therapeutic candidates can then be tested, first in mouse models and then potentially in clinical trials, to inhibit the spread of α-syn aggregates from the gut to the brain.

NIH Research Projects · FY 2025 · 2024-08

ABSTRACT The importance of communications between nerve cells and immune cells in skin has been increasingly recognized, as are the contributions of sensory neurons and the neuropeptides they produce to skin inflammation and disease. Topical therapeutics that target neuro-immune interactions are needed to curtail aberrant skin inflammation in diseases such as psoriasis and atopic dermatitis and to alleviate the disease-associated pathology, pain, and itch. Our ongoing research aims to develop effective topical options to complement systemic immune-targeting biologics, providing targeted relief and improving patient outcomes. The goals of this application are to develop recombinant, cell-penetrating botulinum proteases that inhibit the release of neuropeptides and cytokines in neurons and immune cells, respectively, to examine the in vivo penetration of topically applied proteases into skin with mild barrier perturbation, and to test the utility of the engineered proteases in reducing skin inflammation. Botulinum neurotoxins (BoNTs), such as Botox®, have been widely used in clinics as medicines and cosmetics. BoNT specifically targets motor neurons and deliver its light chain (LC) protease to the cytosol, where it proteolytically cleaves SNARE (soluble N-ethylmaleimide sensitive factor attachment protein receptors) proteins and blocks neurotransmitter release. Prior studies also suggest that BoNTs are able to suppress neuropeptide secretion, such as substance P (SP) and calcitonin gene-related peptide (CGRP), in the skin via disrupting SNARE-mediated vesicle fusion and lead to improvement of inflammation in psoriasis. However, the therapeutic potential of conventional BoNTs in psoriasis is inherently restricted because BoNTs preferentially target motor neurons over sensory neurons and they are ineffective on immune cells. To overcome these limitations, we have engineered recombinant cell-penetrating LC proteases of BoNT that can autonomously enter cells and selectively cleave SNAREs in sensory neurons and/or immune cells to regulate neuropeptide secretion and immunological effects. Here, we propose to further develop and characterize cell-penetrating LC proteases and examine how they inhibit vesicle fusion and secretion in cultured neurons and immune cells (Aim 1). We will also characterize the activity of the engineered LC variants in mouse skin with topical delivery and perform preclinical studies to examine how topically applied LCs affect skin inflammatory response using mouse models of psoriasis (Aim 2). Completion of this work will result in a new and widely-applicable strategy to regulate inflammation in skin that can be further developed as topical therapeutic candidates for the treatment of many skin diseases.

NIH Research Projects · FY 2025 · 2024-08

PROJECT SUMMARY/ABSTRACT Every year, millions of patients suffer from impaired wound healing due to injuries, surgeries, and diseases, creating a significant public health and economic burden. The process of skin wound healing involves clotting, inflammation, cell proliferation and migration, re-vascularization, and remodeling, and often results in scarring. In diabetic patients or large wounds, insufficient angiogenesis slows healing and worsens scarring. Attempts to deliver growth and angiogenic factors or cells fall short of providing complete relief, and there is a critical need for new strategies to promote angiogenesis and tissue repair during wound healing. The proposed project aims to develop a novel therapeutic approach for improved angiogenesis during wound healing by leveraging natural interactions of immune cells. We propose to deliver apoptotic neutrophils (AN) within a degradable hydrogel scaffold that will induce efferocytosis and phagocytosis, respectively, in local macrophages (Mφs), promoting their angiogenic signaling and tissue repair without causing inflammation. In preliminary work, AN delivery in a gelatin methacrylate (GelMA)-based hydrogel significantly enhanced angiogenesis in a murine skin wound model, both in wild type and in diabetic mice. Furthermore, addition of AN and/or GelMA to macrophages in culture stimulated their secretion of angiogenic growth factors. We propose here to investigate the effects of GelMA-AN on Mφ uptake and growth factor secretion (Aim 1), and on angiogenesis and wound healing of a full-thickness skin wound (Aim 2). This project will establish a new method to enhance Mφ angiogenesis signaling, providing a platform for further investigation, and developing a therapeutic intervention for improved wound healing. This proposed approach leverages the role of immune cells and angiogenesis in wound healing, with modulation of Mφs phenotype conversion for successful wound healing and tissue repair.

NIH Research Projects · FY 2024 · 2024-08

Project Summary/Abstract – Overall: The UCI Vaccines for Pandemic Preparedness Center (VPPC) The Mission: "To contribute to human health and well-being by developing agile, safe, effective and accessible vaccines that protect the vulnerable against future pathogens of pandemic importance and by educating the next generation of vaccine scientists that will tackle such challenges.” Joshua Lederberg envisioned the world as a battlefield between microbes and man, famously saying, “The future of humanity and microbes likely will unfold as episodes of a suspense thriller that could be titled Our Wits Versus Their Genes” (Lederberg, 2000). Although the genes of the microbial world have been evolving much longer than our wits, we have come up with efficient ways to respond to infectious diseases, but regrettably evolving microorganisms keep managing to challenge and outsmart us. The latest COVID episode in this series sensitized the world again to the importance of learning from the outbreak experience and challenges us to better prepare for the next one. The 100 Days Mission (100DM), endorsed by government and non-government organizations worldwide is a proposed response to the next “Disease X” by making safe, and effective vaccines available within 100 days of the pathogen’s identification. Achieving that goal could defuse the threat of a pathogen with pandemic potential. The International Pandemic Preparedness Secretariate (IPPS), the Coalition for Epidemic Preparedness Innovations (CEPI), the HHS Administration for Strategic Preparedness and Response (ASPR Next) and the NIH/NIAID have embraced the concept of studying prototype pathogens as a critical element of preparedness. By developing vaccines on rapid-response platforms against examples of a given viral genus or family, researchers can address scientific challenges characteristic of that family in advance, providing an important head start on developing vaccines against related threats. Universal programmable vaccine platforms that can be rapidly employed against broad virus families can be evaluated in clinical trials to provide confidence in their safety, and manufacturing, and regulatory considerations can be managed ahead of the next outbreak. The UC Irvine Vaccines for Pandemic Preparedness Center (VPPC) aims to conduct basic and translational research to develop vaccines against prototype members of the Bunyavirus, Paramyxovirus and Picornavirus families with demonstrated immunogenicity and efficacy in animal models. Two universal, programmable, rapid response vaccine platforms will be characterized and compared in this study: the i) Adjuvanted Recombinant Protein (ARP) Vaccine, and ii) mRNA/Lipid Nanoparticle (LNP) Vaccine. Such prototype vaccines will need to be tested in advance, at a minimum, for clinical safety and immunogenicity, and efficacy where possible, so that emerging viruses in the same family can be rapidly and safely deployed. Gathering such data and experience will build confidence in these rapid response platforms and inform regulators as they make decisions about the emergency authorization of vaccines against related pathogens.

NIH Research Projects · FY 2025 · 2024-08

PROJECT SUMMARY / ABSTRACT Coronary artery disease, aggravated by arterial calcification, poses a significant challenge to successful percutaneous coronary intervention (PCI). Coronary artery calcification (CAC) reduces vessel compliance and increases the complexities of stent deployment, stent expansion, balloon expansion, and results in uneven drug distribution. Specifically, reduced vessel compliance prohibits stent delivery and reduces the ability of deployed stents to expand, or causing “stent regret”, resulting in stent failure through either restenosis or stent thrombosis. Importantly, these complications are exasperated in highly stenotic CAC lesions – hence, endovascular devices and therapeutic techniques are needed with improved safety and efficacy to advance the clinical management of CAC. The objective of this proposal is to develop novel metasurface optical guidewires for therapeutic applications to treat previously untreatable highly stenotic CAC lesions. Our project addresses these challenges by hypothesizing that: 1) metasurfaces are specialized planar lens elements that can provide optimal energy delivery over a sub-millimeter profile; 2) with advances in fiber-coupled diode laser technologies, fiber-optic metasurfaces are an attractive platform for endovascular devices; 2) a flexible, small-diameter fiber-optic embedded guidewire with metasurfaces – termed 'metasurface optical guidewires' – can offer dual benefits of a rapid exchange monorail for PCI devices and provide light-based endovascular therapeutic capabilities including laser intravascular lithotripsy (L-IVL). The metasurface optical guidewires and associated innovative light-based endovascular therapies will be successfully developed and demonstrated by completing the following specific aims: Aim 1: Design, develop and manufacture metasurface optical guidewires for precise control of intravascular laser dosimetry; Aim 2: Develop a PCI workflow for use of an metasurface optical guidewire for laser intravascular lithotripsy (L-IVL); Aim 3: Develop a PCI workflow and study L-IVL’s efficacy in a preclinical model; Aim 4: Evaluate L-IVL treatment efficacy in a pre-clinical CAC animal model. Successful completion of these aims will lead to the development of the metasurface optical guidewire and other innovative devices and procedures that can significantly improve PCI outcomes in patients with calcified coronary arteries, reducing complications and enhancing patient care.

NIH Research Projects · FY 2025 · 2024-08

Abstract Human pluripotent stem cells (hPSCs) transplantation therapies offer an appealing avenue to combat skeletal muscle diseases. Directed differentiation of hPSCs to skeletal muscle is among the few robust in vitro systems able to increase PAX7 expression by 1,000-fold. However, a drawback of these hPSC-derived muscle cells is that they are functionally immature compared to true adult muscle stem cells. Just as adult stem cells are dynamically regulated by their niche, embryonic niches formed in development equivalently control cell fate decisions to mature from an early precursor or progenitor and eventually to an adult quiescent stem cell. Importantly, embryonic niches also change over developmental stages, but for hPSCs which form muscle the niche is understudied or has never been studied. My work is significant because niches which support muscle stem cells during the repair process, also develop in parallel with the maturation of progenitor and stem cells from development through to adulthood. This proposal consists of complementary in vitro and in vivo aims with the overall goal of supporting PAX7 cell functions and numbers from hPSCs. In Aim 1, we will interrogate how muscle cells arise in the first place and develop through key functional hallmarks of myogenesis. To accomplish this aim we will use a lineage tracer built of a key myogenic commitment factor, SIX1, and test whether SIX1 co-factors lead to functional maturation of hPSC myogenic cells. When hPSCs differentiate to muscle they also produce impure cultures containing non-myogenic lineages that we hypothesize support the muscle cells in culture. We will use genetic inhibition of master transcription factors of these non-myogenic lineages to test their need in the support and generation of hPSC muscle. Aim 2, seeks to understand how to support hPSC muscle cells once they are made. We will build a simplified in vitro niche made of myotubes, extracellular matrix taken from human tissue muscle, and PAX7 muscle progenitors, and over express key ligands and receptors that we have already identified by spatial RNA seq to test their potential to support PAX7 cells. We will also test the key role of hypoxia in hPSC PAX7 cell support in vitro. Lastly, in Aim 3, we will pivot to in vivo systems using a mouse model available in the Hicks lab that inducible ablates the mouse Pax7 cells and enables improved engraftment by hPSC PAX7 cells. We will first perform a series of in-depth time course experiments to identify the timing of skeletal muscle stem cell niche formation following hPSC PAX7 cell transplantation. We will then use an inducible overexpression system to test the function of a key hPSC muscle niche factor, MEGF10, for enabling gain-of-function in at multiple stages of PAX7 niche formation. Finally, we will test whether MEGF10 induction can improve the ability of hPSC PAX7 cells to repopulate new myofibers and re-establish in vivo niches after injuries once transplanted. Successful outcomes of this proposal will shed new light on how human muscle commits and matures from hPSCs for improved cell therapies and identify key SC niche factors that can drive muscle regeneration and support its stem cells.

NSF Awards · FY 2024 · 2024-08

For many years, there have been efforts to bring quantitative theory and computational modeling—long cornerstones of engineering and the physical sciences—more firmly into the domain of molecular and cell biology. Harnessing computational modeling in its various forms has helped advance fundamental understanding of how molecular interactions contribute to cellular function, along with accelerating biotechnological innovation. However, the research landscape is changing faster than ever, due to advances in measurement technologies (e.g., sequencing, imaging) and computing (e.g., machine learning and artificial intelligence). This project seeks to provide a forum in which the community can discuss and define best practices for integrating experimental and computational biology research, given the rapid changes in the modern research landscape. The Broader Impacts of the work include the intrinsic merit of the proposed work as it will help the broad community cell and molecular biologists keep pace with new advances in computation and bring computational scientists into the field of biology. The work will also involve the training of a breadth of young scientists. An overarching goal of this project is to connect and strengthen the interdisciplinary research community that is harnessing computational modeling in its various forms to tackle complex biological questions. The major activity will be an annual meeting, which will draw researchers from a broad cross section of disciplines, types of institutions, career stages, and geographic locations (primarily U.S.). Participants in this Research Coordination Network will tackle critical questions facing the field regarding methodology, training, collaboration, standardization, and more. Expected outcomes include the kickstarting of new collaborations, better understanding and documentation of the relevant stakeholders (e.g., industries, centers, institutions, programs), and dissemination of best practices and updated paradigms for experimental-computational biology 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 · 2024-08

One of the most striking features of physical theory over the past century has been the deep and fundamental role of symmetry. Both Einstein’s General Relativity and the Standard Model of Particle Physics are built on symmetry principles, as are frontier theories, such as string theory. Symmetry principles have guided new theorizing, and they have led to the discovery of new fundamental particles, such as the Higgs boson. This project seeks to uncover why symmetry has been so powerful a tool, by revisiting a cluster of fundamental issues concerning how physicists use mathematics to represent the world. A clearer understanding of why symmetry has been so powerful will provide new insights for interpreting contemporary physics and building the next generation of theories. This work will result in both research articles for a professional academic audience and several articles written for a general audience, exploring the role of mathematics in physics and the meaning of symmetry. It will also support training a diverse cohort of PhD students in contemporary philosophy of science. The goals of this project in the philosophical foundations of physics are to first develop a systematic approach to understanding symmetry in physics, based on the idea that symmetry is (always) a guide to what structure the world must have in order to make sense of the fundamental laws and equations of physics; and second, to explore applications of this account to foundational issues in physics. The account of symmetry will be developed in a series of articles exploring how it relates to the status of laws of nature, mathematical representation, the epistemology of science, and structural realism. The applications considered will include the status of the strong equivalence principle in general relativity, the status of the gauge argument in particle physics, and the status of a class of mathematical theorems that infer the specific form of certain physical laws from assumptions about symmetry. 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.