University Of California Riverside

NSF Awards · FY 2025 · 2025-01

With the support of the Macromolecular, Supramolecular and Nanochemistry Program in the Division of Chemistry, Prof. Francisco Zaera of the University of California, Riverside, will explore ways to improve the quality of thin metal films grown on solid surfaces by using atomic layer deposition (ALD). ALD has gained prominence in microelectronics fabrication, catalysis, and the design of energy-related devices such as batteries and supercapacitors due to the high film quality and conformality at a sub-nanometer scale, despite of surface roughness and complexity. However, one key challenge remains when growing metal films because metal atoms sinter into 3D nanoparticles (NPs). Prof. Zaera addresses this challenge via pre-conditioning of the surfaces to produce smoother and better-quality metal films. The knowledge gained shall benefit aforementioned applications, and serve educational purposes by illustrating basic principles in kinetics, catalysis, film deposition, and NP synthesis in undergraduate and graduate classes. Collaborations with Latin American research groups will be forged, and student participation from groups underrepresented in research, Hispanics in particular, will be strongly pursued. The main hypothesis underpinning this project is that control of the structure of the metals deposited on solids by ALD can be achieved via appropriate preconditioning of the surface of the underlying substrates. It should be possible to tune the size and surface density of ALD-grown metal NPs by adjusting the surface density and nature of the ALD nucleation sites: a high density should lead to the rapid coalescence of the developing metal NPs in the early stages of the ALD into 2D films and, conversely, a low density should allow for the NPs to grow in size before coalescing. Zaera's objective will be to study the molecular level chemistry that can afford such control, in particular the use of surface preconditioning as a way to define the characteristics of the metal NPs grown by ALD. Three approaches will be tested: (1) the increase of the density of silanol surface groups to act as nucleation sites; (2) the silylation of the substrate to partially block its nucleation sites; and (3) the derivatization of the nucleation sites to modify the surface chemistry of the metal ALD. Mechanistic studies will be carried out with model flat substrates and controlled ultrahigh vacuum (UHV) environments, relying on a combination of surface-sensitive techniques, including x-ray photoelectron spectroscopy (XPS), temperature programmed desorption (TPD), low-energy ion scattering (LEIS), secondary ion mass spectrometry (SIMS), and Fourier-transform infrared spectroscopy (FTIR). Studies of the preconditioning of the surface will be correlated with subsequent metal ALD tests. 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 2025 · 2025-01

In 1948, Claude Shannon identified error correcting codes as the key tools which enable communication over a noisy channel. Codes have been extensively studied ever since, resulting in remarkable optimizations, generalizations and diverse applications. Important work in the 1990s showcased code constructions based on "pseudorandom" objects in discrete mathematics. This connection between pseudorandomness and coding theory has subsequently evolved to the point that today it is routine for advances in coding theory to follow from results in pseudorandomness. This proposal will explore the interplay between pseudorandomness and coding theory from several angles with the intention of constructing new codes and deepening our understanding of pseudorandomness. Work from this proposal will result in publicly available educational materials including new course materials and technical video streams which will benefit experts, students, and enthusiasts alike. In more detail, we aim to improve recent code constructions based on expander graphs. One recent line of work has used expander graphs to design error correcting codes which approach the Gilbert-Varshamov bound, the optimal tradeoff possible between two important code parameters: distance and rate. A second recent line of work has used "high dimensional" versions of expander graphs to give locally testable codes which have constant rate, soundness and query complexity. Interestingly, both of these codes can be viewed as heavily derandomized versions of the same basic object: the XOR code. Surprisingly, though the XOR code is very simple, many of its fundamental properties are not well understood. We will explore different ways to improve these recent codes by answering questions about the XOR code. For example, is the XOR code combinatorially list decodable beyond the Johnson bound? Is the "natural" 3-query local test on the XOR code sound? Affirmative answers to these basic questions could translate to high-impact advances. This proposal will aim to answer these and other questions in order to improve modern state-of-the-art codes. 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 2025 · 2025-01

The broader impact of this I-Corps project is the development of sensors for a wide array of previously undetectable chemicals. Global industrialization has created advanced materials and chemicals that persist in the environment with lasting effects on human health. Current technologies that test for environmental contaminants using chromatographic methods and laboratory test kits are slow, expensive, and inaccessible to consumers. This chemical sensor technology may provide portable test strips (similar to those used to test for COVID-19) to test for small molecules characteristic of pharmaceuticals, pesticides, and per- and polyfluoroalkyl substances (or PFAS). This technology may make field-based and in-home testing of pesticides and PFAS possible for the first time, giving consumers and regulators a way to alleviate safety concerns about pollutants in drinking water and food. This I-Corps project utilizes experiential learning coupled with a first-hand investigation of the industry ecosystem to assess the translation potential of PYR1 biosensors, plant hormone receptors that, when mutated, may be used to identify a wide variety of chemicals, including environmental contaminants (e.g., organophosphate pesticides and PFAS). Ligand recognition occurs exclusively in the PYR1 subunit, not the HAB1 partner, which makes the system significantly easier to engineer for new ligands than previously developed methods. The efficacy of these sensors has been demonstrated in yeast, bacteria, plants, and in vitro to test for substances of abuse in blood, urine, and saliva. These sensors also have been stabilized for high temperature and used as sensors in living plants. To date, the sensors have been designed for hundreds of target molecules, and ongoing refinement of the pipeline methodology makes it possible to identify sensors for new targets in less than a week. 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 · 2024-12

ABSTRACT Mosquitoes use their chemosensory systems to smell and taste the human host skin, and in the process of subsequent blood feeding, transmit diseases like malaria and Dengue to hundreds of millions of people each year. The olfactory and gustatory systems are thus excellent targets to design repellents that reduce mosquito bites and disease incidence. Topical repellents like DEET are effective against mosquitoes, but are rarely used by at-risk populations in tropical countries for reasons of high-cost relative to incomes, inconvenience of concentrated and repeated application on the skin, and poor cosmetic properties. Globally, the most widely-used intervention is spatial protection from pyrethroid insecticides emitted at low doses from heated dispensers or burning coils. However, the rapid spread of pyrethroid resistance in mosquitoes is cause for great concern about the continued effectiveness of these measures. There is an urgent need to develop safer and more effective repellents and pyrethroid analogs, but traditional chemical ecology approaches, pharmaceutical screens, or receptor targeting have not yielded candidates, and have prohibitive costs for testing for human use approval. In a recent breakthrough, we developed an AI-based cheminformatic method to predict new repellents and new pyrethroid-like molecules from in silico screening of >10 M compounds. In preliminary studies, we tested a subset of the top repellent hits in a behavior assay and validated a high success rate in finding pleasant-smelling repellents from natural sources, including food and flavor compounds. We also tested several pyrethroid-like hits, which identified two new pyrethroid analogs that appear to be up to 100x more effective than allethrin, an industry standard. We now propose to identify the best-in-class insect control compounds that exceed current actives in four important categories: a pleasant topical repellent with longer protection (>12-24 hours), a spatial repellent for indoor or small outdoor spaces, a pyrethroid analog that is active on resistant mosquitoes for bednets or uniforms, and a spatial repellent-pyrethroid formulation that is effective against knockdown-resistant mosquitoes. Our approach is to validate a larger subset of computationally-predicted repellents, representing diverse chemical structures and properties, in various topical and spatial behavior assays. We will apply additional secondary screening criteria to group and select hits for further analysis: responses in taste neurons for topical repellents, prolonged activation of CO2 neurons for spatial repellents, and receptor pathway function as determined from analysis of available Aedes aegypti co-receptor mutants for blends. We will also determine the efficacy of the two newly discovered pyrethroids using topical and spatial assays. Finally, we will test combinations of identified repellents and pyrethroid analogs. Completion of this work will identify safe, affordable, and pleasant-smelling blends that are better than existing actives in reducing contact between humans and mosquitoes. The proposed studies will also provide insight into modes of repellency action and lay the groundwork for future identification of selective receptors for developing targeted control approaches.

NSF Awards · FY 2024 · 2024-12

Protein regulation is vital for maintaining cellular function. Many proteins are regulated by interactions between two proteins, where a small molecule, termed molecular glue, binds at the interface between them. Molecular glues play a crucial role in cellular processes by facilitating these interactions, thereby helping to regulate cellular function more efficiently. Additionally, in nature, proteins often co-localize or assemble to accelerate biomolecular processes. In this project, the investigator will computationally simulate protein-glue-protein binding and dissociation to understand how a molecular glue mediates complex formation and why co-localizing proteins can facilitate their functions. Through iterations of experiments with collaborators and computation, the research will characterize molecular glue spots, elucidate molecular glue-mediated associations and uncover the reason for protein co-localization in cells. The overarching goal of the work is to computationally guide molecular glue design and protein engineering to achieve desired functions. The work has application to cell biology studies and pharmaceutical development, as molecular glues recover lost protein regulation in cells. The project will also contribute to the training of graduate and undergraduate students. A summer workshop will be organized to train students from local community colleges, universities and high schools. Cells may use a molecular glue to form a ternary complex, thereby strengthening protein-protein associations. However, the mechanisms of glue-mediated ternary complex formation and how protein oligomerization enhances the overall function of protein complexes are not well understood. The project combines multi-level simulations and experimental collaboration to investigate the mechanisms of glue-enhanced protein-protein associations and the effects of protein oligomerization on the kinetic enhancement of protein function. The design of molecular glues is informed by the mechanisms of ternary complex formation. The project explores novel ideas and incorporates results from experiments, molecular dynamics (MD), Brownian dynamics (BD) simulations, and deep learning (DL) to understand molecular glues and co-localization effects in molecular binding. The findings promise new insights into molecular glues, glue spots, and protein co-localization that will assist molecular design. 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 · 2024-12

Abstract: Nearly half of the world’s population lives in countries where malaria is endemic. Plasmodium falciparum, the causative agent of the most severe form of human malaria, is responsible for 95% of malaria deaths worldwide. The main goal of this project is to identify the molecular factors that control chromatin organization and gene regulation in P. falciparum with a specific focus on long non-coding RNAs (lncRNAs). We will elucidate the importance of lncRNAs in parasite development, virulence, and sexual differentiation, and determine whether they can be targeted by novel therapeutic intervention. The proposed research builds upon a large body of work generated in the PI’s lab that discovered how 3D genome organization and epigenetic state regulate transcription, parasite development, and sexual differentiation. Despite significant progress in elucidating mechanisms controlling transcription in the human malaria parasite, the exact molecular components underlying changes in epigenetics and chromatin structure remain to be elucidated. The studies proposed here will examine how lncRNAs, together with proteins control epigenetics and chromatin structure, and ultimately parasite development, virulence, survival, and sexual differentiation. The project is organized into two Specific Aims. In Aim 1, we will use two complementary methodologies called ChAR-seq and RADICL-seq to identify patterns of genome-wide RNA and DNA interacting complexes for different classes of transcripts in intact nuclei at different stages of the parasite life cycle. Results from these experiments together with a complementary set of molecular approaches, will not only identify stage-specific RNA-chromatin interaction occupancies but also determine their potential roles in the establishment of chromatin structure and transcriptional regulation. In Aim 2, we will identify the functions at the mechanistic level for candidate lncRNAs that we already identified as potential regulators of antigenic variation and sexual differentiation. For this aim, we have developed a set of molecular, cellular, and genome-wide approaches including the use of complementary CRISPR-Cas technologies, to determine the biological relevance of lncRNAs in the formation and maintenance of epigenetic features and heterochromatin, as well as the sexual development. It is anticipated that the proposed research will offer groundbreaking insights into parasite-specific lncRNAs and their role in controlling parasite biology. Results from this application will most likely lead to novel directions in malaria research and therapy.

NSF Awards · FY 2024 · 2024-12

Quiet owl flight has been an inspiration for quiet airfoils, and owl hearing is a model for how the brain localizes sound. Yet these two well-studied topics have a virtually unexplored evolutionary and ecological nexus: how owls use quiet flight to hunt. This project will address this knowledge gap with three inter-related experiments. Owl attacks on prey will be recorded to ask: do owls employ a ‘stealth mode’, i.e., do owls alter their behavior to minimize sound production? Second, this project will conduct experiments on the quieting features of owl feathers to test how they work. And third, if owls are quiet, virtually nothing is known about the ‘noisy’ flight of regular birds. A phylogenetically diverse array of bird species will be flown through a simple, standardized ‘flight tube’ to measure their sound field in three dimensions during ordinary flight. This project’s intellectual merits include suggesting new directions for both the neurobiology of owl hearing and ‘bioinspiration’ of quiet flight for technical devices such as windmills or drones. Broader impacts include incorporating underserved students as researchers, and outreach about sound with students at the California School for the Deaf. Aim 1 of this project tests two hypotheses of how wing features reduce flight sounds: that they ameliorate aerodynamic (turbulence) sounds, or frictional sounds of feathers rubbing against feathers. These hypotheses will be tested using experimental manipulations of wing features on captive animals. Aim 2 of this project will record the wing kinematics and acoustic signature of hunting owls and other raptors (hawks, falcons) in both captive and wild settings to ask: how do the acoustics of flapping flight vary with kinematics? Quieting features of owl wings may play a particularly important role in reducing sound in hunting kinematics, such as when an owl hovers over prey and the wings are at high angle of attack, near aerodynamic stall. Finally, owl flight has received more attention than sound production mechanisms present in ‘ordinary’ bird flight. Ordinary birds will be flown through a ‘flight tube’ to measure 3D sound production in cruising flight. Data to be recorded and analyzed in phylogenetic context are load (Gutin) sound, frictional sounds, and turbulence sounds. By rigorously documenting the acoustic mechanisms of ordinary flight, including multiple independently evolved instances of quiet flight, this 3rd aim will document the acoustic substrate out of which quiet flight has evolved. 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 · 2024-12

SUMMARY Establishment of proper connections in the developing brain is essential for perception, language, thought, consciousness, learning and memory. Disruption of any of the developmental events that participate in circuit formation can result in a range of neurodevelopmental disorders. Interestingly, signaling by the same guidance cues is used and re-used at different developmental stages to instruct cell migration, neurite guidance, lamination, synapse assembly and pruning. During these developmental events neurons encounter multiple signals at the same time. Does a ligand-receptor pair engage the same downstream signaling effectors regardless of the particular developmental process? How are multiple signaling cues integrated within the cell? To begin to answer these fundamental questions we will study the Cas (Crk associated substrate) family of cytosolic signaling adaptor proteins. Cas proteins are known to signal downstream of both integrins and axon guidance cues, and are differentially phosphorylated by these pathways. This makes the study of Cas protein function a unique opportunity to understand how adhesive and instructive pathways are interpreted and coordinated inside the neuron during embryonic development. Newly developed tools will probe deeply into the functional role for Cas proteins during cortical axon guidance and fasciculation. Given the potential for Cas proteins to act as a nexus where instructive and permissive signaling pathways converge to regulate cell adhesion, these studies will likely increase our understanding of circuit development by: 1) exploring a newly discovered requirement for Cas proteins during cortical development; 2) providing new insight into the poorly understood crosstalk between adhesion to the substrate and guidance cue signaling during axon pathfinding in vivo; 3) contributing to our understanding of how disrupted connectivity impacts cortical processing; 4) providing a platform to assess cortical circuit features underlying normal local and long-range neocortical communication.

NIH Research Projects · FY 2026 · 2024-12

PROJECT SUMMARY The volume-regulated anion channel (VRAC) is an outwardly rectifying anion channel that is activated in response to cell swelling to initiate homeostatic regulation of cell volume. Upon opening, VRAC release Cl- and other anions as well as negatively-charged osmolytes including glutamate into the extracellular space (ECS) to initiate volume regulation in the cell. In brain, astrocytes have been found to regulate the ECS and its contents through dynamic fluctuations in cell volume that correlate with sleep, consciousness, alertness, and levels of synaptic activity. Therefore, VRAC may be especially important in astrocytes for regulation of brain tissue excitability. Evidence suggests that astrocytic VRAC release glutamate in conditions of cell swelling, contributing to ambient glutamate concentrations, stimulation of neuronal glutamate receptors, and excitotoxic cell death in models of stroke. In epilepsy, it has been known for many years that cell swelling is critical for the initiation and recurrence of seizures. Surprisingly, however, the role of VRAC in network excitability, epileptiform activity, epileptogenesis, and seizure generation and severity has never been directly tested. The long-term goal of our research is to identify molecular mechanisms of brain tissue excitability and epilepsy. The objective here is to determine the contribution of astrocytic VRAC to neuronal network excitability, seizure generation and epileptogenesis using astrocyte- specific conditional VRAC knockout (VRAC cKO). Our central hypothesis is that astrocytic VRAC significantly contribute to seizure generation, epileptiform activity, development of epilepsy, and pathology associated with epilepsy including hippocampal sclerosis and neuronal cell loss through swelling-activated release of glutamate. The rationale for the proposed research is that generation of new knowledge on epilepsy mechanisms will lead to development of new therapeutic targets with fewer cognitive side effects. First, we will determine the contribution of astrocytic VRAC in brain tissue swelling and seizure generation in vivo. Second, we will measure the involvement and therapeutic potential of astrocytic VRAC in the development of epilepsy using a combination of VRAC overexpression and rescue strategies in VRAC cKO mice. Third, we will identify mechanisms of VRAC-mediated excitability changes and role in astrocyte volume regulation at the cellular level. At the conclusion of these studies, it is our expectation that we will have generated valuable new knowledge on astrocytic VRAC and its role in hyperexcitability, cell volume regulation, seizure generation and epileptogenesis in situ and in vivo. These results are anticipated to have positive impact by fundamentally advancing understanding of cell volume regulation, mechanisms of glutamate release, and glial-neuronal interactions, while also providing novel targets for the treatment of seizure disorders, excitotoxicity and epilepsy.

NSF Awards · FY 2024 · 2024-10

With support from the Improving Undergraduate STEM Education: Hispanic-Serving Institutions (HSI Program), this Track 2 project aims to improve fundamental analytical skills for STEM students in a large classroom setting with significant enrollment of students from groups historically disenfranchised in STEM. In the data revolution era, increasing representation in the data science workforce from the full spectrum of diverse talent addresses a critical need for remaining globally competitive. Enhancing the learning of fundamental analytical skills such as those taught in introductory statistics courses attends to this need. While project-based curriculum has proven effective, its application in large class settings with significant enrollment of students from groups historically disenfranchised in STEM has not been adequately explored. The project will utilize a theme-based approach to deliver a personalized learning experience. The primary objective is to transform introductory statistics into a subject that is engaging and meaningful for all students but attending to those aspects salient in highly diverse classroom settings. This project aims to enhance students' data literacy, broaden the potential data science workforce, and ultimately address the long-standing diversity gap. This project adopts a constructivist approach with theme-based data sets to foster conceptual understanding, lower the language barrier and reduce the readiness requirement in mathematics, and provide self-paced study materials with real-life examples to personalize learning experience. Centering efforts on the needs and preferences of students from groups historically disenfranchised in STEM, the project focuses on engaging student learning in a large class setting by using exercises with automatic feedback to accommodate students' busy working-learning schedules and cultivating a supportive environment with group study and personalized instructor support. Importantly, this approach establishes an active learning structure that can scale to benefit a diverse student population in classes with large enrollment. After designing and assessing the theme-based approach at the partner institutions, where over 1700 students are taught annually, the project team will disseminate theme-based learning materials across various platforms. Additionally, the project team will conduct online and in-person workshops, maintain a course website and establish a discussion forum to prepare and provide ongoing support for new faculty in implementing the theme-based model. This project is funded by the HSI Program, which aims to enhance undergraduate STEM education, broaden participation in STEM, and build capacity at HSIs. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NSF Awards · FY 2024 · 2024-10

Although crucial for advanced Artificial Intelligence (AI) applications due to their language understanding and generation capabilities, Large Language Models (LLMs) are energy intensive. This project’s goals and novelty are to enhance the efficiency of training and inference associated with LLMs by leveraging emerging high-speed networks and computing architecture. The project’s broader significance and importance are to (1) enable a broad range of LLMs to efficiently operate, advancing AI applications at a low energy cost; (2) strengthen international research collaboration between U.S. and India researchers; and (3) provide educational opportunities for graduate students. This project addresses the energy efficiency challenges of LLMs by optimizing their energy consumption in heterogeneous Compute Express Link (CXL)-enabled hardware environments. By leveraging High-Performance Computing (HPC) middleware and the high-bandwidth, low-latency features of CXL, the project aims to ensure sustainable and efficient AI operations. This project seeks to find solutions to the following set of fundamental issues in training and using LLMs at scale: 1) identifying and characterizing idleness in the LLM workloads; 2) using the knowledge of long idleness to insert low-overhead Dynamic Voltage and Frequency Scaling (DVFS) control and undervolting to save static energy consumption; 3) designing CXL-aware and energy-efficient Message Passing Interface (MPI)-based communication runtime for LLM training and inferencing; and 4) studying the overall impact of the integrated systems on the energy consumption of LLM training and inference. The results are disseminated to collaborating organizations to impact their HPC/AI software applications and hardware chip designs, promoting broader societal advancement through improved technological capabilities. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NSF Awards · FY 2024 · 2024-10

This project will contribute to the national need for well-educated computing professionals by supporting the retention and graduation of high-achieving, low-income students with demonstrated financial need. Over a six-year duration, 55 scholars in four cohorts will receive support for four years, plus an optional fifth year to pursue an M.S. degree. Students from all computing programs at UCR will be considered: computer science, computer engineering, data science, computer science with business applications, and robotics. A key innovation is the creation of the Scholar eXperience Lab ("Scholar XL") through which students will be connected with industry and community partners to work on real and meaningful projects, and participate in skills development workshops, work in collaborative learning spaces, and gain opportunities to pair with faculty on research projects. Specific objectives of the project include: (1) improving social mobility for Scholars by increasing their retention, success and completion rates, and (2) providing individual faculty mentorship and academic coaching that lead students toward internship or research opportunities and post-graduation success. The project will leverage many existing opportunities and support services such as summer internship programs, undergraduate learning assistants, and community outreach programs to create bonding experiences for each cohort. This project is funded by NSF’s Scholarships in Science, Technology, Engineering, and Mathematics program, which seeks to increase the number of low-income academically talented students with demonstrated financial need who earn degrees in STEM fields. It also aims to improve the education of future STEM workers, and to generate knowledge about academic success, retention, transfer, graduation, and academic/career pathways of low-income students. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NSF Awards · FY 2024 · 2024-10

Information and communication technologies generate vast amounts of data that result in an urgent need for increasing the data storage density along with the functional throughput of semiconductor devices. With the support of the Future of Semiconductors (FuSe2) Program, Dr. Alexander Khitun and Professor Jacob Greenstein at the University of California - Riverside together with Professor Caroline Ross at the Massachusetts Institute of Technology will develop a new type of combinatorial memory and logic devices to provide a fundamental advantage over the existing devices in data storage density and data processing throughput. The advantage can be achieved by utilizing phase in addition to amplitude as state variables in devices based on magnetic spin waves. The team will demonstrate prototypes of magnonic combinatorial memory that can store more bits of information than conventional magnetic memory with the same number of magnets. The team will also demonstrate prototypes for special task data processing such as Travelling Salesman Problem. Broader impacts will focus on expanding the participation of a broad range of students in science and technology through activities and programs at both UC Riverside and MIT and by cooperation with community colleges. UCR is an accredited Hispanic Serving Institution and one of the most diverse universities in the USA. This project will also contribute to undergraduate and graduate STEM education. The proposed combinatorial devices are expected to lead to revolutionary advances in a variety of practical applications including magnetic data storage and special task data processing. Magnonic combinatorial devices comprise a magnonic n×n magnonic mesh with an electric part connected in an active ring circuit. The operation of magnonic combinatorial devices is based on the appealing property of the active ring circuit to self-adjust to the resonant path. The number of possible signal propagation paths in the mesh scales factorial (n×n)! with the size of the mesh. The utilization of spin wave superpositions makes it possible to check all the paths at a time. Combinatorial devices can be used for data storage as well as accelerators for non-deterministic polynomial-time (NP) hardness problem solutions. There are working memory and logic prototypes based on ferrite films grown on garnet substrates. To make these devices compatible with conventional technology, the team will demonstrate combinatorial memory and logic devices on a silicon platform. The results of this transformative research will add to the core knowledge in the areas of material science, signal processing, and computer engineering. The proposed magnonic combinatorial devices are expected to lead to revolutionary advances in a variety of practical applications. The development of compact memory devices capable of storing all information generated by humankind in 1-inch × 1-inch matrix together with a functional throughout enhancement above 10^30 Ops/(m^2∙s∙μJ) (i.e., the throughput of all existing supercomputers combined) will have an enormous impact on the semiconductor industry as well as on the various fields of our life. Broader impacts will focus on expanding the participation of a broad range of students in science and technology through activities and programs at both UC Riverside and MIT and by cooperation with community colleges. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NSF Awards · FY 2024 · 2024-10

The academy currently produces far more PhD graduates than can find jobs as professors. Additionally, few PhD advisors have been trained to provide mentorship for career paths that lead to destinations other than academic scholarship. This dual problem highlights the need for graduate student training programs that, as they leverage students’ research skills and technical knowledge, also prepare trainees for career paths beyond the university. One such path leads towards the policy world, a professional milieu in which there is strong demand for early-career science professionals. Additionally, given the ways that policy so often sits at a convergence of scientific issues and key regional or national challenges, many STEM graduate students have a strong interest in policy work. Currently, however, there are few avenues for students to acquire the training that would prepare them for those careers. This National Science Foundation Innovations in Graduate Education (IGE) award to the University of California, Riverside (UCR) will: (1) pilot a new version of UCR’s Science to Policy (S2P) certificate course that will incorporate a set of UCR-designed, science-policy learning modules; and (2) host a series of annual SPOKES Summits whose delegates will be policy professionals. These subject matter experts (SMEs) will collaborate with the SPOKES leadership to assess and refine the science-policy competencies that ground the certificate course’s training system. These summits will culminate in the publication of the SPOKES Framework, which will establish a national standard for science-to-policy education. Thus, in addition to enabling S2P to improve the training it offers to UCR students, the project will also facilitate the SPOKES system’s dissemination to other institutions. The SPOKES Project’s pilot course will be offered annually and will train PhD students from across UCR’s STEM fields. Each cohort will be trained in a set of science-policy competencies applicable to a variety of career paths (whether in policy, industry, or scholarly research). The SPOKES Competencies include knowledge of legislative processes, policy-directed research strategies, and science communication skills that cover a range of policy-relevant genres. Those competencies will provide a framework for the development of the SPOKES learning modules, which will be incorporated into each year’s certificate course as they are developed. In parallel with these efforts, the SPOKES Project will: (1) assess the learning modules by engaging policy professionals as summit SMEs who will provide feedback on those modules’ effectiveness and relevance; (2) conduct qualitative portfolio assessments by soliciting the SMEs’ feedback on students’ written and oral work, (3) collaborate with SMEs to refine S2P’s science-policy competencies, and (4) publish those competencies, along with S2P’s training methods, as the SPOKES Framework. Through their assessments of learning modules and portfolios, the SMEs will provide the feedback that will enable the SPOKES Project to refine all aspects of its training system. The SPOKES Framework will enable science-policy programs to arm their trainees with a powerful set of tools for engaging with and addressing some of our Nation’s most pressing challenges. The Innovations in Graduate Education (IGE) program is focused on research in graduate education. The goals of IGE are to pilot, test and validate innovative approaches to graduate education and to generate the knowledge required to move these approaches into the broader community. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NSF Awards · FY 2024 · 2024-10

Heterogeneous hardware architectures (including graphics processing units, field programmable gate arrays, and application-specific integrated circuits) are shaping the future of computing and artificial intelligence (AI) acceleration. However, the use of such extraordinary computing power from heterogeneity is restricted to a limited pool of software developers with deep microprocessor expertise. Although high-level synthesis (HLS) compilers have been developed to convert computation logic written in high-level programming languages to low-level register transfer level based kernels, this process requires significant code rewriting to meet synthesizability and performance requirements. To improve developer productivity in this emerging domain, this project develops new automated code transpilation, testing, and debugging technologies to lower the barriers of developing heterogeneous applications, thereby making emerging hardware accessible to software engineers with different levels of hardware expertise. This project will also train the technology workforce with interdisciplinary computing backgrounds in software engineering, hardware design, heterogeneous architecture, and compilers. Specifically, this research has three innovative components. First, it will design efficient program transformation and interactive design exploration methods for porting classical software that targets central processing units (CPUs) to its heterogeneous version with behavior preservation and optimized performance. Second, it will design new automated testing methods for heterogeneous applications that obtain increased visibility with new hardware-level probes and adapt existing tests to various platforms. Third, it will design automated debugging methods for source code tracing and pinpointing the root causes of failures throughout a multi-phased hardware compilation process. In summary, this project will produce a suite of advanced open-source debugging and testing tools as a key enabler for harnessing the potential of hardware heterogeneity. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NSF Awards · FY 2024 · 2024-10

The radio access network (RAN) is an important subsystem of 5G networks and beyond – providing universal coverage and ubiquitous Internet access to billions of mobile users. Open radio access network (O-RAN) promotes an open system approach, where components and products from different vendors can interoperate with each other, thus accelerating technology innovations. This thus calls for proper testing which has not received its due attention from the research community. This project seeks to identify and address this new research topic of mobile network diagnostic testing, particularly for the O-RAN subsystem. New diagnostic testing methods are developed to not only determine whether the tests pass or fail, but also diagnose the root causes to learn why. These new designs and their gained insights lead to improvements in operation correctness, interoperability, performance and security of the upcoming RAN infrastructure and jumpstart the growth of O-RAN and future mobile technology ecosystem. The project also seeks to influence the standardization of new 5G releases and 5G beyond technologies. It recruits fresh talents and train a new generation of students and engineers for future mobile Internet design. This project explores a systematic approach to mobile network diagnostic testing, spanning from fresh-view modeling and abstraction, efficient algorithms, to novel instruments for tracing and diagnosis, to address all limitations of RAN testing. The research tasks enhance RAN diagnostic testing in three aspects: (1) near-complete test coverage by exploiting dependency among multiple procedures and multiple interfaces of RAN software to generate missing test cases and pinpoint their root causes, (2) non-intrusive, end-to-end tests to assess full-stack performance and potential threats of applications on commodity 5G devices, and (3) test efficiency to optimize test runs and reuse prior test results by identifying repetitive operations and assessing the updates over evolving RAN technology releases. The proposed testing designs are integrated to an open-source toolkit and evaluated in the lab testbed and real-world O-RAN systems with industry collaborators to facilitate technology transfer. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NSF Awards · FY 2024 · 2024-10

This Smart and Connected Health (SCH) award will fund research that focuses on creating a robotic system for diagnosis of abnormal tissues inside the abdominal cavity. Diseased abdominal organs often present a complex mixture of normal, abnormal but non-cancerous, and cancerous tissues. Existing medical imaging methods fail to offer useful diagnosis due to errors caused by breathing and the limits of imaging resolution and sensitivity. Diagnostic laparoscopy along with tissue biopsies can provide more detailed information to guide treatment but are limited due to subjective errors in visual inspection and errors from sampling a small amount of tissue. To solve these problems, this research project will develop a smart robotic system with multiple sensors and artificial intelligence. The robot will move through the abdominal cavity, analyze the size, shape, and chemical information of tissues, and identify abnormal tissues. The research will also include educational and outreach activities to promote STEM fields, especially among groups that are traditionally underrepresented in these areas. The goal of the research is to design, develop, and evaluate a multimodal robotic system equipped with flexible endoscopy, ultrasound imaging, and Raman spectroscopy for comprehensive cancer diagnosis in the abdominal cavity. The project is built upon three research thrusts: 1) developing a multimodal instrument for multiscale tissue diagnosis, 2) developing a mesoscale continuum robot for tissue surface scanning, and 3) developing multimodal fusion for comprehensive diagnosis. The first thrust integrates a balloon-based ultrasonic probe with a Raman spectroscopy needle to detect, classify, and stage tissue on the surface and deep inside organs. The second thrust integrates the sensing modalities with a tendon-driven continuum robot and equips the robot with the ability to scan tissue surface through data-driven modeling and model predictive control. The third thrust combines data from multiple sources to perform tissue identification and staging and builds robust models to handle missing/occluded data and improve overall accuracy. The robotic system and its individual components will be calibrated and demonstrated by performing navigation tasks and collecting data using gelatin, tissue, and abdomen phantoms. The robotic system may not only provide comprehensive diagnosis of heterogeneous and unstructured tissue environments but also improve the safety and accuracy of surgery through intra-operative diagnosis. This project will generate new knowledge and methods in biomechanics and mechanobiology by revealing multiscale tissue information and potentially identifying new biomarkers critical to cancer treatment. 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

The female genital tract (FGT) is colonized by millions of microbial taxa that have far reaching effects on reproductive health. Resident bacteria in the FGT affect mucosal immune responses, alter the risk of STI acquisition, and predict maternal health and birth outcomes, with lactobacilli typically associated with reduced overall bacterial diversity, inflammation, and risk of STI acquisition. Conversely, communities with little representation of Lactobacillus and an increased abundance of diverse anaerobes are characterized as Bacterial Vaginonsis (BV) and are associated with elevated levels of inflammatory cytokines, heightened risk of STI acquisition and adverse birth outcomes, vaginal discharge, and other sequelae. However, the mechanisms underlying transitions to BV and its high recurrence rates after antibiotic treatment (~50%) remain unknown. The vaginal virome remains largely uncharacterized outside of a few families of DNA viruses associated with adverse conditions (Herpesviridae, Papillomaviridae), with the RNA virome even less studied. Bacteriophages, including integrated prophages, are powerful mediators of bacterial community structure and dynamics across environments, though we know little of bacterial-phage interactions in the the FGT. This study proposes that the vaginal virome is one of the factors influencing transitions to BV, either by eliciting mucosal immune responses directly, or via bacterial-phage dynamics, including prophage induction via abiotic stressors. This proposal will utilize samples already collected from the Evidence for Contraceptive Options and HIV Outcomes (ECHO) Trial to longitudinally characterize (via shotgun metagenomics) interactions between viral and bacterial taxa in participants who do not experience BV (20), participants who experience and clear incident BV (20), and participants who experience persistent BV (20) (Aim 1). We will use strain-resolved analyses to identify alterations in prophage abundance, as well as non-integrated viruses, and we will integrate these data with measurements of 27 cytokines measured previously. In Aim 2, we will characterize the vaginal viral and bacterial metagenomes in our full cohort of participants that seroconverted (28) during our substudy and compare those with the same number of matched controls, identifying alterations in the abundance and functionality of bacterial and viral taxa between groups. In Aim 3, we will follow up the results from our previous work demonstrating that a copper intrauterine device (Cu-IUD) shifted vaginal bacteria toward BV states. We will sequence the bacterial and viral metagenomes across the full subset of women randomized to the Cu-IUD (60) prior to initiation and after six months of use to identify if Cu2+ released from the IUD induced prophages into lytic replication using strain resolved analyses similar to Aim 1, with special attention to lactobacilli prophages. We will assess the results from our metagenomic analyses in vitro via culture experiments using Cu2+ for prophage induction. Together, these aims will provide a characterization of the vaginal virome and its contributions to BV and associated sequelae, including HIV acquisition.

NIH Research Projects · FY 2025 · 2024-09

PROJECT SUMMARY RNA-binding proteins (RBPs), including enzymes that act on RNA, impact all aspects of cellular function. However, the roles, molecular mechanisms and integration with the cellular regulatory networks are still unknown for most RBPs. The goal of this study is to elucidate the function, molecular mechanism, and regulation of a novel endoribonuclease, EndoU. Uniquely, the RNase activity of EndoU in vitro and in cell culture is directly activated by Ca2+ ions, suggesting a role in the cellular responses to this key second messenger. Importantly, EndoU misregulation is associated with uterine, cervical, skin, bronchial, and lung squamous cell cancers. It is heavily downregulated in esophageal, oral squamous, and cervical cancer, and is a strong prognostic marker in head/neck and colorectal cancers. EndoU is cytoplasmically expressed in distinct cell types sharing a major, driving role of programmed cell death in their development: thymocytes, B cells, squamous epithelial cells, and placental syncytiotrophoblasts. We hypothesize that EndoU controls survival/differentiation decisions during thymocyte development by cleaving target RNAs in response to changes in intracellular calcium levels. We specifically aim to fill the knowledge gap in understanding EndoU’s cellular role, RNA targeting repertoire, and the mechanism of EndoU activity and its Ca2+-dependent conformational control.

NSF Awards · FY 2024 · 2024-09

Complex fluids are ubiquitous in daily life. Examples include shampoo, biological fluids like blood, ionic solutions in batteries, and liquid crystals used for display devices. These are fluids with microscopic structures, such as the orientational order of rod-like molecules, the elasticity of deformable particles, and interactions between charged ions. Due to the coupling and competition among various thermo-chemo-mechanical mechanisms on different spatial-temporal scales, complex fluids exhibit a variety of interesting phenomena and properties not encountered in simple fluids or gases. Mathematical models and computer simulations are two indispensable tools in studying complex fluids. Variational principles, such as the energetic variational approaches (EnVarA), provide unified and thermodynamically consistent frameworks to model various complex fluids through their energy and dissipation. In this project we will address the computational challenges for variational models for various complex fluids by developing new computational tools. The project will provide education and training to graduate and undergraduate students, along with postdoctoral associates, including those from underrepresented groups, in the fields of physical and biological modeling, scientific computing, and numerical analysis. Students will participate in the proposed numerical and experimental activities, and acquire a wide range of knowledge and skills from close interaction within the interdisciplinary team involved in the project. The goal of this proposal is to develop structure-preserving, high-order, efficient numerical methods for various complex fluid models, particularly those involving thermo-chemo-mechanical coupling. Rather than relying on partial differential equations, this approach builds numerical discretizations directly from the continuous energetic variational formulations, which describe all physics and assumptions in the system. The "discretize-then-variation" approach ensures that the variational structure, as well as the kinematics of thermodynamic variables, are preserved at the semi-discrete level. Different spatial discretizations, such as Eulerian and Lagrangian approaches, will be utilized based on the continuous variational formulation. The investigators will focus on three major research tasks, targeting different prototype models with increased complexity: (1) Developing high-order variational Lagrangian schemes for generalized diffusions; (2) Developing variational operator splitting schemes for reaction-diffusion models by incorporating Eulerian schemes for chemical reactions with Lagrangian schemes for diffusions; (3) Developing entropy-stable schemes for non-isothermal reactive flows, which will address the challenges in preserving thermodynamic consistency and entropy stability in non-isothermal models. Comprehensive numerical analysis and extensive computational studies of the numerical schemes will be conducted for each research task. 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 ABSTRACT Infants born to HIV-infected mothers are at high risk for HIV acquisition. Additionally, HIV-exposed yet uninfected infants display reduced vaccine responses and increased disease susceptibility compared to unexposed infants. The development of certain T cell subsets, both in the mucosa and systemically, is determined by the presence of specific microbes in the gut and may be important in determining adaptive immunity. However, the gut microbiota of HIV-exposed uninfected (iHEU) infants differs from that of HIV- unexposed (iHU) infants, since their mothers have altered gut microbiota. The gut virome also plays a central role in modulating both the bacterial microbiota and immune response of adults, yet the association between the infant enteric virome and cellular responses to vaccination has not yet been explored. This study proposes that the enteric virome is one of the factors influencing the morbidity of HIV-exposed infants, either by directly altering mucosal immunity or by altering the composition of enteric bacterial communities, as a consequence of bacteriophage or other viral dynamics. This proposal will utilize an already funded, ongoing cohort to longitudinally identify interactions between viruses, bacterial microbiota, and cellular responses to vaccination in 40 iHEU and 40 iHU (Aim 1). Viral metagenome data will be integrated with bacterial community datasets and T cell cytokine responses to BCG vaccination to identify viral and bacterial taxa correlated with BCG responses. The effect of the expanded virome on bacterial microbiota and responses to BCG vaccination will then be assessed for causality in gnotobiotic mouse models (Aim 2). The effect of the expanded iHEU viroem on mucosa and peripheral gene expression will be assayed using single cell RNA sequencing in Aim 3. Integrative analyses will be used to identify interactions between specific bacterial and viral taxa, as well as their associated with BCG responses. Together, these Aims will identify mechanisms of gut dysbiosis in iHEU and reveal potential therapeutics to restore health to this group. Collectively, this proposal will reveal how maternal HIV infection shapes the enteric microbiome and immunity of associated infants.

NIH Research Projects · FY 2025 · 2024-09

Abstract Recent advances in neuroimaging technology have significantly contributed to a better understanding of brain organization, and the development and application of more efficient clinical programs. However, inherent limitations to the existing techniques make large-scale imaging of neural activity with high spatiotemporal resolution and specificity in young populations challenging (1). Functional magnetic resonance imaging (fMRI) is predominantly performed on sleeping infants to minimize motion-related artifacts and avoid exposure to certain stimuli in the novel scanner environment (e.g., loud noise). Techniques that can be used in awake infants, such as electroencephalography (EEG), magnetoencephalography (MEG) and functional near-infrared spectroscopy (fNIRS) are more suited to study cognitive (non-motor) developmental mechanisms. A recent review study from our team revealed high level of exclusion rates associated with technical limitations in pediatric neuroimaging explaining the limited neuroimaging motor-related studies in infants (less than 5%). Functional ultrasound imaging (fUSI) is a novel technology that provides a unique combination of spatial coverage (depth up to 8 cm), unprecedented spatiotemporal resolution (100 μm, up to 10 ms) and compatibility with freely moving subjects (2). While most fUSI studies have been conducted in rodents (2-5), one of the most exciting aspects of this technology is its ability to scale to larger organisms, including monkeys (6, 7), adult humans (8), and sleeping infants (9, 10). Although fUSI typically requires thinned skull surgery or trepanation to enable the penetration of the ultrasound waves, in infants, fUSI images can be acquired non-invasively through the fontanels. The first proof-of-concept application of fUSI in neonates opened a new avenue for studying the brain in infancy (9, 10). However, this study was performed on sleeping infants, limiting the type of behavioral paradigms that can be used to explore neural correlates of motor development. Here, we take the next major leap in functional neuroimaging by extending fUSI technology to study the brain in infancy during motor control performance. Aim 1 will assess the functional organization of the motor system in infants performing a reaching task. Typically developing infants will reach to targets, while brain activity will be recorded using fUSI and biomechanical and behavioral data will be collected. Our hypothesis is that fUSI will successfully detect increased motor-related brain activity during reaching. Aim 2 will develop tools to decode motor activity in the infant brain using fUSI. We will attempt to decode the direction of reaching movements from the fUSI activity – an essential component for building non-invasive brain-machine interface (BMI) systems for very young populations with motor impairments in the future. If successful, this project will provide neuroscience with high resolution imaging technology for monitoring brain activity in awake and behaving infants, while setting the foundation for the development of non-invasive ultrasonic BMI systems for infant motor rehabilitation.

NSF Awards · FY 2024 · 2024-09

Modern Earth is covered by lush tropical forests, extensive grasslands, and soaring redwoods—in striking contrast to landscapes through much of Earth’s early history that consisted largely of bare rock and microbial mats. Plants have dramatically altered Earth’s landscape and climate (like the shapes of rivers and patterns of rainfall). However, there is currently little consensus on how the development of plants, starting with the first ground-hugging mosses and liverworts around 470 million years ago, followed by the eventual rise of trees around 380 million years ago, affected nutrient and oxygen levels both on land and in the oceans. This research combines field, laboratory, and modeling approaches to examine the effects of early land plants on the Earth system. This study focuses on the Canadian Arctic Archipelago which contains some of the best-preserved sedimentary rocks chronicling this key time period of early plant evolution. The team of researchers are studying fossil plants, pollen, and spores and geochemical elements to understand how weathering changed on land, how plant material was delivered to the ocean, how the availability of critical nutrients like phosphorus changed on the land and in the oceans, and how oxygen and sulfur levels changed in the ocean. The broader impacts activities stemming from the research include educational and mentorship opportunities for students in middle-school through graduate school. Graduate students will be co-mentored by the Principal Investigators, and undergraduates will also be recruited to analyze collected samples. The Yale Peabody Museum and the Yale Pathways to Science program will provide platforms for community-oriented outreach efforts, including educational events fostering scientific literacy and engagement in local middle-school students. The team will also take advantage of the unique opportunity provided by recent Peabody renovations to develop a new public-facing exhibit on “Ecosystem Engineering” focused on land plants and their impacts on Earth’s landscapes and ecosystems. The University of California, Riverside’s Camp Highlander program is fostering local high-school student engagement with Earth sciences. Finally, field-conducted telepresence outreach through the new “Annals of the Arctic” program, integrated with existing summer programs at Stanford, Yale, and UCR, will provide public-facing exposure to day-by-day realities of geologic fieldwork in remote terrains. This will increase the accessibility of geologic research and provide a venue for direct illustration of geologic concepts, human experiences of the dynamic nature of polar ecosystems, and their vulnerability to ongoing environmental change. Reconstructing the biotic, biogeochemical and climatic impacts of the evolution of land plants has been hampered by the commonly fragmentary and disassociated records of geochemical and paleontological change across the lower-middle Paleozoic transition, and by the limited integration of empirical observations with the mechanistic framework that can be provided by biogeochemical and Earth-system models. To address these fundamental questions, we are generating new, high-resolution field-based geochemical data (biomarker, programmed pyrolysis, carbon isotope, lithium isotope, osmium isotope, phosphorus speciation and phosphate-oxygen isotope, iron speciation, and trace metal abundances) and sedimentological and paleontological (plant body fossils, palynomorphs, graptolite and conodont biostratigraphy) records from key sections in the Canadian Arctic to reconstruct first-order ecological and environmental changes—in both continental and marine settings—concurrent with the radiation of early land plants. The Silurian–Devonian transition is an under-characterized but key interval for both land plant evolution and marine redox state, and these data will be integrated with long-term records to distinguish perturbations from more permanent state shifts. These new empirical records will be coupled to biogeochemical modeling over a range of scales—from local critical zone and seafloor diagenetic processes to continental climate and ocean and atmospheric carbon-oxygen cycle modeling—to develop a more robust process-based understanding of plant-biogeochemical feedbacks and reconstruct the long-term consequences of early land plant evolution for the broader Earth system. 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

Brown bears (Ursus arctos) have undergone rapid population declines over the last 150 years in the lower 48 states. This project will use DNA sequencing technologies to investigate the effects of this rapid population decline as well as the effects of previous conservation management actions. The researchers will investigate the utility of these genetic technologies for population monitoring and management. New genetic tools will be developed to rapidly sequence and identify individual brown bears in the lower 48 states using non-invasive samples. Samples from both historical (museum) and contemporary populations will be used to better understand the impact of population decline and conservation management efforts on the health of brown bear populations. The project will yield new insights into how small populations of animals can persist and will include a database with applications for general population monitoring and human-wildlife conflict scenarios. This project will also establish a brown bear genetic database and provide training opportunities in genetic and genomic technologies to conservation managers. Genomics is poised to be a potentially useful and cost-effective tool for population monitoring and management, however, the limitations of population genetic estimates for conservation purposes are not well understood. This project will use an extensive set of historic and modern brown bear (Ursus arctos) samples to characterize genomic diversity over the last 200 years, how it has changed over time and whether management decisions (e.g., translocations) have impacted the genomic landscape of the species. Brown bears in the lower 48 have been extensively monitored since approximately 1975. The life history data collected by conservation partners over the past several decades, paired with newly collected genomic data, will be used to analyze the impact of past translocations and population bottlenecks in the lower 48. Relating population genetic statistics to life history traits, such as fecundity, lifespan, and independent population size estimates, will help to better implement recommendations to maintain genetic health for species of conservation concern. This project is jointly funded by the Division of Environmental Biology and Integrative Organismal Systems through the Partnership to Advance Conservation Science and Practice 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 · 2024-09

This is a collaborative project between the University of California-Riverside and University of Notre Dame. A critical challenge in biology is to understand the emergent multicellular features of organ development involving both intracellular processes and cell-cell interactions. This project will focus on investigating a critical late-stage phase of fruit fly wing disc development, called eversion, which undergoes a significant shape change and serves as a model of epithelial remodeling. These same mechanisms are also involved in the development, wound healing and cancer progression. Subsequent morphogenetic processes fully define the adult wing, hinge, and notum to generate the final adult organ structures. Individual cell shape changes lead to extensive tissue deformations during eversion. The proposed study combining modeling and experimentation will provide mechanistic insights into how hormonal signaling, morphogen-driven pattern formation, and cytoskeletal regulators synergistically impact epithelial organ architecture. The newly developed multiscale mathematical and computational modeling and machine learning approaches enable predictive design-based approaches for regenerative medicine and stem cell engineering. University of California-Riverside (UCR) is a Hispanic-serving institution located in one of the most ethnically diverse areas of the country. Many students are the first in their families to attend college. To increase the diversity of students pursuing graduate education in mathematical biology, applied mathematics and bioengineering, the PIs will partner with UCR’s Mentoring Summer Research Internship Program and UCR’s GradEdge/Jumpstart Programs for undergraduate and graduate students from underrepresented groups. Additionally, the PIs at Notre Dame will offer summer research internships to undergraduate students with focused recruitment from underrepresented groups and facilitate cross-disciplinary mentorship of trainees on both campuses. A central, unsolved problem in biology is elucidating the collective molecular mechanisms regulating cell shapes and how these determine the emergent systems-level generating organ shape formation (morphogenesis). The robust morphogenesis of multilayered tissues requires the coordination of a repertoire of cellular processes akin to “unit operations,” including: cellular mass regulation (cell growth, proliferation, and death), cell-environment regulation (cell-cell and cell-substrate adhesion), and cell mechanical regulation (the membrane and cytoskeletal elasticity, cytoskeleton-centered tension, cytosolic pressure). Combining these cellular processes creates the final tissue-scale architecture through a sophisticated communication network. Many congenital disabilities and degenerative diseases result from dysregulation of these unit operations. Thus, it is critical to decipher the complex mechanisms that integrate biochemical and mechanical signals to define emergent organ shape. This project utilizes the fruit fly wing imaginal disc to elucidate the critical signaling pathways and conserved biophysical mechanisms that are functionally significant for organ development and epithelial cell function. This project will develop new multiscale mathematical and computational modeling approaches on 3D deforming domains to simulate multicellular wing disc morphogenesis. Key innovations will include simulation acceleration via neural networks. The new models will be calibrated using experimental data incorporating genetic perturbations and immunohistochemistry and machine learning methods to elucidate the mechanisms integrating mechanical and biochemical regulatory networks during organogenesis. Data-driven and machine learning-enabled pipeline will systematize the calibration of candidate models and enable optimization of the experimental design for validating model predictions and testing mechanisms of morphogenesis. 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.