University Of California Santa Cruz

NSF Awards · FY 2025 · 2025-09

Approximately 85% of the matter in the universe is thought to be dark matter. The presence of this mysterious component is well documented in large galaxies, but the amounts of dark matter in galaxies much smaller than the Milky Way are poorly understood. With a new dataset of 100,000 dwarf galaxies, this program will measure their composition and proportion of dark matter, stars, and gas. The principal investigators will also use advanced computer models and simulations to explain the most important physical properties of these dwarf galaxies. This program will develop summer research internships, seminars, and mentoring schemes to increase the retention rates of undergraduate students majoring in physics and astronomy in the States of California, New Jersey, and Ohio. This program will also support research and training opportunities for undergraduate and graduate students in astrophysics. This program will characterize the baryon and dark matter content of massive dwarf galaxies with a united and novel theory and observational approach. This program is made possible by the Merian survey, which is identifying 100,000 well-characterized massive dwarf galaxies. This program will match the internal kinematics of galaxies with their halo mass, using HI line shapes and weak-lensing masses. The principal investigators will use simulations, which successfully reproduce the HI properties of dwarf galaxies, to determine if Cold Dark Matter (CDM) or self-interacting dark matter (SIDM) is a better match to the kinematics and halo properties of massive dwarfs. Using the DESI Y1 data set, the PIs will study how environmental effects impact dwarf properties and study to what degree this impacts weak lensing measurements. 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 · 2025-09

This Pathways to Enable Open-Source Ecosystems (POSE) project helps a wide range of computer users develop and test the next generation of distributed applications in realistic settings. As the world becomes increasingly connected and digital technologies expand across various industries, commerce, research, education, and everyday life, it becomes ever more challenging to design computer systems that perform well under real-world conditions. This project, the Network Simulation Bridge (NSB), provides developers, practitioners, students, and researchers with a means to seamlessly connect distributed applications and services running on actual devices or in simulated environments to network simulation platforms. This collaboration will enable better understanding and insight into how these applications are impacted by the communications networks they depend on. To keep pace with evolving technology, the project will expand NSB’s current user base and establish an open-source ecosystem (OSE) that supports long-term use and ongoing improvement. By supporting a wide range of users and application domains, NSB can help shape more reliable and adaptable technologies in ways that benefit society broadly. This POSE project develops an open-source ecosystem (OSE) around the Network Simulation Bridge (NSB) - a co-simulation framework that enables application developers, researchers, academics, and students to connect their distributed applications to network simulation backends. The NSB-OSE will allow for better modeling and observation of the interplay between the underlying communication network and target applications and systems. Compared to hardware testbeds, network simulation platforms offer important advantages, including the ability to run reproducible experiments under a wide range of scenarios. In addition, the network simulation platforms are often used for initial experimental steps, since they are more widely accessible, easier to deploy and scale, and offer superior experimental diversity and reproducibility. NSB-OSE will contribute to the domain of networked application development by providing a framework for seamlessly bridging applications to network simulators. This bridge can facilitate testing, validating, and evaluating distributed applications under closer-to-real-world scenarios. Some advantages offered by NSB are its lightweight, portable, and distributed implementation that is agnostic of the users’ applications, and its simple and extensible design that makes it easy to add new co-simulation features. This project creates a pathway for an NSB-OSE to: 1) identify and grow user and contributor communities; 2) develop an OSE infrastructure based on guidance from experts; and 3) provide a productive space within NSB for continued contributions from its communities. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NIH Research Projects · FY 2025 · 2025-09

PROJECT SUMMARY / ABSTRACT There has been an explosion of genomics data in neuroscience that bridges insights from single-cell genomic data to brain function and diseases. Data on hundreds of millions of cells are being generated by consortia such as BICAN/BICCN, PyschENCODE, SEA-AD, SCORCH, and SSPsyGene. As many different cell taxonomies are being generated, the neuroscience field needs a single-cell brain resource for researchers to explore and use as a reference model for their datasets. A huge semi-manual effort would be not only nearly impossible given the data size, but also would quickly become obsolete. Only automated efforts will be able to address the need for a durable, flexible, and nimble neuroscience cell reference. We propose to use cutting-edge AI techniques to build a Universal Cell Embedding for Brain (UCE-Brain), a foundational brain cell taxonomy model across hundreds of millions of cells. We will develop the UCSC Human Brain Single-cell Genomics Explorer to enable users to access and interactively explore the UCE-Brain, the reference cell taxonomy, as well as map new data into the reference. The Data Explorer will be capable of interactive data visualization of the hundreds of millions of cells in a 2D embedding space; the Cell Curator will explore the BICAN taxonomy annotations as well as gathering community-driven cell types; the Cell Mapper will offer two methods to map new data to the reference models and visualize the results; and Tools and Documentation. We will incorporate a Large Language Model (LLM) into the Cell Curator and Cell Mapper to parse users’ requests, provide a natural language summary of the results in a chatbot-style interaction, and integrate user feedback. Our team’s diverse expertise and strong history of successful collaboration will ensure the success of the project. Aim 1. Construct foundation models for human brain cells We will develop UCE-Brain, a brain-specific foundation model that will create high quality universal representations of brain single cell data. We will build UCE-Brain clusters that are most consistent with BICAN taxonomy in gold-standard publications, while still allowing the clusters to evolve in response to new datasets. Aim 2. Mapping new data into the reference cell type taxonomy. We will offer two methods for users to map and annotate their data. One method will allow users to upload their data to a server to map to UCE-Brain. A second method will allow users with sensitive data to map to a stripped-down model on their laptops. Aim 3. Develop the Cell Curator to promote community annotation of the reference cell type taxonomy. The Cell Curator tool will enable users to inspect and curate the reference cell clusters. We will conduct efforts to foster the neuroscience research community’s contributions. Aim 4. Develop the UCSC Brain Explorer website and harmonize single-cell sequencing data. The UCSC Brain Explorer website serves as the gateway to all functionality and resources developed in this application. Data harmonization will occur on Terra, where we will process datasets using the BICAN/BICCN pipelines. We will integrate Google Analytics to track aggregated user interactions.

NSF Awards · FY 2025 · 2025-09

With the ever-widening use of software in safety-critical applications such as autonomous vehicles, design defects are becoming increasingly catastrophic in their consequences. Formal, mathematical techniques to prove the correctness of software provide a promising approach to ensure the safety of such systems. However, formal verification of complex systems often requires an impractical level of human effort: automated theorem provers (ATPs) typically do not scale to real-world applications, forcing correctness proofs to be written largely by hand in interactive theorem provers (ITPs). A similar challenge has arisen in mathematics, where there is growing use of ITPs to formalize (and sometimes find mistakes in) proofs: the lack of scalable automation puts formalization beyond the reach of most working mathematicians. This project aims to address these challenges by developing new techniques allowing ATPs to scale to complex theorems, as well as tools usable by mathematicians for proof formalization. Enhancing the scalability and usability of ATPs will reduce the barrier to entry for safety-critical system designers and mathematicians to verify their systems and proofs, helping to make these safer and more trustworthy. The project has three primary research thrusts. The first two thrusts tackle several obstacles to using Large Language Models (LLMs) to automate proof construction, turning an ITP into an ATP: data scarcity, sparse rewards, and lack of self-play. Thrust 1 will address the data scarcity problem by generating synthetic theorems and proofs: the project will develop LLM-based techniques to generate human-like theorem statements and proofs, as well as techniques for translating between formal theorems/proofs and informal, more easily-interpretable versions. Thrust 2 will address the self-play and sparse reward problems by exploiting high-level structure in proof search: the project will develop techniques to synthesize lemmas providing easier-to-prove intermediate steps on the way to a desired theorem, as well as techniques to guide proof search using human feedback. Finally, the last thrust seeks to ensure that the project's advancements in ATPs transfer to advances in mathematics, and that the developed tools will be useful for working mathematicians. Towards this end, Thrust 3 will apply the project's tools to study important conjectures in the theory of linear groups. 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 · 2025-09

PROJECT SUMMARY Loss of mucosal tolerance is a major hallmark of digestive diseases, including inflammatory bowel disease and celiac disease. Mucosal tolerance to dietary antigens develops during early childhood, a time period that coincides with frequent enteric infections caused by viruses. One highly prevalent cause of viral diarrhea is astrovirus, which infects the vast majority of children by the age of ten. Although there is recent precedent for enteric viruses triggering a loss of tolerance to dietary antigens, we lack a complete understanding of the underlying molecular mechanisms. There are currently two main models for how enteric viruses trigger a break in tolerance– the first is through viral molecular mimicry of a dietary antigen and the second involves bystander activation of immune cells, both of which lead to inappropriate inflammation that can disrupt tolerogenic responses. In this proposal we aim to evaluate a third model that centers around the role of goblet cell-associated antigen passages (GAPs), which have been shown to be the primary pathway for establishing tolerance in the gut. Using the murine model for astrovirus, this proposal will examine how this goblet cell-tropic virus impacts the ability of GAPs to mediate tolerance to the dietary antigen, ovalbumin. In Aim 1, we will use T cell conversion assays and robust measurements to determine whether astrovirus infection leads to a loss of tolerance. We will also pioneer the use of spatial transcriptomics to determine how astrovirus infection alters the cross-talk between infected GAP-forming goblet cells and antigen presenting cells in the lamina propria. In Aim 2, we will test whether GAPs are co-opted by astrovirus to establish infection or aid immune evasion. Completion of these proposed aims will provide the first mechanistic insights to the role of GAPs during enteric virus infection and the consequences of infection on the ability of goblet cells to mediate tolerance. Together these studies will define an entirely new facet of astrovirus pathogenesis and initiate new lines of investigation into how enteric viruses contribute to the risk of digestive disease.

NSF Awards · FY 2025 · 2025-09

The Paleobiology Database (PBDB) is one of the most impactful and widely used digital representations of the fossil record, capturing our best understanding of the age, location, identity, and geological context of fossils. Data held in the PBDB have been used in over 2,000 scientific publications and in a wide range of educational and public outreach materials. The PBDB is an essential resource for geoscientists, biologists, students, educators, and the public. Although the research and educational impact of the PBDB is tremendous, there are key issues with its current computer infrastructure, which was designed in the late 1990s and early 2000s. This project will combine PBDB with the Integrative Paleobotany Portal (PBot) to create a more modern and flexible digital system: the PBDB 2.0. Planned project activities will transform the PBDB to be more useful to a broad community of researchers, educators, and students in the Earth and life sciences, as well as the general public. In particular, the PBDB will adopt features from PBot that will allow users to easily contribute and interact with fossil identifications tied to specimen images, and outreach activities will further motivate community participation with PBDB. This project undertakes a complete technological overhaul of the PBDB, one of the most prominent and widely used fossil databases. Technical improvements include coupling the PBDB with the PBot, whose cutting-edge conceptual framework provides innovative user-centric capabilities. Specifically, development of the PBDB 2.0 will: 1) overhaul the PBDB's data model, database, and application logic to integrate PBot functions, streamline data entry, and improve technical sustainability; 2) create a more capable application programming interface; 3) construct a new web application to leverage back-end upgrades and facilitate new science; and 4) host community events and activities to assess progress, train new members, mobilize data, and produce new educational/outreach materials. Long-term costs of paleobiological cyberinfrastructure will be substantially reduced by consolidating development effort, expanding the PBDB's current functionality to better serve a large community, enhancing overall user experiences, mobilizing new science-critical data, and improving alignments with other data systems. Upgrades will provide explicit support for uncertain taxonomic classification, introduce a more specimen-forward approach to organizing fossil data, make high quality specimen images available alongside data, and add workbench capabilities. Researchers from around the world will utilize the PBDB 2.0 to understand Earth history and Earth systems processes, conduct Rules of Life research, and interpret ecological and evolutionary change across all taxonomic groups, continents, and time periods. The refreshed PBDB 2.0 will make it easier for anyone in the broader community, from professional Earth and life scientists to children, to engage with fossil science. This award by the Geoinformatics program within the Division of Earth Sciences is jointly supported by the Infrastructure Capacity for Biological Research program within the Division of Biological Infrastructure. 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 · 2025-09

PROJECT SUMMARY / ABSTRACT Heritable Breast, Ovarian, Pancreatic and Prostate (HBOP) cancers arise from pathogenic variation in cancer susceptibility genes, including BRCA1 and BRCA2. The average woman in the United States faces a 12% lifetime risk of breast cancer, but this number rises to roughly 66% for women who carry pathogenic variants in the BRCA1 or BRCA2 genes. These variants also present a 44% lifetime risk of ovarian cancer, compared to a 1.5% risk for women on average. Individuals who carry a pathogenic BRCA variant can manage their cancer risk clinically, often avoiding cancer entirely, but these clinical interventions are not available to all individuals at risk. The majority of observed BRCA variants are Variants of Uncertain Significance (VUS), individually rare yet collectively common variants for which there is insufficient evidence for clinical classification. Additionally, one-fourth of the BRCA variants in ClinVar have conflicting classifications. Sharing knowledge to promote accurate variant classification is key to reducing the burden of these heritable cancers. BRCA Exchange is the world’s largest public source of knowledge on variation in BRCA1 and BRCA2, aggregating variants from repositories including ClinVar, gnomAD and LOVD, and annotating them with pathogenicity evidence selected by the ENIGMA research consortium on HBOP Cancers and the ClinGen ENIGMA (BRCA1 and BRCA2) Variant Curation Expert Panel. This resource is visited by more than 3,000 distinct users per month worldwide, with data incorporated into major cancer research platforms including SOPHiA Genetics’ Alamut and the Barcelona Biomedical Genomics Lab’s Cancer Genome Interpreter. We seek funding to maintain and expand BRCA Exchange to leverage and support new progress in clinical genomics. We will 1) refactor the database to promote expansion while leveraging emergent variant annotation standards, 2) leverage new open source resources to expand the data integration pipeline sustainably, 3) continue formalizing the knowledgebase governance, 4) share provisional assignments of the ACMG variant evidence codes to promote VCEP-compliant variant curation, 5) share research datasets to leverage and support new scientific progress in HBOP variation, and 6) expand the scope to share variants for seven related genes for which there is now abundant and growing clinical knowledge but no effective knowledgebase.

NIH Research Projects · FY 2025 · 2025-08

PROJECT SUMMARY Human astroviruses (HAstV) are a leading cause of viral diarrhea in children. Currently, no vaccines or antiviral therapies exist for HAstV infections. Our goal is to identify essential functional sites on the HAstV surface that can be exploited for the development of preventative and therapeutic strategies against HAstV. The HAstV virion is a small, icosahedral virus composed of an RNA genome surrounded by capsid protein. HAstV enters cells through clathrin-mediated endocytosis. The human neonatal Fc receptor (FcRn) was recently identified as a functional receptor for HAstV entry into human cells, and dipeptidyl-peptidase IV (DPP4) was identified as a cofactor for HAstV entry. However, the molecular basis for HAstV interaction with these receptors is unknown, and the mechanism by which these receptors promote virus entry is unknown. Our central hypothesis is that the HAstV capsid spike domain engages FcRn in the endosome to promote virus genome release. Using innovative structural, biophysical, and virological approaches, we will pursue two specific aims to (1) define the atomic interactions, affinity, and specificity of the HAstV capsid for FcRn, and (2) define the roles of FcRn and DPP4 for HAstV attachment, internalization, capsid structural changes, and genome release. Results obtained by this work will elucidate mechanisms of HAstV entry and provide a foundation for the design of vaccines and therapeutics to prevent and treat HAstV infections.

NSF Awards · FY 2025 · 2025-08

The ability to process and use information to make better decisions is driving breakthroughs in science and engineering, and they are being materialized in business. Machine learning is one of the central forces behind such revolutionary progress. For example, machine learning is often used to make predictions for uncertain information such as traffic in a road network or consumer demand for an online business. Unfortunately, machine learning is imperfect and commonly error-prone. The goal of this project is to design efficient decision-making algorithms that result in solutions that are both high-quality and robust to error in the predictions. The investigators of this project will organize a workshop to disseminate research findings to the community. The research will be incorporated into courses and the investigators will develop an undergraduate degree program on the intersection of business and machine learning. This project will develop the foundations of augmenting decision-making algorithms with error-prone machine-learned predictions. The project’s goal is to develop algorithms that break through worst-case analysis barriers with high-quality predictions and have graceful degradation in quality as the error in the predictions grows. The algorithms developed will use predictions to improve the worst-case running time and better cope with uncertainties in the future input. The predictions used will be grounded in computational learning theory and be shown to be efficiently learnable. The project has the following goals. The project will (1) investigate using predictions to improve the running time of algorithms for problems of fundamental importance such as matchings and flows; (2) use predictions to give algorithms information about uncertain inputs for online problems and investigate various measures to better gauge the prediction quality; and (3) develop a theory for which parameters can be efficiently learned. 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 · 2025-08

This award will support a project to explore whether tiny, lab-grown human brain tissues - brain organoids - can perform computations similar to artificial intelligence (AI) systems, such as solving problems or controlling machines. Brain organoids created from human induced pluripotent stem cells can develop into networks of neurons that model early stages of human brain development. This project will involve the design of new tools that allow these brain organoids to interact with their environment using electrical signals, and chemicals, similarly to how the brain operates. Through creating this interactive system, the research team will test whether organoids can learn from experience, respond to feedback, and solve tasks in real time. One major component will be development of a new educational platform that allows students or small groups of public participants to run live experiments with brain organoids. These participants will not only learn about neuroscience and computation but will also participate in curated discussions on ethics and the future of brain-based technology. The project will help inspire a new generation of biomedical scientists and engineers, while ensuring that the research moves forward responsibly and transparently. This project will establish a scalable experimental and computational framework to uncover the learning and computational potential of human brain organoids. Brain organoids, derived from induced pluripotent stem cells (iPSCs), self-organize into complex neuronal circuits composed of diverse cell types, offering a powerful model for investigating the emergence of biological computation. However, current organoid models lack feedback mechanisms, such as electrical and chemical inputs necessary for dynamic learning and adaptive task performance. To address this limitation, the project is structured around three integrated research threads: 1) The project will develop a dynamical systems framework to map the emergence of functional connectivity and low-dimensional attractor landscapes in organoids. Organoids will be trained to solve real-time reinforcement learning (RL) tasks using closed-loop feedback systems that link sensory input to motor output, and their dynamics will be analyzed. 2) The project team will engineer a long-term, cloud-connected Internet-of-Things (IoT) system that combines electrophysiology, real-time imaging, microfluidics, and AI-driven control to support large-scale, reproducible organoid training and maintenance. 3) The project will develop an organoid-specific ‘Turing-like’ test to assess problem-solving and intelligence, while also addressing critical issues such as the potential for consciousness, donor consent, legal status, and safeguards for bio-AI systems. Beginning with brain organoids as self-organizing neuronal systems with an intrinsic capacity for computation, this project will use experimental and analytical methods to define task-specific input-output relationships and assess organoid learning capabilities and public response. Results will be interpreted in a rigorous ethical framework and disseminated through open-source tools and educational outreach. Together, this work will support responsible innovation at the intersection of neuroscience, computing, and society. 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 · 2025-08

PROJECT SUMMARY/ABSTRACT The long-term goal of this proposal is to elucidate the molecular and cellular processes underlying breast cancer risk reduction by an early full-term pregnancy. Specifically, the objective of this project is to determine the impact of age and pregnancy on mammary epithelial cells (MECs). Preliminary analysis of bulk single-cell RNA sequencing data from 18 month old nulliparous (no pregnancy) and 18 month old parous (at least 2 pregnancies) reveals that pregnancy induces a persistent inflammatory and differentiated state in MECs. Intriguingly, luminal MECs from aged, parous mice exhibit heightened inflammatory signaling but reduced proliferative capacity when challenged with TNFα. I have also identified a minority population of Krt6a+ hybrid MECs that increase with age but are lost in parous mice. Building on these exciting preliminary results, I hypothesize that an early pregnancy alters the aging trajectory of stem/progenitor MECs to induce differentiation and inflammation programs that reduce cellular plasticity and oncogenic vulnerability. Aim 1 will determine the impact of aging and pregnancy on TNFα-mediated inflammatory responses and oncogenic vulnerability in MECs. Aim 1A will determine whether Tnfrsf11b, an inhibitor of TNFα-induced apoptosis that is downregulated in aged, parous luminal cells, is responsible for the restricted growth of TNFα-treated luminal organoids from aged, parous mice. Aim 1B further explores whether the altered inflammatory profile in aged, parous MECs diminishes their tumor initiation capacity, a critical factor in understanding breast cancer risk dynamics. Aim 2 addresses the roles of Krt6a+ hybrid MECs in lineage plasticity and oncogenesis. Preliminary data show that Krt6a+ hybrid cells accumulate with age but are lost by pregnancy. Recent studies highlight the importance of lineage plasticity as a precursor to tumor initiation, providing a unique angle for understanding the dynamics of breast cancer protection. Aim 2A investigates whether the pregnancy-induced reduction of Krt6a+ cells lessens tumor burden by inducing specific mutations. Aim 2B explores the roles of unique Krt6a+ genes, Aldh3a1 and Il33, in maintaining a plastic cell state through overexpression and knock-down assays. This approach aims to define the role of Krt6a+ progenitors in pregnancy-induced protection in breast cancer, potentially serving as a future biomarker. In summary, this project will address the significant gap in understanding how an early full-term pregnancy alters age- induced senescence pathways in the mammary gland to ultimately reduce breast cancer risk. The experiments will be conducted under the guidance of Dr. Shaheen Sikandar and with the exceptional resources provided by UC Santa Cruz. This proposal not only has the potential to illuminate the dynamics of breast cancer vulnerability, but the training opportunity also places me in a position to develop into a self-directed and independent scientist.

NIH Research Projects · FY 2026 · 2025-08

Project Summary In this MIRA proposal we will gain insight into how biological timers control development and how the apical extracellular matrix (aECM) is constructed and remodeled. How biological timers control human development is only beginning to be understood. Animal development requires precise temporal synchronization of a broad range of events controlled by developmental clocks. In contrast to the circadian clocks that enable animals to anticipate daily cycles of light, temperature, and other environmental variables, the properties, components, and wiring of these developmental timers is only beginning to emerge. Examples of these timers include the clocks that control somite formation and hair follicle cycling. We use C. elegans as a model to understand developmental timers function. Two independent but interconnected biological timers drive progression through C. elegans development. The heterochronic pathway is a linear timer that controls the serial progression of stage-specific cellular events. A cyclical molting timer coordinates apical extracellular matrix regeneration and shedding of the old cuticle. Understanding these timers will inform how animals transition from juveniles to adults, how cell fate and cell divisions are coordinated with linear developmental progression, and how a dynamic aECM is built during development. Aberrant aECM function has been implicated in a variety of human diseases and defects can impact hearing, wound healing, the skin barrier, and cardiovascular and renal function. Despite extensive study of aECMs in many organisms, we know little about their molecular organization. C. elegans is an ideal model system in which to address these knowledge gaps because it is transparent with a new aECM being built each larval stage over a course of 8-10 hours making it possible to perform real time imaging of aECM formation. In addition to informing human biology, we are also interested in nematode-specific biology, as it offers an intervention point to combat parasitic nematode infections. As a group, these animals afflict an estimated 1.5 billion people worldwide, comprising approximately 85% of global neglected tropical diseases. They also threaten food security by infecting crops and livestock. Our long-term goal is to define the mechanisms that ensure faithful molting at the molecular, cellular, and organismal level in C. elegans and then extend our work into parasitic nematode models with the goal of uncovering vulnerable processes for future therapeutic targeting This work involves three projects. In the first 1 we will determine how biological timers control development, focusing on NHR-23, LIN-42, and KIN-20. In the second project, we will test whether NHR-23 is ligand regulated to control molting. In the third project we will determine how the aECM is formed and remodeled during development, focusing on the role of proteases and protease inhibitors. Our hypothesis is that each protease inhibitor has a cognate protease that it regulates to ensure that the protease is only active at a specific time and location.

NSF Awards · FY 2025 · 2025-08

This project aims to dramatically expand our understanding of RNA modification enzymes (RMEs), a broad class of proteins that chemically alter RNA molecules and influence their function, stability, and therapeutic potential. RNA modifications are increasingly recognized as essential regulators of gene expression and have already been harnessed to improve the stability and efficacy of mRNA-based therapeutics. However, the variety of RMEs and their target specificities remain poorly characterized, limiting their use in basic research, biotechnology, and medicine. By systematically identifying and assaying over 750 RMEs from nearly 100 microbial organisms, this project will establish foundational knowledge and resources to support a new generation of RNA-based tools. It will also foster research and educational opportunities for students and provide a freely accessible database and enzyme library to the broader scientific community. The research team will use an innovative high-throughput platform that combines recombinant protein expression, in vitro RNA modification assays, and advanced sequencing technologies -- specifically, Ordered Two-Template Relay sequencing (OTTR-seq) and Oxford Nanopore direct RNA sequencing -- to characterize enzyme activity across collections of 800 different tRNAs and libraries of many hundreds of other small RNA substrates. A pooling and deconvolution strategy will identify specific enzyme-substrate interactions, revealing both conserved and novel recognition motifs. Enzymes will be selected to span varied phylogenetic sources and chemical modification types, with cloning and expression carried out in a scalable format that enables rapid downstream activity screening. Follow-up validation and biochemical analyses will clarify the evolutionary plasticity and engineering potential of RMEs. The results will be integrated into an interactive web-based resource, MODKIT, which will include searchable enzyme profiles, RNA target data, and downloadable RME expression constructs. This integrated computational and molecular biology resource will broadly catalyze basic RNA modification research and promote the development of RNA-based biotechnologies enabled by a much larger toolbox of readily accessible RMEs. This project is supported by the Division of Molecular and Cellular Biosciences in the Biological Sciences Directorate and by the Division of Chemistry in the Mathematical and Physical Sciences Directorate. 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 · 2025-08

The remoteness of offshore oceans makes it challenging to understand how resources like fish are distributed, especially in deep waters. This project uses northern elephant seals, fitted with small external tracking devices, as ocean explorers to help identify biological hotspots - areas rich in resources that are essential for marine species but vulnerable to human impacts. By studying these seals, the team is mapping where hotspots occur, estimating the abundance of fish in the twilight zone (200–1000 meters deep), and advancing understanding how climate change might threaten these hotspots. The results of the research enhance marine conservation, as effective management efforts require identifying the ocean's by ecologically sensitive areas. In addition to advancing science, this project improves how undergraduate students learn and practice scientific fieldwork skills. By combining cutting-edge ocean research with hands-on training opportunities, this project is uncovering new ways to protect our oceans while preparing the next generation of scientists to tackle environmental challenges. Our understanding of resource distributions in the open ocean is incomplete due to its dynamic and patchy nature. There is a time-sensitive need to quantify the spatial and temporal variation in environmental conditions that drive population and ecosystem processes far offshore and deep below the ocean surface. The project is identifying biological hotspots - areas of intense primary productivity critical for marine species - using instrumented northern elephant seals as ecosystem sentinels. This is being achieved by (1) identifying three-dimensional biological hotspots, (2) validating high- and low-resolution biologgers for measuring fish biomass, and (3) detecting and projecting climate-driven shifts in hotspot distributions. Together, the research aims provide novel insights into the distribution, intensity, and dynamics of biological hotspots in the open ocean and twilight zone (200-1000 m depth). This research facilitates pedagogical innovation through the development of a Practical Skills framework to enhance field-based training for undergraduate students. The framework includes (A) lower-division course modules introducing field skills, (B) structured activities emphasizing practical skill development in an upper-division field course, and (C) a paid field assistant program focused on mastery of practical skills. This integration of research and education advances scientific understanding of resource variability in the ocean, provide evidence-based tools for conservation, and equips the next generation of wildlife biologists with the skills and experiences necessary to address critical environmental challenges. 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 · 2025-08

Pathogen contamination of water is an important public health threat around the world. This project will develop a low-cost and highly effective method to disinfect water., The research will create new single-atom photocatalysts (SAPs) that work as powerful antimicrobial agents under light. The SAPs are metal atoms spread out at the atomic level onto a supporting material. The interactions between the metal and the support improve light absorption and charge separation, which boost their ability to kill microbes. The research will use laboratory experiments and computer simulations to explore different transition metals that bond with nitrogen or oxygen atoms in the support material. Along with scientific discovery, this project will provide strong learning experiences to help train the next generation of STEM professionals. The research will also be integrated into several educational outreach programs. Infection by waterborne pathogenic microorganisms poses a significant threat to human and environmental health. Development of effective technologies for water disinfection is of both fundamental and technological significance in environmental remediation. The proposed research is focused on the rational design and engineering of carbon-supported single (metal) atom nanocomposites as high-performance photodynamic antimicrobial agents, a critical step in environmental cleanup through the elimination of waterborne pathogens. In these single-atom photocatalysts (SAPs), the metal centers are embedded within the supporting substrates by strong coordination bonds. The metal-support interactions can be exploited as a unique powerful variable in the manipulation of the materials' optical and electronic properties, leading to optimal photodynamic activity. The project will focus on three tasks and three unique SAPs: (a) atomic dispersion of select transition-metal species within nitrogen-doped carbon scaffold, where the photodynamic performance will be systematically examined within the context of metal-nitrogen coordination interactions; (b) structural engineering of metal oxide nanoparticle-supported single atom catalysts for enhanced photocatalytic bactericidal performance, by taking advantage of the formation of new electronic states within the oxide bandgap, such that the photodynamic activity can be enhanced and extended to the visible range; and (c) select doping of the B sites of perovskite-type ABO3 metal oxide nanoparticle for enhanced photodynamic performance due to manipulation of the electronic band structures. The materials' structures will be meticulously examined by state-of-the art microscopy and spectroscopy measurements and carefully correlated to the bactericidal activity in conjunction with first principles calculations. The ultimate goal is to establish an unambiguous structure-property-activity framework within which the antimicrobial performance of the SAPs can be manipulated and optimized. The proposed research will offer a unique educational framework that helps nurture the next-generation STEM workforce. 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 · 2025-07

Modern computer chip design faces a critical bottleneck: creating high-performance hardware accelerators requires countless manual iterations and expert-years of development time. This project addresses a national priority by developing automated Artificial Intelligence (AI) systems that can design high-frequency chips with minimal human intervention. The research focuses on Zero Knowledge Proof (ZKP) accelerators, a cutting-edge cryptographic technology that allows users to prove possession of information without revealing it—enabling privacy-preserving verification. The project brings together three complementary areas of expertise: high-frequency chiplet design, AI-powered design automation, and cryptographic applications. We will deliver a unified chiplet-based design flow by (i) co-designing deeply pipelined ZKP accelerators, (ii) developing rotary-clock architectures for stable multi-GHz clock distribution across heterogeneous dies, and (iii) building an Intelligent Design Agentic Programming (IDAP) framework. IDAP will consist of a Large-Language-Model (LLM)-augmented Electronic Design Automation (EDA) framework that leverages formal constraints and solver-guided optimization to explore code transformations beyond today’s tools. AI agents will iteratively navigate design trade-offs, such as pipeline depth, with verification checks to prevent invalid configurations. Prototype ZKP accelerator chips will be fabricated and benchmarked to validate performance gains and robustness. This integrated approach will yield an open blueprint for high-frequency chiplet accelerator design applicable to a broad range of compute-intensive applications. The resulting infrastructure will be an open and accessible setup with broader impacts on semiconductor workforce training. 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 · 2025-07

This project will improve the effectiveness and efficiency of post-mortem execution analysis, a technique for debugging software systems. Post-mortem execution analysis involves inspecting an execution's artifacts, a collection of states gathered during the execution (e.g., a software log, memory core dump, etc.). The work's key innovation lies in exploiting relationships across different types of execution artifacts to treat them as complements rather than alternatives. The work will pursue three synergistic thrusts: First, it will develop a technique that increases the efficiency of post-mortem execution analyses over "high-fidelity" artifacts (i.e., those containing all of an execution's states) by embedding them as "low-fidelity" artifacts (i.e., those containing a sparse subset of an execution's states). Second, the work will improve the effectiveness of analyses over low-fidelity artifacts by extrapolating a low-fidelity artifact into a set of high-fidelity artifacts that could have produced it. The work will support probabilistic analyses over the resulting set. Finally, the work will develop a technique for balancing efficiency and effectiveness by automatically navigating the space of execution artifacts that a given application could produce. The project will enable developers to resolve challenging software issues more quickly, which is increasingly important as society relies upon software in our modern lives. For example, society embeds software into transportation, medicine, finance, and basic human interactions (e.g., dating). In turn, resolving software issues more quickly can save money, limit disruptions, help people find love, and, in some cases, save lives. In addition, the proposed systems and techniques will serve as useful pedagogical tools for teaching students about complex systems and the process of debugging them. 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 · 2025-07

Water bodies often span multiple political boundaries and many of the challenges facing our planet are global in nature, hence international collaboration in general and in the aquatic sciences in particular is necessary to address these challenges. Most universities do not offer formal training for students to guide them in initiating and conducting productive international research collaborations. To address this need, this project provides a comprehensive training program that includes professional development opportunities and on the ground experience in planning and executing a collaborative international research project led by graduate students. This project catalyzes the development of globally engaged U.S. aquatic scientists by providing a multi-stage modular high-quality training and research program for graduate and undergraduate student teams. The experience advances graduate students in their professional development, career achievements and opportunities for success and prepares future scientists to conduct collaborative work, serve to expand networks and mentoring, improve science through collaborations and serves to increase the status of U.S. research in the world. LOREX ME supports graduate students throughout the whole process of conducting international collaborative research. Graduate students prepare individual research proposals for projects aligned with their specific research goals and execute the project at one of several international research stations in four countries (Australia, Canda, Sweden, or Israel). Undergraduate students are matched with graduate student mentors based on mutual interests and work as a team with the graduate student to conduct the research and disseminate findings. Professional development for the graduate students includes training in effective mentoring. Additional in-person and virtual workshops focus on communication and collaboration skills, planning for international work, critical incident analysis, cultural awareness, publishing and more. These webinars are open to the broader student and early career Association for the Sciences of Limnology and Oceanography (ASLO) 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 2025 · 2025-07

Neurosymbolic Artificial Intelligence is broadly understood as the combination of artificial neural network based machine learning (including Large Language Models and more generally deep learning) with symbolic methods from Knowledge Representation and Reasoning. Neurosymbolic Artificial Intelligence is currently gaining significant interest in academia and industry as a way to further advance AI research and practice related to both fundamental methods and applications in a multitude of fields. This project will provide funds to subsidize the travel expenses of 10 students and early career researchers at U.S. universities to attend the 2025 NeSy conference, held September 8-10 in Santa Cruz, California. Neurosymbolic Learning and Reasoning (NeSy) is a long-standing meeting (a conference since 2024, previously a workshop), established in 2005, focused on the synergy between neural network methods and symbolic approaches. Covered topics include Neurosymbolic methods for: generative models, knowledge graphs, knowledge representation and reasoning using neural networks, cognitive modeling, probabilistic programming, causal reasoning, and applications. The location of the conference in Santa Cruz, California, which is in close proximity to Silicon Valley, will bring together both academic and industry professionals interested in Neurosymbolic Artificial Intelligence. This provides a unique opportunity for student and early career researcher networking opportunities across academia and industry. In addition to invited and contributed talks, students will benefit from a doctoral consortium and mentoring activities. 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 · 2025-07

As massive low-cost computing resources become increasingly available, harnessing their power is crucial in modern science and engineering. One particular issue involves scheduling: what is the most effective way to assign resources, say computing cycles, to tasks in order to ensure good performance? The scheduling problem is especially acute when little to nothing is known in advance about the tasks, including when they might arrive and how much compute time they may need; in such cases, dynamic allocation of resources is required. Over the past two decades, exciting advances in approaches for addressing these so-called on-line scheduling problems have emerged, but the field is still struggling to address the increasingly challenging scheduling environments found in modern computing clusters. This project aims to develop new methods to design and analyze online scheduling algorithms systematically with the aid of widely used optimization techniques, and as a result to potentially resolve some key open questions in online scheduling. The research findings will likely provide an alternative method of educating students on scheduling in a broad context, which will have a significant impact on the computer science curriculum. This project will also involve mentoring students and disseminating the research outcomes through workshops, writing tutorials, and developing new course materials. At a more technical level, this project intends to investigate the effectiveness of online scheduling techniques for a variety of problems. The project's first objective is to develop new gradient-descent methods to design and analyze online-scheduling. The second objective is to use bin-packing to study fundamental admission-control problems, and to develop new algorithmic tools when pre-emption is allowed. The third research problem to be studied involves the development of fine-grained scheduling algorithms for low-dimensional scheduling environments. Surprisingly, despite recent advances, many existing algorithms are no match even for the simplest greedy algorithms in the low-dimensional case, which is common in practice. The fourth research goal is to refine the behavior of the online algorithms as the workload approaches the system limit, which is related to fundamental questions regarding the underlying analysis models. The last goal is to explore new models for scheduling jobs with inter-dependencies by taking advantage of large-scale scheduling environments to circumvent the intractability results that are commonly found in the traditional models. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NIH Research Projects · FY 2025 · 2025-07

PROJECT SUMMARY Pediatric diarrhea is the second leading cause of infant mortality worldwide. Astroviruses are one of the most common childhood causes of diarrheal illness, with infants at risk for severe disease and hospitalization. However, astroviruses are very understudied in part due to inadequate diagnostic testing, and consequently, little is known about their pathogenesis. Recent work has shown that astrovirus targets mucus-secreting goblet cells in the small intestine. These cells generate the critical mucus layer that shields the gut epithelium from pathogens and provides a habitat for commensal microbes. However, it is unknown how astroviruses replicate inside goblet cells and how infection impacts the cell’s ability to maintain homeostasis. Therefore, the long- term objective of my research is to define how astrovirus impacts the mucosal barrier to better understand its pathogenesis. This proposal approaches this objective by utilizing infection models in mice as well as enteroids. Our murine model will allow us to better understand the viral mechanisms at play, which will then be applied to understanding human infections. The central issue that my proposal addresses is: defining how mucus secretion is linked to astrovirus release from goblet cells and how hijacking of the secretory pathway results in functional consequences for the host. Completion of the proposed studies will shed light on a critical step in the astrovirus replication cycle and define how astroviruses cause disease based on their impact on the mucosal barrier, which could have broader impacts on gut health during early childhood development. Furthermore, my proposed training will expand my knowledge of virology and cell biology and provide me with the technical tools essential to establish myself as an independent researcher and fufill my future career goals.

NSF Awards · FY 2025 · 2025-06

This award will partially support about 18 U.S.-based students to to attend the 2025 Computer Security Foundations Symposium (CSF) in June. CSF is an annual conference for researchers in computer security to examine current theories of security, the formal models that provide a context for those theories, and techniques for verifying security. Topics of interest include access control, information flow, covert channels, cryptographic protocols, database security, language-based security, authorization and trust, verification techniques, integrity and availability models, and broad discussions concerning the role of formal methods in computer security and the nature of foundational research in this area. Student attendees will benefit in several ways: gaining experience presenting their academic work to peers, meeting and discussing ideas with other researchers, and learning about the latest research in security foundations. Beyond the benefits to the students themselves, supporting student attendance will help grow the CSF community, increasing the quality and breadth of both research and industrial talent available for improving security in the real world. Students will be selected based financial need, having a relevant paper at the conference, and being willing to volunteer to help organize the conference. 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 · 2025-05

PROJECT SUMMARY/ABSTRACT Established in 2007, the Flow Cytometry Core facility serves all research programs and faculty within the Physical and Biological Sciences division and the division of Engineering. It allows access to high-speed flow cytometry-based analysis and cell sorting of dissociated cell populations from human samples, animal experiments, and cell culture studies. The UCSC Cytometry Core is a highly utilized facility that has been critical to all research within the two divisions mentioned above. Our current sorter, a BD FACS Aria II, is over 17 years old and BD will no longer support the service contract for this machine starting 2025. In addition, recent advances in FACS technology have rendered it incapable of meeting state-of-the-art research needs. This threatens to limit critical advances in research. To address these challenges the senior leadership across our two divisions have developed a comprehensive plan to revitalize the UCSC Cytometry Core. The plan involves acquiring the BD FACSymphony™ S6 high parameter cell sorter, a bench-top high-speed cell sorter equipped with five lasers capable of analyzing up to 21 different colors plus forward and side scatter. The BD FACSymphony™ S6 will be contained within a biosafety cabinet to meet safety and regulatory requirements for sorting clinical samples. The BD FACSymphony™ S6 cell sorter represents a crucial early step in advancing the senior leaders' vision to modernize the Cytometry Core. This instrument will ensure that researchers at UCSC have access to the cell sorting technology they need to carry out high-impact funded research 24 hours a day, 7 days a week, 365 days a year. Without this instrument, the Cytometry Core will be unable to offer cell sorting, and the closest cell sorters available to the campus are over an hour away with very limited availability. Acquisition of the BD FACSymphony™ S6 cell sorter is therefore essential to continuing high-impact NIH-funded research at UCSC. Instrument supervision, training, maintenance scheduling, and recharge accounting for use of the proposed instrument will be assured by the Cytometry Core Facility manager and guided by an Advisory Committee. The core facility manager's salary and instrument operation and maintenance costs have historically been guaranteed by UCSC and will continue to be backed by UCSC for at least 5 years after the purchase of this instrument.

NIH Research Projects · FY 2025 · 2025-05

Project Summary/Abstract This proposal requests funds to purchase a laser scanning confocal microscope for a group of 13 investigators, from 4 departments and 2 academic divisions at the University of California at Santa Cruz. 10 of these investigators are NIH-funded. The proposed Leica Stellaris 8 (LS8) confocal microscope will replace a 16-year-old Leica SP5 confocal microscope, which was purchased through a California Institute for Regenerative Medicine grant mechanism and installed in 2008 and is at the end of its life. The LS8 is a flexible and modular confocal laser scanning microscope for high-end fluorescence imaging. The LS8 was confirmed to be an outstanding choice for our core facility through multiple demos as it is well suited for the research objectives of our users. It is easy to use, provides a cost-effective solution to our research challenges and maintains and expands the imaging capabilities of our local research community by introducing a White Light Laser for flexible excitation, a broader detection spectrum compared to what we have now and the ability to do Fluorescence Lifetime Imaging (FLIM). These capabilities make the instrument essential to the continuing the competitive, high-standard NIH-funded biomedical research taking place at UCSC. The user group is funded by 7 NIH institutes. These are the National Institute of General Medical Sciences (NIGMS), National Institute of Neurological Disorders and Stroke (NINDS), the National Institute of Child Health (NICHD), the National Cancer Institute (NCI), the National Institute of Allergy and Infectious Diseases (NIAID), the National Institute of Mental Health (NIMH) and the National Human Genome Research Institute (NHGRI). The users seek to bring the power of confocal microscopy to studies which include cancer, immunity, host-pathogen interactions, neurodevelopment, stem cell fate specification, cell division, and neglected diseases. Additional currently non- NIH funded projects are likely to receive NIH funding and are likely to nucleate NIH-funded inter and intramural collaboration. Anticipated biomedical research faculty hires over the next decade will certainly require confocal microscopy and demand is already projected to outpace availability, ensuring this microscope will be in high use. This microscope system will become an integral part of UCSC's Life Sciences Microscopy Center core facility (RRID:SCR_021135) in the heart of our Molecular, Cell and Developmental Biology Research Building. This placement will allow convenient access for researchers studying basic biology in this building and to researchers in our adjacent Chemistry and Biomedical Sciences buildings. The facility is open to all NIH-funded investigators; thus, this equipment will enhance and sustain biomedical research on this campus, while providing advanced training to our graduate students and postdoctoral research fellows, thereby helping to create the next generation of biomedical investigators. Securing this instrument will have a significant impact on the contributions to research and education made by UC Santa Cruz far beyond the 5-year post-award period.

NSF Awards · FY 2025 · 2025-05

Since the age of sabretooth cats, the energetic demands and hunting behaviors of large (> 25 kg) carnivorous (meat-eating) mammals including the great cats, wild dogs, bears and marine mammals have led to conflicts with human activities. This has shaped land use and fisheries regulations, as well as contributed to species declines and the endangered status of many large mammal populations. While it is recognized that predation by large mammalian carnivores dictates the structure and stability of ecosystems both on land and in the seas, knowledge about the biological traits that determine the energetic demands of these keystone predators is limited. Researchers on this project address this gap by synthesizing 40 years of energetic, behavioral and movement data for 23 species of large keystone carnivores to conduct one on the most comprehensive analyses of mammalian field energetics to date. Broad dissemination of the results to scientific, wildlife management and public communities will foster integrative plans to support activities of both humans and keystone species living on the landscape. Specifically, this project will create a library of 14 bioenergetic metrics and algorithms representing major indicators of ecological resource demands, and thus common keystone attributes of carnivorous mammals. Assessing bioenergetic demands across time and space will enable seasonal and spatial planning for different carnivore lineages comprising the felids, canids, ursids, mustelids, pinnipeds and cetaceans. By creating energetic cost algorithms for swimmers and runners, the scientific community will be able to translate locomotor movements of free-ranging mammalian carnivores into energetic costs for terrestrial or marine living. Harmonizing these data with existing animal tracking-trait databases will ensure global application and accessibility. Successful completion of this project will result in a unique library of allometric equations for comparative bioenergetic modeling across species and temporal and spatial scales that are critical for predicting sustainable resource use. These will be published in scientific journals and two technical books on carnivore energetics and scaling. Publicly accessible online and printed information about living in close proximity of large carnivores are also planned. In this way, the project will transform the understanding of both scientific and public communities regarding the unique resource needs of keystone mammals and neighboring human populations. 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.