University Of California Los Angeles

NIH Research Projects · FY 2025 · 2025-07

The purpose of this proposed Avenir Award is to achieve widespread population health improvements in preventing HIV transmission and overdose amongst people living with substance use disorders (SUD) by mitigating barriers that hinder linkage to healthcare and social services. One in five individuals living with HIV has a comorbid SUD, highlighting the importance of increasing connectivity to low-barrier services to prevent HIV transmission and overdose and increase treatment initiation. While rigorous scientific evidence about the effectiveness and safety of these services exists, the timeliness and user-friendliness of information is limited. Dissemination strategies are critically needed to increase availability of current knowledge about effective HIV and SUD services to help prevent HIV transmission and improve health outcomes for people living with SUD. This proposal is aligned with the goals of the Avenir Award and NIDA’s strategic objectives to improve the implementation of evidence-based services in real-world settings by overcoming upstream barriers that prevent or slow receipt of health services. This Avenir Award research proposes innovative new methods to create more efficient and effective dissemination approaches, maximizing the return on investments in HIV/SUD research. This project draws on interdisciplinary methods from health law and dissemination science while being guided by the Exploration, Implementation, Preparation, Sustainment Framework (EPIS) to reconceptualize how researchers identify dissemination opportunities across contexts to improve SUD and HIV population health outcomes. This project will culminate in: (1) a transferable and efficient tool to identify evidence use behaviors and needs, (2) message frames, (3) dissemination strategies, and (4) a new agenda for dissemination science research to support user-friendly availability of SUD/HIV research and to create new measures for investigating dissemination outcomes. This project will rapidly build effective methods for disseminating science while increasing connectivity to services that can reduce HIV transmission and overdose to improve health outcomes for people living with SUD.

NIH Research Projects · FY 2026 · 2025-07

PROJECT ABSTRACT Irritable bowel syndrome (IBS), the main bowel disorder of the gut-brain interaction (DGBI), affects up to 10% of the US population and is characterized by chronic abdominal pain and altered bowel habits. Early life adversity (ELA) is recognized as a major predisposing factor for the development of IBS later in life. Despite years of research, abdominal pain, the most important determinant of IBS severity, quality of life impairment and healthcare utilization, remains a significant challenge in IBS management and an unmet need in patients. Mounting evidence indicates that IBS patients have compromised engagement of the inhibitory descending pain modulation systems, and contrary to healthy subjects, do not respond with a decreased visceral pain to rectal distention under conditions of heterotypic stimulus. Using a novel non-invasive method of visceral pain monitoring, we discovered that rats exposed to an acute or repeated water avoidance stress (rWAS), a psychological stressor, display a stress-induced visceral analgesia (SIVA). Acute WAS-induced SIVA in naïve male rats can be reproduced by low dose central injections of CRF, supporting a role for brain CRF signaling in SIVA. In addition, we established that rWAS-induced SIVA is partly opiate-dependent in female and opiate- independent in male rats. In preliminary data, we show that SIVA induced by acute WAS or icv CRF depends on the central oxytocin (OT) system, which also exerts an inhibitory tone on basal visceral pain in male rats. We further show that both male and female adult rats exposed to ELA in the form of limited bedding stress (LBS) as neonates lose their ability to mount a SIVA in response to rWAS, and males, but not females, develop a delayed stress-induced visceral hyperalgesia (SIVH). Based on existing and our novel findings, we propose that the loss of SIVA and resulting SIVH to rWAS with prior exposure to ELA is linked to a dysregulation of brain oxytocinergic pathways. The hypothesis will be tested in three aims: Aim 1 will establish that both brain CRF and OT signaling contribute to visceral analgesia and interact throughout the pain modulating pathways to produce SIVA in a sex- dependent manner. In Aim 2, we will establish the dysfunction of central OT following ELA, and investigate whether alterations occurring at the functional (OT release, OT receptor expression, oxytocinase, epigenetic alterations) underlie the loss of SIVA and development of hyperalgesia in adult rats exposed to limited bedding stress (LBS) as neonates. In Aim 3, we will test whether the ELA-induced central oxytocin dysfunction can be corrected using brain- or microbiota-targeted approaches. We will use integrative approaches including molecular, pharmacological, bioassay, immunohistochemistry, in vivo functional assays and state of the art techniques such as RNAscope-ISH-IHC combined analysis. Studying how alterations in the interaction between the central oxytocin and CRF systems participate in the expression of stress-related visceral analgesia or loss thereof could help explain the different degrees of visceral hypersensitivity in IBS and inform the development of safer and more effective treatments for abdominal pain in stress-sensitive IBS.

NIH Research Projects · FY 2026 · 2025-07

Abstract The research in our laboratory centers on our recent discovery that histone H3 is an oxidoreductase enzyme, catalyzing the reduction of cupric (Cu2+) to cuprous (Cu1+) ions. Historically, histones have been considered as DNA packaging proteins that regulate gene expression through epigenetic mechanisms. However, considering that ancestral histones existed in simple organisms lacking nuclei and epigenetic capabilities, we thought it would be plausible that histones may have a different function predating their current epigenetic roles. It is also noteworthy that a histone-containing archaeon was the host for the first endosymbiotic event leading to the mitochondria, raising questions about the role of ancestral histones in eukaryogenesis. Inspired by geochemical events surrounding the appearance of the first eukaryotic cell, we have discovered a novel function for histone H3 as a copper reductase enzyme. This activity is important because copper must be in its reduced, Cu1+ state to be effectively transported and utilized by copper-dependent proteins and enzymes. Over the last five years, we have shown that histone H3 binds a Cu2+ ion at the H3-H3’ interface, reconstituted the copper reductase activity of recombinant histone H3 in vitro, confirmed this activity within nucleosomes, and provided genetic and molecular evidence that this activity regulates cellular Cu1+ levels, impacting copper- dependent activities like mitochondrial respiration. Additionally, our research has provided the first example of how the copper reductase activity of histone H3 may contribute to the pathology of a human disease, namely, Friedreich’s ataxia, a neurodegenerative disease. Our data have established histone H3 within nucleosomes as the first known protein-based mechanism for regulating copper oxidation state inside the cell. Our overarching future goal is to expand our understanding of chromatin structure and function by deeply exploring the enzymatic activity of the nucleosome. We aim to investigate both the immediate questions about the mechanism and regulation of enzyme activity, and the broader questions about how this enzymatic activity influences cellular metabolism. Over the next few years, we plan to develop a detailed understanding of nucleosome enzyme activity through structural and functional studies, examine how this activity integrates with broader cellular metabolism, including copper homeostasis, and investigate potential biological connections between the lysosome—the main copper repository—and the nucleosome. We will also explore how copper homeostasis could facilitate a previously unrecognized connection between the mitochondria and the nucleus. Armed with a deeper understanding, we will then begin to extend our investigations to mammalian systems. We envision our work will provide a new metabolic context for understanding the eukaryotic nucleosome, forming a common thread from eukaryogenesis to human disease.

NSF Awards · FY 2025 · 2025-07

This project seeks to provide an improved understanding of turbulent transport and the chemistry of reactive trace species in the stable boundary layer of the atmosphere. The primary hypothesis is that the layered structure of the stable boundary layer, together with the nonlinear character of chemical reactions, impacts vertical fluxes and the reaction rates of many important trace gases and must be considered in the interpretation of observations and the development of air pollution models. A better understanding of stable boundary layer mixing will lead to improved predictions of severe air pollution events, especially in wintertime urban regions where persistent cold air pools can result in weak vertical mixing and a buildup of pollutants at the surface. This project will address the following scientific questions: (1) How is vertical transport of passive trace species impacted by the layered vertical structure of the stable boundary layer (SBL) with strong internal inversions? Does this structure impact the applicability of traditional eddy diffusivity models as the bulk stability of the SBL increases? (2) What impact does chemistry of trace gases have on the vertical transport in the SBL? How can we parameterize the transport of reactive species and the segregation of gases as a function of atmospheric stability? (3) How much does the simulation of air pollution chemistry in stable boundary layers improve with a better description of vertical transport and segregation? (4) How does the urban canopy alter the structure of fronts in the SBL and the effects of turbulence on the vertical transport and segregation of chemical species? The broader impacts of the project include the design of an interactive exhibition as part of UCLA’s Exploring Your Universe, an annual science festival that attracts over 10,000 visitors, including many K-12 students, to the UCLA campus. 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 award is made in response to Dear Colleague Letter 24-130, as part of the ECosystem for Leading Innovation in Plasma Science and Engineering (ECLIPSE) interdisciplinary program. This grant supports research that addresses the sustainable use of etch gases in semiconductor manufacturing, which is increasingly important for the US microelectronics industry and associated supply chain, and national prosperity and security. Semiconductor manufacturing of a chip (the “brain” in smart phones) is like building an “entire city on a fingernail”, where each “building” has a specific function, together they make the “city” work. With limited and precious “real estate, the fingernail”, each new version of the “city” gets smaller with taller “skyscrapers” thus achieving improved performance and making the smart phone more and more powerful. The process of manufacturing these chips uses chemical etch gases such as PFAS (per- and polyfluoroalkyl substances) that pose environmental and health concerns. This award supports fundamental research that seeks to provide knowledge to discover and use novel environmentally friendly etch gases and break them down to minimize their emission to the environment. Findings from this research intend to benefit the U.S. economy, environment and society. Research outcomes are integrated into existing curricula on semiconductor manufacturing with new modules focusing on plasma physics and chemistry, plasma-surface interaction, and related chemical processes to realize sustainable semiconductor manufacturing. In addition to educational benefits, this award provides hands-on training to students and helps prepare them for job opportunities in the semiconductor industry. This project aims to address the sustainable use of etch gases in semiconductor manufacturing with a combined modeling and experimental approach. While plasmas are effective in breaking the Carbon-Fluorine (C-F) bonds in per- and polyfluoroalkyl substances (PFAS) gases, the challenges remain in how to avoid the reformation of C-F bonds that can lead to the production of PFAS byproducts. Specifically, this proposal looks to evaluate the thermodynamics and kinetics related to the dissociation of PFAS gases, understand the effect of reactive oxygen and hydrogen species, delineate the role of secondary gases or catalysts in shifting the equilibrium of product formation, and assess the efficacy of the overall process in terms of processing performance and environmental impact. The experimentally validated data will be shared with the artificial intelligence/machine learning community where there is a need for training data. If successful, this research will help minimize the impact of PFAS, enable more efficient process in fabricating of microelectronics, and lay the foundation to address the effect of increasing semiconductor manufacturing on the environment in the United States. 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

After recent breakthroughs in quantum error correction, research on quantum computing is entering a new era. Now computer science is more important than ever to the success of quantum computing. We have more exciting algorithms and more qubit technologies than ever, and now we can suppress hardware errors to some degree. In this diverse field, computer science people can devise quantum algorithms and prove limits on what can be achieved, they can design and implement a software stack, and they can formally verify that algorithms and tools work correctly. As a precursor to addressing these challenges, the investigators will host a workshop devoted to identifying the main research challenges in quantum computing. The workshop will bring together researchers from academia, industry, and government research labs working in the area of quantum computing. The main deliverable of the workshop will be a workshop report summarizing the discussions and recommendations made during the meeting. The workshop report will inform researchers about new directions in the field and provide a basis upon which next-generation elements of quantum computing can be specified, designed, and implemented. 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

With support from the Chemical Measurement and Imaging Program in the Division of Chemistry, Steffen Lindert and his group at Ohio State University are working to understand and improve mass spectrometry (MS) measurements of covalently labeled proteins. Chemical reactions of accessible sites on a protein with specific labels followed by the use of MS to identify the areas that were labeled helps illuminate protein conformation. Dr. Lindert will perform molecular dynamics simulations to understand how labeling reagents interact with proteins and whether they might induce unwanted conformational changes. Additionally, a web server will be developed to identify the optimal covalent labeling reagents for a given protein sequence. These studies are designed to improve MS covalent labeling measurements, and in this way lead to a better understanding of protein conformation, with potentially broad long term scientific impact in protein conformational/folding studies. If successful, these studies will support work with minimally invasive covalent labeling reagents and support the design of new labeling reagents that do not distort the probed structure. The performance and utility of MS covalent labeling measurements would be greatly improved by a better understanding of how covalent labeling reagents interact with proteins and through a systematic understanding of which labels are most suited for a particular protein under investigation. To address these needs, continued computational work that advances covalent labeling measurement science is required. Dr. Lindert’s research is expected to further improve covalent labeling measurements by addressing these current limitations. MD simulations will be used to develop better models of how different covalent labels interact with proteins. The interaction of several commonly used covalent labels with proteins in solution will be simulated before and after covalent attachment, and the Lindert group will explore if and potentially how certain labels distort protein structure or dynamics. Knowledge gained from these simulations has the potential to elevate understanding of covalent labeling measurements. The protein sequence defines possible structural conformations, illuminating which residues may be optimal for labeling in structure determination studies. Subsequently, a web server will be developed to identify the optimal covalent labeling reagents for a given protein sequence. The projected development of this web server stands to benefit the entire protein covalent-labeling 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.

NIH Research Projects · FY 2025 · 2025-07

PROJECT SUMMARY: Mpox virus (MPXV), formerly Monkeypox virus is a zoonotic pathogen that spreads rapidly through human- human transmission via respiratory droplets and direct contact, causing painful rashes and systemic issues. It also causes moderate to severe ophthalmic manifestations, most commonly ocular surface complications such as keratitis, conjunctivitis, and blepharitis, with poorly understood pathogenic processes. The 2022 MPXV strain (Clade IIb) has caused approximately 100,000 infections and 207 deaths to date, indicating its evolution towards more rapid human-to-human transmission compared to previous strains (Clade I and Clade IIa). Our preliminary data show that the 2022 MPXV strain induces an inflammatory response and increases cell death in human corneal epithelial cells. Similarly, MPXV infection in mouse eyes causes periocular pock lesions, ptosis, and corneal opacity, indicating keratitis. Infected mouse corneas exhibit increased infiltration of CD45+ immune cells. Moreover, MPXV infection decreases levels of the antiviral STING protein that senses cytoplasmic DNA through cGAS and triggers type I interferon responses to restrict virus replication. Genomic analysis of the 2022 MPXV strain indicates the acquisition of new mutations across the viral genome. Two genes have been identified among the 21 Clade IIb viral gene variants that degrade antiviral STING proteins. Based on these data, we hypothesize that MPXV continuously evolves to better circumvent the host innate immune system and cause ocular Mpox. The overall goal of this study is to define both viral and host determinants of MPXV in causing ocular pathology and to identify potential therapeutic targets for antiviral therapy. This will be accomplished through three specific aims. Aim 1 is designed to determine the in vitro susceptibility of ocular cell types and host inflammatory responses to MPXV. In addition, using a library of kinase inhibitors and innate immune agonists, we will dissect cellular signaling and innate immune pathways during MPXV infection of ocular cells. In Aim 2, we will characterize the MPXV viral genes antagonizing antiviral STING pathway activation. Recombinant MPXV mutant viruses lacking the ability to evade cGAS-STING detection will be evaluated for their ability to replicate and modulate innate responses in ocular cells. In Aim 3, we will study the pathogenesis of ocular Mpox caused by MPXV clades in mouse models and test the efficacy of two novel antiviral compounds (kinase inhibitors). Collectively, this proposed study would yield novel insights into the pathogenesis of ocular Mpox and potentially lead to the identification of newer therapeutic targets.

NIH Research Projects · FY 2025 · 2025-07

Yellow fever is a mosquito-borne viral hemorrhagic fever and re-emerging threat, causing multiple recent outbreaks in Africa and South America. Delayed detection of yellow fever in endemic regions leads to epidemics and increased mortality. Factors contributing to delayed recognition of outbreaks in Africa include the changing populations at risk for yellow fever, diagnostic delays, and resource constraints. The overall objective of the proposed study is to improve early detection of yellow fever outbreaks through predicting areas at greatest risk, identifying relative diagnostic delays, and comparing the impact of new diagnostic strategies. This work will take place in Ghana, a high-risk country for yellow fever with multiple recent outbreaks. The central hypothesis is that yellow fever outbreaks are most likely to originate in rural locations with limited access to diagnostics, and local data-informed models can identify these areas to allocate diagnostic resources. The central hypothesis will be tested through pursuing three specific aims: 1) to develop subnational risk maps for yellow fever in Ghana using local data and machine learning, 2) to quantify patient and specimen delays using local yellow fever diagnostic data and spatial statistics, and 3) to compare the cost- effectiveness of different strategies for yellow fever diagnostic resource allocation. Each aim will involve field data collection, novel analytical and modeling methods, and evidence translation for policymakers. This innovative approach could then be applied to improve detection of yellow fever and other emerging zoonotic and vector-borne diseases in other countries. The results of this research will be directly translatable to national and international policymakers. It will also increase knowledge about the risk for yellow fever and other Aedes-borne arboviruses in Africa in the setting of environmental change. This K08 award will also support the career development of the PI, Dr. Seth Judson, an infectious disease physician who aims to become an independent investigator at the nexus of virus eco-epidemiology, modeling, and policy. To achieve these goals and the proposed research, Dr. Judson has created a career development plan and mentorship team to gain expertise in field epidemiology, virus ecology, laboratory diagnostics, spatial modeling, and evidence translation for policymakers. This includes primary mentor, Dr. David Dowdy (Johns Hopkins University), and co-mentors Drs. Vincent Munster (NIAID), Amy Wesolowski (Johns Hopkins University), and Ernest Kenu (University of Ghana). By conducting this research and developing a unique skillset combining field data collection, modeling, and policy translation, Dr. Judson will be well-prepared to become an independent investigator who creates tools for decision-makers to improve early detection and mitigation of arboviruses and hemorrhagic fever viruses.

NSF Awards · FY 2025 · 2025-07

This project investigates problems in algebraic geometry. Algebraic geometry is the field of mathematics that studies the geometric shape of objects defined by polynomial equations. Often, the shape of these objects, called algebraic varieties, reflects the complexity of the defining equations and vice-versa. For instance, from the defining equations, we can understand if the algebraic variety has singularities, i.e., whether the geometric object has sharp points at which the curvature changes abruptly. These points are known as algebraic singularities. This project aims to develop new tools to understand algebraic singularities and apply these techniques to understand algebraic varieties of positive curvature. As part of the broader impacts of this project, the PI will run online research seminars for graduate students related to the proposed research. The PI will initiate a summer reading program in algebraic geometry for undergraduates. The educational component of this project includes training in algebraic geometry for graduate students. Two summer research schools will be hosted at UCLA by the PI and experts in the field to train the new generation of mathematicians in birational geometry. Fano varieties are considered one of the three building blocks of projective varieties. There has been a lot of progress towards understanding the geometry of Fano varieties in the last few decades. Nevertheless, the understanding of log terminal singularities (the local analog of Fano varieties) is far from being satisfactory. Complexity is an invariant that allows us to understand how far a Fano variety or a log terminal singularity is from being toric, i.e., defined by binomial equations. In this project, the PI will develop techniques to understand Fano varieties and log terminal singularities of small complexity, for instance, complexity zero, one, and two. There are two guiding principles: understanding the connection between the complexity and minimal log discrepancies (in the local setting) and understanding the connection between the complexity and anti-pluricanonical systems of Fano varieties (in the global setting). The PI aims to apply the former to study the termination of flips and the latter to understand the classification of cluster type Fano varieties. 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 use a novel technique in artificial intelligence (AI) and machine learning (ML) to automatically discover the fundamental driving Partial Differential Equations (PDEs) of the Earth’s magnetically trapped high-energy electron population, the so-called radiation belts. Understanding and predicting radiation belt dynamics is essential for protecting the rapidly growing satellite fleet from damage, which has been identified in numerous governmental, and agency reports as a high national priority. Making headway in developing PDE-discovery techniques to work effectively in a demanding situation will open the doors and enable PDE discovery to work in similar challenging environments in the Earth and Space sciences (and beyond), leading to a change in paradigm in how fundamental science is done. The overarching science goal of this project is to develop a methodology that will automatically discover the Partial Differential Equations (PDEs) governing the dynamic evolution of the Phase Space Density (PSD) of radiation belt electrons and use that methodology to enable significant breakthroughs in Geoscience research, namely identifying the driving physical processes at different times and locations during geomagnetically active periods. The proposed study will use a recent multi-spacecraft PSD dataset developed in our group, which is openly available to the public, and leverage innovative approaches in Artificial Intelligence (AI). The proposed activity has the potential to advance knowledge in its own field and many related fields in geoscience and the physical sciences. This project supports undergraduate and graduate students and a postdoc, which creates educational opportunities for STEM workforce development that span various career stages. 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

Contact structures are central objects of study in modern geometry and topology. They appear naturally as the boundary of space-time in mathematical physics, and as such, play an essential role in the mathematical study of three- and four-dimensional spaces and the knotting of DNA. In dimension three, contact structures are comparatively well-understood due to dramatic advances in the previous decades. The goal of this research project is to study the relationship of contact topology to quantum physics and to quantum invariants of knots and links and further develop the study of contact structures in higher dimensions, which is still in its infancy despite significant advances in recent years. As part of this project, the Principal Investigator will also promote the training of future mathematicians. This research project on higher-dimensional contact topology, Floer theory, and their interactions with quantum topology has two parts: The first is to study the mathematics surrounding the recent discovery of the relationship between Hecke algebras --- essential ingredients in quantum knot invariants --- and the higher-dimensional Heegaard Floer homology of the cotangent bundle of a surface. One of the goals is to better understand the topological quantum field theory (TQFT) underlying this discovery, relate it to string topology, and define and analyze the 3- and 4-manifold invariants corresponding to this theory. The second is to continue the systematic study of convex hypersurface theory --- a technique to decompose a contact manifold into easier-to-analyze pieces --- following the works of the Principal Investigator in collaboration with Breen and Huang and to apply them in the analysis of codimension two contact submanifolds and higher homotopy groups of the space of contact structures. 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 · 2025-07

Project Summary The ability to keep track of elapsed time is essential for many forms of reward-guided learning and behavior. Midbrain dopamine (DA) neurons are implicated in both reinforcement learning (RL) and timing, however, these two functions have largely been studied in parallel rather than under a unified framework. One of the most elegant demonstrations that DA dynamics contain timing information is found in trace conditioning tasks, when reward is unexpectedly omitted. This form of negative reward prediction error appears as a brief inhibition, or dip, in DA activity around the time of expected reward. While this DA dip is usually interpreted as a negative reinforcement signal, it also represents a highly effective neurophysiological readout of predicted reward timing. However, despite being a well-known phenomenon, it is still unclear how DA neurons learn to predict the timing of reward. This project seeks to address this significant gap in understanding by studying the neural circuit mechanisms underlying the timing of the DA reward omission dip. We will examine the role of DA signals and neural dynamics in the ventral striatum, an area implicated in reward and temporal processing. The project’s central hypothesis is that DA and striatal timing processes are interdependent, with the striatum relying on DA signals to learn a more refined representation of time, and DA neurons relying on this striatal code in order to predict the timing of reward, and thus undergo properly timed dips if reward is omitted. The project will combine experimental and computational approaches to measure, perturb, and model DA, striatal dynamics, and licking behavior in mice engaged in classical trace conditioning tasks, with rewards omitted on a subset of trials in order to probe timing processes. Aim 1 will examine how the temporal precision of DA reward omission dips and striatal dynamics changes across learning. This will provide a crucial test of the prediction that the representation of time in these circuits is a plastic property and not fixed, as assumed by most reinforcement learning models. Additionally, this will reveal whether specific striatal populations, namely either D1 or D2 receptor expressing projection neurons, become better at encoding time over the course of learning. Aim 2 will pursue causal evidence that DA and striatal dynamics mutually influence each other’s temporal coding properties, by transiently manipulating activity in one circuit and monitoring changes in the temporal precision of the other circuit. Here we will also determine whether these manipulations alter the temporal precision of licking behavior. Last, Aim 3 will seek to develop a computational framework for describing the experimental results. We will build and test predictions of temporal difference reinforcement learning (TDRL) as well as biologically inspired recurrent neural network models constrained by experimentally observed data. Taken together, this highly synergistic experimental and computational effort is expected to lead to a more unified understanding of the mechanisms underlying RL and timing.

NIH Research Projects · FY 2025 · 2025-06

In light of the increasing importance of heat and wildfires as growing contributors to air pollution (AP) in the US, there is a pressing need for investigations into effects they have on the cognitive and mental health of vulnerable elderly and to better understand biologic pathways. Here we propose to assess the impact of wildfire smoke and heat on cognition, mood, and the human metabolome in a vulnerable older population. Parkinson's Disease (PD), a common neurodegenerative disease with high rates of cognitive decline and depressive mood, affects older adults and has been linked to air pollution; those with PD may also be particularly susceptible to heat wave and wildfire smoke exposures as they may curtail physical activity, impair sleep, and affect mood. The California Central Valley, a region notorious for its high level of AP from traffic and agricultural sources, is under strong pressure from heat and wildfires, making it an ideal environment to investigate health impacts in older residents of rural communities. Our large case-control study (with follow-up) of ~1000 well-characterized PD patients and as many community controls has assembled comprehensive lifelong risk factor information, detailed residential histories, and biosamples over two decades. Data on cognitive status and decline (in patients) as well as depressive symptoms/diagnoses have been collected and, for the first time, will be used to assess heat and wildfire-related impacts while controlling for other pollutants (air pollutants, pesticides). Heat waves not only generate short term physiologic stress, but also prevent older adults from sleeping, exercising, and socializing which are important for healthy aging. Our approach relies on cutting-edge spatiotemporal modeling techniques, incorporating land-use regression (LUR) and harnessing the power of machine learning algorithms. These methods will allow us to generate exposure measures for a range of pollutants and wildfires. To generate heat measures, we will use the gridMET data and apply the U.S. National Weather Service Heat Index algorithm. For wildfire smoke, we will use the Community Multi-Scale Air Quality (CMAQ) model, a well-established tool for simulating air quality from specific sources as well as an innovative ensemble model that incorporates novel statistical techniques to capture the dynamic and evolving nature of wildfire smoke and its impact on air quality. We have generated untargeted metabolomics data for 919 PD patients and 419 controls with repeat samples available for 450 patients. These data will be used to explore pathways implicated in cognitive decline and mood – mainly depressive symptoms/diagnoses - in older subjects, many at high risk for the outcomes as they suffer from PD, with the aim to illuminate underlying biological mechanisms of wildfire smoke and heat stress exposures in rural older adults. We will be leveraging advanced modeling techniques and a robust systems biology analytical approach with our metabolomic data to identify short and long-term physiologic responses to these exposures in PD and older controls. Our approach will address the complex interplay between environmental factors and cognitive and mental health of older adults with a potential to shed light on metabolomic features and pathways that increase susceptibility or resilience as we face heat and increasing wildfire frequencies.

NIH Research Projects · FY 2026 · 2025-06

Project Summary: High-speed volumetric imaging of dynamic neuronal activity over extended periods is a challenging yet crucial objective in neuroscience. Conventional optical measurements of neuronal activity primarily rely on calcium signals, which provide limited information about natural signal processing in the nervous system and offer minimal data on the continuous inhibitory and excitatory signals in most neurons. In contrast, voltage imaging directly measures neuronal electrical activity, potentially overcoming the limitations inherent to calcium imaging. Recent advances in NIR voltage-sensitive dyes have significantly expanded the use of voltage imaging in brain research, driving the development of new optical instrumentation optimized for this purpose. Capturing neural action potentials in 3D poses a significant challenge for imaging instrumentation, requiring millisecond temporal resolution for precise recording. Traditional 3D optical imaging techniques, such as confocal or multiphoton microscopy, rely on extensive point scanning to create volumetric images. However, these methods often result in lengthy acquisition times, making them unsuitable for capturing rapid changes in neural activity. Recent advancements in light field microscopy have significantly boosted the frame rate of 3D microscopy, making it an ideal strategy for imaging neuronal networks. However, because light field imaging records both spatial and angular information, it typically requires a large-format image sensor, which has a low frame rate due to limited electronic bandwidth. The temporal resolution achieved thus far (tens of milliseconds) is insufficient to resolve individual neuron firing events (~one millisecond). Moreover, despite its digital refocusing capabilities at specific depths, light-field microscopy lacks inherent optical sectioning abilities. This limitation becomes pronounced in environments with high background light, reducing image contrast and diminishing its efficacy for in-vivo imaging. To overcome the above limitations, we propose to develop a NIR confocal Squeezed Light-field Microscopy (SLIM) method for kilohertz volumetric imaging of neuronal action potentials. This method has recently become feasible due to the emergence of SLIM, which is highly efficient in acquiring light field data for 3D imaging. Instead of measuring the entire light field data cube, SLIM captures a compressed light field representation, significantly reducing the data load and enabling a kilohertz volumetric frame rate. Additionally, by incorporating a confocal slit, we will be able to suppress background light and significantly increase image contrast, which is crucial for in-vivo imaging. When combined with NIR voltage-sensitive dyes, the resulting system will provide a comprehensive solution for high-speed voltage imaging of 3D neuronal networks in deep tissues. Furthermore, the proposed system will be compatible with experiments in behaving animals, allowing researchers to link neuronal activity to behavior. The insights gained from this research will be instrumental in interpreting complex animal behaviors based on electrical activities at the single-cell level.

NSF Awards · FY 2025 · 2025-06

This doctoral dissertation research studies the ways that different communities participate in government-led land management initiatives. Using a comparative research design between two groups, the investigators specifically test for the social, historical, and spatial variables that impact how different communities approach land management and in turn how this affects their participation in and collaboration with broader land management initiatives. In addition to providing scientific training for a graduate student in anthropology, broader impacts of the project involve collaborative creation of an archive to document land management efforts. This collaborative design contributes to enhancing the impacts of community engagement and knowledge co-production in STEM. Research findings will also provide scientifically tested insights into how communities can be integrated into broader land management initiatives by national governments. To understand the variability of participation in land management efforts, the investigators utilize a comparative research design that traces differences between multiple sub-groups. They use historical/archival and qualitative research methods that include semi-structured interviews and behavioral and participant observation. The research expands the science of land management. It contributes to the knowledge base in anthropology and cultural and human geography and provides science-based insights into collaborative land management efforts. 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 · 2025-06

The recent wildfires in Los Angeles County in January 2025, which affected thousands of lives and caused substantial property damage, have underlined the urgent need for new, advanced, data-informed strategies for efficient and proactive management of such devastating events. However, the development of such data-informed solutions is still largely hampered by limited access to multisource, multi-resolution remote sensing imagery, leaving many in the machine learning and computational sciences communities unable to contribute robustly. This project uses large language models (LLMs) to extract properties and relationships from relevant LA fire data sources, storing them in a comprehensive knowledge database. By integrating complementary wildfire-related information, the framework facilitates monitoring of key physical parameters, such as real-time evacuation orders, meteorological variables, and air quality indicators. The project aims to develop an LA Fire Knowledge Graph-Agent (LAFireKG-Agent) platform--an autonomous and end-to-end LLM-based framework designed to meet the diverse data needs of end users, and enhance situational awareness for both safety and timeliness in wildfire risk management. The LAFireKG-Agent framework focuses on three key objectives: rapid decision-making, predictive modeling, and complex reasoning. Beyond these core capabilities, end-users, including computational scientists, environmental scientists, and risk managers, will be able to explore wildfire-specific questions, generate tailored insights, and receive data-driven recommendations. By integrating advanced machine learning and knowledge graph methodologies, this project will not only lead to more effective disaster preparedness and response strategies, but also promote open science and reproducible research in AI-driven environmental studies. The resulting tools and best practices will be shared through publicly accessible platforms, expanding research synergy among scientists, practitioners, and community organizations. 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 · 2025-06

ABSTRACT Apical periodontitis is a chronic inflammatory disease that results from advanced dental infection of the root canal system. Studies of global populations provide an estimate that the prevalence of apical periodontitis after endodontic infection may range between 12% to 80%. Collectively, generalized periodontitis and apical periodontitis thereby represent two of the most common chronic inflammatory diseases in humans; however, the pathological mechanism of apical periodontitis is less established. Oral chronic inflammatory diseases are associated with a subset of helper T cells expressing IL-17 (Th17 cells). Pathogenic Th17 cells are now recognized as a distinct Th17 subset, uniquely classifiable from homeostatic Th17 populations. These cells have been implicated as key drivers of disease pathogenesis in various systemic chronic inflammatory diseases. Similarly, an infiltration of Th17 cells has recently been associated with the severity of periodontal disease in response to oral microbial dysbiosis. Our preliminary studies with single-cell RNA sequencing confirm that periodontal T cells infiltrate the local inflammatory environment during pathogenesis of ligature- induced periodontitis in mice. Notably, these infiltrating T cells were found to highly express the major Ca2+ signaling via Ca2+ release-activated Ca2+ (CRAC) channel protein—ORAI1. ORAI proteins compose the core subunits of CRAC channels, which are essential for T helper cell differentiation and effector function. Recent studies demonstrate that the differentiation and pathogenicity of effector Th17 cells are highly sensitive to disruption of Ca2+ signaling. Although the transcriptional networks directly relying on CRAC channel activity to mediate differentiation and pathogenicity have yet to be fully elucidated, modulation of Ca2+ dependent mechanisms via ORAI have been proposed as an attractive therapeutic strategy for T-cell mediated diseases. Therefore, herein we seek to: 1) Establish the physiological role of ORAI1 in apical periodontitis. 2) Determine the ORAI-dependent transcriptional program in effector T cells. 3) Test the therapeutic potential of targeting ORAI to suppress apical periodontal T cell responses in oral inflammation. Outcomes of this investigation will help define the impact of oral Th17 cells and, more specifically, the pathological role of ORAI1 in microbial induced apical periodontitis. The candidate, Dr. Hasiakos, is an Endodontic Dental Specialty and PhD Program (DSPP) scholar pursuing an academic career in dentistry. The proposed project is directly relevant to his professional career development. The candidate identifies primary research mentors: Drs. Gwack and Srikanth—who discovered the role of CRAC channels in T cells and thus provide an ideal research training environment. The professional career development co-mentors, Drs. Nishimura and Kapila, are Co-PD/PI of the UCLA K12 DSPP that currently supports the candidate. Drs. Nishimura and Kapila are committed to guiding Dr. Hasiakos towards the completion of his PhD, application of translational methods in dentistry, and, ultimately, to his successful development as an academician.

NIH Research Projects · FY 2025 · 2025-06

PROJECT SUMMARY/ABSTRACT The long-term objective of our studies is to understand the molecular mechanisms underlying the formation of synaptic connections between neurons in the brain. These patterns are complex and highly specific and they represent the genetic hardwiring of behavior. Extensive maps of connections between neurons have been assembled in Drosophila melanogaster. These maps of unprecedented completeness provide an extraordinary opportunity to leverage the molecular and genetic toolkit in Drosophila and the dramatic advances in light microscopy to uncover the logic and mechanistic basis for the formation of the connectome. Here we focus on the development of specific patterns of connections in the Drosophila visual system. We focus on how different synapses form in different domains of the same dendrite and how neurons select between different potential synaptic partners. Specific proteins will be tagged in cell-type specific ways allowing for precise subcellular resolution of protein distribution. The precise localization of proteins to specific synapses is facilitated by imaging isotropically expanded tissue using light-sheet microscopy. Synapse associated proteins are identified in complexes associated with tagged neurotransmitter receptors using an affinity purification-mass spectrometry workflow. This proposal seeks to close the gap between cell recognition molecules mediating interactions between developing axons and dendrites and the precise patterns of synapses between neurons. We explore this relationship by focusing on cell recognition molecules which allow developing processes of different axons and dendrites to discriminate between one another and protein complexes comprising different neurotransmitter receptor subunits and associated proteins at synapses within specific dendritic spatial domains. The specific aims of this project are: 1. Uncovering the molecular basis of synaptic specificity at GluClα synapses in the distal domain of T4 dendrites. These studies will focus on Mmd, a fly homolog of a mammalian synaptic adhesion molecule Adam22 and other GluClα-associated proteins; 2. Uncovering the molecular basis of synaptic specificity at nAChRα5-containing synapses in the central domain of T4 dendrites. These studies will focus on Side-VI protein, a synapse-specificity related protein, and other AChRα5-associated proteins; and 3. Uncovering the molecular basis of synaptic specificity at Rdl-containing synapses in the proximal domain of T4 dendrites. These studies will focus on the role of the Turtle (Tutl) protein, a fly homolog of mammalian Igsf9b, a synaptic adhesion protein selective for GABAergic synapses. It will also explore other proteins associated with Rdl. These studies will provide fundamental insights into the molecular logic and mechanisms regulating the formation of connections between neurons. As disruption of connectivity plays a central role in neurological and psychiatric disorders these studies provide a basis for the development of effective therapies in the future.

NSF Awards · FY 2025 · 2025-06

X-ray science has been a cornerstone of innovation since its discovery over 125 years ago, contributing to medical advancements, scientific research, and technology development. However, recent breakthroughs in quantum electrodynamics are opening a new era of possibilities for X-ray technology. This project aims to revolutionize X-ray science by developing new nanoscale photonics technologies. The Principal Investigator (PI)'s work holds the potential to bring about major leaps in the life sciences, energy sectors, and various other fields. These advancements could lead to new tools in quantum information science, ultrafast imaging, and spectroscopies that were once considered science fiction. This project is not only about advancing technological capabilities but also about promoting the overall progress of science in alignment with NSF’s mission. By integrating various fields such as quantum physics, laser technology, and accelerator science, the PI is setting the stage for novel applications that impact everything from medical imaging to quantum computing. Furthermore, their commitment to develop educational initiatives will foster a new pipeline of future scientists and engineers. In summary, this research endeavors to redefine how X-ray technology is utilized in various fields, while simultaneously addressing important educational and societal challenges. Nurturing talent from all segments of society and promoting interdisciplinary collaboration will ensure that the benefits of this research are widespread, enhancing national health, prosperity, and knowledge. Technical Abstract The PI will experimentally validate the production of X-rays via the quantum interference of electrons. This will be achieved by shaping electron wave packets from a true quantum electrodynamic (QED) perspective, enabling us to produce highly directional and monochromatic X-rays with energies reaching up to several tens of keV. The project aims to extend the PI's demonstration to generate attosecond-duration X-ray wave packets, thereby creating extremely bright X-ray pulses. This will be comparable in brightness to those of billion-dollar large-scale X-ray free electron laser (XFEL) facilities but from much more compact radiation sources. The methods and approaches are centered around the fusion of QED, laser technology, and advanced accelerator physics techniques. By harnessing the capabilities of QED, the PI aims to provide an ultracompact X-ray source, that reduces both cost and size and features a scalable architecture suitable for integration and portability. This will offer the possibility of achieving on-chip X-ray frequency combs. The anticipated contributions of this project include not only the foundational demonstration of novel electron-photon quantum interference but also potential applications in quantum information science. Such applications span from quantum-level semiconductor lithography and ultrafast microscopy to compact XFEL devices and atom-by-atom matter assembly. Overall, the execution of this project is expected to significantly advance the field of X-ray science and facilitate a new class of radiation sources with broad applicability. By aligning cutting-edge research with interdisciplinary collaboration and education initiatives, this project also sets the groundwork for nurturing the future STEM workforce, and enhancing the technological infrastructure to meet ongoing societal and scientific demands. 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 · 2025-06

Project Summary Impairments of attention are common across neurodevelopmental disorders (e.g., ADHD), and contribute to negative life outcomes such as in academic achievement. Critically, leading treatment strategies are ineffective at improving educational outcomes. Lacking is assessment of attention deficits in real-life contexts, where visuospatial attention circuitry is influenced by interactions with regulatory systems including arousal and motivation. As such, tracking of neuro-behavioral attention states in natural environments has been increasingly recognized as crucial to: (i) understanding the interaction between neural circuitry of attention and regulatory influences, and (ii) identifying pathways to improving behavioral outcomes. Several technical challenges in this effort exist, however, and include quantification and synchronization of objective measures of such interacting systems with neural indicators of attention, portability of such multi-modal assessment systems, and increasingly, protection of privacy, with video recordings a gold standard in the field. The objective of this R61/33 proposal is to address these challenges. We will (Aim 1) develop an integrated, portable sensor suite for concurrent recording of neural activity, physiological arousal, motor signals, and physical interactions in social environments. We will integrate our previously developed tracking of neural oscillatory features of visual attention with additional sensors (heart rate, motor, and novel LiDAR/millimeter wave sensing) to extract physiological and movement-derived features of arousal and motivation. Project milestones quantify our aims to (i) optimize synchronization & portability, while (ii) introducing privacy-preservation technology to eliminate reliance on video recordings, and (iii) achieve above-chance classification of system states, and overall attention state as expressed in behavior. Next, we will deploy this technology to explain and predict neuro-behavioral attention states during mock- classroom and real-classroom learning activities, while manipulating contextual variables such as degree of attention support (group vs individual work), motivation (rewarded activities) and arousal (testing context). We will test the hypotheses (Aim 2) that (i) a multi-dimensional profile of attention states will improve prediction of neural activity and behavioral attention states and delineate how visual attention circuitry and regulatory influences interact in natural contexts, while also (ii) accounting for individual variability in inattention by differentiating between causal pathways to inattention, and (iii) identifying individual learning contexts that optimize an individual’s attention. The result of the project will be a scalable, integrated, portable technology designed to improve the accuracy of determining sources of inattention on individual basis, thus allowing for more targeted treatments.

NIH Research Projects · FY 2025 · 2025-06

Summary For over 55 years, the UCLA IDDRC has been committed to improving the lives of individuals with intellectual and developmental disabilities (IDDs) through basic and translational research, education, and outreach. Our Center aims to provide outstanding resources and infrastructure to UCLA IDD researchers using the most innovative technologies with the goal of impacting the well-being of individuals with IDDs and their families. The IDDRC serves as the central hub for IDD research on a campus that is widely known for its outstanding neuroscience research environment. Our mission is to create an ideal environment that promotes world-class research in IDD by providing open access to cutting edge core facilities, administrative infrastructure, and by fostering close interactions among investigators from a variety of disciplines who are committed to translational research in intellectual and developmental disabilities. Activities of the IDDRC consist of providing key technical resources, a high level of administrative support and integration activities across the UCLA and national IDDRC communities. During the current award cycle, the IDDRC has supported high quality research through the 5 Cores and the Research Project. Critical changes in personnel have included a new Director, Harley Kornblum, and Associate Directors Suma Jacob and Peyman Golshani who will lead the IDDRC into the future. One purpose of this bridge funding is to maintain the key core functions of the IDDRC to support IDD research at UCLA and maintain a high standard of excellence. These cores are: Core A: Administration and Dissemination, Core B: Clinical Translation, Core C: Genetics genomics and Bioinformatics, Core D: Cells, Circuits, and Systems Analysis, and Core E: Functional Visualization. Each core plays a critical role and has demonstrated a high level of productivity and innovation during the current cycle. Taken together, the cores will support at least 99 projects during the coming year. A second purpose of the bridge funding is to provide support to complete a limited set of aims for our Research Project. This project focuses on one of the most clinically important yet poorly studied facets of IDD, disordered sleep. The project has made substantial progress in our originally proposed Aims in defining sleep disturbances in Rett and Dup 15q syndromes, investigating sleep phenotypes in animal models of these syndromes, and utilizing brain organoids to identify cellular and molecular changes that may underlie disordered sleep and other processes such as cognition. We request one year of bridge funding to complete clinical studies, analyze previously-collected overnight EEG in Rett patients, and to generate more compelling organoid models of Rett and Dup 15 syndrome. Bridge funding will allow us to maintain an integrated, vibrant and productive IDD research community at UCLA and springboard us into the future of IDD research, which will rely heavily on transdisciplinary studies to take on the enormous task of developing novel therapeutic strategies that directly address causes and symptoms of IDD.

NSF Awards · FY 2025 · 2025-06

With support from the Environmental Chemical Sciences (ECS) program in the Division of Chemistry, Professor Victoria Barber of the University of California, Los Angeles is investigating the gas-phase reaction pathways of peroxy radicals (RO2), the central intermediates formed in the oxidation of organic compounds in the Earth’s atmosphere. While some reaction pathways of RO2 are well understood, others—particularly isomerization and self- or cross-reactions—remain poorly characterized, despite their implications for secondary organic aerosol formation. Professor Barber and her students will use sophisticated, real time analytical techniques to examine how isomerizations and self- and cross- reactions of peroxy radicals work together to shape gas-phase product distributions and produce secondary organic aerosol. Their studies could result in improved understanding of the role of peroxy radical chemistry in determining atmospheric composition, tropospheric ozone production, and the formation of secondary organic aerosol, which would enable future improvements in 3D modeling of atmospheric composition and air quality. The proposed work will help cultivate the next generation of researchers in atmospheric chemistry at both the graduate and undergraduate level, and results from the work will be integrated into Professor Barber’s undergraduate environmental chemistry course. Gas-phase non-methane organic compounds are present in air in small concentrations, but exert outsized influence on atmospheric composition via oxidation chemistry. RO2 are central intermediates in oxidation, with four major reaction pathways: reaction with NO, reaction with HO2, isomerization, and self- or cross-reactions. While the first two pathways are well-characterized, isomerizations and self- or cross-reactions remain poorly understood, despite their implications for secondary organic aerosol (SOA) formation. This project will investigate the interactions between these pathways and their effects on product distributions and SOA formation using controlled environmental chamber experiments. Traditional oxidant-based chamber experiments struggle to isolate these pathways due to concurrent generation of NO and/or HO2. The proposed work circumvents this using alkyl iodide photolysis as a radical source, enabling precise control over RO2 concentrations and reactivity. Coupled to online chemical ionization mass spectrometry and scanning mobility particle sizing, this approach allows for systematic investigations of these reaction pathways, their interactions, and their role in aerosol formation. Specific project goals include examining how RO2 concentrations influence product distributions and SOA yields, assessing the impacts of low levels of NOx on oxidation outcomes, and systematically exploring the role of RO2 structure in modulating isomerization and self- or cross-reaction pathways. 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 · 2025-05

This I-Corps project is based on the translation from lab to market of low-cost passive radio frequency identification (RFID) tags. The tags track assets commonly used in firefighting such as hand tools or equipment within a few meters accuracy from a reader mounted on a mobile platform. During emergency situations such as wildfires, this technology tracks hundreds to thousands of individual items in a cost-effective way by using inexpensive, passive RFID tags. The commercialization of this solution has the potential to benefit the society by enabling better real-time situational awareness and better emergency response to more effectively. This I-Corps project utilizes experiential learning coupled with a first-hand investigation of the industry ecosystem to assess the translation potential of the technology. Passive radio frequency identification (RFID) tags are used to track individual items to within a couple of meters. This solution consists of novel machine learning algorithms used for identification that are capable of performing in a variety of forested environments. This solution is cost-effective and efficient, as RFID tags are inexpensive, do not require power, operate on the backscatter principle utilizing energy emitted by a nearby reader device, and do not require maintenance. The RFID tags provide a considerable advantage over conventional wireless technologies. The benefits of this approach include a reduction in the overall costs involved in tracking numerous assets and the development of a real-time situational awareness practical even during large fires. 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 The goal of the California NanoSystems Institute (CNSI) at the University of California at Los Angeles (UCLA) is to enable cutting-edge nanobiology and biomedical research. CNSI is home to the Molecular Screening Shared Resource (MSSR), which provides transformative high throughput screening (HTS) capabilities to the research community to facilitate discovery and development of new drugs, development of novel screening technologies, and training of the next generation of scientists. Since 2003, the services of the MSSR have been leveraged to obtain $268 million in grant funding. The first MSSR-originated small molecule, TRE- 515, is in phase II clinical trials for the treatment of solid cancers at UCLA and other large molecule drugs developed at MSSR are in cGMP production in preparation for clinical trials. The MSSR has been able to scale its services to meet increasing demand through the extension of its machine park. As part of the build-out of the machine park, MSSR is requesting the purchase of the CellXpress.AI automated cell culture system. The system will allow researchers throughout UCLA to scale cell culture in preparation for high throughput screening campaigns and meet the overwhelming demand for genome engineered cell lines and advanced cellular assay systems like organoids. Over 30 users have been identified across the fields of natural sciences, engineering, and biomedical science/medicine with active federal funding that will significantly benefit from the resulting engineered and advanced cell line models for drug discovery enabled by an automated cell culture instrument. The new instrument will also meet a critical need for improved rigor and repeatability as the transition of cell culture work to automated processes eliminates human associated variability and errors. The new system will also enable MSSR to push the envelope on the development of next generation assay systems including spheroids and organoids needed for the pre-clinical evaluation of its next drug candidates. Together with MSSRs existing high throughput screening infrastructure, small molecule, and functional genomics libraries, this instrument will provide a robust resource for faculty members who are eager to expand the scope of their current biomedical and biological research projects to include engineered cell line models and advanced 3D systems in their drug discovery and basic research efforts. The proposed instrument enjoys strong institutional support thus ensuring lasting impact while allowing MSSR to expand its drug discovery capabilities. High Throughput Screening methodologies have become an integral part of CNSI’s highly successful research resources that bring UCLA’s academic research discoveries to patients in the form of new drug treatments.