University Of California Los Angeles

NIH Research Projects · FY 2025 · 2024-08

: EMERGE: Early Markers of Expressive and Receptive (language) Growth in Emergent autistic toddlers The majority of 18-24-month-old autistic children have no words, demonstrating significant delays in their language development, a leading source of concern that often brings them to the attention of physicians or other professionals in community settings91,92. About half of these children continue to show significant language delay, speaking no words at 30-33 months2 and exhibiting delays in language greater than expected for their nonverbal cognitive age2. The period of development between 18-30 months is critical for language learning, coinciding with the period of time parents note differences in their children’s development93. We do not understand why some children begin to use words and others do not but speaking early (before 36 months) has long- lasting and cascading effects on development94,95. This may be especially true for children who are diagnosed later, and when diagnosed, often have lower cognitive/intellectual abilities8. Starting out with language delays can limit opportunities for children, tracking them into specialized settings that result in poorer outcomes overall. Understanding why language outcomes diverge over this critical language learning window, is essential to optimize the targets and timing of early, effective interventions. Therefore, a major gap in our knowledge concerns the measures and timing of when we can predict spoken language outcomes of young children with autism. To explore the vast heterogeneity in language outcomes, it will be necessary to deeply phenotype children using a range of concurrent neural and behavioral markers of spoken language and examine how these changes progress over time. This study will be the first to collect simultaneous social communication, language, sensory, motor development, and neural activity (via remote EEG) measures in the homes of families who have typically not been engaged in research studies, which we will do at three distinct times over the 18-30-month window of development. Participants include 132 18-month-old toddlers with autism who screen as having no words at study start. Our outcome will be the total number of novel words on a language sample. This study has the potential to dramatically improve our understanding of language growth among developmentally delayed autistic toddlers. It also addresses a high priority need of the Interagency Autism Coordinating Council and NIH, which includes a focus on minimally verbal, intellectually disabled children and community samples.

NIH Research Projects · FY 2025 · 2024-08

PROJECT SUMMARY: Significance: To date, no targeted therapies exist that prevent or improve the outcomes of patients with Acute Respiratory Distress Syndrome (ARDS). Despite an increasing awareness of hyperoxia (HO)-induced lung injury and low tidal volume mechanical ventilation (MVL) strategies, mortality rates have plateaued at 35-45% causing 75,000 deaths/year, and suggesting that we may have maximized the therapeutic potential of these standard interventions. Additionally, progress in this field is hindered by the technical difficulties in experimentally replicating the inflammatory environment at the alveolar-capillary interface with current ARDS models. Therefore, the identification of molecular targets, and the development of new therapeutic strategies and improved ARDS models represents a high priority topic with substantial impact in Pulmonary and Critical Care Medicine. In search for new therapeutic approaches, the Schwingshackl laboratory discovered epithelial TREK-1 K+ channels as key regulators of alveolar inflammation using simple, one-hit HO- and Influenza-A virus (IAV)- induced lung injury models. However, the importance and protective potential of TREK-1 K+ channels in clinically more relevant triple hit (IAV+HO+MVL) ARDS models remains unknown. To bridge these knowledge gaps and advance the field in a new direction, based on strong and exciting new preliminary data the authors now hypothesize that (i) ARDS decreases epithelial and endothelial TREK-1 levels, which causes cell membrane depolarization and subsequently promotes Ca2+-dependent alveolar inflammation, and (ii) this injurious cascade can be counteracted by activation of the subset of residual TREK-1 channels. Using IAV as the most common ARDS trigger worldwide (besides SARS-CoV-2), and clinically-relevant HO and MVL strategies, Aim 1 will investigate whether IAV, alone and combined with HO/MVL, decreases epithelial and endothelial TREK-1 levels, and thus accelerates further lung injury. Aim 2 will determine whether activation of the subset of residual TREK-1 channels can protect against IAV-induced ARDS. Aim 3 will establish the molecular signaling mechanisms and protein-protein interaction networks underlying TREK-1-mediated protection, by using high-throughput electrophysiological approaches and precision medicine Functional Enrichment Analysis tools, to ultimately facilitate rational drug design. For these studies, the authors will utilize novel and complementary pharmacological and genetic loss- and gain-of-function approaches, including newly- developed TREK-1 activating compounds (ML335, ML6733, BL1249), targeted cell type-specific TREK-1 overexpressing and TREK-1 KO mouse models, primary human alveolar epithelial/endothelial cells and lung tissue, and two next-generation experimental ARDS models (Bioreactor; modified microfluidic SynVivo platform). Potential for high Impact: (i) Establish aberrant TREK-1 signaling as an unrecognized pathway in ARDS; (ii) highlight TREK-1 activation as a novel therapeutic target for rational drug design; (iii) introduce two novel experimental ARDS models to study injurious events at the notoriously challenging alveolar-capillary interface.

NIH Research Projects · FY 2024 · 2024-08

PROJECT SUMMARY Family separations due to disasters, armed conflict, and migration affect millions, are expected to increase, and damage children’s health across the lifecourse. Given the extreme trauma of separations, reunifications should occur quickly in the child’s best interest, when safe to do so. Young, pre-verbal children are unlikely to be able to recount contact information of family members. DNA data can be powerful both for identification and for kinship verification of children separated from their families, as DNA can quickly, accurately, and inexpensively provide concrete evidence of genetic family ties. We propose to investigate strategies for (1) protection of children’s DNA data; and (2) consent for children at varying developmental stages to inform development of a U.S. family reunification DNA database strategy to serve as a scalable humanitarian “techquity” intervention to be activated when needed to reconnect separated children with their families. Our goal is to inform U.S.-relevant protocols, partnerships, and infrastructure for DNA-based family reunification responses that can be activated following separations, including after a mass separation event such as a natural disaster, while ensuring protections of children’s DNA data are in place. In the past, DNA data have been successfully used for disaster victim identification and for limited, scenario-based family reunifications of “disappeared” children abducted in war; however, no protocol exists for use of living children’s DNA to reunify families. We can learn from past contexts to develop strategies for securing sensitive samples and data from secondary misuse. We aim to define the scope of current and prior humanitarian use of children’s DNA data to analyze: (a) the contexts in which children’s DNA data are or have been used; (b) the role of DNA in each context; and (c) the extent to which DNA data advances or harms children’s interests. We will interview key informants to capture nuanced scenarios within each context to record factors related to risks and benefits of children’s DNA data use, and apply framework analyses to describe utilities and pitfalls of children’s DNA data use. We also will identify and interview key allies and experts with expertise on age-appropriate consent processes. Interview data will provide insight into principles of consenting children for DNA use for reunification across developmental stages. Finally, we will host a one-day virtual summit among allies and experts that will involve facilitated dialogue and visual mapping to identify and deliberate the contentious matters in consenting for children’s DNA use for reunification. Based on the summit discussions, we will formulate and visualize a set of informed consent principles for children’s DNA use for family reunification. Findings will have immediate impact for informing protocols and policy, and can prompt further research, including the immediate next step of conducting a modified-Delphi and implementation study to determine and test application of best practices for children’s DNA data use for family reunification. Achieving these aims will contribute to structuring an ethically sound DNA family reunification response that can be activated quickly when needed.

NIH Research Projects · FY 2025 · 2024-08

Ovarian cancer patients are burdened with a lack of effective therapeutic options resulting in a low survival rate due to chemotherapy resistance, recurrence, and metastasis. The overall goal of the proposed project is to establish innovative anti-cancer drug targets by mapping mechanical regulators of ovarian cancer progression. Cancer metastasis requires cells to deform and migrate through confined spaces. To survive, cancer cells must sense physical forces and adapt to maintain cellular and nuclear mechanical homeostasis. If we could map the mechanical regulators of cancer cells—molecules that control cell deformability and migration—this would enable us to define novel, complementary treatment strategies. To identify novel mechanical regulators, we developed a high throughput deformability screen that tested the effects of 1280 compounds (Library of Pharmacologically Active Compounds) on the deformability of human high-grade serous ovarian cancer (OVCAR5) cells. Our screen revealed drug compounds that reduced cell deformability. A meta-analysis across top drug hits revealed NUDT5 as a predicted regulator of cellular mechanical behaviors. NUDT5 is a member of the Nudix (nucleoside diphosphate linked moiety X) hydrolase superfamily. Our preliminary analyses revealed NUDT5 is highly expressed in various cancer types compared to normal tissue. My preliminary data shows that NUDT5 regulates cell stiffness, morphology, and migration in OVCAR5 cells. The goal of my project is to test the hypothesis that NUDT5 drives ovarian cancer progression by regulating cancer cell mechanical behaviors. In Aim 1, I will assess how NUDT5 relates to ovarian cancer progression by measuring NUDT5 expression and localization at different disease stages in distinct histological subtypes, including high-grade serous (HGSOC) and clear cell (OCCC) carcinoma tumors using patient tissue microarrays. I will also examine in vitro how NUDT5 regulates PARP inhibitor resistance and ovarian cancer cell behaviors, such as proliferation, migration, spheroid formation, and invasion. In Aim 2, I will determine the role of NUDT5 activity in catalyzing ATP production for actin cytoskeletal and nuclear remodeling following confined migration. Understanding how NUDT5 regulates cancer cell mechanical behaviors will guide future clinical treatment strategies to improve patient survival.

NIH Research Projects · FY 2026 · 2024-08

Project Summary/Abstract This proposal is an R24 research network application. The Social Science Genetic Association Consortium (SSGAC) is a research network that provides a platform for large-scale, interdisciplinary collaborations on genome-wide association studies (GWASs) of behavioral, social, and other aging-related phenotypes. Summary statistics produced by the SSGAC are widely used in medical, epidemiological, and social-science research for studying biosocial science, health disparities, and aging-related topics, and for integrated analyses with omics including genome-wide methylation, gene expression, and brain imaging. The overarching goal of this proposal is to create and disseminate resources for the genomics and omics of behavioral and social phenotypes. The Specific Aims are: • Conduct genome-wide association studies (GWAS) of a wide range of behavioral, social, and other aging-related phenotypes in unprecedentedly large samples, using the most up-to-date methods to maximize power, and broadly disseminate the resulting summary statistics and PGIs. In addition to (standard) population-based GWAS (i.e., in samples of unrelated individuals) in samples with genetic ancestries similar to those of the 1000 Genomes subsample EUR, we will also disseminate results from family-based GWAS (i.e., controlling for parental genotypes, either measured or imputed from other genotypes relatives) and diverse-ancestry GWAS. Diverse-ancestry GWAS may be particularly useful for studying, and ultimately mitigating, health disparities across genetic ancestries. • Produce and disseminate materials for non-technical audiences that address appropriate interpretation of genomics research on behavioral and social phenotypes and its social and ethical implications. Building on the SSGAC’s practice of accompanying every major paper with Frequently Asked Questions (FAQs), we will convene a Community Advisory Panel to get public input on important questions that may be missed by FAQs to date. We will write general FAQs about the field as a whole, which can then be referenced by subsequent, briefer, paper-specific FAQs. We will create paper-specific FAQs that address the new and major issues raised by family-based and diverse-ancestry GWAS and PGIs and their potential uses and misuses. • Develop new methods for analysis of summary statistics and PGIs, prepare user-friendly software manuals, and make the software tools publicly available on a GitHub repository featuring a Q&A forum. We will also host and advertise monthly online methods/software seminars, taught by the developers of new methods. We will emphasize new methods that integrate the analysis of genomic summary statistics with other omics data.

NSF Awards · FY 2024 · 2024-08

The National Science Foundation (NSF) Graduate Research Fellowship Program (GRFP) is a highly competitive, federal fellowship program. GRFP helps ensure the vitality and diversity of the scientific and engineering workforce of the United States. The program recognizes and supports outstanding graduate students who are pursuing research-based master's and doctoral degrees in science, technology, engineering, and mathematics (STEM) and in STEM education. The GRFP provides three years of financial support for the graduate education of individuals who have demonstrated their potential for significant research achievements in STEM and STEM education. This award supports the NSF Graduate Fellows pursuing graduate education at this GRFP institution. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NSF Awards · FY 2024 · 2024-08

In this project, high-precision rotation measurements of Europa, Ganymede, and Venus will be acquired and interpreted to make advances in icy shell geology, geophysics, and astrobiology. The technique is Earth-based radar speckle tracking, in which radio waves are emitted by large transmitters towards these Solar System bodies and the radar echoes are recorded with our largest radio telescopes. This project trains a graduate student in observational astronomy. It also develops a module (teacher resource and student worksheet) that engages students in grades 3–5 about planetary astronomy, recognized as a gateway into the STEM fields (Science, Technology, Engineering, and Mathematics). This activity is expected to awaken or nurture a passion for STEM in young kids and set a fraction of them on a course towards a career in STEM. The rotational response of planetary bodies to a variety of forcings provides fundamental insights into their interior structure and rheology, their dynamical and thermal evolution, and core-mantle or shell-ocean interactions. This investigation will test models of the origin of Europa’s surface features, whether its ice shell is decoupled from its interior, and determine the rheology and moment of inertia of the shell. For Ganymede and Venus, this project seeks to determine their interior structure and provide insights into their dynamical, thermal, and magnetic field evolutions. Previous results from the radar speckle tracking observations have been confirmed at the 1% level by spacecraft observations. Project objectives are: (1) To confirm and improve the first measurements of the spin axis orientations of Europa and Ganymede, yielding obliquities with 10% precision; (2) To measure or place upper bounds on the amplitude of longitude librations of Europa; (3) To measure the orientation of the spin axis of Venus with 2” precision, the spin precession rate, and the polar moment of inertia with 4% uncertainties. The project trains a graduate student in the techniques of observational astronomy – how to write proposals, operate a radio telescope, process radar signals, write manuscripts, and present at conferences – thus contributing to renewal of the 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.

NIH Research Projects · FY 2025 · 2024-08

PROJECT SUMMARY The human brain has an expanded cortex compared to its closest relatives, and this outer layer of the brain provides humans with complex functions including integration of sensory inputs, judgement, and conscious decision making. Each of these areas of the cortex contains unique cell types, density of cells across layers, transcriptional identities, and connectivity patterns that emerge during developmental timepoints. Importantly, virtually all neurodevelopmental and neuropsychiatric disorders develop with cortical area specific phenotypes, and often with specific laminar manifestations as well. The vulnerabilities to these disorders are established during these developmental timepoints. While the existence of early morphogenetic gradients is known to establish the poles of the cortical areas, and “inside-out” neurogenesis lays the foundations for the six layers of the cortical plate, open questions regarding the transcriptional regulators of these terminal fates remains partially unknown in the developing human brain. Recent efforts through the BRAIN Initiative and others have generated expansive single-cell characterizations of the developing human cortex, providing an opportunity to mine these datasets in order to identify novel regulators of these cell fate specification events. Additionally, previous work characterizing the developing human brain has generated an “atlas of arealization” that identifies the genes that are expressed in each cortical area across developmental time. This dataset serves as a hypothesis generating tool for the identification of specific mechanisms of cortical arealization. Cortical organoids are three-dimensional models of the developing human brain that enable genetic access to and mechanistic interrogation of the developing human brain. These models have revolutionized our ability to model and characterize human development and neurodevelopmental disease, but recent characterizations of the system have identified that these organoids are not cortical area specific, but can be used for the exploration of terminal specification factors. Understanding the detailed mechanisms of cortical arealization and laminar specification could enable not only more specific understanding of disease etiology, but could also improve organoid models for the study of normal development and disease. Thus, this proposal will evaluate the signals that drive cortical arealization and laminar identity using both a bioinformatic and CRISPR activation screen. Additional efforts will explore the timing and permanence of these specification factors via knockdown of candidate regulators; proof of the pipeline will be executed with the factors identified in our preliminary studies related to the specification of FEZF2 deep layer neurons. Together, these studies will establish mechanisms and models of arealization and laminar identity in the developing human brain.

NIH Research Projects · FY 2026 · 2024-08

Project summary Growing evidence suggests that adaptive value representations in the brain are critical to flexible decision making. Inflexible decisions are a hallmark of a range of neuropsychiatric disorders. Thus, understanding the typical neural substrates of value representation may provide critical insights into the patterns of disordered decisions that characterize pathological conditions. Convergent evidence over the past decades points to the orbitofrontal cortex (OFC) as a critical locus for value representation and adaptive decisions. Evidence for neural encoding of the value of choice options is abundant, but it is less well appreciated that such representations are also intertwined with spatial information the reflects the location where the outcomes in question will be delivered. The utility—if any—of these pervasive OFC spatial representations is unknown. This is at least partly due to the fact that most studies of OFC’s role in decision making involve subjects that make their choices with minimal, if any, movement. We hypothesize that OFC spatial representations are a neural substrate for spatial credit assignment, the process by which organisms learn to associate locations with the value of outcomes those locations predict. Drawing inspiration from decision problems that foraging animals face in natural settings, we developed two new behavioral tasks for rats that require spatial credit assignment. In the patch-leaving task rats shuttle between two foraging patches where food pellets are delivered at different rates. The longer rats remain in one foraging patch, the lower the rate of reward becomes. Switching between patches resets the reward rate to its maximal level, but incurs a time penalty in the form of delay, during which food is not available. Adaptive decision making requires rats to associate information about reward rate with each patch. In the value-map task, rats are trained to approach visual stimuli projected on to the floor of an open-field arena, and are reinforced probabilistically for successfully completing trials. Reward probability is determined by an uncued underlying probability map with localized regions where reward is more or less likely to be delivered. Choosing correctly on choice trials requires learning the underlying probability structure of the task, and attributing higher or lower value to locations in the arena with increased or decreased reward probability. Preliminary data demonstrate that rats successfully perform both of these tasks. Neural recordings in lateral OFC identified two classes of spatially-responsive neuron, one of which encodes space coarsely, over a large scale, and the other of which encodes space over a much finer scale exhibiting discrete firing fields at particular locations. We hypothesize that these spatial cells are recruited to represent value over large spatial scales (as required by the patch-leaving task) or finer spatial scales (as required by the value-map task). Combining electrophysiology, modelling, and chemogenetic manipulations, we will quantify spatial representations across the medial-lateral axis of OFC, assess how OFC spatial representations are modified by spatial value learning, and test the role of cortio-hippocampal interactions in these processes. This work will provide the first detailed characterization of the prevalence, form, and dynamics of medial and lateral OFC spatial responses, and take the first steps towards understanding their role in value-based decision making.

NSF Awards · FY 2024 · 2024-08

Quantum sensing presents a unique opportunity for early adoption of technology with a true quantum advantage in the market. The Quantum Sensing and Imaging Lab (Q-SAIL) develops high-performance quantum sensors for a variety of applications ranging from frequency metrology and fundamental physics to terahertz (THz) and hyperspectral imaging, based on two-dimensional arrays of trapped ions. Optical atomic clocks based on single trapped ions, for example, are the most accurate sensors of any type, with systematic uncertainties below one part in 10^{18}. This performance has the potential to revolutionize existing frequency metrology applications such as telecommunications and navigation, as well as enable new capabilities such as relativistic geodesy and searches for physics beyond the Standard Model. Q-SAIL’s sensors leverage entangled ion arrays to improve the bandwidth of optical frequency metrology by an order of magnitude or more beyond what is possible with classical sensors. THz imaging has applications in medicine and astronomy, but current sensors suffer from low quantum efficiency. Q-SAIL THz imaging sensors use molecular ions as pixels to achieve high quantum efficiency, and implement quantum compressed sensing algorithms with entangled arrays of molecules for highly sensitive spatial or spectral pattern recognition. Q-SAIL’s central quantum science technology demonstration (QSTD) is a 128-zone microfabricated surface-electrode ion trap array with integrated passive and active photonics for laser generation, control, and delivery. At each ion trap zone, a single logic ion qubit is trapped together with one or more sensor ion(s), which is a different atomic or molecular ion species for each sensing application, using quantum-logic spectroscopy (QLS). The sensor ions in different trap zones are entangled with each other via quantum gates with and between the logic ions, and can serve as individual pixels for imaging applications or combined using multi-ensemble clock protocols, quantum compressed sensing, quantum variational optimization, or quantum machine learning for precision sensing of scalar signals. The Q-SAIL user community is invited to contribute hardware modules, propose new sensing modalities, test new sensing algorithms, and use this flexible quantum platform to explore their own applications of interest. Additionally, quantum information science and technology (QIST) workforce education in general, and improving access and retention for underrepresented minority (URM) and female or non-binary students in particular, is a primary thrust of Q-SAIL. This project advances the objectives of Quantum Information Science and Engineering at NSF in response to the National Quantum Initiative Act for the continued leadership of the United States in QIS and its technology applications. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NIH Research Projects · FY 2024 · 2024-08

ABSTRACT Tobacco use is the leading cause of preventable death and disease in the United States. The majority of smokers report the desire to quit smoking; however only 3-5% of unaided quit attempts are successful; highlighting the need for TUD treatments. Currently, there are only three classes of FDA-approved pharmacotherapies for smoking cessation. While these medications have shown effectiveness in increasing abstinence during randomized clinical trials, the benefit of using such treatments decreases over the course of a year, and long-term quit rates rarely exceed 30%. Thus, innovations in treatment approaches are needed to reach further reductions in tobacco use. Δ9-Tetrahydrocannabivarin (Δ9-THCV) is a phytocannabinoid, which is thought to be a CB1 receptor antagonist and partial CB2 receptor agonist. Δ9-THCV has shown initial promise as a novel therapeutic for nicotine dependence and addictive disorders. Evidence from several animal models indicates that THCV reduces nicotine self-administration, reduces cue- and nicotine-induced relapse-like behavior, and improves nicotine withdrawal symptoms. The proposed study consists of a randomized, double- blind, counter-balanced, crossover human laboratory study of Δ9-Tetrahydrocannabivarin (Δ9-THCV) for daily smokers. A total of 32 daily smokers will complete two outpatient study visits after 5 days underΔ9-THCV and matched placebo, during which they will undergo a Smoking Lapse task to assess: (a) the ability to resist smoking, (b) cigarette smoking self-administration, (c) subjective craving, (d) withdrawal, and (e) subjective effects of nicotine. This study will test the initial efficacy of Δ9-THCV, which is essential for understanding the clinical potential of this naturally occurring cannabinoid as a treatment for smoking cessation. Given the wide prevalence cigarette use and the high acceptability of naturally-occurring products, such as cannabinoids, as therapeutic agents, the proposed study has the potential to be transformative in uncovering the therapeutic benefits of Δ9-THCV.

NIH Research Projects · FY 2024 · 2024-08

Project Summary/Abstract (30 lines max) The ability to leverage early biomarkers, clinical, and demographic data to accurately predict a patient’s likely recovery trajectory following moderate-to-severe traumatic brain injury (TBI) is paramount to allow definition of appropriate therapeutic strategies and to evaluate medical decision-making in the context of critical decisions such as early withdrawal of life supporting therapies. Prognostication of neurofunctional recovery following TBI, however, is known to be as critical as challenging. Extensive work has shown that current approaches suffer from high variability across physicians and medical centers, as well as a tendency for overestimation of poor outcomes and underestimation of positive outcomes, and to be affected by non-clinical factors such as geographic region and socioeconomic variation. To overcome such gaps in prognostication, this project is aimed at developing and assessing novel frameworks that can be employed in early post-injury care. Specifically, we leverage non-parametric models and machine learning techniques to fuse and incorporate routine multimodal and multiplex magnetic resonance imaging (MRI) signals into a prediction framework. In two aims, we address the ability of univariate multimodal fusion and machine learning architectures, respectively, to predict accurately functional outcome at six months post injury on the sole basis of acute data, and compare their performance to existing clinical algorithms. This project is thus aimed at developing a novel tools that can be easily deployed in the Intensive Care Unit to help guide medical decision-making in an evidence-based manner. If the development and assessment proposed in the present project is successful, the ultimate aim of this line of work is to develop this research into broadly accessible platform that can be used by practicing clinicians all over the world to supplement prognosis based solely on gross clinical indicators with quantitative and spatial multimodal MR data.

NIH Research Projects · FY 2026 · 2024-08

PROJECT SUMMARY / ABSTRACT There are various psychological, cognitive, behavioral, medication and neurostimulation treatments that can improve the outcomes of people with common depressive and anxiety disorders. However, in usual practice, there is large variability in provider characteristics and delivery of treatments. Routine treatments are often poorly characterized and structured clinical data on patients are scarce. The effectiveness and quality of routine mental health services in the community are not accurately monitored and are poorly understood. It will be necessary to implement monitoring of treatment quality so that treatment and outcomes can be improved. At present, healthcare organizations, payers, and policy makers usually know little about the quality of care they support. Similarly, patients and their families have very limited information on quality to guide their choice of provider or treatment organization. This study develops, tests and validates a new, transdiagnostic outcome-focused mental health quality measure. This measure is based on routine, regular patient reports of their symptoms. The measure can be aggregated at the provider, clinic, organization or plan level; inform choice of provider; and be used to improve routine delivery of services and health equity and reduce disparities among patients with common psychiatric disorders. The quality measure is broadly relevant across community settings and populations, and suitable for endorsement by regulatory and governing bodies. The study is guided by partnership with stakeholders and end-users of quality measurement. The project aims to: 1) analyze existing data with responses to a wide variety of items that are known to assess depression or anxiety, and empirically select symptom items for a transdiagnostic outcome-focused quality measure; 2) inform risk adjustment and benchmarking of the quality measure by studying the effects on outcomes of patient, provider, and practice factors, including social determinants of health, baseline symptom severity, and diagnoses; and, 3) fully specify an outcome-focused quality measure that includes risk adjustment and benchmarks for improvement; and study, at practices nationally, its feasibility and psychometric properties, the effect of treatment characteristics on the quality of care, and the effect of quality on health-related quality of life. The study leverages a unique existing database that contains more than 5 million symptom assessments from 500,000 patients collected during treatment episodes with more than 5,000 providers and 200 real- world practices. These patient-reported outcomes are supplemented with data on the characteristics of patients, providers and treatment organizations. Analyses use psychometric methods, item response theory, and hierarchical and longitudinal modeling to study symptom data from patients over time during episodes of care. Results support development of an outcomes-focused quality measure than can be used to routinely assess and improve the quality of mental health services.

NIH Research Projects · FY 2025 · 2024-08

Abstract/Summary The negative health outcomes associated with poor sleep health, including insufficient duration of sleep and chronic insomnia, have been well documented. These outcomes include an elevated risk for cognitive decline and Alzheimer’s disease. The combination of insomnia with short sleep duration may elevate the risk for cognitive impairments and Alzheimer’s disease even further, given the growing literature linking this particular insomnia phenotype with increased risk for cardiovascular disease and type 2 diabetes, both of which have been linked to cognitive decline risk. However, the direct connection between biological pathways disrupted in short sleep insomnia and Alzheimer’s disease is not well understood, and only limited experimental sleep deprivation research has tried to identify changes in Alzheimer’s disease biomarkers indicating neuronal degeneration. The current proposal seeks to address this gap in knowledge. With training from, and collaborations with several experts in sleep research, biostatistical, multi-omics, metabolomics analyses, and Alzheimer’s disease research, the applicant will gain the expertise needed to address these questions. By utilizing an interdisciplinary approach incorporating complex data analytics, the project aims to generate a broad range of independent research. The project has three main aims. In the first aim, we will use a multi-omics approach analyzing both methylation and metabolomics data and the associated with short sleep and insomnia, independently and interacting, among a high-risk Hispanic population. Then, we will compare the results from aim 1 to previously identified methylation and metabolomics biomarkers for Alzheimer’s disease to identify overlapping pathways. The second aim is to determine the direct relationship between partial sleep deprivation and the presence of metabolites and blood-based Alzheimer’s disease biomarkers. For this, we will use an experimental design, namely individuals undergoing a partial sleep deprivation experiment, and analyze changes among these biomarkers using advanced bioinformatic tools to identify underlying pathways. The final and third aim will integrate the results from the first aims and decipher the causal effect of short sleep and insomnia on Alzheimer’s disease and then identify the mediating effects of the biomarkers identified in the earlier projects. This study will be, by far, the largest study to date to utilize novel, innovative multi-omics, and bioinformatics approaches to study short sleep insomnia. Addressing a critical need, we will identify underlying biological pathways affected by insomnia and short sleep and characterize its connection to Alzheimer’s disease and related neurodegenerative processes. This research can critically inform future research on potential therapeutic targets, especially for a population with known health disparities.

NSF Awards · FY 2024 · 2024-08

With the support of the Macromolecular, Supramolecular and Nanochemistry Program in the Division of Chemistry, Prof. Heather Maynard of the University of California, Los Angeles will use gold to make materials found in nature better. Prof. Maynard proposes that chemicals containing gold can be used to modify proteins with plastics. Proteins are not only found in food, but are also interesting materials, and some can even be used as medicines or to produce chemicals that are useful for society. By modifying proteins with plastics, they will last longer and may be able to function better. Prof. Maynard’s research group will study the gold compounds to make ones that will modify proteins in a specific way with a range of different plastics, in order to make the proteins better. This project will help students at UCLA learn the techniques necessary to later obtain jobs that benefit the United States. In addition, Prof. Maynard will teach the importance of proteins and plastics to Brownie and Girl Scouts in Los Angeles area. Furthermore, K-12 teachers in Los Angeles will be given tools to be able to teach gold chemistry to their students. Gold(III) complexes will be employed for the cysteine arylation of proteins with polymers. By utilizing a combination of theory and experiment, protein conjugates with complex polymer architectures will be achieved, the kinetics of the reaction will be understood, and that expansion of the synthesis from carbon-sulfur to other bond formations will be possible. This research will develop new, highly efficient syntheses to prepare advanced protein-polymer conjugates and polymeric materials. Other efforts will include outreach to girls in Los Angeles Brownie and Girl Scout Troops. This will reach a diverse population of girls at the critical age where role models in science are needed. Furthermore, the impact of the research project will be augmented by introducing a new module on bioconjugation in UCLA’s Nanoscience Teacher Workshops. This will allow teachers to disseminate bioconjugation knowledge to K-12 students in the greater Los Angeles Area. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NSF Awards · FY 2024 · 2024-08

Since the advent of human civilization, science has played a pivotal role in addressing societal challenges and provided us with the necessary knowledge, tools, and methodologies to drive progress. However, the process of scientific understanding and discovery can itself be quite slow as it requires meticulous observation and analysis of complex natural phenomena. This can be discouraging as we grapple with pressing sustainability challenges in areas such as climate and energy security that demand a swift response. This project will develop generative artificial intelligence (AI) frameworks to aid scientific reasoning by efficiently analyzing vast streams of scientific data to identify patterns, simulate natural phenomena, and suggest experiments. The resulting algorithms will be grounded in real-world applications aimed at accelerating sustainable development. The project will be complemented by educational and outreach activities aimed at diverse interdisciplinary audiences. The central goal of this project is to develop generative AI systems for scientific workloads that can learn with inexpensive supervision and exhibit strong generalization and reliability across broad domains, akin to foundation models for language and vision. To achieve this goal, the project will encompass innovations in data engineering, large-scale pretraining, and finetuning techniques to enhance reliability. On the data and modeling side, this research will lead to new generative architectures and objectives to fuse heterogeneous multi-modal and multi-scale datasets for scalable training of scientific foundation models. The project will further develop methodologies to efficiently finetune these models to novel scenarios using in-context learning, permit online updates with new experimental evidence, and align inference with relevant domain knowledge. In addition to fundamental advances, the project will be grounded in key scientific tasks spanning simulation, forecasting, and experimental design for climate and energy domains. Educational and outreach efforts will include the development of interdisciplinary courses, open-source software and interactive tutorials, as well as seminars and workshops in AI for Science targeting diverse groups of students, researchers, and practitioners. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NIH Research Projects · FY 2025 · 2024-08

PROJECT SUMMARY (See instructions): Autism comprises a class of developmental disorders characterized by significant social, communication, and behavioral challenges. Autism is thought to result from neural cell type imbalance during early development, partly from the discovery of chromatin regulators as genes linked with autism. Yet, the cellular, molecular, behavioral, and developmental mechanisms of these autism-linked genes are not well known. This is underscored by the wide variation in type and severity of symptoms. Systematic dissection of the roles of candidate histone modifier autism-linked genes is therefore fundamental to understanding how mutations in these genes leads to cell type imbalances and altered behaviors, affecting physiological well-being. We have taken advantage of the fast-developing vertebrate system zebrafish, in which histone modifier genes are highly conserved, to identify behavioral and developmental phenotypes in mutants of candidate autism-linked genes. By screening for behavioral phenotypes in zebrafish morphants, we have prioritized 7 zebrafish lysine methyltransferase genes (corresponding to 5 human genes) for further study: kmt2a, kmt2ca/b, kmt2e, setd1 a, and setd1 b. Despite their overlapping functions as H3K4 lysine methyltransferases, mutations in these genes led to different behavioral phenotypes in morphants. The full developmental and behavioral phenotypes, the cell types and circuits/pathways, and gene regulatory functions that are affected in these mutants, remain unknown. The proposed study will combine behavioral and developmental assays, pharmacological profiling, brain activity assays, and single-cell transcriptomic and chromatin accessibility profiling to directly test the hypothesis that these genes function to specify cell types required for cell type and circuit development and, ultimately, behavioral responses during development. Altogether, findings from this study will uncover unique functional roles and mechanisms for conserved candidate histone modifier autism-linked genes during early development.

NIH Research Projects · FY 2026 · 2024-08

ABSTRACT Our long-term objective is to define cellular pathways that regulate cellular cholesterol flux and to elucidate their impact on metabolism and pathology. Most of the free cholesterol in mammalian cells resides in the plasma membrane (PM). We previously showed that the Aster family of nonvesicular lipid transporters are critical for the movement of cholesterol from the PM to the ER in most if not all mammalian cells. Asters are ER-anchored proteins that bind cholesterol and facilitate the formation of ER-PM contacts in response to elevated accessible PM cholesterol levels. Although they are required for efficient PM to ER transport, Asters almost certainly do not act alone. Other factors are very likely to be involved in the spatial organization of accessible PM cholesterol, the formation and stabilization of PM-ER contacts, the movement of Aster proteins from ER to PM, and the channeling of PM cholesterol to specific regions of the ER for SREBP regulation or esterification by ACAT. The identity of such factors is currently unknown. A complete understanding of how cellular cholesterol is transported in vascular cells through nonvesicular pathways will fill important knowledge gaps and may uncover new opportunities for therapeutic intervention in cholesterol movement in the setting of cardiovascular disease. Specific Aim 1 will identify new players in nonvesicular lipid transport. We have devised proximity labeling strategies to identify proteins that localize with Asters to ER-PM contacts in a cholesterol-dependent manner. Specific Aim 2 will define the physiological functions of Aster interactors in cellular and systemic lipid transport. We will validate the functional importance of Snap23 and other factors for lipid metabolism and inflammation in cell culture and animal models. Specific Aim 3 will elucidate the mechanisms and physiological consequences of Aster phosphorylation. We have discovered that Aster-A is phosphorylated in response to cholesterol loading or LPS stimulation. Dissecting the molecular mechanisms that control PM cholesterol levels in cells, and thereby impact lipid metabolism and inflammation, is central to understanding cell physiology and is expected to provide insight into the etiology and future therapy of metabolic disease.

NIH Research Projects · FY 2025 · 2024-08

ABSTRACT The developing brain becomes active before it is ready to receive sensory input. Such stimulus-independent developmental activity was originally described and characterized in the visual system over three thirty years ago. Since then, the phenomenon has been observed and studied in many additional areas of the brain, including other sensory systems as well as in the thalamus and cortex. Where tested, altering developmental activity leads to disorganization of neuronal connections. While its role in instructing wiring fidelity has received significant attention, two important questions about developmental activity remain largely unaddressed: First, is the activity is coordinated across disparate brain regions? And, secondly, what is the significance of developmental activity to shaping behavior, and more specifically, how does it contribute to the maturation of a healthy nervous system? Understanding brain development is a significant scientific challenge with direct relevance to human health. Studies into the causes of neurodevelopmental disorders rightly cast a wide net, covering progressive stages of neural development from proliferation to morphogenesis to synaptogenesis. Notably, developmental activity— as an evolutionarily conserved process—remains a blind spot, mostly due to the challenges of working with the mammalian model: both in utero development and the daunting size and complexity, make the requisite exploratory studies prohibitively costly. The fruit fly brain also has developmental activity comparable to that seen in mammals. Patterned, Stimulus- Independent Neural Activity (PSINA, ‘see-nah’) engages the whole brain in highly structured and stereotyped activity, providing neurons their first opportunity to communicate across previously inaccessible spatiotemporal scales. The fly, with its approachably complex brain and an ever-expanding molecular-genetic toolkit, is at the forefront of cellular, systems, and behavioral neuroscience research. The discovery of PSINA introduced this powerful fly model to complement mammalian studies into developmental activity. Recently, our lab reported that a population of ~2,000 neurons, genetically defined by their expression of the cation channel Trpγ, is critical to coordinating PSINA across the brain. We know that a much smaller subset of this population is directly involved in PSINA. In my first Aim, I will use a recently developed molecular-genetic approach to functionally fractionate Trpγ+ population down to individual cells. In the process, I will learn how the circuitry of PSINA is organized to produce its distinct spatiotemporal structure. Further insights into the biology of PSINA will come from my second Aim, where I will ask how a neuropeptide signaling pathway acts through specific neurons to shape the activity. With the successful completion of this project, we will gain the experimental control to explore how critical brain functions, from sensory processing to sleep and learning-and-memory, are shaped by developmental activity. I expect that the discovery science I carry out in fly will motivate studies in the mammalian system to address the relevance of developmental activity to the assembly of a healthy brain.

NSF Awards · FY 2024 · 2024-08

This project aims to transform the field of protein engineering by developing an innovative technology called PicoShells. PicoShells are tiny, hollow particles that can hold and test large numbers of proteins quickly and efficiently. With PicoShells, scientists can screen up to one million different protein variations in just one day to find useful proteins for research, industrial or medical applications. This rate of screening improves substantially over current methods, which makes it easier to look through many new proteins to identify ones with useful functions. This project is important because it helps solve key problems in protein research, such as finding the proteins best suited to particular functions, such as sensing glucose concentration in the body and reporting it, which can help diabetic patients avoid low or high glucose levels in the blood that cause health problems. By making this process of protein identification faster and more effective, PicoShells can lead to new discoveries in medicine, energy, and environmental science. Additionally, this project supports education by involving students in research and creating teaching materials for schools to learn about concepts like concentration, polymers, and phase separation. Overall, the development of PicoShells will benefit society by speeding up scientific advancements and helping train the next generation of scientists. This research focuses on advancing protein engineering through the development of PicoShells, which are hollow, porous microparticles made of functionalized polyethylene glycol (PEG). PicoShells can encapsulate various cell types, including bacteria, yeast, microalgae, and mammalian cells, while keeping them viable or allowing for protein retention and testing for activity and properties after cell lysis. The project has two main objectives: first, to develop methods for retaining antibodies and enzymes within PicoShells to expand their use beyond their current application as fluorescent protein sensors; second, to create a comprehensive workflow for the directed evolution of proteins, specifically targeting high-performing variants of a fluorescent calcium biosensor and glucose biosensor. PicoShells can enable the rapid screening of proteins under multiple environmental conditions and analyte concentrations using fluorescence-activated cell sorting (FACS), significantly enhancing the scale and efficiency of directed evolution and protein engineering. The project's outcomes will provide the research community with a transformative tool for protein design and development, accelerating discoveries and innovations in biological research and creating data sets important for developing machine learning models to design proteins with specific functions. Results of the project will be available at www.biomicrofluidics.com. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NIH Research Projects · FY 2026 · 2024-08

ABSTRACT Sensory hypersensitivity and the resulting avoidance behaviors represent a major challenge for most individuals with Fragile X syndrome (FXS) and for many autistic people. Differences in sensory processing can also contribute to inattention/distraction, learning disability, repetitive behaviors, and even social avoidance. Indeed, exaggerated responses to tactile stimuli could also worsen anxiety about social interactions, especially if they involve physical contact (e.g., shaking hands, hugging, kissing) and if the contact is unwanted. For this proposal we will explore this relationship between sensory hypersensitivity and social experience in FXS/autism. Social touch per se has not been investigated in animal models of autism, including FXS; therefore, it is presently unknown whether they display unique avoidance behaviors or aversive facial expressions to different types of social touch. It is also not known how such maladaptive behaviors to social touch might be represented in neural dynamics of relevant brain areas. To address these knowledge gaps, we have developed a novel assay for social touch in mice. We previously demonstrated that Fmr1-/- mice, the main model of FXS, show avoidance and defensive behaviors to repetitive whisker stimulation, akin to tactile defensiveness in humans with FXS. In more recent studies we have shown that Fmr1-/- mice and maternal immune activation (MIA) model mice both show strikingly similar behavioral phenotypes in response to repeated bouts of social touch, including hyperarousal, running avoidance, and sustained eye closure. Here, we will follow a symptom-to-circuit strategy to better understand social touch deficits in FXS/autism. First, we will characterize behavioral responses to social touch in Fmr1-/- and MIA mice with our novel behavioral assay we have developed. Second, we will `reverse- engineer' such phenotypes by identifying the underlying circuit and neuronal changes using in vivo electrophysiological recordings with Neuropixels probes. Finally, we will intervene at the level of neuronal activity in the relevant circuits (focusing on somatosensory cortex and amygdala) with pharmacology and chemogenetics, to mitigate deficits in social touch. Our hope is that these preclinical studies will yield significant insights for the treatment of FXS/autism.

NSF Awards · FY 2024 · 2024-08

Non-Technical Abstract This project investigates network-forming suspensions of ferromagnetic colloids. It offers insights and strategies for designing, programming, and controlling both the microstructure and the macroscopic magnetic and mechanical functionalities of these systems. Technological potential broader impacts of this work include bioelectronic devices, benefiting areas of health care and liquid robotics. It also provides rich and novel colloidal physics and may provide a novel perspective on equilibrium gelation. Technical Abstract Network-forming suspensions of ferromagnetic colloids, which are coined "permanent fluidic magnets" (PFM), are distinct from well-studied ferrofluids due to the use of larger particles and highly viscous solvents, which suppress Brownian motion and sedimentation. Following application of an external magnetic field, the particles assemble into an anisotropic network structure (i.e., an anisotropic gel), and the material acquires a remnant magnetization. Specifically, this EAGER proposal aims to test experimentally, with theoretical comparisons, the question of whether the anisotropic networks are equilibrium states or rather arrested or jammed ones. These experiments would be complemented by both simulations and theory. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NSF Awards · FY 2024 · 2024-08

Cell division is a dynamic set of events that copies and transmits genetic material from one mother cell to two daughter cells. Protein phosphorylation, the modification of proteins by the addition of a phosphate group, is critical to the fidelity of cell division. However, the enzymes that carry out phosphorylation and the proteins that are modified by phosphorylation during cell division are still not well understood. This project will advance this understanding by identifying new enzymes that carry out phosphorylation and the substrate proteins that they modify to ensure proper cell division. This project will have a broader impact on society by providing educational, mentoring, research training, and career development opportunities to a large number of diverse high school, undergraduate, and graduate students that will prepare them for molecular and cellular bioscience careers. Through this training, students will acquire rigorous experimental design skills, statistical skills for data analysis, computational skills, analytical and critical thinking skills, and science communication skills. All research results and computational software will be disseminated broadly through publicly accessible publications, research presentations, and databases. The fidelity of cell division relies heavily on phosphorylation, which can act as a molecular switch to affect protein activity, protein-protein interactions, protein localization, and protein abundance. Current knowledge of the phospho-circuitry of cell division is limited by the small number of kinase-phosphosite pairs that have been validated and shown to be important for cell division. This project will integrate computational, biochemical, mass proteomic, and cell biological approaches to address this knowledge gap. The investigators will take proximity-labeling proteomic approaches to identify phosphoproteins that associate with poorly characterized mitotic kinases, which will elucidate high-confidence kinase-phosphosite pairs. They will take computational approaches to scan curated phosphoproteome databases and mitosis-specific phosphoproteomic datasets with the atlas of kinase consensus motifs to define mitosis-relevant kinase-phosphosite pairs. Identified kinase-phosphosite pairs and their importance to cell division will then be evaluated via in vitro kinase reactions and in-cell multiparametric phenotypic analyses. This project will produce large phospho-proteomic data sets and will develop novel computational pipelines that will be made freely available to the scientific community. Together, these interdisciplinary approaches will advance our understanding of the phospho-circuitry that coordinates cell division. This award is funded by the Cellular Dynamics and Function Cluster of the Division of Molecular and Cellular Biosciences in the Directorate for Biological Sciences. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NIH Research Projects · FY 2025 · 2024-08

ABSTRACT The remarkable effectiveness of the COVID-19 mRNA vaccines heralds a transformative immunization platform against viral infections. A key innovation—recognized with the 2023 Nobel Prize—is the replacement of uridine (U) with N1-methylpseudouridine (m1Ψ) in their mRNA constructs. This substitution reduces side effects and increases antigen production. However, applying m1Ψ-modified mRNA vaccines to the realm of cancer immunotherapy introduces a host of new and complex challenges. These range from understanding the implications of U-to-m1Ψ substitution on anti-tumor CD8+ T cell responses to devising effective priming and boosting strategies, creating more predictive animal models, and surmounting the immunosuppressive elements within the tumor microenvironment (TME). To address these challenges, this proposal outlines a research framework built around mechanistic studies with the goal of generating new mRNA vaccines for pancreatic ductal adenocarcinoma (PDAC)—a cancer with urgent unmet therapeutic needs. Specific Aim 1 seeks to engineer a new class of mRNA vaccines targeting clinically relevant tumor antigens, mesothelin (MSLN), and mutant KRAS (KRASG12D). SubAim 1.1 consists of mechanistic studies to inform strategies for optimizing mRNA-encoded antigen and adjuvant properties and devising effective priming and boosting approaches to enhance immunogenicity and reduce reactogenicity. SubAim 1.2 uses stringent PDAC models to evaluate whether the new vaccines significantly improve the efficacy of T cell transfer therapies. Specific Aim 2 evaluates the new mRNA vaccines in humanized immune system mouse models. Due to significant interspecies differences in innate immune responses to mRNA vaccines, it is vital to move beyond traditional mouse models. SubAim 2.1 aims to understand the effects of these vaccines on human conventional type 1 dendritic cells and subsequent CD8+ T cell activation. SubAim 2.2 focuses on validating the vaccines' safety and efficacy in humanized mouse models engrafted with human PDAC tumors. Specific Aim 3 assesses the potential for allele-specific KRAS inhibitors to reprogram the immunosuppressive PDAC TME, thus enhancing mRNA vaccine efficacy. SubAim 3.1 will investigate whether the new mRNA platform prevents tumor recurrence in PDAC mouse models treated with allele-specific KRAS inhibitors. SubAim 3.2 seeks to elucidate how combining mRNA-based immunotherapies with KRAS-targeted therapies impacts the immunogenicity of PDAC cells, the composition of the immune TME, and anti-tumor efficacy. Deliverables range from developing and optimizing new mRNA vaccines to a systematic mechanistic evaluation of these vaccines in both conventional and humanized mouse models, and finally, to investigating synergies with clinical-stage mutant KRAS-targeted therapies. The anticipated impact consists of advancing the understanding of how new mRNA-based immunotherapies enable priming and sustaining the cancer- immunity cycle and developing effective combination therapies against PDAC for future clinical translation.

NIH Research Projects · FY 2025 · 2024-08

The Ras family of proteins contain four major isoforms, and altogether these proteins are constitutively activated in a third of cancers. In the past decade, inhibitors to mutant Ras (RasG12C) have been developed, but most patients administered RasG12C inhibitors (RasG12Ci) relapse. Interestingly, these Ras inhibitor resistant tumors have Ras signaling reactivated and the signaling mechanisms underlying this drug resistance are unknown. To uncover these drug resistance mechanisms, I developed Ras activity sensors and Ras activity dependent proximity labelers, applied them to RasG12C-addicted cancer cells treated with RasG12Ci, and observed that RasG12Ci blocked mutant Ras signaling at the plasma membrane while wildtype (WT) Ras is activated at endomembranes to fuel oncogenic signaling and cell growth. While these results are preliminary as these studies were done in 2D cell culture and do not delineate which particular Ras isoforms enable RasG12Ci resistance, these exciting findings beg the question of whether cancer cells can evade other recently developed Ras inhibitors targeting RasG12C, G12D, G12R, or G12S by also reactivating Ras signaling. Therefore, the objective of this K99/R00 proposal is to expand the molecular toolkit for Ras and utilize these tools to profile and uncover the molecular mechanisms driving Ras inhibitor resistance. The central hypothesis driving this work is that WT Ras compensation for mutant Ras inhibition is a general feature cancer cells employ to evade Ras inhibitors. Profiling the subcellular Ras activities during Ras inhibitor treatment and uncovering the molecular components driving this reorganization of Ras signaling will allow better understanding of Ras inhibitor resistance and illumination of new therapeutic targets. To investigate this hypothesis, the following specific aims will be addressed: (1) Developing and applying Ras sensors in complex cancer cell models (K99); (2) De novo design of Ras isoform selective tools (K99/R00); and (3) Profiling and dissecting the mechanisms underpinning Ras inhibitor resistance (R00). In the proposed research, I will protein engineer current and new Ras tools (sensors, proximity labelers, perturbators) along with microscopy and proteomic techniques to determine how Ras inhibitors impact compartmentalized Ras signaling. The expected outcomes are (1) an expansion of tools that can be applied to in vivo models and probe specific Ras isoforms and (2) a better understanding of how Ras inhibitors operate and how drug resistance can occur. Of note, I believe these new Ras tools will be of great interest to the cancer community (e.g. NCI’s Ras initiative) and can be useful for other applications beyond the scope of this proposal such as diagnostics and therapeutics. Towards completion of the proposed work, I will be trained in protein design methods and complex cancer models and guided by an advisory committee composed of experts in cancer, Ras signaling, and cell culture. The long-term goal of this project is to develop an independent research program that bridges protein design with cancer cell biology to understand how oncogenic signaling pathways rewire themselves during oncogenesis and drug resistance.