University Of Chicago

NIH Research Projects · FY 2025 · 2024-08

Project Summary In cardiovascular disease diagnosis, treatment, and monitoring, a plethora of deformable biointerface devices are utilized. These devices are adept at gauging physiological metrics, administering bioelectrical modulation, or dispensing therapeutics. Notwithstanding the advent of preclinical biotechnologies like optogenetics and cell-based biological pacing, non-genetic electronic pacing persists as the predominant therapeutic approach for cardiac rhythm anomalies. Recently, semiconductors have been identified as promising instruments for non-genetic cardiovascular investigations. Our team is focusing on designing minimally invasive photostimulation tools specifically tailored for cardiac pacing applications. We recently published several photoelectrochemical methods for optically modulating cardiac activity in cultured cells and adult rodent models ex vivo. Using these methods, we can achieve light-activated modulation of cardiac tissue with a light intensity comparable to that used in optogenetics. In this current work, Tian, Hibino, Jia and Aziz will work together to expand and strengthen our newest photostimulation system, porosity-based silicon heterojunctions, for multi-site, leadless, nongenetic, and optoelectronic modulation of cardiac tissues. Specifically, our team aims to design, fabricate, and evaluate a range of porosity-based heterojunctions tailored for optical modulation of cardiac tissues. We will synthesize silicon membranes with non- porous/nanoporous heterojunctions and three-dimensional surface topographies. To enhance the stability of these heterojunctions and modulate their longevity under physiological conditions, we will employ atomic layer deposition to passivate the silicon interfaces. We plan to modify the surface with metal or metal-oxide catalysts to bolster signal transduction. To support the silicon heterojunctions, we will integrate soft matrices, including polymers and hydrogels, enhancing both biocompatibility and signal transduction at biointerfaces. Concurrently, we will produce biocompatible, stretchable optical fibers tailored for in vivo photostimulation. Our team is also developing a catheter-analogous minimally invasive photostimulation tool. For multi-site optical pacing, we will engineer and assess the requisite software, mechanical, electrical, and optical subsystems. We will validate the performance metrics of our random access photostimulation tools, including accuracy, scanning velocity, and power delivery, followed by ex vivo photostimulation trials. In vivo biocompatibility assessments will be conducted in a rat model, while we will gauge heart pacing efficacy in acute and chronic scenarios using single-chamber, dual-chamber, and multi-site stimulations in a pig model. We will test our hypothesis that deformable and biocompatible heterojunction devices can be used for multi-site cardiac resynchronization therapy. The new designs for semiconductor-based biointerfaces will allow for minimally-invasive, wireless, nongenetic, multiscale, and random access photostimulation.

NSF Awards · FY 2024 · 2024-08

Increasing data sizes, greater hardware specialization, faster networks, and larger collaborative teams result in modern research employing ever-more distributed cyberinfrastructure (CI). It is now commonplace for data to be produced in multiple locations (e.g., in research laboratories or on supercomputers), analyzed in others (e.g., local, campus, or national CI), and shared, published, or archived in yet others. This increasingly distributed CI is enabling exciting discoveries in many domains, but also leads to difficulties for researchers who must manage, discover, and act upon large volumes of distributed data. Growing amounts of valuable research time is spent on mundane but necessary data management tasks; crucial data are lost; important provenance information cannot be determined; and analyses are repeated. To tackle these problems, this project will build Globus Search, a new capability integrated into the widely used Globus platform, that will enable the creation of, and search within and across, distributed Globus collections. By thus allowing researchers to easily discover data regardless of location, group data into “virtual” collections, and act on virtual collections irrespective of where individual files reside, Globus Search will allow even the largest and most distributed teams to organize, navigate, and operate on their data. Globus has emerged as an essential tool for alleviating the numerous frictions associated with managing, accessing, moving, and sharing data within and across the many distinct data collections that constitute the modern CI experience. However, an implicit assumption has always been that researchers know where data reside: an assumption that becomes increasingly untenable as data and CI grow in complexity. This project will implement a suite of new capabilities including methods to crawl parallel and distributed storage systems; capture events (e.g., file creation, modification, deletion) from these storage systems; extract metadata from within diverse scientific file formats; communicate events securely and reliably to the cloud-hosted service; index files and metadata in a secure and accessible manner; and develop new interfaces for navigating distributed data collections, creating virtual collections, and acting on these virtual collections. Leveraging the hybrid cloud/local service deployment approach that has proven so successful for other Globus services, Globus Search will build on powerful, scalable, and robust cloud-hosted search services to deliver a rich search experience to users via the Globus web app, command line interface, and Python and Javascript libraries. 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

This award will fund a research project to improve the methodology for testing coefficients in linear regressions. Linear regression has been the workhorse of empirical research in economics but existing methods of making inference about estimates cannot produce results that are appropriate without making restrictive assumptions about the distribution of error terms in small samples or relying on infinitely large sample properties. This research will develop new test methods that are appropriate without regard to assumptions about the distribution of the underlying error terms or sample size. The new approach will allow researchers to construct test statistics that are valid under weaker assumptions than current methods. These methods will be useful for the analyses of observational data as well as guide the design of experiments. The results of this research project will lead to more precise coefficient estimates, hence improve decision making, increase economic growth, and improve the living standards of many citizens. This award will fund a research project that will develop a complete small sample and asymptotic theory for randomization-based inference for linear regressions. This estimator is not only asymptotically robust to heteroskedasticity but also to serial dependence, making it an omnibus procedure with small-sample guarantees. The conceptual aspect of the research will frame the randomization inference, which is tailored to observational data and Fisher tests and experimental data in the same framework to better understand the connections between the two. The research results will show that randomization inference has a natural interpretation as a robust alternative to Fisher tests, which in turn suggests important methodological developments. The results of this research project will lead to more precise coefficient estimates, improve decision making, increase economic growth, and improve the living standards of many citizens. 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 · 2024-07

PROJECT SUMMARY Vibrations from sound and mechanical stimuli from head movements are transformed into electrochemical signals for brain processing by inner-ear hair-cell mechanoreceptors mediating our senses of hearing and balance. Essential to hair-cell function are the proteins that form its mechanotransduction apparatus comprised of a fine tip-link filament that pulls on an ion channel complex to trigger sensory perception. The tip-link filament is formed by cadherin-23 (CDH23) and protocadherin-15 (PCDH15) proteins while the ion channel complex is thought to be formed by members of the transmembrane channel-like protein family TMC1 and TMC2, the transmembrane inner ear protein TMIE, and the tetraspan membrane protein of hair-cell stereocilia TMHS (also known as LHFPL5). In addition, the calcium and integrin binding protein CIB2 binds to TMC channels to regulate mechanotransduction. All these proteins are important for hearing and balance and are involved in inherited deafness, yet their molecular structures and the functional architecture of the transduction complex they form are poorly understood. The overall long-term goal of this project is to reveal the structural determinants of function for the proteins forming the inner-ear tip link and transduction ion channel complex. In Aim 1, we will use cryo-electron microscopy, high-speed atomic force microscopy, and molecular dynamics simulations to study the full-length extracellular domains of CDH23 and PCDH15 and thereby establish the structural determinants of tip-link function in inner ear mechanotransduction. In Aim 2, we will generate testable predictions using microsecond-long molecular dynamics simulations with biasing membrane potentials to characterize permeation of ions and ototoxic aminoglycosides through experimentally validated structural models of TMC protein pores. In Aim 3, we will use various computational and biophysical techniques, including nuclear magnetic resonance and native mass spectrometry, to explore regulatory mechanisms of transduction by CIB proteins. Results obtained from the proposed experiments and simulations will provide an initial and dynamic molecular view of the protein components of the inner ear mechanotransduction apparatus as we advance to understand its architecture and function in normal and impaired hearing and balance.

NIH Research Projects · FY 2025 · 2024-07

Project Summary The overarching goal of this project is to understand how RNA splicing is encoded in DNA sequence and how it impacts biological function and to use this knowledge to help design treatments or drugs to improve human health. Achieving these goals requires a comprehensive and deep characterization of mRNA splicing mechanisms and function, which can only be achieved by developing and applying novel genomic assays, computational approaches, and analytical framework to study mRNA splicing. In this project, we propose to: (i) develop computational methods to facilitate studies of RNA splicing in human biology and disease, (ii) characterize splicing-mediated regulation of gene expression levels, which our preliminary findings indicate is a common mechanism and can redefine our functional view of splicing, (iii) investigate mechanisms of RNA splicing modulation by small molecules. Our project has the potential to significantly advance our understanding of RNA splicing mechanisms and function and will help us leverage mRNA splicing as a target for therapies.

NIH Research Projects · FY 2025 · 2024-07

PROJECT SUMMARY Tuberculosis (TB), caused by the intracellular pathogen Mycobacterium tuberculosis (Mtb), infects one-fourth of the world’s population. Majority of the infected individuals are latently infected (LTBI), of which 5-10% stand a risk of progressing to active TB disease (ATB) during their lifetime. There is limited knowledge about the precise mechanisms and pathways that mediate protective versus pathologic immunity during TB. Using RNA- sequencing analysis, we recently identified novel immune pathways upregulated during TB latency across species, namely Bone Morphogenetic Protein (BMP) signaling pathway. The BMP signaling pathway plays a prominent role in the regulation of lung development and adult lung homeostasis, and tissue repair following injury. However, the role of lung tissue repair and regeneration during TB latency is unexplored, and the specific role of the protective BMP-pathway in latent Mtb infection remains unknown. Moreover, our data suggests that lung tissue damage is being actively repaired in controllers during TB latency, without triggering a substantial inflammatory response. Therefore, we hypothesize that during TB latency, BMP signaling is upregulated mediating lung tissue repair, regeneration and Mtb control. This hypothesis will be addressed in the following two Specific Aims. In Specific Aim 1, we will determine the functional role of the BMP- pathway in Mtb control and TB reactivation. In Specific Aim 2, we will characterize the cellular mechanisms of BMP-pathway activation during TB latency. These studies can then pave the way for new strategies that will aid in the development of therapeutic interventions which can deter the progression from TB latency to TB disease.

NIH Research Projects · FY 2025 · 2024-07

The mission of the NIH/NIAID Bioinformatics Resource Center (BRC) program is to accelerate basic and applied infectious disease research by providing access to cutting edge bioinformatic tools, knowledgebases, and expertise, ensuring that our knowledge of pathogenesis can be translated into diagnostics, therapeutics and a public health response that mitigates the morbidity and mortality resulting from infectious diseases. The current NIH/NIAID-funded Bacterial and Viral Bioinformatics Resource Center (BV-BRC; Contract No. 75N93019C00076) supported this mission by providing a bioinformatics knowledgebase and analysis platform covering all bacterial and viral pathogens. In response to the NIAID notice of funding opportunity, RFA-AI-23- 032, our proposal intends to maintain, improve, and expand the BV-BRC to combat future infectious disease threats, while maintaining our commitment to enhance accessibility to the bioinformatics resources and serve the global infectious disease research community. BV-BRC will support bacteria, archaea, viruses, bacteriophages, as well as metagenomic analyses, with particular emphasis on human pathogens relevant to infectious diseases and public health. BV-BRC will continue to support the basic scientific research necessary to understand the biology of these organisms, their pathogenesis, and disease processes; support development of diagnostics and therapeutics to combat pathogenic organisms: and provide a rapid response framework to effectively deal with the inevitable and unpredictable outbreaks and pandemics. To support these overarching goals, we propose to extend and enhance BV-BRC through the following four key elements: 1) Maintain and enhance the BV-BRC knowledgebase to support exponential growth of data and usage and provide integrated access to omics data, metadata, analysis services and visualization tools, private user workspace, and user documentation to allow users to analyze public and private data and share or publish results; 2) Develop innovative tools and technologies to provide comprehensive services for viral and bacterial bioinformatics, metagenomics, drug development, and developing AI-driven natural language-based user interface for interacting with data and tools, with emphasis on improving user experience; 3) Offer critical bioinformatics expertise, outreach, and training to the research community, with emphasis on fostering opportunities for students by providing freely accessible training material and conducting training for educators; and 4) Provide cutting-edge support to rapidly respond to emerging needs, outbreaks, and pandemics by building on the tools and procedures developed during COVID-19 and Mpox pandemics and enhancing them to improve readiness and response to future outbreaks and pandemics.

NIH Research Projects · FY 2025 · 2024-07

Project Summary Different cognitive behaviors appear to engage distinct activity patters across brain-wide circuits. This distributed nature poses a big challenge to understanding which specific activity patterns are causal to different behaviors, for a few reasons. First, it is technically challenging to perturb neural activity at large scales. Second, the same brain regions are often involved in disparate cognitive processes, but they appear to interact and communicate differently depending on behavioral demands. Third, cognitive behaviors do not exist in a vacuum. For example, you may walk around as you deliberate about your future college, but that action is not required for the decision. Thus, to truly understand the neural mechanisms of cognition, we need to use circuit perturbations to disentangle distributed neural activity and interaction patterns that are causal to a behavior from those that are simply incidental to it. Perturbation methods currently available to neuroscientists cannot accomplish this because they tend to target one or few regions at a time, and not account for inadvertent changes in the activity of other interconnected brain regions. To address these challenges, we propose to develop a new set of methodologies for simultaneous, distributed perturbation of multiple cortical regions using patterned light. Specifically, we will design a custom apparatus for head-fixed mice that uses a digital micromirror device to deliver spatially stochastic light patters at cortex-wide scales. This will allow us to borrow concepts from systems identification, used in electrical engineering and sensory-receptive-field mapping, to infer how large-scale patterns of cortical activity underlie decision-making behaviors in a data-driven fashion. Specifically, we will first develop an open- source hardware and software suite to enable these experiments, which will be disseminated to the community at large. We will then perform proof-of-principle experiments in which we will combine spatially stochastic optogenetics with reflectance imaging or extracellular electrophysiological recordings using silicon probes, to estimate distributed cortico-cortical interactions in mice running spontaneously. Finally, we will employ these approaches in mice performing two ground-truth decision-making tasks in virtual reality, for which we have strong expectations for the patters of behavioral deficits caused by the perturbation of different cortical areas. These initial experiments will therefore establish the feasibility and showcase the versatility of our approach. They will also pave the way for future work using these new methods to probe how distributed cortical interactions support complex cognitive tasks. I expect the methods we develop will be readily applicable to multiple other behaviors, neural systems, and model organisms to reveal the elusive causal link between neural interactions and behavioral function.

NSF Awards · FY 2024 · 2024-07

This project aims to connect detailed microbial processes to broader ecological and environmental outcomes such as soil fertility and greenhouse gas emissions, with critical implications from climate change to agriculture. The project includes a robust outreach mechanism that will support hands-on educational activities that integrate mathematical and biological thinking for K-8 students, secondary school teachers, and undergraduates, fostering a well-prepared STEM workforce equipped with cutting edge mathematical and experimental tools. The research objective of the project is to understand the mechanistic basis of functional robustness in the soil microbiome. The project will reveal how environmental variation impacts ecological processes within the microbiome giving rise to variation in denitrifying metabolic activity in soils. The approach leverages massively parallel experiments on soil microcosms, precise quantification of metabolite dynamics, and mathematical models to connect metagenomic, transcriptomic, and population dynamics to the emergent functional properties of these complex microbial communities. The project is structured around three main objectives. The first is to elucidate the mechanisms through which soil microbiomes respond to pH changes and how these responses impact the rate of anaerobic nitrate reduction in soils, a key process in nitrogen cycling. In this objective the researchers will combine transcriptomic and metagenomic measurements with mathematical modeling to predict how pH perturbations impact the metabolism of soil microbiomes. The second objective is to identify specific microbial taxa that drive observed changes in soil functions under different environmental conditions. This objective will involve identifying the key groups of bacterial taxa that are responsible for the metabolism identified in the first objective. The goal is to define the set of bacterial taxa that are responsible for the transcriptional and metagenomic responses to environmental perturbations described in the first objective. The third objective focuses on isolating and characterizing key microbial taxa identified in earlier phases of the study. The goal is to perform isolations and quantitative phenotyping of individual strains in the microbiome with the objective of linking individual bacterial traits to higher level microbiome metabolic function again via quantitative modeling. The goal will be to understand the metabolic response of the nitrate reduction rate to changes in pH in terms of the underlying traits of members of the microbiome. Collectively, this research will provide new insights into the soil microbiome's resilience and adaptability, offering strategies for enhancing soil health and agricultural productivity in the face of global environmental changes. 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 · 2024-07

Mechanisms of Cell-type-specific pre-mRNA Splicing Abstract: The overarching goal of this project is to uncover cis- and trans-regulatory mechanisms of pre-mRNA splicing at the cell-type level. While single-cell RNA Sequencing (scRNA-Seq) is revolutionizing our understanding of cell- type heterogeneity in animal tissues, the extent and mechanism of cell-type-specific splicing remain largely uncharted. The major challenges are threefold: 1) Current scRNA-Seq platforms are predominantly built on read counts of the 3’ or 5’ end fragments of polyadenylated RNAs and do not have sufficient coverage for splice junctions; 2) Homologous RNA binding proteins (RBPs) frequently have overlapping expression patterns and redundant functions, making it challenging to uncover their full functions in vivo; and 3) Protein-RNA interaction has been predominantly studied in cell lines or bulk tissues using UV-crosslinking and immunoprecipitation- based approaches, and it remains a challenge to identify RBP targets in specific cell types from intact tissues. My group uses the mouse brain as a model system and has been developing new tools to overcome these challenges. We have made proof-of-concept progress and seek to 1) uncover cis-regulatory elements and coordinated splicing patterns by single-cell long-read sequencing; 2) study redundant RBP functions by multiplexed genome editing; and 3) investigate protein-RNA interaction at the cell-type level by dual RNA- deaminase editing and sequencing. Successful completion of this project will generate new tools and datasets to understand the mechanisms of cell-type-specific pre-mRNA processing. The MIRA funding mechanism will permit the flexibility to integrate technological advances and study new biological questions.

NIH Research Projects · FY 2026 · 2024-07

PROJECT SUMMARY Acute exposure to ultrapotent synthetic opioids (UPSO), such as fentanyl, represents a significant public health concern. In the ongoing opioid epidemic, it is estimated that UPSO exposure contributes to over 80% of overdose-related deaths. The current defense strategy against UPSO exposure has been the development of reversal agents, such as naloxone, that aim to effectively reverse opioid-induced respiratory depression and related secondary complications with breathing. However, the high potency of UPSO decreases the window of time in which a counteragent can be administered before UPSO-dependent cardiorespiratory collapse (CRC) occurs and immediate resuscitative action is required. Optimal strategies for resuscitation following UPSO- dependent CRC are unknown. Resuscitation increases the risk for hypoxic-ischemic reperfusion injury (HIRI), which can lead to additional morbidity and death despite reversal of the opioid-mediated effects on breathing. Critical knowledge gaps exist in understanding how UPSO exposure impacts post-resuscitative outcomes in vital organ systems such as the heart, lungs, and brain. These gaps are a significant roadblock to successfully minimizing the morbidities and mortalities associated with UPSO exposure. Proposal Objective: Establish a foundational understanding of the cellular and systemic outcomes after reversing fentanyl-induced CRC (fiCRC). We have developed a novel model of fiCRC where we observe pulmonary edema following naloxone administration and reversal of respiratory depression, closely modeling documented clinical observations. Central Hypothesis: Factors beyond respiratory depression contribute to the progression of fentanyl overdose, leading to injury following the reversal of fiCRC; these factors are tractable targets in minimizing injury due to fentanyl overdose and its reversal. We propose the following aims to test this. Aim 1: Characterize how fentanyl and the reversal of OIRD impact the relationship between breathing and O2 consumption, mitochondrial activity, and tissue-specific glucose metabolism. Aim 2: Characterize physiological outcomes of fentanyl overdose and reversal of fiCRC in the cardiopulmonary system and brain. Aim 3: Test the efficacy of adjunctive strategies during naloxone-mediated reversal of fiCRC to improve outcomes in the cardiopulmonary system and brain. This proposal and its aims align with RFA-DA-23-056 to support mechanistic investigations into persistent/delayed pathophysiological effects following acute UPSO exposure.

NSF Awards · FY 2024 · 2024-07

Developing a predictive understanding of sensory membrane proteins is imperative for our ability to address environmental stresses including global warming. The proposed research will study how humans and other animals’ sensors perceive pressure, heat, and sound, and then send signals that enable one to feel pain, hear, and sense when muscles are moving, lungs are filling, and even when stomachs are full. The perception of force and heat at the atomic level is a complicated process. Our sensors are proteins that are embedded in the outer layer, or membrane, of a cell. How these sensors and other membrane-imbedded proteins respond to external stimuli provides information on how they move and function. Computer simulations are an integral part of modern biological research as they augment many experimental studies and provide a test bed for our ideas on how biological molecules function. The goal of the research is to produce computational tools that have the detail, flexibility, and accuracy to conduct realistic simulations of sensory membrane proteins. This project will enhance the training of a diverse STEM workforce, including graduate students and postdoctoral scholars, and extend our nation’s leadership in biophysics. Ideally, a computational tool should exist to simulate dynamics and predict structure. The sequence-to-structure challenge has largely been solved by AlphaFold2. However, simulating dynamics, especially for large membrane proteins involved in sensing of force and heat, remains a challenge. The research will produce a fast and easy-to-use tool called Upside that has the accuracy to simulate realistic conformational changes in membrane proteins. Upside fills an important niche in the “simulation biosphere”. The model uses 5 atoms and has a multi-position side chain center, and authentic H-bonds. Upside can be used to investigate the dynamics of large membrane proteins for long times with near-atomic resolution. This enables a variety of studies including those on environmental sensing, ion channels and protein folding. Our development of methods to integrate hydrogen-deuterium exchange-mass spectrometry (HDX) data with simulations will be beneficial to the computational and experimental communities. Accuracy will be assessed using our validation protocols and the HDX-MS data. These data identify which parts of the protein are most stable making an excellent complement and method to validate simulations. Upside also is an excellent complement to many other computational studies as it can rapidly sample the energy surface and identify regions for exploration by more detailed methods. In addition to experimental validation, Upside will be compared to all-atom molecular dynamics simulations. 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 · 2024-07

Social robots can help people in a variety of ways. They can serve as tutors to elementary school students. Social robots can contribute as teammates in collaborative human-robot teams. They can also provide daily care to older adults. These social robots have potential to improve the lives of everyday people. Yet, social robots will fail to reach their full potential unless they have social skills. It is especially important that a robot’s social skills allow them to interact with groups of people. If they do not have these social skills, people will ignore them. Robots without social skills will also interrupt people and support harmful biases. If robots have social skills, they can have effective communication in group settings. They can act with social awareness, and better encourage team collaboration. In this project, the research team will design three robot social skills. These skills will enable successful interactions between a robot and a group of people. These social skills first include building rapport with people in a group. Second, they will adapt to the human-human relationships present in the group. Last, the robot will promote the group's social norms. First, the research team will develop and test each of these social skills. Next, they will combine these three social skills into one robot. This robot will interact with groups of 3rd-5th grade elementary school students. The robot will help these students with a collaborative learning activity. The research team will study the benefits of the robot’s social skills. This research will enhance human-robot communications, group dynamics, and group performance. The robot social skill designs created can be adapted for robots in other contexts. These social skills may apply to search and rescue as well as hospital delivery robots. These skills will also help to improve human-robot group outcomes. The goal of this project is to design social skills for a robot to use to collaborate with groups of people. Recent advancements in computing have provided robots with increased technical abilities. Yet, it will be difficult for robots to integrate into daily life without appropriate social skills. Having usable social skills will enable improved interactions with groups of people. The research team will design three robot social skills that will enable robots to better collaborate with groups of people. The first skill is building rapport with groups of people. The second set of skills is adapting to human-human relationships. The third skill is promoting group norms. To develop these social skills, the research team will rely on prior work in psychology. They will use data-driven techniques to define a set of constituent fine-grained robot behaviors. These social skills may include engaging in mutual gaze when making key decisions. Another social skill may be learning to ask appropriate follow-up questions. The design and implementation of these social skills will be adaptable to different robots and contexts. The research team will perform laboratory studies with groups of adults. These studies will determine the effectiveness of the developed robot social skills. They will explore if the social skills have the intended effect and influence group outcomes. The final step for this research is a real-world evaluation. The research team will adapt the social skills developed in earlier project phases. These adapted skills will enable a robot to assist with collaborative learning. The research team will perform this study with groups of 3rd-5th grade students in elementary school classrooms. In this evaluation, the aim is to show the positive influence of the robot's social skills on both student engagement and learning outcomes with collaborative learning tasks. 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 · 2024-07

ABSTRACT Staphylococcus aureus is a human-adapted pathogen that replicates by asymptomatically colonizing its host. S. aureus is also the causative agent of purulent skin and soft tissue infections as well as bloodstream infections that result in the metastatic seeding of abscess lesions in all organ tissues. A hallmark of infection and colonization is recurrence, a phenomenon that reflects both a failure of the host to generate protective immunity and the highly versatile capacity of this pathogen to surmount innate and adaptive immune defenses. As a consequence, approaches to identify the protective antigens of S. aureus to develop a successful vaccine have failed, leading to the notion that staphylococcal-neutralizing adaptive responses may not be sufficient to reduce burdens imposed by this pathogen. Here, we find that this might not always be the case. Mice lacking functional H2-O (the equivalent of human HLA-DO) inoculated with a mouse-adapted strain of S. aureus efficiently de-colonized the pathogen. De-colonized mice resisted bloodstream challenge with the MRSA isolate USA300 suggesting that they were immune to the pathogen. We found that T-cell dependent B cell responses were required to control S. aureus colonization in H2-O-deficient mice and that H2-O-deicient mice produced higher titer S. aureus-specific antibodies compared to wild-type mice. H2-O is a negative regulator of MHC-II peptide loading and presentation and was shown to restrict the loading of high affinity peptides. Thus, we hypothesize that the muted immune responses against S. aureus are derepressed in mice lacking H2-O. We propose to exploit this observation and identify S. aureus-immunodominant antigens and -specific T cells and B cells as well as antibody sub-classes that lead to decolonization of the pathogen.

NIH Research Projects · FY 2024 · 2024-07

PROJECT SUMMARY Peripheral neuropathy and neuropathy pain can be caused by a myriad of genetic and environment factors as well as therapeutic or recreational drug use. Chemotherapy-induced peripheral neuropathy (CIPN) is the major dose-limiting neurotoxic side effect of standard chemotherapy regiments. Over 68% of cancer patients experience neuropathic symptoms after chemotherapy, and that contributes to a significant percent of the population that suffer from chronic pain and often resort to opioid use. Peripheral neuropathy is closely associated with Alzheimer’s related dementia. Specifically, a negative correlation between the severity of peripheral neuropathy and cognitive performance has been reported in patients with dementia. The mechanisms of CIPN and Alzheimer’s related neuropathy intersect at the dysregulation of neuronal microtubules. CIPN is caused by microtubule-targeting chemo drugs, while a major pathology in AD is the dysregulation of microtubule associated protein Tau (tauopathy). There is an urgent need to understand the in vivo mechanisms of CIPN and AD related peripheral neuropathy. Recently, we have optimized a model of peripheral neuropathy using Drosophila larvae that recapitulates salient behavioral, physiological, and cellular aspects of sensory dysfunction. Our work using this model has uncovered a new mechanism underlying peripheral neuropathy and identified a neuroprotective protein NMNAT with promising potential for mitigating neuropathic pain. Our preliminary studies have identified several natural compounds that potentially upregulate NMNAT transcription and discovered the exciting role of microRNAs in regulating both the pre-mRNA splicing and mature mRNA stability. The aims of the parent R33 grant include, (1) test the neuroprotective activity of 9 microRNAs that regulate nociceptive hypersensitivity and pain, (2) characterize the molecular pharmacology of 13 natural compounds in regulating NMNAT expression and enhancing neuroprotection against peripheral neuropathy and chronic pain. The objectives for the supplement application are to expand our testing portfolio to include genetic models of Alzheimer’s disease and identify microRNAs and natural compounds that mitigate peripheral neuropathy in AD. We have established Tauopathy models that recapitulate cellular pathology of Alzheimer’s including filamentous accumulation of hyperphosphorylated Tau (pTau), neuronal degeneration, impaired nervous system physiology, and shorted survival. Our preliminary pain behavior studies in AD models have observed a hypersensitivity to pain in mutant hTau (hTauR406W) expressing nociceptors, consistent with clinical presentation of peripheral neuropathy in AD patients. We propose to test our hypothesis that the neuronal microtubule dysregulation in nociceptor neurons is a shared cellular mechanism underlying CIPN and AD induced pain. The proposed supplement work is within the scope of the parent R33 project but expands the outcome to include I) mechanistic characterization of microRNAs and natural compounds that augment NMNAT-mediate protection against neuropathic pain in AD, and II) identify shared cellular mechanisms between CIPN and AD.

NIH Research Projects · FY 2026 · 2024-07

Project Summary Pathogens are one of the strongest selective pressures on the human genome. As modern humans migrated out of Africa, they encountered markedly different pathogenic environments, likely resulting in population-specific selection of immune phenotypes. Consistent with this hypothesis, some of the most compelling evidence for local positive selection in the human genome has been detected among genes involved in immunity and host defense. Yet, our understanding of the role that local adaptation plays in shaping phenotypic variation in immune responses across populations is still in its infancy. To better understand the complex relationship between pathogens and host adaptation we propose to explore the effects of natural selection and genetic ancestry on gene expression, epigenetic traits, and immune responses to infection across a large array of human populations. Our research program is grounded on three outstanding questions in the fields of genomics, population variation in host response to pathogens, and evolutionary biology: (i) the degree to which immune responses to pathogens are differentiated across ancestry groups; (ii) the genetic variants that account for such differences; and (iii) the evolutionary mechanisms (neutral genetic drift vs positive selection) that led to the establishment of these variants in modern human populations. Addressing these questions is not only important for understanding the recent evolution of the human immune system but may also help reveal the molecular basis to interindividual differences in susceptibility to infectious diseases, chronic inflammatory disorders, and autoimmune disorders.

NIH Research Projects · FY 2025 · 2024-07

Multiple innate immune mechanisms regulate commensal microbes and promote responses to pathogens. Identification of non-redundant functions of such mechanisms is not a simple task, especially with regulation of complex microbial communities such as intestinal commensals. Commensals are indispensable for the existence of their eukaryotic hosts and provide essential functions) required for the host’s survival. The composition of microbial communities varies greatly from individual to individual and is shaped by multiple factors including the mode of transmission during birth, breastfeeding, alimentary infections and diet. An important question remains unanswered: to what extent and which host’s polymorphic genetic mechanisms are involved in shaping the repertoire of the commensals. Although many polymorphic genes were found to be good potential contributors to shaping commensal communities, a drastic difference in expression of defensins alpha (aDef encoded by Defa genes) was detected between the small intestines of B6 and BALB/c mice. Defensins are anti-microbial peptides that are thought to safeguard the stem cells of the gut epithelium. Defa genes are localized to a chromosomal locus that undergoes a rapid evolution and is characterized by multiple duplications and deletions. In addition, these genes have very high level of homology and there are other defensins with similar functions. There is no consensus whether aDef have some specificity towards different groups of microbes or whether their specificities are very broad. Most of specificity suggestions came from the studies of bactericidal effects in vitro (done with limited variety of Defa-encoded peptides and from the studies of MMP7 KO mice, a metalloprotease that cleaves aDef peptides to activate them), which by today standards cannot be fully accepted as these studies did not exclude cage (legacy) effects. Armed with two state of the art approaches – CRISPR/Cas9 gene editing and germ-free technology – we aim at shedding light on the spectrum of specificities of the aDef peptides, their contribution to host’s genetic polymorphism in shaping the microbiota and resistance to pathogens. The current proposal aims at defining the place of aDef in homeostatic and induced by pathogenic signals innate host defense. Most importantly, it will be done in the most refined and most reliable way. We will pursue the following specific aims: Specific Aim 1. Use the combination of reverse genetic and gnotobiotic approaches to study the homeostatic role of alpha-defensins. Germ-free mice carrying aDef deletions will be colonized with natural or synthetic microbiomes to detect shifts in microbiota composition or gene expression dependent on aDef peptides. Specific Aim 2. Study importance of aDef using infectious and non-infectious stress. Mice lacking Defa will be tested for sensitivity to infections with intestinal pathogens and chemical insult on the intestinal epithelium.

NSF Awards · FY 2024 · 2024-07

Urban gangs are major security threats in many countries. Who joins these gangs and why? This project builds on a survey of 10,000 grade 7 and 8 boys in a setting characterized by hundreds of well-organized drug-selling gangs. The survey is designed to better understand their beliefs about gang versus legal careers. The project follows the subjects over time, tracking who stays in school, who drops out, who is arrested, and who joins a gang. It assesses what beliefs and circumstances drive gang entry, and how one may predict (and ultimately prevent) gang entry before it happens. After identifying the highest risk youth, the project develops and tests two programs to reduce gang entry. One improves children’s familiarity with and the attractiveness of higher education and legal careers and builds their planning and goal-achievement skills. The other provides financial incentives to avoid criminality. The project tests both approaches with randomized trials. Successful program models could be duplicated and implemented in cities around the world. The project builds on a longitudinal study in a single city charactered by high gang presence that attempted to survey 13- and 14-year-old boys in highest-risk schools. The survey focuses on subjective beliefs about a range of careers, including gangs. It elicits beliefs about financial and non-financial benefits and costs, plus interest in each career. The investigators use these data to estimate structural models of criminal occupational choice, assess which beliefs matter most to the decision, and simulate policies. Using rich administrative data, the project follows respondents long-term in school, arrest, and social security records to determine actual participation in legal and criminal careers. The investigators implement and evaluate several information and field experiments to test which misperceptions drive gang entry and if they can be corrected. Altogether, this is the first longitudinal panel study and experimental evaluations of armed group entry outside a high-income country. Compared to existing longitudinal studies of delinquency, the study has several advantages. The survey begins following youth before the age of recruitment and collects and follows their social network. It links all children to lifetime schooling, crime, and social security data. It is also the first panel to elicit beliefs about the financial and nonfinancial returns to criminal and legal careers (and hence estimate which beliefs matter). Findings from this project inform anti-dropout and anti-child recruitment interventions. 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 · 2024-07

PROJECT SUMMARY: Renal cell carcinoma (RCC) is the sixth most common cancer in the United States, with ~ 82k new diagnoses estimated for 2023. Surgery is the preferred option for initial management of RCC, but the number of patients who qualify is reduced each year due to the aging, comorbid population. Histotripsy is a noninvasive, focused ultrasound therapy used for tissue ablation via bubble activity, and is an attractive alternative to surgery. Indeed, a pilot clinical trial to test histotripsy for the treatment of RCC is scheduled for 2023. Standard B-mode ultrasound imaging is used to monitor histotripsy via the detection of hyperintense bubble pixels. In the kidney, histotripsy bubbles are obscured on B-mode due to artifacts, image degradation at depth, and a lack of contrast specificity. Patients will be disqualified from receiving treatment with histotripsy when bubbles cannot be located and monitored with imaging. Further, B-mode bubble imaging does not provide the information necessary to assess the likelihood of successful oncological outcomes. Real-time feedback to adjust the histotripsy exposure and ensure ablation is of particular importance for heterogenous tumors common to RCC. Hence, there is a need for improved histotripsy bubble detection to enable therapy automation. To address this gap, we have developed ultrafast, bubble-specific ultrasound imaging for monitoring histotripsy. Using this imaging sequence, we can assess the diffusive properties of histotripsy bubbles, a key marker of ablation outcomes, with sub-millisecond resolution. The scientific premise of this study is that ultrafast imaging will elevate histotripsy bubble monitoring, and provide feedback to ensure effective and safe RCC ablation. We have demonstrated strong translational potential to monitor histotripsy with ultrafast imaging in vitro, ex vivo, and in murine renal tumors on a pre-clinical system. Our objective is to refine and integrate this sequence onto a clinical-grade imager, develop and test feedback algorithms in RCC tissues and a relevant large animal model, and rapidly translate this imaging protocol into use in patients. To test our scientific premise, we will investigate the following aims: We will develop a translational histotripsy system for RCC in Specific Aim 1. We will integrate our ultrafast sequence onto a clinical-grade imaging platform, and evaluate its sensitivity and accuracy for bubble detection. In Specific Aim 2, methods to monitor and modulate the bubble cloud lifetime will be developed. These methods will be used to adjust the histotripsy pulsing rate to enhance the efficacy of histotripsy ablation. Specific Aim 3 will use information on the bubble cloud dissolution rate to provide real-time feedback of treatment outcomes using an in vivo porcine kidney ablation model. The rate of urological sequelae will be determined in short-term survival studies. This study will deliver validated ultrafast sequences on a commercial histotripsy imaging system to improve RCC ablation and ensure safety. Following these validation steps, the sequence will be translated immediately in a clinical trial for histotripsy RCC.

NSF Awards · FY 2024 · 2024-07

Skin color discrimination, regardless of race, is common across societies around the world. Also known as colorism, it typically manifests itself in favoring lighter skin over darker skin and has been found to be an important predictor of many outcomes, including occupation, educational attainment, criminal justice system involvement, and marital outcomes, among others. However, there is no objective way of measuring skin color. This CAREER award will fund research to develop new methods, based on artificial intelligence technology, to accurately measure skin tone, for a large number of young people and make the data available to other researchers. This will allow more research on the relationship between skin tone and several outcomes. The research will also use the data to investigate how skin tone affects who is chosen to participate in crime intervention programs as well as parental investments in their children’s education. The results of this research will provide inputs into efforts to reduce differential opportunities based in skin tone differences. This will improve the overall quality of the US labor force, increase productivity, economic growth, and improve the well-being of citizens. The results of this research will also help establish the US as a global leader in reducing the effects of colorism on outcomes. Despite the potential distortionary effects on decision-making, colorism has been understudied in the economics literature, partly because it is difficult to measure colorism. The first part of this CAREER research award will develop AI and neural networks assisted computational protocols to systematically classify skin color that is scalable, replicable, accounts for local knowledge in a study setting, and use the protocols to create a large data set on skin color. The methods and data collected will open new avenues of inquiry across the social sciences, medicine, humanities, and law. The research project will also study how individual-level interventions, such as those related to education and other human capital investments, and empowerment programs, may be causally influenced by colorism. This part of this research will also study the heterogeneous impacts of interventions based on skin color, as well as explore potential underlying mechanisms that contribute to these differential effects. The results of this research will provide inputs into efforts to reduce differential opportunities to people based on skin color; efforts that are likely to improve the overall quality of the US labor force, increase productivity, economics growth, and the well-being of American citizens. The results of this research will also help establish the US as the global leader in reducing the effects of colorism on many outcomes. 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 · 2024-07

Over the past half-century, the global geopolitical balance of scientific, technological, and economic leadership has shifted, with China’s meteoric rise and the ascendance of new powers including Korea and India. Technological leadership requires driving advances and setting standards that catalyze the future of global productivity. To understand pathways that enhance U.S. competitiveness in critical technology capacity, production, and use, this project will create a global observatory and virtual laboratory for U.S. science and technology in the context of global advancement. It will produce data sets and technology outcome models that capture the complex and emergent interdependencies among technologies; the funders, resources, researchers, and universities that catalyze and invent them; the workforces and organizations that produce them; and the markets that consume them. Drawing upon the power of deep neural network “transformer” architectures, the project will then build a deep-learned, chronologically trained, large language model (LLM) to function as a data-driven “digital double” of the global techno-scientific system. The LLM will embed research artifacts (e.g., articles, patents, products, related news, and their rich meta-data) in a high-dimensional space, mapping them to quantitative metrics of technology capability, production, and use. The project team will fine-tune our LLMs to capture changes in key metrics as corresponding trajectories within embedding space, and thus enable them to function as 1) a global observatory for technology catalysis, capacity, production, and use; and 2) a virtual laboratory for simulated experiments that can guide 3) causal estimation of relationships among policy levers (funding, competition, immigration), technology performance, and global leadership. They will also tune the LLMs and related models to enable customized extraction, structuring, and disambiguation of data on research, products, funding, and policy from novel sources to enrich modeled observations and predictions, which will enable the continuous incorporation of additional data and extraction of insight. Finally, they will use the models as resources for scientists and policymakers by building dashboards to provide funding agencies, policymakers, and researchers with the situational awareness required to improve the quality and diversification of their technology development portfolios. 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 · 2024-07

PROJECT ABSTRACT Cells assemble functionally diverse actin cytoskeleton networks with distinct architectures and dynamics to drive fundamental processes such as polarization, motility, and division. The size, organization, and dynamics of different actin filament networks are tailored by the coordinated activity of distinct but overlapping sets of actin-binding proteins with complementary binding properties. Because cells assemble and maintain multiple self-organized F-actin networks simultaneously from the same pool of limited cellular components, focusing on single networks provides limited overall understanding of actin cytoskeletal dynamics. We have established important cross-talk interactions between diverse F-actin networks that help dictate their size, form, and function. We use systems level approaches to investigate the underlying molecular mechanisms that govern the direct and indirect interactions between self-organized F-actin networks that determine their unique identities and functions within a common cytoplasm. We are focusing on two major outstanding questions relating to actin cytoskeleton self- organization, which we are simultaneously addressing in both fission yeast cells and one-cell C.elegans embryos to compare key mechanistic similarities and differences between these important model systems. The first is to determine how cells allocate actin monomers between competing F-actin networks to help tune network size and density (Focus 1). Although unassembled G-actin was not thought to be limiting, we systematically showed that competition for G-actin helps control the size and density of competitive F-actin networks in fission yeast, and that the actin monomer protein profilin plays a major role in regulating competition for limiting G- actin. Our goal is to determine the underlying mechanisms by which actin-binding proteins (ABPs) contribute to the proper distribution of G-actin between functionally diverse actin cytoskeleton networks. The second is to elucidate how F-actin networks recruit the specific set of ABPs whose biochemical activities define the unique characteristics of each network (Focus 2). We will investigate the underlying intrinsic molecular mechanisms by which ABPs self-sort to particular F-actin networks within a common cytoplasm, including (1) the contribution of competition and cooperation between ABPs for associating with actin filaments, and (2) whether actin assembly factors initiate self-sorting by biasing the association of particular ABPs.

NIH Research Projects · FY 2025 · 2024-07

Project Summary: For this proposal in response to PAR-22-085: Microbial-based Cancer Imaging and Therapy - Bugs as Drugs, we will focus on metastatic pancreatic ductal adenocarcinoma (PDAC), for several reasons: PDAC is particularly difficult to target and generally considered recalcitrant, but the pancreatic tumor microenvironment (TME) features an abundance of tumor-associated macrophages (TAMs) and few T cells. Therefore, methods to reprogram TAMs and enhance T-cell activation and proliferation will likely synergize with radiotherapy and checkpoint immunotherapy to control local and metastatic disease. Bifidobacteria is a commensal that preferentially targets tumors, and oral Bifidobacteria has been found to translocate from the gastrointestinal tract with subsequent homing to and replication specifically in tumors. Building on these findings, we recently reported that systemically administered Bifidobacterium (i.v.) specifically colonize and replicate in hypoxic tumor regions. Notably, we also found that i.v. administration of Bifidobacterium also converted non-responding mice into responders, in the context of local immunotherapy and/or ionizing radiation (IR). This data serves as proof-of-principle that systemic administration of Bifidobacterium can enhance tumor control in combination with immunotherapy and/or IR. We have now successfully developed genetic tools to regulate gene expression in Bifidobacterium longum. We propose to investigate the systemic administration of genetically-engineered Bifidobacterium delivering a novel human IL-2 (SumIL2) to the TME in combination with radiotherapy and/or immunotherapy. This strategy centers on harnessing both innate and adaptive pro-immune responses and is aimed at capitalizing on several known mechanisms of tumor evasion. In addition, our plan to include a precise gene circuit for precise protein secretion and bacteria self-destruction is a systemic therapeutic delivery innovation. Most importantly, we anticipate that our approach using Bifidobacterium will elicit significant anti- tumor effects for several reasons: 1. Bifidobacterium is selectively taken up by tumors, and SumIL2 secretion is precisely controlled after bacteria colonization, which will obviate the treatment-limiting toxicity commonly associated with IL-2 administration. 2. Our preliminary data presented here indicate that systemic (IV) administration of Bifidobacterium converts non-responder mice into responders to anti-CD47 immunotherapy and radiotherapy. 3. In contrast to E. coli, Bifidobacterium is a human commensal anaerobic bacterium, giving our approach a less toxic profile and more translational relevance. Our approach takes advantage of the natural features and genetic engineering of Bifidobacterium to reinvigorate the immune suppressive TME via systemic injection, and thus could have broad applicability in other hard-to-treat cancers.

NIH Research Projects · FY 2026 · 2024-07

Evolution of 3D Genome Folding Mechanisms and Gene Regulatory Strategies in Metazoans Abstract: The overarching goal of this project is to elucidate the role that 3D genome folding plays in shaping transcriptional regulatory strategies in animals. It has been proposed that organisms use multiple mechanisms, notably loop extrusion and phase separation, to fold nuclear DNA into a variety of structures including compartments and topologically associating domains (TADs). These features have been shown to have functional consequences on the transcriptional regulation of genes. As 3D features differ between lineages and have different regulatory properties, it is likely that changes to 3D folding mechanisms could have profound consequences on the transcriptional regulation strategies used in distinct lineages. Despite rapid progress, largely driven by development of chromosomal conformation capture techniques, in identifying the mechanisms of genome folding in major animal model organisms such as flies, nematodes and mouse, several barriers exist to our broader understanding of the relationship between evolution of 3D genome folding and evolution of transcriptional regulatory strategies including 1) 3D genome studies cover only a fraction of the diversity of animal genomes and many critical transitional lineages are not sampled 2) 3D genome maps generated by HiC represent an averaged view of the interplay between several co-existing mechanisms, making it challenging to link specific transcriptional processes to 3D architecture and disentangle their contribution to gene regulation. To overcome these challenges, we will employ a novel phylogenetic comparative approach using chromatin technologies, functional genetics and single-cell approaches to 1) generate 3D genome maps in outgroups to the vertebrates and to the Bilateria using approaches we have established in non-model marine invertebrates 2) functionally assay the role of chromatin-interacting proteins we have isolated from these lineages to determine the mechanistic basis of changes to genome folding 3) characterize the transcriptional regulatory strategies used in these animals via approaches we have developed to study gene regulatory mechanisms. This work will generate a fuller view of the evolution of 3D genome folding mechanisms in animals and will provide insight into the global drivers that shape gene regulatory strategies, which ultimately form the basis of changes to body plan complexity and phenotypic evolution. Furthermore, by contributing to our understanding of the basic mechanisms that shape 3D genome folding and gene regulation, insight generated through this comparative work will better inform our understanding of the dysregulation of gene expression that occurs in pathological contexts in humans such as cancer. The flexibility and perspective of the MIRA is ideally suited to support this integrated, multi-faceted program whereby rapidly evolving technologies can be readily integrated into the scope of this research program over the next five years.

NIH Research Projects · FY 2025 · 2024-07

ABSTRACT The premise of our proposal is that by characterizing the in vitro response of different types of cardiac single cells to different cancer drug treatments, we will be able to identify biomarkers that can help us classify patients at risk for cardiotoxicity. By applying single-cell sequencing to a novel system of cardiac guided differentiation cultures, we are proposing to study the effects of the anticancer drugs doxorubicin (DOX), 5-fluorouracil (5-FU), and bevacizumab (BVC) in multiple relevant cell types from a genetically diverse panel of 70 individuals. Our goal is to build a genetic-based classifier that can stratify cancer patients by their susceptibility to drug-induced cardiovascular toxicity (CT). To achieve this goal, we need to first identify candidate loci that underlie the functional differences between individuals. This is required, because whole-genome approaches to predict complex risk (such as polygenic risk scores) have generally shown not to be effective beyond the sample in which they were developed. A classifier based on relevant functional loci (the response eQTLs, in our case) is more likely to be generally effective and transferable. The premise of our study rests on two assumptions. The first is that inter-individual variability in response to chemotherapeutic drugs is at least partially mediated by genetic variants that affect gene regulation in a drug-dependent manner. In other words, genetic variants respond to chemotherapeutic drugs by regulating the activity of specific genes. The second assumption is that different cell types vary in their response to chemotherapeutic drugs. That is, a regulatory variant that affects gene expression in cardiomyocytes, for example, may have a different effect (or none at all) on gene expression in endothelial cells. To achieve our goals, we propose to collect single cell RNA-seq data from a panel of 100 cardiac guided differentiation cultures in control and drug-treated conditions (aim 1); to identify genetic variants that regulate the transcriptomic response of cardiac culture cell types to each drug (aim 2); and to test whether response QTLs identified in cardiac in vitro cultures can be used to retrospectively classify patients as resistant or sensitive to drug-induced cardiotoxicity (aim 3).