Yale University

NSF Awards · FY 2024 · 2024-09

NONTECHNICAL SUMMARY This award supports research and education activities with a goal to develop a fundamental understanding of quantum phases of matter with many interacting particles, using the concepts of symmetry and topology. Symmetry is a fundamental aspect of a physical system and has been recognized as a powerful principle in modern theoretical physics. A familiar example is the fact that total electric charge is conserved in everyday physical processes, which can help distinguish between electric conductors, insulators and superconductors. In the realm of quantum mechanics, a system of interacting particles, such as electrons, can form unusual quantum states, in which the constituent particles move collectively in highly intricate patterns, making them resilient to small changes in external conditions. Deciphering these subtle patterns requires ideas from topology, a branch of mathematics that concerns properties of geometric shapes that are unchanged by smooth deformations. A deeper understanding of these quantum states may enable new schemes in harnessing quantum materials and designing quantum devices. This project will leverage the power of the symmetry principle to advance the knowledge of exotic quantum states. The first thrust will investigate the properties of "symmetry defects", which are specific disturbances introduced to the system to reveal its underlying symmetry. Studying how the system reacts to such changes provides new methods to observe and characterize the unique quantum properties of the states involved. In the second thrust, the focus will be on the relationship between physical properties of a quantum crystal and microscopic interactions at the atomic level. This will furnish new perspectives on how crystalline quantum materials can be modeled theoretically. In the last thrust, the project will explore how the quantum behaviors of many interacting particles are affected by their interactions with the environment. Progress on this front will be crucial in exploiting these quantum states as memory for quantum information processing. This award also supports the PI's educational and outreach activities through mentoring and training of graduate students and postdocs in theoretical condensed matter research; writing pedagogical review articles and organizing conferences and workshops; outreach to K-12 students and the general public. TECHNICAL SUMMARY This award supports research and education activities with a goal to advance knowledge about quantum phases of matter with global symmetry and many-body topology as guiding principles. Characterizing the emergence of quantum phases from complex interactions between microscopic degrees of freedom represents a key challenge in quantum science. Advances in both condensed matter physics and quantum information science have significantly broaden the scope of quantum phases and provided new settings where universal behaviors of quantum many-body systems can arise. The project has three main thrusts: 1) Systematically develop a theory for a new type of non-local observables, called the disorder operators. These operators probe the fluctuations of symmetry charges in a given spatial region of the system, whose scaling behavior contains universal information about the underlying quantum state. The team will study how subleading corrections to the disorder operator depend on microscopic details, and develop field-theoretic techniques to compute them at quantum critical points. 2) Examine new aspects of UV/IR mixing: The interplay between microscopic conditions in lattice systems and macroscopic observables will be examined using the newly developed perspective of topological defects. The project will study how anomaly of a low-energy theory manifests in lattice quantum numbers and, conversely, how anomalous fractonic symmetries constrain low-energy dynamics. 3) Symmetry breaking and topological order in open quantum systems: the research team will investigate a new kind of symmetry breaking in mixed-state quantum phases and its implications on equilibration dynamics, and explore many-body topological order in quantum states under decoherence and beyond. This award also supports the PI's educational and outreach activities through mentoring and training of graduate students and postdocs in theoretical condensed matter research; writing pedagogical review articles and organizing conferences and workshops; outreach to K-12 students and the general public. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NSF Awards · FY 2024 · 2024-09

Active dynamics encompasses a wide range of collective behaviors exhibited by flocks of birds, schools of fish, layers of cells, and networks of filamentous proteins. In all these examples, out-of-equilibrium organization emerges spontaneously from interactions among active agents that consume energy from an internal reservoir or derive it from their surroundings. This project supports the development of scalable and automated software to simulate active dynamics and to infer the laws that govern it from the analysis of state-of-the-art experimental data, such as high-resolution microscopy videos. The goals of this project are to empower researchers to reliably extract hidden rules from noisy experimental observations of active dynamics, lower the barrier for analyzing large microscopy videos, reduce the time-consuming reimplementation of simulation and estimation, and promote cross-disciplinary collaborations. The dynamics of active matter, such as collections of fibroblasts or epithelial cells, is intrinsically stochastic and out of thermal equilibrium, and affected by a variety of complex processes, such as cell division. The large intrinsic fluctuations present in active matter systems hinder the efficient extraction of signals from noisy experimental data and thus it urgently demands the development of data-science-enabled tools to accelerate the analysis and improve the reproducibility of the findings. The development of the Dynamics Lab ecosystem addresses this urgent need by establishing two classes of interconnected software packages for real-space and scattering-based analysis of microscopy data. Together, these tools enable visualization and integration of physics-based simulations and statistical machine learning in both real space and Fourier space. Furthermore, to address the practical concerns of data sharing, such as size limit, this project supports the development of an efficient paradigm for data acquisition of active dynamics, where large raw data are stored offline, and small online data sets that sufficiently capture the raw data set are easily transferred and used for most research purposes. A major goal of Dynamics Lab infrastructure is to achieve sustained impacts on basic and applied sciences, ranging from biophysics to biomimetic materials. This award by the NSF Office of Advanced Cyberinfrastructure is jointly supported by the Division of Materials Research and the Division of Mathematical 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.

NSF Awards · FY 2024 · 2024-09

This CAREER project aims to explore how mathematical ideas from geometry and topology combine with quantum mechanics to affect properties of quasicrystalline materials. All materials require quantum mechanics to explain their basic properties. However, “quantum materials” are a subset of materials that exhibit macroscopically observable quantum effects. Topology in materials refers to a mathematical property that remains unchanged when a material is distorted. The discovery of topological phases of matter has been an eye-opening breakthrough in condensed matter physics and has led to surprises in possible phases of matter and in the behavior of electrons flowing through materials. Geometry is important for describing crystal symmetries and it places constraints on the behavior of materials, depending on the specific symmetries at play. Altogether, topological quantum materials (TQMs) are materials for which quantum mechanics, geometry and topology are important for describing emergent material properties. The research this CAREER award enables has high synergy with ongoing experimental and theoretical efforts across atomic physics, condensed matter physics, chemistry and beyond. This CAREER project will use atomic physics techniques to build and probe an experimental analogue of a quasicrystalline material with unusual symmetries. This research team will build an experiment that traps atoms in dynamically reconfigurable and aperiodic grids of light; here, the atoms are analogous to electrons in a material, and the light grid is analogous to the underlying patterns of atoms in a material. They will observe the behavior of atoms moving around the light grid and take measurements that provide detailed information on how geometry and topology play a role in the analogue quasicrystal. The PI will continue to generate impactful community-based programming that supports physicists and continue to develop high-visibility role models and new educational opportunities for students to learn about the scientific and technical aspects of cutting-edge research in physics. This research group is also developing educational opportunities for a group of over 1,000 young local students and will engage the students with quantum science from their laboratory. This CAREER project will experimentally explore the physics of quasicrystalline quantum materials by mimicking these materials with quantum degenerate matter in optical lattices. A quasicrystal is an aperiodic crystal with rotational symmetries that are mathematically forbidden in periodic crystals. The standard mathematical analysis techniques used to understand the behavior of periodic crystals does not work for quasicrystals due to a lack of translation symmetry. Quasicrystals exhibit anomalous and, potentially, topological transport properties that are thus difficult to understand analytically. This project aims to experimentally probe the effects of geometry and topology in the quantum behavior of a quasicrystal and how these effects lead to unusual transport properties in quasicrystals. New experimental techniques developed during this project are poised to open a new class of experimental probes of quasicrystalline material properties and of atomic physics systems. These experiments may lead to a jump in the understanding of the fundamental properties of TQMs, and the quantum many-body problem more broadly, especially for addressing scientific questions that are hard to answer with quantum many-body theory alone. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NIH Research Projects · FY 2025 · 2024-09

Non-Hodgkin lymphomas (NHL) represent about 90% of all lymphomas diagnosed each year and is classified based on cell type - B cell, T cell and natural killer (NK) cell types, location - nodal or extra nodal, and the tumor grade - aggressive (high grade) and indolent (low grade). Follicular lymphoma (FL) is the most common indolent B-cell lymphoma but remains a largely incurable malignancy. The most clinically challenging aspect of FL is the transformation into diffuse large B-cell lymphomas (DLBCL), characterized by the emergence of more aggressive subclones, loss of the follicular growth spatial architecture, and resistance to treatment, leading to a much shortened survival period, typically less than 2 years. Among T-cell lymphomas, angioimmunoblastic T-cell lymphoma (AITL) is one of the most common subtypes characterized by a tumor with follicular helper phenotype surrounded by an inflammatory microenvironment, arborizing vasculature, and progression with dramatic changes in spatial architecture. Although the discovery of FL transformation and AITL tumor evolution was initially documented over 50 years ago, the biological mechanisms and clinical implications remain poorly understood. No biomarkers exist to predict or therapies to prevent its metastases or progression to highly aggressive lymphomas. Both of these tumors hijack normal follicle biology to escape immune surveillance and potentially develop resistance clones. Yale HTAN Center aims to leverage the latest development in single-cell and spatial omics technologies to construct a spatiotemporal atlas of human FL transformation to DLBCL and AITL evolution. Specifically, we will apply high-plex immunofluorescence protein imaging to map all major cell types and spatial whole transcriptome sequencing to link cell type to mutational landscape, clonal evolution, and spatial interaction within the tumor microenvironment. We will further integrate spatial omics data with single nucleus RNA sequencing to identify cell subtypes and niches across tissue samples over various disease stages to construct a complete cell atlas associated with tumor transformation for different sexes and racial/ethnic groups and then computationally model the spatiotemporal evolutionary dynamics. Finally, we will apply and integrate spatial-epigenome-transcriptome co-profiling to unveil epigenetic mechanism underlying such transformation and potentially discover earliest events to predict the progression. The proposed spatiotemporal lymphoma atlas represents a valuable resource to test a range of hypotheses such as how different tumor clone emerge, interact, compete or cooperate in the spatial tissue context to drive lymphomagenesis, how T cells recognize and interact with different mutant clones, how the microenvironment co-evolves with tumor cells, and how to predict the likelihood of transformation and therapeutic stratification of patients. Single-cell spatial omics techniques and computational models can be applied to other types of human tumors within the HTAN consortium.

NIH Research Projects · FY 2025 · 2024-09

PROJECT ABSTRACT E-cigarettes are the most popular nicotine-delivery devices used by US adolescents. Many adolescents do not like being addicted to e-cigarettes and want to quit. However, there are no empirically validated interventions to help them quit using e-cigarettes. We have developed an adolescent-focused smartphone-app called Kick-Nic!© that uses an engaging, multi-media rich, and interactive cognitive-behavioral therapy platform to teach coping skills for e-cigarette-specific triggers and support cessation. App content to address e-cigarette appeal, quit motivations, and coping skills, was developed using focus group evidence from 60 adolescent e-cigarette users. The structure, format and design of the app was developed using iterative feedback from 14 adolescents. A feasibility pilot with 19 adolescents who used the app, indicated that it was engaging, easy to use, and useful to support e-cigarette quit efforts. An open label pilot is testing the use of the app with engagement methods commonly used in digital interventions that were identified by youth as important for engagement [text message reminders & weekly in-person check-ins]; 8 high school adolescents have initiated the trial, are completing all app sessions, weekly check-ins, and assessments with 100% retention. The current proposal will: Aim 1: Examine the efficacy of the Kick-Nic!© App: We will conduct an RCT with 306 adolescents in high schools who use e-cigarettes regularly (>/=1 day/week in the past month) and want to quit. Adolescents will be randomized to the ACTIVE (Kick-Nic!© App for eight weeks, along with text message reminders and weekly virtual check-ins, & assessments) or the CONTROL condition (assessments alone with referrals to NCI Quit Vaping webpage). E-cigarette use will be assessed at baseline, biweekly during treatment, and end of treatment (EOT; 8 weeks), and then at 1, 2, 3 and 6 month follow ups (FU). Salivary cotinine levels </= 30 ng/ml) will verify self-reports of abstinence at EOT and 6-month FU. We will explore changes in other tobacco and cannabis use behaviors. Our primary outcome will be 7-day, biochemically verified, point-prevalence abstinence (PPA) rates at 6-months, and secondary outcomes include 7-day PPA at EOT, % days e-cig free (during treatment, at EOT, 3 and 6 mths FU) and continuous abstinence (at EOT, 3 and 6 mths FU). We will also examine the impact of app engagement, coping skill knowledge, and baseline variables (nicotine dependence, e-cig use frequency, sex) and other tobacco product use on outcomes. Aim 2: Identify strategies for dissemination and implementation of the app within schools. Individual qualitative interviews with up to 50% of youth in the ACTIVE condition will examine likeability of the app and engagement methods used, how to disseminate the app to youth in school settings. Interviews with 20 school staff/administrators will examine how the app could be implemented and used within the school setting. Thus, this innovative proposal will support the testing, as well as dissemination and implementation within schools, of an appealing digital app that addresses the critical need for an adolescent-focused e-cigarette cessation intervention.

NIH Research Projects · FY 2025 · 2024-09

Project Summary New solutions are desperately needed to reduce the annual global burden of dengue. As we have witnessed for SARS-CoV-2, virus genomics can be harnessed to directly inform public health control measures. However, for most other pathogens, including dengue virus, the depth of genomic information needed for such applications is lacking. For dengue virus, part of the issue is its complexity: it is comprised of four genetically distinct serotypes with many defined genotypes and even more undefined variants. Furthermore, current surveillance and research programs are not optimized to fully leverage virus genomics. This proposal aims to bridge this gap by proposing a detailed phylogenetic analysis to uncover critical dengue epidemiological processes, including the outbreak emergence interval and pattern of spread. Through this initiative, our understanding of dengue virus diversity, evolution, and epidemiology will significantly advance. The proposed research, which integrates insights from the COVID-19 pandemic and the 2014-2016 West African Ebola outbreak, aims to determine which DENV lineages were integral to past outbreaks and explore the temporal and geographic factors influencing their persistence. The anticipated outcomes encompass the identification of DENV lineages responsible for causing outbreaks, estimation of average emergence intervals, and insights into the factors impacting lineage persistence. These findings can revolutionize DENV disease forecasting and contribute to the development of genomics-informed control strategies, offering a timely and vital approach to addressing the escalating challenge of dengue transmission globally.

NSF Awards · FY 2024 · 2024-09

Our workshop aims to explore how the emerging quantum systems enable and expand novel Computer Systems Research (CSR) opportunities and promoting cross-disciplinary collaborations. Computer systems researchers possess expertise in building efficient programming environments, modeling and optimizing large-scale systems, and designing architectures for fault tolerance and performance. The workshop will highlight the necessity of rethinking the Quantum Computing (QC) software stack to efficiently process and respond to real-time events and data from quantum hardware. As quantum hardware scales up and becomes more heterogeneous and distributed, the quantum OS will be essential for executing error-correcting kernels, allocating system resources, managing shared quantum memory, and scheduling batch and concurrent programs. The quantum Operating System (OS) is a critical tool for maintaining precision control of large quantum systems and managing quantum resources for practical QC applications. Recent advancements in QC platforms have not only improved the quantity and quality of qubits but also introduced new capabilities such as mid-circuit measurements and real-time error detection. These advancements open new opportunities for exploring algorithms and quantum error correction protocols, but they also add significant complexity to the control systems and the programming/compilation toolchain. For example, significant improvements are needed in integrating classical high-performance computing resources with QC, developing software for optimizing and executing dynamic quantum circuits, benchmarking and verifying real-time control systems. As a result, this workshop will inform the CSR community emerging trends of QC technologies and introduce research recommendations to address scalable and reliable software systems to achieve practical QC applications. This workshop will bring together researchers with expert knowledge across algorithms, software, architecture and physical devices to stimulate discussion and foster collaborations. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NIH Research Projects · FY 2025 · 2024-09

PROJECT SUMMARY: Although the detection of gene expression by quantitative PCR, bulk or single cell RNA sequencing represents a cornerstone of biological inquiry, these approaches are limited in their ability to measure transcriptional dynamics over time and throughout the spatial heterogeneity of tissues, and to detect low-abundance transcripts including those from cytokines. Cytokine expression shapes the infiltration and activity of immune cells in tumors and tissues and represents an important correlate of response to immunotherapy. However, cytokine expression is context-dependent, pleiotropic, dynamic and asynchronous. As such, it is particularly poorly suited to single ‘snapshot’ measurements in time, or the detection of a single or even a few inflammatory mediators in isolation. To address these challenges, we will combine advances in CRISPR- mediated transcriptional activation technology with genetically-encoded set reporting, to fluorescently report the transcriptional activity of 9 or more cytokines simultaneously, dynamically and in situ in tissues. We have previously validated the core capability of our system to report single gene expression in preliminary studies and will now optimize its detection capabilities and implement a Cre-Lox-based randomized fluorescent reporter set-encoding strategy to multiplex detection. If successful, our study will establish a novel approach to multiplexed and high-sensitivity CRISPR-based detection of gene expression. It will also produce tools and reagents that can be directly applied to interrogate the basis for tumor microenvironment inflammation and can be adapted for functional genomic and in vivo studies.

NIH Research Projects · FY 2025 · 2024-09

ABSTRACT Excessive alcohol use is a significant and serious public health problem, with 28.6 million US adults meeting diagnostic criteria for current alcohol use disorder (AUD). The stress response is a promising target for understanding vulnerability and possible intervention, as risky drinking patterns are deeply and bidirectionally linked to stress responses. However, key characteristics of the stress response have not yet been leveraged: as studies to date have focused on individual brain regions and static snapshots of brain responses, we cannot capture the predictive potential of the multifaceted stress response, which involves widespread interactions between brain regions and unfolds dynamically over time. Indeed, recent evidence indicates that dynamic whole- brain responses can provide unique insight into stress-related conditions. The goal of this R01 is to leverage advances in machine learning and computational modeling to develop and validate whole-brain biomarkers for stress, and test whether dynamic engagement of these stress networks can predict individual differences in drinking and alcohol-related cognition. Using a combination of secondary analysis (N = 390) and new collection of functional MRI data (N = 100), we will identify and validate stress-predictive neuromarkers, capture dynamic trajectories of stress neuromarkers, and test the consequences of these moment-to-moment dynamics for cognitive mechanisms driving risky drinking. In Aim 1, we will build a connectome-based model that predicts responses to multiple modalities of stress exposure in previously unseen individuals using rigorous cross- validation techniques. We will identify functional connections that predict stress responses in clinically heterogeneous samples as well as those specific to individuals with AUD. In Aim 2, we will create a novel moment-to-moment framework to characterize stress response trajectories in the brain and their alterations in AUD. This framework will enable us to test the hypothesis that, rather than simply having higher or lower engagement of a stress-predictive network, individuals with AUD will show atypical stress network engagement trajectories in response to a stressful event. In Aim 3, we will develop a novel neuroimaging paradigm to quantify the temporal dynamics of brain stress network engagement on memory formation and subsequent drinking. With this design, we will test the hypotheses that: 1) information that is temporally and conceptually congruent with stress will be preferentially encoded; 2) dynamic stress networks will co-fluctuate with a validated neuromarker of attention to facilitate learning; and 3) the timecourse and neural networks by which stress dynamically modulates learning will differ in AUD and predict future drinking. Together, this work will provide new insight into the brain’s stress response, including the ways in which its neural architecture (where), temporal dynamics (when), and consequences for adaptive cognition (how), are predictive of chronic alcohol. The long-term goal of this work is to develop clinically actionable neurocognitive markers of heavy drinking for early assessment, intervention, and treatment. Future grants will apply this framework to predict treatment and relapse outcomes.

NIH Research Projects · FY 2025 · 2024-09

Project Summary The development of specific therapeutics infectious coronaviruses remains a significant challenge and requires a detailed mechanistic understanding of virus–host cell interactions and viral pathogenesis. A potential target for therapeutic intervention is the nonstructural protein 1 (Nsp1), a major virulence factor produced by alpha- and beta-coronavirus (α-, β-CoV) that regulates host gene expression. Nsp1 is a key player in a strategy deemed “host shutoff,” in which expression pathways are shifted from host to viral genes, allowing for virus proliferation and immune evasion. Biochemical and structural studies have shown that Nsp1 exerts direct translational control, in certain cases binding to the 40S ribosomal subunit with nanomolar affinity. The structurally conserved N-terminal core of the protein is thought to be critical for its function, yet its contribution to Nsp1’s mechanisms remain unclear. Furthermore, α-CoV Nsp1s only contain and function solely through this core. Structural studies with Nsp1 and the ribosome together have yet to resolve the Nsp1 N-terminus, generating a gap in knowledge regarding this domain and the protein’s overall function, and impeding the development of effective drug candidates targeting Nsp1. The goal of this proposal is to uncover structural insights into the Nsp1 N-terminal core and establish Nsp1’s specificity in enacting host shut-off, focusing on Nsp1 proteins in human alpha-coronaviruses. The study will contribute to the long-term goal of understanding coronavirus pathogenesis and evolution and developing effective therapies against the many prevalent diseases caused by coronaviruses.

NIH Research Projects · FY 2025 · 2024-09

PROJECT SUMMARY Mitral valve prolapse (MVP), a condition affecting 2-3% of the general populace, is typified by irregular thickening of valve leaflets. The histopathological modifications associated with MVP are well known, yet a comprehensive understanding of the specific molecular structures and their impact on the disease's onset remains elusive. Bulk RNA-sequencing has been utilized to investigate gene expression in MVP, although inconsistencies between these data and those derived from traditional IHC and RT-PCR analysis have been observed. This discrepancy may be due to the fact that averaged expression cannot accurately portray heterogeneity across different cellular populations. At present, the study of MVP mitral valve leaflet samples using single-cell approaches is considerably limited. Moreover, spatial omics methodologies, capable of illustrating the spatial heterogeneity within tissue microenvironments, have not been applied to MVP research. To address this knowledge gap, we intend to construct a single-cell and spatial molecular atlas using mitral valve leaflet samples from both MVP patients and healthy contributors. In-depth data analysis will enable us to elucidate the molecular underpinnings of the disease. In this endeavor, we will focus on three specific objectives: 1) we aim to accurately identify cell subpopulations and molecular states in MVP using single-nucleus multi-omics sequencing; 2) we plan to characterize MVP's mitral valve tissue through spatially resolved transcriptomic, epigenomic, and proteomic techniques such as spatial-CITE-seq and spatial ATAC-seq; 3) we will extend our research to construct a molecular atlas of Marfan syndrome MVP utilizing single-cell and spatial omics analysis. In sum, the molecular data and insights gained from this research will facilitate further exploration into the diverse cell populations and tissue microenvironment associated with MVP.

NIH Research Projects · FY 2025 · 2024-09

Project Summary/Abstract: Alterations in the immune system occur with aging, likely contributing to infections and malignancies. In T cells, probably the most prominent change with aging is memory T cell expansion. A possible mechanism for this finding is immune stimulation over a lifetime. The nucleotide binding domain and leucine-rich-repeat-containing (NLR) protein X1 or NLRX1 located in mitochondria is a negative regulator of multiple inflammatory pathways including the retinoic acid-inducible gene I (RIG-I), NLR pyrin domain containing 3 (NLRP3) inflammasome, and NF-κB signaling. Our published and preliminary studies support the possible implication of NLRX1 in aging. Aging induced the reduction of NLRX1 in murine lungs. The lungs from whole body NLRX1 null mutant (-/-) or knockout (KO) mice revealed increased lung compliance, a key feature of the “aging lung”8. Of interest, we found decreased expression of NLRX1 in peripheral blood mononuclear cells (PBMCs) of older adults, raising the implication of NLRX1 in immune aging. Indeed, the NLRX1 KO mice have changes in T cell immunity known to occur with aging. These changes include an expansion of memory CD4+ and CD8+ T cells, decreased naïve T cell survival and IL-2 production, increased T cell exhaustion molecules and effector cytokine IFN-γ. Our RNA-seq analysis on effector memory (EM) CD4+ T cells of WT and NLRX1 KO mice highlighted an aging-like change in the global gene expression profile in NLRX1 KO mice, implying the role of NLRX1 in altering T cell immunity with aging. This point is further supported by noticing well-known age-associated changes in NLRX1 KO mice, including reduced mitochondrial mass, nicotinamide adenine dinucleotide (NAD+) and SIRT1 as well as enhanced mitochondrial reactive oxygen species (ROS), mTOR activation, hypoxia-inducible factor 1-alpha (HIF-1α) expression and cellular exhaustion which are mechanistically linked. However, our understanding remains poor about how NLRX1 plays in altering T cell immunity in the context of aging biology and whether such changes can be restored by increasing NLRX1 in aged hosts. Here we address this question based on the hypotheses that decreased NLRX1 augments T cell aging by mechanistically affecting a set of aging-associated molecules (i.e., mitochondrial ROS, NAD+, SIRT1, and mTOR) and that such aging-associated changes can be improved by restoring NLRX1 expression in old mice. The goal of our proposal is to test these hypotheses with the following specific aims: 1) Aim 1. Elucidate the mechanism of how NLRX1 deficiency alters T cell characteristics, especially ones related to immune aging; 2) Aim 2. Elucidate the implication of mitochondrial ROS and NAD+ in inducing T cell immunity changes via affecting mTOR activity in NLRX1 KO mice; and 3) Aim 3. Elucidate whether restoration of NLRX1 in vivo can attenuate aging-associated changes in T cell immunity. The results of our study will reveal a novel mechanism of T cell aging in the setting of decreased NLRX1, providing a potential anti-aging strategy by restoring NLRX1.

NSF Awards · FY 2024 · 2024-09

Researchers and engineers worldwide are racing to build quantum computers to solve computationally challenging problems, enabling new scientific discoveries and generating valuable intellectual property and data. Decades of research have shown that wherever valuable or sensitive information is on a computer system, it's at risk of being stolen or attacked. To understand and mitigate security risks, this project proactively studies system security for quantum computers. The project focuses on fundamental security vulnerabilities that can affect existing noisy intermediate-scale quantum computers and upcoming fault-tolerant quantum computers. This project also studies remediation for both hardware-specific and agnostic side-channel vulnerabilities. The project's broader significance and importance are rooted in the need to democratize access to costly and scarce quantum hardware by sharing it efficiently among multiple users while ensuring secure and confidential computations to foster innovation. The team also integrates the research into educational components by conducting tutorials and workshops and developing course materials. The project studies and develops a secure execution model for quantum computers by building prototypes of a novel quantum trusted execution environment and developing a systematic understanding and defenses for physical attacks on quantum computing systems. Given rapid advances in quantum error correction, the project targets fault-tolerant quantum computing architectures, specifically focusing on developing remediation techniques to prevent physical attacks, including timing, power-based, and other side channels arising at large scales. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NIH Research Projects · FY 2025 · 2024-09

Abstract: Seasonal influenza causes a significant burden of disease in low-middle income countries, specifically in some of the most vulnerable populations such as infants, pregnant women, and the elderly. Influenza spreads primarily within households and while this has been extensively studied in the high-income countries, there remains a significant gap in the literature around household transmission of influenza in low-middle income countries. Differences in population structure, household membership, vaccine availability, and contact patterns make it difficult to apply knowledge from high to low-middle income countries. Understanding household transmission of influenza in this setting will help to generate key epidemiologic parameters of influenza such as secondary attack rate and help to model potential interventions to decrease transmission. This K23 offers an outstanding opportunity to leverage respiratory and serologic samples from a household- based cohort with self-reported and sensor-based social contact data who were followed prospectively for any respiratory illness in three low-middle income countries: Guatemala, Mozamique, India. Our approach will be to use established molecular techniques including hemagglutination inhibition assay and RT-PCR to calculate seroprevalence curves, the force of infection, and with-in household secondary attack rates. We will the develop a heterogenous chain binomial model of within household transmission by incorporating household contact data and risk of infectious between pairs of individuals in the household. Aim 1 is to quantify the spread of with-in household transmission of influenza. Aim 2 is to develop a heterogenous chain binomial model of within household transmission with the hopes of projecting how effective different interventions such as vaccination and masking are in mitigating intra-household influenza transmission. To complete this project, I will require additional training in infectious disease modeling, advanced methods in infectious disease quantification, influenza epidemiology and emerging infectious diseases. To help ensure this projects success, I am surrounded an international team of experts in influenza epidemiology and infectious disease modeling with whom I have established relationships. This K23 award would provide the crucial link in my career from having a foundation in infectious disease epidemiology to having an expertise in infectious disease modeling. At the end of this award period, I will be prepared to submit a strong NIH R01 application focused on modeling emerging infectious diseases transmission in low-resource settings.

NIH Research Projects · FY 2025 · 2024-09

PROJECT SUMMARY Helicobacter pylori infection is commonly associated with several gastric diseases including gastritis, peptic ulcer disease, lymphoma of the mucosa-associated lymphoid tissue, and gastric adenocarcinoma. H. pylori has evolved various mechanisms to evade the host innate immune response, and as a result, these bacteria can thrive for decades in the gastric mucosa. Chronic infection elicits the continuous generation of reactive oxygen species (ROS) by neutrophils and gastric epithelial cells. Elevated levels of ROS can damage macromolecules, and previous studies have focused on how ROS mediate DNA damage during infection. However, ROS can also generate oxidative post-translational modifications on host proteins containing redox-sensitive cysteines that regulate important cellular functions. Our lab previously performed a chemical proteomic screen to identify cysteines in host proteins that exhibit decreased reactivity during H. pylori infection of human gastric cancer cells. This proposal will focus on two ribosomal proteins, uL14 and eS27, which contain cysteine residues that were among the top hits from this screen. Host translational inhibition is a well-characterized response to infection by several microbes, and Aim 1 of this proposal will elucidate whether ribosome biogenesis and translational function are similarly affected during H. pylori infection. Aim 2 will focus on characterizing how the reactivity of the specific cysteines Cys125 of uL14 and Cys77 of eS27 contributes to the cellular localization and interactions of the ribosomal proteins. Overall, this proposal will provide insight into how redox regulation of host ribosomal proteins affects their function and expand our understanding of host cellular processes that are modulated by H. pylori infection.

NIH Research Projects · FY 2025 · 2024-09

Project Summary/Abstract Congenital Heart Disease (CHD) is the most prevalent birth defect affecting 1% of live births and is one the top causes of infant mortality worldwide. Heterotaxy (HTX) is a severe form of CHD resulting from abnormal left- right (LR) patterning during embryonic development. Heterotaxy is highly genetic, yet the complex genetic underpinnings of this potentially life-threatening disorder remain poorly understood. Whole exome sequencing of two siblings born with heterotaxy symptoms identified a novel CHD gene Trinucleotide Repeat Containing Protein 18, TNRC18. TNRC18 is understudied with only one, recent study investigating its function. A preliminary loss-of-function (LOF) screen in the high-throughput human disease model Xenopus resulted in malformation of the cardiac outflow tract and LR patterning defects, recapitulating the patient phenotype. Thus, the overall goal of this proposal is to elucidate the molecular mechanism by which abnormal TNRC18 leads defects in LR patterning and CHD/HTX. The first aim will use LOF experiments to determine the earliest role of TNRC18 in LR patterning cascade by visualizing global pitx2c expression and dand5 expression in the left-right organizer. Determination of spatiotemporal tnrc18 expression in early development in will focus subsequent mechanistic analysis. The second aim will explore the functional significance of TNRC18 patient variants and whether the BAH domain known to have significance for chromatin modification also impacts development. Together, these experiments will elucidate the role of tnrc18 in left-right patterning, cardiac development, and CHD pathogenesis. This will aid future patient diagnosis and outcomes as their treatment can be targeted to genotype in addition to CHD phenotype. This application also outlines my (the applicant’s) training plan in advanced coursework, research mentorship, new techniques, and professional skills including written and oral data presentation. This training plan will equip me with the skills to pursue a career as an independent physician-scientist.

NIH Research Projects · FY 2026 · 2024-09

Project Summary There have been numerous outbreaks of human immunodeficiency virus (HIV) among people who use drugs (PWUD) since the well-publicized outbreak in Scott County, Indiana in 2015. In addition to HIV infections, hepatitis C virus (HCV) infections, skin and soft tissue infections (SSTI), sexually transmitted infections (STIs), and infective endocarditis (IE) commonly occur among PWUD, along with fatal and non-fatal overdoses (ODs). Furthermore, for the past decade rates of syphilis have risen dramatically among PWUD, both among injectors and non-injectors, creating additional risk for HIV transmission through sexual contact. This has created a “converging public health crisis” that threatens the success of the federal Ending the HIV Epidemic initiative in the United States (US). No single prevention or containment approach is going to end the HIV epidemic among PWUD. We require an integrated set of strategies that address outbreaks at different stages of their life cycle. In this proposal, we will develop and evaluate a portfolio of novel methods that will permit decision makers to predict and detect new outbreaks and get patients diagnosed with greater speed, accuracy, and efficiency. In short, we aim to intervene at three critical stages in outbreak emergence: 1) Prediction: we will build on our prior work to develop and evaluate modeling and pattern-recognition frameworks that permit the earliest and most reliable forecasts possible of jurisdictions at high risk of incipient outbreaks; 2) Detection: we will develop novel algorithms to minimize the time it takes to detect new outbreaks once they have begun; and finally; 3) Diagnosis: we will expand upon our previous work to optimize sampling and search algorithms to diagnose previously undiagnosed cases through community-based active case finding. The proposed studies will provide a novel framework for addressing outbreaks of infectious diseases, from potential threat, to emerging outbreak, to endemic persistence, offering methodological innovations alongside the development of practical decision support tools for health departments around the country in addressing the most serious infectious complications of substance use. These tools will be designed to make it easier to pinpoint locales at risk of outbreaks among PWUD, more quickly identify them when they do occur, and find patients in need of care more efficiently as public health officials seek to manage these outbreaks. However, while these tools will be designed for HIV infection, particularly in the context of drug use, they are pathogen- and population- agnostic and can be used in the context of active surveillance for other infectious diseases and among other demographic groups.

NIH Research Projects · FY 2026 · 2024-09

Despite the high prevalence of pregnancy loss during the early post-implantation period, a detailed understanding of cell and molecular workings at this stage of development remains elusive. During this period, specification of the principal lineages of the future body occurs at the gastrulation stage, an evolutionary conserved landmark event in life. While early embryonic cells are known to be sensitive to the changes in the metabolite availability in their immediate surroundings, extremely little is known about the role of the intrauterine metabolic environment during gastrulation and how it shapes embryo viability. The maternal metabolic environment can be disrupted via somatic mutations in metabolic enzymes, such as the gain-of-function mutation IDH2R140Q. This mutation leads to the conversion of the tricarboxylic acid cycle metabolite alpha-ketoglutarate (αKG) into the epigenetically active metabolite 2-hydroxyglutarate (2-HG), which subsequently accumulates in the bloodstream of affected patients and has downstream metabolic effects. In my preliminary work, I have modeling maternal metabolic dysfunction by inducing this mutation in results in significant developmental delays at the time of gastrulation and failure to form distinct primary germ layers. My work also revealed increased histone methylation, as well as differential expression of genes involved in key developmental processes, such as cellular migration, as a response to 2-HG exposure in 2D cell culture. Collectively, these findings suggest that maternal metabolic dysfunction driven by mutant IDH is prohibitive to proper gastrulation. In light of these findings, I hypothesize that maternal 2-HG accumulation disrupts primary germ layer formation via both bioenergetic and epigenetic mechanisms. My first aim is to characterize the impact of IDH2R140Q-driven maternal metabolic dysfunction on primary germ layer formation. I will characterize the morphological effects of maternal 2-HG accumulation using high-resolution 3D confocal microscopy to investigate the spatiotemporal dynamics of germ layer cell specification and expansion. I further will characterize the changes in mitochondrial activity and cell death caused by maternal 2-HG accumulation using fluorescence-based assays. My second aim is to evaluate changes in the embryonic epigenetic landscape caused by maternal 2-HG accumulation. I will identify variable histone modifications in exposed embryos and the associated genomic loci using histone modification profiling followed by Cleavage Under Targets and Tagmentation (CUT&Tag) in the embryonic portion of gastrulas. Together, this project will pave the way toward a mechanistic and functional understanding of how maternal metabolic dysfunction modulates embryonic development as well as adverse pregnancy outcomes. Thus, in addition to providing me with valuable training that will further my career as a developmental biologist and reproductive medicine specialist, the proposed research has significant potential to provide a rich source of new molecular and cellular targets for therapeutic intervention in clinical settings where embryonic development is compromised.

NIH Research Projects · FY 2025 · 2024-09

Project Summary There is strong association between cannabis use and depression and suicide, but the underlying cellular links are poorly understood. This presents a challenge for understanding how drug use can lead to additional psychiatric disorders. It is believed that cannabis use alters the development of key brain regions which in turn makes the brain more susceptible to additional stressors that could lead to major depressive disorder (MDD). These findings are particularly concerning given the popularity of cannabis legalization. One of the key unsolved problems is how to link drug use with specific molecular changes in the brain that can lead to depression. In this proposal, we take the first steps to bridging this gap. First, we will use innovative single cell type postmortem genomics to identify the molecular (transcriptomic and chromatin) changes occurring in the cannabis use disorder (CUD) brain. We will focus our studies on two discreet brain regions: the dorsolateral prefrontal cortex and the ventral striatum in 120 donors with CUD, MDD, and neurotypical controls. We will use reverse genetic approaches to identify genomic alterations in the CUD brain that harbor GWAS risk signals for MDD. We hypothesize that these alterations lead to widespread epigenomic changes that make the brain vulnerable to stress and developing MDD. We will prioritize a credible set of genomic regions and genes and validate their function in a human iPSC brain organoid model using massively parallel reporting assays (MPRA). We will also test the effect THC (the active compound in cannabis) has on these organoids by comparing THC-exposed organoids from donors with a history of CUD (but not MDD) with our MDD postmortem brain genomics to identify convergent molecular mechanism changes. These studies will uncover genes driving MDD pathogenesis and establish if cannabis use shares and drives these mechanisms. We expect this project will open new lines of exploration in the comorbidity of substance use disorders and major depression and contribute broadly to understanding the relationship between gene regulation and functional roles in cannabis use, which may identify new therapeutic targets.

NIH Research Projects · FY 2024 · 2024-09

SUMMARY Pacific Islanders in the US are disproportionately affected by diabetes, obesity, and hypertension. Among US Pacific Islanders, those most at risk are resident in the US-affiliated Pacific Island territories, which are geographically isolated, medically underserved, health professional shortage areas. Despite obesity often being established in childhood, adolescence is a critical time for intervention to prevent associated chronic diseases. In American Samoa, this age group has been completely overlooked in existing efforts to mitigate disease risk. There is a need to intervene on adolescent's individual behaviors, but health-related decisions are not made in vacuum – family, peers, and the wider surrounding environment are important influences. Equally, adolescents play a critical role in food preparation in the Samoan familial structure and are responsible for cooking daily meals for immediate and extended family from early adolescence, thereby shaping familial risk. To date, there has been limited consideration of specific Samoan cultural and social influences on adolescent risk behaviors. The important impacts AS adolescents may have on familial and peer habits have also been underrecognized. Therefore, the central premise of this thesis is to understand the distribution of obesity, diabetes, and hypertension, and factors associated with these conditions, in the adolescent population in American Samoa. With this proposal we will: (1) use qualitative methods to identify factors influencing healthful nutrition among American Samoan adolescents; (2) employ a school-based survey to identify factors associated with obesity, diabetes, and hypertension in adolescents in American Samoa; and (3) use social network analysis to examine the patterning of obesity, diabetes, and hypertension among friendship networks in American Samoa. Findings from this work are expected to enhance our understanding of the range of behavioral and social influences on chronic disease risk in this setting and to concretely inform future intervention strategies. Importantly, the findings are likely to translate to Pacific Islander adolescents in other settings in the US and US-affiliated Pacific Islands. Through this work the applicant will develop skills in qualitive methods, advanced epidemiologic study design and management of epidemiological surveys, and social network analysis. This training is central to the applicant's long-term goal of become a Pacific-focused noncommunicable disease epidemiologist integrating advanced epidemiologic methods with locally relevant interventions to support health promotion in Pacific Island communities.

NIH Research Projects · FY 2025 · 2024-09

Anxiety disorders are the most prevalent childhood psychiatric disorders, impacting up to one third of youth. Pediatric anxiety disorders are highly impairing and, when not effectively addressed in childhood, persist across the lifespan and predict the onset of additional psychiatric disorders. Up to 50% of youth who receive the current first-line psychosocial treatment for pediatric anxiety do not sufficiently improve, highlighting the urgent need to improve treatment response rates. Prior research underscores the critical role of parents in supporting children’s fear regulation. Across species, parental presence is associated with alterations in key corticolimbic circuitry associated with fear regulation. In healthy youth, parental modulation of corticolimbic circuitry is in turn linked with reductions in anxiety. However, youth with anxiety disorders may be at risk for becoming overly reliant on parents for fear reduction. The vast majority of anxious youth (90%) report relying on their parent to help regulate their anxiety, and 97% of parents of youth with anxious children report accommodating their child’s anxiety by engaging in behaviors to reduce their child’s distress. Although accommodation reduces children’s anxiety in the short-term, it contributes to the maintenance and worsening of anxiety in the long-term. Supportive Parenting for Anxious Childhood Emotions (SPACE) offers an entirely parent-based alternative to traditional child-focused treatment that directly addresses parental accommodation of anxiety and targets parental modulation of their child’s medial prefrontal cortex activation to fearful stimuli. While SPACE has established efficacy, it is unlikely to be equally effective for all families, and questions remain regarding which families are likely to benefit most from this targeted intervention. The current multimodal study aims to identify specific pre-treatment predictors of the efficacy of SPACE as a step towards personalized treatment for pediatric anxiety disorders. A well-characterized sample of children with anxiety disorders (n=212, ages 6-12 years) completed an fMRI paradigm assessing youth’s neural reactivity to fearful face stimuli in the presence versus absence of a parent. A subset of families was then randomized to complete 12 sessions of SPACE (n=106) as part of an ongoing R61/R33-funded trial. Aim 1 will use a whole-brain approach to identify neural mechanisms related to parental accommodation of youth’s anxiety pre-treatment. Aim 2 will examine how pre-treatment individual differences in these neural and behavioral factors relate to changes in anxiety symptoms following SPACE. Finally, Aim 3 will use connectome-based predictive modeling to predict the efficacy of SPACE based on pre-treatment patterns of task-based functional connectivity. This study has important implications for improving our mechanistic and clinical understanding of family-level factors involved in anxiety. The results of this study could ultimately improve our ability to determine which families would benefit most from SPACE and thus mark an important step towards personalizing treatment for pediatric anxiety disorders.

NIH Research Projects · FY 2025 · 2024-09

PROJECT SUMMARY/ABSTRACT Alcohol directly stimulates the hypothalamic-pituitary-adrenal (HPA) axis, a primary stress system, initiating the release of glucocorticoid hormones. Preclinical work indicates that chronic alcohol exposure increases both brain and peripheral corticosterone in rodents, with some studies suggesting greater increases in the brain. These increases in rodent brain glucocorticoid levels are prolonged and persist long after plasma corticosterone returns to baseline. Thus, brain glucocorticoid dysfunction may underlie long-lasting, persistent alcohol use. Studies of HPA axis dysregulation in humans with alcohol use disorder (AUD) have only examined peripheral cortisol in relation to alcohol and with mixed results. Chronic alcohol use is associated with both elevated and blunted levels of peripheral cortisol in response to alcohol and stress in individuals with AUD. So, what we know about HPA dysregulation in AUD is based solely on peripheral cortisol, and results are inconsistent and incomplete because we have not been able to study a marker of brain cortisol - forming a significant gap in the existing literature. Translating preclinical findings in the brain to human AUD and examining the relationship between brain-peripheral cortisol is a critical next step in understanding HPA dysfunction in this population. Levels of glucocorticoids in the brain are dependent on the enzyme 11β- Hydroxysteroid dehydrogenase type 1 (11β-HSD1), which catalyzes the conversion of cortisone to cortisol (or corticosterone in rodents). 11β-HSD1 is expressed in brain regions critical to alcohol addiction, including the amygdala and prefrontal cortex (PFC). Using a novel radiotracer called [18F]FMOZAT together with Positron Emission Tomography (PET) brain imaging, we can now measure levels of 11β-HSD1 in the living human brain. Using these methods, we have exciting preliminary data (obtained through K01AA025670) suggesting that individuals with AUD (n=9) have higher 11β-HSD1 availability compared to healthy controls (n=12) in prefrontal-limbic regions. Preliminary data also demonstrate that 11β-HSD1 availability in ventromedial PFC is associated with drinks per week, quantity of drinks per drinking episode, and AUD severity. However, we do not know how 11β-HSD1 availability in brain corresponds to peripheral cortisol in humans, and whether brain vs. periphery predicts drinking behavior. This proposal will derive critical foundational information on brainperiphery HPA axis dysregulation by: fully characterizing both availability of 11β-HSD1, a cortisol regenerating enzyme, in brain and peripheral cortisol in those with AUD vs. healthy controls, and determining whether brain vs. periphery predicts drinking behavior (Primary Aim 1). We will also evaluate whether 11β-HSD1 availability vs. peripheral cortisol predict stress-related drinking using EMA and a biosensor system in individuals with AUD compared to healthy controls (Exploratory Aim 2). This will build the future foundation for additional mechanistic studies probing the HPA axis and provide needed data to support translational upstream HPA axis targets as AUD treatments in humans.

NIH Research Projects · FY 2025 · 2024-09

PROJECT SUMMARY The field of human neuroimaging has long been suffering from a problem of low power, in which low signal-to- noise ratio, multiple comparisons, and small sample sizes result in insufficient statistical power for many studies. For studies attempting to reveal brain-behavior relationships via functional and structural connectomes, which are a matrix representation for statistical and physical relationships between brain regions, the story is the same. From a scientific perspective, this issue reduces the number of findings presented in the literature while also lowering the replicability of any findings. Since connectomics research strives to ultimately be clinically relevant by, for example, predicting risk for mental health conditions or informing personalized treatment approaches for those with existing illness, this problem of low power greatly hinders progress. Fortunately, recent work has introduced a framework shift in statistics whereby an emphasis on brain networks, rather than individual connections or edges, improves overall statistical power in functional connectivity analyses. Further work has shown that using information of the relationships between edges in the connectome to construct the networks results in even greater power increases, but it is not yet known whether deriving networks within-dataset is more effective than using independent networks. Therefore, this proposal will investigate whether using within-dataset networks in network-level statistical procedures results in further power increases. It will also test these network- level approaches that were developed in functional datasets on the structural connectome. In Aim 1, I will use data from 3 large functional connectivity datasets spanning several phenotypes to examine if creating the networks in the same dataset that undergoes statistical testing will offer power improvements over deriving networks from an independent dataset. In Aim 2, I will evaluate the utility of network-level statistical procedures in the structural connectome, and in Aim 3, I will extend the methodology from Aim 1 to the structural connectome to comprehensively determine whether the results seen in the functional connectome extend to the structural connectome. This work will improve understanding of which variables we can manipulate to achieve higher statistical power in human connectivity studies and lead the field towards eventual clinical relevance by improving the neuroimaging tools available to mental health researchers.

NIH Research Projects · FY 2025 · 2024-09

PROJECT SUMMARY. Progression to metastatic disease from Non-Small Cell Lung Cancer (NSCLC) is a significant cause of mortality. Central nervous system (CNS) metastases, which carry poor prognosis and limited treatment options, can form intraparenchymally (IP) within the tissue of the brain or within the cerebrospinal fluid (CSF) filled spaces between the leptomeninges. The latter, termed leptomeningeal disease (LMD), is difficult to diagnose and treat, and the pathophysiological mechanisms underlying progression to LMD are poorly understood. 60% of patients with LMD have past or concurrent IP metastases, but the mechanisms promoting a switch to LMD invasion remain unknown. Interestingly, patients with EGFR-mutant NSCLC are more likely to progress to LMD, particularly at resistance to tyrosine kinase inhibitors (TKIs), the standard of care for these patients. While third-generation TKIs such as Osimertinib show excellent brain penetrance, resistant CNS disease, including LMD, remains a pressing clinical problem. The primary aims of this project are to identify mechanisms underlying progression to and persistence of LMD, and determine what factors favor this progression in cases of TKI-resistant EGFR-mutant disease. I hypothesize that in a subset of IP cases, progression to LMD occurs through invasion of parenchymal cells through the perivascular spaces in the brain, and that this progression is promoted by mechanisms that synergistically foster TKI resistance. I have validated multiple NSCLC murine models of comorbid IP and LMD following intra-arterial injection, including an EGFR- mutant model that emerges at late-stage TKI resistance as well as a syngeneic model. In Aim 1, I will utilize spatiotemporal barcoding of these lines to chart the anatomical routes cells traverse to reach the leptomeningeal space. In particular, I will determine whether LMD metastases descend from parenchymal metastases, or enter the CSF from systemic circulation across the blood-CSF-barrier. I will then assess how pathways downstream of mechanosensing by β1-integrin, previously shown by our laboratory to promote CNS TKI resistance, may modulate the ability of EGFR-mutant cells to complete this journey at resistance. Then, in Aim 2, I will investigate the mechanistic role of the protein Tissue Inhibitor of Metalloproteinases 1 (TIMP-1), identified in our biorepository samples as upregulated in the CSF of patients with LMD. TIMP-1 can signal through β1-Integrin and CD63 to promote anchorage-independent survival, mirroring a phenotype observed in our LMD model lines in vitro. Given the role of β1-integrin in this pathway, I will investigate whether stromal TIMP-1 levels play a dual role in EGFR-mutant LMD by promoting cell survival while also promoting signaling underlying TKI resistance. As a graduate student in Dr. Don Nguyen’s laboratory in the Pathology department at Yale University, I have the support of a diverse array of translational and clinical researchers as my mentors and collaborators. Through completion of the research proposed during the NRSA F31 fellowship, I will hone my experimental skills as I progress towards my goal of becoming an independent researcher in the field of CNS metastases.

NIH Research Projects · FY 2025 · 2024-09

7. Project Summary/Abstract Peri-transplantation inflammation of solid organ allografts exacerbates acute cell-mediated rejection and increases late graft loss, primarily caused by chronic rejection. The two most common causes of perioperative inflammation are ischemia reperfusion injury and, in sensitized recipients, pre-formed donor specific antibodies, both of which deposit antibody and complement membrane attack complexes (MACs) on graft endothelial cells (ECs). MAC deposition leads to increased T cell-mediated rejection by inducing expression of surface proteins on the EC surface that intensify host T cell responses. Two such proteins are ICOS-L (which in humans engages T cell CD28) and IL-15/IL-15R (which engages T cell IL-2Rc). We hypothesize that preventing surface expression of these molecules on graft of ECs—i.e “ treating the graft rather than the recipient”—will reduce early T cell-mediated rejection episodes and late term graft loss and thereby allow reductions in systemic immunosuppression. In aim 1, we will develop and optimize new antibody-targeted, degradable solid polyamine co-ester (PACE) nanoparticles (NPs) that can be administered during ex vivo normothermic machine perfusion and deliver therapeutic siRNAs selectively to ECs that we have shown can prevent these molecules from being expressed. Solid NPs can slowly release the siRNAs and we will evaluate efficacy and duration of effects in both cultured cells and perfused human vessel segments. We will then use these model systems to evaluate changes in allogeneic T cell responses in vitro and, in the case of arteries, in vivo transplant into human immune system mice. In Aim 2, we will develop antibody-targeted liquid PACE NPs (polyplexes) to deliver mRNAs encoding Cas enzymes and guide strands that can produce permanent gene disruption or epigenetic silencing and test these in the same model systems. In Aim 3, we will further develop approaches to optimize delivery of the antibody-targeted NPs to ECs of human kidneys and hearts that have been declined for transplantation using established methods of ex vivo normothermic machine perfusion. These experiments will exploit advances already made by our team, such as fibrinolytic clearing of fibrinogen/erythrocyte occlusions of graft vasculature to increase access to the whole vasculature and improved coupling of targeting antibodies using monobody adapters that greatly enhance binding to ECs. Additionally, we will develop a mouse model of transplant to allow testing of efficacy vs. a fully replete immune system. The technologies developed in all three aims can be readily adapted for use against other EC targets.