Yale University

NIH Research Projects · FY 2024 · 2024-07

Lung cancer is the leading cause of cancer-related mortality in the United States, and non-small cell lung cancer (NSCLC) comprises over 80 percent of all types of lung cancer. The tumor microenvironment plays an important role in cancer progression and tumor endothelial cells (TECs) are critical components of this microenvironment. TECs harbor molecular abnormalities that keeps them in a persistent “activated” state and are also chronically stimulated by cytokines in the tumor microenvironment. In this proposal, we will study the significance of a molecular abnormality in TECs, that is induced by vascular endothelial growth factor (VEGF) and regulates the levels of microRNAs (miRNAs). MiRNAs are small (21-22 nucleotides) noncoding RNAs that regulate gene expression by recruiting messenger RNAs to the RNA-induced silencing complex (RISC). MiR-1 is a flagship example of a tumor suppressor miRNA. We have previously shown that miR-1 levels in TECs isolated from NSCLC patients are significantly lower than endothelial cells isolated from the non-cancerous lung tissues. Moreover, overexpression of miR-1 specifically in endothelium decreased tumor burden and vascularity in KRAS-mutant, P53 knock-out (KP) mice, showing that the downregulation of miR-1 is critical for NSCLC tumor angiogenesis and progression. A mechanistic investigation on miR-1 downregulation in endothelial cells showed that VEGF downregulates mature miR-1 without altering the transcription, processing, or loading of its precursors on RISC. i.e it degrades mature miR-1. One of the main mechanisms of selective mature miRNA degradation is the modification and trimming of its 3' end. This process produces 3’ miRNA variants (isomiRs). A small RNA sequencing analysis on VEGF-stimulated endothelial cells revealed the emergence of unique 3’-adenylated and -trimmed isomiRs in these cells, suggesting that 3’-adenylation triggers miR-1 degradation. In accord with this finding, VEGF stimulation selectively increased the expression of terminal nucleotidyltransferase 2 (TENT2), the main enzyme known to adenylate miRNA 3’ end. TENT2 expression was also increased after VEGF stimulation in TECs isolated from NSCLC patients. We preliminarily assessed the role of TENT2 in miR-1 regulation and angiogenesis by testing the effects of its knockdown. These experiments showed that TENT2 knockdown increases miR-1 levels, inhibits endothelial cell proliferation, and decreases the tumor burden in KP mice. Based on these findings we have hypothesized that: TENT2 triggers miR-1 degradation in TECs via the non-templated addition of adenines to its 3' end and through this mechanism regulates tumor angiogenesis and progression in NSCLC. To test this hypothesis, we propose following aims: Aim 1: To determine the role of TENT2 in miRNA adenylation and degradation in the tumor endothelium. Aim 2: To determine the role of endothelial TENT2 in NSCLC tumor angiogenesis and progression

NIH Research Projects · FY 2026 · 2024-07

Summary The vascular system constantly remodels in response to tissue growth or changes in metabolism to efficiently deliver nutrients and oxygen to tissues. Remodeling encompasses sprouting angiogenesis, arteriogenesis and expanding vessel diameters. Failure of these mechanisms contributes greatly to coronary artery disease, peripheral artery disease and cerebral vascular dysfunction. While many genes and signaling proteins in these processes have been identified, our incomplete understanding of regulatory networks impedes identification of therapeutic targets and development of new treatments for these conditions. Vascular remodeling is regulated principally by VEGF secreted by ischemic cells of the target tissues, and fluid shear stress (FSS) from blood flow that act on vascular endothelial cells (ECs). Our recent work has revealed novel aspects of FSS- dependent remodeling and interactions between FSS and VEGF that determine these processes. But we know little about how these pathways interact to determine tissue-level outcomes. The Kholodenko lab has developed a powerful new method called cell State Transition Assessment and Regulation (cSTAR) for exploiting `omics' data to develop pathway models that can accurately encompass cell regulation, predict outcomes, and identify therapeutic targets. Our three labs will work closely together to acquire quantitative data on interactions within vascular remodeling regulatory networks and develop a quantitative model of vascular remodeling that will be tested in vitro and in vivo. Aim 1 will address the roles of VEGF and FSS in EC fate decisions during angiogenesis and arteriogenesis. Here, we will perturb candidate mediators of FSS and VEGF signaling and measure effects on signaling and gene expression pathways. cSTAR will then identify and precisely quantify causal connections in the regulatory network that guides EC phenotypic transitions to allow purposeful manipulation of EC states and fate decisions, which will then be tested experimentally in vitro. Aim 2 will utilize a similar strategy to address the effects of low, physiological, high and oscillatory FSS that determine artery diameter and disease susceptibility. We will first characterize the effects of FSS profiles on pathway activation, then carry out a perturbation study to determine effects of inhibiting pathways on EC signaling and gene expression. cSTAR will again develop a causal computational model and generate predictions that for testing in vitro. Aim 3 will then test predictions in vivo in mice, deleting candidate genes and observing the impact on vascular remodeling. Together, these studies will develop a novel experimental- computational approach to elucidate in unprecedented depth the regulatory networks that govern vascular remodeling and develop insights into these biological processes that identify novel therapeutic targets for improving vascular insufficiency in coronary, peripheral and cerebral artery disease.

NIH Research Projects · FY 2025 · 2024-07

PROJECT SUMMARY/ABSTRACT Cerebral palsy (CP) is the most common life-long neuromotor physical mobility. CP affects about1 in 345 newborns each year condition that permanently affects children's in the United States. The etiology of CP is complex and multifactorial. We know that CP is caused by lesions occurring in the developing brain, but what risk factors trigger the developing brain damage remain largely unknown. Newborn asphyxia at delivery only presents in less than 10% of cases. While ambient/household environmental risk factors for CP have long been suspected and discussed, few studies have been conducted to evaluate environmental exposure effects on CP development. Recently, a seasonal pattern of CP occurrence was observed in our California study, where air pollution exposure was suspected to play an important role. Air pollution is one of the most widespread environmental pollutants, and the literature has consistently suggested maternal exposure to ambient air pollution during pregnancy can affect major perinatal predictors of CP, including maternal preeclampsia, preterm birth, and Apgar scores. Moreover, emerging research shows air pollution affects cognitive, neurobehavioral, and motor function deficits in childhood, as well as increases the risk for white matter injury and thinning of the cerebral cortex in the developing brain which are highly relevant to CP etiology. The collective set of scientific evidence points toward a need to thoroughly examine whether air pollution exposure poses a risk to CP development. Our proposed study is novel and will be the first and largest population-based study of CP and air pollution to date. We will use records from the California Department of Developmental Services (DDS) to identify children who were born during 2000-2015 and diagnosed with CP in California. We expect to identify ~10,000 CP cases and we will utilize a case-cohort design and select 20% of births in California during the study period (N=~1.6M births) as the population controls. We will apply a sibling-matched analysis to triangulate the main results. We will utilize a newly developed land-use-regression (LUR) model with a high temporal (daily) and spatial resolution (100m X 100m) to estimate gestational exposures to three major ambient air pollutants (PM2.5, NO2, and O3), study the associations between maternal pregnancy exposures and CP risk using single and multi- pollutant analyses, and explore the critical time window of exposure. Moreover, we will perform causal mediation analyses to examine to what extent the racial/social disparities of CP in California may be explained by environmental disparities in exposure to air pollution, and whether a specific pregnancy complication or adverse birth outcome mediates the association between air pollution exposures and CP risk. Findings from this project will advance our knowledge of suspected environmental risk factors of CP, and possibly inform risk identification and primary prevention of CP. Results from this project will be critical for future research strategies to examine environmental hypotheses of CP, possibly using an approach integrating biomarkers and active data collection.

NIH Research Projects · FY 2025 · 2024-07

PROJECT SUMMARY Thoracic aortopathy – aneurysm, dissection, and rupture – is increasingly responsible for morbidity and mortality in younger (having genetically predisposed lesions) and older (having sporadic lesions) individuals alike, female and male. Despite many seminal discoveries since 1991, when the genetic basis of Marfan syndrome (MFS) was uncovered, advances in clinical care have largely remained limited to improvements in surgical methods and devices as well as better identification of patients who warrant monitoring of aortic diameter until surgery; patients otherwise continue to be treated with anti-hypertensive medications mainly to reduce hemodynamic loads on the vulnerable aorta. There is clearly a need for increased understanding. Although such aortopathy can arise from a predisposing monogenic mutation, we will test the compelling hypothesis that secondary changes in cell signaling and gene expression represent either potentially protective compensations or further pathological consequences, and macrophages play key roles in this regard. We submit that, in the absence of gene editing to correct the predisposing mutation, there is a need to preserve / promote compensatory gene products while preventing pathological ones. Noting further that hypertension is a key risk factor for aortic disease, we hypothesize that detailed associations of the transcriptional profile and biomechanical phenotype will better elucidate mechanisms by which hypertension exacerbates thoracic aortopathy. Toward this end, we will use consistent methods to quantify the transcriptional profile that drives the bio- mechanical phenotype of the aorta in 3 mouse models (2 novel) of Marfan syndrome. In this way, we will quantify, for the first time, specific roles of hypertension as well as two sub-populations of macrophages (resident vs. recruited) to determine regulatory pathways and cell-cell interactions that superimpose on those associated with the underlying predisposing mutation and drive changes in aortic structure and function. We submit that consistent “transcript-to-tissue” level data across these mouse models, as a function of sex as a biological variable, will provide the large data sets needed to develop 2 new classes of multifidelity, multiscale, data- informed computational models that will enable unprecedented integrative understanding of molecular, cellular, and biomechanical mechanisms that drive thoracic aortopathy while providing unique insight into possible new targets for treatment. This project is significant given the increasing morbidity and mortality associated with thoracic aortopathy; it is innovative in its consistent quantification of the transcriptionally driven biomechanical phenotype across diverse mouse models, its use of two new double-mutant mouse models, and its use of novel advanced (multi-cell, multiscale) computational models to integrate findings across predisposing mutation, cell- type, and risk factors to delineate protective versus pathologic factors that dictate disease progression.

NIH Research Projects · FY 2025 · 2024-07

PROJECT SUMMARY Epigenetic perturbations in cancer are widely recognized but poorly understood. A detailed understanding of how latent epigenetic information contributes to tumorigenesis would enable us to stratify risk among vulnerable patients, classify tumors based on epigenetic state, and better target therapeutic approaches. Animal models of early-onset epigenetic perturbation offer a unique opportunity to study the potential contribution of epigenetic signatures to prediction of cancer risk, since epigenetic changes precede tumor initiation in these models and can therefore be separated from secondary effects of tumorigenesis. In preliminary studies, we found that epigenetic changes induced by loss of the epigenetic regulator KDM6A (UTX) in the paternal germ line in mice result in elevated lung tumor burden in offspring even when the mutant Kdm6a allele itself is not inherited, implying that these offspring carry silent epigenetic perturbations that predispose to cancer. These mice are an excellent experimental model for defining signatures of epigenetic sensitization that predict cancer risk. Our central hypothesis is that preexisting, detectable epigenetic perturbations in lung tissue interact with genetic driver mutations to enhance lung tumorigenesis, and that the resulting tumors have a distinct epigenetic and genetic signature. The objective of this study is to define a signature of these preexisting epigenetic changes in the lung in a mouse model and determine if a memory of this signature can be detected in lung tumors. Aim 1 will define the transcriptional and epigenetic phenotypes of normal lung tissue in epigenetically sensitized mice. Aim 2 will evaluate the molecular phenotypes of epigenetically sensitized lung tumors using both spontaneous tumors and tumors induced by activated KRAS. If both are successful, the results of the two Aims will be compared to identify signatures of epigenetic sensitization that are present in histologically normal tissue and that persist in tumors. We expect this work to reveal new markers for epigenetic risk of lung tumorigenesis and define the molecular signatures associated with prior epigenetic sensitization in tumors. Future work will determine the extent to which such signatures can be applied to human populations in the clinic.

NIH Research Projects · FY 2025 · 2024-07

Project Summary Privacy and security of personal information has become one of the major grand challenges in modern society, especially for healthcare studies. Re-identification risks and data breaches require new policies and regulations for data sharing across healthcare institutions and research laboratories. While policy cannot solve the problem on its own, advanced technologies that work hand in hand with policy are important to address the privacy/security concerns. Predictive analytics can support quality improvement, clinical research, and eventually impact patient health status. Extensive clinical variable information and voluminous data records from multiple institutions and laboratories are necessary to further improve the performance of modeling approaches and to identify medication-outcome associations for diseases. Nonetheless, the transfer of such sensitive data among institutions/laboratories can present serious privacy risks, which can jeopardize NIH’s mission. Aiming at mitigating the privacy problem while increasing predictive capability via cross-institutional modeling, prior studies proposed distributed methods to exchange only the predictive models, but not patient data. However, these methods still pose many challenges to the clinical cross-institutional learning problem, including the need for more comprehensive clinical variables and more patient records to achieve better prediction discrimination and build more generalizable models, the necessity for discovery/alleviation of data manipulation to increase the trustworthiness of the collaboratively trained models, and the requirement for more validation to ensure usability. In this proposal, we plan to develop SOCAL (Privacy-protecting Sharing Of Clinical data Across Laboratories), a distributed framework addressing these challenges by integrating vertical/horizontal modeling methods to include both more complete variables and more records, discovering/alleviating data manipulation incidents using models recorded on blockchain, and conducting controlled experiments and designing/testing a web portal with physician-researchers to increase the usability of the system. SOCAL will be evaluated on a Coronavirus Disease 2019 (COVID-19) dataset from five University of California (UC) Health medical centers. We expect the knowledge/capability of collaborative modeling can be improved, the trustworthiness of the learning process can be enhanced, and the framework will be ready for use. SOCAL is innovative because it will be a new integration methodology for vertical/horizontal modeling, a novel data manipulation resisting methods, and a hardened prototype for a practical blockchain application. We anticipate a powerful impact of the SOCAL framework to largely reduce the privacy concerns of predictive modeling tasks for various stakeholders, including healthcare providers, clinical researchers, and patients. Upon completion, SOCAL can accelerate the development of methods/technologies to increase willingness of institutions to participate in such a collaboration for improving the effectiveness of healthcare.

NIH Research Projects · FY 2025 · 2024-07

Alzheimer’s disease (AD) is the leading cause of dementia in older adults. Early diagnosis of AD and AD-related dementias (ADRD) is crucial to both avoiding potentially harmful delays in medical care, and stratifying patients for treatment and research studies. AD pathogenesis is associated with several biomarkers, including brain deposition of amyloid-beta (Aß) plaques and hyperphosphorylated tau, classified by the A/T/N framework. The “A” and “T” represent measures of Aß and tau, respectively. The “N” encompasses biomarkers of neuronal injury and neurodegeneration, including neuronal activity. While reductions in neuronal activity are associated with rapid cognitive decline in ADRD including amnestic AD, neuronal activity has not been established as a sensitive biomarker for AD, possibly due to limitations on current neuroimaging techniques to detect such changes early in disease course. Although 18F-flourodeoxyglucose (FDG) functional positron emission tomography (fPET) measurements can directly quantify neuronal metabolism, the use of FDG-fPET has previously been discouraged by inadequate spatial resolution and sensitivity. Addressing this limitation, the Carson lab and our collaborators recently developed the NeuroEXPLORER (NX), a brain-dedicated PET imaging system with ultra-high sensitivity that is tenfold greater than the current state-of-the-art, the High Resolution Research Tomography (HRRT), with ultra-high resolution and continuous head-motion tracking. Leveraging the ultra-high performance (UHP) of the NX to measure visual-stimulation induced neuronal activity using FDG-fPET could permit reliable measurements of metabolism in small brain regions. Further, several studies have demonstrated olfactory dysfunction (OD) early along ADRD, and Parkinson’s disease progression. However, olfactory impairments specific to AD, that may permit its early detection or distinction from other diseases, have not yet been established. Thus, it is hypothesized that NX FDG-fPET will yield measurements of small differences in olfactory-stimulation induced neuronal activity between ADRD and cognitively normal subjects. Finally, it is hypothesized that NX FDG-fPET signals will be correlated, but temporally and spatially distinguishable from functional magnetic resonance imaging (fMRI). Aim 1 of this study will investigate the capability of the NX to measure dynamic changes in glucose metabolism in small brain nuclei. Aim 2 will investigate the application of a novel paradigm, olfactory-stimulation FDG-fPET, to investigating early neurodegeneration in ADRD. Both aims will compare NX FDG-fPET to fMRI. My research will set the groundwork for future studies evaluating metabolism and tau, using ultra-high sensitivity and resolution, as AD biomarkers, while validating and extending tasks currently reliant on fMRI. The rigorous research skills I will obtain throughout this study, in combination with my training plan and excellent mentorship will prepare me to become an independent physician-scientist.

NSF Awards · FY 2024 · 2024-07

Systems software, such as an operating system, is relied upon by the applications and services built upon it. However, due to rapidly evolving complexity, ensuring the correctness of systems software through formal verification, which provides very strong guarantees, is costly. This project leverages the type system of the Rust programming language to achieve correctness more cost-effectively, albeit with weaker guarantees, complementing formal verification. In doing so, the project targets several scientific contributions. It will develop an intralingual representation system where a system resource is represented by a linear-type instance, and its runtime management can be reasoned about at compile-time. Additionally, the project will discover and apply design patterns for operating system implementation, where correctness theorems, their assumptions, and hardware knowledge are encoded into Rust types and checked at compile-time. The project will also develop a hybrid approach that selectively employs formal and informal reasoning to further enhance intralingual design. Lastly, the project will extend the aforementioned technologies to Linux kernel modules written in Rust. This project aims to make correctness more affordable for systems software developers, thereby improving the security and reliability of computer systems, ranging from embedded devices to datacenter servers. It is expected to significantly influence the development of systems software, and consequently impact many aspects of computer users' lives. The project will foster interaction with other research fields, specifically programming languages and formal methods, by inspiring new language features and introducing additional ways to ensure correctness statically, as well as by extending the scope of formal verification to large-scale systems software. Additionally, the project will provide resources to modernize introductory systems courses and serve as a platform to engage both undergraduate and high school students in computer systems research. 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 Exposure to traumatic events is associated with increased HIV risk in adults, however for young, forcibly displaced persons this relationship is less clear. An insurgency in northern Mozambique has internally displaced >1 million inhabitants from Cabo Delgado province. Moreover, Mozambique has an HIV prevalence of 11.5% and adolescent girls and young women (AGYW; ages 15–24) in sub-Saharan Africa account for 63% of all new infections. It is critical to investigate how forced migration can impact internally displaced Mozambican AGYW's vulnerability to HIV and devise relevant strategies to mitigate this potential effect. Individuals may encounter a range of traumatic stressors (violence, conflict, family separation, etc.,) throughout their displacement journeys. Few studies have examined traumatic stressors specific to displacement as predictors of HIV vulnerability, particularly for AGYW in sub-Saharan Africa. Similarly, trauma informed HIV prevention could prove beneficial to displaced AGYW, however it has yet to be delivered in humanitarian settings. The proposed F31 responds to these research and practice gaps by engaging with recently displaced AGYW in northern Mozambique to determine predictors of HIV vulnerability for this population (Aim 1) and explore HIV prevention implementation strategies for AGYW in contexts of displacement (Aim 2). In Aim 1a., I will employ mediation analysis to determine the relationship between exposure to (traumatic) stressors related to displacement, common mental disorders, and HIV risk behaviors. In Aim1b., I will use latent class analysis to create displacement stressor profiles for AGYW and then identify which classes of the sample confer the highest level of HIV risk. The results of these aims will inform Aim 2: a needs assessment for the development of a trauma-informed HIV prevention implementation strategy for displaced AGYW. The outcomes of this study will contribute to HIV prevention efforts for displaced AGYW in Mozambique. Studying the impact of forced migration on HIV vulnerability and HIV prevention for AGYW in Mozambique is critical to understanding its influence on HIV prevention efforts in other regions of sub-Saharan Africa and globally. The F31 fellowship will provide the candidate a specialized training in advanced quantitative methods, HIV prevention implementation science, forced migration and health, and leading global health research teams. This training, and the multidisciplinary mentorship team, will prepare the candidate for a career as a HIV and mental health social epidemiologist conducting research in forced migration contexts and developing trauma-informed HIV prevention strategies for displaced AGYW in sub-Saharan Africa.

NIH Research Projects · FY 2026 · 2024-07

Abstract: Wilson disease (WD) is an inherited disorder of copper metabolism present in 1:30,000 due to reduced biliary copper excretion and pathologic copper accumulation in the liver and later in extrahepatic sites. Despite 60 years of available medical therapy, there are unmet needs and a significant burden of disease (disability, liver transplant or death) due to late diagnosis, treatment non-adherence and issues with monitoring. Given its rarity and wide-ranging phenotype, we created a WD patient registry and biospecimen repository sponsored by the Wilson Disease Association, a patient advocacy organization, to study the natural history of WD and search for biomarkers. In collaboration with the Regional Laboratory for Metal Analysis (Surrey, UK) directed by Dr. Harrington, an innovative method was developed for testing blood samples for “bioavailable” or non-ceruloplasmin bound copper measured accurately (ANCC) to determine a patient’s “copper status”. We aim to establish ranges for ANCC for patients with WD in different phases of treatment by showing that ANCC is elevated in untreated patients and with treatment failure or non-adherence, and that ANCC decreases with treatment. We will test whether ANCC is a biomarker for treatment target and prognostic indicator for treatment outcome for WD by correlating ANCC with patient clinical outcomes. This will help determine whether ANCC is useful for guiding treatment and for patient prognostication, or whether a matrix of biochemical and clinical measures is needed. We also plan exploratory studies to determine if urinary copper excretion measured after treatment interruption for patients on different therapies for their WD correlates with ANCC, as this alternative measurement may be a cost-effective option superior to currently used on-treatment 24 h urine copper studies for managing WD therapy. WD is managed most frequently by liver specialists given frequent injury to the liver in this disorder, but multidisciplinary care of patients is important given the extrahepatic features of the disease that impact a patient’s quality of life. Having a biomarker such as ANCC for clinical use as a surrogate for the state of a WD patient’s disease would be extremely useful and help to avoid treatment errors when treatment dosing or choice of therapy is based on 24 h urine copper excretion results alone due to confounders for this measurement. With respect to future clinical studies for WD, as it is no longer acceptable to use survival alone as a study endpoint, we must define clinically meaningful endpoints, optimize treatments to achieve best clinical outcomes and enhance patient quality of life, and evaluate cost effectiveness of current and future therapies. Benefits of these studies outside of WD will be the bettering of our understanding of human copper metabolism and establishment of useful assays for assessing copper status and their expected ranges in health and disease. With recent discoveries of the critical role that copper plays in cell metabolism and cell survival, furthering our ability to measure “copper status” using potential biomarkers like ANCC have an even larger importance beyond WD.

NSF Awards · FY 2024 · 2024-07

The US National Science Foundation (NSF) has named Dr. Rebecca Kramer-Bottiglio as one of three recipients of the 2024 Alan T. Waterman Award, the agency's highest honor. This award, named for the agency's first director, recognizes outstanding young researchers in any field of science or engineering supported by NSF. In addition to a medal, awardees receive a grant of $1 million over five years to support scientific research and advanced study. Dr. Kramer-Bottiglio is the John J. Lee Associate Professor of Mechanical Engineering & Materials Science at Yale University. She is recognized for groundbreaking contributions to robotics, particularly in advancing the vision and realization of machines that can evolve new capabilities in response to new tasks or a changing environment. Kramer-Bottiglio's research blends materials science, robotics, artificial intelligence, biology, and art. She is recognized for her invention of robotic skins, which are thin, skin-like robots that can wrap around and manipulate a passive deformable core, allowing the system to respond to new task demands with morphological adaptations. She also created an amphibious turtle-inspired robot with morphing limbs that transition from flippers to legs, allowing efficient movement both in water and on land. Using this morphing robot platform, she proved that morphological adaptation is an energetically favorable strategy for mobile robots encountering multiple environments. Her achievements range from innovations at the level of individual components, such as distributed sensors, phase-changing actuators, and stretchable electronics, to new algorithms for embodied intelligence to discover effective behavioral control policies for mutable body morphologies. Dr. Kramer-Bottiglio has received multiple awards including the NSF Career Award, the NASA Early Career Award, the AFOSR Young Investigator Award, and the ONR Young Investigator Award. She was named to the Forbes "30 under 30" list for her approach to manufacturing liquid metals through printable emulsions and scalable sintering methods. Her development of robotic skins that turn inanimate objects into multifunctional robots was recognized with the Presidential Early Career Award for Scientists and Engineers (PECASE), the highest honor bestowed by the U.S. government on early-career scientists and engineers. She was named a National Academy of Engineering Gilbreth Lecturer in 2022 and a National Academy of Science Kavli Fellow in 2023. She also serves on the Technology, Innovation & Engineering Committee of the NASA Advisory Council. The Alan T. Waterman Award will enable Dr. Kramer-Bottiglio to pursue new interdisciplinary and high-risk research, and to continue to reimagine conventional ideas of what a robot -- or a roboticist -- can be. 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/Abstract The co-occurrence of substance use and trauma is an urgent health priority. The vast majority of U.S. adults (89.7%) have experienced at least one traumatic event in their lifetime. Individuals with (versus without) posttraumatic stress disorder (PTSD) have higher rates of problematic drug and alcohol use, and individuals with co-occurring PTSD and substance use disorders have greater functional impairment, more severe PTSD symptoms, and worse substance use outcomes relative to individuals with either disorder alone. Yet, work focusing on mechanisms which underlie this co-occurrence has been limited in its use of retrospective, self- report designs. Emotional processes may be especially potent predictors of substance use among trauma- exposed individuals. Given that emotions and substance use each tend to fluctuate widely across contexts and over time, they are best captured through methodologies which allow them to be modeled as such. The proposed project will leverage a combination of subjective (i.e., experience sampling methodology) and objective (i.e., physiological indices via biosensor) metrics to explore the role of emotional processes in substance use in the daily lives of trauma-exposed community adults. This study lays the groundwork for the early detection and intervention of substance use among trauma-exposed individuals. Dr. Schick is extremely well-qualified for the Mentored Patient-Oriented Research Career Development Award. She is a highly productive NIDA-funded T32 Postdoctoral Fellow in Substance Use Prevention Research in the Department of Psychiatry at the Yale School of Medicine. During the training period, Dr. Schick will be housed within the Department of Psychiatry at the Yale School of Medicine, which provides an intellectually stimulating environment with outstanding resources to ensure the successful achievement of her training plan. She has assembled a team of mentors who are each nationally known for their research in areas pertinent to the training plan, which will provide access to world-class expertise in research design, methodology and analysis. Dr. Schick's program of research focuses on the ways in which intra-individual processes, most notably emotional processes, influence substance use. Her long-term goals are to be a leader in research aimed at elucidating emotional processes in substance use among trauma-exposed individuals and to lead an interdisciplinary research team to develop, test, and disseminate prevention and treatment programs targeting reduced substance use among trauma-exposed individuals. Continued sponsorship, mentorship, and directed study will facilitate the development of advanced research skills so Dr. Schick can be at the forefront of cutting- edge research in these areas. Short-term career objectives focus on (a) developing proficiency in micro- longitudinal research design, methods, and analysis; (b) enhancing knowledge of autonomic nervous system functioning and psychophysiological indices of emotional processes; and (c) use of wearable biosensors to passively collect indices of emotional processes.

NIH Research Projects · FY 2025 · 2024-07

Diisocyanates are crucial ingredients in many important products and industries (i.e. construction, automotive, aerospace, medical, military/civilian). Recognized in 1951 as occupational allergens, progress in understanding diisocyanate asthma has lagged behind that of environmental asthma. Gaps in understanding diisocyanate asthma pathogenesis impede almost all aspects of disease control; exposure surveillance and prevention, disease screening and diagnosis, and prophylactic or post-exposure therapeutics or treatments. Differences between diisocyanate asthma and common environmental asthma are especially critical to screening and clinical workup, notably the lack of antigen (e.g. chemical)-specific IgE in affected workers. Individuals that continue to work with diisocyanates after developing “hypersensitivity” face long-term adverse pulmonary health outcomes, and in rare cases have died. In a prior R01 we developed a novel approach for delivering diisocyanate to the lower airways in mice (overcoming upper airway “scrubbing” that hampered prior studies) to help understand pathogenic responses and identify new exposure biomarkers useful for exposure surveillance. Our novel mouse diisocyanate asthma model has provided substantial insight into the immune responses triggered by exposure, particularly differences between pathogenic responses in immune sensitized hosts vs. non-pathogenic responses in non- sensitized hosts and differences in chemical (MDI) asthma vs. environmental asthma (see preliminary data). Importantly, the data highlight innate immune responses that differentiate “self” from “non-self” as a critical aspect of pathogenesis and identify candidate genes and molecular targets that mediate this process. The present investigation proposes to complete the elucidation of pathogenic mechanisms triggered by diisocyanate using our animal model and to translate promising preliminary findings in mice on biomarkers to clinical samples from exposed workers. We hypothesize that we can utilize our mouse model of diisocyanate asthma, taking advantage of genetic manipulation and experimental drugs that focus on specific molecular targets, to better understand the mechanisms that differentiate pathogenic from non-pathogenic responses. We further hypothesize that exposure biomarkers from animal studies, including di-lysine-diisocyanate recently discovered by our laboratory, can translate to humans and serve as an effective basis for biomonitoring workplace exposures. The Specific Aims are: Aim 1. Identify and characterize the dendritic cell(s) that initiates pathologic systemic immune sensitization to diisocyanate. Aim 2. Identify and characterize the effector cells and molecules in the lungs that mediate asthma pathology following respiratory tract exposure. Aim 3. Identify, validate, and translate biomarkers of diisocyanate exposure and sensitivity/disease. The application is relevant to Construction, Manufacturing, and Transportation NORA sectors and Respiratory Health, Immune, Infectious and Dermal Disease Prevention cross-sectors.

NIH Research Projects · FY 2025 · 2024-07

PROJECT SUMMARY Myocardial infarction (MI) can lead to heart failure (HF), which severely impacts the quality of life of millions of Americans. MI triggers a cascade of cardiac growth and remodeling (G&R) patterns. They change ventricular size, shape, and function, driven by biomechanical, neurohormonal, and genetic stimuli. Adaptive short-term G&R can stabilize cardiac performance. Yet, in many patients, adverse long-term G&R is unstable and progresses to HF. Unfortunately, those patients lack robust clinical predictors because the biomechanical stimuli of adverse G&R patterns are still unclear. Computational models of full-heart biomechanics, informed by cardiac magnetic resonance imaging (CMR), show high potential to fill this gap. The foundation of this project is a novel microstructure-based model of cell-scale G&R based on the homogenized constrained mixture theory, co-developed by the applicant, Dr. Pfaller. In addition, this research plan will leverage a multiscale model that combines cell-scale G&R and organ-scale cardiac contraction and validation with CMR in swine and humans to predict the propensity to develop HF with the mechanobiological stability theory. In Aim 1, Dr. Pfaller will refine and validate a framework for subject-specific models of cardiac G&R. After calibrating the model to pressure and kinematic CMR measurements in control swine, he will introduce MI to the multiscale model and validate the prediction of G&R with matching measurements in post-MI swine. In Aim 2, Dr. Pfaller will quantify the propensity of developing adverse G&R with the mechanobiological stability theory and identify risk factors of post-MI HF from infarct properties. He will test the validity of his HF prediction with longitudinal human CMR and clinical data from the UK Biobank. Dr. Pfaller has excellent prior training in cardiac biomechanics, medical imaging, and computational engineering with an established publication record in cardiac and cardiovascular biomechanics. His career development plan (K99-phase) will provide additional training in cardiac biology and using CMR for human subjects. Dr. Pfaller will also receive a wealth of informal and didactic training at Stanford University, which will be critical for Dr. Pfaller to gain autonomy and launch a productive career as an independent engineering-scientist. Mentor Dr. Marsden is a leading expert in patient- specific modeling of the cardiovascular system. Co-Mentor Dr. Ennis (CMR) and advisors Drs. Humphrey (cell- scale modeling), Cyron (stability theory), Kuhl (organ-scale modeling), Yang (cardiac biology), Salerno (heart failure) offer complementary expertise. Dr. Pfaller will receive the necessary guidance and resources to accomplish these goals and efficiently transition to independence (R00-phase). In summary, the strong mentoring environment and training plan will fully prepare Dr. Pfaller to launch his independent career. The proposed studies promise to offer insights into biomechanical stimuli of adverse G&R and help optimize diagnostics and therapies that predict and ultimately prevent HF after MI.

NIH Research Projects · FY 2025 · 2024-07

Project Abstract As cannabis becomes legalized in regions around the country, developing effective treatments for Cannabis Use Disorder (CUD) becomes increasingly important. Transcranial Direct Current Stimulation (TDCS) holds promise as an augment to existing behavioral treatments. Based on recent work in internet gaming disorder by our team, enhancement of regulation skills through TDCS of the Dorso-lateral Prefrontal cortex (DLPFC) may constitute a helpful treatment for addictive behaviors. Pairing TDCS of the DLPFC with specific training in reappraisal may further help individuals regulate craving by enhancing effectiveness of training in the beneficial emotional regulation strategy of reappraisal. Thus, the goal of this work is to examine if neurostimulation paired with reappraisal training may enhance emotional regulation, resulting in a reduction of cannabis use coupled with change in EEG correlates of regulation. Sixty participants will be recruited and assigned to either receive real or sham TDCS alongside reappraisal training in 5 weekly single 20-minute sessions using a double-blind design. Cannabis use will be measured daily using ecological momentary assessment (EMA) for the duration of the month. Use of EMA technique will allow us to obtain detailed cannabis use information and determine any change in use patterns. Further, we will examine EEG correlates of regulation of craving, using the regulation of craving task, after TDCS at the first and final visit. Use of EEG during the regulation of craving task post-stimulation at baseline and post-treatment will allow us to determine if DLPFC stimulation results in enhancement of reappraisal coupled with both reduction in self-report of craving to cannabis images and changes in EEG correlates of regulatory control and reactivity while participants attempt to regulate their craving. We predict that real, as opposed to sham, TDCS will be associated with reduction in cannabis use as measured by EMA, along with reductions in self-reported craving and enhancement of EEG correlates of regulation at the final visit. If our predictions hold, findings will serve as important proof-of-concept data on the effectiveness of TDCS in tandem with reappraisal training as a potential treatment augment for CUD as well as elucidating potential mechanisms by which TDCS works. These data will set the stage for future work in larger samples and longer durations investigating TDCS as a method to augment treatment for CUD.

NIH Research Projects · FY 2025 · 2024-07

The primary goal of this research proposal is to provide Dr. O’Neil with four years of training and research experience in implementation science and mixed-methods research techniques to support his transition to being an independent researcher focused on improving the early detection of breast cancer and breast cancer care more broadly in low- and middle-income countries (LMICs). Breast care patients from LMICs face far higher mortality that patients from the USA, in part because a lack of screening mammography results in more than 50% being diagnosed with stage III or IV cancer. Breast cancer screening using clinical breast exam has been shown it to be nearly as effective at detecting early BC as mammography and capable of decreasing BC stage at diagnosis and mortality. However, screening CBE (sCBE) has not been widely implemented in LMICs, including Nigeria. Dr. O’Neil proposes to use the Implementation Mapping process to collaboratively design and pilot a set of strategies for implementing sCBE in the primary health centers (PHCs) of Abuja, Nigeria. In Aim 1, he will engage with provider and patient stakeholders at two participating PHCs to conduct a baseline needs assessment, identify determinants of implementation with change objectives, select applicable strategies, and then produce implementation materials. Determinant and strategy selection will be organized using the COM-B and behavioral wheel of change frameworks. In Aim 2, Dr. O’Neil will conduct a feasibility pilot study of sCBE implementation in the same two PHCs, using the strategies developed in Aim 1. This study will allow for refinement of the strategies, and the primary outcome will compare receipt of sCBE among eligible women before and after implementation. These results and other secondary results from the RE-AIM framework will provide preliminary data supporting an R01 proposal for a large-scale hybrid trial measuring the effectiveness and implementation success of the sCBE implementation package developed here. Dr. O’Neil has substantial experience studying breast cancer care quality and barriers to care in sub-Saharan Africa. His training plan adds to that foundation by emphasizing new skills essential to actually improving care, with formal instruction in the theories and methods of implementation science and mixed-methods research. His mentoring team includes experts in breast cancer clinical research, implementation science, and global oncology, who are uniquely qualified to supervise Dr. O’Neil’s research program and to help him expand his academic global oncology network. Dr. O’Neil will also be leveraging a partnership with breast cancer researchers at the Institute of Human Virology Nigeria / International Research Center of Excellence in Abuja, Nigeria, who will be enthusiastic collaborators in the proposed work and provide vital support. This work will the first step towards scaling-up and studying breast cancer screening throughout Nigeria and other LMICs, a public health goal with the potential to decrease global breast cancer mortality. It will also position Dr. O’Neil for a successful career as an independent global oncology implementation scientist.

NIH Research Projects · FY 2026 · 2024-07

PROJECT SUMMARY/ABSTRACT The goal of this proposal is to compare and contrasts the effects of different medications for opioid use disorder (MOUD) on driving abnormal immune activation in the central nervous system (CNS) in people living with HIV (PLWH) through the lens of epigenetic programming. Prior published research suggests that opioids and opioid receptor agonists lead to a proinflammatory state in the CNS through changes to myeloid cells. Conversely, pre- clinical studies suggest potential beneficial anti-neuroinflammatory effects of opioid antagonists. Cerebrospinal fluid (CSF) studies are a window into the CNS of PLWH, revealing a role for abnormal myeloid cell activation and persistent viral transcription in the CNS, despite apparent systemic viral suppression with ART. Our own single cell genomic studies of fresh CSF cells from PLWH have shown that a rare microglia-like myeloid cell population resides in the CSF in PLWH; that these cells are linked to HIV disease status; and are defined by a distinct epigenetic state consisting of alterations in chromatin accessibility of myeloid/microglia-like cell type specific proinflammatory genes. However, despite myeloid cells being recognized as crucial cellular mediators of CNS abnormalities in PLWH, the impact of different MOUD therapies on the epigenetic landscapes of CNS myeloid and other immune cells in PLWH remain uncharted. Our central hypothesis is that opioid antagonist MOUD (XR-naltrexone) suppresses myeloid cell activation by exerting anti-inflammatory epigenetic effects in CNS myeloid cells of PWH, thereby improving cognitive function; while, in contrast, opioid receptor full/partial agonists (methadone, buprenorphine) induce a pro-inflammatory epigenetic landscape increasing myeloid cell activation, and impairing cognitive function. This hypothesis will be tested in our established InSTRIDE Research MOUD program at Yale that includes a mobile health clinic to perform lumbar puncture and cognitive testing “on the road” meeting research participants in their own communities. We have assembled a multidisciplinary team with expertise in Neuro-HIV, addiction medicine including treatment of OUD, single cell epigenetics, HIV neuropsychology, and data science. In PLWH, we will longitudinally assess CSF biomarkers of neuroinflammation, neuronal injury, and myeloid cell activation over the course of either opioid antagonist or agonist MOUD treatment. Using single cell simultaneous profiling of epigenetic chromatin accessibility and gene expression from the same CSF cells, we will then ask whether there is damage to the epigenomes of CSF myeloid cells sustained during specific MOUD treatments that persists over time as epigenetic “scars”. Lastly, we will evaluate the effect of the different MOUD regimens on post-treatment cognitive trajectories and associations with post-MOUD CSF biomarker and single cell biological measures. The proposed work will significantly advance our understanding of how specific MOUD treatments interact at a molecular and cellular level in the CNS, potentially leading to improved treatments and outcomes for PLWH with opioid use disorder.

NIH Research Projects · FY 2025 · 2024-07

This proposal seeks to develop and evaluate a novel tailored family-based videogame, FamilyBond (FamB), to prevent increases in substance misuse among mid-adolescents with early substance use in primary care settings. Over six million adolescents misuse substances despite existing interventions due to many hurdles in care delivery that can be addressed using digital interventions. Adolescents also have universal and unique risk and protective factors for substance use and parents can play an important role in adolescent substance use prevention by developing family skills (e.g., parent-adolescent communication, parental support, parental socialization and parent-adolescent cohesion), underscoring the need for tailored family-based interventions. Family-based interventions can address these factors, and digital interventions can mitigate hurdles to intervention delivery that adolescents and their caregivers face, facilitating wide uptake. However, digital family-based interventions for adolescents with early substance misuse in primary care settings are lacking. The scientific objective of this proposal is to apply theoretically and empirically driven approaches to develop and evaluate FamB, an intervention to prevent increases in substance misuse among adolescents. Research Aims are: 1) To develop FamB and assess its usability among adolescents and parents, 2) to assess the feasibility and effect size of FamB among 60 parent-adolescent (14-17-year-old) dyads in a) lowering adolescent intention to misuse substances (primary outcome), b) improving parental self-efficacy regarding parent-adolescent substance misuse communication, and c) improving parent-adolescent communication about substance misuse. Completing this K23 proposal will provide Dr. Aneni with critical new training in several key areas to achieve her long-term career goal of becoming an independent investigator capable of developing, testing, and implementing effective, accessible, and tailored family-based substance use prevention interventions for adolescents. Dr. Aneni and her mentors have compiled a comprehensive plan that will allow her to achieve the following training goals: 1) Gain mastery in conducting family-focused research for substance misuse prevention among adolescents, 2) acquire expertise in developing family-based digital substance misuse prevention interventions for adolescents, 3) obtain knowledge and skills in Implementation Science methods, and 4) hone skills in conducting randomized controlled trials, responsible conduct of research, and grant writing. This proposal is significant in addressing a major public health problem, substance misuse among adolescents, by implementing novel approaches to addressing both risk and protective factors and care delivery hurdles. The vital support from this K23 award will allow Dr. Aneni’s scientific development, leading to an independent, highly integrated family-focused research program addressing substance misuse and improving wellbeing among adolescents.

NIH Research Projects · FY 2025 · 2024-07

PROJECT SUMMARY Individuals must predict threats in the environment in order to survive. However, maladaptive threat computation processes can lead to psychiatric disorders such as post-traumatic stress disorder. For threat predictions to be adaptive, they must be temporally accurate and capable of predicting threats which may be distant in time. However, the mechanisms underlying predictions involving temporal distance are poorly understood. The overall aim of this project is to determine the neural substrates underlying learned encoding of temporal threat proximity and temporally accurate defensive responses to threat. I have recently shown that the in the prefrontal cortex, norepinephrine represents a teaching signal which also encodes proximity of incoming threat. Furthermore, threat-predictive stimuli evoke increases in prefrontal cyclic AMP (cAMP) concentration that persist past the stimulus and to an aversive event, consistent with temporal linkage of predictive stimulus to outcome. These results are consistent with both the encoding of temporal information within prefrontal cortex (PFC) and the necessity of PFC for delayed threat prediction. Taken together, current work on the prediction of distant threat suggests an interplay between norepinephrine signaling of threat proximity during learning, second messenger linkage of predictive cue to distant outcome across learning, and encoding of threat proximity in PFC in order to effect accurate defensive behavior. The proposed project seeks to test this model of threat prediction. The proposed project seeks to understand the roles of norepinephrine, second messengers, and prefrontal neurons in encoding of and effecting behavioral responses to threat proximity. In Aim 1, I will determine the role of norepinephrine time-to-danger signals in supporting temporally accurate threat responding and encoding of threat proximity information by prefrontal cortex. I will do so by employing behavioral optogenetics and in vivo calcium imaging, techniques essential to this work and my future systems neuroscience studies. In Aim 2, I will determine whether cAMP links temporally distant events during learning by determining whether sustained cAMP supports delayed threat preparation and elucidating the effect of temporal distance on threat cAMP. I will use optogenetic manipulation and fluorometry of prefrontal cAMP to complete these aims, as well as to gain personal expertise in future manipulation and measurement of second messengers, which are key to learned behavior but highly understudied in vivo. In total, I seek to understand the neural processes underlying the accurate prediction of threats across timescales. The proposed project will accomplish the technical training goals aforementioned, and I will also use this fellowship for my personal advancement in science communication, teaching, and mentorship within an environment of technical experts. My sponsors, collaborators, contributors, and research environment are technically and intellectually equipped to support the proposed training and research under this fellowship.

NIH Research Projects · FY 2026 · 2024-07

Abstract Opioid use disorder (OUD) is a significant public health problem with opioid-associated overdoses and deaths reaching epidemic levels in recent years. Methadone and buprenorphine are widely used and generally effective medications for OUD (MOUDs). However, relapse and nonadherence rates remain high and average treatment retention is suboptimal (e.g., <6 months in 30-50% of cases). As risk of overdose is highest following relapse and treatment dropout, improved mechanistic understanding of risk and resilience factors in individuals in early MOUD (i.e., <6 months) is urgently needed. This application uses network-based analysis, with built-in cross- validation, to identify brain networks associated with (i) patterns of illicit opioid use during early MOUD and (ii) medication adherence during early MOUD in a diverse sample of individuals (N=240, 50% female, 50% male, 50% receiving methadone, 50% receiving buprenorphine). This is critical to improve understanding of mechanisms and predictors of MOUD response and is an essential precursor to development of improved, evidence-based interventions grounded in known neurobiology. This work builds on our prior work identifying brain connections prospectively associated with future relapse to illicit opioids during sustained MOUD. The identified ‘opioid abstinence network’ included connections between frontoparietal, salience, sensorimotor and default mode regions and was robust to analyses controlling for relevant clinical variables (e.g., MOUD dose, years of opioid use). In AIM 1, we seek to externally validate and extend this finding via collection of neuroimaging data from a larger, more diverse sample of individuals early in MOUD treatment. In AIM 2, we propose to collect additional, multi-task neuroimaging data to determine the impact of different, task-induced brain states on network identification. Finally, in AIM 3, we will use our recently developed approach, in which variation in model accuracies are assessed as a function of core sources of clinical diveristy (e.g., sex, medication dose, co-occurring disorders), to identify sources of model bias and neurobiological heterogeneity. Assessing sources of model bias and neurobiological heterogeneity embraces the clinical complexity that is inherent to the current opioid epidemic. These clinical sources of variance have typically either been excluded for or ignored (e.g., treated as covariates of no interest) in prior neuroimaging studies of MOUD. All acquired data will be shared via the NIMH Data Archive.

NIH Research Projects · FY 2026 · 2024-07

Project Summary/Abstract The aim of this proposal is to enhance the technical development of an open MRI system that can be integrated into an exam table in a doctor's office, allowing MRI scans to be used similarly to ultrasound. This open-low-field MRI is silent and can produce high-quality images of any organ with the patient lying flat on the examination bed or standing for weighted spine or limb imaging with the device wall-mounted. Developing a small-footprint compact and low-cost MRI system allows MRI to be moved from hospitals to doctors' offices, with the impact that MRI could become more accessible to a wider population. This proposal combines developments in MR imaging with non-linear gradients, field-cycling MRI, spatial encoding using RF, and non-Fourier based algebraic reconstruction techniques incorporating parallel imaging. The objective is to enhance the image quality through innovative developments in both spatial encoding and pulse sequences. The preliminary data indicates strong signal, prolonged T2s, and exceptional image quality. Aims 1 and 2 integrate and optimize new encoding developments through novel RF coil designs, stop-motion imaging, and the introduction of gradient encoding to the system. The goal of these studies is to optimize resolution across the targeted volume (24x24x20cm). The proposal also introduces new pulse sequences with an emphasis on fat/water separation and quantification. Aim 3 tests three forms of fat-water contrast manipulation and gathers preliminary data on the effectiveness of this device for assessing fatty liver disease in both lean and obese subjects. Together, these aims will establish the imaging capabilities of the device, which would be a significant step forward on the path to improved accessibility. This proposal is innovative as it combines several proven technologies in novel ways to develop a new class of low-cost MRI devices that operate in inhomogeneous B0 fields.

NIH Research Projects · FY 2025 · 2024-07

PROJECT SUMMARY / ABSTRACT Different sensory modalities elicit distinct neural signatures in the brain, however, a fundamental subset of circuits for perception is shared across modalities. Subcortical arousal systems are known to influence long- lasting states such as sleep/wake and levels of vigilance, but their role in dynamic short-term modulation of arousal shared across perceptual modalities has been little studied. Subcortical systems are increasingly recognized as playing an important role in cognition. Recent work suggests that multiple parallel arousal systems in the thalamus, upper brainstem and basal forebrain contribute to phasic modulation of perception through a transient increase in activity following sensory stimuli. Therefore, our central hypothesis is that a transient pulse of activity in the intralaminar thalamus, upper brainstem and basal forebrain occurs after sensory stimuli across diverse modalities, augmenting perceptual awareness. If confirmed, this may identify both fundamental circuits for normal perception and potential therapeutic targets for disorders where perception is impaired. We will investigate shared subcortical arousal circuits in perception using techniques with complementary strengths based on promising initial studies. We found that large fMRI data sets showed shared transient activation in thalamus, midbrain and basal forebrain with visual, tactile and gustatory tasks. To investigate this further, our first aim will contrast perceived vs not perceived visual, auditory and tactile stimuli to study shared fMRI signals in subcortical arousal areas with both whole brain and high-resolution subcortical methods. In our second aim, we will leverage recent findings that pupil, blink and microsaccade measurements combined with machine learning can isolate the components of subcortical perception-related fMRI signals which are independent of task report. These methods will be used to identify shared fMRI signals in subcortical arousal systems with visual, auditory and tactile perception independent of report. Finally, direct access to the human intralaminar thalamus through devices implanted in epilepsy patients, provides a unique opportunity for both thalamic recording and stimulation. In our third aim, we will use this approach to record and stimulate the intralaminar thalamus to determine the role of this key subcortical arousal area in perception. Understanding the role of transient increases in subcortical arousal shared across perceptual modalities will both shed light on fundamental mechanisms of perception, and provide new treatment avenues for perceptual disorders.

NSF Awards · FY 2024 · 2024-07

Addressing the questions of how the two-meter-long human DNA fits into the space of a cell's nucleus (~20 um) and how it is organized within this space has been among the major mysteries of cell biology. DNA is packaged into the nucleus in the form of chromatin, consisting of a complex between DNA and histone proteins. DNA wrapped in compacted histones is thought of as “repressed” and “inaccessible”, and thus chromatin compaction plays a critical role in regulating gene activity. Current chromatin modeling is based on polymer simulations at different levels of resolution. However, given the slow time scales of these processes of the order of minutes to hours, the size scales of the order of 5--10 um (typical size of nucleus) are not accessible using methods such as molecular or dissipative dynamics approaches. The objective of this project is to decode the quantitative relationship between the physical microenvironment, multiscale 3D genome organization, and transcriptional output. The project will employ a convergent research strategy that integrates super-resolution microscopy, genomics, biophysical modeling and simulation, and machine learning. The new tools developed in this project will impact many areas in biology, including normal and abnormal tissue development, tissue degeneration in disease, as well as tissue regeneration. The research team will educate future scientists and a diverse workforce with a collaborative expertise in interdisciplinary training. Additional outreach activities will include research experiences for undergraduate students and high school students. Tissue-resident cells continuously sense changes in their chemo-physical environment and use this information to maintain their phenotype and tissue homeostasis. The project will develop a predictive framework of emergent epigenetic and transcriptional features of cells in response to changes in their physical environment. The project will develop new quantitative models for the distribution of heterochromatin domains in the interior of the nucleus as well as along the nuclear periphery. Specifically, a mathematical model will be developed to study the effect of rates of histone tail acetylation, methylation, and transcription on determining the distribution of heterochromatin domains in the interior of the nucleus. The project will further extend this model to include the formation of lamina-associated domains (LADs) by incorporating the energetic interactions between chromatin and the nuclear lamina via chromatin anchoring proteins. To verify the theoretical model, cells of fixed fate and fluid fate will be grown under varying micro-environments, and their whole genome organization at the nano- and micro-scale will be visualized and quantified through super-resolution microscopy. In addition, a machine learning framework leveraging novel deep neural operators will be developed for nonlinear inverse problems to extract the high-dimensional parameter fields implicitly and explicitly from noisy experimental images. To enhance the robustness, accuracy, and efficiency of neural operators with small data, the project will endow neural operators with prior knowledge, physics, multifidelity data, and active learning. 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

Soot emissions from combustion devices and fires have been plaguing humans for centuries, with repercussions on health and climate. Understanding the process by which soot forms remains a challenging topic in combustion research because of difficulties in describing the critical steps involved. The most sophisticated approaches to study soot formation in flames entail detailed measurements of gaseous soot precursors and soot particles with multiple, complementary diagnostics that follow the entire evolution from parent fuel molecule. At the other end of the diagnostic spectrum, the sooting tendency is described by a simple sooting index, without the assessment of soot production rates necessary for modeling soot in engine-relevant conditions. This proposal seeks a middle ground, aiming to quantify the soot production rate while maintaining the simplicity of single index characterizations. The study will impact the design of practical engines, the reduction of the environmental footprint of combustion, and, indirectly, air quality, public health, and climate. The research goal is to quantify soot production rates of several relevant fuels in a simple but fundamental manner, without ad hoc assumptions. The approach involves establishing opposed jet gaseous diffusion flames, doping them with a few thousand parts per million of pre-vaporized practical fuel components and measuring soot volume fraction through pyrometry. The experimental work is complemented by numerical simulation of the flames structure to accurately describe the velocity and temperature fields. These data enable the quantification of the soot production rate from the soot governing equation. In this study, fuels to be tested are common components of Jet fuels and Diesel fuels, and their surrogates, including: iso-octane, n-decane, n-hexadecane, iso-cetane, toluene, 1,2,4 tri-methylbenzene, methyl-naphthalene and decalin. They will be tested individually at first and then in blends mimicking the sooting tendency of jet fuel and Diesel fuel. The developed database will allow a quantitative comparisons of different fuels in highly controlled environments either by keeping a constant temperature-time history, which affects soot formation critically, or by varying peak temperature over several hundred degrees and pressure in the 0.1-3.0 MPa range. The quantified soot production rates will be converted to sooting yields and their explicit dependence on temperature, pressure, strain rate, and local mixture fraction will be established. 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 The hallmark of epilepsy is recurrent seizures, i.e., paroxysmal attacks of abnormal brain electrical activity that are associated with high morbidity and premature mortality. In addition to the direct morbidity of seizures, people with epilepsy must also contend with the ever-present uncertainty about when the next seizure will occur. The unpredictability of seizures represents a significant and disabling feature of epilepsy. Despite decades of research, there is no established method for determining when a seizure could occur. Akin to weather forecasts that estimate the probability of rain, seizure forecasts that quantify the likelihood of seizures over a future temporal window could increase the quality of life for patients and families living with epilepsy, so they could plan around a seizure event. A forecast could help patients and families prepare for, or even mitigate upcoming seizures. The overarching goals of the present proposal are (1) to elucidate the relationship between biochemical changes in saliva (a readily available biofluid that reflects systemic chemistry) and electrophysiological features that determine seizure likelihood (recorded from a Responsive Neurostimulation (RNS®) System) and (2) to leverage these relationships to develop effective seizure forecasting methods that will empower people with epilepsy with the unprecedented ability to anticipate and prevent seizures. We have strong preliminary data from people with epilepsy that several saliva chemicals exhibit novel multidien (multi- day) and circadian (~24-hour) concentration changes that correlate with periods of increased seizure likelihood. Our central hypothesis states that a latent biochemical variable for seizure likelihood can be detected in people with epilepsy using serial salivary sampling. We will pursue the following specific aims: (1) establish biochemical signatures of multidien seizure likelihood and develop effective seizure forecasting approaches; and (2) establish biochemical signatures of increased seizure likelihood over the circadian cycle. Successful completion of this project will significantly advance the fields of chronobiology, metabolism, and epilepsy by: (a) identifying novel multidien and circadian rhythms in biochemical and metabolic pathways in people with epilepsy and healthy controls, (b) linking these changes to possible causes of seizures, and (c) using these changes to forecast seizures and define a more effective standard of care. The expected positive impacts on public health will be to (a) empower people with epilepsy with the ability to anticipate and prevent seizures, (b) provide researchers with validated saliva sample collection and analysis approaches, and (c) discover ground-breaking biochemical insight into the human chrono-metabolome. Detailed knowledge about the chrono-metabolome is expected to fuel innovative studies on various episodic brain disorders that place a large burden on society, like migraine, cluster headaches, affective disorders, and substance use disorders.