Grants

NYC Department of Cultural Affairs

Dyckman Farmhouse Museum Alliance

Fish and Wildlife Service

This project will fund Siskiyou County Dept. of Agriculture to chemically treat 55 acres of invasive weeds at Yreka phlox populations and 38 acres at Siskiyou mariposa lily populations. Due to the nearly year-round germination of dyer s woad from the seedbed and the threat of encroachment from adjacent lands, long-term treatment is necessary to protect the habitats of these protected plants. This agreement will provide funding for weed surveys and treatment on private lands in and around know populations of these plants. At each population area, private lands will be worked or surveyed at least twice each year for the presence of dyer s woad. Identified plants will be controlled by chemical spot treatment, or hand pulling if within the designated buffer zone adjacent to the known populations, two to three times per year.

NHLBI - National Heart Lung and Blood Institute

The Medicare Hospice Benefit, which dictates hospice policy for most Americans, was designed based on the needs of people with cancer, a disease with a trajectory vastly different from that of heart failure (HF). Implicit in the Medicare Hospice Benefit is the assumption that people have the supports necessary to facilitate a home death. Yet, individuals with fewer financial and social resources, who experience the greatest HF morbidity and mortality, are less likely to use hospice and die at home than individuals with greater resources. Dr. Cross’s long-term career goals are 1) to use patient-centered mixed methods to identify and understand the end-of-life experiences of people with HF and 2) to develop interventions that address differences in end-of-life HF care outcomes through practice and policy change. This K01 project includes three specific aims. Aim 1 will use hierarchical multiple regression to characterize the influence of individual and hospital level factors on end-of-life HF care. Aim 2 will incorporate geographically bounded areas into hierarchical multiple regression to quantify the impact of neighborhood-based attributes on end-of-life HF care. Aim 3 will explore end-of-life HF needs and perceived opportunities to receive optimal care among adults with HF, their caregivers, and clinicians through semi-structured interviews. Dr. Cross will strengthen and address gaps in her experience through the following career development objectives: 1) acquire increased proficiency in mixed methods research, 2) develop expertise in advanced analytic methods for health outcomes research, 3) advance her understanding of the management of patients with advanced HF and the role of hospice and palliative care within the HF trajectory, and 4) acquire skills in designing, conducting, and evaluating socio-behavioral interventions. This proposal lays out a comprehensive career development plan consisting of expert mentorship, specialized coursework, and completion of a research project. Dr. Cross’s development during this four-year award will be guided by an interdisciplinary team of mentors at Emory University, led by Dio Kavalieratos, PhD, Associate Professor and Director of Research for the Division of Palliative Medicine; Neal Dickert, MD, PhD, the Thomas R. Williams Professor of Medicine in the Division of Cardiology; Shivani Patel, PhD, MPH, Associate Professor of Public Health in the Departments of Global Health and Epidemiology; and Modele Ogunniyi, MD, MPH, Professor of Medicine in the Division of Cardiology. This research training and career development plan will support Dr. Cross in achieving her goal of becoming an independent investigator in supportive cardiology and will inform the development of evidence-based solutions to improve end-of-life HF care.

City of Richmond

Dynamic Artists Management, LLC

NIAAA - National Institute on Alcohol Abuse and Alcoholism

Rates of alcohol, cannabis, and nicotine peak in young adulthood and rates of dual- (e.g., alcohol and cannabis) and tri-use (alcohol, cannabis, and nicotine) of these substances is prevalent and growing. Dual-/tri-use is particularly concerning given associations with heavier substance use, substance use disorder, and acute alcohol-related harms (e.g., blacking out, acute physical effects). There is a pressing need to understand risk factors that contribute to dual-/tri-use to tailor intervention content to be more impactful. Guided by dual process and incentive salience theories, impulsivity and craving are critical risk factors for alcohol use at the person- and day level. Scant research, however, has considered how impulsiveness and craving may vary between and within specific types of substance use episodes. Understanding how craving and different impulsive facets relate to dual-/tri-use may highlight underlying mechanisms for use and points of intervention. Toward this end, this R21 application seeks to collect intensive, momentary data (5 timepoints/day across 17 days) from 250 young adults who report tri-use of alcohol, cannabis, and nicotine. We aim to examine the additive effects of cannabis and/or nicotine use on the association between impulsivity facets (UPPS-P) and craving relative to alcohol-only occasions. Using a complementary set of intensive longitudinal analytic methods, we will contrast levels of impulsivity and craving between alcohol-only, dual-use, and tri-use episodes and will examine the role of cannabis and nicotine on impulsivity and craving as it unfolds across an alcohol use occasion. Lastly, we will examine day-/moment-level (mood, peer factors, location, craving) and person-level (sex, racial-ethnic group, baseline measures of impulsivity [UPPS-P, impulsive action, impulsive choice]) moderators to determine when and for whom associations are strongest and most in need of timely intervention. Specifically, this R21 application has three aims. Aim 1 is to examine within-person associations between impulsivity facets and craving as predictors of dual-use (alcohol + cannabis, alcohol + nicotine) vs. alcohol-only use, tri-use (alcohol + cannabis + nicotine) vs. alcohol-only use, and tri-use vs. dual-use. Aim 2 will examine the dynamic nature of each impulsivity facet and craving and the role of cannabis and nicotine use across moments leading up to, during, and after alcohol use initiation. Aim 3 will explore (a) day- and person-level characteristics as moderators of Aim 1; and (b) the time-varying effect of moment- and person-level characteristics on Aim 2. Findings from the current R21 will have critical implications for developing just-in-time interventions focused on attenuating the relationships between impulsivity, craving, and higher-risk substance use.

NIMH - National Institute of Mental Health

Project Summary The proposed work will enhance clinical prediction for individuals with serious mental illness (SMI), across diagnoses, by incorporation of novel, scalable cognitive measures that can be delivered in acute inpatient settings (for clinical screening), outpatient settings (for identifying time periods of relative risk), and in ethnoracially diverse populations. Our overall goal is to improve prediction of mental health outcomes and clinical decision-making through the validation and integration of dynamic cognitive phenotypes (novel and innovative measures that capture fluctuations in cognition and behavior over time) in clinical care. For Aim 1, we will recruit 1500 participants across five inpatient psychiatry units (four adult, one nondementia geriatric) at McLean Hospital that provide care to individuals with the highest levels of clinical severity. In this group, we will use a combination of brief cognitive ecological momentary assessment (over 3 days), actigraphy, and clinical records to prospectively predict clinical health outcomes, including change in transdiagnostic symptoms, change in suicidality, length of stay, and 12-month hospitalization (from electronic health records). Dynamic cognitive phenotypes derived from time series data (including slope of cognitive change, diurnal cycle, volatility, cognition/symptom coupling) will be used to improve prediction. For Aim 2, 250 participants will be followed post-discharge to collect longitudinal cognitive ecological momentary assessment (EMA) data and build personalized models of clinical risk. In Aim 3, we will evaluate generalizability and transfer learning of clinical prediction models from Aims 1-2, applied to 250 ethnoracially diverse participants with elevated psychiatric symptoms recruited from Bronx County, New York who are patients in the Montefiore Health System. Finally, in Aim 4, we will adapt cognitive assessment to ensure broad usability among culturally- diverse participants including those with low English literacy through participatory design sessions and large- scale online data collection. Across aims, the project will incorporate structured and ethical return of individual results to patients, clinicians, and volunteers to enhance the potential for clinical integration and support engagement and trust among diverse perspectives. This project is significant as it will improve risk stratification, allowing resources to be directed to those most in need and during risk periods when timely intervention can most improve clinical outcomes. Successful completion of the aims will create low-cost and scalable cognitive prediction tools that can be widely disseminated (as part of existing dissemination infrastructure) for screening and personalized prediction across clinical settings and in diverse populations.

NSF

With the support of the Macromolecular, Supramolecular and Nanochemistry Program in the Division of Chemistry, Professor Johnson of the University of Oregon will expand on a molecular self-assembly strategy to make stable, complex molecular cages and large cyclic structures from simple building blocks. This project aims to establish design rules on how the shapes and sizes of the building blocks as well as subtle effects in the self-assembly process will influence the structures and properties of the resulting products. This research may provide efficient routes to new dynamic structures for stimuli-responsive materials. Professional development activities for students will include experience in mentorship and participation in Lens of the Market workshops to learn the basics of intellectual property protection and research translation. The Johnson lab has developed a design strategy to use Group 15 ions (or Cu+) as directing elements in self-assembly reactions of oligothiols to direct formation of discrete disulfide assemblies under mild oxidizing conditions. These products are formed under thermodynamic control to yield a variety of macrocycles, dimeric cages, unsymmetrical cages, and tetrahedral assemblies. The project will involve three specific aims: Aim 1 will explore the fundamental physical organic chemistry of dynamic disulfide formation in order to develop subtle control of thiol oxidation and self-assembly pathways; Aim 2 will seek to harness subtle effects in ligand sterics, shape, and reactivity to control self-assembly and influence product distribution. Aim 3 will extend the approach to controlling disulfide assembly in water. 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.

NIMH - National Institute of Mental Health

Depressed patients who fail to respond to >2 antidepressants are burdened by treatment-resistant depression (TRD) and endure lengthy trial-and-error attempts on multiple treatment regimes while at risk for poor outcomes. Clinicians lack decision support tools to select initial or subsequent TRD treatments in part because predictors of treatment response are considered static (time-fixed), despite varying over time. Clinical decision support systems (CDSS) called for in MH-25-190 need dynamic treatment regimes (DTRs): sequences of rules that dynamically update response predictions as information accumulates. We will achieve this with: 1. Electronic Health, Patient-Reported Outcome, and Digital Biomarker Data on >10,000 TRD Patients Annually; 2. Advanced Causal Inference and Target Trial Emulation to Control for Time-Varying Confounding; and a 3. Sequential Multiple Assignment Randomized Trial (SMART) to Optimize Dynamic Decision Support Rules in: Aim 1. Pipeline to Identify Dynamic Treatment Regimes (DTRs) for Clinical Decision Support Systems TRD regimes received by >10,000 TRD outpatients in >85,000 visits annually, will include: medication management (e.g., combining, switching, or augmenting antidepressants); rTMS; psychotherapies; and esketamine or ketamine. We will create a pipeline to: a) generate features from electronic health, patient-reported outcome, and raw digital biomarker data; b) filter features; c) control for time-varying confounding with advanced causal inference; d) evaluate dynamic prediction rules to classify patients according to treatments they are likely to benefit from; and e) empirically design a CDSS with optimal DTRs for TRD. Aim 2. Target Trial Emulation (TTE) of the Clinical Decision Support System (CDSS) for TRD Although milestones (e.g., AUROC> .8) will be used to analytically validate models in Aim 1, they cannot estimate clinical benefits of using a CDSS to select treatments v. usual trial-and-error care. Before committing to a randomized trial, target trial emulation (TTE) is a gold standard way to first use observational data to evaluate comparative effectiveness. We will employ TTE to compare using DTRs in a CDSS to select TRD treatments v. usual trial-and-error care; milestones from our TTE (e.g., Cohen’s d for CDSS-informed care >.5) will determine if we proceed with user-centered design of a CDSS and testing in the randomized effectiveness trial in Aim 3. Aim 3. Effectiveness Trial of Clinical Decision Support System (CDSS)-Informed vs. Usual TRD Care We will conduct an effectiveness trial in which 1,000 TRD patients are randomized to a CDSS with optimal DTRs from a SMART v. usual trial-and-error care. On-line (live and in real-time) reinforcement learning models will use past and current tailoring variables to predict an individual’s response to treatments in the next interval, and also adapt based upon prior participants’ responses. We will compare both arms on distal outcomes (i.e., ER visits or hospitalizations for depression; all-cause and suicide deaths), and work with NIMH/FDA to ensure the trial serves as a “Real-World Performance” review for FDA Software as a Medical Device designation.

NYC Department of Cultural Affairs

Dynamic Forms, Inc.

NSF

This project addresses motions of interfaces that arise from physical applications such as the freezing of water into ice, the wetting of water drops on a rough surface, and density-constrained tumor growth. These motions generate a diverse set of singularities: some are topological ones, for instance created by merging and splitting of water drops, and some involve dendrite-like growth, such as in ice crystals or in aggressive tumor growth, due to scale-dependent instability of the evolution dynamics. The Principal Investigator (PI) aims to analyze basic properties of solutions and clarify the critical scale of instability, to validate or invalidate available models in the literature. The project involves collaboration with students and researchers at all stages. The presence of lower-dimensional structure is ubiquitous in the physical literature, either as a boundary of a domain or as a singular part of an evolution. Many problems which are otherwise well-understood face significant challenges when coupled with a moving interface, even in seemingly simple settings. Besides the nonlinearity of the problem, the difficulty lies in the nonlocality of the problem, in the sense that the behavior of solutions depends on the global geometry of the interface. Compared with stationary problems, the aforementioned interface motions face an additional difficulty, due to the presence of the time variable which often is of hyperbolic nature. The project aims to develop general methods to investigate the aforementioned problems and the interesting singularities they feature. The first research direction of the project develops a new perspective on the Stefan problem, in the context of optimal transport and interacting particle systems. This viewpoint was recently introduced by the PI and others to prove global well-posedness of the supercooled Stefan problem, a famously borderline ill-posed problem, in all space dimensions. The project builds on this framework to study geometric properties of the solutions as well as to extend the theory to a broader context. The second direction concerns the motion of liquid droplets on solid surfaces with microscopic defects. The presence of defects results in hysteresis, where there is pinning and de-pinning of the droplets during the motion, due to the microscopic contact angle between the surface and the drop. A simplified model is considered, where the problem is formulated as the homogenization of Bernoulli-type free boundary problems, and the goal is to study the dependence of the large-scale geometry of the droplet on the shape and distribution of the defects. The third research direction is on several types of tumor growth models, where the tumor cell density evolves subject to the maximal density constraint. The density then forms a patch where it reaches its maximal density, yielding a Hele-Shaw type flow with a growth term. Here the goal is to understand the effect of different parameters, such as the diffusion strength of the nutrient or the viscosity of the fluid, by focusing on the stability or the instability property of the patch evolution. 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.

NIBIB - National Institute of Biomedical Imaging and Bioengineering

Abstract Total-body (TB) Positron Emission Tomography (PET) is a medical imaging technology that enables comprehensive imaging of metabolic processes across the entire body in a single bed position. It offers substantial advantages for dynamic imaging and kinetic modeling, such as high temporal resolution and multiparametric capabilities, making it invaluable for assessing cancer staging, early treatment response, and distinguishing malignancy from infection/inflammation. However, the widespread adoption of TB PET is limited by its high cost, primarily due to the expense of scintillator material and readout electronics. This proposal seeks to develop an affordable dynamic TB PET system through the use of sparse detector architectures, which will reduce material costs while maintaining the performance benefits of full-body coverage. We hypothesize that sparse designs can produce high-quality dynamic images that allow for kinetic modeling and parametric imaging with minimal loss of quantitative accuracy compared to full-rank TB PET. Our innovative approach combines spatial down sampling of the detector matrix of the 2-m long EXPLORER TB PET scanner with advanced reconstruction algorithms. Classical and deep learning-based Kernel methods will help recover image quality in high-noise, low-count environments. This project will address three specific aims: (1) demonstrating parametric imaging using sparse TB PET, (2) comparing image quality between sparse TB PET and conventional PET scanners, and (3) optimizing reconstruction parameters and detector matrix configurations for high temporal resolution in dynamic imaging. By achieving these aims, we will develop a robust, cost- effective TB PET system with potential to revolutionize both clinical and research applications. The successful implementation of this technology will expand access to dynamic TB PET, enhance diagnostic workflows, and accelerate research in cancer and other diseases.

NIGMS - National Institute of General Medical Sciences

PROJECT SUMMARY In multicellular organisms, development and homeostasis require exquisitely precise, dynamic, and coordinated deployment of complex regulatory programs. As many genes are under the control of vast regulatory regions – with some enhancers located over a million base pairs away from target genes – we and others have explored to what extent the 3D organization of the genome facilitates the establishment of specific regulatory interactions. Additionally, regulatory regions are pervasively transcribed to generate a striking diversity of long noncoding (lnc)RNAs, which are emerging as important chromatin and transcriptional regulators. However, the molecular determinants and regulatory roles of genome organization remain unclear, and only a minute fraction of known lncRNAs have been ascribed any function. My recent work used innovative single-cell live imaging approaches to show that genome organization and cis-regulatory lncRNAs both play a key role in regulating the temporal dynamics of gene expression. My findings also suggest that lncRNAs may exploit – or even regulate – genome organization to exert long-range transcriptional control. The goal of my research is to understand how genome organization and lncRNAs regulate gene expression, and to investigate their mutual interplay. My lab will use our cutting-edge approaches to measure transcriptional dynamics in Drosophila embryos to investigate how long-range interactions are established; how lncRNAs operate in the context of long-range regulation and utilize genome organization; and how in turn lncRNAs can control genome organization. In my prior work, I identified novel “tethering elements” that foster specific long-range interactions to enable fast gene activation during development. In Project I, I will investigate the role of a well-known epigenetic repressor, Polycomb Repressive Complex 1, in facilitating transcriptional activation by mediating long-range interactions between tethering elements. Through a combination of genomics and live imaging, I will identify the molecular mechanisms establishing long-range interactions and determine their impact on gene expression. My recent work also showed that both long-range enhancers and tethering elements are pervasively transcribed genome- wide. In Project II, using methods I developed to visualize the transcription of endogenous lncRNAs in living embryos in combination with complex genetic perturbations, I will begin to determine the regulatory functions of select lncRNAs associated with important developmental genes and dissect their interplay with genome organization. In particular, I will investigate how lncRNAs regulate the recruitment of architectural factors and the establishment of long-range interactions. Finally, in Project III, I will use novel single-cell live imaging approaches that I developed to investigate how lncRNAs dynamically control local regulatory microenvironments to regulate genome organization and gene expression in vivo. Collectively, these three synergistic projects will enable my future research program by identifying guiding principles that will inform our understanding of the dynamics of gene regulation and be examined in future studies in other model systems and cellular and temporal contexts.

NIGMS - National Institute of General Medical Sciences

Project Summary Transcription factors are proteins that control the expression of target genes. Key questions about transcription factor function include: how does their DNA binding activate transcription? How do activation domains interact with specific co-factors? What sequence features are required for activity? As a model system to address these fundamental questions, I will use the transcriptional output of the Notch signaling pathway. The Notch pathway is essential for development of multiple tissues and its aberrant activity is associated with disease including cancer. Upon signal activation, Notch assembles a transcription complex (NTC) on DNA, consisting of the DNA binding protein RBPJ, the Notch intracellular domains (NICD), and a MAML family co-activator. MAML proteins are thought to act as a platform for assembly of co-factors required to activate transcription, but a thorough identification of these factors, how they regulate transcription, and how MAMLs interacts with them are unknown. This study will combine a variety of experimental approaches that allow temporal resolution of transcriptional induction and transcriptional complex assembly in response to signaling activation. This work will identify co- activators that interact with the primary MAML protein in humans, MAML1, using APEX2-based proximity labeling, and will interrogate the dynamics of the transcriptional response using nascent transcriptomics (Aim 1). In the independent phase of this aim, it will determine how these co-activators work with the NTC to induce gene expression. This study will directly visualize MAML1 nuclear dynamics in response to Notch activation, and assess the role of higher order protein assemblies in Notch dependent transcription (Aim 2). It will also identify the sequence features of MAML1 that confer transcriptional activation activity (Aim 3). Successful completion of these aims will both elucidate how Notch signaling activates transcription, and more broadly provide key mechanistic insight into transcriptional activation domain function. This multidisciplinary proposal provides an excellent training opportunity for the PI, enabling her to expand her repertoire of techniques to study transcription factors in their cellular context, and strengthen her expertise in gene regulation. The combined mentorship from Dr. Stephen Blacklow, expert in structural mechanisms of Notch signaling, and Dr. Karen Adelman, leader in mechanisms of transcriptional regulation, will provide an exceptional environment for the PI to complete this work and gain the skills necessary to transition to independence. The extensive training plan will equip the PI to achieve her goal of running an independent laboratory studying mechanisms by which transcription factors activate specific gene expression patterns. Participation in the MOSAIC UE5 programs will expand the PI’s network and provide mentoring and leadership skills to empower the PI to promote diversity in academic science.

NIGMS - National Institute of General Medical Sciences

Project Summary It has been well established that small non-coding RNAs, such as microRNA (miRNA) and small interfering RNA (siRNA), act as potent regulators in numerous biological processes. MiRNA, for instance, modulate gene expression by targeting mRNA based on sequence complementary via the RNA Induced Silencing Complex (RISC). This allows miRNA to regulate key cellular events including cell differentiation, proliferation, and apoptosis. Consequently, when expression levels of miRNAs are dysregulated or alterations to the miRNA sequence occur, individuals can become more susceptible to the development of a variety of disease types, such as cancer, immune-related and neurodegenerative diseases. In response, researchers have been using a combination of techniques to identify the mechanism(s) behind points of dysregulation to guide future RNA- targeted therapeutics. Towards this goal, extensive studies have been carried out to identify and characterize the proteins involved in the miRNA biogenesis pathway, which include the endoribonuclease III protein Dicer. Dicer performs the final cleavage reaction to remove the hairpin loop region of precursor miRNA (pre-miRNA) to produce mature miRNA strands. While in humans, Dicer’s role is centralized around miRNA maturation and regulation, exploration into Dicer proteins from other species has revealed a highly dynamic and multifunctional activity, which includes the cleavage of siRNAs, a key component in antiviral defense. Differences in substrate specify are seemingly dependent on the ATP hydrolysis activity of Dicer’s N-terminal helicase domain. To further investigate this functionality and determine its connection to substrate specificity, structural and biochemical studies have been implemented to uncover the mechanisms behind ATP-independent vs ATP-dependent helicase activity. However, these approaches have been unable to capture the conformational heterogeneity associated with this functionality. Therefore, this proposal puts forth a new approach that combines results from a series of molecular dynamics simulations used to investigate Dicer’s flexibility (Aim 1) with published experimental observations from biochemical, kinetic, and structural studies to create data-informed predictive simulations (Aim 2). These predictive simulations will be used to investigate the central hypothesis of this proposal which is that the overall flexibility of Dicer’s helicase domain is dependent on whether it can hydrolyze ATP, and that in the absence of this activity, the helicase domain is unable to maintain one stable structure and samples a variety of conformational states. Overall, with the extensive resources offered by the University of Utah and expert guidance provided to me by my mentors, I am confident that this proposal will not only generate the first comprehensive integrative dynamic model of Dicer function, but also introduce a novel workflow to explore hypotheses and predict related functional outcomes of other disease-associated RNA interactions.

NEI - National Eye Institute

PROJECT ABSTRACT Cataracts and glaucoma are the two leading causes of blindness worldwide. Crucial ophthalmic procedures to treat cataract, glaucoma, and other vision conditions require precise visualization of anatomy and microsurgical instruments. Visualization in such surgeries has been limited to stereo optical microscopes since the early 20th century. With advancements in optical coherence tomography (OCT), we can now obtain real-time 3D visualization within the eye. Over the past decade, intraoperative OCT (iOCT) systems have become widely researched and integrated into the latest ophthalmic microscopes built by companies such as Zeiss and Leica. These iOCT systems come with the potential to revolutionize ophthalmic surgery, with an unparalleled ability to resolve key anatomic features at micron-level precision. However, there is a crucial challenge that hampers the clinical utility of iOCT. This challenge stems from the fundamental tradeoff between OCT field-of-view and imaging speed. This tradeoff constrains state-of-the-art systems to operate with a relatively small (e.g. 5x5 mm) field of view to achieve the volume update speeds (~10-15 Hz) required for surgical visualization. Consequently, a trained operator on the surgical team must manually reposition the OCT scan throughout the surgery. The current implementation of iOCT results in a “point-and-shoot” approach to imaging, i.e. using OCT as an intermittent snapshot tool, rather than as a continuous surgical visualization technology. With even small movements of the surgical instruments, the OCT image can quickly lose sight of the surgical region of interest (ROI). Manual tracking of iOCT discards a key advantage of OCT, which is real-time 3D data collection. With advances in deep learning methods for image processing and object recognition, there are new opportunities to tackle this problem. The goal of this project is to engineer a novel computational system for automatic, real- time tracking of the surgical ROI in a clinical iOCT system. Our vision is to develop a system that can be readily applied to existing clinical microscopes, and adaptable to future robotic surgical systems. As part of our preliminary work, we have created a lateral tool tracking OCT system using deep learning models applied to the microscope feed. Our current system utilizes a novel synthetic data approach, making use of 3D-rendered models of eyes and tools to accelerate deep learning model development. In the proposed project, we expand on this preliminary work by developing a system for 3D multimodal surgical ROI tracking of iOCT that can be applied to many different types of ophthalmic surgeries. We will then evaluate our platform via ex-vivo porcine and human cadaver eye studies with wet-lab benchmarking and simulated surgeries with our clinical collaborators. Our immediate application is ophthalmic surgery, but the methodology has relevance to a wide range of 3D imaging systems for microsurgical procedures. By developing this system for dynamic OCT surgical tracking, we hope to improve ophthalmic visualization in both training and surgical practice.

NIDDK - National Institute of Diabetes and Digestive and Kidney Diseases

PROJECT SUMMARY / ABSTRACT Type 1 diabetes (T1D) is an autoimmune disease from an immune-mediated attack on the pancreatic beta cells. As ~5% of those developing T1D have a positive family history, there is little awareness of symptoms. T1D is most virulent in children, yet it affects all age and ancestry groups. The beta cell destruction in T1D is identified only through presence of islet autoantibodies to insulin (IAA), glutamic acid decarboxylase (GADA), insulinoma- associated protein 2 (IA-2A), and zinc transporter 8 (ZnT8A), although their prevalence can vary depending on age, sex, and ancestry. Genetic factors account for ~50% of T1D risk, and we (and others) have identified over 100 loci containing disease-associated variants. The vast majority of T1D variants reside in the non-coding genome and map to enhancer regions in immune-relevant cell types (e.g., CD4+ T cells). The mechanisms underlying the transition from an individual’s genetic risk to islet autoimmunity and development of T1D have not been resolved. The proposed research is an ancillary project of The Environmental Determinants of Diabetes in the Young (TEDDY) study. TEDDY is a longitudinal cohort study designed to discover triggers of islet autoimmunity by following newborns at high genetic risk with frequent follow-up and collection of samples for deep phenotyping and biological profiling. This project proposes to use TEDDY data and PBMC samples to examine an under-studied mechanism in T1D, the role of alternative splicing. Alternative splicing of pre-mRNA generates diversity in gene expression (regulation) and protein in a tissue-specific manner. Errors in alternative splicing can result in errors in gene regulation and has been shown to lead to human disease, including autoimmune diseases. Further, genetic variation also impacts proper splicing of mRNA, generating aberrant variants. We have shown that alternative splicing is associated with T1D in known T1D loci using short-read RNA sequencing. In addition, RNA-binding proteins (RBPs) with roles in alternative splicing can generate different mRNA and protein isoforms with change or loss of protein function. We have identified 12 genes in known T1D loci that encode RBPs of relevance to gene expression and T1D susceptibility. To gain a comprehensive understanding of the role of these RBP-regulated alternative splicing events on initiation and progression of islet autoimmunity leading to T1D, we propose to focus on a relevant cell type (CD4+ T cells) obtained from TEDDY participants at multiple time points during the transition periods of islet autoimmunity. We will obtain long-read RNA sequencing (for full isoform detection) and short-read RNA sequencing (for isoform abundance) to define differential alternative splicing events, construct RBP networks, and utilize deep learning time series models to map T1D risk over time. We will experimentally validate alternatively spliced genes, their RBPs, and biological mechanisms that lead to islet autoimmunity and T1D. Together, the outcome of the proposed research will enable better prediction of islet autoimmunity and T1D risk trajectory, the timing for monitoring, and novel therapeutic interventions in T1D.

NIGMS - National Institute of General Medical Sciences

SUMMARY This research broadly seeks to reveal molecular principles that enable biological systems to sense and adapt to changing environments, and to understand how to use these principles to engineer synthetic biological systems that benefit humankind. A focal point of this work is RNA – a fundamental component of all living systems that enacts genetic, regulatory and catalytic functions by folding into intricate shapes within cells. As RNA folding can occur immediately during transcription, this raises a fundamental question as to how nascent RNA structures can influence many aspects of gene expression including transcription, translation, splicing, and polyadenylation. The overall vision for this proposed research program is to address aspects of this question through detailed structure-function studies of riboswitches and model eukaryotic systems, and development of technologies that can measure and model nascent RNA folding in broad RNA systems. Riboswitches are broadly distributed non- coding regulatory RNAs that bind to specific ligands and in response control gene expression. A critical feature of many riboswitches is that regulation occurs during transcription, making them ideal model systems to study the impacts of nascent RNA structure on gene expression. Principles of nascent RNA folding and function learned from riboswitches is beginning to be shown to hold true in other areas of biology including non-coding RNA biogenesis and eukaryotic RNA Pol III transcription termination. Our goal is to develop a molecular understanding of how cotranscriptional RNA folding regulates and coordinates cellular gene expression. Towards this goal, over the next five years we propose two research themes. The first uses diverse riboswitches, and eukaryotic RNA Pol III transcription termination, as model systems, to uncover general, quantitative relationships between RNA sequence, nascent folding, and transcription termination and translation initiation. We will combine high throughput cellular and in vitro functional characterization approaches to rapidly characterize model regulatory RNA sequence variants, with a hybrid experimental-computational approach called Reconstructing RNA Dynamics from Data (R2D2) to measure and model cotranscriptional RNA folding. Biophysical and data-driven modeling will be used to uncover quantitative relationships to address fundamental questions about how RNA folding kinetics and nascent RNA-RNA polymerase interactions govern transcription and translation regulation. Theme two will incorporate RNA folding energetics extracted from RNA structure chemical probing to improve R2D2’s accuracy and integrate new computational RNA folding algorithm developments to allow R2D2 to reconstruct RNA structure sub-populations of longer RNA systems. Detailed knowledge of how nascent RNA folding links to RNA regulatory function will contribute to a deeper understanding of gene expression processes, as well as numerous RNA biotechnologies such as diagnostics, RNA-targeting antibiotics and drugs, and nucleic acid therapeutics.

Economic Development Initiatives 16-17

Dynamic Systems Working Capital

NSF

Dynamical systems are ubiquitous: they govern the motion of the planets, the weather, the stock market, and the ecosystems. These systems depend on different parameters, and as these parameters change, the corresponding system changes. Sometimes there are special values of the parameters for which the corresponding dynamical system is relatively simple. In complex dynamics, these are known as postcritically finite parameters. The postcritically finite parameters form a thin but sprawling collection that helps the understanding of the global structure of the parameter space. This project aims to extensively study the postcritically finite parameters and record several essential data that uniquely encode them. Broader impacts of the project are through mentoring at all levels, including a Math Corps summer camp for middle school campers and high school mentors from Ypsilanti, Michigan. In complex dynamics, one typically studies rational maps on the Riemann sphere from the point of view of iteration. A main principle in the subject asserts that in order to understand the dynamical behavior of a rational map, it is necessary to study the orbits of the critical points of the map. Those rational maps for which all critical points have finite forward orbits are quite special; they are known as postcritically finite rational maps. These maps possess only repelling and superattracting cycles, and their Julia sets are locally connected. Furthermore, (excluding well-understood exceptional cases), postcritically finite maps are inherently algebraic: every map can be conjugated by an automorphism of the Riemann sphere so that the resulting map has algebraic coefficients. In the moduli space of rational maps of a given degree, the postcritically finite locus can be used to study the geometry of this space. This project aims to investigate and explore dynamical data associated to postcritically finite maps. The projects in the proposal incorporate complex analysis, Teichmueller theory, topology, and geometric group theory to better understand these data. 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

This project will develop analytical methods to approximate the state of certain dynamical systems to within manageable errors, with an eye towards computational feasibility. Dynamical systems provide mathematical models for the long-term trajectories of objects moving according to physical principles. The subject has its foundations in Newtonian mechanics, and features widely in both pure and applied mathematics (e.g., fluid dynamics, airflow dynamics, Hamiltonian mechanics). Hamiltonian mechanics, which provides an alternative formulation to Newtonian mechanics and is particularly useful in classical and quantum mechanics, expresses the time evolution of a system in terms of partial derivatives of a certain energy. The resulting equations, called Hamilton’s equations, describe how the coordinates and momenta of a system evolve over time. The project will seek to further the understanding of quantitative aspects of the analysis of various dynamical systems, under the mathematical rubric of rigidity. The project also provides opportunities for the training and mentoring of early career researchers, especially graduate students. The PI will contribute to the dissemination of mathematical knowledge through the organization of various conferences, workshops, and long research programs. The project resides at the intersection of dynamical systems, ergodic theory, number theory, and geometry. It seeks both to establish new rigidity results and to advance and refine existing results, in the setting of the dynamics of group actions on structured spaces. A major focus is on an enhanced understanding of finitary analysis and effective conclusions. Rigidity phenomena for the dynamics of group actions on homogeneous spaces and moduli spaces have been studied extensively. However, a quantitative understanding of the behavior of orbits has proven to be challenging. This project seeks results in this direction, with an emphasis on systems with polynomial rates, and will also investigate implications of these findings within the domains of number theory and geometry. In addition, recent results of the PI and collaborators regarding finitary analysis on homogeneous spaces will be studied with an eye towards extensions to other settings, including dynamics on the moduli spaces of Riemann surfaces. 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

This research is focused on understanding the strong-field regime of Einstein's theory of general relativity. This encompasses both observational and theoretical aspects of general relativity. On the observational side, the main effort is numerical simulations of black hole collisions. This is important to support the nascent field of gravitational wave astronomy that began in 2015 with LIGO's detection of the collision of two black holes. This has given us the first direct observational window into the strong-field regime of general relativity, showing tentative scientific evidence that space and time do behave as predicted in these extreme environments. One avenue of work supported by this award will be to investigate hypothetical alternatives to black hole mergers as the source of LIGO's observations, to either rule out the alternatives and improve our confidence in general relativity or to discover novel physics. On the theoretical side, there are many outstanding questions about the nature of spacetime in extreme situations. Two such questions that will be addressed through this award are what happens to a black hole that is spun up to the maximum rotation rate allowed by Einstein's theory, and what happens when two black holes traveling at close to the speed of light collide. The pursuit of these projects will be carried out by graduate students as part of their thesis work. They will be trained to do leading scientific research, become knowledgeable in corresponding areas of physics, and be adept in high-performance computing and numerical methods. These skills are invaluable to many professions and would thus also benefit and further the development of those students who subsequently wish to pursue careers outside academia. A specific list of projects that will be pursued are (1) develop analytical and numerical methods to model so-called shell-like black hole mimickers, focusing on AdS (Anti de-Sitter) black shells as a concrete example, (2) numerically study the ultrarelativistic collision problem using both black holes and photon packets as the objects being collided, (3) numerically study the non-linear dynamics of perturbed near extremal black holes, beginning with the simpler case of charged scalar field perturbations of Reissner-Nordstrom black holes, before moving onto the more relevant gravitational wave perturbations of Kerr black holes, and (4) work on the following set of miscellaneous projects: the nonlinear dynamics of 5-dimensional black strings, the foundations of relativistic dissipative hydrodynamics, the interior structure of black holes, non-singular bouncing cosmologies, and gravitational collapse at the threshold of black hole formation. 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.

NCCIH - National Center for Complementary and Integrative Health

SUMMARY The rapid detection of mechanical stress - and adaptation to it - is essential to all organisms. In vertebrates, this task is mainly achieved by two homotrimeric ion channels called PIEZO1 and PIEZO2. Together, these mechanosensitive channels transduce a rich diversity of mechanical forces, such as compression, vibration, stretch, torque, and shear stress, into cellular signals that play essential roles across all physiological systems. To date, it remains unclear how such a complex landscape of mechanical stimuli can be effectively transduced by the two PIEZO mechanotransducers. In Aim1 of this exploratory proposal, we address this question by testing the hypothesis that PIEZO1 and PIEZO2 subunits interact to form heterotrimeric channels, potentially expanding the functional properties of PIEZO channels. To fulfill this aim, we will use bimolecular fluorescence complementation (BFC), co-immunoprecipitation and electrophysiology. Our preliminary data reveals that, when co-expressed in the same cells, the PIEZO1 and PIEZO2 subunits position their C-termini within nanometric proximity, consistent with both subunits co-existing within the same channel. Co- immunoprecipitation with validated antibodies will allow us to test whether wild-type PIEZO1/2 subunits also interact. To test whether these heteromers consist of functional channels, we will use a novel functional BFC approach (based on a split fluorescent calcium indicator) that we have created and validated. In Aim2, we will test the hypothesis that different mechanical stimuli (including indentations, fluid shear stress, and osmotic shocks) activate PIEZO channels through distinct conformational rearrangements of mechanosensory blade- like domains. To this aim, we will measure intramolecular fluorescence resonance energy transfer (FRET) from donor/acceptor probes genetically-inserted at strategic positions of adjacent PIEZO1 blades. Our preliminary data shows that FRET efficiency decreases as a response to osmotic shocks. FRET will be measured using epifluorescence, total internal reflection fluorescence and confocal imaging. We will determine if a correlation exists between changes in FRET efficiency and the nature of the mechanical stimulus. If successful, this exploratory R21 proposal will advance our fundamental understanding of mechanotransduction by mammalian PIEZO channels, provide innovative research tools, and contribute to elucidating the molecular bases of force- based therapeutic interventions.

NHLBI - National Heart Lung and Blood Institute

Project summary/Abstract Hematopoiesis is a highly regulated process fueled by hematopoietic stem cells (HSCs) and progenitors in response to physiological and pathological changes throughout life. During development, the system quickly expands to provide increasing numbers of blood cells for the growing tissues and organs. In regeneration, HSCs re-establish the hematopoietic hierarchy and supply lost blood cells to restore tissue function. In pathological conditions, dysregulated hematopoiesis drives disease progression. A detailed cellular and molecular understanding of the mechanisms of dynamic hematopoiesis is key to intervening in these processes for therapeutic benefits. Although the niche critically regulates HSCs and hematopoiesis, how the niche is dynamically regulated to adapt to the distinct demands in the ever-changing conditions is not clear. Our previous work has identified key cellular components of the niche in the bone marrow and developing liver, allowing precise studies of niche dynamics in these organs. Our recent work has also revealed surprising cell fate plasticity in the bone marrow niche. The proposed work in this application builds on these findings to 1) define niche dynamics and plasticity in development, regeneration, and hematological disease, 2) uncover the mechanisms that regulate these processes, and 3) harness the mechanisms to enhance niche function and boost blood cell production. We will use several novel mouse models generated in the lab to study the function of key pathways in regulating niche dynamics and cell fate plasticity. We will employ single-cell transcriptomics, imaging, metabolic analysis, functional studies, and other cutting-edge approaches to understand how these key pathways regulate niche dynamics and plasticity. Collectively, these experiments will uncover novel mechanisms that regulate niche cell dynamics and plasticity with broad implications for better treatment of blood diseases. They may lead to transformative strategies for boosting blood cell production by enhancing niche function.

NSF

Mathematical systems underlie today’s data encryption, navigation, and imaging technologies. Yet many of their most important behaviors occur in “infinite‐volume” settings that current theory cannot explain. This project develops new mathematical tools to understand the long-term dynamics and inherent rigidity of such systems, with an emphasis on groups that model negatively curved-space symmetries. By advancing the frontier of pure mathematics, the work directly fulfills the National Science Foundation’s mission “to promote the progress of science.” The results will be presented widely, including in a plenary lecture at the International Congress of Mathematicians (ICM 2026)—the world’s largest mathematics meeting—taking place July 23–30 2026 in Philadelphia, Pennsylvania, USA (https://www.mathunion.org/icm/icm-2026.) Sharing these results on a global stage accelerates discovery in the mathematical sciences and inspires the next generation of STEM talent. The project also incorporates research opportunities for graduate students and postdoctoral scholars. The project investigates dynamics on infinite-volume homogeneous spaces which are quotients of semisimple Lie groups by their discrete subgroups, with a focus on Kleinian groups and higher-rank Anosov subgroups.Goals are to (1) establish ergodicity, quantitative mixing, and orbit-closure criteria for diagonal and unipotent flows, (2) classify invariant measures in settings where finite-volume methods fail, and (3) derive sharp orbit-counting and equidistribution theorems via thermodynamic formalism. Methods blend homogeneous dynamics, Riemannian geometry, geometric group theory, Lie-theoretic representation theory, and spectral/transfer-operator techniques. Expected outcomes include new measure-rigidity theorems, effective counting asymptotics, and a unified framework connecting Kleinian, Anosov, and arithmetic lattice dynamics, laying groundwork for applications in geometry and number theory. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.